# document

id: ce0ab875411056dac397215387ee83b9
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 33578
content:
"[...] impacts and their interactions with other anthropogenic stressors calls \r for integrated approaches that identify trade-offs and synergies across \r sectors and scales in space and time to build resilience of ocean and \r coastal ecosystems and the services they deliver (high confidence). \r {3.4.2, 3.5.2, 3.5.3, 3.5.5.3, 3.5.5.4, 3.5.5.5, 3.6.2.2, 3.6.3.2, 3.6.5, \r Figure 3.25, Table 3.SM.6}"


id: 77f8a72a2d4fd6a08ca43a2bc5419647
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 18312
content:
"Humans are already adapting to climate-driven changes in \r marine systems, and while further adaptations are required even \r under low-emission scenarios (high confidence), transformative \r adaptation will be essential under high-emission scenarios \r (high confidence).  Low-emission scenarios permit a wider array \r of feasible, effective and low-risk nature-based adaptation options \r (e.g., restoration, revegetation, conservation, early-warning systems \r for extreme events and public education) (high confidence). Under \r high-emission scenarios, adaptation options (e.g., hard infrastructure \r for coastal protection, assisted migration or evolution, livelihood \r diversification, migration and relocation of people) are more uncertain \r and require transformative governance changes  (high confidence). \r Transformative climate adaptation will reinvent institutions to \r overcome obstacles arising from historical precedents, reducing current \r [...]"


id: a4bfced46eece7aa22f609d2fe159e0d
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 26209
content:
"[...] barriers to climate adaptation in cultural, financial and governance \r sectors (high confidence). Without transformation, global inequities will \r likely increase between regions (high confidence) and conflicts between \r jurisdictions may emerge and escalate. {3.5, 3.5.2, 3.5.5.3, 3.6, 3.6.2.1, \r 3.6.3.1, 3.6.3.2, 3.6.3.3, 3.6.4.1, 3.6.4.2, 3.6.5, Cross-Chapter Box SLR \r in Chapter 3, Cross-Chapter Box ILLNESS in Chapter 2}"


id: da366cc0358a49160f29533ecc542742
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 35687
content:
"by redistributing heat and water (WGI AR6 Chapter  9; Fox-Kemper \r et al., 2021). The ocean also provides a wealth of aesthetic and cultural \r resources (Barbier et al., 2011), contains vast biodiversity (Appeltans \r et al., 2012), supports more animal biomass than on land (Bar-On et al., \r 2018) and produces at least half the world's photosynthetic oxygen \r (Field et al., 1998). Ecosystem services (Annex II: Glossary) delivered \r by ocean and coastal ecosystems support humanity by protecting \r coastlines, providing nutrition and economic opportunities (Figure 3.1; \r Selig et al., 2019) and providing many intangible benefits. Even though \r ecosystem services and biodiversity underpin human well-being and \r support climate mitigation and adaptation (Portner et al., 2021b), there \r are also ethical arguments for preserving biodiversity and ecosystem \r functions regardless of the beneficiary (e.g., Taylor et al., 2020). This \r [...]"


id: b97205355d5304c11181c287d7c0d004
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 29840
content:
"[...] chapter assesses the impact of climate change on the full spectrum of \r ocean and coastal ecosystems, on their services and on related human \r activities, and it assesses marine-related opportunities within both \r ecological and social systems to adapt to climate change."


id: 8db850b5af6f257d522f3697ddc9651f
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 22123
content:
"The ocean contains approximately 97% of Earth's water within a \r system of interconnected basins that cover 71% of its surface. Coastal \r systems mostly extend seaward from the high-water mark, or just \r beyond, to the edge of the continental shelf and include shores of soft \r sediments, rocky shores and reefs, embayments, estuaries, deltas and \r shelf systems. Oceanic systems comprise waters beyond the shelf edge, \r from ~200 m to nearly 11,000 m deep (Stewart and Jamieson, 2019), \r with an average depth of approximately 3700 m. The epipelagic zone, \r or upper 200 m of the ocean, is illuminated by sufficient sunlight to \r sustain photosynthesis that supports the rich marine food web. Below \r the epipelagic zone lies the barely lit mesopelagic zone (200-1000 m), \r the perpetually dark bathypelagic zone (depth >1000 m) and the \r deep seafloor (benthic ecosystems at depths >200 m), which spans \r rocky and sedimentary habitats on seamounts, mid-ocean ridges and \r [...]"


id: b4aabdf74acb88e52949a9159e40f43e
created_at: 2023-04-19 13:22:52
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content_type: text
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vector_id: 29037
content:
"[...] canyons, abyssal plains and sedimented margins. Semi-enclosed seas \r (SES) include both coastal and oceanic systems."


id: 72e72ade545a97bc417cd6a50cfc654e
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 17463
content:
"Figure 3.1 |  Estimated relative human dependence on marine ecosystems for coastal protection, nutrition, fisheries economic benefits and overall. Each \r bar represents an index value that semi-quantitatively integrates the magnitude, vulnerability to loss and substitutability of the benefit. Indices synthesize information on people's \r consumption of marine protein and nutritional status, gross domestic product, fishing revenues, unemployment, education, governance and coastal characteristics. Overall \r dependence is the mean of the three index values after standardisation from 0-1. (Details regarding component indices are found in Table 1 and Supplementary Material of Selig \r et al., 2019.) The overall index does not include the economic benefits from tourism or other ocean industries, and data limitations prevented including artisanal or recreational \r [...]"


id: 81403480f1fa918aac62b22f558d62c1
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
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"[...] fisheries or the protective impact of salt marshes (Selig et al., 2019). Values for reference regions established in the WGI AR6 Atlas (Gutierrez et al., 2021) were computed as \r area-weighted means from original country-level data (Table S6 in Selig et al., 2019)."


id: 64d92891ab818f2360b8e55cb3a7be8b
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
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content:
"also influence ocean and coastal systems (Section 3.2; Cross-Chapter \r Box  SLR in Chapter  3; Cross-Chapter Box  EXTREMES in Chapter  2; \r Figure  3.SM.1), from individual biophysical processes to dependent \r human activities. Several marine outcomes of CIDs are themselves \r drivers of ecological change (e.g., climate velocities, stratification, \r sea ice changes). This chapter updates and extends the assessment \r of SROCC (IPCC, 2019b) and WGI AR6 by assessing the ecosystem \r effects of the CIDs in WGI AR6 Figure SPM.9 (IPCC, 2021b) and their \r biologically relevant marine outcomes (detailed in Section 3.2), which \r are referred to collectively hereafter as 'climate-induced drivers'4\r .\r Detrimental human impacts on ocean and coastal ecosystems are not \r only caused by climate. Other anthropogenic activities are increasingly \r affecting the physical, chemical and biological conditions of the ocean \r (Doney, 2010; Halpern et al., 2019), and these 'non-climate drivers5\r ' also \r [...]"


id: a91370b64499576bad5c21024f22ba73
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
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vector_id: 26958
content:
"[...] alter marine ecosystems and their services. Fishing and other extractive \r activities are major non-climate drivers in many ocean and coastal systems \r (Steneck and Pauly, 2019). Many activities, such as coastal development, \r shoreline hardening and habitat destruction, physically alter marine spaces \r (Suchley and Alvarez-Filip, 2018; Ducrotoy et al., 2019; Leo et al., 2019; \r Newton et al., 2020; Raw et al., 2020). Other human activities decrease \r water quality by overloading coastal water with terrestrial nutrients \r (eutrophication) and by releasing runoff containing chemical, biological \r and physical pollutants, toxins, and pathogens (Jambeck et  al., 2015; \r Luek et al., 2017; Breitburg et al., 2018; Froelich and Daines, 2020). Some \r human activities disturb marine organisms by generating excess noise \r and light (Davies et al., 2014; Duarte et al., 2021), while others decrease \r natural light penetration into the ocean (Wollschlager et  al., 2021). \r [...]"


id: 820df3db033a0c384fae662b83ecdae
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 20002
content:
"[...] Several anthropogenic activities alter processes that span the land-sea \r interface by changing coastal hydrology or causing coastal subsidence \r (Michael et al., 2017; Phlips et al., 2020; Bagheri-Gavkosh et al., 2021). \r Atmospheric pollutants can harm marine systems or unbalance natural \r marine processes (Doney et al., 2007; Hagens et al., 2014; Lamborg et al., \r 2014; Ito et  al., 2016). Organisms frequently experience non-climate \r drivers simultaneously with climate-induced drivers (Section  3.4), and \r feedbacks may exist between climate-induced drivers and non-climate \r drivers that enhance the effects of climate change (Rocha et al., 2015; \r Ortiz et al., 2018; Wolff et al., 2018; Cabral et al., 2019; Bowler et al., 2020; \r Gissi et al., 2021). SROCC assessed with high confidence that reduction \r of pollution and other stressors, along with protection, restoration and \r precautionary management, supports ocean and coastal ecosystems \r [...]"


id: 29325a6f75aec765cac295d4ac3ce588
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 4460
content:
"[...] and their services (IPCC, 2019b). This chapter examines the combined \r influence of climate-induced drivers and primary non-climate drivers on \r many ecosystems assessed."


id: 7c3768211809c30d938341d3ce557e02
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 19066
content:
"and attribute climate impacts on marine-dependent human systems, \r where culture, governance and society also strongly influence observed \r outcomes. To assess climate-driven change in natural and social systems \r robustly, IPCC reports rely on multiple lines of evidence, and the \r available types of evidence differ depending on the system under study \r (Section  1.3.2.1, Cross-Working Group Box ATTRIB). Lines of evidence \r used for ocean and coastal ecosystems for this and previous assessments \r include observed phenomena, laboratory and field experiments, long\u0002term monitoring, empirical and dynamical model analyses, Indigenous \r knowledge (IK) and local knowledge (LK), and paleorecords (IPCC, 2014b; \r IPCC, 2014c; IPCC, 2019b). The growing body of climate research for ocean \r and coastal ecosystems and their services increasingly provides multiple \r independent lines of evidence whose conclusions support each other, \r [...]"


id: 4d992d9a0f5beeefe476e12f7d3037
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 10927
content:
"[...] raising the overall confidence in detection and attribution of impacts over \r time (Section 1.3.2.1, Cross-Working Group Box ATTRIB in Chapter 3)."


id: 946c3970ad1910cdc575948fe0acc18d
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 23321
content:
"Natural adaptation to climate change in ocean and coastal systems \r includes an array of responses taking place at scales from cells to \r ecosystems. Previous IPCC assessments have established that many \r marine species 'have shifted their geographic ranges, seasonal \r activities, migration patterns, abundances and species interactions \r in response to climate change' (high confidence) (IPCC, 2014b; \r IPCC, 2014c), which has had global impacts on species composition, \r abundance and biomass, and on ecosystem structure and function \r (medium confidence) (IPCC, 2019b). Warming and acidification have \r affected coastal ecosystems in concert with non-climate drivers (high \r confidence), which have affected habitat area, biodiversity, ecosystem \r function and services (high confidence) (IPCC, 2019b). Confidence \r has grown in these assessments over time as observational datasets \r have lengthened and other lines of evidence have corroborated \r [...]"


id: 4eb252dec51944098977796a7ce8a918
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 11117
content:
"[...] observations. AR5 and SROCC assessed how physiological sensitivity \r to climate-induced drivers is the underlying cause of most marine \r organisms' vulnerability to climate (high confidence) (Portner et  al., \r 2014; Bindoff et al., 2019a). Since those assessments, more evidence \r supports the empirical physiological models of tolerance and plasticity \r (Sections 3.3.2, 3.3.4) and of interactions among multiple (climate and \r non-climate) drivers at individual to ecosystem scales (Sections 3.3.3, \r 3.4.5). New experimental evidence about evolutionary adaptation \r (Section 3.3.4) bolsters previous assessments that adaptation options \r to climate change are limited for eukaryotic organisms. Tools such \r as ecosystem models can now constrain probable ecosystem states \r (Sections 3.3.4, 3.3.5, 3.4). Observations have increased understanding \r of how extreme events affect individuals, populations and ecosystems, \r helping refine understanding of both ecological tolerance to climate \r [...]"


id: bd5a192c67e505539574a8f1f1debf4a
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 30560
content:
"Paleorecords can be used to trace the correlation between past changes in climate and marine life. Paleoclimate is \r reconstructed from the chemical composition of shells and teeth or from sediments and ice cores. Changes to sea \r life signalled by changing biodiversity, extinction or distributional shifts are reconstructed from fossils. Using large \r datasets, we can infer the effects of climate change on sea life over relatively long time scalesusually hundreds to \r millions of years. The advantage of paleorecords is that they provide insights into how climate change affects life \r from organisms to ecosystems, without the complicating influence of direct human impacts. A key drawback is that \r the paleo and modern worlds do not have fully comparable paleoclimate regimes, dominant marine species and \r rates of climate change. Nevertheless, the paleorecord can be used to derive fundamental rules by which organisms, \r [...]"


id: e351ef900910a3b10f75f42fbef9953a
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 37292
content:
"[...] ecosystems, environments and regions are typically most affected by climate change. For example, the paleorecord \r shows that coral reefs repeatedly underwent declines during past warming events, supporting the inference that \r corals may not be able to adapt to current climate warming."


id: 25f623fb4ed904bbf87d0bc7053964cf
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 3856
content:
"This chapter assesses the current understanding of climate-induced \r drivers, ecological vulnerability and adaptability, risks to coastal \r and ocean ecosystems, and human vulnerability and adaptation \r to resulting changes in ocean benefits, now and in the future \r (Figure 3.2). It starts by assessing the biologically relevant outcomes \r of anthropogenic climate-induced drivers (Section  3.2). Next, it \r sets out the mechanisms that determine the responses of ocean \r and coastal organisms to individual and combined drivers from the \r genetic to the ecosystem level (Section 3.3). This supports a detailed \r assessment of the observed and projected responses of coastal and \r ocean ecosystems to these hazards, placing them in context using the \r paleorecord (Section 3.4). These observed and projected impacts are \r used to quantify consequent risks to delivery of ecosystem services \r and the socioeconomic sectors that depend on them, with attention \r [...]"


id: cb4a67867c8b937a9b90652bdd3a5b62
created_at: 2023-04-19 13:22:52
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content:
"[...] to the vulnerability, resilience and adaptive capacity of social-\r ecological systems (Section 3.5). The chapter concludes by assessing \r the state of adaptation and governance actions available to address \r these emerging threats while also advancing human development \r (Section  3.6). Abbreviations used repeatedly in the chapter are \r defined in Table 3.1."


id: 596dc3244ea7c30e6fa23c31b4250b49
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 12970
content:
"overlapping climate-induced drivers and non-climate drivers confound \r implementation and assessment of the success of marine adaptation, \r revealing the complexity of attempting to maintain marine ecosystems \r and services through adaptation. SROCC assessed with high confidence\r that while the benefits of many locally implemented adaptations exceed \r their disadvantages, others are marginally effective and have large \r disadvantages, and overall, adaptation has a limited ability to reduce the \r probable risks from climate change, being at best a temporary solution \r (Bindoff et al., 2019a). SROCC also concluded that a portfolio of many \r different types of adaptation actions, effective and inclusive governance, \r and mitigation must be combined for successful adaptation (Bindoff \r et al., 2019a). The portfolio of adaptation measures has now been defined \r (Section 3.6.2), and individual and combined adaptation solutions have \r [...]"


id: c165b7d4ca7deb50010475730c10498b
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 31329
content:
"[...] been implemented in several marine sectors (Section 3.6.3). Delays in \r marine adaptation have been partly attributed to the complexity of \r ocean governance (Section 3.6.4; Cross-Chapter Box 3 and Figure CB3.1 \r in Abram et  al., 2019) and to the low priority accorded the ocean in \r international development goals (Nash et al., 2020), but in recent years \r the ocean is being increasingly incorporated in international climate \r policy and multilateral environmental agreements (Section 3.6.4)."


id: 4bb2116d43de7829eaa8f24b4881c504
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 10575
content:
"Global mean SST has increased since the beginning of the 20th century \r by 0.88degC (very likely range: 0.68-1.01degC), and it is virtually certain\r that the global ocean has warmed since at least 1971 (WGI AR6 \r Section  9.2; Fox-Kemper et  al., 2021). A key characteristic of ocean \r temperature change relevant for ecosystems is climate velocity, a \r measure of the speed and direction at which isotherms move under \r climate change (Burrows et al., 2011), which gives the rate at which \r species must migrate to maintain constant climate conditions. It has \r been shown to be a useful and simple predictor of species distribution \r shifts in marine ecosystems (Chen et al., 2011; Pinsky et al., 2013; Lenoir \r et al., 2020). Median climate velocity in the surface ocean has been \r 21.7 km per decade since 1960, with higher values in the Arctic/sub\u0002Arctic and within 15deg of the Equator (Figure 3.3; Burrows et al., 2011). \r While climate velocity has been slower in the mesopelagic layer (200-\r [...]"


id: 8f4378507cd5e9b50be7882303526574
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 22412
content:
"[...] 1000 m) than in the epipelagic layer (0-200 m) over the past 50 years, \r it has been shown to be faster in the bathypelagic (1000-4000 m) and \r abyssopelagic (>4000 m) layers (Figure 3.4; Brito-Morales et al., 2020), \r suggesting that deep-ocean species could be as exposed to effects of \r warming as species in the surface ocean (Brito-Morales et al., 2020)."


id: a0361ba79d217018c10fba72abe137ed
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 25401
content:
"Marine heatwaves (MHWs) are periods of extreme seawater temperature \r relative to the long-term mean seasonal cycle, that persist for days to \r months, and that may carry severe consequences for marine ecosystems \r and their services (WGI AR6 Box  9.2; Hobday et  al., 2016a; Smale \r et  al., 2019; Fox-Kemper et  al., 2021). MHWs became more frequent \r over the 20th century (high confidence) and into the beginning of the \r 21st century, approximately doubling in frequency (high confidence) \r and becoming more intense and longer since the 1980s (medium \r confidence) (WGI AR6 Box 9.2; Fox-Kemper et al., 2021). These trends in \r MHWs are explained by an increase in ocean mean temperatures (Oliver \r et al., 2018), and human influence has very likely contributed to 84-\r 90% of them since at least 2006 (WGI AR6 Box 9.2; Fox-Kemper et al., \r 2021). The probability of occurrence (as well as duration and intensity) \r of the largest and most impactful MHWs that have occurred in the past \r [...]"


id: ff460284ee07036cca382bfd9f20488f
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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vector_id: 42314
content:
"[...] 30 years has increased more than 20-fold due to anthropogenic climate \r change (Laufkotter et al., 2020)."


id: 8054c39de4638ad193cafebecde9c5fc
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 19710
content:
"Ocean warming will continue over the 21st century (virtually certain), \r with the rate of global ocean warming starting to be scenario\u0002dependent from about the mid-21st  century (medium confidence). \r At the ocean surface, it is virtually certain that SST will continue to \r increase throughout the 21st century, with increasing hazards to many \r marine ecosystems (WGI AR6 Box 9.2; Fox-Kemper et al., 2021). The \r future global mean SST increase projected by CMIP6 models for the \r period 1995-2014 to 2081-2100 is 0.86degC (very likely range: 0.43-\r 1.47degC) under SSP1-2.6, 1.51degC (1.02-2.19degC) under SSP2-4.5, 2.19degC \r (1.56-3.30degC) under SSP3-7.0 and 2.89degC (2.01-4.07degC) under SSP5-\r 8.5 (WGI AR6 Section 9.2.1; Fox-Kemper et al., 2021). Stronger surface \r warming occurs in parts of the tropics, in the North Pacific, and in the \r Arctic Ocean, where SST increases by >4degC in 2080-2099 under SSP5-\r 8.5 (Kwiatkowski et al., 2020). The CMIP6 climate models also project \r [...]"


id: c935ef418db2e982eb6f98a4e9199be
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 32726
content:
"[...] ocean warming at the seafloor, with the magnitude of projected changes \r being less than that of surface waters but having larger uncertainties \r (Kwiatkowski et al., 2020). The projected end-of-the-century warming \r in CMIP6 as reported here is greater than assessed with Coupled Model \r Intercomparison Project  5 (CMIP5) models in AR5 and in SROCC for \r similar radiative forcing scenarios (Figure 3.5; Kwiatkowski et al., 2020), \r because of greater climate sensitivity in the CMIP6 model ensemble \r than in CMIP5 (WGI AR6 Chapter 4; Forster et al., 2020; Lee et al., 2021)."


id: b439c7a6042eb9a87c910f101423056f
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 28941
content:
"Ocean stratification is an important factor controlling biogeochemical \r cycles and affecting marine ecosystems. WGI AR6 Section  9.2.1.3 \r (Fox-Kemper et  al., 2021) assessed that it is virtually certain that \r stratification in the upper 200 m of the ocean has been increasing \r since 1970. Recent evidence has strengthened estimates of the rate \r of change (Yamaguchi and Suga, 2019; Li et al., 2020a; Sallee et al., \r 2021), with an estimated increase of 1.0 +- 0.3% (very likely range) \r per decade over the period 1970-2018 (high confidence) (WGI AR6 \r Section  9.2.1.3; Fox-Kemper et  al., 2021), higher than assessed in \r SROCC. It is very likely that stratification in the upper few hundred \r metres of the ocean will increase substantially in the 21st century in all \r ocean basins, driven by intensified surface warming and near-surface \r freshening at high latitudes (WGI AR6 Section 9.2.1.3; Capotondi et al., \r 2012; Fu et al., 2016; Bindoff et al., 2019a; Kwiatkowski et al., 2020; \r [...]"


id: 8dd4b73cfdddca71feaab131b5a99bcf
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 22143
content:
"units in 2081-2100 relative to 1995-2014, for SSP1-2.6, SSP2-4.5, \r SSP3-7.0 and SSP5-8.5, respectively (Figure 3.5; WGI AR6 Section 4.3.2; \r Kwiatkowski et al., 2020; Lee et al., 2021). Projected changes in surface \r pH are relatively uniform in contrast with those of other surface\u0002ocean variables, but they are largest in the Arctic Ocean (Figure 3.6; \r WGI AR6 Section  5.3.4.1; Canadell et  al., 2021). Similar declines in \r the concentration of carbonate ions are projected by Earth system \r models (ESMs; Bopp et al., 2013; Gattuso et al., 2015; Kwiatkowski \r et al., 2020). The North Pacific, the Southern Ocean and Arctic Ocean \r regions will become undersaturated for calcium carbonate minerals \r first (Orr et al., 2005; Portner et al., 2014). Concurrent impacts on the \r seasonal amplitude of carbonate chemistry variables are anticipated \r (i.e., increased amplitude for pCO2 and hydrogen ions, decreased \r amplitude for carbonate ions; McNeil and Sasse, 2016; Kwiatkowski \r [...]"


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vector_id: 21568
content:
"Ocean acidification is also developing in the ocean interior (very high \r confidence) due to the transport of anthropogenic CO2 to depth by \r ocean currents and mixing (WGI AR6 Section 5.3.3.1; Canadell et al., \r 2021). There, it leads to the shoaling of saturation horizons of aragonite \r and calcite (high confidence) (WGI AR6 Section 5.3.3.1; Canadell et al., \r 2021), below which dissolution of these calcium carbonate minerals \r is thermodynamically favoured. The calcite or aragonite saturation \r horizons have migrated upwards in the North Pacific (1-2 m yr-1 over \r 1991-2006) (Feely et al., 2012) and in the Irminger Sea (10-15 m yr-1\r for the aragonite saturation horizon over 1991-2016) (Perez et  al., \r 2018). In some locations of the western Atlantic Ocean, calcite \r saturation depth has risen by ~300 m since the pre-industrial era \r due to increasing concentrations of deep-ocean dissolved inorganic \r carbon (Sulpis et al., 2018). In the Arctic, where some coastal surface \r [...]"


id: d4a3b8868616a6c1b6c1a5ebffc1c4ec
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 34728
content:
"[...] waters are already undersaturated with respect to aragonite due to \r the degradation of terrestrial organic matter (Mathis et  al., 2015; \r Semiletov et al., 2016), the deep aragonite saturation horizon shoaled \r on average 270 +- 60 m during 1765-2005 (Terhaar et al., 2020)."


id: f8d40f4f189420295be46f8d085e0df1
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 41140
content:
"Detection and attribution of ocean acidification in coastal environments \r are more difficult than in the open ocean due to larger spatio-temporal \r variability of carbonate chemistry (Duarte et  al., 2013; Laruelle \r et al., 2017; Torres et al., 2021) and to the influence of other natural \r acidification drivers such as freshwater and high-nutrient riverine \r inputs (Cai et al., 2011; Laurent et al., 2017; Fennel et al., 2019; Cai \r et  al., 2020) or anthropogenic acidification drivers (Section  3.1) like \r atmospherically deposited nitrogen and sulphur (Doney et  al., 2007; \r Hagens et  al., 2014). Since AR5, the observing network in coastal \r oceans has expanded substantially, improving understanding of both \r the drivers and amplitude of observed variability (Sutton et al., 2016). \r Recent studies indicate that two more decades of observations may be \r required before anthropogenic ocean acidification emerges over natural \r [...]"


id: 87839df75d412fbe6f1035a543ee5d32
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 20998
content:
"[...] variability in some coastal sites and regions (WGI AR6 Section 5.3.5.2; \r Sutton et al., 2019; Turk et al., 2019; Canadell et al., 2021)."


id: e86b4f3cf8a973f8d58b8f0101f75fb5
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 38224
content:
"The most recent estimates of future oxygen loss in the subsurface \r ocean (100-600 m), using CMIP6 models, amount to -4.1  +-  4.2 \r (very likely range), -6.6 +- 5.7, -10.1 +- 6.7 and -11.2 +- 7.7% in \r 2081-2100 relative to 1995-2014 for SSP1-2.6, SSP2-4.5, SSP3-7.0 \r and SSP5-8.5, respectively (Figure  3.5; Kwiatkowski et  al., 2020). \r Based on these CMIP6 projections, WGI AR6 concludes that the \r oxygen content of the subsurface ocean is projected to decline to \r historically unprecedented conditions over the 21st century (medium \r confidence) (WGI AR6 Section 5.3.3.2; Canadell et al., 2021). These \r declines are greater (by 31-72%) than simulated by the CMIP5 \r models in their Representative Concentration Pathway (RCP) \r analogues, a likely consequence of enhanced surface warming and \r stratification in CMIP6 models (Figure 3.5; Kwiatkowski et al., 2020). \r At the regional scale and for subsurface waters, projected changes \r [...]"


id: d8835e998e345323fa3901d6e0ca269c
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 35386
content:
"[...] are not spatially uniform, and there is lower agreement among \r models than they show for the global mean trend (Bopp et al., 2013; \r Kwiatkowski et al., 2020). In particular, large uncertainties remain for \r these future projections of ocean deoxygenation in the subsurface \r tropical oceans, where the major OMZs are located (Cabre et  al., \r 2015; Bopp et al., 2017)."


id: ee63d6e76df031a2b9447787c5fe3efd
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 39317
content:
"Earth system models project distinct regional evolutions of the \r different CIDs over the 21st century (very high confidence) (Figures 3.5, \r 3.6, 3.7; Kwiatkowski et al., 2020). Tropical and subtropical oceans are \r characterised by projected warming and acidification, accompanied by \r declining nitrate concentrations in equatorial upwelling regions. The \r North Atlantic is characterised by a high exposure to acidification and \r declining nitrate concentrations. The North Pacific is characterised by \r high sensitivity to compound changes, with high rates of warming, \r acidification, deoxygenation and nutrient depletion. In contrast, the \r development of compound hazards is limited in the Southern Ocean, \r where rates of warming and nutrient depletion are lower. The Arctic \r Ocean is characterised by the highest rates of acidification and \r warming, strong nutrient depletion, and it will likely become practically \r sea ice free in the September mean for the first time before the year \r [...]"


id: 4eb47b82a02fdf531fe3d6e4409f44b8
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 11120
content:
"[...] 2050 in all SSP scenarios (high confidence) (Figures  3.5, 3.6, 3.7; \r Sections 3.2.2, 3.2.3)."


id: 47352dd18ccb77143364e6a12d0ee70
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 9726
content:
"The availability of nutrients in the surface ocean often limits primary \r productivity, with implications for marine food webs and the biological \r carbon pump. Nitrogen availability tends to limit phytoplankton \r productivity throughout most of the low-latitude ocean, whereas \r dissolved iron availability limits productivity in high-nutrient, low\u0002chlorophyll regions, such as in the main upwelling region of the Southern \r Ocean and the Eastern Equatorial Pacific (high confidence) (Moore \r et  al., 2013; IPCC, 2019b). Phosphorus, silicon, other micronutrients \r such as zinc, and vitamins can also co-limit marine phytoplankton \r productivity in some ocean regions (Moore et  al., 2013). Whereas \r some studies have shown coupling between climate variability and \r nutrient trends in specific regions, such as in the North Atlantic (Hatun \r et  al., 2016), North Pacific (Di Lorenzo et  al., 2009; Yasunaka et  al., \r 2014) and tropical (Stramma and Schmidtko, 2021) Oceans, very few \r [...]"


id: 51e3754b1470a127e31fe6ff9bcc272b
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 11691
content:
"[...] studies have been able to detect long-term changes in ocean nutrient \r concentrations (but see Yasunaka et al., 2016)."


id: 63f46fda3f9c7957d83998e936940cfd
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 14874
content:
"The literature assessed in SROCC mainly focused on surface ocean \r properties and gradual mean changes. Since then, the time of \r emergence has also been investigated for subsurface properties, ocean \r extreme events and particularly vulnerable regions, such as the Arctic \r Ocean (Hameau et al., 2019; Oliver et al., 2019; Burger et al., 2020; \r Landrum and Holland, 2020; Schlunegger et al., 2020), but subsequent \r assessments are low confidence due to limited evidence. Below \r the surface, changes in temperature typically emerge from internal \r variability prior to changes in oxygen; however, in about a third of the \r global thermocline, deoxygenation emerges prior to warming (Hameau \r et al., 2019). Permanent MHW states, defined as when SST exceeds \r the MHW threshold continuously over a full calendar year, will emerge \r during the 21st  century in many parts of the surface ocean (Oliver \r et al., 2019). Ocean acidification extremes have already emerged from \r [...]"


id: 62575422154e04bef7f845bd3c983155
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 14578
content:
"[...] background natural internal variability during the 20th century in most \r of the surface ocean (Burger et al., 2020). In the Arctic, anthropogenic \r sea ice changes have already emerged from the background internal \r variability, and anthropogenic alteration of air temperatures will \r emerge in the early- to mid-21st century (Landrum and Holland, 2020)."


id: 173e8c2445cffd7f809ce7d11c72df68
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 1306
content:
"This section assesses new evidence since AR5 (Portner et al., 2014) and \r SROCC (Bindoff et al., 2019a) regarding biotic responses to multiple \r environmental drivers. It assesses differential sensitivities among life \r stages within individual organisms, changing responses across scales \r of biological organisation and the potential for evolutionary adaptation \r to climate change (e.g., Przeslawski et  al., 2015; Boyd et  al., 2018; \r Reddin et al., 2020), providing examples and identifying key gaps and \r uncertainties that limit our ability to project the ecological impact of \r multiple climate-induced drivers (Figure 3.8a). The assessment includes \r physiological responses to single environmental drivers and their \r underlying mechanisms (Section 3.3.2), the characteristics of multiple \r drivers and organisms' responses to them (Section 3.3.3), short-term \r acclimation and longer-term evolutionary adaptation of populations \r [...]"


id: d7d3c04f968ce52967dc74f988578ee0
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 35278
content:
"[...] (Section  3.3.4), and it concludes with an assessment of progress in \r upscaling laboratory findings to ecosystems within in situ settings \r (Figure 3.8b; Section 3.3.5)."


id: 3d8d730e7b2e3a811745408f04523d53
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 8004
content:
"Paleoclimatology observations are useful to assess multiple hazards \r of environmental change while excluding direct anthropogenic \r impacts (Section 3.4.3.3). Ancient intervals of rapid climate warming \r that occurred between 300 and 50  million  years ago (Ma) were \r triggered by the release of greenhouse gases (high confidence). The \r sources of greenhouse gases varied but include volcanic degassing \r from continental flood basalts and methane hydrates stored in \r marine sediments and soils (Foster et al., 2018). Six extreme ancient \r hyperthermal events are known from the last 300 Ma, when tropical \r SSTs reached 1.5degC-10degC warmer than pre-industrial conditions, and \r with substantial impacts on ancient life (Cross-Chapter Box  PALEO \r in Chapter  1). Warming and deoxygenation in the oceans were \r closely associated in hyperthermal events (high confidence), with \r anoxia reaching the photic zone and abyssal depths (Kaiho et  al., \r [...]"


id: bcd23e26c966f3b69a744ea06115d8a6
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 30461
content:
"[...] 2014; Muller et al., 2017; Penn et al., 2018; Weissert, 2019), whereas \r ocean acidification has not been demonstrated consistently (medium \r confidence) (Honisch et al., 2012; Penman et al., 2014; Clarkson et al., \r 2015; Harper et al., 2020a; Jurikova et al., 2020; Muller et al., 2020)."


id: 45c54f640ee6aefba3a9db5a369766a7
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 9492
content:
"Temperature affects the movement and transport of molecules and, \r thereby, the rates of all biochemical reactions; thus, ongoing and \r projected warming (Section 3.2.2.1) that remains below an organism's \r physiological optimum will generally raise metabolic rates (very \r high confidence) (Portner et  al., 2014). Beyond this optimum (Topt; \r Figure  3.9), metabolism typically decreases sharply, finally reaching \r a critical threshold (Tcrit) beyond which enzymes become thermally \r inactivated and cells undergo oxidative stress. Local and regional \r adaptation affect the heat tolerance thresholds of organisms. For \r example, organisms adapted to thermally stable environments (e.g., \r tropical, polar, deep sea) are often more sensitive to warming than \r those from thermally variable environments (e.g., estuaries) (very \r high confidence) (Section  3.4; Sunday et  al., 2019; Collins et  al., \r 2020). Heat tolerance also decreases with increasing organisational \r [...]"


id: e8cfb9183b0b6282b17a30aa2dbcffdc
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 38308
content:
"[...] complexity (Storch et al., 2014; Portner and Gutt, 2016) and is lower in \r eggs, embryos and spawning fish than for their larval stages or adults \r outside the spawning season (high confidence) (Dahlke et al., 2020b). \r By altering physiological responses, projected changes in ocean \r warming (Section 3.2.2.1) will modify growth, migration, distribution, \r competition, survival and reproduction (very high confidence) \r (Messmer et al., 2017; Dahlke et al., 2018; Andrews et al., 2019; Pinsky \r et al., 2019; Anton et al., 2020)."


id: 4ec2002be03996a91198bc91e57b8abe
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 11133
content:
"Increased density stratification and mixed-layer shallowing, caused by \r warming, freshening and sea ice decline, can alter light climate and \r nutrient availability within the surface mixed layer (high confidence) \r (Section  3.2.2.3). As light and nutrient levels drive photosynthesis, \r changes in these drivers directly affect primary producers, often in \r different directions (Matsumoto et al., 2014; Deppeler and Davidson, \r 2017). Decreased upward nutrient supply is expected to decrease \r primary production in the low-latitude ocean (medium confidence) \r (Section  3.4.4.2.1; Moore et  al., 2018a; Kwiatkowski et  al., 2019). \r Alternatively, higher mean underwater light levels resulting from \r changes in sea ice and/or mixed layer shallowing can increase primary \r production in high-latitude offshore regions, provided nutrient levels \r remain sufficiently high (medium confidence) (Section 3.4.4.2.1; Cross\u0002Chapter Paper 6; Vancoppenolle et al., 2013; Deppeler and Davidson, \r [...]"


id: 6095775f378f04bcf408c5835984f584
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 14291
content:
"[...] 2017; Tedesco et al., 2019; Ardyna and Arrigo, 2020; Lannuzel et al., \r 2020). In some parts of the open Southern Ocean, where iron limitation \r largely controls primary productivity (Tagliabue et al., 2017), changes \r in wind fields will deepen the summer mixed-layer depth (Panassa \r et al., 2018), entrain more nutrients, and raise primary productivity in \r the future (medium confidence) (Cross-Chapter Paper 6; Hauck et al., \r 2015; Leung et al., 2015; Moore et al., 2018a; Kwiatkowski et al., 2020)."


id: 68ea1c6c601969af52c18e9403bb7406
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 15728
content:
"macroalgal and seagrass species (high confidence) (Portner et al., 2014; \r Seifert et al., 2020; Zimmerman, 2021), while lower pH levels decrease \r calcification (high confidence) (Portner et al., 2014; Falkenberg et al., \r 2018; Doney et  al., 2020; Fox et  al., 2020; Reddin et  al., 2020) or \r silicification (low confidence) (Petrou et al., 2019). Organisms' capacity \r to compensate for or resist acidification of internal fluids depends \r on their capacity for acid-base regulation, which differs due to \r organisms' wide-ranging biological complexity and adaptive abilities \r (low to medium confidence) (Vargas et  al., 2017; Melzner et  al., \r 2020). Detrimental impacts of acidification include decreased growth \r and survival, and altered development, especially in early life stages \r (high confidence) (Dahlke et al., 2018; Onitsuka et al., 2018; Hancock \r et al., 2020), along with lowered recruitment and altered behaviour in \r [...]"


id: 4c2a35b32059b2febf63c572025fdc40
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 10659
content:
"[...] animals (Kroeker et al., 2013a; Wittmann and Portner, 2013; Clements \r and Hunt, 2015; Cattano et al., 2018; Esbaugh, 2018; Bednarsek et al., \r 2019; Reddin et al., 2020). For finfish, laboratory studies of behavioural \r and sensory consequences of ocean acidification showed mixed results \r (Rossi et al., 2018; Nagelkerken et al., 2019; Stiasny et al., 2019; Velez \r et  al., 2019; Clark et  al., 2020; Munday et  al., 2020). Calcifiers are \r generally more sensitive to acidification (e.g., for growth and survival) \r than non-calcifying groups (high confidence) (Kroeker et  al., 2013a; \r Wittmann and Portner, 2013; Clements and Hunt, 2015; Cattano et al., \r 2018; Bednarsek et al., 2019; Reddin et al., 2020; Seifert et al., 2020). \r For calcifying primary producers, including phytoplankton and coralline \r algae, ocean acidification has different, often opposing effects, for \r example, decreasing calcification while photosynthetic rates increase \r [...]"


id: 6b3cd604d85d1ee9068e6e4bc32c34c0
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 16162
content:
"[...] (high confidence) (Riebesell et al., 2000; Van de Waal et al., 2013; Bach \r et al., 2015; Cornwall et al., 2017b; Gafar et al., 2019)."


id: 14b47037b1a39a4dc99d4c3a3042797c
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 869
content:
"Climate-induced drivers fluctuate on time scales ranging from diurnal \r to annual, with potential consequences for organismal responses \r (Figure 3.10), but these fluctuations are commonly not incorporated \r experimentally. Experiments that simulate natural fluctuations in \r drivers, especially beyond tidal or diel cycles, can result in more \r detrimental impacts than those based on quasi-constant conditions \r (Eriander et al., 2015; Sunday et al., 2019), but can also ameliorate \r effects (Comeau et al., 2014; Laubenstein et al., 2020; Cabrerizo et al., \r 2021), confirming that the influence of environmental variability \r requires evaluation (Dowd et al., 2015). Marine heatwaves exacerbate \r the impacts of rising mean temperatures, with major ecological \r consequences (very high confidence) (Frolicher et al., 2018; IPCC, 2018; \r Arafeh-Dalmau et al., 2020; Laufkotter et al., 2020). Higher temperature \r variability decreased phytoplankton growth and calcification in \r [...]"


id: efb10faad8167284b9f30eedf7970b2e
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 39549
content:
"[...] Emiliania huxleyi relative to a stable warming regime (Wang et  al., \r 2019b). Diel fluctuations (i.e., over 24 h) in carbonate chemistry \r superimposed on current and future pCO2 levels influenced diatom \r species differently, depending on their habitat (Li et  al., 2016). CO2\r fluctuations overlaid on changing mean values also altered phenotypic \r evolutionary outcomes of picoeukaryotic algae (Schaum et al., 2016). \r In the bivalve Mytilus edulis, fluctuating pH regimes exerted higher \r metabolic costs (Mangan et  al., 2017), while salinity fluctuations \r might be more influential than pH fluctuations in other bivalves (Velez \r et al., 2016). The amplitude of diel and seasonal pH and CO2 changes \r are projected to increase in the future due to lowered CO2 seawater \r buffering capacity (very high confidence) (Section 3.2.3.1; Burger et al., \r 2020), which can impose additional stress on organisms."


id: 2981ef3a821f5f847faa400d0894691a
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 4522
content:
"Oxygen concentrations affect aerobic and anaerobic processes, \r including energy metabolism and denitrification. Projected decreases \r in dissolved oxygen concentration (Section 3.2.3.2) will thus impact \r organisms and their biogeography in ways dependent upon their \r oxygen requirements (Deutsch et  al., 2020), which are highest for \r large, multicellular organisms (Portner et al., 2014). The upper ocean \r generally contains high dissolved-oxygen concentrations due to \r air-sea exchange and photosynthesis, but in subsurface waters, \r deoxygenation may impair aerobic organisms in multiple ways \r (Oschlies et al., 2018; Galic et al., 2019; Thomas et al., 2019; Sampaio \r et  al., 2021). Many processes contribute to lowered oxygen levels: \r altered ventilation and stratification; microbial respiration enhanced \r by nearshore eutrophication; and less oxygen solubility in warmer \r waters. For example, deoxygenation in highly eutrophic estuarine and \r [...]"


id: 7fac49ad3188cfba5cbc690da4693af5
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 19597
content:
"[...] coastal marine ecosystems (Section 3.4.2) can result from accelerated \r microbial activity, leading to acute organismal responses. Under \r hypoxia (oxygen concentrations <=2 mg  l-1; Limburg et  al., 2020), \r physiological and ecological processes are impaired and communities \r undergo species migration, replacement and loss, transforming \r community composition (very high confidence) (Chu and Tunnicliffe, \r 2015; Gobler and Baumann, 2016; Sampaio et  al., 2021). Hypoxia \r can lead to expanding OMZs, which will favour specialised microbes \r and hypoxia-tolerant organisms (medium confidence) (Breitburg \r et  al., 2018; Ramirez-Flandes et  al., 2019). As respiration consumes \r oxygen and produces CO2, lowered oxygen levels are often interlinked \r with acidification in coastal and tropical habitats (Rosa et al., 2013; \r Gobler and Baumann, 2016; Feely et al., 2018) and is an example of a \r compound hazard (Sections 3.2.4.1, 3.4.2.4)."


id: 5d2236137a4462401f9824abf0c1fbe1
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 13657
content:
"(b) The hierarchy of accumulating physiological knowledge (grey layers), from single (e.g., Portner et al., 2012) to multiple drivers, and from simple outcomes (e.g., Sciandra et al., \r 2003), interactions among drivers (e.g., Crain et al., 2008) and identification of physiological roles of drivers (e.g., Bach et al., 2015) to mechanistic understanding of drivers (e.g., \r Thomas et al., 2017). At present, the upper grey layer has been achieved, in full, for two drivers (e.g., temperature and nutrient concentrations), with validation of dual controls \r on phytoplankton growth rate (Thomas et al., 2017). Hatched layers denote major advances since WGII AR5 Chapter 6 (Portner et al., 2014). The green layer indicates the level of \r understanding potentially needed to project the response of marine life subjected to multiple drivers. Red horizontal arrows indicate the influence of confounding factors on our \r [...]"


id: 894e61703d9f29a04566cfca5d027ca1
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 21330
content:
"[...] current understanding, including population genetics, fluctuating oceanic conditions or extreme events."


id: d823067403f9368b3d9b644ed188d5ec
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 35328
content:
"duration of its exposure to these drivers and associated sensitivities. \r Both geographic location (e.g., polar, tropical) and marine habitat (e.g., \r benthic, pelagic) strongly affect the combination of climate and non\u0002climate drivers to which organisms are exposed. Non-climate drivers \r (Section 3.1) can dominate outcomes or amplify vulnerability to climate\u0002induced drivers, with mostly detrimental effects such as extirpation \r (very high confidence) (Section 3.4; Boyd et al., 2018; Gissi et al., 2021), \r and unique feedbacks may exist between climate change and drivers \r like habitat loss or invasive species that further confound climate\u0002change effects (Ortiz et al., 2018; Wolff et al., 2018; Gissi et al., 2021). \r Individual responses are further influenced by an organism's behaviour, \r trophic level and life-history strategy (Figure 3.10; Przeslawski et al., \r 2015; Boyd et al., 2018). Evidence is increasing that some life-history \r [...]"


id: 60bea0e38fe2619fcf1a9b66cde96658
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 14315
content:
"[...] stages are more sensitive to specific drivers than others (Dahlke et al., \r 2020b). To identify the most influential drivers for an organism requires \r targeting key traits (e.g., calcification, reproduction). The trophic level \r of the organism must also be considered, because autotrophs directly \r depend on light and nutrients while invertebrates are often more \r sensitive to changes in oxygen or altered prey, but temperature plays \r a key role for both groups (Figure 3.10b)."


id: b34205f7cefdfb4df05abe13414f53b8
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vector_id: 28778
content:
"Thermal sensitivity of pelagic primary producers changes with nutrient \r supply (high confidence) (Thomas et al., 2017; Maranon et al., 2018; \r Fernandez et al., 2020). Phosphorus limitation lowers the temperature \r optimum for growth of phytoplankton, making these organisms more \r prone to heat stress (Thomas et al., 2017; Bestion et al., 2018). This \r trend may hold for open-ocean phytoplankton, which are often iron\u0002limited (medium confidence) (Boyd, 2019). Such temperature-nutrient \r interactions might be especially relevant during summer MHWs \r (Section  3.2.2.1; Cross-Chapter Box  EXTREMES in Chapter  2; IPCC, \r 2018; Holbrook et  al., 2019; DeCarlo et  al., 2020; Hayashida et  al., \r 2020), when primary producers are often nutrient-limited and near their \r thermal limits. Increasingly frequent and intense MHWs along with \r projected decreases in nutrient availability (Section 3.2.3.3) may push \r some primary producers beyond tolerance thresholds. Temperature-\r [...]"


id: b38e43b69f63280388731b0bbe5a1280
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 28831
content:
"[...] nutrient interactions can also alter the photosynthesis-to-respiration \r ratio in phytoplankton (Maranon et al., 2018). Overall, rising metabolic \r rates due to warming will be restricted to primary producers in high\u0002nutrient regions (medium confidence) (Thomas et al., 2017; Maranon \r et al., 2018). For zooxanthellae-containing corals, nutrient supply from \r upwelling or from runoff can increase coral susceptibility to bleaching \r during warm-season MHWs (DeCarlo et al., 2020; Wooldridge, 2020)."


id: 774883561a3dbd4bddc8aa16689afe2
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 18190
content:
"Co-occurring environmental drivers often cause complex organismal \r responses (high confidence) (Portner et  al., 2014). Individual drivers \r can have detrimental, neutral or beneficial effects, depending on the \r relationship between driver and physiological process (Section 3.3.2; \r Figure 3.9a). Multiple drivers can have interactive effects, where the \r response to one driver alters the sensitivity to another, and outcomes \r cannot be deduced from individual drivers' effects (Figure  3.9b). \r Impacts of multiple drivers can be additive, synergistic or antagonistic \r (Figure 3.9c; Crain et al., 2008; Piggott et al., 2015; Boyd et al., 2018; \r Bindoff et al., 2019a). Well-controlled laboratory studies on multiple\u0002driver effects have revealed insights into the mode of action of \r individual drivers and their interdependence (Kroeker et al., 2017; Gao \r et al., 2019; Reddin et al., 2020; Seifert et al., 2020; Green et al., 2021b; \r [...]"


id: 59203d794cba84b6ad2bf067c1193264
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 12924
content:
"[...] Sampaio et  al., 2021). Understanding the outcomes of interactive \r drivers is important for robustly assessing risks to organisms under \r different climate-change scenarios."


id: 7d0a48477b747d7209a7467b70431623
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 19184
content:
"The effects of ocean acidification on growth, metabolic rates or \r elemental composition of primary producers changes with nutrient \r availability and light conditions (high confidence) (Gao et al., 2019; \r Seifert et  al., 2020). While interactions with nutrients are often \r additive in phytoplankton, diatoms revealed predominantly synergistic \r interactions (Seifert et al., 2020). Growth or photosynthesis of some \r diatom and HAB species, for instance, are stimulated by ocean \r acidification only if nutrients are replete (Hoppe et al., 2013; Boyd et al., \r 2015b; Eberlein et al., 2016; Griffith et al., 2019a). Interactions with \r light are more complex because relative effects of ocean acidification \r are larger under limiting irradiances, while saturating light levels \r decrease beneficial or detrimental effects on these processes (Kranz \r et al., 2010; Garcia et al., 2011; Rokitta and Rost, 2012; Heiden et al., \r 2016). For the coccolithophore Emiliania huxleyi, for example, the \r [...]"


id: badd168bc08c81881320cb21c0e8df06
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 30091
content:
"[...] impacts of ocean acidification are less detrimental under high light \r availability, which could partly explain why this species is moving \r poleward (Winter et al., 2014; Kondrik et al., 2017; Neukermans et al., \r 2018), although acidification is more pronounced in polar waters \r (Section 3.2.3.1; Cross-Chapter Paper 6). Under excess light, however, \r the detrimental impacts of ocean acidification are amplified for many "


id: 705bdb0b9560fde5b3177de4397baada
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 17023
content:
"Warming and rising CO2 concentrations enhance growth and/or \r photosynthetic rates in many species of cyanobacteria, picoeukaryotes, \r coccolithophores, dinoflagellates and diatoms (high confidence) \r (Fu et  al., 2007; Sett et  al., 2014; Hoppe et  al., 2018a; Wolf et  al., \r 2018; Brandenburg et al., 2019), and the optimum pCO2 for growth \r and/or primary production shifts upward under warming (medium \r confidence) (Sett et al., 2014; Hoppe et al., 2018a). Warming and ocean \r acidification appear to jointly favour the proliferation and toxicity of \r harmful algal bloom (HAB) species (limited evidence, high agreement) \r (Section  3.5.5.3; Bindoff et  al., 2019a; Brandenburg et  al., 2019; \r Griffith et  al., 2019a; Wells et  al., 2020), but a 2021 analysis found \r no uniform global trend in HABs or their distribution over 1985-2018 \r once field data were adjusted for regional variations in monitoring \r effort (Hallegraeff et al., 2021). The predominantly detrimental impacts \r [...]"


id: a889c48a89f0331ce8016797231e9a82
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 26863
content:
"[...] of ocean acidification on coccolithophores can partly be offset by \r warming (Seifert et al., 2020) but also be exacerbated, depending on \r the magnitudes of drivers (D'Amario et al., 2020). For non-calcifying "


id: c16eb17df43e4e2826036a5c19c0e10d
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 31337
content:
"Lievanos et al., 2019; Schwieterman et al., 2019). Warming and hypoxia \r are mostly positively correlated and tolerances to both phenomena \r are often linked after long-term acclimation (e.g., Bouyoucos et  al., \r 2020). Acute short-term heat shocks can impair hypoxia tolerance, \r for instance, in intertidal fish (McArley et al., 2020). This is relevant \r for shallow waters, specifically for MHWs (Section  3.2.2.1; Hobday \r et al., 2016a; IPCC, 2018; Collins et al., 2019a). Ocean acidification can \r increase hypoxia tolerance in some cases, possibly by downregulating \r activity (Faleiro et  al., 2015) and/or changing blood oxygenation \r (Montgomery et al., 2019). Other studies, however, reported additive \r negative effects of acidification and warming on hypoxia tolerance \r (Schwieterman et al., 2019; Gotze et al., 2020), in line with the oxygen\u0002and capacity-limited thermal tolerance (OCLTT) hypothesis presented \r in AR5 (Portner et  al., 2014): Warming causes increased metabolic \r [...]"


id: d44dd8065705c547cf7569cacbaf38c3
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 34677
content:
"[...] rates and oxygen demand in ectotherms, which at some point exceed \r supply capacities (which also depend on environmental oxygen \r availability) and reduce aerobic scope. In consequence, expansion of \r OMZs and other regions where warming, hypoxia and acidification \r combine will further reduce habitat for many fish and invertebrates \r (high confidence) (Sections 3.4.3.2, 3.4.3.3)."


id: 2a5b436508c7a5b0639fbf950f0341be
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 4676
content:
"Food availability modulates, and may be more influential than, \r other driver responses by affecting the energetic and nutritional \r status of animals (Cole et  al., 2016; Stiasny et  al., 2019; Cominassi \r et al., 2020). Laboratory studies conducted under an excess of food \r risk underestimating the ecological effects of climate-induced \r drivers, because increased feeding rates may help mitigate adverse \r effects (Nowicki et  al., 2012; Towle et  al., 2015; Cominassi et  al., \r 2020). Lowered food availability from reduced open-ocean primary \r production (Sections 3.2.3.3, 3.4.4.2.1) will act as an additional driver, \r amplifying the detrimental effects of other drivers. However, warming \r and higher CO2 availability may increase primary productivity in some \r coastal areas (Section 3.4.4.1), ameliorating the adverse direct effects \r on animals (e.g., Sswat et al., 2018). Due to the few studies addressing \r food availability under multiple-driver scenarios (Thomsen et al., 2013; \r [...]"


id: 55ec94639dbb53b2758a5f47505dcca0
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 12392
content:
"[...] Pistevos et al., 2015; Towle et al., 2015; Ramajo et al., 2016; Brown \r et al., 2018a; Cominassi et al., 2020), there is medium confidence in its \r modulating effect on climate-induced driver responses."


id: 89cd425244dc30757410c59619b57c9a
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 21412
content:
"When changing CO2 concentrations affect marine ectotherms, they \r typically combine additively or synergistically with warming (medium \r confidence) (e.g., Lefevre, 2016; Reddin et al., 2020; Sampaio et al., \r 2021), and their cumulative effects can lead to detrimental, neutral or \r beneficial effects (high confidence) (Figure 3.9a; Bennett et al., 2017; \r Buscher et al., 2017; Dahlke et al., 2017; Foo and Byrne, 2017; Johnson \r et al., 2017b; Cominassi et al., 2019). Higher ocean CO2 influences the \r thermal tolerance of species adapted to extreme but stable habitats \r in tropical and polar regions, more than that of thermally tolerant \r generalists (high confidence) (Byrne et al., 2013; Schiffer et al., 2014; \r Flynn et al., 2015; Kunz et al., 2016; Portner et al., 2017; Kunz et al., \r 2018; Bindoff et  al., 2019a; but see Ern et  al., 2017), especially in \r early life stages (Dahlke et  al., 2020a). In thermal generalists from \r [...]"


id: efaabe8119e25e656811b2d19fbd1125
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 39547
content:
"[...] temperate and subtropical species, warming and ocean acidification \r generally have detrimental effects on growth and survival (e.g., Gao \r et al., 2020), but warming can also alleviate the detrimental effects \r of ocean acidification by increasing metabolic rate and/or growth \r (Garzke et  al., 2020), provided that other conditions (e.g., thermal \r niche, food availability) are beneficial. For example, larval growth and \r survival of Australasian snapper (Pagrus auratus) appear to benefit \r from combined acidification and warming (but see Watson et al., 2018; \r McMahon et al., 2020), introducing major uncertainties to population \r modelling (Section 3.3.4; Parsons et al., 2020)."


id: 583f54f9f5fc180c0564b84c14fed811
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 12781
content:
"Animal behaviour can be affected by ocean acidification, warming \r and hypoxia. While warming and hypoxia mostly induce avoidance \r behaviour, potentially leading to migration and habitat compression \r (Section 3.4; McCormick and Levin, 2017; Limburg et al., 2020), the \r effects of acidification appear more complex. Some studies reported \r that acidification dominates behavioural effects (Schmidt et al., 2017), \r although outcomes vary with experimental design and duration \r of exposure (low confidence, low agreement) (Maximino and de \r Brito, 2010; Munday et  al., 2016; Laubenstein et  al., 2018; Munday \r et  al., 2019; Sundin et  al., 2019; Clark et  al., 2020; Munday et  al., \r 2020; Williamson et  al., 2021). Behaviour represents an integrated \r phenomenon that can be influenced both directly and indirectly \r by multiple drivers. For instance, increased pCO2 can directly act \r on neuronal signalling pathways (e.g., Gamma-aminobutyric acid \r [...]"


id: 31673243e942579e7860a5e77276709c
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 5936
content:
"[...] hypothesis; Nilsson et  al., 2012; Thomas et  al., 2020) and influence \r learning (Chivers et al., 2014), vision (Chung et al., 2014), and choice \r and escape behaviour (Watson et al., 2014; Wang et al., 2017b). There \r is further evidence that observed alterations in fish olfactory behaviour "


id: 6b221b27d77ee0013a3857c073d4b342
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 16145
content:
"under ocean acidification may result from physiological and molecular \r changes of the olfactory epithelium, influencing olfactory receptors \r (Roggatz et al., 2016; Porteus et al., 2018; Velez et al., 2019; Mazurais \r et al., 2020). Temperature mainly drives metabolic processes and thus \r energetic requirements, which can indirectly influence behaviour, \r including increased risk-taking during feeding (Marangon et  al., \r 2020). Ocean warming also accelerates the biochemical reactions \r and metabolic processes that are primarily influenced by acidification. \r It is therefore difficult to generalise to what extent co-occurring \r ocean warming ameliorates or exacerbates effects of acidification on \r behaviour (Laubenstein et al., 2019); outcomes depend upon species \r and life stage (Faleiro et al., 2015; Chan et al., 2016; Tills et al., 2016; \r Wang et al., 2018b; Jarrold et al., 2020), interactions between species \r (e.g., Paula et  al., 2019) along with confounding factors including \r [...]"


id: ef03b1c3c62682ff4bc634ec2bb0a707
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 39419
content:
"[...] food availability and salinity (medium confidence) (Ferrari et  al., \r 2015; Pistevos et al., 2015; Pimentel et al., 2016; Pistevos et al., 2017; \r Horwitz et al., 2020)."


id: 5be95b064de5235a884f0c1e2d06371
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 13429
content:
"Other mechanisms acting within and across generations can influence \r selection and inter-population tolerances to environmental and \r climate-induced drivers. For instance, transgenerational effects and/or \r developmental acclimation, both 'carry-over effects' (where the early\u0002life environment affects the expression of traits in later life stages or \r generations), can influence within- and cross-generational changes \r in the tolerances of marine organisms (medium confidence) to ocean \r warming (Balogh and Byrne, 2020) and acidification (Parker et al., 2012). \r Over longer time scales, increasing tolerance to these drivers may be \r mediated by mechanisms such as transgenerational plasticity (Murray \r et al., 2014), leading to locally adapted genotypes as seen in bivalves \r (Thomsen et al., 2017), annelids (Rodriguez-Romero et al., 2016; Thibault \r et al., 2020), corals (Putnam et al., 2020) and coralline algae (Cornwall \r [...]"


id: 99910cafb3fcf43ffbaadd998e27ca1b
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 24248
content:
"[...] et  al., 2020). However, transgenerational plasticity is species specific \r (Byrne et al., 2020; Thibault et al., 2020) and, depending on the rate and \r magnitude of environmental change, it may either be insufficient for \r evolutionary rescue (Morgan et al., 2020) or could induce maladaptive \r responses (i.e., reduced fitness) in marine organisms exposed to multiple \r drivers (medium confidence, low evidence) (Figure  3.11; Griffith and \r Gobler, 2017; Parker et al., 2017; Byrne et al., 2020)."


id: bc319d014395875ff1334e7bf257788b
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 30354
content:
"Climate change is and will continue to be a major driver of natural \r selection, causing important changes in fitness-related (e.g., growth, \r reproduction, survival) and functional (e.g., body/cell size, morphology, \r physiology) traits, and in the genetic diversity of natural populations \r (medium confidence) (Pauls et  al., 2013; Merila and Hendry, 2014). \r Climate-change impacts will continue to be exacerbated by interactions \r with non-climate drivers such as habitat fragmentation or loss, pollution \r or resource overexploitation, which limit the adaptive potential of \r populations to future conditions (Trathan et al., 2015; Gaitan-Espitia \r and Hobday, 2021). However the ultimate responses to complex \r change are conditioned by the rate and magnitude of environmental \r change, organisms' capacity for acclimation, the degree of local \r adaptation of natural populations and populations' potential for \r adaptive evolution (Figure 3.11; Pespeni et al., 2013; Calosi et al., 2017; \r [...]"


id: 7f18ea1710e285aa726437f7ed3af450
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 19510
content:
"[...] Vargas et al., 2017). These controlling factors are mainly determined \r by local environmental conditions encountered by populations across \r their geographic distribution (Boyd et al., 2016). In highly fluctuating \r environments (e.g., upwelling regions, coastal zones), multiple drivers \r can change and interact across temporal and spatial scales, generating \r geographic mosaics of tolerances and sensitivities to environmental \r and climate change in marine organisms (medium confidence) (Pespeni \r et al., 2013; Boyd et al., 2016; Vargas et al., 2017; Li et al., 2018a). A \r further challenge for marine life lies in its ability to cope with extreme "


id: a93ffc973734e076b219ecb8b5e39cf7
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 26999
content:
"Acclimation to environmental pressures and climate change via \r phenotypic plasticity (Section  3.3.3; Collins et  al., 2020) enables \r species to undergo niche shifts such that their present-day climatic \r niche is altered to incorporate new or shifted conditions (Fox et al., \r 2019). Although plasticity provides an adaptive mechanism, it is \r unlikely to provide a long-term solution for species undergoing \r sustained directional environmental change (e.g., global warming) \r (medium confidence) (Fox et  al., 2019; Gaitan-Espitia and Hobday, \r 2021). Beyond the limits for plastic responses (Figure  3.9; DeWitt \r et al., 1998; Valladares et al., 2007), genetic adjustments are required \r to persist in a changing world (Figure  3.11; Fox et  al., 2019). The \r ability of species and populations to undergo these adjustments (i.e., \r adaptive evolution) depends on extrinsic factors including the rate \r and magnitude of environmental change (important determinants \r [...]"


id: 2bea3afd4c431b853d97a529f8fde0d4
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 4977
content:
"a plausible envelope of trajectories across a range of assumptions \r (Fulton et al., 2018; Peck et al., 2018; Tittensor et al., 2018). On a global \r scale, ecosystem models project a -5.7  +-  4.1% (very likely range) \r to -15.5  +-  8.5% decline in marine animal biomass with warming \r under SSP1-2.6 and SSP5-8.5, respectively, by 2080-2099 relative to \r 1995-2014, albeit with significant regional variation in both trends \r and uncertainties (medium confidence) (Section  3.4.3.4; Tittensor \r et  al., 2021). Biological interactions may exacerbate or buffer the \r projected impacts. For instance, trophic amplification (strengthening \r of responses to climate-induced drivers at higher trophic levels) may \r result from combined direct and indirect food-web-mediated effects \r (medium confidence) (Section 3.4.3.4; Lotze et al., 2019). Alternatively, \r compensatory species interactions can dampen strong impacts on \r species from ocean acidification, resulting in weaker responses at \r [...]"


id: 2d8bc551057b0183c16ee0c0d2c22791
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 5307
content:
"[...] functional-group or community level than at species level (medium \r confidence) (Marshall et al., 2017; Hoppe et al., 2018b; Olsen et al., \r 2018; Gissi et al., 2021). Globally, the projected reduction of biomass \r due to climate-induced drivers is relatively unaffected by fishing \r pressure, indicating additive responses of fisheries and climate change \r (low confidence) (Lotze et al., 2019). Regionally, projected interactions \r of climate-induced drivers, fisheries and other regional non-climate \r drivers can be both synergistic and antagonistic, varying across regions, \r functional groups and species, and can cause nonlinear dynamics with \r counterintuitive outcomes, underlining the importance of adaptations \r and associated trade-offs (high confidence) (Sections 3.5.3, 3.6.3.1.2, \r 4.5, 4.6; Weijerman et al., 2015; Fulton et al., 2018; Hansen et al., 2019; \r Trolle et al., 2019; Zeng et al., 2019; Holsman et al., 2020; Pethybridge \r et al., 2020; Gissi et al., 2021)."


id: 2ed3de12034e52bb3c05348e58b6419f
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 5514
content:
"Assessing ecological responses to multiple climate-induced drivers \r requires a combination of approaches, including laboratory- and \r field-based experiments, field observations (e.g., natural gradients, \r climate analogues), study of paleo-analogues and the development \r of mechanistic and empirical models (Clapham, 2019; Gissi et  al., \r 2021). Experimental studies of food-web responses are often limited \r to an individual driver, although recent manipulations have used a \r matrix of >1000-l mesocosms to explore ecological responses to both \r warming and acidification (see Box  3.1; Nagelkerken et  al., 2020). \r Hence, complementary approaches are needed to indirectly explore \r the mechanisms underlying ecosystem responses to global climate \r change (Parmesan et al., 2013). Observations from time series longer \r than modes of natural variability (i.e., decades) are essential for \r revealing and attributing ecological responses to climate change (e.g., \r [...]"


id: 8d1fd36ef8256c1b11bd072e60a18086
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 22015
content:
"[...] Section 3.4; Barton et al., 2015b; Brun et al., 2019). Also, paleorecords \r provide insights into the influence of multiple drivers on marine \r biota (Cross-Chapter Box  PALEO in Chapter  1; Reddin et  al., 2020). \r Specifically, associations between vulnerabilities and traits of marine \r ectotherms in laboratory experiments correspond with organismal \r responses to ancient hyperthermal events (medium confidence) \r (Reddin et  al., 2020). This corroboration suggests that responses to \r multiple drivers inferred from the fossil record can help provide insights \r into the future status of functional groups, and hence food webs, under \r rapid climate change."


id: ca4caec9eac26a19340cff33601f678
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 32936
content:
"Given the limitations of individual ecological models discussed above, \r model intercomparisons, such as the Fisheries and Marine Ecosystem \r Model Intercomparison Project (Fish-MIP; Tittensor et al., 2018) show \r promise in increasing the robustness of projected ecological outcomes \r (Tittensor et  al., 2018). Model ensembles include a greater number \r of relevant processes and functional groups than any single model \r and thus capture a wider range of plausible responses. Among the \r global Fish-MIP models, there is high (temperate and tropical areas) \r to medium agreement (coastal and polar regions) on the direction of \r change, but medium (temperate and tropical regions) to low agreement\r (coastal and polar regions) on magnitude of change (Lotze et al., 2019; \r Heneghan et al., 2021). Although model outputs are validated relative \r to observations to assess model skills (Payne et  al., 2016; Tittensor \r et  al., 2018), the Fish-MIP models under-represent some sources of \r [...]"


id: c89aa10cf717502697d3661f010f7d3e
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 32609
content:
"[...] uncertainty, as they often do not include parameter uncertainties and \r do not usually include impacts of ocean acidification, oxygen loss \r or evolutionary responses because there remains high uncertainty \r regarding the influences of these processes across functional groups. \r Ensemble model investigations like Fish-MIP have also identified gaps \r in our mechanistic understanding of ecosystems and their responses \r to anthropogenic forcing, leading to model improvement and more \r rigorous benchmarking. These investigations could inspire future \r targeted observational and experimental research to test the validity \r of model assumptions (Payne et al., 2016; Lotze et al., 2019; Heneghan \r et  al., 2021). The state of the art in such experimental research is \r presented in Box 3.1."


id: c567927ef770271c1f4e97069477a51e
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 32038
content:
"Multi-species and integrated end-to-end ecosystem models are \r powerful tools to explore and project outcomes to the often-interacting \r cumulative effects of climate change and other anthropogenic drivers \r (Section 3.1; Kaplan and Marshall, 2016; Koenigstein et al., 2016; Peck \r and Pinnegar, 2018; Tittensor et  al., 2018; Gissi et  al., 2021). These \r models can integrate some aspects of the knowledge accrued from \r manipulation experiments, paleo- and contemporary observations, help \r test the relative importance of specific drivers and driver combinations, \r and identify synergistic or antagonistic responses (Koenigstein et al., \r 2016; Payne et al., 2016; Skogen et al., 2018; Tittensor et al., 2018). \r As these models are associated with wide-ranging uncertainties \r (SM3.2.2; Payne et  al., 2016; Trolle et  al., 2019; Heneghan et  al., \r 2021), they cannot be expected to accurately project the trajectories \r of complex marine ecosystems under climate change; hence, they are \r [...]"


id: 9b11b0a277d05198cefd904b2bc1fa63
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 24533
content:
"The majority of the examples in Section 3.3 are from studies mimicking projected conditions in the year 2100 that report the responses \r of an individual species or strain to multiple drivers. This powerful generic experimental approach has largely been restricted to single \r species because it is logistically complex to conduct experiments that straddle multiple trophic levels, and that also include more than \r two drivers (see Figure Box 3.1.1b); the need for multiple replicates, drivers and treatment levels greatly increase the work required \r (Parmesan et al., 2013; Boyd et al., 2018). It is challenging to apply this experimental approach to communities or ecosystems (see Figure \r Box 3.1.1). To date, most research on community or ecosystem response to climate-induced drivers has been in large-volume (>10,000 l) \r mesocosms (Riebesell and Gattuso, 2014), or at natural analogues such as CO2 seeps, in which only one driver (ocean acidification) is \r [...]"


id: 25ae3efc612639bdbd8eae765907921b
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 3815
content:
"[...] altered (see (4) in Figure Box 3.1.1). Only very recently have two drivers been incorporated into climate-change manipulation studies \r examining responses of primary producers to secondary consumers (see (5) in Figure Box 3.1.1a; Nagelkerken et al., 2020). Therefore, \r 'natural experiments' from the geological past (Reddin et al., 2020) provide insights into how food webs and their constituents respond to \r complex change involving multiple drivers. Contemporary observations are occasionally long enough (>50 years) to capture community \r responses to complex climate change. For example, Brun et al. (2019) reported a shift in zooplankton community structure in the North \r Atlantic (1960-2014), with major biogeochemical ramifications."


id: 14c85de272443ec0cf6d8f6f7e0f46cf
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 882
content:
"Conducting sufficiently long manipulation experiments to study the effect of adaptation on organisms is equally difficult (see Figure \r Box 3.1.1b), with much research restricted to multi-year studies of the microevolution of fast-growing (more than one division per day) \r phytoplankton species responding to single drivers (Lohbeck et al., 2012; Schaum et al., 2016). In a few experimental evolution studies \r (see (7) in Figure Box 3.1.1a; Brennan et al., 2017), multiple drivers have been used, but none have used communities or ecosystems (see \r Figure Box 3.1.1b). Nevertheless, the fossil record provides limited evidence of adaptations to less rapid (relative to present day) climate \r change (Jackson et al., 2018). Despite the need to explore ecological or biogeochemical responses to projected future ocean conditions, \r logistical challenges require that assessments of climate-change impacts at scales larger than mesocosms use large-scale, long-term in \r [...]"


id: 2992ee885128022c9e8fe1721a775d4d
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 4541
content:
"Ocean acidification and associated declines in aragonite saturation \r state (Oaragonite) decrease rates of calcification by corals and other \r calcifying reef organisms (very high confidence), reduce coral settlement \r (medium confidence) and increase bioerosion and dissolution of reef \r substrates (high confidence) (Hoegh-Guldberg et  al., 2018a; Bindoff \r et  al., 2019a; Kline et  al., 2019; Pitts et  al., 2020). Warming can \r exacerbate the coral response to ocean acidification (Kornder et al., \r 2018) and accelerate the decrease in coral skeletal density (Guo et al., \r 2020). In addition, reefs with lower coral cover and a higher proportion \r of slow-growing species, because of bleaching, are more sensitive to \r acidification (net dissolution occurs Oaragonite  =  2.3 for 100% coral \r cover, and Oaragonite  >3.5 for 30% coral cover; Kline et  al., 2019). \r However, experimental evidence suggests that coral responses to \r [...]"


id: aca9838881621542e444347cfdb8bd12
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 27622
content:
"[...] ocean acidification are species specific (medium confidence) (Fabricius \r et al., 2011; DeCarlo et al., 2018; Comeau et al., 2019). Evidence from "


id: bb8f06b7e1c8007642d2953a186e9b47
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 30217
content:
"larval dispersal and evolutionary processes find limited ability to adapt \r this century at rates of warming at or exceeding that in RCP4.5 (high \r confidence, very likely) (Bay et  al., 2017; Kubicek et  al., 2019; Matz \r et  al., 2020; McManus et  al., 2020; Logan et  al., 2021; McManus \r et al., 2021). For example, a global analysis (Logan et al., 2021) finds \r that increased thermal tolerance via evolution or switching to more \r stress-tolerant algal symbionts enable most (73-81%) coral to survive \r through 2100 under RCP2.6, but coral-dominated communities with a \r historical mix of coral taxa still disappear (0-8% coral survival) under \r RCP6.0 in simulations with adaptive mechanisms (Figure 3.13). Due \r to the impacts of warming, and to a lesser extent ocean acidification, \r global reef carbonate production is estimated to decline 71% by \r 2050 in SSP1-2.6, and the rate of SLR is estimated to exceed that of \r reef growth for 97% of reefs assessed, without adaptation by corals \r [...]"


id: 17e59a4c020a340f99b8ba9af2ddf1c1
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 1407
content:
"[...] and their symbionts (WGI AR6 Table 9.9; Cornwall et al., 2021; Fox\u0002Kemper et al., 2021). The increased water depth due to coral loss and \r reef erosion, as well as reduced structural complexity, will limit wave \r attenuation and exacerbate the risk of flooding from SLR on reef\u0002"


id: 2a44c693bff990f5d5203176782ebee6
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 4655
content:
"In response to the global-scale decline in coral reefs and high \r future risk, recent literature focuses on finding thermal refuges and \r identifying uniquely resilient species, populations or reefs for targeted \r restoration and management (Hoegh-Guldberg et  al., 2018b). Reefs \r exposed to internal waves (Storlazzi et al., 2020), turbidity (Sully and \r van Woesik, 2020) or warm-season cloudiness (Gonzalez-Espinosa \r and Donner, 2021) are expected to be less sensitive to thermal \r stress. Mesophotic reefs (30-150 m) have also been proposed as \r thermal refugia (Bongaerts et  al., 2010), although evidence from \r recent bleaching events, subsurface temperature records and species \r overlap is mixed (Frade et al., 2018; Rocha et al., 2018b; Eakin et al., \r 2019; Venegas et al., 2019; Wyatt et al., 2020). A study of 2584 reef \r sites across the Indian and Pacific oceans estimated that 17% had \r sufficient cover of framework-building corals to warrant protection, \r [...]"


id: 3fb1d9b2a2e8d05556746c30c270b831
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 8396
content:
"[...] 54% required recovery efforts and 28% were on a path to net erosion \r (Darling et al., 2019). There is medium evidence for greater bleaching \r resistance among reefs subject to temperature variability or frequent \r heat stress (Barkley et  al., 2018; Gintert et  al., 2018; Hughes et  al., \r 2018a; Morikawa and Palumbi, 2019), but with trade-offs in terms of \r diversity and structural complexity (Donner and Carilli, 2019; Magel \r et  al., 2019). There is limited agreement about the persistence of \r thermal tolerance in response to severe heat stress (Le Nohaic et al., \r 2017; DeCarlo et al., 2019; Fordyce et al., 2019; Leggat et al., 2019; \r Schoepf et al., 2020). Recovery and restoration efforts that target heat\u0002resistant coral populations and culture heat-tolerant algal symbionts \r have the greatest potential of effectiveness under future warming \r (high confidence) (see Box 5.5 in SROCC Chapter 5; Bay et al., 2017; \r [...]"


id: 5831c0b9ea66ea88a9100b7ba99f3d2d
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 12769
content:
"[...] Darling and Cote, 2018; Baums et  al., 2019; Bindoff et  al., 2019a; \r Howells et al., 2021); however, there is low confidence that enhanced \r thermal tolerance can be sustained over time (Section  3.6.3.3.2; \r Buerger et  al., 2020). The effectiveness of active restoration and \r other specific interventions (e.g., reef shading) are further assessed in \r Section 3.6.3.3.2."


id: 5fc944f4e937f439d66a11cb5feab358
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 14153
content:
"Observations since AR5 and SROCC (Table 3.4) find increased impacts \r of ocean warming on rocky shores. This includes extirpation of species \r at the warm edge of their ranges (Yeruham et al., 2015; Martinez et al., \r 2018), extension of poleward range boundaries (Sanford et al., 2019), \r mortality from climate extremes (Seuront et  al., 2019), reduction in \r survival at shallower depths (Sorte et al., 2019; Wallingford and Sorte, \r 2019) and reorganisation of communities (Wilson et al., 2019; Mulders \r and Wernberg, 2020; Albano et al., 2021). Data collected after MHWs \r find ecological phase shifts (moderate evidence, high agreement) \r (e.g., California; Rogers-Bennett and Catton, 2019; McPherson et al., \r 2021) and homogenisation of communities (limited evidence) (e.g., \r Alaska; Weitzman et al., 2021). For example, the collapse of sea star \r populations in the Northeast Pacific due to a MHW-related disease \r outbreak (Hewson et al., 2014; Menge et al., 2016; Miner et al., 2018; \r [...]"


id: 6dd2fde46f322ff0ae1c592be8f45f97
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 16585
content:
"[...] Schiebelhut et  al., 2018), including 80-100% loss of the common \r predatory sunflower star, Pycnopodia helianthoides (very high \r confidence) (Harvell et al., 2019), triggered shifts from kelp- to urchin\u0002dominated ecosystems (Schultz et  al., 2016; Gravem and Morgan, \r 2017; McPherson et al., 2021)."


id: 87584c60fb0f38732dbbc347a00f9b48
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 20973
content:
"Multiple lines of evidence find that foundational calcifying organisms \r such as mussels are at high risk of decline due to both the individual \r and synergistic effects of warming, acidification and hypoxia (high \r confidence) (Sunday et al., 2016; Sorte et al., 2017; Sorte et al., 2019; \r Newcomb et  al., 2020). Warmer temperatures reduce mussel and \r barnacle recruitment (e.g., northwest Atlantic; Petraitis and Dudgeon, \r 2020) and the upper vertical limit of mussels (e.g., northeast Pacific, \r Harley, 2011; and southwest Pacific, Sorte et al., 2019). Experiments \r show that ocean acidification negatively impacts mussel physiology \r (very high confidence), with evidence of reduced growth (Gazeau \r et  al., 2010), attachment (Newcomb et  al., 2020), biomineralisation \r (Fitzer et  al., 2014) and shell thickness (Pfister et  al., 2016; McCoy \r et  al., 2018). Net calcification and abundance of mussels and other \r [...]"


id: 9cfb40c7411f82883ee5442e0eab60fb
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
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content:
"[...] foundational species, including oysters, are expected to decline due to \r ocean acidification (very high confidence) (Kwiatkowski et al., 2016; \r Sunday et al., 2016; McCoy et al., 2018; Meng et al., 2018), causing \r the reorganisation of communities (high confidence) (Kroeker et al., \r 2013b; Linares et al., 2015; Brown et al., 2016; Sunday et al., 2016; \r Agostini et al., 2018; Teixido et al., 2018). Experiments indicate that \r acidification can interact with warming and hypoxia to increase the "


id: b55e96cf96e727284400f091907d7002
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 29142
content:
"Figure  3.13 |   Coral reef futures, with and without adaptation. Graphs are based on a model of coral-symbiont evolutionary dynamics from Logan et  al. (2021), \r which simulates two coral types and symbiont populations for 1925 reef cells worldwide, from 1950 to 2100 drawn from simulations with National Oceanic and Atmospheric \r Administration-Geophysical Fluid Dynamics Laboratory Earth System Model (ESM2M) under four RCPs. Top panels show the simulated fraction of cells with healthy reefs, when \r both coral types are not in a state of severe bleaching or mortality, (i) without adaptive responses and (ii) with adaptive responses (symbiont evolution). Colours indicate maximum \r monthly sea surface temperature increase across all reef cells, versus a 1861-2010 baseline. Panels (a,b,c) depict snapshots of coral reef conditions at time points in the future, \r [...]"


id: 9b972e5960dab51ba55d0d91c25e939e
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 24627
content:
"[...] each with different levels of warming, drawn from the model-projected cover of the two coral types and from a literature assessment (Section 3.4.2.1; Hughes et al., 2018b; Bindoff \r et al., 2019a; Darling et al., 2019; Leggat et al., 2019; Cornwall et al., 2021)."


id: 22c8ceb8bdc5b436de9fd99e307fcf1c
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 3330
content:
"Recent research (Straub et al., 2019; Butler et al., 2020; Filbee-Dexter \r et  al., 2020b; Tait et  al., 2021) supports the findings of previous \r assessments (Table 3.5) that kelp and other seaweeds in most regions \r are undergoing mass mortalities from high temperature extremes \r and range shifts from warming (very high confidence). Kelp are \r highly sensitive to the direct effect of high temperature on survival \r (Nepper-Davidsen et  al., 2019) and indirect impact of temperature \r on herbivorous species (Ling, 2008; Verges et  al., 2016), upwelling \r and nutrient availability (Carr and Reed, 2015; Schiel and Foster, \r 2015). Synergies between warming, storms, pollution and intensified \r herbivory (due to removal or loss of predators including sea stars and \r otters that constrain herbivory by fish and urchin populations) can \r also cause physiological stress and physical damage in kelp, reducing \r productivity and reproduction (Rogers-Bennett and Catton, 2019; \r [...]"


id: aef7790d55311c25b85b453096f53ba6
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 28028
content:
"While reducing non-climate drivers can help prevent kelp loss from \r warming and MHWs, there is limited potential for restoration of kelp \r ecosystems after transition to urchin-dominant ecosystems (high \r confidence). Current restoration efforts are generally small scale \r (<0.1 km2\r ) and less advanced than those in ecosystems like coral \r reefs (Coleman et al., 2020b; Eger et al., 2020; Layton et al., 2020). \r Although abundance of herbivores limits kelp populations, there is \r limited evidence that restoring predators of herbivores by creating \r marine reserves, or directly removing grazing species, will increase \r kelp forest resilience to warming and extremes (Verges et al., 2019; \r Wernberg et  al., 2019). Active reseeding of wild kelp populations \r through transplantation and propagation of warm-tolerant genotypes \r (Coleman et  al., 2020b; Alsuwaiyan et  al., 2021) can overcome low \r dispersal rates of many kelp species and facilitate effective restoration \r [...]"


id: f6a3bd6ef03443aa73785950e0f0433e
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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vector_id: 40764
content:
"Estuaries, deltas and lagoons encounter environmental gradients over \r small spatial scales, generating diverse habitats that support myriad \r ecosystem services, including food provision, regulation of erosion, \r nutrient recycling, carbon sequestration, recreation and tourism, \r and cultural significance (D'Alelio et  al., 2021; Keyes et  al., 2021). \r Although these coastal ecosystems have historically been sensitive to \r erosion-accretion cycles driven by sea level, drought and storms (high \r confidence) (Peteet et al., 2018; Wang et al., 2018c; Jones et al., 2019b; \r Urrego et  al., 2019; Hapsari et  al., 2020; Zhao et  al., 2020b), they \r were impacted for much of the 20th century primarily by non-climate \r drivers (very high confidence) (Brown et  al., 2018b; Ducrotoy et  al., \r 2019; Elliott et al., 2019; He and Silliman, 2019; Andersen et al., 2020; \r Newton et  al., 2020; Stein et  al., 2020). Nevertheless, the influence \r [...]"


id: ec65599976f039b240abc683df2f14a
created_at: 2023-04-19 13:22:52
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vector_id: 38949
content:
"[...] of climate-induced drivers has become more apparent over recent \r decades (medium confidence) (Table 3.6)."


id: d99a25d805d4f26c39cc037019929507
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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vector_id: 35584
content:
"Acidification of estuarine water is a growing hazard (medium confidence) \r (Doney et al., 2020; Scanes et al., 2020a; Cai et al., 2021), and resident \r organisms display sensitivity to altered pH in laboratory settings \r (medium confidence) (Young et  al., 2019a; Morrell and Gobler, 2020; \r Pardo and Costa, 2021). However, attribution of the biological effects \r of acidification is difficult because many biogeochemical processes \r affect estuarine carbon chemistry (Sections 3.2.3.1, 3.3.2). Warming can \r exacerbate the impacts of both acidification and hypoxia on estuarine \r organisms (Baumann and Smith, 2018; Collins et al., 2019b; Ni et al., \r 2020). These effects are further complicated by eutrophication, with high \r nitrogen loads associated with lower pH (Rheuban et al., 2019). Warming \r (including MHWs) and eutrophication interact to decrease estuarine \r oxygen content and pH, increasing the vulnerability of animals to MHWs \r [...]"


id: 73088baa5a2f552e78d2c6c11b9097fa
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index: climate_gpt_v2
vector_id: 17490
content:
"[...] (Brauko et al., 2020) and exacerbating the incidence and impact of dead \r zones (medium confidence) (Altieri and Gedan, 2015). The impacts of \r storms on estuaries are variable and are described in SM3.3.1."


id: abdf3dbf554407f6b7092e92f65e8128
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 27479
content:
"All these impacts are projected to escalate under future climate \r change, but their magnitude depends on the amount of warming, \r the socioeconomic development pathway and implementation of \r adaptation strategies (medium confidence). Modelling studies (Lopes \r et al., 2019; Rodrigues et al., 2019; White et al., 2019; Zhang and Li, \r 2019; Hong et al., 2020; Krvavica and Ruzic, 2020; Liu et al., 2020e; \r Shalby et  al., 2020) suggest that responses of estuaries to SLR will \r be complex and context dependent (Khojasteh et  al., 2021), but \r project that salinity, tidal range, storm-surge amplitude, depth and \r stratification will increase with SLR (medium confidence), and that \r marine-dominated waters will penetrate farther upstream (high \r confidence). Without careful management of freshwater inputs, \r sediment augmentation and/or the restoration of shorelines to more \r natural states, transformation and loss of intertidal areas and wetland \r [...]"


id: ff1ea776c84c3f77d2acf9dd23bc28a0
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content:
"[...] vegetation will increase with SLR (high confidence) (Doughty et  al., \r 2019; Leuven et al., 2019; Yu et al., 2019; Raw et al., 2020; Shih, 2020; \r Stein et al., 2020), with small, shallow microtidal estuaries being more \r vulnerable to impacts than deeper estuaries with well-developed \r sediments (medium confidence) (Leuven et al., 2019; Williamson and \r Guinder, 2021). Warming and MHWs will enhance stratification and \r deoxygenation in shallow lagoons (medium confidence) (Derolez et al., \r 2020) and will continue to drive range shifts among estuarine biota "


id: af9bd7e538f55f79ece43f7d2374e25e
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 28132
content:
"Relative SLR extends the upstream limit of saline waters (high confidence) \r (Harvey et  al., 2020; Jiang et  al., 2020) and alters tidal ranges (high \r confidence) (Idier et al., 2019; Talke et al., 2020). Elevated water levels \r also alter submergence patterns for intertidal habitat (high confidence) \r (Andres et al., 2019), moving high-water levels inland (high confidence) \r (Peteet et al., 2018; Appeaning Addo et al., 2020; Liu et al., 2020e) and \r increasing the salinity of coastal water tables and soils (high confidence) \r (Eswar et  al., 2021). These processes favour inland and/or upstream \r migration of intertidal habitat, where it is unconstrained by infrastructure, \r topography or other environmental features (high confidence) (Kirwan \r and Gedan, 2019; Parker and Boyer, 2019; Langston et al., 2020; Magolan \r and Halls, 2020; Saintilan et al., 2020). The spread of 'ghost forests' along \r the North American east coast (Kirwan and Gedan, 2019) and elsewhere \r [...]"


id: e01a4f1d5945346b943bc8a4c9384ef1
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 36675
content:
"[...] (Grieger et  al., 2020) illustrates this phenomenon. Along estuarine \r shorelines, changing submergence patterns and upstream penetration \r of saline waters interact synergistically to stress intertidal plants, \r changing species composition and reducing above-ground biomass, \r in some cases favouring invasive species (Xue et al., 2018; Buffington \r et al., 2020; Gallego-Tevar et al., 2020). Overall, changing salinity and \r submergence patterns decrease the ability of shoreline vegetation to \r trap sediment (Xue et al., 2018), reducing accretion rates and increasing "


id: d03131d834a0e2984858128036f6a0aa
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 33989
content:
"As noted in SROCC, given the diversity of coastal wetlands as well \r as the dependence of their future vulnerability to climate change on \r adaptation pathways (Krauss, 2021; Rogers, 2021), projections of \r future impacts based on shoreline elevation estimated from satellite \r data and CMIP5 projections (Spencer et  al., 2016; Schuerch et  al., \r 2018) vary greatly. Although all approaches have individual strengths \r and weaknesses (Tornqvist et al., 2021), paleorecords provide some \r clarity because they yield estimates of wetland responses to changes in \r climate in the absence of other anthropogenic drivers and are therefore \r inherently conservative. On the basis of paleorecords (Table 3.8), we \r assess that mangroves and salt marshes are likely at high risk from \r future SLR, even under SSP1-1.9, with impacts manifesting in the mid\u0002term (medium confidence). Under SSP5-8.5, wetlands are very likely\r at high risk from SLR, with larger impacts manifesting before 2040 \r [...]"


id: 3dc67bef52cecfedc2c802187f0b11a5
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index: climate_gpt_v2
vector_id: 8033
content:
"[...] (medium confidence). By 2100, these ecosystems are at high risk of \r impacts under all scenarios except SSP1-1.9 (high confidence), with \r impacts most severe along coastlines with gently sloping shorelines, \r limited sediment inputs, small tidal ranges and limited space for inland \r migration (very high confidence) (Cross-Chapter Box SLR in Chapter 3; \r Schuerch et al., 2018; FitzGerald and Hughes, 2019; Leo et al., 2019; \r Schuerch et al., 2019; Raw et al., 2020; Saintilan et al., 2020)."


id: 9b50d4b7022d6bd8973a86742a3842cc
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vector_id: 24574
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"species to expand their ranges poleward (high confidence) (Friess \r et  al., 2019; Whitt et  al., 2020). This expansion can affect species \r interactions (Guo et  al., 2017; Friess et  al., 2019), and enhance \r sediment accretion and carbon storage rates in some instances \r (medium confidence) (Guo et al., 2017; Kelleway et al., 2017; Chen \r et al., 2018b; Coldren et al., 2019; Raw et al., 2019). Drought, low sea \r levels and MHWs can cause significant die-offs among mangroves \r (medium confidence) (Lovelock et  al., 2017b; Duke et  al., 2021). \r Seagrasses are similarly vulnerable to warming (high confidence) \r (Repolho et al., 2017; Duarte et al., 2018; Jayathilake and Costello, \r 2018; Savva et al., 2018), which has been attributed as one cause of \r observed changes in distribution and community structure (medium \r confidence) (Hyndes et  al., 2016; Nowicki et  al., 2017). MHWs, \r together with storm-driven turbidity and structural damage, can \r [...]"


id: 7f0ce9138df04c77dbae21fd2c527fdd
created_at: 2023-04-19 13:22:52
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content:
"[...] cause seagrass die-offs (high confidence) (Arias-Ortiz et  al., 2018; \r Kendrick et al., 2019; Smale et al., 2019; Strydom et al., 2020), shifts \r to small, fast-growing species (high confidence) (Kendrick et  al., \r 2019; Shields et  al., 2019; Strydom et  al., 2020) and ecosystem \r collapse (Serrano et al., 2021)."


id: a6065be5fd233b44b9ad6055808a8304
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 26433
content:
"The sensitivity of salt marshes and mangroves to RSLR depends on \r whether they accrete inorganic sediment and/or organic material at \r rates equivalent to rising water levels (very high confidence) (Peteet \r et al., 2018; FitzGerald and Hughes, 2019; Friess et al., 2019; Gonneea \r et  al., 2019; Leo et  al., 2019; Marx et  al., 2020; Saintilan et  al., \r 2020). Otherwise, wetland ecosystems must migrate either inland or \r upstream, or face gradual submergence in deeper, increasingly saline \r water (very high confidence) (Section  3.4.2.4; Andres et  al., 2019; \r Jones et  al., 2019b; Cohen et  al., 2020; Mafi-Gholami et  al., 2020; \r Magolan and Halls, 2020; Sklar et al., 2021). Ability to migrate depends \r on local topography, the positioning of anthropogenic infrastructure \r and structures placed to defend such infrastructure (Schuerch et al., \r 2018; Fagherazzi et  al., 2020; Cahoon et  al., 2021). Submergence \r [...]"


id: 23e04b04751af35a71600dac22544109
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 3499
content:
"[...] drives changes in community structure (high confidence) (Jones et al., \r 2019b; Yu et al., 2019; Douglass et al., 2020; Langston et al., 2020) \r and functioning (high confidence) (Charles et  al., 2019; Buffington \r et al., 2020; Stein et al., 2020), and will eventually lead to extirpation \r of the most sensitive vegetation (medium confidence) (Schepers et al., \r 2017; Scalpone et al., 2020) and associated animals (low confidence) \r (Rosencranz et  al., 2018). The impacts of storms on wetlands are \r variable and described in SM3.3.1."


id: 9c217d399090dd22584a9e590aa1192b
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
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content:
"et al., 2017b; Mori et al., 2018; Ritphring et al., 2018; Hallin et al., \r 2019; Kasmi et  al., 2020). Within regions, projected impacts scale \r negatively with beach width and positively with the magnitude of \r projected SLR. None of these local studies, however, considered \r high-energy storm events, which are known to also impact sandy \r coasts (high confidence) (e.g., Burvingt et  al., 2018; Garrote et  al., \r 2018; Duvat et al., 2019; Sharples et al., 2020), and model structure \r often had more influence on projected shoreline responses than did \r physical drivers (Le  Cozannet et  al., 2019). Nevertheless, the most\u0002advanced available models, which incorporate multiple coastal \r processes, including SLR, project that without anthropogenic barriers \r to erosion, 13.6-15.2% and 35.7-49.5% of the world's beaches likely\r risk undergoing at least 100 m of shoreline retreat (relative to 2010) \r by 2050 and 2100, respectively (low confidence) (Vousdoukas et al., \r [...]"


id: db8316632e9a65e343ee66586a9194e
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 35899
content:
"[...] 2020b). Aggregating these trends regionally suggests that relative \r rates of shoreline change under RCP4.5 and RCP8.5 diverge strongly \r after mid-century, with trends towards erosion escalating under \r RCP8.5 by 2100 (medium confidence) (Figure 3.14; Vousdoukas et al., \r 2020b). This trend supports the WGI AR6 assessment that projected \r SLR will contribute to erosion of sandy beaches, especially under high\u0002"


id: 92aaf1b6432573d77843a52ca9eb5b18
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 23022
content:
"For beach fauna, emerging evidence links range shifts, increasing \r representation by warm-affinity species and mass mortalities to ocean \r warming (limited evidence, high agreement) (McLachlan and Defeo, \r 2018; Martin et  al., 2019). But even amongst the best-studied taxa, \r such as turtles, vulnerability to warming (high confidence) and SLR \r (medium confidence) anticipated on the basis of theory (Poloczanska \r et al., 2009; Saba et al., 2012; Pike, 2013; Laloe et al., 2017; Tilley et al., \r 2019) yields only a few detected impacts in the field associated mainly \r with feminisation (female-skewed sex ratios driven by warmer nest \r temperatures) (Jensen et al., 2018; Colman et al., 2019; Tilley et al., 2019), \r phenology (Monsinjon et al., 2019), reproductive success (Bladow and \r Milton, 2019) and inter-nesting period (Valverde-Cantillo et al., 2019). \r Moreover, although established vulnerabilities imply high projected \r [...]"


id: 33e767d9162dd8ff20400e2977cefc5f
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 6373
content:
"[...] future risk for turtles (high confidence) (e.g., Almpanidou et al., 2019; \r Monsinjon et al., 2019; Patricio et al., 2019; Varela et al., 2019; Santidrian \r Tomillo et  al., 2020), many populations remain resilient to change \r (Fuentes et al., 2019; Valverde-Cantillo et al., 2019; Laloe et al., 2020; "


id: bcf7eea74ba724030d50aaf139c18430
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 30487
content:
"Lamont et al., 2020), perhaps because variation in sand temperatures \r at nesting depth among beaches very likely exceeds the magnitude of \r warming anticipated by 2100, even under RCP8.5 (medium confidence) \r (Bentley et al., 2020a). As expected for a taxon with a long evolutionary \r history, turtles display natural adaptation, not only by virtue of broad \r geographic distributions that include natural climate-change refugia \r (Boissin et al., 2019; Jensen et al., 2019), but also because some initial \r responses to warming might counteract anticipated impacts. For \r example, although feminisation poses a significant long-term risk to \r turtle populations (high confidence), it might contribute to population \r growth in the near to mid-term (medium confidence) (Patricio et  al., \r 2019). Resilience to climate change might be further enhanced by range \r extensions, alterations in nesting phenology and fine-scale nest-site \r [...]"


id: 979e0d7126ccb926dd1f4848d746bd73
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 23892
content:
"[...] selection (medium confidence) (Abella Perez et al., 2016; Santos et al., \r 2017; Almpanidou et al., 2018; Rivas et al., 2019; Laloe et al., 2020)."


id: 1769b7509cddc48d43a2abd0043a3a6e
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 1339
content:
"Since AR5, there is evidence for increasing frequency and duration of \r MHWs, extreme-weather events and a diversity of threats across depth \r strata causing mass-mortality events, local extirpations and coral reef \r decline (high confidence) (Section 3.4.2.1; SM3.3.2; Buchanan et al., \r 2016a; Shlesinger et al., 2018; Wabnitz et al., 2018b; Garrabou et al., \r 2019). In most SES, non-climate drivers, including pollution, habitat \r destruction and especially overfishing, are decreasing the local \r adaptive capacity of organisms and the ability of ecosystems to cope \r with climate-change impacts (high confidence) (Cramer et al., 2018; \r Hidalgo et  al., 2018; Ben-Hasan and Christensen, 2019). The SLR is \r accelerating faster than expected (high confidence) (Kulp and Strauss, \r 2019), posing a key risk to SES' coastal ecosystems and the services \r they provide in urban areas, including drinking water provision, \r housing and recreational activities, among others (Herivaux et  al., \r [...]"


id: ac2ecbe51ebc729e5aeb3d007cb4f2e4
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 27540
content:
"In the Mediterranean Sea (Cross-Chapter  Paper  4), the increase in \r climate extremes and mass-mortality events reported in AR5 has \r continued (very high confidence) (Gomez-Gras et al., 2021). Extreme\u0002weather events (including deep convection; Gonzalez-Aleman et al., \r 2019) and MHWs have become more frequent (Darmaraki et al., 2019) \r and are associated with mass mortality of benthic sessile species \r across the basin (high confidence) (Garrabou et  al., 2019; Gomez\u0002Gras et al., 2021). Since AR5, in the Persian Gulf and Red Sea, extreme \r temperatures, together with disease and predation, have continued \r to cause bleaching-induced mortality of corals, along with declines \r in the average coral-colony size (high confidence) (Burt et al., 2019). \r Poleward migration and tropicalisation of species (Section 3.4.2.3) has \r also continued in the Mediterranean, and these phenomena have also \r become an issue in the Black Sea (high confidence) (Boltachev and \r [...]"


id: d33abb432c67eed4dc384a6c14da3c08
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 34507
content:
"[...] Karpova, 2014; Hidalgo et al., 2018). Climate impacts on phytoplankton \r production and phenology show high spatial heterogeneity across the \r Mediterranean Sea (medium evidence) (Marba et al., 2015b; Salgado\u0002Hernanz et  al., 2019), with consequent effects on the diversity and \r abundance of zooplankton and fish species (medium confidence) \r (Peristeraki et al., 2019). Changes in primary production and a decrease \r in river runoff have also altered the optimum habitats for small \r pelagic fish in the Mediterranean, from the local to the basin scale \r (Piroddi et al., 2017). Evidence of impacts from ocean acidification is \r increasing, with the rates of coral calcification showing major decline \r in the Red Sea (medium confidence) (Section  3.4.2.1; Steiner et  al., \r 2018; Bindoff et  al., 2019a). In the Mediterranean Sea, evidence of \r acidification events have been reported at the local scale (Hassoun \r et  al., 2015), with impacts on bivalves and coralligenous species \r [...]"


id: 28effd5d0ea59be8b8fad47af4800b42
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 4419
content:
"Similar to other coastal ecosystems, evidence since SROCC (Table 3.11) \r suggests that shelf-sea ecosystems and the fisheries and aquaculture \r they support are sensitive to the interactive effects of climate-induced \r drivers, as well as non-climate drivers, including nutrient pollution, \r sedimentation, fishing pressure and resource extraction (Table  3.12; \r Figure  3.12). Changes in freshwater, nutrient and sediment inputs \r from rivers due to both climate-induced and non-climate drivers can \r influence productivity and nutrient limitation, ecosystem structure, \r carbon export and species diversity and abundance (Balch et  al., \r 2012; Picado et  al., 2014), and can result in reduced water clarity \r and light penetration (Dupont and Aksnes, 2013; McGovern et  al., \r 2019). Seasonal bottom-water hypoxia occurs in some shelf seas (e.g., \r northern Gulf of Mexico, Bohai Sea, East China Sea) due to riverine \r inputs of freshwater and nutrients, promoting stratification, enhanced \r [...]"


id: 204c5cf6cb610d00f177f5dda3c39d9e
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 2899
content:
"[...] primary production and organic carbon export to bottom waters (high \r confidence) (Zhao et al., 2017; Wei et al., 2019; Del Giudice et al., 2020; \r Grosse et al., 2020; Jarvis et al., 2020; Rabalais and Baustian, 2020; \r Song et al., 2020a; Xiong et al., 2020; Zhang et al., 2020a)."


id: 49c874bcdc14bbfde678a03e9b47a304
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 10214
content:
"Ocean warming has shifted distributions of fish (Free et  al., 2019; \r Franco et  al., 2020; Pinsky et  al., 2020b; Fredston et  al., 2021) and \r marine mammal species (Salvadeo et al., 2010; Garcia-Aguilar et al., \r 2018; Davis et al., 2020) poleward (high confidence) or deeper (low \r to medium confidence) (Section 3.4.3.1; Nye et al., 2009; Pinsky et al., \r 2013; Pinsky et al., 2020b). Warming has also tropicalised the pelagic \r and demersal fish assemblages of mid- and high-latitude shelves \r (high confidence) (Montero-Serra et  al., 2015; Liang et  al., 2018; \r Maharaj et al., 2018; Ma et al., 2019; Friedland et al., 2020a; Kakehi \r et al., 2021; Punzon et al., 2021). Fisheries catch composition in many \r shelf-sea ecosystems has become increasingly dominated by warm\u0002water species since the 1970s (high confidence) (Cheung et al., 2013; \r Leitao et al., 2018; Maharaj et al., 2018; McLean et al., 2019). Warming \r has taxonomically diversified fish communities along a latitudinal \r [...]"


id: 769142da4ff7583cbb15880022746087
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 18077
content:
"[...] gradient in the North Sea but has homogenised functional diversity \r (McLean et al., 2019). However, in some regions, changing predator \r or prey distributions, temperature-dependent hypoxia, population \r changes, evolutionary adaptation and other biotic or abiotic processes, \r including species' exploitation, confound responses to climate-induced \r drivers, which must therefore be interpreted with caution (Frank et al., \r 2018). For example, although, most species' range edges are tracking \r temperature change on the northeast shelf of the USA (medium \r confidence) (Fredston-Hermann et  al., 2020; Fredston et  al., 2021), \r range edges of others are not."


id: 1f6509011afcb79186c6963c8733347e
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 2726
content:
"Since SROCC, changes in the community structure and diversity of \r plankton, macrofauna and infauna have been detected in some shelf \r seas, although attribution has been regionally specific (e.g., bottom\u0002water warming or hypoxia) (Meyer and Kroncke, 2019; Rabalais and \r Baustian, 2020). Detection of the picoplankton Synechococcus spp. in \r the North Sea is potentially linked to a summer decrease in copepod \r stocks and declining food-web efficiency (low confidence) (Schmidt \r et al., 2020). The seasonally distinct phytoplankton assemblages in the \r North Sea have begun to appear concurrently and homogenise (Nohe \r et al., 2020). Changes in abundance, species composition and size of \r zooplankton have been detected in some shelf seas (Yellow Sea, North \r Sea, Celtic Sea and Tasman Sea), including a decline in stocks of larger \r copepods, increased abundances of gelatinous and meroplankton, and \r a shift to smaller species due to warming, increased river discharge, \r [...]"


id: 86ee6c33956baf2bf27c210f7e9897ec
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 20905
content:
"[...] circulation change and/or extreme events (high confidence) (Wang \r et al., 2018a; Bedford et al., 2020; Evans et al., 2020; Shi et al., 2020; \r Edwards et al., 2021)."


id: cf02b98f1917c30fc79ab430bb5878de
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 33763
content:
"Since AR5, increasing spatio-temporal extent of hypoxia has been \r projected due to enhanced benthic respiration and reduced oxygen \r solubility from warming (Del Giudice et  al., 2020). Similar to the \r open ocean, large shifts in the phenology of phytoplankton blooms \r have been projected for shelf seas throughout subpolar and polar \r waters (medium confidence) (Henson et al., 2018a; Asch et al., 2019). \r Zooplankton, which are important prey for many fish species and sea \r birds, are expected to decrease in abundance on the northeast shelf \r of the USA (Grieve et  al., 2017); however, responses vary by shelf \r ecosystem (Chust et  al., 2014b). Trends towards tropicalisation will \r continue in the future (high confidence) (Cheung et al., 2015; Stortini \r et al., 2015; Allyn et al., 2020; Maltby et al., 2020; Costa et al., 2021), \r but uncertainty of future projections of fisheries production increases \r [...]"


id: cd67b56354b88e4752159857c36734b7
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 33475
content:
"[...] substantially beyond 2040 (Maltby et al., 2020). Nevertheless, shelf\u0002sea fisheries at lower latitudes are most vulnerable to climate change \r (Monnereau et  al., 2017). Under future climate change marked by \r more frequent and intense extreme events and the influences of \r multiple drivers, more flexible and adaptive management approaches \r could reduce climate impacts on species while also supporting industry \r adaptation (high confidence) (Section 3.6.3.1.2; Shackell et al., 2014; \r Stortini et al., 2015; Hare et al., 2016; Stortini et al., 2017; Greenan \r et al., 2019; Ocana et al., 2019; Maltby et al., 2020)."


id: 6bd9a19ecc3965518aa60e3a85f7e777
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 16275
content:
"Major community shifts, both gradual and abrupt, are observed in polar \r oceans in response to warming trends and MHWs (Arctic only) (high \r confidence) (Figure 3.12; Cross-Chapter Paper 6; Beaugrand et al., 2019; \r Meredith et al., 2019; Huntington et al., 2020). In general, abundances \r and ranges of Arctic fish species are declining and contracting, while \r ranges of boreal fish species are expanding, both geographically and \r in terms of feeding interactions and ecological roles (high confidence) \r (Huserbraten et al., 2019; Meredith et al., 2019; Huntington et al., 2020; \r Pecuchet et al., 2020a), with variable outcomes for large commercial \r fish stocks (Cross-Chapter Paper 6; Kjesbu et al., 2014; Holsman et al., \r 2018; Free et al., 2019). The extreme seasonal solar radiation cycles of \r these high latitudes may both act as a barrier for species immigration \r and change predator-prey dynamics in previously ice-covered areas, \r [...]"


id: 4167c7c78c5503fc0f28a5fb643b1500
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 8696
content:
"[...] factors not currently considered in projections (limited evidence) \r (Kaartvedt and Titelman, 2018; Ljungstrom et al., 2021). Responses by \r marine mammals and birds to the ongoing changes in polar ecosystems \r are both positive and negative (Meredith et al., 2019; Bestley et al., \r 2020). Phenological, behavioural, physiological and distributional \r changes are observed in marine mammals and birds in response to \r altered ecological interactions and habitat degradation, especially to \r loss of sea ice (high confidence) (see Box  3.2; Cross-Chapter  Paper \r 6; Beltran et  al., 2019; Cusset et  al., 2019; Descamps et  al., 2019; \r Meredith et al., 2019; Huntington et al., 2020). Reproductive failures \r and declining abundances attributed to warmer polar oceans and \r less sea ice cover are observed in populations of polar bears, Ursus \r maritimus, seals, whales and marine birds (high confidence) (see \r Box  3.2; Duffy-Anderson et  al., 2019; Ropert-Coudert et  al., 2019; \r [...]"


id: 9d7b55ffc68d775e836fd7f97311a5aa
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 24945
content:
"[...] Bestley et al., 2020; Chambault et al., 2020; Molnar et al., 2020; Stenson \r et al., 2020). The ongoing changes in polar marine ecosystems can lead \r to temporary increases in biodiversity and functional diversity (e.g., \r due to immigration of boreal species in the Arctic, high confidence), \r but reduced trophic-transfer efficiencies and functional redundancy, \r with uncertain consequences for ecosystem resilience and vulnerability \r (limited evidence, low agreement) (Griffith et al., 2019b; Alabia et al., \r 2020; du Pontavice et al., 2020; Alabia et al., 2021; Frainer et al., 2021).\r Calcareous polar organisms are among the groups most sensitive \r to ocean acidification (high confidence) (Section  3.3.2). Niemi et  al. \r (2021) reports that >80% of sampled sea snail, Limacina helicina, a key \r species in pelagic food webs, displayed signs of shell dissolution in the \r Amundsen Gulf. However, bacteria, phytoplankton, zooplankton and \r [...]"


id: 1da5bbdccf96c2933beea6db7c02c199
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 2401
content:
"[...] benthic communities are found to be detrimentally impacted, resilient \r or even positively influenced by ocean acidification in observational "


id: 987ed6238137a3d2e240d13342409871
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 24039
content:
"The polar seas cover ~20% of the global ocean and include the deep \r Arctic Ocean and surrounding shelf seas as well as the Southern \r Ocean south of the polar front. They play a significant role in ocean \r circulation and absorption of anthropogenic CO2 (Meredith et  al., \r 2019). The Arctic is characterised by polar seas surrounded by land, \r while the Antarctic comprises continental Antarctica surrounded \r by the Southern Ocean. These high-latitude ecosystems share key \r properties, including strong seasonality in solar radiation and sea \r ice coverage. Sea ice regulates water-column physics, chemistry and \r biology, air-sea exchange and is a critical habitat for many species. \r In spring, when solar radiation returns and sea ice melts, intense \r phytoplankton blooms fuel food webs that include rich communities \r of both resident and summer-migrant species, with typically high \r dependency on a few key species for trophic transfer (Meredith et al., \r [...]"


id: d0a0a02e045d3bb978a76ac889b3f8a
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 34054
content:
"[...] 2019; Rogers et al., 2020). Over the past two decades, Arctic Ocean \r surface temperature has increased in line with the global average, \r while there has been no uniform warming across the Antarctic (high \r confidence) (WGI AR6 Chapter 9; Fox-Kemper et al., 2021). Thus, the \r rate of change due to warming, and associated sea ice loss, is greater \r in the Arctic than in the Antarctic (high confidence) (Section  3.2; \r Table  3.14; WGI AR6 Chapter  9; Fox-Kemper et  al., 2021). Both \r Arctic and Antarctic regions have a long history of living resource \r extraction, including some of the largest fisheries on the globe in \r terms of catches. However, only the Arctic hosts human populations, \r holding a rich Indigenous knowledge and local knowledge (IKLK) on \r these social-ecological systems (Cross-Chapter  Paper 6; Meredith \r et al., 2019)."


id: 354c632d770657c7dd25241716741bda
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 6624
content:
"declining) in productivity for key ecological and commercial species, \r and functional groups, with weak to strong dependence on emission \r scenarios, indicating low confidence in future outcomes for polar \r marine ecosystems and associated ecosystem services (Section  3.5; \r Pinones and Fedorov, 2016; Griffiths et  al., 2017; Klein et  al., 2018; \r Hansen et al., 2019; Meredith et al., 2019; Steiner et al., 2019; Tai et al., \r 2019; Alabia et  al., 2020; Holsman et  al., 2020; Reum et  al., 2020; \r Veytia et  al., 2020; Sando et  al., 2021). Potentially highly influential \r tipping points associated with Arctic sea ice melt and Antarctic ocean \r circulation change adds to this uncertainty (Cross-Chapter  Paper 6; \r Heinze et  al., 2021). Nevertheless, increasing evidence supports that \r sustainable and adaptive ecosystem-based fisheries practices can \r reduce detrimental impacts of climate change on harvested populations \r [...]"


id: 6463f06538e3417c2313b473a4446240
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 14939
content:
"[...] (medium confidence) (Section 3.6.3.1.2; Klein et al., 2018; Free et al., \r 2019; Hansen et al., 2019; Holsman et al., 2020)."


id: 1c414b26d70976dc4fa58818fa72ef5d
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vector_id: 2166
content:
"and experimental studies (Section 3.3; Hildebrandt et al., 2016; Thor \r et al., 2018; Ericson et al., 2019; McLaskey et al., 2019; Meredith et al., \r 2019; Petrou et  al., 2019; Renaud et  al., 2019; Brown et  al., 2020; \r Hancock et  al., 2020; Henley et  al., 2020; Johnson and Hofmann, \r 2020; Torstensson et  al., 2021). While fish larval stages may be \r sensitive, adult fish are expected to have low vulnerability to projected \r acidification levels (Section  3.3.3; Hancock et  al., 2020), although \r reduced swimming capacity in polar cod in an ocean acidification \r experiment has been observed (Kunz et  al., 2018). Polar organisms' \r sensitivity to ocean acidification may increase with increasing light \r levels due to the loss of sea ice (algae; Donahue et al., 2019; Kvernvik \r et  al., 2020), temperature stress (pteropods; Johnson and Hofmann, \r 2020) or indirectly via increased heterotrophic bacterial productivity \r [...]"


id: ea7840868fcb0d5a61ed225e988ec53b
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 38616
content:
"[...] (limited evidence) (Vaque et  al., 2019). Due to limited mechanistic \r understanding of observed effects, and mixed responses among Arctic \r species, future impacts of ocean acidification are assigned medium \r confidence for polar species and low confidence for outcomes for polar \r ecosystems (Meredith et al., 2019; Green et al., 2021b)."


id: 73d707b3ddab7a0cd70b5e3c722371d4
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 17633
content:
"Thermal tolerances of epipelagic populations drive biogeographic \r change (Figures 3.10, 3.15), but the strength and direction of range \r shifts tend to be modulated by both climate-induced and non-climate \r drivers (Pinsky et al., 2020b), including: (a) interactive effects of hypoxia \r and ocean acidification (Sampaio et al., 2021); (b) oceanic dispersal \r barriers (Choo et al., 2021), food and critical habitat availability (Alabia \r et  al., 2020; Tanaka et  al., 2021); (c)  geographic position, including \r depth (Mardones et al., 2021); and (d) ocean currents (Sunday et al., \r 2015; Chapman et  al., 2020; Fuchs et  al., 2020). The difference \r between physiological thermal tolerances (Section  3.3.2) and local \r environmental conditions determines safety margins against future \r climate warming in ectotherms (Pinsky et al., 2019). Acclimation and \r evolution (Section  3.3.4) and life-history stage (Section  3.3.3) also \r [...]"


id: 2711750b6dd287fb4a068858cdb6bbb2
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 4038
content:
"[...] alter species' thermal tolerances. Biogeographic responses are further \r modulated by other interacting factors (Table 3.17)."


id: 6f1e43fdd2be1f7a0d17b999370d2de0
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 16817
content:
"Ensemble global model projections indicate future increases in primary \r production and total animal biomass towards 2100 under RCP2.6 (~5 \r and 50%, respectively) and RCP8.5 (~10 and 70%, respectively), in the \r Arctic (Bryndum-Buchholz et  al., 2019; Lotze et  al., 2019; Nakamura \r and Oka, 2019), highlighting opportunities for, and possibly conflicts \r over, new ecosystem services (Section  3.5). For the Southern Ocean, \r no overall trends are apparent, but greater variability in both primary \r production and total animal biomass are projected under RCP2.6, with \r an ~5 and 15% increase in primary production and total animal biomass \r under RCP8.5, respectively (Bryndum-Buchholz et al., 2019; Lotze et al., \r 2019; Nakamura and Oka, 2019). All projections presented exhibit \r high inter-model variability and hence uncertainty (Heneghan et  al., \r 2021). Furthermore, regional models project significant distributional \r [...]"


id: df3f271dad7a9fca5309b7f667f24d90
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 36530
content:
"Breitburg et  al., 2018). Oxygen availability and the effects of ocean \r acidification (Sections  3.3, 3.4.2) on zooplankton might become a \r dominant constraint in the upper ocean's metabolic index, which is \r projected to decrease globally by 20% by 2100 (Deutsch et al., 2015; \r Steinberg and Landry, 2017). In addition, extremely rapid acceleration \r of climate velocities projected in the mesopelagic under all emissions \r scenarios suggest that species in this ocean stratum will be even \r more exposed to future warming than species in the epipelagic \r (Figure 3.4; Brito-Morales et al., 2020). But projections also suggest \r that warming-related increases in trophic efficiency lead to a 17% \r increase in the biomass of the deep-scattering layer (zooplankton \r and fish in the mesopelagic) by 2100 (low confidence) (Bindoff et al., \r 2019a). Observational studies appear to show that mesopelagic fishes \r adapted to warm water increased in abundance and distribution in the \r [...]"


id: c0923248b60593db6b4420229f524f91
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 31177
content:
"[...] California Current associated with warming and the expansion of OMZ \r (Koslow et al., 2019), suggesting that some mesopelagic fish stocks \r might be resilient to a changing climate (medium confidence)."


id: d0c7aa22ae229129fcfb283890555cc1
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 34082
content:
"Epipelagic isotherms have recently (1980-2015) deepened at an \r average of 6.6 +- 18.8 m per decade (Pinsky et al., 2019), but there \r is low agreement on whether species move deeper in pursuit of \r thermal refuge. Prior studies suggested range shifts to depth (Dulvy \r et al., 2008; Pinsky et al., 2013; Yemane et al., 2014), but increasing \r evidence suggests that fish and planktonic communities across large \r parts of the North Atlantic, sub-Arctic and northeast Pacific Ocean \r redistribute horizontally with horizontal climate velocity, except where \r vertical temperature gradients are particularly steep. There is low \r confidence for temperature-driven depth shifts in the epipelagic zone \r (Burrows et al., 2019; Campana et al., 2020; Caves and Johnsen, 2021). \r At the same time, decreasing oxygen concentrations and the vertical \r expansion of OMZs have already decreased suitable habitat of pelagic \r fishes, including tuna and billfishes, by ~15% primarily due to vertical \r [...]"


id: 1e5e446e162deb684cb138cf60e5cddd
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 2540
content:
"Since SROCC, field data have continued to show that the phenology \r of biological events in the ocean is very likely (high to very high \r confidence) advancing in response to climate change, with 71.9% \r of published observations consistent with these anticipated effects \r (Figure 3.16a,b; Table 3.19), although most reports (95.6%) were from \r the Northern Hemisphere (Figure  3.16a). Biological events that are \r shifting earlier in response to climate change include phytoplankton \r blooms (Scharfe and Wiltshire, 2019; Chivers et  al., 2020) such as: \r (a)  those of HAB species (Forsblom et  al., 2019; Bucci et  al., 2020); \r (b) peaks in zooplankton abundance (Chevillot et al., 2017; Forsblom \r et al., 2019); (c) the migration (Otero et al., 2014; Kovach et al., 2015; \r Chust et al., 2019) and spawning of commercial fish (McQueen and \r Marshall, 2017; Kanamori et  al., 2019), including crabs and squid \r (Henderson et al., 2017); and (d) breeding of marine reptiles (Mazaris \r [...]"


id: f39de660fd2afc7a2b8cf740017b7366
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 40234
content:
"[...] et al., 2008; Cherkiss et al., 2020). Moreover, different trophic levels \r within epipelagic food webs are responding at different rates (very \r high confidence) (Table  3.19; Figure  3.16b,c), with greater and \r more consistent responses by lower trophic levels (phytoplankton, \r holozooplankton and meroplankton) but less consistent, weaker \r and more varied responses by higher trophic levels. There were too \r few independent time series to make robust estimates for benthic \r invertebrates, plants, marine reptiles and mammals. This differential \r response across trophic levels could lead to trophic mismatches \r (Neuheimer et  al., 2018), where predators and their prey respond \r asynchronously to climate change (Edwards and Richardson, 2004; \r Rogers and Dougherty, 2019; Rubenstein et al., 2019; Emond et al., \r 2020), with potential population-level consequences, including \r declines in fish recruitment (Burthe et al., 2012; Chevillot et al., 2017; \r [...]"


id: 79acd3b6bae4312d9b1d96f6afc749a5
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 18609
content:
"[...] McQueen and Marshall, 2017; Asch et al., 2019; Durant et al., 2019; \r Regnier et  al., 2019). Available evidence also suggests that feeding \r relationships could modulate species responses to climate change, "


id: b737da6db0aa8f91412f5177f12db55d
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 29447
content:
"The CMIP6 ESM ensembles project that, by 2100, 18.8  +-  19.0% \r (mean  +-  very likely range) and 38.9  +-  9.4% of the ocean surface \r will very likely undergo a change of 20 d or more (advance or delay) \r in the start of the phytoplankton growth period under SSP1-2.6 and \r SSP5-8.5, respectively (Figure  3.17a,b) (low confidence  due to the \r dependence with the projected changes in phytoplankton biomass, \r the trends of which are reported with low confidence) (Section 3.4.3.4; \r SROCC Section  5.2.3; Bindoff et  al., 2019a). Phytoplankton growth \r is projected to begin later in the Northern Hemisphere subtropics, \r and earlier at high latitudes in some regions around the Antarctic \r Peninsula, and over large areas in the Northern Hemisphere (low to \r medium confidence as there are improved constraints from historical \r variability in this region and consistency with CMIP5-based-studies \r results) (Henson et  al., 2018b; Asch et  al., 2019). There is  high \r [...]"


id: 8b0a31c9e384c934917394e86356020
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 21630
content:
"measures indicate that the most dramatic increases in diversity relative \r to current conditions are expected for photosynthetic eukaryotes \r and copepods in the Arctic Ocean (Ibarbalz et  al., 2019). However, \r component eukaryotic taxa, for example diatoms (Busseni et al., 2020), \r are projected to lose diversity by 2100 under RCP8.5. Ecosystem models \r project a decline in nutrient supply that drives the disappearance of \r less-competitive and larger phytoplankton types, leading to extinction \r of up to 30% of diatom types, particularly in the Northern Hemisphere, \r by 2100 under RCP8.5 (Henson et al., 2021). Models further suggest \r that high latitudes are likely to encounter entirely novel phytoplankton \r communities by 2100 under RCP8.5 (100% change in community \r composition; Dutkiewicz et al., 2019; Reygondeau et al., 2020). At the \r polar edges, the increased richness is projected to coincide with high \r species turnover and increasing dominance of smaller phytoplankton \r [...]"


id: e7a7ff7906287f3ed200fc87c991041f
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 38063
content:
"[...] types (Henson et  al., 2021). These imply pronounced changes to \r both the oceans' ecological and biogeochemical function, as regions \r dominated by small phytoplankton typically support less-productive \r food webs (Section 3.4.3.4; Stock et al., 2017; Armengol et al., 2019) \r and sequester less particulate organic carbon (POC) in the deep ocean "


id: c742823d7b6d35fc6cbf9c4cd15d6be8
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 32374
content:
"At local to regional scales, tropicalisation often increases species \r richness where warm-water species extend their ranges to overlap with \r existing communities and decreases species richness where warming \r waters extirpate species (medium to high confidence) (Friedland et al., \r 2020a; Chaudhary et  al., 2021; Worm and Lotze, 2021). Latitudinal \r estimates from catalogued observations show declining species richness \r in equatorial waters over the past 50 years, with concomitant increases \r in species richness at mid-latitudes; the pattern is especially prominent \r in free-swimming pelagic species (Figure 3.18; Chaudhary et al., 2021). \r Similar patterns among marine animals have been described previously \r for historical warming events (Song et  al., 2020b). Tropicalisation is \r associated with increased representation of herbivorous species (Verges \r et  al., 2016; Zarco-Perello et  al., 2020; Smith et  al., 2021), although \r [...]"


id: 8a7cda1c3a0bfd16fdd6e487b180ca4f
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 21536
content:
"[...] observations and theory suggest that dietary generalism can also favour \r range-shifting species (Monaco et al., 2020; Wallingford et al., 2020)."


id: 49ed9cb4cf32e21b12f83bd58159ccf8
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 10245
content:
"The profound climatic and environmental changes projected for the \r Arctic region by 2100 (Cross-Chapter Paper 6) are also anticipated to \r alter the composition of apex assemblages like marine mammals (see \r Box 3.2; Albouy et al., 2020). Under both RCP2.6 and 8.5 scenarios \r the most vulnerable marine mammal species will be the North Pacific \r right whale (Eubalaena japonica, listed as an endangered species; \r IUCN, 2020) and the grey whale (Eschrichtius robustus, which has \r critically endangered subpopulations; IUCN, 2020). The extinction of \r the most-vulnerable species will disproportionately eliminate unique \r and important evolutionary lineages as well as functional diversity, \r with consequent impacts throughout the entire marine ecosystem \r (Section  3.3.4). More generally, future warming and acidification \r simulated in mesocosm experiments support projections of a \r substantial increase in biomass and productivity of primary producers \r [...]"


id: ec45a29e2262835c0cad575c92b334ac
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 38933
content:
"[...] and secondary consumers, but a decrease by >40% of primary \r consumers (Nagelkerken et al., 2020). On longer time scales, alteration \r of energy flow through marine food webs may lead to ecological \r tipping points (Wernberg et al., 2016; Harley et al., 2017) after which \r the food web collapses into shorter, bottom-heavy trophic pyramids \r (medium confidence)."


id: 285c29ff3091ed3ebd61c1901d6bc999
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 4304
content:
"Climate-change-driven changes in ocean characteristics and the \r frequency and intensity of extreme events (Section 3.2) increase the \r risk of persistent, rapid and abrupt ecosystem change (very high \r confidence), often referred to as ecosystem collapses or regime shifts \r (AR6 WGI Chapter 9; Collins et al., 2019a; Canadell and Jackson, 2021; \r Ma et  al., 2021). Such abrupt changes include altering ecosystem \r structure, function and biodiversity outside the range of natural \r fluctuations (Collins et al., 2019a; Canadell and Jackson, 2021). They \r can involve mass-mortality events and 'tipping points' or 'critical \r transitions', where strong positive feedbacks within an ecosystem lead \r to self-sustaining change (Figure 3.19a; Scheffer et al., 2012; Mollmann \r et  al., 2015; Biggs et  al., 2018). Abrupt ecosystem shifts have been \r observed in both large open-ocean ecosystems and coastal ecosystems \r (Section 3.4.2), with dramatic social consequences through significant \r [...]"


id: 4324f2e910fa5247b6f7bb4ed35a7f96
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 9023
content:
"[...] loss of diverse ecosystem services (high confidence) (Section 3.5; Biggs \r et al., 2018; Pinsky et al., 2018; Beaugrand et al., 2019; Collins et al., \r 2019a; Filbee-Dexter et al., 2020b; Huntington et al., 2020; Trisos et al., \r 2020; Turner et al., 2020b; Canadell and Jackson, 2021; Ma et al., 2021; \r Ruthrof et al., 2021). A summary of previous assessments of abrupt \r ecosystem shifts and extreme events is provided in Table 3.21."


id: 4ee4147b45d1ad0550d43cc00757ec50
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 11159
content:
"Marine birds (seabirds and shorebirds) and mammals include charismatic species and species that are economically, culturally and \r ecologically important (Sydeman et al., 2015; Albouy et al., 2020; Pimiento et al., 2020). Their long generation times and slow population \r growth suggests limited evolutionary resilience to rapid climate change (Section 3.3.4; Sydeman et al., 2015; Miller et al., 2018). According \r to the Red List Species Assessments of the International Union for Conservation of Nature (IUCN, 2020), the greatest current hazards to \r these groups include human use of biological resources and areas, invasive species and pollution (see Figure Box 3.2.1; Dias et al., 2019; \r Lusseau et al., 2021). Impacts of climate change and severe weather are ranked among the five most-important hazards influencing \r 131 and 45 bird and mammal species, respectively (see Figure Box 3.2.1 for selection of species), including 24 bird and 7 mammal \r [...]"


id: 35be097cc7a953d20685ab2f405e6bf4
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 6709
content:
"[...] species that are currently listed as endangered, critically endangered or threatened. Furthermore, according to these IUCN assessments, \r climate change and severe weather are expected to impact an additional 122 and 18 marine bird and mammal species over the next \r 50-100 years, respectively (see Figure Box 3.2.1; Dias et al., 2019)."


id: 843c3bbdd4e11e895a5c9e8bd4ba6c96
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 20420
content:
"Climate change is affecting marine food-web dynamics (high confidence) (Sections 3.4.2, 3.4.3), and the vulnerability and adaptive \r capacity of marine birds and mammals to such changes is linked to the species' breeding and feeding ecology. Higher-vulnerability \r species include central-place foragers (confined to, for example, breeding colonies fixed in space), diet and habitat specialists, and species \r with restricted distributions such as marine mammal populations in SES (medium confidence) (McMahon et al., 2019; Ropert-Coudert \r et al., 2019; Albouy et al., 2020; Grose et al., 2020; Sydeman et al., 2021). Surface-feeding and piscivorous marine birds appear to be more \r vulnerable to food-web changes than diving seabirds and planktivorous seabirds (medium confidence) (Sydeman et al., 2021). During \r the 2014-2015 Pacific heatwave, around 1 million piscivorous common murres died along a 1500 km coastal stretch in the Pacific USA \r [...]"


id: 39a1272093e7db16aa407fc9a02facc
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 7348
content:
"[...] due to reduced prey availability (Jones et al., 2018b; Piatt et al., 2020). Marine birds are vulnerable to phenological shifts in food-web \r dynamics, as they have limited phenotypic plasticity of reproductive timing, with potentially little scope for evolutionary adaptation \r (medium confidence) (Keogan et al., 2018), although changes in reproduction timing are observed in several species (Section 3.4.4.1; \r Sydeman et al., 2015; Descamps et al., 2019; Sauve et al., 2019). There is limited evidence of marine mammals' capacity to adapt to \r shifting phenologies, but observed responses include changes in the onset of migrations, moulting and breeding (Section 3.4.4.1; Ramp \r et al., 2015; Hauser et al., 2017; Beltran et al., 2019; Bowen et al., 2020; Szesciorka et al., 2020)."


id: 2bef599f9903783d1125bf8b3f06a32b
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 4983
content:
"Ecosystems can recover from abrupt shifts (e.g., Babcock et al., 2019; \r Christie et al., 2019; Medrano et al., 2020). However, where climate \r change is a dominant driver, ecosystem collapses increasingly cause \r permanent transitions (high confidence), although the extents of \r such transitions depend on the emission scenario (Trisos et al., 2020; \r Garrabou et al., 2021; Klein et al., 2021; Pratchett et al., 2021; Wernberg, \r 2021). Over the coming decades, MHWs are projected to very likely\r become more frequent under all emission scenarios (Section 3.2; WGI \r AR6 Chapter  9; Fox-Kemper et  al., 2021), with intensities and rates \r too high for recovery of degraded foundational species, habitats or \r biodiversity (medium confidence) (Babcock et  al., 2019; Garrabou \r et al., 2021; Klein et al., 2021; Serrano et al., 2021; Wernberg, 2021). \r Emission pathways that result in temperature overshoot above 1.5o\r C \r [...]"


id: 6366732f00712ef0c62dbf21f701f7a3
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 14782
content:
"[...] will increase the risks of abrupt and irreversible shifts in coral reefs and \r other vulnerable ecosystems (Section 3.4.4)."


id: 9fcb3649379863b19e9f954638acecb6
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 25321
content:
"The time of emergence of ecosystem responses supports planning \r for specific time-bound actions to reduce risks to ecosystems \r (Section 3.6.3.2.1; Bruno et al., 2018; Trisos et al., 2020). Although under \r RCP8.5, climate refugia from SST after 2050 are primarily in the Southern \r Ocean in tropical waters, these refugia are mainly from deoxygenation \r (Bruno et  al., 2018). Marine assemblages in these places will be \r exposed to unprecedented temperatures after 2050, peaking in 2075 \r (Figure 3.20a,b; Trisos et al., 2020). In contrast, changes in phytoplankton \r community structure will emerge earlier, primarily in the Pacific Ocean \r subtropics and through much of the North Atlantic Ocean (Figure 3.20c,d; \r Dutkiewicz et  al., 2019). Under RCP8.5, changes in phytoplankton \r community structure and, to a lesser extent, exposure of marine species \r to unprecedented temperatures, will emerge earlier in marine protected \r [...]"


id: 16d72a0c95b750e63a54b14ff337552e
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 1233
content:
"[...] areas (MPAs), covering ~7.7% of the global oceans (Section 3.6.2.3.2.1; \r UNEP-WCMC and IUCN, 2020; UNEP-WCMC and IUCN, 2021) as \r compared with non-MPAs (Figure 3.20b,d). Such assessment can support \r planning for future MPA placement and extent. Because MPAs can \r serve as refugia from non-climate drivers (Sections  3.6.2.3, 3.6.3.2.1), \r they facilitate opportunities for adaptation among marine species and \r communities in coastal oceans (Section 3.4.2)."


id: 80ed51ca0e37c879d76bb887548ff922
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 19816
content:
"declines (with very likely range) are -5.7 +- 4.1% and -15.5 +- 8.5% \r under SSP1-2.6 and SSP5-8.5, respectively, by 2080-2099 relative to \r 1995-2014 (Figure 3.21g), showing greater declines and lower inter\u0002model uncertainties (Tittensor et al., 2021). These declines result from \r combined warming and decreased primary production (with low \r confidence in future changes in primary production; Section 3.4.3.5) \r and are amplified at each trophic level within all ESM and marine \r ecosystem model projections across all scenarios (medium confidence) \r (Kwiatkowski et al., 2019; Lotze et al., 2019; Tittensor et al., 2021). \r However, there is limited evidence about how underlying food-web \r mechanisms amplify the climate signal from primary producers to \r higher trophic levels, and several putative mechanisms have been \r proposed (Section 3.4.4.2.2; Chust et al., 2014a; Stock et al., 2014; \r Kwiatkowski et al., 2019; Lotze et al., 2019; Heneghan et al., 2021). \r [...]"


id: 7ca4584eb32a304d37fdfbc1fa73e658
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 19129
content:
"[...] As assessed in SROCC, the biomass projections contain considerable \r regional variation with declines in tropical to temperate regions \r and strong increases in total animal biomass are projected in polar \r regions under high-emission scenarios, with climate-change effects "


id: 6b027d41f10a83d2fad0cb07b94bffc3
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content:
"SROCC assessed that reduced food supply to the deep sea will \r drive a reduction in abyssal seafloor biota by 2100 for RCP8.5 \r (Table  3.23). Simulations from one size-resolved benthic biomass \r model coupled to an ocean-biogeochemistry model forced with the \r CMIP5 ESM HadGEM2-ES (Yool et al., 2017) project a decline in the \r globally integrated total seafloor biomass of -1.1 and -17.6% by \r 2100 under RCP2.6 and RCP8.5, respectively (limited evidence, high \r agreement). In waters shallower than 100 m, total benthic biomass \r is projected to increase by 3.2% on average by 2100 under RCP8.5, \r primarily driven by warming-increased growth rates (Yool et  al., \r 2013), while at depths >2000 m (representing 83% of the ocean \r seafloor), declines of -32% arise from climate-driven decreases in \r surface primary production and POC flux to the seafloor (Yool et al., \r 2013; Kelly-Gerreyn et al., 2014; Yool et al., 2015; Yool et al., 2017). \r [...]"


id: cf6e89ff17ebc34ce8a77d96dd98bd2b
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"Regionally, multi-model mean changes in primary production show \r generally similar patterns of large declines in the North Atlantic and \r the western equatorial Pacific, while in the high latitudes, primary \r production consistently increases in CMIP5 and CMIP6 by 2100 \r (Cross-Chapter Paper 6; Kwiatkowski et al., 2020). In the Indian Ocean \r and subtropical North Pacific, which were regions of consistent NPP \r decline in CMIP5 projections (Bopp et al., 2013), the regional declines \r are reduced in magnitude, less spatially extensive and are typically \r less robust in CMIP6. Further assessment of simultaneous changes in \r processes such as nutrient advection, nitrogen fixation, the microbial \r loop and top-down grazing pressure (WGI AR6 Section  5.4.4.2; \r Laufkotter et al., 2015; Bindoff et al., 2019a; Canadell et al., 2021) are \r required to fully understand the regional primary production response \r in CMIP6 (Kwiatkowski et al., 2020). Given the regional variations in \r [...]"


id: 78663abd805966b9d94b92d187ac672e
created_at: 2023-04-19 13:22:52
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content:
"[...] the estimates of primary production changes and the uncertainty in the \r representation of the dominant drivers, there remains low confidence\r in the projected global decline in NPP."


id: 9be8752cf6810a591f535c0f1b47e409
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
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content:
"Analyses of satellite-derived primary production over the past two \r decades (1998-2018) showed generally weak and negative trends (up \r to -3.0%) at low and mid latitudes (Kulk et  al., 2020). In contrast, \r positive trends occurred in large areas of the South Atlantic and South \r Pacific Oceans, as well as in polar and coastal (upwelling) regions (up \r to +4.5%; Cross-Chapter Paper 6; Kulk et al., 2020). Data-assimilating \r ocean biogeochemical models estimate a global decline in primary \r production of 2.1% per decade in the period 1998-2015, driven by \r the shoaling mixed layer and decreasing nitrate concentrations (Gregg \r and Rousseaux, 2019). This is consistent with previous assessments \r that identified ocean warming and increased stratification as the main \r drivers (high confidence) affecting the regional variability in primary \r production Bindoff et al. (2019). However, as noted in SROCC and WGI \r AR6 Chapter 2 (Table 3.24; Gulev et al., 2021), observed interannual \r [...]"


id: c36bfa21649e148cb83509929130dfd4
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 31655
content:
"[...] changes in primary production on global and regional scales are \r nonlinear and largely influenced by natural temporal variability, \r providing low confidence in the trends."


id: fd570cf2ef73ddf9a4097e1a2d0e8e66
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 41924
content:
"The SROCC medium confidence assessment that warming, stratification, \r declines in productivity and changes in plankton community in the \r epipelagic zone result in reduced export of primary production to deeper \r layers (Table 3.24) is supported by subsequent literature (Bach et al., \r 2019; Leung et al., 2021). Particulate organic carbon export efficiency \r is constrained by altered mixing and nutrient availability (Boyd et al., \r 2019; Lundgreen et  al., 2019), particle fragmentation (Briggs et  al., \r 2020) as well as viral, microbial and planktonic community structure \r (Fu et al., 2016; Guidi et al., 2016; Flombaum et al., 2020; Kaneko et al., \r 2021) and metabolic rates (Cavan et al., 2019). These processes are \r strongly interlinked, and their net effect on primary production export \r from the upper ocean remains difficult to quantify observationally \r (Boyd et  al., 2019). Since SROCC, there is increasing evidence that \r [...]"


id: d53cac2493b195ba644b2db3a6bd396e
created_at: 2023-04-19 13:22:52
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content:
"[...] ocean deoxygenation can alter zooplankton community structure \r (Wishner et al., 2018), zooplankton respiration rates (Cass and Daly, \r 2014; Cavan et  al., 2017) and patterns of diel vertical migration \r (Aumont et  al., 2018), which may focus remineralisation of organic \r carbon at the upper margins of OMZs (Section 3.4.3.4 on depth shifts \r due to OMZ; Bianchi et al., 2013; Archibald et al., 2019)."


id: dd1b337e4d5e86ef29d9208321f0bfe4
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
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content:
"drivers during the overshoot period. WGI AR6 assessed that temporary \r overshoot of a 2degC warming threshold has irreversible effects on global \r mean sea level and also effects on ocean heat content that persist \r beyond 2100 (WGI AR6 Section 4.6.2.1; Lee et al., 2021). Model results \r indicate that sea surface temperatures (high confidence), Arctic sea ice \r (high confidence), surface ocean acidification (very high confidence) \r and surface ocean deoxygenation (very high confidence) are reversible \r within  years to decades if net emissions reach zero or below (WGI \r AR6 Table 4.10; Lee et al., 2021). Although changes in these surface \r ocean variables are reversible, habitat-forming ecosystems, including \r coral reefs and kelp forests, may undergo irreversible phase shifts with \r >1.5degC warming (Sections 3.4.2.1, 3.4.2.3), and are thus at high risk \r this century in 1.5degC or 2degC scenarios involving overshoot (Tachiiri \r [...]"


id: c99cab0c37ec65a0290fa71d518c1e05
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
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content:
"[...] et al., 2019). In an overshoot scenario in which CO2 returns to 2040 \r levels by 2100 (SSP5-3.4-OS; O'Neill et al., 2016), SST and Arctic sea \r ice do not fully return by 2100 to levels prior to the CO2 peak (medium \r confidence) (WGI AR6 Section 4.6.2.1; Lee et al., 2021), suggesting that \r reversal of marine ecological impacts from 21st century climate impacts \r would extend into the 22nd century or beyond (McManus et al., 2021). \r Models also indicate that global sea level rise, as well as warming, \r ocean acidification and deoxygenation at depth, are irreversible for \r centuries or longer (very high confidence) (WGI AR6 Section 4.6.2.1 and \r Table 4.10; Palter et al., 2018; Li et al., 2020c; Lee et al., 2021)."


id: 424918628a39f28aac86b5c139399926
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
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content:
"Deep-sea ecosystems include all waters below the 200-m isobath as well as the underlying benthos, and they provide habitats for highly \r diversified and specialised biota, which play a key role in the cycling of carbon and other nutrients (see Figure Box 3.3.1; Thurber et al., \r 2014; Middelburg, 2018; Snelgrove et al., 2018). The deep sea covers >63% of Earth's surface (Costello and Cheung, 2010) and is exposed \r to climate-driven changes in abyssal, intermediate and surface waters that influence sinking fluxes of particulate organic matter (high \r confidence) (see Figure Box 3.3.1; Sections 3.1, 3.2.1, 3.2.2, 3.4.3.4; WGII AR5 Section 30.5.7; SROCC Sections 5.2.3, 5.2.4; Hoegh-Guldberg \r et al., 2014; Bindoff et al., 2019a). These ecosystems are also influenced by non-climate drivers, especially fisheries, oil and gas extraction \r (Thurber et al., 2014; Cordes et al., 2016; Zhang et al., 2019a); cable laying (United Nations, 2021); and mineral resource exploration (Hein \r [...]"


id: 7e9551da01c7a08e6927bb872d30efb9
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vector_id: 19424
content:
"[...] et al., 2021); with proposed large-scale deep-sea mining a potential future source of impacts (Danovaro, 2018; Levin et al., 2020)."


id: fa886bfd9ccff230928584be6d8114bd
created_at: 2023-04-19 13:22:52
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content_type: text
index: climate_gpt_v2
vector_id: 41449
content:
"Ocean warming alters biological processes in deep-sea ecosystems in ways that affect deep-sea habitat, biodiversity and material \r processing. Enhancement of microbial respiration by warming attenuates sinking POC, which has been associated with the globally \r projected declines in total seafloor biomass of -9.8 and -13.0% by 2081-2100 relative to 1995-2014 under SSP1-2.6 and SSP5-8.5, \r respectively (limited evidence) (Section  3.4.3.4). Additionally, climate-change-driven oxygen loss (Section  3.2.3.2; Luna et  al., 2012; \r Belley et al., 2016) and geographic shifts in predator distributions (Section 3.4.3.1) are anticipated to affect deep-sea biodiversity (limited \r evidence, high agreement) (Smith et al., 2012; Morato et al., 2020). Complex responses of some bathyal crustacean assemblages to \r environmental change suggest an increase in phylogenetic diversity but limited decreases in abundances with temperature (Ashford \r [...]"


id: db3103d80b197f4b86220c5b4c9dbe69
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content:
"[...] et al., 2019). Acute mortality of some reef-forming cold-water corals to laboratory-simulated warming (Lunden et al., 2014) suggests \r that both long-term warming and the increase of MHWs in intermediate and deep waters (Elzahaby and Schaeffer, 2019) could pose \r significant risk to associated ecosystems (high confidence). Thermal tolerance thresholds (lethal and sub-lethal) of scleractinians in \r laboratory settings depend on their geographic position and capacity for thermal adaptation, as well as other factors including food, \r oxygen and pH (medium to high confidence) (Naumann et al., 2013; Hennige et al., 2014; Lunden et al., 2014; Naumann et al., 2014; \r Georgian et al., 2016; Gori et al., 2016; Maier et al., 2016; Buscher et al., 2017)."


id: 9403b8ab7c82c801cf136c526e0884b8
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 23245
content:
"The extension and intensification of deep-water acidification (Section 3.2.3.1) has been identified as a further key risk to deep-water coral \r ecosystems (medium confidence) (Bindoff et al., 2019a). Literature since SROCC supports this assessment (Morato et al., 2020; Puerta \r et al., 2020), although scleractinians and gorgonians are found in regions undersaturated with respect to aragonite (Thresher et al., 2011; \r Fillinger and Richter, 2013; Baco et al., 2017). Laboratory experiments on reef-forming scleractinians show variable results, with regional \r acclimation potential and population-genetic adaptations (Georgian et al., 2016; Kurman et al., 2017). Desmophyllum pertusum7 and \r Madrepora oculata maintain calcification in moderately low pH (7.75) and near-saturation of aragonite (Hennige et al., 2014; Maier et al., \r 2016; Buscher et al., 2017), but lower pH (7.6) and corrosive conditions lead to net dissolution of D. pertusum skeletons (high confidence) \r [...]"


id: a56645b0ca5466133386d6e80421a551
created_at: 2023-04-19 13:22:52
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content:
"[...] (Lunden et al., 2014; Kurman et al., 2017; Gomez et al., 2018). Experiments suggest that D. dianthus is more sensitive to warming than \r acidification and when both are high, as projected under climate change. Warming appears to compensate for declines in calcification, \r with fitness also sensitive to food availability (Bramanti et al., 2013; Movilla et al., 2014; Gori et al., 2016; Baussant et al., 2017; Buscher \r et al., 2017; Schonberg et al., 2017; Hofer et al., 2018; Maier et al., 2019)."


id: 94477c26d3495b2415e0abf5da6b4426
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 23293
content:
"In OMZ regions (Section 3.2.3.2), benthic species distributions (Sperling et al., 2016; Levin, 2018; Gallo et al., 2020), abundance and \r composition of demersal fishes in canyons (De Leo et al., 2012) and deep-pelagic zooplankton (Wishner et al., 2018) follow oxygen \r gradients, indicating that deep-sea biodiversity and ecosystem structure will be impacted by extension of hypoxic areas (medium \r confidence). Fossil records show benthic population collapse and turnover when oxygen ranged from oxic to mildly or severely hypoxic \r (Cross-Chapter Box PALEO in Chapter 1; Moffitt et al., 2015). Regional extirpations among cold-water corals in the paleorecord were \r associated with substantial declines in oxygen, coincident with abrupt warming and altered properties of intermediate water-masses \r (Wienberg et al., 2018; Hebbeln et al., 2019). Despite mortality and functional impacts from low oxygen concentrations observed in \r [...]"


id: ec5c5a4f1358f8c2ed858a8930d54ae7
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 38945
content:
"[...] aquaria (Lunden et al., 2014), recent observations of the deep-water coral D. pertusum suggest adaptive capacity to hypoxia among \r specimens from OMZ regions that are highly productive (low confidence) (Hanz et al., 2019; Hebbeln et al., 2020)."


id: 8a7f90184505ffbd2164646f70c59bb6
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 21538
content:
"Climate-driven impacts further limit the resilience of deep-sea ecosystems to impacts from human activities (high confidence) (Levin and \r Le Bris, 2015; Rogers, 2015; Sweetman et al., 2017). However, assessing cumulative climatic and non-climatic impacts is challenging for \r these data-poor environments (Ashford et al., 2018; Levin, 2018; Armstrong et al., 2019; Heffernan, 2019; Kazanidis et al., 2020; Orejas \r et al., 2020), where lack of knowledge increases the possibility of overlooking ecosystem vulnerabilities and risks (Levin, 2021). A paucity \r of information about the natural variability and historical trends of these habitats prevents robust assessment of adaptive capacities and \r potential vulnerabilities to extreme events (Aguzzi et al., 2019; Levin et al., 2019; Chapron et al., 2020; Danovaro et al., 2020; Le Bris and \r Levin, 2020; Levin, 2021). The spatial resolution of CMIP5 models is too coarse to robustly project changes in mesoscale circulation at the \r [...]"


id: 3a8eb3347540bbe1b6d4350c7015af97
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content:
"[...] seafloor (Sulpis et  al., 2019), on which deep-sea ecosystems depend for organic material supplies and dispersal of planktonic and \r planktotrophic larvae (high confidence) (Fox et al., 2016; Mitarai et al., 2016; Dunn et al., 2018). Higher-resolution modelling from CMIP6 \r (Orr et  al., 2017), multi-annual and high-frequency records of ocean bottom-water properties (Meinen et  al., 2020), and better \r understanding and accounting of biogeochemical mechanisms of organic carbon transport to the ocean interior is expected to improve \r this capacity (Boyd et al., 2019; Seferian et al., 2020)."


id: 13c2d3965d259bef5d5ea60d6d362445
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content:
"of non-indigenous species have directly or indirectly decreased \r commercially important fishery species and nursery habitat (Booth \r et al., 2018). Non-indigenous species outperform indigenous species \r in coastal zones experiencing warming and freshening (McKnight \r et al., 2021). Non-climate drivers, especially marine shipping in newly \r ice-free locations (Chan et  al., 2019), fishing pressure (Last et  al., \r 2011), aquaculture of non-indigenous species (Mach et  al., 2017; \r Ruby and Ahilan, 2018) and marine pollution and debris (Gall and \r Thompson, 2015; Carlton et  al., 2018; Carlton and Fowler, 2018; \r Lasut et al., 2018; Miralles et al., 2018; Rech et al., 2018; Therriault \r et al., 2018), promote range shifts and movement of non-indigenous \r species (high confidence). Non-climate drivers can also intensify \r the ecological effects of non-indigenous species (Geraldi et  al., \r 2020). Invasive marine species can alter species behaviour, reduce \r [...]"


id: a8829412a02dd8f5997a556ff2324d7a
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index: climate_gpt_v2
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content:
"[...] indigenous species abundance, reduce water clarity, bioaccumulate \r more heavy metals than indigenous species and inhibit ecosystem \r resilience in the face of extreme events (medium confidence) \r (McDowell et al., 2017; Geburzi and McCarthy, 2018; Anton et al., \r 2019; Ruthrof et al., 2021). Risks from invasive species to the sources \r of other ecosystem services or aquatic goods, including valuable \r materials, mining activities, shipping or ocean energy installations, \r have not been evaluated."


id: ea110c994682d5bdbe262ebd72cc7f7b
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 38529
content:
"Climate change is a key agent of biodiversity change in numerous ocean \r and coastal ecosystems (very high confidence) (Table 3.26; Worm and \r Lotze, 2021), and climate change and biodiversity loss reinforce each \r other (Portner et al., 2021b). Biodiversity has changed in association \r with ocean warming and loss of sea ice (Sections 3.4.2.10, 3.4.3.3.3; \r Section  CCP6 2.4.2), SLR (Section  3.4.2; Cross-Chapter  Box  SLR in \r Chapter 3), coral bleaching (Section 3.4.2.1), MHWs (Sections 3.4.2.1-\r 3.4.2.5) and upwelling changes (high confidence) (Section  3.4.2.9). \r Overlapping non-climate drivers (Section 3.1) also decrease ocean and \r coastal ecosystem biodiversity (very high confidence) (O'Hara et  al., \r 2021; Portner et al., 2021b). There is medium confidence that local and \r regional marine biodiversity losses from climate disrupt ecosystem \r services provided by specific ocean and coastal species or places \r [...]"


id: b161dddf8592adedf91ea62c7a5ec628
created_at: 2023-04-19 13:22:52
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content_type: text
index: climate_gpt_v2
vector_id: 28435
content:
"[...] (Sections 3.5.3-3.5.6; Figure 3.23; Table 3.26; see Box 3.3; Dee et al., \r 2019a; Hossain, 2019; Smale et al., 2019; Teixeira et al., 2019; Martin \r et al., 2020; Pathak, 2020; Weiskopf et al., 2020; Zunino et al., 2020; \r Archer et al., 2021). However, adaptive capacity varies greatly among \r ecosystems, and ecological functions sometimes remain, despite \r changes in species assemblages, as in certain coral reef communities \r (Richardson et  al., 2020). Projected changes in biodiversity due to \r climate change (Section 3.4.3.3.3) are expected to alter the flow and \r array of ocean and coastal ecosystem services (high confidence) (Smale \r et  al., 2019; Cavanagh et  al., 2021; Ruthrof et  al., 2021; Worm and \r Lotze, 2021), but data gaps hinder developing projections of ecosystem \r service changes detailed enough to support decision making (Rosa \r et al., 2020)."


id: 5ec767842cacbee124bf0c87b84631fa
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content:
"Globally, about 17% of humans' average per capita intake of animal \r protein in 2017 came from marine and freshwater wild-caught and \r aquacultured aquatic animals (Costello et  al., 2020; FAO, 2020a). \r Per capita intake of seafood is 50% or more in some Small Island \r Developing States (SIDS) (Vannuccini et al., 2018), and consumption per \r capita is 15 times higher in Indigenous Peoples than non-Indigenous \r Peoples (Cisneros-Montemayor et  al., 2016). Fishery products also \r supply critical dietary micronutrients worldwide (Section  3.5.4.1; \r Hicks et al., 2019; Vianna et al., 2020). Marine and freshwater fisheries \r and aquaculture provide livelihoods for an estimated 10-12% of the \r world's population (Barange et  al., 2018). Fishing and aquaculture \r provide women and their families with substantial amounts of food \r and income (Harper et  al., 2020b), because at least 11% of small\u0002scale fishers (Harper et al., 2020b) and up to half of all fishery and \r [...]"


id: 5441c011e30da47ed44efc94ba6ca1db
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vector_id: 12098
content:
"[...] aquaculture workers (FAO, 2018) are women. This section assesses \r how climate-driven alterations of the abundance or nutritional quality \r of food from the sea could affect humans. Aquaculture, catch potential \r changes and human adaptations to changes in wild and cultured \r harvests are assessed in Section 5.9."


id: a4f9d8c7bccf9ed43ed10477448a38cd
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index: climate_gpt_v2
vector_id: 26246
content:
"to have detrimental effects on seabirds, pelagic fish and marine \r mammals (medium confidence) (Lindegren et al., 2018; Steiner et al., \r 2019), which may harm dependent human communities, including \r Arctic Indigenous Peoples (low confidence) (Arctic Monitoring and \r Assessment Programme, 2018; Steiner et al., 2019). Modelled fishery \r futures and revenue depend on environmental scenario, fishing\u0002fleet composition and management, and ocean acidification and \r temperature responses of harvested species (high confidence) (Punt \r et al., 2014; Punt et al., 2015; Seung et al., 2015; Fernandes et al., 2017; \r Rheuban et al., 2018; Tai et al., 2019; Punt et al., 2020). Detrimental \r effects of ocean acidification are projected to begin emerging in specific \r fisheries by 2030 (limited evidence, high agreement) [(southern Tanner \r crab (Chionoecetes bairdi) (Punt et al., 2015); sea scallop (Placopecten \r magellanicus) (Rheuban et  al., 2018); Northeast Arctic cod (Gadus \r [...]"


id: 60f5293a2af45bc2baecad761aa3d3d4
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index: climate_gpt_v2
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content:
"[...] morhua) (Hansel et al., 2020); Arctic fisheries (Lam et al., 2016)]. At the \r same time, projected hypoxic conditions of ~2 mg l-1 of oxygen will \r be consistently detrimental across taxonomic groups, developmental \r stages and climate regions (high confidence) (Sampaio et al., 2021). \r Ecosystem-based management (Section 3.6.3.1.2) shows promise for \r decreasing risk from interacting climate and non-climate drivers to \r forage species and fished species."


id: c86576d3bfce67ea19eedda15b2fb07f
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 32561
content:
"strains (Section 5.9.4; Barton et al., 2015a). Laboratory studies show \r that ocean acidification decreases the fitness, growth or survival of \r many economically and culturally important larval or juvenile shelled \r mollusks (high confidence) (Cao et  al., 2018; Onitsuka et  al., 2018; \r Stevens and Gobler, 2018; Griffith et al., 2019a; Mellado et al., 2019) \r and of several valuable wild-harvest crab species (Barton et al., 2015a; \r Punt et al., 2015; Miller et al., 2016; Swiney et al., 2017; Gravinese \r et al., 2018; Tomasetti et al., 2018; Long et al., 2019; Trigg et al., 2019). \r Ocean acidification alters larval settlement and metamorphosis of fish \r in laboratory studies (high confidence) (Cattano et al., 2018; Espinel\u0002Velasco et al., 2018), suggesting possible changes in fish survival and \r thus fishery characteristics. Deoxygenation can decrease size and \r abundance of marine species and suppress trophic interactions (Levin, \r [...]"


id: 54e9b4084dc328bd197a0cd992411ad9
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updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 12210
content:
"[...] 2003), decrease the diversity within marine ecosystems (Sperling et al., \r 2016) while temporarily increasing catchability and increasing the risk \r of overfishing (Breitburg et  al., 2018) and decrease the ecosystem \r services provided by specific fisheries (Orio et al., 2021). The chronic \r effects of deoxygenation on wild fisheries are complex and highly \r interactive with co-occurring drivers and overall ecosystem responses \r (medium evidence, high agreement) (Townhill et al., 2017; Rose et al., \r 2019). Detecting and attributing marine ecosystem responses to \r ocean acidification and deoxygenation outside of laboratory studies \r remains challenging because of the strong influence of co-occurring \r environmental changes on natural systems (Section 3.3.5; Rose et al., \r 2019; Doo et al., 2020)."


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vector_id: 33060
content:
"The interaction of climate and non-climate drivers endangers the \r supply of non-food consumable products developed from marine \r organisms (limited evidence, high agreement). This broad class \r includes nutraceuticals (derived from fish, krill, shellfish, seaweeds and \r microbes), food preservatives or additives (derived from crustaceans, \r fish, microalgae and seaweeds, and cyanobacteria), pharmaceuticals \r (derived from fish, shellfish, microbes, cyanobacteria, corals and \r sponges) or cosmetic products (derived from sponges, phytoplankton \r and seaweeds, fish etc.) (Freitas et  al., 2012; Dewapriya and Kim, \r 2014; Leal and Calado, 2015; Stengel and Connan, 2015; Greene \r et al., 2016; Ciavatta et al., 2017; Gutierrez-Rodriguez et al., 2018). \r But biodiversity changes, warming, acidification and non-climate \r drivers (especially fishing pressure) may decrease the availability \r of these organisms or the potency of the compounds they produce \r [...]"


id: ff9ac36479c616bacb98e7ae2d47a933
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 42369
content:
"[...] (Section  5.7.5.1; Figure  3.23; Table  3.26; Webster and Taylor, 2012; \r Mehbub et al., 2014; Kotta et al., 2018; Martins et al., 2018; Conrad \r et al., 2021). Observed and projected declines and movement of fish \r stocks due to fishing pressure and climate change impacts (IPCC, \r 2019b) have generated concerns that the supply and safety of fish and \r krill oil for human dietary supplements may decline (Section 5.7.5.1; \r Gribble et al., 2016; Lloret et al., 2016). This risk can be lowered by \r technological adaptations (Section 3.6.2.2), such as increasing the use \r of alternative sources like marine phytoplankton, macroalgae, marine \r microbes (Dewapriya and Kim, 2014; Greene et al., 2016; Dave and \r Routray, 2018; Nguyen et al., 2020) and underutilised resources such \r as fish, seal, crab and shrimp byproducts (Dave and Routray, 2018), \r and by improving extraction and processing efficiency (Cashion et al., \r 2017). Climate effects on non-food consumable products could be \r [...]"


id: fa7ed972caa052dd10096fdaeb040733
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 41437
content:
"[...] widespread yet poorly detected, complicating assessment of impacts, \r risks and vulnerability reduction."


id: e247d20f5a05d78a60e160e2bc738ae9
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 37098
content:
"Temperature will continue to be a major driver of fisheries changes \r globally, but other non-climate factors like organism physiology and \r ecosystem response (Section 3.3) and fishing pressure (Chapter 5), as \r well as other climate-induced drivers like acidification, deoxygenation \r and sea ice loss (Section 3.2), will play critical roles in future global \r and local fisheries changes (high confidence). Warming, acidification \r and business-as-usual fishing policy under RCP8.5 are projected \r to place around 60% of global fisheries at very high risk (medium \r confidence) (Cheung et  al., 2018). Model intercomparison showed \r that ocean acidification and protection affect ecosystems more than \r fishing pressure, and ecological adaptation will significantly determine \r impacts on fishery biomass, catch and value until approximately 2050 \r (medium confidence) (Olsen et  al., 2018). Ecosystem responses to \r warming water, fishing pressure, food-web changes, MHWs and sea \r [...]"


id: 51688462863faced0ed3ca81cb3b61f5
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 11601
content:
"[...] ice algal populations have been responsible for highly variable or \r collapsing populations of Northern Hemisphere high-latitude forage \r fish species including sand lances (Ammodytes spp.), Arctic cod \r (Boreogadus saida), capelin (Mallotus catervarius) and herring (Clupea \r spp.) (Lindegren et  al., 2018; Steiner et  al., 2019; Arimitsu et  al., \r 2021; Suca et al., 2021). Declining stocks of forage fish are expected "


id: eae0209d80a886b0de65f242241b0f3c
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 38685
content:
"There is insufficient evidence to develop global projections of future \r climate impacts on humans through changes in non-food consumable \r marine products, but specific local examples have been investigated, \r such as the Arctic ooligan (eulachon; Thaleichthys pacificus), a small \r smelt fish. Ooligan grease has been used by Indigenous Peoples of the \r North Pacific coast (Phinney et al., 2009) for at least 5000 years to treat \r stomach aches, colds and skin conditions, and as a traditional food \r source high in omega-3 fatty acids (Byram and Lewis, 2001; Cranmer, \r 2016; Patton et al., 2019). Analysis of remains have shown that ooligan \r could comprise up to 67% of traditional historical fisheries catches \r (Patton et al., 2019). Because ooligan spawning relies on the timing \r of the spring freshet, and because the species has declined in the past \r 25 years due to fishing pressure and predation, the species may be at \r [...]"


id: b68fc247616e727a30b394a4b03bdb8e
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 29324
content:
"[...] risk from combined climate-induced and non-climate drivers (medium \r confidence) (Talloni-Alvarez et  al., 2019). Projections under RCP2.6 \r or RCP8.5 estimate reductions by 21 or 31% by 2050 in essential \r nutrients from traditional seafood for Indigenous Peoples in Canada, \r relative to 2000, with a modelled nutritional deficit that includes non\u0002traditional dietary substitutions (Marushka et al., 2019)."


id: 3248fc81a49bc707187f9570202c2a8c
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 6101
content:
"Climate impacts have already altered ocean and coastal habitats \r (Section 3.4.2; Table 3.26; Gissi et al., 2021) in ways that have led to \r species range shifts, biodiversity changes, phenology changes and \r regime shifts (Section  3.4.3) from the surface ocean to the seafloor \r (very high confidence) (see Box 3.3; Figure 3.22). Continued ocean and \r coastal habitat impacts are projected, and their severities will depend \r on emissions scenario and co-occurring drivers (Section 3.4.3; Qiu et al., \r 2019) or extremes (e.g., Babcock et al., 2019). Warming and physical \r circulation are projected to change larval dispersal, a habitat-related \r service (Bashevkin et  al., 2020), but identifying probable outcomes \r remains challenging owing to the high variability among species, \r locations and recruitment (Schilling et  al., 2020; King et  al., 2021; Le \r Corre et al., 2021; Raventos et al., 2021). Climate risks to habitat can \r [...]"


id: a8186740d36c68f12ead38d825e22335
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 26786
content:
"[...] be decreased by reducing non-climate drivers, preserving ecosystems or \r restoring habitat (Sections 3.6.2, 3.6.3.2). Risk to larval dispersal cannot \r be meaningfully addressed at scale by human-implemented adaptations; \r instead, declines in this service will pressure natural systems to adapt via \r physiological plasticity or evolution (Section 3.3; Bashevkin et al., 2020)."


id: 83b3580a662f9bb383ae2ae76b0a187a
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 20312
content:
"Limited evidence about climate impacts exists for valuable non-food \r aquatic materials. Ocean warming and acidification harm red coral \r (Corallium rubrum) (Bramanti et al., 2013) and communities hosting \r black coral (Antipatharian spp.), both used for jewellery (Ross et al., \r 2020). While no-take MPAs (Section  3.6.3.2) enhance red-coral \r structural complexity, they only weakly compensate for warming effects \r (Cerrano et al., 2013; Montero-Serra et al., 2019). Antipatharian spp. \r are not well studied or monitored (Gress and Andradi-Brown, 2018). \r Acidification and warming negatively impact pearl oysters (Welladsen \r et al., 2010; Liu and He, 2012; Liu et al., 2012; Hoegh-Guldberg et al., \r 2014; Zhang et  al., 2019b). For example, projected climate impacts \r for 2035 would decrease the average net present value of French \r Polynesia's pearl aquaculture industry by 29.1% compared with the \r present (Hilsenroth et  al., 2021). Climate impacts on ornamental \r [...]"


id: 763607c22f9fde4e0c19f319b99f34a3
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
vector_id: 18021
content:
"Decreasing the vulnerability of renewable-energy installations, \r particularly wind turbines, to climate risks (Table 3.26; Bindoff et al., \r 2019a) could include technological adaptations (Section 3.6.2.2) such \r as storm 'survival mode' settings (Penalba et al., 2018); preparation \r for hazards such as icing, SLR, drifting sea ice and wave activity (Neill \r et al., 2018; Goodale and Milman, 2019; Solaun and Cerda, 2019); and \r biofouling (medium confidence) (Want and Porter, 2018; Joyce et al., \r 2019; Vinagre et al., 2020), which is expected to increase in response \r to warming and acidification (medium confidence) (Dobretsov et al., \r 2019; Khosravi et  al., 2019; Liu et  al., 2020d; Lamim and Procopio, \r 2021). Macroalgae and fish-processing byproducts are being tested \r for biofuel use (Greene et al., 2016; Alamsjah et al., 2017; Saifuddin \r and Boyce, 2017; Sakthivel et al., 2018; Sudhakar et al., 2019; Nguyen \r [...]"


id: 21938faddb205be18b6f252ae6c218ba
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
vector_id: 3116
content:
"[...] et al., 2020; Ramachandra and Hebbale, 2020; Tan et al., 2020), but \r weather variability could pose financial risk to this sector (Kleiman \r et al., 2021)."


id: 185b03458897291a8a76aaf60c3afe65
created_at: 2023-04-19 13:22:52
updated_at: 2023-04-19 13:22:52
content_type: text
index: climate_gpt_v2
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content:
"the geographic spread and risk of marine-borne human pathogen \r outbreaks, including Vibrio spp. (very high confidence) (Table  3.26; \r Bindoff et al., 2019a; Logar-Henderson et al., 2019; Froelich and Daines, \r 2020; Montanchez and Kaberdin, 2020; Semenza, 2020; Ferchichi \r et  al., 2021). Climate change affects at least 30 human pathogens \r with aquatic-system infection routes (e.g., ingestion of contaminated \r water or seafood, or contact with wounds; Table  3.SM.2; Cross\u0002Chapter Box ILLNESS in Chapter 2; Nichols et al., 2018). Conditions \r favourable for Vibrio cholerae are increasing globally, which raises the \r risk to humans (Cross-Chapter Box ILLNESS in Chapter 2). Increased \r storm-related flooding and SLR further increase human encounters with \r Vibrio spp. (Froelich and Daines, 2020). Aquatic diseases, particularly \r Vibrio spp., have caused large economic losses in aquaculture by \r decreasing the quality or survival of cultured species (Lafferty et al., \r [...]"


id: 4b04e3abe00f6494cd1f444222d4833c
created_at: 2023-04-19 13:22:52
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index: climate_gpt_v2
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content:
"[...] 2015; Novriadi, 2016). Temperature-based model projections show that \r all Canadian shellfish beds will experience conditions that promote \r high risk of Vibrio spp. growth by 2100 for both RCP4.5 and RCP8.5 \r scenarios (Ferchichi et al., 2021). Climate-induced drivers may increase \r Vibrio spp. loads in seafood species: laboratory-simulated heatwaves \r increase Vibrio spp. abundance in Pacific oyster (Crassostrea gigas) \r (Green et al., 2019) and simulated ocean acidification increases hard \r clam (Mercenaria mercenaria) susceptibility to Vibrio spp. infection \r (Schwaner et al., 2020). Projected increases in temperature, extreme \r and variable rainfall conditions, coastal flooding and SLR (Section 3.2; \r Cross-Chapter  Box  SLR in Chapter  3) strongly increase the risk of \r frequent and severe aquatic human pathogen outbreaks in ocean \r and coastal areas that will continue to harm human health and cause \r economic losses (high confidence) (Cross-Chapter  Box  ILLNESS in \r [...]"


id: 5bb9efefac6cf484b9a16351d79fe2dd
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 13392
content:
"[...] Chapter 2; Froelich and Daines, 2020; Semenza, 2020; Ferchichi et al., \r 2021). Section 3.6.3.1.5 assesses human adaptations to increasing risk \r of marine-borne pathogens."


id: a2b2db929651dd535f75832da5b13bad
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 25841
content:
"et al., 2020; Mastrocicco and Colombani, 2021). Coastal salinisation \r is attributed to regionally varying combinations of climate-induced \r drivers, like SLR and storm-related flooding by seawater, and non\u0002climate drivers, like water withdrawal and land-use changes (very high \r confidence) (Islam et al., 2019; Rahman et al., 2019; Paldor and Michael, \r 2021). Monitoring-related adaptations (Section  3.6.2.2.2), including \r advances in modelling and monitoring, are providing decision-relevant, \r regional-scale information (Colombani et  al., 2016; Mukhopadhyay \r et  al., 2019; Slama et  al., 2020; Corwin, 2021). For example, new \r projections indicate which drinking-water intake stations on China's \r Pearl River Estuary will be unable to meet demands by 2100 due to \r SLR and drought (Wang and Hong, 2021), while others show that SLR \r effects on seawater intrusion into the coastal aquifer in Kerala, India, \r under both RCP4.5 and RCP8.5 scenarios are negligible (Sithara et al., \r [...]"


id: 1bce2856fffd182447fc6aace7e23121
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 2076
content:
"[...] 2020). Salinisation-associated changes may disproportionately burden \r women responsible for securing drinking water and fuel, such as in \r the Indian Sundarbans (Mukhopadhyay et al., 2019). Salinisation will \r continue to endanger coastal water and soil quality in the future (high \r confidence) (Islam et  al., 2019; Paldor and Michael, 2021), but the \r evidence assessed above shows that subsequent impacts to human \r health and agriculture will depend heavily on regional variations in \r environment and human behaviour (medium confidence)."


id: 2032d279fd98617bc3233411d3101e41
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 2876
content:
"Together, climate-induced and non-climate drivers can mobilise \r toxins and contaminants in ways that harm human and marine \r species health (very high confidence) (see Box  3.2), and climate \r change is altering these relationships (high confidence) (Table  3.26; \r Bindoff et al., 2019a). Under warming or ocean acidification, marine \r molluscs exposed to pharmaceuticals via wastewater experience \r more detrimental biological consequences or greater bioaccumulation \r (limited evidence, high agreement) (Costa et al., 2020a; Costa et al., \r 2020b; Dionisio et al., 2020; Freitas et al., 2020; Kibria et al., 2021). \r Physical circulation, temperature and biogeochemical characteristics \r (Bowman et al., 2020; Liu et al., 2020a; Liu et al., 2020b; Sun et al., \r 2020; Zhang et al., 2020b) control the ubiquitous oceanic distribution of \r methylmercury, and ocean acidification- and warming-driven changes \r [...]"


id: 462497865b46f18ee105813938bb94c
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 9558
content:
"[...] in planktonic speciation and interactions can promote additional food\u0002web bioaccumulation of methylmercury (Tada and Marumoto, 2020; \r Wu et al., 2020b; Zhang et al., 2020b; Zhang et al., 2021a). Interactions \r among drivers also matter: temperature plus overfishing increased \r tissue methylmercury concentrations in Atlantic bluefin tuna from \r the 1970s to the 2000s more than the decreases in the late 1990s \r and 2000s from lower environmental mercury levels (Schartup et al., \r 2019). This appears true for persistent organic pollutants as well, but \r their bioaccumulation is related more to temperature effects on animal \r behaviour than on pollutant dynamics (Houde et  al., 2019; Wagner \r et  al., 2019; Kalia et  al., 2021). By 2100 under RCP8.5, productivity \r changes and community structure shifts are expected to increase \r methylmercury concentrations in polar oceans and high-latitude \r phytoplankton and decrease it in low latitudes (Zhang et al., 2021a). \r [...]"


id: dcb711336d5f8ae5ed2aed947e93427b
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index: climate_gpt_v2
vector_id: 36092
content:
"[...] The estimated average global cost of mercury-related health effects by \r 2050, mainly from seafood consumption during 2010-2050, will be \r 19 trillion USD (2020), assuming a 3% discount rate, if methylmercury \r emissions are not reduced (Zhang et al., 2021b).\r Since previous assessments, evidence has increased that climate \r impacts, such as warming, extreme weather and SLR, are increasing "


id: e179b3038663c804a719abe9ef4af5da
created_at: 2023-04-19 13:22:53
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content_type: text
index: climate_gpt_v2
vector_id: 36939
content:
"Climate-driven changes in temperature, salinity (from ice melt and \r precipitation changes), deoxygenation and ocean acidification can \r alter dynamics of infectious diseases that target ocean and coastal \r species by increasing hosts' susceptibility or pathogens' abundance \r or virulence (high confidence) (Burge and Hershberger, 2020; Byers, \r 2021). Coral and urchin diseases have increased over time driven \r by warming-related declines in organism recovery and survival or \r immunity (medium confidence) (Cohen et al., 2018; Tracy et al., 2019). \r Seagrass and sea star wasting disease outbreaks have occurred \r under combinations of ocean warming or MHWs and non-climate \r drivers (e.g., eutrophication, bottom trawling), but attribution of \r these outbreaks to specific drivers is still not resolved (Harvell et al., \r 2019; Jakobsson-Thor et al., 2020; Krause-Jensen et al., 2021). Disease \r outbreaks threaten marine biodiversity, species that create habitat or \r [...]"


id: 1031f8621f11d3f67685034ec6869682
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 36
content:
"[...] dampen wave action, and keystone species (Harvell and Lamb, 2020). \r Attributing observed changes in marine disease patterns to climate \r remains extremely difficult owing to interacting climate and non\u0002climate drivers (Burge and Hershberger, 2020) and lack of baseline \r data (Tracy et al., 2019). Projected increases in the frequency, duration \r and intensity of warming events would reduce survival and recovery \r of some species from hot events, reduce immunity of other species to \r pathogens, extend poleward ranges of some pathogens and increase \r infection risk when host species congregate in scarce habitat (Cohen \r et al., 2018). Pathogens that target ocean and coastal organisms may \r themselves be sensitive to future climate conditions or subsequent "


id: fa271c79ecc5f56a0dccbe50a58407be
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 41381
content:
"New examples have illustrated how toxic HABs interfere with regulating, \r provisioning (Section 3.5.3) and cultural ecosystem services (Section 3.5.6) \r in interconnected ways (limited evidence, high agreement). A massive \r toxic Pseudo-nitzschia spp. bloom in 2013-2016 along the USA West \r Coast triggered Dungeness crab, rock crab and razor clam fishery \r closures to protect human consumers (Sections 3.6.2, 3.6.3.1.5; McCabe \r et al., 2016), and this disproportionately harmed fishers, especially small\u0002vessel owners, and fishing-support service industries, primarily through \r lost revenue (Ritzman et al., 2018; Moore et al., 2019; Trainer et al., 2019; \r Jardine et al., 2020; Moore et al., 2020a). Toxic Alexandrium spp. blooms \r promoted by climate-driven coastal extremes (e.g., MHWs, stratification, \r runoff) in Tasmania, Australia, in 2012 and Chile in 2016 caused fish kills, \r shellfish product recalls, substantial economic losses, and human sickness \r [...]"


id: e0f4d4228feecd1b21e70a82d3f7977b
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 36841
content:
"[...] and death (Trainer et al., 2019). The Chile event caused an estimated loss \r of 800 million USD in the farmed salmon industry (Diaz et al., 2019) \r and resulted in a series of large, long-lasting regional protests calling \r for national aid (Delgado et al., 2019). New evidence, however, suggests \r that the perceived global increase in harmful algal blooms results from \r better monitoring and more detrimental bloom impacts, rather than a \r climate-linked mechanism (Hallegraeff et al., 2021)."


id: 21be61536ee43094c2d4e2a04cc94021
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 3150
content:
"Coastal ecosystems physically protect people and property from storms \r and flooding, and climate change threatens this protection function \r (Figure  3.22; Table  3.26). Increasingly detailed models show how \r warm-water coral reefs (Reguero et  al., 2019; Storlazzi et  al., 2019; \r Reguero et al., 2021) mangroves (Blankespoor et al., 2017; Menendez \r et  al., 2020; Tregarot et  al., 2021) and wetlands (Sun and Carson, \r 2020) prevent billions of US dollars of direct and indirect damage to \r private and public property and shield millions of people from flooding \r each year. Protection by mangroves provides more economic benefits \r in higher-income nations and shields more people in lower-income \r nations (Menendez et  al., 2020). Seagrasses (James et  al., 2020; \r James et al., 2021), kelp (Morris et al., 2020b; Zhu, 2020), suspended \r shellfish aquaculture (Gentry et al., 2020; Zhu et al., 2020a), oyster reefs \r [...]"


id: 4cf8efb96818ce0653b45e0690075ad6
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content_type: text
index: climate_gpt_v2
vector_id: 10815
content:
"[...] (Chowdhury et al., 2019), coastal wetlands (Moller, 2019; Keimer et al., \r 2021) and sandy coastlines (Section 3.4.2.6) Herivaux et al., 2018) also \r measurably decrease wave energy. Non-climate drivers [e.g., invasive \r species (James et al., 2020), sediment-supply changes (Ganju, 2019; Ladd \r et al., 2019; Ilia, 2020), erosion and storm damage (Mehvar et al., 2019; \r Bacopoulos and Clark, 2021)], acting together with climate-induced \r drivers and associated impacts [e.g., SLR (Cross-Chapter  Box  SLR in \r Chapter 3), changes in plant biodiversity (Section 3.5.2; Lee Smee, 2019; \r Silliman et al., 2019; Schoutens et al., 2020), MHWs (Section 3.4.3.7) \r and acidification (Section 3.4.2.1)], compromise physical protection by \r coastal ecosystems (very high confidence). (See Cross-Chapter Box SLR \r in Chapter  3 and Sections  3.6.3.1 and 3.6.3.2.2 for assessment of \r adaptations that address this ecosystem service.)"


id: 39185bb0aaa86a6e91a614285ec81234
created_at: 2023-04-19 13:22:53
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content_type: text
index: climate_gpt_v2
vector_id: 7251
content:
"Natural and engineered systems have long been used effectively \r to manage precipitation and wastewater safely (see  Box  4.5), and \r maintaining and enhancing them is a key nature-based adaptation \r strategy for coastal communities (Section 3.6.2.3; Cross-Chapter Paper \r 2). Estimated values of water purification and stormwater management \r provided by coastal ecosystems are in the hundreds to thousands \r of USD per hectare [e.g., 272  Euro per 0.01 km2\r   yr-1 from the \r Mediterranean's sandy coastline (Herivaux et  al., 2018); 1100-2800 \r USD per 0.01 km2\r   yr-1 from the state of Maryland, USA (Campbell \r et al., 2020b); 600 USD per 0.01 km2\r  yr-1 in Zhuzhou City, China (Zhan \r et al., 2020)]. Both wild and cultured organisms also provide filtration \r services. Seagrasses' ability to purify water is well recognised by coastal \r residents and ocean resource users in tropical and temperate locations \r (Ambo-Rappe et al., 2019; Quevedo et al., 2020; Heckwolf et al., 2021; \r [...]"


id: aebc44c3728b12d2ef61609665b8b874
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index: climate_gpt_v2
vector_id: 27980
content:
"[...] McKenzie et  al., 2021a). Globally, aquacultured shellfish remove an \r estimated 49,000 tonnes of nitrogen and 6000 tonnes of phosphorus \r from coastal waters, worth a potential 1.20 billion USD, and they may \r help improve existing engineered wastewater treatment systems (van \r der Schatte Olivier et al., 2020). Climate change, especially episodic \r extreme rains and RSLR (Romero-Lankao et al., 2014), is challenging \r management and design of wastewater and stormwater systems (high \r confidence) (Flood and Cahoon, 2011; Trtanj et  al., 2016; Hummel \r et al., 2018; Kirshen et al., 2018; Nazarnia et al., 2020; Reznik et al., \r 2020; McKenzie et  al., 2021b) and the integrity of coastal landfills \r (Beaven et al., 2020). Without substantial adaptation that addresses \r projected wastewater management challenges and community needs \r (Section  4.2.6.1; Kirshen et  al., 2018; Kirchhoff and Watson, 2019; \r Kool et al., 2020; Nazarnia et al., 2020; Hughes et al., 2021), coastal \r [...]"


id: 2deed76cb998673a7907cd74087acd6c
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index: climate_gpt_v2
vector_id: 5361
content:
"[...] water quality in many areas will decrease because of more frequent \r or severe releases of untreated wastes (high confidence) (Flood and \r Cahoon, 2011; Hummel et  al., 2018; Hughes et  al., 2021; McKenzie \r et al., 2021b), and this will have harmful consequences for human and "


id: 96918fd3fc579dd7388b5c48fe1f9a55
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
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content:
"Current and future total carbon storage and cycling in the ocean are \r governed by past and future CO2 emissions trajectories (Table 3.26), \r but regional ocean and coastal carbon stocks and cycling vary over \r time and space due to processes being altered by climate, including \r ocean circulation, sea ice cover, coastal upwelling and thermal \r stratification (Section 3.2.2.3); ocean primary production and export \r (Sections  3.2.3, 3.4.4); and marine ecosystem biodiversity (high \r confidence) (Section 3.5.2; Figure 3.22). Quantifying regional carbon \r fluxes and stocks is still challenging and relies on indirect measures \r (e.g., Fennel et  al., 2019; Clay et  al., 2020), especially in coastal \r ecosystems where drivers interact. Carbon cycling and storage co\u0002occurs with other regulating services such as habitat provision, \r water-quality maintenance and coastal protection (Ouyang et  al., \r 2018), particularly in vegetated coastal ecosystems (see Box  3.4). \r [...]"


id: 6f97d40f24b060d314f3cf5ea540ab52
created_at: 2023-04-19 13:22:53
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content:
"[...] Adaptations to support regional carbon cycling and storage generally \r focus on area-based management and conservation (Section 3.6.3.2), \r but interventions to enhance ocean carbon storage are being explored \r for mitigation (WGIII AR6 Chapter 7)."


id: 67f7322dd1e142cf46e68892912fde9c
created_at: 2023-04-19 13:22:53
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content:
"Climate change and other anthropogenic drivers, including eutrophication, land-use changes and overexploitation, directly and indirectly \r threaten blue carbon ecosystems (Annex II: Glossary). Commonly considered blue carbon ecosystems include vegetated coastal ecosystems \r (Sections 3.4.2.3-3.4.2.5), whose mangroves, salt marshes and seagrass beds host rooted, vascular plants known to store large amounts of \r carbon for long periods and to be amenable to management (Lovelock and Duarte, 2019). Other ocean and coastal taxa, including rooted \r or floating macroalgae (e.g., non-vascular multicellular kelp or seaweed genera such as Macrocystis spp., Sargassum spp. or Laminaria spp. \r (Filbee-Dexter and Wernberg, 2020), phytoplankton and even pelagic fauna (e.g., finfish or whales; Chami et al., 2019), have also been \r proposed as blue carbon ecosystems. Terrestrial vascular-plant-derived material can also carry and store significant amounts of carbon in \r [...]"


id: 10e90949649cfbd520a08f0013e17a9c
created_at: 2023-04-19 13:22:53
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content:
"[...] marine environments (Cragg et al., 2020). There is increasing evidence about the coverage and carbon content of macroalgal, planktonic \r and faunal taxa, but low agreement about their long-term carbon-storage potential and manageability (Alongi, 2018b; Wernberg and \r Filbee-Dexter, 2018; Lovelock and Duarte, 2019; Ortega et al., 2019; Pfister et al., 2019; Queiros et al., 2019; Filbee-Dexter et al., 2020a; \r Gallagher, 2020; Mariani et al., 2020; Thorhaug et al., 2020; van Son et al., 2020; Bach et al., 2021; Bayley et al., 2021; Cavanagh et al., 2021; \r Frontier et al., 2021; Martin et al., 2021; Pedersen et al., 2021; Weigel and Pfister, 2021). This section focuses on the array of ecosystem \r services and adaptation opportunities provided by vegetated coastal blue carbon ecosystems, where consensus and evidence are most \r abundant. Mitigation potential of blue carbon ecosystems is assessed with land-based mitigation options in WGIII AR6 Section 7.4."


id: 71b562a9633277117cec4eb3ad8abebf
created_at: 2023-04-19 13:22:53
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content:
"Carbon storage and burial in mangroves, salt marshes and seagrass meadows (see Table Box 3.4.1) help regulate ocean and coastal carbon \r cycling and may contribute to nature-based mitigation, although regional estimates vary widely based on climatic and edaphic conditions \r (WGIII AR6 Section  7.4). In addition, coastal vegetated ecosystems provide substantial and interdependent regulating, provisioning \r and cultural ecosystem services. These services include: (a) disproportionately high biodiversity per unit area (Portner et al., 2021a); \r (b) abundant habitat (Section 3.5.5.1) and nurseries for aquatic, terrestrial, aerial and microbial species; (c) natural filtration of waste \r and stormwater runoff into the coastal ocean (Sections 3.5.5.3, 4.2.7; Cross-Chapter Box ILLNESS in Chapter 2); (d) coastal protection \r (Section 3.5.5.4; Ouyang et al., 2018; Quevedo et al., 2020); (e) food and natural materials (Sections 3.5.3, 3.5.4); and (f) support for \r [...]"


id: d938472142807e707998ec5b40bbe505
created_at: 2023-04-19 13:22:53
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content:
"[...] tourism, livelihoods and cultural activities (Section  3.5.6). Global estimates of services provided by coastal blue carbon ecosystems \r depend on the quality of available mapping, which is currently best developed for mangroves (Macreadie et al., 2019), and improving for \r salt marshes and seagrasses (McOwen et al., 2017; McKenzie et al., 2020; Young et al., 2021)."


id: 965ae4560bf209fd10eadd6123eaf47f
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
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content:
"Coastal vegetated ecosystems are vulnerable to harm from multiple climate-induced and non-climate drivers, and together these have \r reduced wetland area globally (high confidence) (Section 3.4.2.5) and endangered the services provided by these ecosystems (high \r confidence). Loss of coastal vegetated ecosystems changes biodiversity (Sections 3.5.2, 3.4.2.3-3.4.2.5; Numbere, 2019; Parreira et al., \r 2021), increases risk of damage and erosion from SLR and storms (Sections 3.4.2.3-3.4.2.5; Cross-Chapter Box SLR in Chapter 3; Galeano \r et al., 2017) and impacts provisioning (Sections 3.5.3-3.5.4; Li et al., 2018b; Maina et al., 2021). These changes also strongly determine \r the quantity and longevity of blue carbon storage (high confidence) (Macreadie et al., 2019; Lovelock and Reef, 2020). Specific site \r characteristics and ecosystem responses to climate change will determine future local blue carbon storage or loss (high confidence) (see \r [...]"


id: 240582b8c986d35c3e38098ee98805c8
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"[...] Table Box 3.4.2). For instance, poleward migration of mangroves to areas dominated by salt marshes is expected to increase carbon "


id: b021e2f5b3b229cfaa493dc53d4811ea
created_at: 2023-04-19 13:22:53
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content:
"storage (Kelleway et al., 2016); however, this change in the dominant vegetation and associated faunal changes can modify carbon stocks \r and sequestration, as well as other ecosystem services (Martinetto et al., 2016; Kelleway et al., 2017; Smee et al., 2017; Macreadie et al., \r 2019; Macy et al., 2019). Landward range expansion of mangroves, marshes and seagrass in response to gradual RSLR can enhance \r carbon sequestration (Section 3.4.2.5; Cross-Chapter Box SLR in Chapter 3; Macreadie et al., 2019), but coastal squeeze can limit this \r (Phan et al., 2015; Schuerch et al., 2018) and RSLR can either submerge and bury or erode and release stored blue carbon (Section 3.4.2.5; \r Macreadie et al., 2019; Lovelock and Reef, 2020). Gains and losses of mangrove habitat area (and therefore carbon storage) projected for \r nations under RCP4.5 and RCP8.5 depend primarily on the combination of SLR rate, adaptation scenario (including coastal development) \r [...]"


id: 686c83a0c638c6c3e7c8abcaad47830d
created_at: 2023-04-19 13:22:53
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vector_id: 15638
content:
"[...] and island or continental status (Lovelock and Reef, 2020). The influence of warming, MHWs and acidification on seagrass meadows \r (Kendrick et al., 2019; Strydom et al., 2020), and associated coralligenous reefs (Zunino et al., 2019), suggests that future warming and \r especially MHWs will cause more widespread loss of services from these ecosystems (Section 3.4.2.5). Loss of blue carbon ecosystems \r will not only halt carbon storage but also release stored carbon: emissions after 2000 due to global mangrove deforestation have been \r estimated at 23.5-38.7 Tg Cyr-1 (Ouyang and Lee, 2020). Mitigation estimates for avoided conversion and restoration of coastal wetlands \r and the implications of the impacts of climate change are assessed in WGIII AR6 Section 7.4."


id: 6799d1c7d59c8d0ad9c8c70079f8e779
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content:
"To date, initiatives aiming to restore coastal wetland ecosystems primarily address ecosystem characteristics other than carbon storage \r (Herr et al., 2017; de los Santos et al., 2019; Lovelock and Duarte, 2019; Friess et al., 2020a). But recovery of coastal vegetated ecosystems is \r expected to bring back the full suite of ecosystem services they provide, not just carbon storage (medium confidence) (Marba et al., 2015a; \r Burden et al., 2019; Friess et al., 2020a), making coastal restoration a low-risk action that offers both adaptation and mitigation benefits \r (Steven et al., 2020; Gattuso et al., 2021). Successful restoration requires using appropriate plant species in suitable environmental settings \r (Wodehouse and Rayment, 2019; Friess et al., 2020a) with favourable geomorphology and biophysical conditions (Cameron et al., 2019; Ochoa\u0002Gomez et al., 2019) and considering social, economic, policy and operational constraints (Section 3.6.3.2.2; Cross-Chapter Box NATURAL in \r [...]"


id: e3ccd788d0b7744283b5efdf68f2a527
created_at: 2023-04-19 13:22:53
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content:
"[...] Chapter 2), now and in the future (high confidence) (Duarte et al., 2020; Lovelock and Reef, 2020). Nevertheless, restored spaces may not \r store carbon at rates equal to those of undisturbed spaces (Yang et al., 2020), and it may take decades to determine or achieve carbon-storage \r outcomes of restoration (Sasmito et al., 2019; Duarte et al., 2020; Oreska et al., 2020). Integration improves efforts to restore or conserve \r coastal wetland ecosystems to accomplish both adaptation and mitigation outcomes (Steven et al., 2020). Government-led conservation of \r blue carbon ecosystems as part of national and subnational climate strategies (e.g., Friess et al., 2020a; Kelleway et al., 2020; Wedding et al., \r 2021) benefits from coordination with private activities, such as incentivising conservation with payments for ecosystem services (Muenzel \r [...]"


id: 19e9fb14dfd0c6fea8aa3fa9b54d7346
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content:
"[...] and Martino, 2018; Friess et al., 2020a). Moreover, successful area-based protection measures consider both environmental and social issues \r (Section 3.6.3.2). Continued integration and alignment of policies at international to local levels (Section 3.6.5) will also support achieving \r the adaptation and mitigation benefit of blue carbon spaces (Friess et al., 2020a; Steven et al., 2020; Wu et al., 2020a)."


id: 1eb2f13dccf44979bf7c62bba25c55b7
created_at: 2023-04-19 13:22:53
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content:
"Cultural services provided by ocean and coastal ecosystems help maintain \r psychological well-being, cultural development, human identities, \r educational opportunities and reserves that could support development \r of future goods or activities (Table 3.25). Most recent studies of ocean \r and coastal cultural services simply detail local benefits using replicable \r methods (e.g., Drakou et al., 2018; Folkersen, 2018; Forster et al., 2019; \r Lau et al., 2019; Pouso et al., 2019; Weitzman, 2019; Yang et al., 2019), \r focusing on diverse ocean and coastal environments and ecosystems \r (Jobstvogt et al., 2014; Balzan et al., 2018; Drakou et al., 2018; Ingram \r et al., 2018; Pouso et al., 2018; Zapata et al., 2018; Ghermandi et al., \r 2019; Pouso et al., 2019; Tanner et al., 2019; Turner et al., 2019; Ortiz \r Linan and Vazquez Solis, 2021). Cultural ecosystem services may directly \r benefit from marine development activities, such as marine aquaculture \r [...]"


id: 5861b3f603e479cdf783fad2ce5ae9eb
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"[...] (e.g., Alleway et al., 2018), and indirectly benefit from marine activities \r that increase biodiversity (e.g., Causon and Gill, 2018). Cultural services \r are generally quantified using interviews and revealed-preference or \r stated-preference valuation (National Research Council, 2005; Sangha \r et  al., 2019), but people often are especially reluctant to evaluate \r cultural ecosystem services in monetary terms, given the spiritual and \r community linkages to these services (Oleson et al., 2018)."


id: 44b2dc497c22fd255dd73a14a9d057c5
created_at: 2023-04-19 13:22:53
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content:
"Observed disruption of ocean and coastal cultural services by climate \r impacts, plus increasingly severe and widespread projected climate\u0002change impacts on ocean and coastal ecosystems, imply that the risk \r to cultural ecosystem services will remain constant or even increase \r (medium confidence) (Figure 3.22; Table 3.26). Recent studies assert \r that cultural ecosystem services are at risk from climate change (high \r confidence) (Singh et al., 2019a; Koenigstein, 2020). However, limited \r evidence and complex social-ecological interactions (e.g., Ingram et al., \r 2018) challenge development of specific projections. For instance, the \r little auk (Alle alle) in the North Water Polynya is traditionally harvested \r by Indigenous Inughuit for food and community-wide celebrations and \r seasonal activities, but harvests are threatened to an undetermined \r degree as the seabird competes for food with recovering bowhead \r whale (Balaena mysticetus) populations and northward range shifts \r [...]"


id: 194eb599bd705ffee695d77f4379a7af
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
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content:
"[...] of capelin (Mallotus villosus) due to warming (Mosbech et al., 2018). \r Section 3.6 assesses the cultural implications of implemented human \r adaptations."


id: a4f0d8c990384b045d45721dd8e9197e
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content:
"Additional evidence since previous assessments (Table 3.26) confirms \r that climate-change impacts on ocean and coastal cultural ecosystem \r services have already disrupted people's place-based emotional \r attachments and cultural activities (limited evidence, high agreement) \r (Figure  3.22). Bleaching and mortality of corals in the Great Barrier \r Reef have induced measurable 'reef grief', a type of solastalgia, among \r reef visitors and researchers (Conroy, 2019; Curnock et  al., 2019; \r Marshall et al., 2019). The mental health of people in Tuvalu (Gibson \r et  al., 2020), Alaska (Allen, 2020) and Honduras (Kent and Brondo, \r 2020) have suffered from both the experience of climate impacts \r on ocean and coastal ecosystems (e.g., SLR and changes in fisheries \r and wildlife), and the anticipation of more in the future. The climate\u0002associated MHWs and harmful algal bloom events in 2014-2016 in \r the US Pacific Northwest (Moore et al., 2019) prevented seasonal razor \r [...]"


id: 1e5b1a0454a06dc89e6a6e3f13118321
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content:
"[...] clam harvests culturally important to Indigenous Peoples and the local \r community (Section 3.5.5.3; Crosman et al., 2019). Sea level rise and \r storm-driven coastal erosion endanger coastal archaeological and \r heritage sites around the world (very high confidence) (Hoque and \r Hoque, 2008; Carmichael et al., 2018; Reimann et al., 2018; Elliott and \r Williams, 2019; Ravanelli et  al., 2019; Anzidei et  al., 2020; Chemeli \r et al., 2020; Garcia Sanchez et al., 2020; Harkin et al., 2020; Hil, 2020; \r Rivera-Collazo, 2020)."


id: 9c212c5520d694f844af4263e3eff97c
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
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content:
"Human adaptation comprises an array of measures (adaptation options; \r IPCC, 2014a) that modulate harm or exploit opportunities from climate \r change (Section  1.2.1.3). Adaptation options that respond to key \r ocean and coastal risks (Section 3.4) focus on individuals, livelihoods \r and economic sectors that benefit from ocean and coastal ecosystem \r services (Section 3.5). AR5 concluded that local adaptation measures \r would not alone be enough to offset global effects of increased \r climate change on marine and coastal ecosystems, and that mitigation \r of emissions would also be necessary (high confidence) (Table 3.27; \r Portner et  al., 2014; Oppenheimer et  al., 2019). SROCC assessed \r that ecosystem-based adaptation, including MPAs (high confidence) \r (Bindoff et  al., 2019a) and adaptive management, are effective to \r reduce climate-change impacts (IPCC, 2018; IPCC, 2019b), but that \r existing marine governance is insufficient to provide an effective \r [...]"


id: 1c34b6578c71aa2c8355bdf3a3268bc5
created_at: 2023-04-19 13:22:53
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content:
"Increasing evidence shows that an effective solution portfolio includes \r social and institutional adaptation (Figure 3.23, top; Table 3.28). Social \r adaptation to climate change is already occurring, as people use \r strategies ranging from accommodating change, to coping, adapting \r and transforming their livelihoods (Bene and Doyen, 2018; Fedele \r et al., 2019; Galappaththi et al., 2019; Barnes et al., 2020; Ojea et al., \r 2020; Green et al., 2021c). Although management and institutions have \r major roles in adaptation (Gaines et al., 2018; Barange, 2019), marine \r governance is impeded by increasing numbers of often-competing \r users and uses (Boyes and Elliott, 2014); sector-led, fragmented efforts \r (Nunan et al., 2020); and a legal framework less clear than those on \r land (Crespo et al., 2019; Guggisberg, 2019). Future social responses \r depend on warming levels and on the institutional, socioeconomic \r and cultural constructs that allow or limit livelihood changes (medium \r [...]"


id: 43426b3099c8414fc786a84b4dab240f
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index: climate_gpt_v2
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"[...] confidence) (Chapter 18; Galappaththi et al., 2019; Ford et al., 2020; \r Green et  al., 2021c). Both social and institutional transformations \r are needed to change the structures of power, culture, politics and/\r or identity associated with marine ecosystems (Section 1.5.2; Wilson \r et  al., 2020b). Ideally, institutional and social adaptation will work \r together to sustain knowledge systems and education, enhance \r participation and social inclusion, facilitate livelihood support and \r transformational change of dependent coastal communities, provide \r economic and financial instruments, and include polycentric and multi\u0002level governance of transboundary management (Fedele et al., 2019; \r Fulton et al., 2019)."


id: 606cbb850985405919aa09e54aaf4768
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"The vulnerability of communities to losses in marine ecosystem services varies within and among communities. \r Tourists seeking to replace lost cultural services can adapt by engaging in the activity elsewhere. But communities \r who depend on tourism for income or who have strong cultural identity linked to the ocean have a more \r difficult time. Furthermore, climate-change impacts exacerbate existing inequalities already experienced by some \r communities, including Indigenous Peoples, Pacific Island countries and territories and marginalised peoples, such \r as migrants and women in fisheries and mariculture. These inequities increase the risk to their fundamental human \r rights by disrupting livelihoods and food security, while leading to loss of social, economic and cultural rights. \r These maladaptive outcomes can be avoided by securing tenure and access rights to resources and territories for \r [...]"


id: ce1a959dab86e6df5760ba62fb274adf
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content:
"[...] all people depending on the ocean, and by supporting decision-making processes that are just, participatory and \r equitable."


id: 2fb979510a71e8028cdef9215a2396b5
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index: climate_gpt_v2
vector_id: 5653
content:
"Engineering and technology support marine and coastal adaptation \r (Table  3.29). Built infrastructure includes engineered solutions that \r protect, accommodate or relocate coastal assets using hard engineering, \r like seawalls, and soft engineering, such as beach and shore nourishment \r (Cross-Chapter Box SLR in Chapter 3). Technological tools include early\u0002warning systems for extreme events (Bindoff et al., 2019a; Collins et al., \r 2019a), improved forecast and hindcast models (Winter et  al., 2020; \r Davidson et  al., 2021; Spillman and Smith, 2021) and environmental \r monitoring (Claudet et  al., 2020a; Wilson et  al., 2020a; Melbourne\u0002Thomas et al., 2021) that support informed decision making (Tommasi \r et  al., 2017; Rilov et  al., 2020; A. Maureaud et  al., 2021). Emerging \r adaptation technologies, such as habitat development, active restoration \r and assisted evolution (Bostrom-Einarsson et al., 2020; Kleypas et al., \r [...]"


id: d6ad0bd4344065d0acd5a1816cf437cc
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content:
"[...] 2021), intend to accelerate recovery of damaged ecosystems and \r promote ecological adaptation to climate change (Jones et al., 2018a; \r Bostrom-Einarsson et al., 2020; Kleypas et al., 2021)."


id: 706231b593aa1701debd6be560e92c01
created_at: 2023-04-19 13:22:53
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content_type: text
index: climate_gpt_v2
vector_id: 17030
content:
"The ocean and coastal adaptation portfolio (Figure  3.23) also \r includes marine and coastal NbS (Table 3.30). NbS that contribute \r to climate adaptation, also known as ecosystem-based adaptations \r (EBA), are cross-cutting actions that harness ecosystem functions to \r restore, protect and sustainably manage marine ecosystems facing \r climate-change impacts, while also benefiting social systems and \r human security (Abelson et  al., 2015; Barkdull and Harris, 2019) \r and supporting biodiversity (high confidence) (Annex II: Glossary; \r Cross-Chapter  Box  NATURAL in Chapter  2; Seddon et  al., 2021). \r NbS are expected to contribute to global adaptation and mitigation \r goals (high confidence) (Beck et  al., 2018; Cooley et  al., 2019; \r Hoegh-Guldberg et al., 2019b; Menendez et al., 2020; Morris et al., \r 2020a) by protecting coastal environments from SLR and storms \r (Cross-Chapter  Box  SLR; Reguero et  al., 2018), and by storing \r [...]"


id: 421d807d0512b4d7ac02696919fbd3fb
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content:
"[...] substantial quantities of carbon (Sections  3.4.2.5, 3.6.3.1.5; WGIII \r AR6 Chapter 7; Howard et al., 2017; Chow, 2018; Smale et al., 2018; "


id: 88d0511cc4a5485d0b7695e42f9495a4
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 21233
content:
"Since SROCC, coastal adaptation using NbS, like restoration of coastal \r vegetation, has advanced substantially (Cohen-Shacham et al., 2019; \r Kuhl et al., 2020; Kumar et al., 2020; Morris et al., 2020a). Field and \r modelling studies confirm that wetland restoration and preservation \r are key actions to restore coastal protection and reduce community \r vulnerability to flooding (very high confidence) (see also Section 3.6; \r Chapter  15; Cross-Chapter  Box  SLR in Chapter  3; Jones et  al., 2020; \r Menendez et al., 2020; Van Coppenolle and Temmerman, 2020), while \r maintaining coastal ecosystem services (Section  3.5). Restoring coral \r reefs, oyster reefs and mangroves (Section  3.6.2.1) and protecting \r macrophyte meadows dissipates wave energy (Section  3.4.2.1; Yates \r et  al., 2017; Beck et  al., 2018; Wiberg et  al., 2019; Menendez et  al., \r 2020), accretes sediment and elevate shorelines, which reduces \r exposure to waves and storm surges, and offsets erosional losses \r [...]"


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"[...] (medium confidence) (Kench and Mann, 2017; Pomeroy et  al., 2018; \r Dasgupta et al., 2019; James et al., 2019; Morris et al., 2019; David and \r Schlurmann, 2020; Masselink et al., 2020). However, irreversible regime \r shifts in ocean ecosystems due to SLR and extreme events, such as MHWs, \r can limit or compromise restoration in the long term (high confidence) \r (Section 3.4.3.3.3; Cross-Chapter Box SLR in Chapter 3; Marzloff et al., \r 2016; Johnson et  al., 2017a). Under all warming scenarios, coastal \r wetlands will be impacted by warming and MHWs (Sections 3.2.2.1, \r 3.2.4.5; Cross-Chapter  Box  9.1 in WGI Chapter  9; Fox-Kemper et  al., \r 2021), while also being pressed inland by RSLR (Section 3.4.2.5; Cross\u0002Chapter Box SLR in Chapter 3). Therefore, restoration and conservation \r are more successful when non-climate drivers are also minimised (high \r confidence) (Brodie et al., 2020; Duarte et al., 2020; Liu et al., 2021)."


id: d20a74330c68b7bef43109e036051c4
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
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"Mobility allows fishing fleets and fishers to adapt to shifts in marine \r species distributions (high agreement) (Sections 3.4.3.1, 3.5.3; Peck \r and Pinnegar, 2018; Pinsky et al., 2018; Frazao Santos et al., 2020) \r but with limits and unintended consequences (Pinsky and Fogarty, \r 2012; Bell et  al., 2021). Diversification of target species, harvest \r tactics and employment sectors, including transitions from fisheries \r to mariculture and ecotourism, allows some fishers to accommodate \r some impacts on their livelihoods (Miller et al., 2018; Robinson et al., \r 2020; Gonzalez-Mon et  al., 2021). Technology and infrastructure \r adaptations can improve marine harvest efficiency, reduce risk and \r support resource management goals (Friedman et al., 2020; Bell et al., \r 2021; Melbourne-Thomas et al., 2021), but their ability to overcome \r climate-change impacts remains uncertain (Bell et  al., 2020). \r Improving capacity to predict anomalous conditions in coastal and \r [...]"


id: c67ae4e30b660a2d3cf3850c37c804e6
created_at: 2023-04-19 13:22:53
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content:
"[...] marine ecosystems (Jacox et al., 2019; Holbrook et al., 2020; Jacox \r et al., 2020), storm-driven flooding in reef-lined coasts (Scott et al., \r 2020; Winter et  al., 2020) and fisheries stocks (Payne et  al., 2017; \r Tommasi et  al., 2017; Muhling et  al., 2018) can improve forecasts \r of coastal and marine resources; these can enhance sustainability \r of wild-capture fisheries under climate change (high confidence) \r (Blanchard et  al., 2017; Tommasi et  al., 2017; Pinsky et  al., 2020a; \r Bell et  al., 2021). Limiting overexploitation is the central goal of \r fishery management, and it very likely benefits fisheries adaptation \r to climate change (Burden and Fujita, 2019; Free et al., 2019; Sumaila "


id: 8fd6ee7449d9e4a1492072211a9e22f1
created_at: 2023-04-19 13:22:53
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"The rate of global mean SLR was 1.35 mm yr-1 (0.78-1.92 mm yr-1, very likely range) during 1901-1990, faster than during any century \r in at least 3000 years (high confidence) (WGI AR6 Chapter 9; Stanley and Warne, 1994; Woodroffe et al., 2016; Fox-Kemper et al., 2021). \r Global mean SLR has accelerated to 3.25 mm yr-1 (2.88-3.61 mm yr-1, very likely range) during 1993-2018 (high confidence). Extreme \r sea levels have increased consistently across most regions (WGI AR6 Chapter 9; Fox-Kemper et al., 2021). The largest observed changes \r in coastal ecosystems are being caused by the concurrence of human activities, waves, current-induced sediment transport and extreme \r storm events (medium confidence) (Chapters 3, 15, 16; Takayabu et al., 2015; Mentaschi et al., 2018; Duvat, 2019; Murray et al., 2019; \r Oppenheimer et al., 2019). Early impacts of accelerating SLR detected at sheltered or subsiding coasts include chronic flooding at high tides, \r [...]"


id: b3fd385fe5b8739b64899667de85588b
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 28908
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"[...] wetland salinisation and ecosystem transitions, increased erosion and coastal flood damage (Chapters 3, 11, 13-16; WGI AR6 Chapter 9; \r Sweet and Park, 2014; Moftakhari et al., 2015; Nunn et al., 2017; Oppenheimer et al., 2019; Sharples et al., 2020; Fox-Kemper et al., 2021; \r Strauss et al., 2021). The exposure of many coastal populations and ecosystems to SLR is high: economic development is disproportionately \r concentrated in and around coastal cities and settlements (virtually certain) (Chapters 3, 9-15; Cross-Chapter Papers 2, 4)."


id: 75c216ee7e9fc3d73bc0e7edb77b2ed1
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
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"Risks from SLR are very likely to increase by one order of magnitude well before 2100 without adaptation and mitigation action as \r agreed by parties to the Paris Agreement (very high confidence). Global mean SLR is likely to continue accelerating under SSP1-2.6 and \r more strongly forced scenarios (Figure BoxSLR1; WGI AR6 Chapter 9; Oppenheimer et al., 2019; Fox-Kemper et al., 2021), increasing the \r risk of chronic coastal flooding at high tide, serious flooding during extreme events such as swells, storms and hurricanes, and erosion, \r and coastal ecosystem losses across many low-lying and erodible coasts (very high confidence) (Chapters 3, 9-15; Cross-Chapter Paper \r 2; Hinkel et al., 2014; McLachlan and Defeo, 2018; Kulp and Strauss, 2019; Vousdoukas et al., 2020b). The compounding of rainfall, river \r flooding, rising water tables, coastal surges and waves are projected to exacerbate SLR impacts on low-lying areas and rivers further \r [...]"


id: df98efa2d7e87ae1069dd10a444e1517
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
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content:
"There is high confidence that coastal risks will increase by at least one order of magnitude over the 21st century due to committed SLR \r (Hinkel et al., 2013; Hinkel et al., 2014; IPCC, 2019b). Exposure of population and economic assets to coastal hazards is projected to \r increase over the next decades, particularly in coastal regions with fast-growing populations in Africa, Southeast Asia and Small Islands \r (medium evidence) (Chapters 9-15; Cross-Chapter Papers 2, 4; Neumann et al., 2015; Jones and O'Neill, 2016; Merkens et al., 2016; \r Merkens et al., 2018; Rasmussen et al., 2020). For RCP8.5, 2.5-9% of the global population and 12-20% of the global gross domestic \r product is projected to be exposed to coastal flooding by 2100 (Kulp and Strauss, 2019; Kirezci et al., 2020; Rohmer et al., 2021). Above \r 3degC global warming levels (GWL) and with low adaptation, SLR may cause disruptions to ports and coastal infrastructure (Camus et al., \r [...]"


id: fc6f987a0d575796df0d9fa456a88283
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
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content:
"[...] 2019; Christodoulou et al., 2019; Verschuur et al., 2020; Yesudian and Dawson, 2021), which in turn may cascade and amplify across \r sectors and regions, generating impacts to financial systems (Chapters 11, 13; Mandel et al., 2021). Depending on the hydrogeological \r context, SLR causes salinisation of groundwater, estuaries, wetlands and soils, adding constraints to water management and livelihoods \r in agriculture sectors, for example, in deltas (Chapters 9, 15; Cross-Chapter Paper 4; Oppenheimer et al., 2019; Nicholls et al., 2020)."


id: 7ceefe38f03d5893f37cb735e2d93952
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content:
"Under a high-emissions, low-likelihood/high-impact scenario, where low confidence ice-sheet mass loss occurs, global mean SLR could \r exceed the likely range by more than one additional metre in 2100 (Figure BoxSLR1b; Cross-Chapter Box DEEP in Chapter 17; WGI AR6 \r Technical Summary and Chapter 9; Arias et al., 2021; Fox-Kemper et al., 2021). This is a reason for concern given that rapid SLR after the \r last glacial-interglacial transition caused a drowning of coral reefs (high confidence) (Camoin and Webster, 2015; Sanborn et al., 2017; \r Webster et  al., 2018), extensive loss of coastal land and islands, habitats and associated biodiversity (high confidence) (AR6 WGI \r Chapter 9; Fruergaard et al., 2015; Fernandez-Palacios et al., 2016; Hamilton et al., 2019; Helfensdorfer et al., 2019; Kane and Fletcher, \r 2020; Fox-Kemper et al., 2021), and triggered Neolithic migrations in Europe and Australia (medium confidence) (Cross-Chapter Box PALEO \r [...]"


id: 60a532c2cd489966a7fd596633fba40
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
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content:
"Risks can be anticipated, planned and decided upon, and adaptation interventions can be implemented over the coming decades \r considering their often long lead- and lifetimes, irrespective of the large uncertainty about SLR beyond 2050 (high confidence) \r (Figure  BoxSLR1; Cross-Chapter  Box  DEEP in Chapter  17; Cross-Chapter  Paper 2; Chapters  11, 13; Haasnoot et  al., 2018; Stephens \r et al., 2018; Stammer et al., 2019). Adaptation capacity and governance to manage risks from projected SLR typically require decades \r to implement and institutionalise (high confidence) (Chapters 11, 13; Haasnoot et al., 2021). Without considering both short- and long\u0002term adaptation needs, including beyond 2100, communities are increasingly confronted with a shrinking solution space, and adverse \r consequences are disproportionately borne by exposed and socially vulnerable people (Chapters 1, 8). Sea level rise is likely to compound \r [...]"


id: e485fe02ebf4c5f35dcaf36ebcefc6b4
created_at: 2023-04-19 13:22:53
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"Coastal impacts of SLR can be avoided by preventing new development in exposed coastal locations (Chapters 3, 9-15; Cross-Chapter Paper \r 2; Doberstein et al., 2019; Oppenheimer et al., 2019). For existing developments, a range of near-term adaptation options exists, including: \r (a) engineered, sediment- or ecosystem-based protection; (b) accommodation and land-use planning, to reduce the vulnerability of people \r and infrastructure; (c) advance through, for example, land reclamation; and (d) retreat through planned relocation or displacements and \r migrations due to SLR (Chapters 9-15; Cross-Chapter Paper 2; Oppenheimer et al., 2019). Only avoidance and relocation can remove \r coastal risks for the coming decades, while other measures only delay impacts for a time, have increasing residual risk or perpetuate risk \r and create ongoing legacy effects and virtually certain property and ecosystem losses (high confidence) (Cross-Chapter Paper 2; Siders \r [...]"


id: 1200aed9490ec78bbe18f2b297ec159b
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
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content:
"[...] et al., 2019). Large-scale relocation has immense cultural, political, social and economic costs, and equity implications, which can be \r reduced by fast implementation of climate mitigation and adaptation policies (Chapter 8; Cross-Chapter Paper 2; Gibbs, 2015; Haasnoot \r et al., 2021). While relocation may currently appear socially unacceptable, economically inefficient or technically infeasible today (Lincke \r and Hinkel, 2021), it becomes the only feasible option as protection costs become unaffordable and the limits to accommodation become \r obvious (Chapters 11, 13, 15; Hino et al., 2017; Siders et al., 2019; Strauss et al., 2021). Effective responses to rising sea level involve \r locally applicable combinations of decision analysis, land-use planning, public participation and conflict resolution approaches; together \r these can anticipate change and help to chart adaptation pathways, over time addressing the governance challenges due to rising sea \r [...]"


id: 98f3071f21dfee12239dd83345d544f8
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index: climate_gpt_v2
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content:
"Figure Cross-Chapter BoxSLR.1 |  The challenge of coastal adaptation in the era of sea level rise (SLR): (a) typical time scales for the planning, implementation \r (grey triangles) and operational lifetime of current coastal risk-management measures (blue bars); (b) global sea level projections, which are representative of relative SLR \r projected for 60-70% of global shorelines, within +-20% errors (WGI AR6 Chapter 9; Fox-Kemper et al., 2021); (c) frequency of illustrative adaptation decisions to +0.5 m \r of SLR under different SSP-RCP scenarios. In response to accelerated SLR, adaptation either occurs earlier and faster, or accounts for higher amounts of SLR (e.g., to +1 m \r instead of to +0.5 m). Adaptation to +0.5 m from today's sea levels have a lifetime of 90 years for SSP1-2.6, but lifetime is reduced to 60 years for SSP5-8.5 and 30 years \r [...]"


id: 1329bb7fff28e6782a1dd8b147302e8d
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"[...] for a high-end scenario involving low confidence processes. Adaptations to +0.5 m are comparable to, for example, the Thames Barrier in the United Kingdom or the Delta \r Works in the Netherlands, which primarily had an intended lifetime of 100-200 years. Adaptation measures to +0.2 m may include nourishment or wetland or setback zones."


id: ab1ae4abd4877a31badfe749a74a20e2
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
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content:
"There is increasing evidence that current governance and institutional arrangements are unable to address the escalating risks in low\u0002lying coastal areas worldwide (high confidence). Barriers to adaptation, such as decision making driven by short-term thinking or vested \r interests, funding limitations and inadequate financial policies and insurance, can be addressed equitably and sustainably through \r implementation of suites of adaptation options and pathways (Chapters  11, 13, 17-18; Cross-Chapter  Paper 2). Improved coastal \r adaptation governance can be supported by approaches that consider changing risks over time, such as 'dynamic adaptation pathways' \r planning (Chapters  11, 13, 18; Cross-Chapter  Box  DEEP in Chapter  17). Integrated coastal zone management and land-use and \r infrastructure planning are starting to consider SLR by, for example, monitoring early signals (Haasnoot et al., 2018; Stephens et al., 2018; \r [...]"


id: e925c1d6f86c0342bcea3f5b1c6c1bbd
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content:
"[...] Kool et al., 2020), updating sea level projections (Stephens et al., 2017; Hinkel et al., 2019; Kopp et al., 2019; Stammer et al., 2019), \r considering uncertainties of sea level projections and coastal impacts (e.g., Stephens et al., 2017; Jevrejeva et al., 2019; Rohmer et al., \r 2019), as well as engaging with communities, practitioners and scientists, recognising the values of current and future generations (e.g., \r Nicholls et al., 2014; Buchanan et al., 2016b). While there is high agreement that the majority of adaptation needs are not met yet, there \r is robust evidence of SLR increasingly being considered in coastal adaptation decision making and being embedded in national and local \r guidance and regulations (Nicholls et al., 2014; Le Cozannet et al., 2017; Lawrence et al., 2018; Kopp et al., 2019; McEvoy et al., 2021)."


id: f784f6abe56f30711699da082c302f1f
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content:
"and Tai, 2020). Conventional tools include catch and size limits, spatial \r management and adaptive management. Ecosystem-based fisheries \r management outperforms single-species management (Fulton et al., \r 2019), is widely legislated (Bryndum-Buchholz et  al., 2021) and \r can reduce climate impacts in fisheries in the near-term, especially \r under low-emission scenarios (Karp et  al., 2019; Holsman et  al., \r 2020). Transboundary agreements on shifting fisheries will reduce \r the risk of overharvesting (medium confidence) (Gaines et al., 2018). \r Permits tradable across political boundaries could also address this \r challenge, but limited evidence is available regarding their efficacy \r (Cross-Chapter  Box  MOVING SPECIES in Chapter  5; Pinsky et  al., \r 2018). Climate-smart conservation (Section  3.6.32.1) under the \r negotiations on areas beyond national jurisdiction (ABNJ) (Pinsky \r et al., 2018; Tittensor et al., 2019; Frazao Santos et al., 2020), and in \r [...]"


id: 79723b734b39071c8c9e57c5e005d0f8
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"[...] the Convention on Biological Diversity (CBD) areas designed as other \r effective area-based conservation measures (OECMs) (Tittensor et al., \r 2019), provide further benefits. Despite the potential for adaptive \r management to achieve sustainable fisheries, outcomes will very \r likely be inequitable (Gaines et al., 2018; Lam et al., 2020), with lower\u0002income countries suffering the greater biomass and economic losses, \r increasing inequalities, especially under higher-emission scenarios \r (high confidence) (Boyce et  al., 2020). Flexible and polycentric \r governance approaches have facilitated some short-term successes in \r achieving equitable, sustainable fisheries practices, but these may be \r challenging to implement where other governance systems, especially \r hierarchical systems, are well established (Cvitanovic et al., 2018; Bell \r et al., 2020)."


id: 317bbb8fdeaead4dd3e2955e6abd609
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index: climate_gpt_v2
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content:
"Marine ecotourism, integrating conservation, education and provision \r of benefits to local communities (Donohoe and Needham, 2006) can \r provide significant economic benefits (Wabnitz, 2019) and is among \r the most common livelihood alternatives to support both marine \r conservation and climate-change adaptation (Kutzner, 2019; Pham, \r 2020; Prasetyo et al., 2020). Ecotourism can enhance social and political \r will for marine conservation (Cisneros-Montemayor and Sumaila, \r 2014) and facilitates integration of local and Indigenous Peoples in \r employment, ownership and industry governance. The community \r of Cabo Pulmo, Mexico, self-imposed an MPA and replaced fishing \r with ecotourism, which now generates millions of USD yr-1, sustains \r locally owned and operated tour companies and has increased some \r fish populations tenfold (Knowlton, 2020). In Misool, Indonesia, local \r ecotourism incorporates IK by including local communities' preferences \r [...]"


id: 7b2241e62afbab6624d8706a0f2657a5
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 18860
content:
"and NbS (Section 3.6.2.3). Seafood quality and safety are decreasing \r due to climate-driven increases in marine-borne diseases (Cross\u0002Chapter Box ILLNESS in Chapter 2), toxic HABs or toxin bioaccumulation \r (high agreement) (Karagas et al., 2012; Krabbenhoft and Sunderland, \r 2013; Rafaj et  al., 2013; Curtis et  al., 2019; Schartup et  al., 2019; \r Thackray and Sunderland, 2019). Future exposure to seafood-borne \r contaminants also depends partly on consumers' seafood preferences \r (Elsayed et  al., 2020) and seafood supply (Sunderland et  al., 2018). \r Reducing this risk by decreasing seafood consumption increases the risk \r of eating less nutritious foods, and loss of cultural practices (Chapter 5; \r Cross-Chapter Box MOVING SPECIES in Chapter 5; Donatuto et al., 2011; \r Bindoff et  al., 2019a). Models incorporating high-resolution satellite \r images, field survey data, meteorological observations and historical \r [...]"


id: 47ebad0620f590fbd9582a4d2b04f77d
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index: climate_gpt_v2
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content:
"[...] records can provide early-warning forecasts of HABs or conditions that \r favour microbial pathogen outbreaks (Cross-Chapter  Box  ILLNESS in \r Chapter  2; Semenza et  al., 2017; Franks, 2018; Hattenrath-Lehmann \r et al., 2018; Borbor-Cordova et al., 2019; Davis et al., 2019; Campbell \r et  al., 2020a; Davidson et  al., 2021). Forecasts facilitate preventive \r public health measures (World Health Organisation and United Nations \r Children's Fund, 2017), or seafood harvest guidance (Maguire et  al., \r 2016; Leadbetter et al., 2018; Anderson et al., 2019; Bolin et al., 2021), \r reducing risks of disease outbreaks, waste and contaminated seafood \r entering the market (medium confidence) (Cross-Chapter Box ILLNESS \r in Chapter  2; Nichols et  al., 2018). Monitoring of water quality and \r seafood safety (Cross-Chapter Box ILLNESS in Chapter 2), paired with \r effective public communication and education (Ekstrom et al., 2020), \r [...]"


id: 4be5c1cdbaebb31407f0d7068749a48e
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index: climate_gpt_v2
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content:
"[...] inform individual and local adaptations, including use of (a) personal \r protective equipment, (b) seafood selection and preparation (Elsayed \r et al., 2020; Froelich and Daines, 2020; Fielding et al., 2021), (c) income \r diversification (Section  3.6.2.1; Moore et  al., 2020b), (d)  public \r education (Borbor-Cordova et al., 2019) or (e) community-level actions \r to decrease risk from coastal aquifer and soil salinisation (Slama et al., \r 2020; Mastrocicco and Colombani, 2021), HAB toxins (Ekstrom et al., \r 2020) and other contaminants (e.g., methylmercury, metals, persistent \r organic pollutants) in seafood (Chan et al., 2021). A full assessment of \r climate-change impacts on human health is found in Chapter 7 and \r Cross-Chapter Box ILLNESS in Chapter 2."


id: fe3c1067f731c09caaa5b29c3f38bda3
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index: climate_gpt_v2
vector_id: 42095
content:
"Increased maritime transport and cruise-ship tourism in the Arctic are \r already impacting local and Indigenous Peoples, revealing conflicts \r over the uses of the ocean and the governance needed to support local \r people and a sustainable blue economy (high confidence) (Debortoli \r et al., 2019; Palma et al., 2019; Berman et al., 2020; Dundas et al., 2020). \r While shipping and its associated environmental impacts are projected \r to grow (Palma et al., 2019; Dawson et al., 2020), adaptation efforts \r are only at the planning stage (Debortoli et al., 2019). Increased Arctic \r traffic due to ice loss can benefit trade, transportation and tourism \r (medium confidence), but will also affect Arctic marine ecosystems \r and livelihoods (high confidence) (Palma et al., 2019; Dawson et al., \r 2020). Increasing search-and-rescue activities (Ford and Clark, 2019) \r reveal capacity gaps to support future demands (Ford and Clark, 2019; \r [...]"


id: b5a42b141b29bf11047b284908835f4f
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vector_id: 29184
content:
"[...] Palma et al., 2019). The Low-Impact Shipping Corridors initiative has \r been developed as an adaptation strategy in the Arctic, although with \r limited inclusion of IKLK (Dawson et al., 2020)."


id: 19b2bab49a355eedf983372cd8ed782c
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index: climate_gpt_v2
vector_id: 1722
content:
"Relative SLR and the increased frequency and severity of storms \r are already affecting port activity, infrastructure and supply chains, \r sometimes disrupting trade and transport (Monios and Wilmsmeier, \r 2020), but these hazards are not systematically incorporated into \r adaptation planning (medium evidence) (Monios and Wilmsmeier, \r 2020; O'Keeffe et  al., 2020). Climate-change impacts that increase \r food insecurity, income loss and poverty can exacerbate maritime \r criminal activity, including illegal fishing, drug trafficking or piracy \r (medium evidence) (Germond and Mazaris, 2019). A transformational \r adaptation approach to address climate impacts on maritime activities \r and increase security (Germond and Mazaris, 2019) would relocate \r ports, change centres of demand, reduce shipping distances or shorten \r supply chains (medium agreement) (Walsh et al., 2019; Monios and \r Wilmsmeier, 2020) as well as decrease marginalisation of vulnerable \r [...]"


id: 7b9f23528b0c52be43a8114a042e6f6b
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index: climate_gpt_v2
vector_id: 18957
content:
"[...] groups, develop polycentric governance systems and eliminate \r maladaptive environmental policies and resource loss (Belhabib et al., \r 2020; O'Keeffe et al., 2020)."


id: 19ade1395891299e25aa462bcf698e71
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vector_id: 1719
content:
"underscores the urgent need to pursue biodiversity, ecosystem\u0002service provision and climate-adaptation goals simultaneously, while \r acknowledging inherent trade-offs (Claudet et al., 2020a; Sala et al., \r 2021). Frameworks to create 'climate-smart' MPAs (Tittensor et  al., \r 2019) generally include: (a) defining conservation goals that embrace \r resource vulnerabilities and co-occurring hazards; (b)  carefully \r selecting adaptation strategies that include IKLK while respecting \r Indigenous rights and accommodating human behaviour (Kikiloi et al., \r 2017; Thomas, 2018; Yates et  al., 2019; Failler et  al., 2020; Wilson \r et al., 2020a; Croke, 2021; Reimer et al., 2021; Vijayaraghavan, 2021); \r (c)  developing protection that is appropriate for all ocean depths \r (Brito-Morales et al., 2018; Frazao Santos et al., 2020; Wilson et al., \r 2020a), especially considering climate velocity (Arafeh-Dalmau et al., \r 2021); (d) using dynamic national and international management tools \r [...]"


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"[...] to accommodate extreme events or species distribution shifts (Gaines \r et al., 2018; Pinsky et al., 2018; Bindoff et al., 2019a; Scheffers and \r Pecl, 2019; Tittensor et al., 2019; Cashion et al., 2020; Crespo et al., \r 2020; Frazao Santos et al., 2020; Maxwell et al., 2020b), which could \r build on dynamic regulations already in place for fishing or ship strikes \r (Maxwell et  al., 2020b); and (e)  seeking to increase connectivity \r (Wilson et al., 2020a), using genomic or multi-species model insights \r (Xuereb et al., 2020; Friesen et al., 2021; Lima et al., 2021)."


id: ec7710aaefd70dbe960d1bfb340bece7
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 38961
content:
"Figure  3.26; Bates et  al., 2014; Lubchenco and Grorud-Colvert, 2015; \r Gattuso et  al., 2018) because they alleviate non-climate drivers and \r promote biodiversity (i.e., 'managed resilience hypothesis') (Bruno \r et  al., 2019; Maestro et  al., 2019; Cinner et  al., 2020). Current MPAs \r offer conservation benefits such as increases in biomass and diversity \r of habitats, populations and communities (high confidence) (Pendleton \r et al., 2018; Bates et al., 2019; Stevenson et al., 2020; Lenihan et al., 2021; \r Ohayon et al., 2021), and these benefits may last after some (possibly \r climate-enhanced) disturbances (e.g., tropical cyclones) (McClure et al., \r 2020). But current MPAs do not provide resilience against observed \r warming and heatwaves in tropical-to-temperate ecosystems (medium \r confidence) (Bates et al., 2019; Bruno et al., 2019; Freedman et al., 2020; \r Graham et al., 2020; Rilov et al., 2020). There is robust evidence that \r [...]"


id: ead4c806ddaab7d4442220101ea15abb
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 38676
content:
"[...] processes around MPA design and implementation strongly influence \r whether outcomes are beneficial or harmful for adjacent human \r communities (McNeill et al., 2018; Zupan et al., 2018; Ban et al., 2019)."


id: ef3993acff9424f35282bb229da080d8
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 39457
content:
"Current placement and extent of MPAs will not provide substantial \r protections against projected climate change past 2050 (high \r confidence), as the placement of MPAs has been driven more often \r by political expediency (e.g., Leenhardt et al., 2013) than by managing \r key drivers of biodiversity loss (Cockerell et al., 2020; Stevenson et al., \r 2020) or climate-induced drivers (Bruno et  al., 2018). Only 3.5% of \r the area currently protected will provide refuges from both SST \r and deoxygenation by 2050 under both RCP4.5 and RCP8.5 (Bruno \r et al., 2018), and MPAs are more exposed to climate change under \r RCP8.5 than non-MPAs (Section 3.4.3.3.4; Figure 3.20d). Community \r thermal tolerances will be exceeded by 2050 in the tropics and by \r 2150 for many higher-latitude MPAs (Bruno et al., 2018). Most MPA \r design has focused on the surface ocean, but MPAs are assumed to \r protect the entire water column and benthos. Climate-induced drivers \r [...]"


id: aef1ee9c34f56a4f424063041b30d170
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 28021
content:
"[...] (Section  3.2) throughout the water column and rapidly accelerating \r climate velocities at depths below 200 m (Johnson et al., 2018; Brito\u0002Morales et al., 2020) are projected to affect virtually all North Atlantic \r deep-water and open-ocean area-based management zones in the \r next 20-50 years (Johnson et al., 2018), and the conservation goals of \r benthic MPAs in the North Sea are not expected to be fulfilled (Weinert \r et al., 2021). Heightened risk of non-indigenous species immigration \r from vessel traffic plus climate change further endangers MPA success \r (Iacarella et  al., 2020), a particular concern in the Mediterranean \r (D'Amen and Azzurro, 2020; Mannino and Balistreri, 2021), where \r the current MPA network is already highly vulnerable to climate \r change (Kyprioti et  al., 2021). This new evidence supports SROCC's \r high confidence assessment that present governance arrangements, \r including MPAs, are too fragmented to provide integrated responses \r [...]"


id: 159c4fef955d80e85f10a2b5cc933dfc
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 1016
content:
"[...] to the increasing and cascading risks from climate change in the ocean \r (SROCC SPMC1.2; IPCC, 2019c)."


id: c61612f94a25acb65c95a2f957473976
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 32160
content:
"2019; Coleman et  al., 2020b; Fredriksen et  al., 2020; Wade et  al., \r 2020). Managed breeding of corals has also had limited success in the \r laboratory and at small local scales (National Academies of Sciences, \r 2019). There is also limited evidence that physiological interventions, \r such as algal-symbiont or microbiome manipulation, could increase \r coral thermal tolerance in the field (National Academies of Sciences, \r 2019). Employing the natural adaptive capacity of species or \r individuals in active restoration for corals and kelps with current \r technology involves fewer risks than assisted evolution or long\u0002distance relocation (high confidence) (Filbee-Dexter and Smajdor, \r 2019; National Academies of Sciences, 2019). More ambitious \r engineered interventions like reef shading remain theoretical and \r not scalable to the reef level (Condie et al., 2021). Debate continues \r on how to apply planned adaptation in cost-effective ways that will \r [...]"


id: a0e8fa22eadb6d9a273090fdd0ef013e
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 25533
content:
"[...] accomplish the intended goals (National Academies of Sciences, 2019; \r Duarte et al., 2020; Kleypas et al., 2021)."


id: 6e91b289a00b0d58fe7445e273593f14
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 16718
content:
"Local restoration projects often target vegetated ecosystems like \r mangroves, seagrasses and salt marshes that are valued and used \r by coastal communities (Veettil et al., 2019; Duarte et al., 2020; Wu \r et  al., 2020a; Bertolini and da Mosto, 2021). Detail on mangroves \r and corals as EbA and protection/restoration hotspots is provided in \r SM3.8. Common and effective actions (Sasmito et  al., 2019; Duarte \r et  al., 2020; Oreska et  al., 2020) include securing accommodation \r space (Sections 3.4.2.4-3.4.2.5), restoring hydrological (Kroeger et al., \r 2017; Al-Haj and Fulweiler, 2020) and sediment dynamics; managing \r harvesting (particularly in mangroves); reducing pollution (especially \r in seagrasses) (de los Santos et al., 2019); and replanting appropriate \r species in suitable environmental settings (Wodehouse and Rayment, \r 2019; Friess et al., 2020a). Although efficacy is context dependent (Zeng \r et al., 2020; Krause-Jensen et al., 2021) and implementation is most \r [...]"


id: bd5257a209d9088312add0363ed46e24
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 30555
content:
"[...] often local (Alongi, 2018a), such projects facilitate tangible community \r engagement in climate action. Moreover, because these ecosystems \r sequester disproportionate amounts of carbon (blue carbon) (Annex II: \r Glossary; see Box 3.4), restoration supports climate-change mitigation \r (Lovelock and Reef, 2020; Gattuso et  al., 2021). Yet, constraints \r remain. For instance, Southeast Asia has 1.21 million km2\r  of terrestrial, \r freshwater and mangrove area biophysically suitable for reforestation, \r which could mitigate 3.43 +- 1.29 Pg CO2e yr-1 through 2030; however, \r reforestation is only feasible in a small fraction of this area (0.3-18%) \r given financial, land-use and operational constraints (Zeng et al., 2020). \r Nevertheless, the multiple benefits offered by ecosystem restoration \r will likely outweigh competing costs and increase its relevance as part \r of adaptation-strategy portfolios (Silver et  al., 2019; Wedding et  al., \r [...]"


id: 9096e4c229f623ea28f400327a54adc1
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 22645
content:
"[...] 2021), national carbon-accounting systems and nationally determined \r contributions by parties to the Paris Agreement (Friess et al., 2020a; \r Wu et al., 2020a)."


id: e9f80073189924415da0364febd63ccb
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 38513
content:
"Models show that a combination of available management approaches \r (restoration, reducing non-climate drivers) and speculative interventions \r (e.g., enhanced corals, reef shading) can contribute to sustaining some \r coral reefs beyond 1.5degC of global warming with declining effectiveness \r beyond 2degC of global warming (medium confidence) (Figure  3.25; \r WGII Chapter  17). These proposed interventions are also currently \r theoretical and impractical over large scales; for example, engineered \r solutions like reef shading are untested and not scalable at the reef \r level (Condie et al., 2021). Existing projects suggest that restoration \r and ecological interventions to habitat-forming ecosystems have the \r additional benefits of raising local awareness, promoting tourism, \r and creating jobs and economic benefits (Fadli et al., 2012; Bostrom\u0002Einarsson et al., 2020; Hafezi et al., 2021), provided communities are \r involved in planning, operation and monitoring (Bostrom-Einarsson \r [...]"


id: 4cf2bed2402b3ae648f9cd940f1243de
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 10808
content:
"Interactions with oceans are fundamental to the identities of many coastal \r Indigenous Peoples (Norman, 2017), and this influences Indigenous \r responses to climate hazards and adaptation. Around 30  million \r Indigenous Peoples live along coasts (Cisneros-Montemayor et  al., \r 2016). Seafood consumption among Indigenous Peoples is much higher \r than for non-Indigenous populations, and marine species support many \r cultural, medicinal and traditional activities contributing to public health \r (Section 3.5.3.1; Kenny et al., 2018). Perpetuation of Indigenous cultures \r depends on protecting marine ecosystems and on adapting to changes \r in self-led ways (Section  3.5.6; Sangha et  al., 2019) that promote self\u0002determination (von der Porten et  al., 2019). Indigenous resurgence, or \r reinvigorating Indigenous ways of life and traditional management, can \r include marine resource protection and ocean-sector development founded \r [...]"


id: 31101b918f94af58c0901a2275c5ee12
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 5882
content:
"Countries with large ocean areas within their EEZs have opportunities \r to develop 'blue-green economies' to reduce emissions and finance \r adaptation pathways (Chen et al., 2018a; Lee et al., 2020). Shifting from \r grants to results-based financing can help attract more private capital \r to ocean adaptation (Lubchenco et  al., 2016; Claudet et  al., 2020a). \r Public-private partnerships can also increase ocean adaptation finance \r (Goldstein et al., 2019; Sumaila et al., 2021). For example, the financial \r benefits that biodiversity conservation confers to seafood harvest \r resilience could be used to leverage industry participation in adaptation \r and conservation finance (Barbier et al., 2018). Connecting restoration \r of blue carbon ecosystems with offset markets (e.g., Vanderklift \r et  al., 2019) shows potential, but uncertainties remain about the \r international emissions trading under the UN Framework Convention \r [...]"


id: d13470c44406df22514d0e7b480e879a
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 34156
content:
"[...] on Climate Change and climate impacts on blue carbon ecosystems \r (Section 3.6.3.1.6; Lovelock et al., 2017a; Macreadie et al., 2019)."


id: d40d6684dc29289459b0bfe179b14980
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 34638
content:
"Finance is a key barrier globally for ocean health, governance and \r adaptation to climate change (high agreement) (Annex II: Glossary; \r Cross-Chapter  Box  FINANCE in Chapter  17; Hinkel et  al., 2018; \r Miller et al., 2018; Wabnitz and Blasiak, 2019; Woodruff et al., 2020; \r Sumaila et al., 2021). Global adaptation finance was estimated to total \r 30 billion USD yr-1 in 2017-2018, or 5% of all climate finance (CPI, \r 2019), with no tracking specifically for coastal or marine adaptation in \r low- to middle-income countries. Marine-focused adaptation finance \r is difficult to trace and label due to the cross-sectoral nature of many \r projects (Blasiak and Wabnitz, 2018) and the lack of clear definitions \r about what qualifies as adaptation or as new and additional finance \r (Donner et  al., 2016; Weikmans and Roberts, 2019). Finance for \r marine conservation from Overseas Development Assistance doubled \r between 2003 and 2016, reaching 634 million USD in 2016, similar to \r [...]"


id: 62f31c75afc5a44df9fa704156ff1bb8
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 14708
content:
"[...] the level provided by philanthropic foundations (Berger et al., 2019). \r Yet coastal adaptation to SLR alone is projected to cost hundreds of \r billions of USD yr-1, depending on the model and emission scenario \r (e.g., Wong et al., 2014; Nicholls et al., 2019). Economic and financing \r barriers to marine adaptation are often higher in low- to middle\u0002income countries, where resources influence governance and constrain \r options for implementation and maintenance (high confidence) \r (Hinkel et al., 2018; Klock and Nunn, 2019; Tompkins et al., 2020), and \r impacts on their coastal and marine ecosystems could total several \r percentage points of their gross domestic product (Wong et al., 2014). \r Current financial flows are insufficient to meet the costs of coastal and \r marine impacts of climate change (very high confidence) and ocean\u0002focused finance is unevenly distributed, with higher flows within, and \r to, developed countries (very high confidence)."


id: 30a19a2f41d8056b36eed35a4259c612
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 5808
content:
"Transparency, coherence between different actors and initiatives, and \r project monitoring and evaluation enhance success in adapting and \r achieving SDG14 (Life Below Water) (Blasiak et al., 2019). Maladaptation \r (WGII Chapter  16; Magnan et  al., 2016) is a common risk of current \r project-based funding due to the pressure to produce concrete results \r (medium confidence) (Parsons and Nalau, 2019; Nunn et  al., 2020; \r Nunn et al., 2021). Maladaptation can be avoided through a focus on \r building adaptive capacity, community-based management, drivers of \r vulnerability and site-specific measures (low confidence) (Magnan and \r Duvat, 2018; Piggott-McKellar et al., 2020; Schipper, 2020). More research \r is needed to identify ways that governance and financing agreements can \r help overcome financial barriers and sociocultural constraints to avoid \r maladaptation in coastal ecosystems (high confidence) (Hinkel et  al., \r [...]"


id: 574da97aef68002b76339e76aea7f6e5
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 12614
content:
"Communities and governments at all levels increasingly use decision\u0002making frameworks (e.g., structured decision making) or decision\u0002analysis tools to evaluate trade-offs between different responses, \r rather than applying generic best practices to different physical, \r technical or cultural contexts (high confidence) (Watkiss et al., 2015; \r Haasnoot et al., 2019; Palutikof et al., 2019). Increased effort has also \r been devoted to developing climate services (actionable information \r and data products) that bridge the gap between climate prediction \r and decision making (Hewitt et al., 2020). Climate services have the \r potential to inform decision making related to disaster-risk reduction, \r adaptation responses, marine environmental management (e.g., \r fisheries management and MPA management) and ocean-based \r climate mitigation (e.g., renewable-energy installations) (Le Cozannet \r et  al., 2017; Gattuso et  al., 2019; Gattuso et  al., 2021). Although \r [...]"


id: a1d745849a5d57e1960e3566b47789f6
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 25694
content:
"[...] improving observational and modelling capacity is important to \r developing ocean-focused services, particularly in high-risk regions \r like SIDS where regional climate projections are scarce (WGI AR6 \r Chapter  9; Morim et  al., 2019; Fox-Kemper et  al., 2021), data are \r not the only limiting factor in decision making (Weichselgartner and \r Arheimer, 2019). Focusing on user engagement, relationship building \r and the decision-making context ensures that climate services are \r useful to, and used by, different stakeholders (high confidence) (Soares \r et  al., 2018; Mackenzie et  al., 2019; Weichselgartner and Arheimer, \r 2019; Findlater et al., 2021; West et al., 2021)."


id: 41dcf7e153657b3895b06e23b2a28cec
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 8782
content:
"Relationships between Climate Action (SDG13) targets and SDG14 \r targets are mostly synergistic (Figure  3.26; Fuso Nerini et  al., 2019). \r Responding to climate-change impacts requires transformative \r governance (high confidence) (Chapters  1, 18; Collins et  al., 2019a; \r Brodie Rudolph et al., 2020; Claudet et al., 2020a), especially for extreme \r events and higher-impact scenarios (e.g., higher emissions) (Fedele et al., \r 2019), and for achieving SDGs through one of the global ecosystems \r transitions (Chapter 18; Sachs et al., 2019; Brodie Rudolph et al., 2020). \r Opportunities to transform ocean governance exist in developing new \r international and local agreements, regulations and policies that reduce \r the risks of relocating ocean and coastal activities (Section 3.6.3.1.1) \r or in reinventing established practices (Section  3.6.3.3.3). Policy \r transformations improving ocean sustainability under SDG14 also help \r [...]"


id: 5401d167d3589a95b41b97371d4e39c2
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 12052
content:
"[...] address SDG13 (Brodie Rudolph et al., 2020; Dundas et al., 2020; Claudet, \r 2021; Sumaila et al., 2021). Emergent situations, such as the COVID-19 \r pandemic, may provide opportunities to implement transformative \r 'green recovery plans' that support achievement of the SDGs and NDCs \r (Cross-Chapter Box COVID in Chapter 7)."


id: eae989491632e603262475b443ac3bb4
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 38692
content:
"Ocean and coastal NbS can contribute to global mitigation efforts, \r especially with ocean renewable energy and restoration and \r preservation of carbon ecosystems (see Box  3.4; Section  3.6.2.3). \r Technological, economic and financing barriers presently hamper \r development of renewable ocean energy (AR6 WGIII Chapter 6). Such \r development could help small nations reliant on imported fuel meet \r their climate-mitigation goals and decrease risk from global fuel\u0002supply dynamics (Millar et al., 2017; Chen et al., 2018a), but progress \r is limited by lack of investment (Millar et al., 2017; Lee et al., 2020) or \r equipment (Aderinto and Li, 2018; Rusu and Onea, 2018). Wave-energy \r installations, possibly co-located with wind turbines (Perez-Collazo \r et al., 2018), are promising for both low- to middle-income nations and \r areas with significant island or remote coastal geographies (Lavidas \r and Venugopal, 2016; Bergillos et al., 2018; Jakimavicius et al., 2018; \r [...]"


id: 38b5ca05f5ad1ca5e866ffd9616c9da9
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 7182
content:
"[...] Kompor et al., 2018; Penalba et al., 2018; Saprykina and Kuznetsov, \r 2018; Lavidas, 2019). Wave-energy capture may also diminish storm\u0002induced coastal erosion (Abanades et al., 2018; Bergillos et al., 2018). \r Tidal energy is a relatively new technology (Haslett et al., 2018; Liu et al., \r 2018; Neill et al., 2018) with limiting siting requirements (Mofor et al., \r 2013). Ocean renewable-energy expansion faces other technological \r obstacles including lack of implementable or scalable energy-capture \r devices, access to offshore sites, competing coastal uses, potential "


id: b8f67ea3059ddabb2d51e1d7eac0a76c
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 29747
content:
"from risks associated with poverty (SDG1), hunger (SDG2), health \r and water sanitation (SDG3 and SDG6), and inequality (SDG10) by \r supporting aquaculture (Sections  3.5.3, 3.6.3.1), alerting the public \r about poor water quality (Sections 3.5.5.3, 3.6.3.1) and empowering \r marginalised groups, such as women and Indigenous Peoples, with \r decision-relevant information (medium evidence, high agreement) \r (Sections  3.5.5.3, 3.6.3.1). Effectively implemented and managed \r marine NbS (Section 3.6.2.3) contribute to attainment of social SDGs \r by: (a)  preserving biodiversity (Carlton and Fowler, 2018; Warner, \r 2018; Scheffers and Pecl, 2019), which benefits most ocean and \r coastal ecosystem services (Section 3.5.3; Figure 3.22); (b) increasing \r marine fishery and aquaculture sustainability (Section  3.6.3); (c) \r including vulnerable people and communities in management \r (Section  3.6.3.2.1); (d)  lowering risk of flooding from storms and \r [...]"


id: 4e1a6279e44c8f129b0b41aa4eb887c
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 11013
content:
"[...] SLR (Cross-Chapter  Box  SLR in Chapter  3; Sections  3.6.3.1.1); and \r (e) implementing spatial-management tools that make room for \r new uses like renewable-energy development (Section  3.6.3.3.4). \r Nature-based solutions can therefore help support achievement of \r No Poverty (SDG1) (Ntona and Morgera, 2018), Zero Hunger (SDG2), \r Good Health and Well-Being (SDG3) (Duarte et al., 2020), Affordable \r and Clean Energy (SDG7) (Fuso Nerini et  al., 2019; Levin et  al., \r 2020) and Reduced Inequality (SDG10). Socio-institutional marine \r adaptations (Section  3.6.2.2) that support current livelihoods and \r help develop alternatives can contribute to attainment of social SDGs \r by enhancing social equity and supporting societal transformation \r (medium confidence) (Cisneros-Montemayor et al., 2019; Pelling and \r Garschagen, 2019; Nash et  al., 2021). Even societal changes that \r are not directly marine related can decrease human vulnerability to \r [...]"


id: 8af42d42496d6dc69ce826f566898c3f
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 21617
content:
"[...] ocean and coastal climate risks by improving overall human adaptive \r capacity (Section 1.2).\r Marine adaptation also shows promise for helping support achievement \r of economic SDGs (medium confidence) (Figure  3.26). Marine NbS \r could help blue-economy frameworks achieve Decent Work and \r Economic Growth (SDG8) (Lee et al., 2020) by sustainably and equitably \r incorporating ecosystem-based fisheries management, restoration "


id: 300197abbb0d12b682ccdc4d4256e269
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 5705
content:
"or conservation (Sections  3.6.3.1.2, 3.6.3.2.1, 3.6.3.2.2; Voyer et  al., \r 2018; Cisneros-Montemayor et al., 2019; Cohen et al., 2019; Okafor\u0002Yarwood et  al., 2020). Nature-based solutions that involve active \r restoration or accommodation can contribute to Sustainable Cities and \r Communities (SDG11) and Infrastructure (SDG9) (Section  3.6.3.1.1). \r Newly developed marine industries and livelihoods associated with \r NbS might support attainment of Sustainable Communities (SDG11) \r (Cisneros-Montemayor et al., 2019). Finance and market mechanisms \r to support disaster relief or ocean ecosystem services, such as blue \r carbon or food provisioning, and innovations (SDG9) including new \r technologies like vessel-monitoring systems (Kroodsma et  al., 2018), \r can contribute to Responsible Consumption and Production (SDG12) \r (Sumaila and Tai, 2020). Blue-economy growth that includes sustainable \r shipping, tourism, renewable ocean energy and transboundary fisheries \r [...]"


id: e7a7d0f235d5e804b1fa38ab7b73c415
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 38062
content:
"[...] management (Pinsky et al., 2018) have the potential to contribute to \r Economic Development (SDG8), affordable and clean energy (SDG7) as \r well as global mitigation efforts (SDG13) (Hoegh-Guldberg et al., 2019b; \r Duarte et  al., 2020). Participatory approaches and co-management \r systems (Section 3.6.2.1) in many maritime sectors can contribute to \r SDG11 and SDG12 while helping align the blue economy and the SDGs \r (high agreement) (Lee et al., 2020; Okafor-Yarwood et al., 2020)."


id: a4079a977341679c3efa1ebfaf1132ed
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"shellfish harvesting (Turner et  al., 2020a) and account for 11% of \r global artisanal fisheries participants (Harper et al., 2020b), they are \r often not specifically counted in datasets and excluded from decision \r making and support programmes (Cross-Chapter  Box  GENDER in \r Chapter  18; Harper et  al., 2020b; Michalena et  al., 2020). Targeted \r efforts to incorporate knowledge diversity, and include artisanal \r fishers, women and Indigenous Peoples within international, regional \r and local policy planning, promote marine adaptation that supports \r achievement of gender equality (SDG5) and reduces inequalities \r (SDG10) (limited evidence, high agreement) (FAO, 2015). Integrated \r planning, financing and implementation can help overcome these \r limitations (Section  3.6.3.3.2; Cross-Chapter  Box  FINANCE in \r Chapter  17), ensuring that marine adaptations do not compromise \r overall human equity or specific SDGs (Osterblom et al., 2020; Nash \r [...]"


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"[...] et al., 2021), but are in fact fully synergistic with these goals (Bennett \r et al., 2021)."


id: dca694eb01d2c791d28eb58aff49e2fc
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"approach to both mitigation and adaptation. Following adoption of \r the Paris Agreement in 2015, the UN SDGs (Table  3.31) came into \r force in 2016, including SDG14 specifically dedicated to Life Below \r Water (Table 3.31). In 2017, the first UN Ocean Conference was held \r (United Nations, 2017), the UNFCCC adopted the Ocean Pathway to \r increase ocean-targeted multilateral climate action (COP23, 2017) \r and the UN Assembly declared 2021-2030 the Decade for Ocean \r Science for Sustainable Development (Visbeck, 2018; Lee et al., 2020). \r Next, 14 world leaders formed the High-Level Panel for a Sustainable \r Ocean Economy to produce the New Ocean Action Agenda, founded \r on 100% sustainable management of national ocean spaces by 2025 \r (Ocean Panel, 2020). All of these initiatives position oceans centrally \r within the climate-policy and biodiversity-conservation landscapes \r and seek to develop a coherent effort and common frameworks to \r [...]"


id: beee44b49f673b6d8a480b973ee3a3c6
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"[...] achieve marine sustainability (Visbeck, 2018; Lee et  al., 2020), new \r economic opportunities (Konar and Ding, 2020; Lee et al., 2020), more \r equitable outcomes (Osterblom et  al., 2020) and decisive climate \r mitigation and adaptation (Hoegh-Guldberg et al., 2019a), to achieve \r truly transformative change (Claudet et al., 2020a)."


id: 78a87c7f7c17642c241d2733496ca418
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content:
"Adaptation efforts (Sections  3.6.3.1-3.6.3.2) have three common \r characteristics that facilitate implementation and success, and \r contribute to climate resilient development pathways (Chapter  18). \r First, availability of multiple types of information (e.g., monitoring, \r models, climate services; Section 3.6.3.3) exposes the magnitude and \r nature of the adaptation challenge. Well-developed observation and \r modelling capabilities (Reusch et al., 2018) offer insights on climate\u0002associated risks at different time scales (Cvitanovic et al., 2018; Hobday \r et  al., 2018), and this facilitates adaptation within multiple areas \r (e.g., industries over shorter time scales, societies over longer scales) \r (Hobday et  al., 2018). Environmental data have supported building \r societal and political (socio-institutional) will to adopt national and \r subnational adaptive management principles (Hobday et  al., 2016b; \r Champion et al., 2018; McDonald et al., 2019). However, incorporating \r [...]"


id: c6688bd15f45c9ac8274eb053ed57413
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"[...] IKLK at the same time provides more diverse social-environmental \r insight (Section 3.6.3.4.1; Goeldner-Gianella et al., 2019; Petzold and \r Magnan, 2019; Wilson et al., 2020b). This can help align adaptation \r solutions with cultural values and increase their legitimacy with \r Indigenous and local communities (Chapter 1.3.2.3), achieving climate \r resilient development pathways (Chapter 18; Adger et al., 2017; Nalau \r et al., 2018; Penaherrera-Palma et al., 2018; Raymond-Yakoubian and \r Daniel, 2018; Wamsler and Brink, 2018). Second, implementation of \r multiple low-risk options (Hoegh-Guldberg et al., 2019a; Gattuso et al., \r 2021) such as economic diversification (Section 3.6.2.1) can provide \r culturally acceptable livelihood alternatives and food supplies (e.g., \r fishing to ecotourism and mariculture) (Froehlich et al., 2019) while also \r providing environmental benefits (e.g., seaweed mariculture's potential \r [...]"


id: d2075045d8187b1644fd11b2ef5ef7e9
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"[...] carbon storage co-benefits) (WGIII AR6 Chapter  7; Hoegh-Guldberg \r et al., 2019a; Gattuso et al., 2021). Third, inclusive governance that is \r well aligned to the systems at risk from climate change is fundamental \r for effective adaptation (Barange et al., 2018). Solutions implemented \r within polycentric governance systems (Section  3.6.3; Bellanger \r et al., 2020) benefit from synergies between knowledge, action and \r social-ecological contexts and stimulate governance responses at \r appropriate spatio-temporal scales (Cvitanovic and Hobday, 2018). \r Governance aligned with Indigenous structures and local structures \r supports successful outcomes that prioritise the concerns and rights \r of involved communities (Section 3.6.3; Mawyer and Jacka, 2018) and \r better leverages existing social organisation (i.e., network structures), \r learning processes and power dynamics (Barnes et al., 2020)."


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"There is robust evidence that a combination of global and local solutions \r offers the greatest benefit in reducing climate risk (Gattuso et al., 2018; \r Hoegh-Guldberg et al., 2019a; Hoegh-Guldberg et al., 2019b). Ambitious \r and swift global mitigation offers more adaptation options and pathways \r to sustain ecosystems and their services (Figure 3.25). Some solutions \r target both mitigation and adaptation (e.g., blue carbon conservation; \r Cross-Chapter  Box  NATURAL in Chapter  2;  see Box  3.4), and cross\u0002cutting solutions simultaneously support several ocean-related sectors \r (e.g., area-based measures support fishing, tourism; Section 3.6.3.2.1) or \r ecosystem functions (e.g., NbS support coastal protection, biodiversity, \r habitat, etc.; Section 3.6.3.2.2; Sala et al., 2021). Combined solutions \r also leverage a variety of existing policies and governance systems \r (Section 3.6.4.3; Duarte et al., 2020) to advance climate mitigation and \r [...]"


id: 37d7ceb0bdcd138305f56df4c40c9da3
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"[...] adaptation. Even communities that face the limits of adaptation, like \r those who must relocate to cope with rising seas (McMichael et  al., \r 2019; Bronen et  al., 2020), urgently require solutions that combine \r scientific projections, IKLK, cultural and community values, and ways to \r preserve cultural identity to support planning and implementation of \r relocation (McMichael and Katonivualiku, 2020)."


id: fe3da4e6a4d00ff3a5e1e8f5a6a5eb6d
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"Nature-based solutions are showing promising results in achieving \r adaptation and mitigation outcomes across marine and coastal \r ecosystems (Sections  3.6.3.2.1-3.6.3.2.2), but NbS have different \r degrees of readiness in marine ecosystems (Duarte et al., 2020). Habitat \r restoration and recovery are highly effective in specific settings and \r conditions (McLeod et al., 2019). Restoring and conserving vegetated \r coastal habitats (Sections  3.4.2.4-3.4.2.5) represent robust NbS, \r especially in the tropics, and particularly when paired with restoration and \r conservation of terrestrial ecosystems (robust evidence) (e.g., peatlands \r and forests; WGIII AR6 Chapter 7; Hoegh-Guldberg et al., 2019b; Duarte \r et al., 2020; Griscom et al., 2020). Although most of the focus on NbS \r efficacy has been on coastal and shelf ecosystems (Section  3.6.3.2), \r recent advances point to an emerging role of NbS beyond coastal waters \r [...]"


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"[...] in the form of area-based management tools in marine areas beyond \r national jurisdiction (Section 3.6.2.3; Gaines et al., 2018; Pinsky et al., \r 2018; Crespo et al., 2020; O'Leary et al., 2020; Visalli et al., 2020; Wagner \r et al., 2020), because sustainable fisheries and aquaculture and climate\u0002responsive MPAs have high potential to adapt (Tittensor et al., 2019)."


id: c29102ae9e196aa459d0d202d910011d
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"There is an opportunity to improve current practices when developing \r new ocean and coastal adaptation efforts so that they routinely contain \r these successful characteristics and resolve technical, economic, \r institutional, geophysical, ecological and social constraints (Figure 3.25; \r Section  3.6.3.3; IPCC, 2018; Singh et  al., 2020). Enhancements are \r needed in human, technical and financial resources; regulatory \r frameworks (Ojwang et  al., 2017); political support (Rosendo et  al., \r 2018); institutional conditions and resources for fair governance (Gupta \r et al., 2016; Scobie, 2018); political leadership; stakeholder engagement; \r multidisciplinary data availability (Gopalakrishnan et al., 2018); funding \r and public support for adaptation (Cross-Chapter  Box  FINANCE in \r Chapter 17; Ford and King, 2015); and incorporating IKLK in decision \r making (Nalau et al., 2018; Jabali et al., 2020; Petzold et al., 2020). As \r [...]"


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"[...] climate change continues to challenge ocean and coastal regions, there \r is high confidence associated with the benefits of developing robust, \r equitable adaptation strategies that incorporate scientific projections, "


id: d562874e9cb9af988b688d2f573cb051
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"Contributing Authors: Malcolm Araos (Canada/USA), Soumya Balasubramanya (Sri Lanka/\r India), Angelica Katharina Casparina Brackel (the Netherlands), John Caesar (UK), Holly B. \r Caggiano (USA), Benjamin Cook (USA), Constantino Dockendorff (Germany/Chile), Calynn Dowler \r (USA), Robert Dunn (UK/Germany), Lina Elisabeth Erika Eklund (Sweden), Zhang Fan (China), \r Valeria Fanghella (Italy), Rodrigo Fernandez (USA/Guatemala), Colin M. Finlayson (Australia), \r Sabine Fuss (Germany), Animesh Kumar Gain (Italy/Bangladesh), Freya Garry (UK), Laila Gohar \r (UK), Valentin Golosov (Russian Federation), Sharlene Liane Gomes (the Netherlands/Canada), \r Benjamin Jerome Gray (USA), Lukas Gudmundsson (Switzerland/Germany/Iceland), Tania Guillen \r Bolaneos (Germany/Nicaragua), Kate Halladay (UK), Ed Hawkins (UK), Greeshma Hegde (India), \r Masoud Irannezhad (China/Iran), Bjorn Klove (Finland/Norway), Aristeidis G. Koutroulis (Greece), \r [...]"


id: a0d08792b3faed521c861f4d762e48d8
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"[...] Manish Kumar (India), Jonathan Lautze (South Africa/USA), Deborah Ley (Mexico/Guatemala), \r Ashwina Mahanti (India), Ganquan Mao (China), Deborah McGregor (Canada), Mamta Mehar \r (India), Megan Mills-Novoa (USA), Tessa Moller (Germany/Luxemburg), Sanchari Mukhopadhyay \r (India), Tero Mustonen (Finland), Lakshmikantha N. R. (India), Gustavo Naumann (Italy/Argentina/\r Germany), Prajjwal Kumar Panday (USA/Nepal), Vishnu Prasad Pandey (Nepal), Jagadish Parajuli \r (USA/Nepal), Assela Pathirana (the Netherlands/Sri Lanka), Ritu Priya (India), E. B. Uday Bhaskar \r Reddy (India), Ekaterina Rets (Russian Federation), Pamela Rittelmeyer (USA), Conrado M. Rudorff \r (Brazil), Orie Sasaki (Japan), Corinne Schuster Wallace (Canada/Wales), Christopher A. Scott (USA), \r Cydney Kate Seigerman (USA), Sonali Senaratna Sellamuttu (Myanmar/Sri Lanka), Rinan Shah \r (India), Mohammad Shamsudduha (UK/Bangladesh), Gitta Shrestha (Nepal), Afreen Siddiqui (USA/\r [...]"


id: e5cbfcd772ba883664ec8b1cc5b5f45d
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"[...] Pakistan), Balsher Singh Sidhu (Canada/India), Aprajita Singh (USA/India), Anna Sinisalo (Norway/\r Finland), Francesca Spagnuolo (Italy), Jaishri Srinivasan (USA/India), Makere Stewart-Harawira \r (Canada/New Zealand), Debra Tan (Hong Kong, Special Administrative Region, China/Malaysia), \r Masahiro Tanoue (Japan), Brock Ternes (USA), William Rigoberto Delgado (USA/UK/Mexico), Peter "


id: 2e424c3fb4c9aad18cd4e4e6da78e749
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"challenges (Bijl et  al., 2018). Vulnerability to water-related impacts \r of climate change and extreme weather are already felt in all major \r sectors and are projected to intensify in the future, for example, in \r agriculture (high confidence) (Sections  4.3.1, 4.5.1); energy and \r industry (high confidence for observed drought impacts and projected \r impacts) (Sections  4.3.2, 4.5.2); water for health and sanitation \r (high confidence about links to precipitation extremes and disease \r outbreaks) (Sections  4.3.3, 4.5.3); water for urban, peri-urban and \r municipal sectors (medium confidence) (Sections  4.3.4, 4.5.4) and \r freshwater ecosystems (high confidence in climate change as a driver \r in degradation of freshwater ecosystems) (Sections  4.3.5, 4.5.5). \r Agriculture and irrigation account for the most significant proportion \r of consumptive water use and account for 60-70% of total water \r withdrawals (Hanasaki et al., 2018; Burke et al., 2020; Muller Schmied \r [...]"


id: d85e2a0cfdcfed0b01c25fa4c5d8a538
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content:
"[...] et al., 2021). Globally, 10% of the most water-stressed basins account \r for 35% of global irrigated calorie production (Qin et al., 2019), and \r food production is at risk in those basins and worldwide due to \r changes in hydrological components of climate change. Lack of access \r to clean water and sanitation has been one of the leading causes of \r water-borne diseases. In 2017, approximately 2.2 billion people lacked \r access to safe drinking water, and roughly 4.2 billion people could not \r access safe sanitation (WHO and UNICEF, 2019). Inequities in access to \r safe water are being amplified during the current COVID-19 pandemic \r (Box 4. 5 and Cross-Chapter Box COVID in Chapter 7). The same 10% \r of most water-stressed basins also account for 19% of global thermal \r electricity generation (Qin et al., 2019), and globally, both production \r of hydropower and thermal power has been negatively affected by \r droughts and other extreme events. Globally, between 16% and 39% \r [...]"


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"[...] of cities experienced surface-water deficits between 1971 and 2000. \r If environmental flow requirements (EFRs) are accounted for, these \r numbers increase to 36% and 63%, respectively. Even under a scenario \r where urban water gets the highest priority, more than 440.5 million \r people in cities globally are projected to face a water deficit by 2050 \r (Florke et  al., 2018). The situation is particularly precarious in the \r Global South, where most of the population lacks access to piped \r water (WRI, 2019)."


id: 1df70aa21450d1fa9f144388ffe8846d
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content:
"Water security is defined as 'the capacity of a population to safeguard \r sustainable access to adequate quantities of acceptable quality water \r for sustaining livelihoods, human well-being, and socio-economic \r development, for ensuring protection against water-borne pollution \r and water-related disasters, and for preserving ecosystems in a climate \r of peace and political stability' (Grey and Sadoff, 2007). Risks emanating \r from various aspects of water insecurity have emerged as a significant \r global challenge. The Global Risks Report by the World Economic Forum \r lists water crisis as one of the top five risks in all its reports since 2015 \r (WEF, 2015; WEF, 2016; WEF, 2017; WEF, 2018; WEF, 2019; WEF, 2020). \r Water also features prominently in the SDGs (Section 4.8) and plays a \r central role in various systems transitions needed for climate resilient \r development. Most SDGs cannot be met without access to adequate \r [...]"


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"[...] and safe water (Ait-Kadi, 2016; Mugagga, 2016). In addition, without \r adequate adaptation, future water-related impacts of climate change \r on various sectors of the economy are projected to lower the global \r GDP by mid-century, with higher projected losses expected in low- and \r middle-income countries (World Bank, 2017; GCA, 2019)."


id: 97b5c814e4f5722350fbcc879404f70c
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"First, approximately half the world's population (~4  billion out of \r ~8 billion people) are assessed as being currently subject to severe water \r scarcity for at least some part fo the year (medium confidence) due to \r climatic and non-climate factors (Box 4.1). Water insecurity arises from \r many factors, both environmental and societal. Environmental factors \r include too little freshwater due to drought or pollution, and too much \r water, due to extreme precipitation and flooding, and are being affected \r by climate change. Societal factors include economic and governance\u0002related barriers to water access or protection from water-related damages. \r Currently, many people are experiencing climate change on a day-to-day \r basis through water-related impacts such as the increased frequency \r and intensity of heavy precipitation (high confidence) (Section 4.2.1.1, \r Seneviratne et al., 2021 ); accelerated melting of glaciers (high confidence) \r [...]"


id: 4c48ab63093e46320f3ab2c138bef02e
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index: climate_gpt_v2
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content:
"[...] (Section 4.2.2, Douville et al., 2021); changes in frequency, magnitude and \r timing of floods (high confidence) (Section 4.2.4, Seneviratne et al., 2021 \r ); more frequent and severe droughts in some places (high confidence) \r (Section 4.2.5, Seneviratne et al., 2021); decline in groundwater storage \r and reduction in recharge (medium confidence) (Section 4.2.6, Douville \r et  al., 2021) and water quality deterioration due to extreme events \r (medium confidence) (Section  4.2.7). For example, since the 1970s, \r 44% of all disaster events have been flood-related (WMO, 2020). With \r the added stressor of climate change, globally, a larger fraction of land \r and population are projected to face increased water scarcity due to \r climate change. For example, at an approximately 2degC GWL, between \r 0.9 and 3.9 billion people are projected to be at increased exposure to \r water stress, depending on regional patterns of climate change and the \r [...]"


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"Third, a large majority (~60%) of all adaptation responses documented \r since 2014 are about adapting to water-related hazards like droughts, \r floods and rainfall variability (Berrang-Ford et  al., 2021b) (high \r confidence). Water-related adaptation action features prominently in \r NDC pledges by a large majority of countries in both Global North \r and Global South (GWP, 2018). These adaptation responses and their \r current benefits and effectiveness in reducing water-related risks in \r the future are systematically assessed in this chapter (Sections  4.6, \r 4.7.1, 4.7.2 and 4.7.3). These adaptation measures aim to reduce \r impacts of water-related hazards through responses such as irrigation, \r water and soil moisture conservation, rainwater harvesting, changes \r in crops and cultivars, improved agronomic practices, among others \r (Sections 4.6.2; 4.7.1). Only ~20% of all documented case studies on \r observed water-related adaptations measure outcomes (positive or \r [...]"


id: c09b156468a61d6321c1bc738c3116fe
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"[...] negative), but the link between positive outcomes and climate risk \r reduction is unclear and remains challenging to assess (Section 4.7.1) \r (medium confidence). On the other hand, most of the future projected \r water-related adaptations are more effective at lower GWLs (1.5degC) \r than at higher GWLs, showing the importance of mitigation for future \r adaptations to remain effective (high confidence)."


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"This chapter draws on previous IPCC reports and new methodologies \r (Section 4.1.1 and SM4.1, SM4.2) and assesses the impacts of climate \r change on natural and human dimensions of the water cycle with \r a particular focus on water-related vulnerabilities and adaptation \r responses (Figure 4.1). Section 4.2 assesses observed changes in the \r hydrological cycle, and Section 4.3 focuses on their societal impacts \r and detects which parts of these changes are directly attributable to \r climate change. Section 4.4 assesses projected risks of changes in the \r hydrological cycle on various components of the hydrological cycle, and \r Section 4.5 assesses the same for sectoral risks. Projections and risks \r assessments for future impacts are framed in terms of GWLs and time \r horizons, as these are useful for informing mitigation policy under the \r Paris Agreement and informing adaptation planning. Sections 4.6 and \r 4.7 assesses current and future water-related adaptation responses in \r [...]"


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"[...] reducing climate and associated impacts and risks and looks at limits \r to adaptations, especially in a future warmer world. Finally, Section 4.8 \r outlines the enabling principles for meeting water security, SDGs and \r climate resilient development."


id: e50f0a103e1a80a050319b63ac4017
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vector_id: 37596
content:
"Water scarcity and water insecurity are related concepts but not identical, and each has a range of interpretations leading to some overlap. \r Water scarcity can be broadly described as a mismatch between the demand for fresh water and its availability, quantified in physical terms. \r Water security/insecurity is a broader concept with definitions beyond physical water scarcity, encompassing access to water services, safety \r from poor water quality and flooding, and appropriate water governance that ensures access to safe water (Sadoff et al., 2020). Metrics \r of water security include both physical and socioeconomic components and are a tool for comparison between different locations and \r countries regarding relative levels of water security in the context of water-related risks. Some definitions of water scarcity also incorporate \r these broader issues. For example, 'economic water scarcity' has been defined as a situation where 'human, institutional, and financial \r [...]"


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content:
"[...] capital limit access to water, even though water in nature is available locally to meet human demands' (Comprehensive Assessment of Water \r Management in Agriculture, 2007). Economic water scarcity can also occur where infrastructure exists, but water distribution is inequitable \r (Jaeger et al., 2017). Much of the literature exploring the impacts of climate change on water security, however, focuses on quantifying \r physical water scarcity. Discussions in this box consider physical water scarcity as a quantifiable measure of water availability compared to \r its demand and consider the societal elements of economic water scarcity to be part of the more comprehensive concept of water insecurity."


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"Using a Water Scarcity Index (WSI) defined as the ratio of demand and availability, accounting for EFRs, it is estimated that 4 billion \r people live under conditions of severe water scarcity for at least one month per year (Figure Box 4.1.1a; Mekonnen and Hoekstra, 2016). \r Nearly half of these people live in India and China. Although regions with high water scarcity are already naturally dry (virtually certain2\r ),\r human influence on climate is leading to reduced water availability in many regions. It is very likely that global patterns of soil moisture \r change are being driven by human influence on climate, and an overall global decline in soil moisture is attributable to greenhouse \r forcing [4.2.1.3]. Climate change patterns of streamflow change include declines in western North America, northeast South America, the \r Mediterranean and South Asia (medium confidence) [4.2.3]. However, quantification of the contribution of anthropogenic climate change \r [...]"


id: 65ee3415abd0e66f7756680bd2b58a07
created_at: 2023-04-19 13:22:53
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"Figure Box 4.1.1 |  Geographical distributions of current water scarcity and levels of challenge for policies addressing future change.\r (a) The number of months per year with severe water scarcity (ratio of water demand to availability > 1.0). Reproduced from Mekonnen and Hoekstra (2016).\r (b) Local levels of policy challenges for addressing water scarcity by 2050, considering both the central estimate (median) and the change uncertainty in projections of a \r Water Scarcity Index (WSI) from the present day to 2050 (Greve et al., 2018). Projections used five CMIP5 climate models, three global hydrological models from ISIMIP \r and three Shared Socioeconomic Pathways (SSPs). Levels of policy challenges refer to the scale and nature of policies to address water scarcity and range from monitoring \r and reviewing risks ('low') through transitional changes in water systems ('medium') to transformational changes ('high'). Low policy challenges arise when the projected \r [...]"


id: ba8bb42e3468e370f3963680801cfe51
created_at: 2023-04-19 13:22:53
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"[...] water scarcity in 2050 is lower (<0.4), and the level of uncertainty remains relatively stable in future projections. Medium policy challenge arises when either the central \r estimate of water scarcity remains low but uncertainty increases, or the uncertainty is stable but the central estimate of water scarcity for 2050 is higher (>0.4). High \r policy challenges arise when the central estimate of water scarcity is higher and the uncertainty increases. White areas show grid points defined as non-water-scarce (75th \r quantile of the WSI < 0.1 at all times) or very low average water demand. Reproduced from Greve et al. (2018)."


id: bd213d5a501a28a58549d98ea692aaa3
created_at: 2023-04-19 13:22:53
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"Gain et al. (2016) define a Global Water Security Index (GWSI) metric on a scale of 0 to 1 combining indicators of relative levels of availability \r of freshwater, accessibility to water services, water management and water quality and safety (including flood risk, which can affect water \r quality as well as being a direct physical hazard). Global application of this index indicates large worldwide differences in water security \r arising from different combinations of reasons (Figure Box 4.1.2a). In North Africa, the Middle East, large parts of the Indian sub-continent \r and north China, low water security arises predominantly from low water availability. However, many areas with relatively high water \r availability have relatively low levels of water security due to other factors. In 2015, 29% of the world's population did not have access to safe \r [...]"


id: fcfeed4790cdca7abaf1643108b4cc00
created_at: 2023-04-19 13:22:53
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content:
"[...] drinking water (Ritchie and Roser, 2019). In large parts of South and Southeast Asia, significant contributions to water insecurity came from \r increased flood risk and deteriorated water quality (Burgess et al., 2010; Ward et al., 2017; Farinosi et al., 2018). Water availability is relatively \r high across most of Africa, but water security is relatively low due to low accessibility, management and safety/quality standards. Most \r people in Africa do not have access to safe drinking water and improved sanitation (Marson and Savin, 2015; Naik, 2017; Armah et al., 2018)."


id: f4cf12233a6aa18daf22022fe0ab4a8e
created_at: 2023-04-19 13:22:53
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content:
"(a) Top: a global map of local values of GWSI constructed from the following components with their subjectively weighted contribution to the combined metric indicated \r in brackets. Middle left: relative effectiveness of water management (15%), comprising a World Governance Index at country scale (itself representing six components: \r voice and accountability, political stability and absence of violence/terrorism, government effectiveness, regulatory quality, rule of law and control of corruption) and \r indicators of transboundary legal frameworks and political tensions at a river-basin scale. Middle right: relative accessibility to water services (20%), including drinking \r water and sanitation. Bottom left: relative water quality and safety (20%), including a Water Quality Index and Flood Frequency Index. Bottom right: relative availability of \r [...]"


id: 31b333ca4095a2e5ad267547f2759b1b
created_at: 2023-04-19 13:22:53
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vector_id: 5987
content:
"[...] fresh water (45%), comprising a Water Scarcity Index, Drought Index and the groundwater depletion rate. Data for the components do not apply to the same set of dates \r but are generally applicable to recent decades up to 2010. White areas indicate no data available for at least one component. For further details, see Gain et al. (2016).\r (b) Factors through which climate change or action on mitigation or adaptation could influence water security."


id: a4daefdf0d8f11b0def39eee6630bdcb
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 26227
content:
"Future water security will depend on the magnitude, rate and regional details of future climate change and non-climatic factors, including \r agricultural practices, water demand and governance. In many cases, climate change may not be the dominant factor affecting water \r security. Nevertheless, climate change poses clear risks to water security in many regions through potential impacts on water availability, \r quality and flooding. The range of possible outcomes is extremely large, and assessing the likelihood of particular outcomes depends on \r consideration of uncertain regional climate changes and uncertain socioeconomic futures. Uncertainty in future water scarcity projections \r makes climate change risks to water security and planning for adaptation challenging. Limiting climate change to lower levels of global \r warming would reduce the risks to water security arising from climate change, partly because uncertainties in regional climate change \r [...]"


id: 6e50fe9d6c19cdd24651678ba68a3da7
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
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"In summary, roughly half of the world's population are assessed as currently subject to severe water scarcity for at least some part \r of the year due to climatic and non-climatic factors, and this is projected to be exacerbated at higher levels of warming (medium \r confidence). General water insecurity issues are seen worldwide, particularly in South Asia, North China, Africa and the Middle East, due \r to high population densities often coupled with low water availability, accessibility, quality and governance (high confidence). Areas with \r high water availability can also be water-insecure due to increased flood risk, deteriorated water quality, and poor governance (high \r confidence). Future water security will depend on the evolution of all these socioeconomic and governance factors and future regional \r climate change (high confidence). The main climate change contribution to water insecurity is the potential for reduced water availability, \r [...]"


id: 377a00112b805321b5d61d80874f2b00
created_at: 2023-04-19 13:22:53
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content:
"[...] with a secondary contribution from increased flooding risk (medium confidence). Future socioeconomic conditions are a crucial driver of \r water insecurity, implying the need for further adaptation to some level of future climate change (medium confidence). However, policy \r challenges are high in many regions, with uncertainty in the regional climate outcomes being a key factor (high confidence)."


id: ae00b858d3ae35037636d553e1734d4b
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 27855
content:
"The Sixth Assessment Report (AR6) Working Group I (WGI) (Douville \r et  al., 2021) concluded that anthropogenic climate change has \r increased atmospheric moisture and precipitation intensity (very likely\r by 2-3% per 1degC) (high confidence), increased terrestrial ET (medium \r confidence) and contributed to drying in dry summer climates including \r in the Mediterranean, southwestern Australia, southwestern South \r America, South Africa and western North America (medium to high \r confidence), and has caused earlier onset of snowmelt and increased \r melting of glaciers (high confidence) since the mid-20th century. The \r report also stated with high confidence that the water cycle variability \r and extremes are projected to intensify, regardless of the mitigation \r policy. The share of the global population affected by water-related \r hazards and water availability issues is projected to increase with the \r intensification of water cycle variability and extremes. They concluded \r [...]"


id: b23172aca126b3c9f8017211afdf78e5
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
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content:
"Second, this chapter follows the developments set in motion by \r SR1.5, SRCCL and SROCC to incorporate Indigenous knowledge (IK), \r traditional knowledge (TK) and local knowledge (LK). SR1.5 stated \r that disadvantaged and vulnerable populations, including Indigenous \r Peoples and certain local communities, are at disproportionately \r higher risk of suffering adverse consequences due to global warming \r of 1.5degC or more (Roy et al., 2018). SRCCL highlighted the enhanced \r efficacy of decision-making and governance with the involvement \r of local stakeholders, particularly those most vulnerable to climate \r change, such as Indigenous Peoples (Arneth et  al., 2019). SROCC \r found adaptation efforts have benefited from the inclusion of IK and \r LK (IKLK) (Abram et al., 2019). In this chapter, we engage directly with \r Indigenous contributing authors and use multiple evidence-based \r approaches, as undertaken by the IPBES (Tengo et  al., 2014; Tengo \r [...]"


id: f21a70b61b6454305ac3fdb9aa852231
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content:
"[...] et al., 2017). This approach is guided by the understanding that the co\u0002production of knowledge (between scholars and local communities) \r about water and climate change vulnerability, impacts and adaptation \r has the potential to lead to new water knowledge and context\u0002specific governance strategies (Arsenault et  al., 2019; Chakraborty \r and Sherpa, 2021). Additionally, shifting beyond the exclusive use \r of technical knowledge and Western viewpoints redresses the \r shortcomings of resource- and security-oriented understandings to \r water and acknowledges the more holistic and relational approaches \r common to IKLK (Section 4.8.4) (Stefanelli et al., 2017; Wilson, 2019; \r Chakraborty and Sherpa, 2021)."


id: 5f129ba4d00cce2b6adc2c48d5009563
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vector_id: 14026
content:
"annual or seasonal precipitation and others less, (b) many regions have \r seen increased heavy precipitation, and many have seen either increases \r or decreases in dry spells and (c) some regions have seen shifts towards \r heavier precipitation events separated by more prolonged dry spells \r (Section  4.2.1.1). Observationally based calculations suggest that ET \r has changed in response to changes in precipitation and increasing \r temperatures, resulting in changing patterns of soil moisture worldwide \r which are now detectable by satellite remote sensing (Sections 4.2.1.2, \r 4.2.1.3). Rising temperatures have caused profound and extensive \r changes in the global cryosphere, with mountain glaciers, land ice and \r snow cover shrinking, causing substantial, permanent impacts on the \r ways of life of people in these regions, particularly Indigenous Peoples \r with strong cultural links to long-term or seasonally frozen environments \r [...]"


id: bc28d2a3ccdd0ee5af1a2d1e2ec6527f
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index: climate_gpt_v2
vector_id: 30343
content:
"[...] (Sections 4.2.2, 4.3.8). Groundwater recharge in spring may have been \r reduced due to shorter snowmelt seasons, although the dominant impact \r on groundwater has been non-climatic and through intensification of \r irrigation (Section 4.2.6). The global-scale pattern of streamflow changes \r is now attributable to observed historical climate change, with human \r land and water use insufficient by themselves to explain the observed \r streamflow changes at global scales (Section 4.2.3). Numerous examples \r of extreme hydrometeorological events, including heavy precipitation, \r flooding, drought and wildfire events causing deaths, high levels of \r economic damage and extensive ecological impacts, have been shown \r to have been made more likely by human influence on climate through \r increased GHG concentrations in the atmosphere (Sections 4.2.1.1, 4.2.4, \r 4.2.5). Overall, there is a clear picture of human alteration of the global \r [...]"


id: 81e93593cd915b6bb48422f4a37bc749
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vector_id: 19982
content:
"The intensity of heavy precipitation has increased in many regions (high \r confidence), including much of North America, most of Europe, most \r of the Indian sub-continent, parts of northern and southeastern Asia, \r much of southern South America, parts of southern Africa and parts of \r central, northern and western Australia (Figure 4.3 f) (Dunn et al., 2020; \r Sun et al., 2020). Conversely, heavy precipitation has decreased in some \r regions, including eastern Australia, northeastern South America and \r western Africa. The length of dry spells has also changed, with increases \r in annual mean consecutive dry days (CDD) in large areas of western, \r eastern and southern Africa, eastern and southwestern South America, \r and Southeast Asia, and decreases across much of North America \r (Figure 4.3g). Precipitation extremes have changed in some places where \r annual precipitation shows no trend. Some regions such as southern \r [...]"


id: 6b7dcf71d3e16036d99b3a2d15083195
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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content:
"[...] Africa and parts of southern South America are seeing increased heavy \r precipitation and longer dry spells. Many regions with changing extremes \r are highly populated, such as the Indian sub-continent, Southeast Asia, \r Europe and parts of North America, South America and southern Africa \r (Figure 4.3h,i). Substantially more people (~709 million) live in regions \r where annual maximum one-day precipitation has increased than in \r regions where it has decreased (~86  million) (medium confidence). \r However, more people are experiencing longer dry spells than shorter \r dry spells: approximately 711 million people live in places where annual \r mean CDD is longer than in the 1950s, and ~404 million in places with \r shorter CDD (medium confidence) (Figure 4.3i)."


id: 6c8fc6321745ebab5ce8635d93fb256d
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vector_id: 16389
content:
"AR6 WGI (Douville et  al., 2021) concluded that GHG forcing has \r driven increased contrasts in precipitation amounts between wet and \r dry seasons and weather regimes over tropical land areas (medium \r confidence), with a detectable precipitation increase in the northern \r high latitudes (high confidence). GHG forcing has also contributed \r to drying in dry summer climates, including the Mediterranean, \r southwestern Australia, southwestern South America, South Africa \r and western North America (medium to high confidence) (Figure 4.3). \r AR6 WGI (Seneviratne et al., 2021) also concluded that the frequency \r and intensity of heavy precipitation events have likely increased at the \r global scale over most land regions with good observational coverage. \r Heavy precipitation has likely increased on the continental scale \r over North America, Europe and Asia. Regional increases in heavy \r precipitation frequency and (or) intensity have been observed with \r [...]"


id: a7985af5dd9046f78a456cc614c31e17
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content:
"[...] at least medium confidence for nearly half of the AR6 WGI climatic \r regions (Figure 4.3). Human influence, in particular GHG emissions, is \r likely the main driver of the observed global-scale intensification of \r heavy precipitation in land regions"


id: c6f39c77ed13e78c8bba146844052785
created_at: 2023-04-19 13:22:53
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vector_id: 32312
content:
"Large numbers of people live in regions where the annual mean \r precipitation is now 'unfamiliar' compared to the mean and variability \r between 1891 and 2016 (Figure  4.3c). \"Unfamiliar\" is defined as \r the long-term change being greater than one standard deviation in \r the annual data (Figure  4.3b). In 2020, approximately 498  million \r people lived in unfamiliarly wet areas, where the long-term average \r precipitation is as high as previously seen in only about one in \r 6 years (medium confidence) (Figure 4.3c). These areas are primarily \r in mid and high latitudes (Hawkins et al., 2020). On the other hand, \r approximately 163 million people lived in unfamiliarly dry areas, mostly \r in low latitudes (medium confidence). Due to high variability over time, \r the signal of long-term change in annual mean precipitation is not \r distinguishable from the noise of variability in many areas (Hawkins \r et al., 2020), implying that the local annual precipitation cannot yet be \r [...]"


id: 23701798b42e77dee13b9176e8113d1
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 3432
content:
"Recent studies report global ET increases from the early 1980s to \r 2009 and 2013 (Table  4.1). Calculations informed by observations \r suggest that ET has increased in most regions, with statistically \r significant (p<0.05) trends of up to 10 mm yr-2 observed in large parts \r of North America and northern Eurasia. Larger increases in ET are \r also observed in several regions, including northeast Brazil, western \r central Africa, southern Africa, southern India, southern China, and \r northern Australia. Decreases of around 10 mm yr-2 are reported for \r western Amazonia and central Africa (Miralles et al., 2014), although \r not across all data sets (Zeng et  al., 2018). In estimates of past \r changes in long-term drying or wetting of the land surface driven by \r climate, uncertainties in ET observations or reconstructions make a \r more substantial contribution to the overall uncertainty than observed \r changes in precipitation (Greve et al., 2014). Other changes in ET are \r [...]"


id: 39e2131d0fb64ee65529a0986bba8ff5
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content:
"Regional and global decreasing trends in glacier mass loss are about \r linear until 1990, after which they accelerated, especially in western \r Canada, the USA, and the southern Andes (WGMS, 2017). There is a \r worldwide growth in the number, total area and total volume of glacial \r lakes by around 50% between 1990 to 2018 due to the global increase \r in glacier melt rate (Shugar et al., 2020) (Shugar et al., 2020) that can \r potentially increase risks of glacial lake outburst floods (GLOFs) with \r significant negative societal impacts (Ikeda et  al., 2016). A drop in \r glacier runoff has happened in the regions where the glaciers have \r already passed their peak water stage, for example, in the Canadian \r Rocky Mountains, European Alps, tropical Andes and North Caucasus \r (Bard et al., 2015; Hock et al., 2019b; Rets et al., 2020). There is medium \r confidence that the accelerated melting of glaciers has negatively \r impacted glacier-supported irrigation systems worldwide (Buytaert \r [...]"


id: a58b7a772fcb97a592e576a2f138a4ef
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content:
"[...] et al., 2017; Nusser and Schmidt, 2017; Xenarios et al., 2019). Varying \r impacts on hydropower production (Schaefli et al., 2019) and tourism \r industry in some places due to cryospheric changes have also been \r documented (Hoy et al., 2016; Steiger et al., 2019)."


id: 9c20dac6b365fc42a0e63a330eed96a2
created_at: 2023-04-19 13:22:53
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content:
"Recent studies confirmed with high confidence that snow cover extent \r continues to decrease across the Northern Hemisphere in all months \r of the year (see Douville et al. (2021); Eyring et al. (2021); Fox-Kemper \r et al. (2021) for more details). From 1922 to 2018, snow cover extent in \r the Northern Hemisphere peaked in the 1950s to 1970s (Mudryk et al., \r 2020) and has consistently reduced since the end of the 20th century \r (Hernandez-Henriquez et  al., 2015; Thackeray et  al., 2016; Mudryk \r et al., 2017; Beniston et al., 2018; Hammond et al., 2018; Thackeray \r et al., 2019; Mudryk et al., 2020). The consistently negative snow-mass \r trend of approximately 5 Gt yr-1 in 1981-2018 for all winter-spring \r months (Mudryk et al., 2020), including 4.6 Gt yr-1 decrease of snow \r mass across North America and a negligible trend across Eurasia, \r has been observed (Pulliainen et al., 2020). Negative trends in snow\u0002dominated period duration of 2.0-6.5 weeks per decade was detected \r [...]"


id: ffcb3a6fd37d83b1a9273a540aa14d0d
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vector_id: 42394
content:
"[...] from surface and satellite observations during 1971-2014 (Allchin \r and Dery, 2017), mainly owing to earlier seasonal snowmelt (Fox\u0002Kemper et  al., 2021). The observed decrease of snow cover metrics \r (extent, mass, duration) led to changes in runoff seasonality and has \r impacted water supply infrastructure (Bloschl et al., 2017; Huss et al., \r 2017), particularly in southwestern Russia, western USA and central \r Asia. In these regions, snowmelt runoff accounts for more than 30% \r of irrigated water supplies (Qin et  al., 2020). Negative impacts on \r hydropower production due to changes in the seasonality of snowmelt \r have also been documented (Kopytkovskiy et al., 2015)."


id: d28107a957b6bba458858c3a8c20b5fa
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vector_id: 34388
content:
"Permafrost changes mainly refer to changes in temperature and active \r layer thickness (ALT) (Hock et  al., 2019b; Fox-Kemper et  al., 2021; \r Gulev et  al., 2021). Permafrost temperature near the depth of zero \r annual temperature amplitude increased globally by 0.29+-0.12degC \r during 2007-2016, by 0.39+-0.15degC in the continuous permafrost \r and by 0.20+-0.10degC in the discontinuous permafrost (Biskaborn \r et al., 2019). Thus, permafrost has been warming during the last 3-4 \r decades (Romanovsky et  al., 2017) with a rate of 0.4degC-1.4degC per \r decade throughout the Russian Arctic, 0.1degC-0.8degC per decade in \r Alaska and Arctic Canada during 2007-2016 (Biskaborn et al., 2019) \r and 0.1degC-0.24degC per decade in the Tibetan plateau (Wu et al., 2015). \r The ALT has also been increasing in the European and Russian Arctic and \r high-mountain areas of Eurasia since the mid-1990s (Hock et al., 2019b; \r Fox-Kemper et al., 2021; Gulev et al., 2021). Unfortunately, unlike glaciers \r [...]"


id: eaf6f60c7b9e424eb51707093f612cab
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"[...] and snow, the lack of in situ observations on permafrost still cannot be \r compensated for by remote sensing. Still, some methodological progress \r on this front has been happening recently (Nitze et al., 2018)."


id: f9938ab0447e8e796336b83e8f39c1b
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vector_id: 41276
content:
"different basins worldwide, with conclusions on the relative contribution \r of climatic and anthropogenic factors sometimes depending on the \r methodology (Dey and Mishra, 2017). Precipitation explains over 80% \r of the changes in discharge of large rivers from 1950 to 2010 in northern \r Asia and northern Europe, where the impact of human activities is \r relatively limited (Li et al., 2020b). In northwest Europe, precipitation \r and evaporation changes explain many observed trends in streamflow \r (Vicente-Serrano et al., 2019). In several polar areas in northern Europe \r (e.g., Finland), North America (e.g., British Columbia in Canada) and \r Siberia, many studies reported increased winter streamflow primarily \r due to climate warming, for instance, more rainfall instead of snowfall \r and more glacier runoff in the winter period (e.g., Bonsal et al., 2020) \r (Section 4.2.2). A similar phenomenon of the earlier snowmelt runoff is \r [...]"


id: 304cd763d1ae74b95e6fdd95efbb82dd
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vector_id: 5749
content:
"[...] also found in North America during 1960-2014 (Dudley et al., 2017). \r Thus, climate drivers largely explain changes in the average and \r maximum runoff of predominantly snow-fed rivers (Yang et al., 2015a; \r Bring et al., 2016; Tananaev et al., 2016; Frolova et al., 2017b; Ficklin \r et al., 2018; Magritsky et al., 2018; Rets et al., 2018)."


id: c525c5042989a19d315680417115224f
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 31994
content:
"Shi et  al. (2019) found that in 40 major basins worldwide, both \r climatic and direct human impact contribute to observed flow \r changes to varying degrees. Climate change or variability is the main \r contributor to changes in basin-scale trends for 75% of rivers, while \r direct human effects on streamflow dominate for 25%. However, this \r does not consider attribution of the climate drivers to anthropogenic \r forcing. Using time series of low, mean and high river flows from 7250 \r observatories around the world (1971-2010) and global hydrological \r models (GHMs) driven by Earth System Model (ESM) simulations with \r and without anthropogenic forcing of climate change, Gudmundsson \r et  al. (2021) also found direct human influence to have a relatively \r small impact on global patterns of streamflow trends. Gudmundsson \r et al. (2021) further identified anthropogenic climate change as a causal \r driver of the global pattern of recent trends in mean and extreme river \r [...]"


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content:
"[...] flow (Figure 4.7). Overall, the sign of observed trends and simulations \r accounting for human influence on the climate system was found to \r be consistent for decreased mean flows in western and eastern North \r America, southern Europe, northeast South America and the Indian sub\u0002continent, and increased flows in northern Europe. Similar conclusions \r were drawn for low and high flows, except for the Indian sub-continent. \r However, in some regions, the observed trend was opposite to that \r simulated with anthropogenic climate forcing. Thus, human water and \r land use alone did not explain the observed pattern of trends."


id: 5714de761bc8216be1bbacdf0c6b22fc
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 12574
content:
"There is high confidence that the frequency and magnitude of river \r floods have changed in the past several decades in some regions \r mentioned below (and in WGI 11.5.2; SM4.1) with impacts across \r human and natural systems (Section  4.3). A global flood database \r based on in situ measurement and satellite remote-sensing during \r 1985-2015 show that floods have increased 4-fold and 2.5-fold in the \r tropics and northern mid-latitudes, respectively (Najibi and Devineni, \r 2018). Estimates of flood exposure using satellite-derived inundation \r area and high-resolution population data showed a 20-24% increase \r during 2000-2018 (Tellman et al., 2021). Analyses of in situ streamflow \r measurement showed both increases and decreases in the frequency \r of river floods for 1960-2010 in Europe (Berghuijs et  al., 2017a; \r Bloschl et al., 2019a) and the USA (Berghuijs et al., 2017a), an overall \r increase in China, Brazil and Australia (Berghuijs et  al., 2017a) but \r [...]"


id: 461cda93a3542afa7b4b785a1a3a602e
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 9552
content:
"[...] decrease in some areas in the Mediterranean (Tramblay et al., 2019) \r and southern Australia (Ishak et al., 2013; Do et al., 2017). Warming \r in the last 40-60 years has led to a 1-10-d earlier per decade spring \r flood occurrence depending on the location (the most frequent being \r 2-4 d per decade) (high confidence) (Yang L. et  al., 2015; Bloschl \r et al., 2017; Dudley et al., 2017; Solander et al., 2017; Rokaya et al., \r 2018; Kireeva et al., 2020)."


id: 1d80b8a3f9d2dc05f7981986585f4423
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 2368
content:
"Between 1970 to 2019, 44% of all disasters and 31% of all economic \r losses were flood related (WMO, 2021). Observed flood risks changes \r in recent decades are often caused by human factors such as increased \r urbanisation and population growth rather than climate change \r alone (Tramblay et al., 2019). There is medium confidence that flood \r vulnerability varies among various regions and countries (Jongman \r et al., 2012; Scussolini et al., 2016; Tanoue et al., 2016) (Figure 4.8), \r reflecting differences in GDP, severity and characteristics of hazard and \r political and social conditions (Rufat et al., 2015). Flood vulnerability \r has decreased with economic development in many regions, while \r increased exposure has elevated risk in some places (Mechler, 2016; \r Tanoue et al., 2016). Global annual mean expected damage considering \r the current flood protection standard is estimated to be USD 54 million \r under the climate of 1976-2005 and unevenly distributed (Alfieri et al., \r [...]"


id: 512e4a7f19e6a9d8e315332735e5e4e1
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 11568
content:
"[...] 2017). Similar estimation using different models shows an increase of \r flood exposure in the past (USD 31 million for 1971-1990 and USD \r 45 million for 1991-2010 without population change as fixed in 2010) \r (Tanoue et al., 2016) (Section 4.7.5)."


id: 138e9f8a7f875cf15536d2dfee2d279
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 653
content:
"The link between rainfall and flooding is complex. While observed \r increases in extreme precipitation have increased the frequency and \r magnitude of pluvial floods and river floods in some regions, floods \r could decrease in some regions due to other factors. These factors \r could include soil wetness condition, cryospheric change, land cover \r change and river system management, adaptation measures or water \r usage within the river basin (WGI FAQ8.2). For example, in the USA \r and Europe, a study indicated that major (e.g., 25-100-year return \r period) floods did not show significant long-term trends (Hodgkins \r et  al., 2019). Nevertheless, anthropogenic climate change increased \r the likelihood of a number of major heavy precipitation events and \r floods that resulted in disastrous impacts in southern and eastern \r Asia, Europe, North America and South America (Table  4.3) (high \r confidence). Davenport et al. (2021) demonstrated that anthropogenic \r [...]"


id: bc05c8449d7104a3a25d7416cd2f1ea1
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 30314
content:
"[...] changes in precipitation extremes had contributed one third of the \r cost of flood damages (from 1988 to 2017) in the USA. Anthropogenic \r climate change has altered 64% (eight out of 22 events increased, \r eight decreased) of floods events with significant losses and damages \r during 2010-2013 (Hirabayashi et  al., 2021a). Gudmundsson et  al. \r (2021) attributed observed change in extreme river flow trends to \r anthropogenic climate change (Section  4.2.3). Although there is \r growing evidence on the effects of anthropogenic climate change \r on each event, given the relatively poor regional coverage and high \r model uncertainty, there is low confidence in the attribution of human\u0002induced climate change to flood change on the global scale."


id: b169145ea74570d565611945de5679ca
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 28436
content:
"When hazard, vulnerability and exposure are considered together, \r drought risk is lower for sparsely populated regions, such as tundra \r and tropical forests, and higher for populated areas and intensive \r crop and livestock farming regions, such as southern and central Asia, \r southeastern South America, central Europe and the southeastern \r USA (Figure  4.9). Dynamics in exposure and vulnerability are rarely \r addressed (Jurgilevich et al., 2017; Hagenlocher et al., 2019). Quantifying \r economic vulnerability to drought in terms of damages as a percentage \r of exposed GDP, Formetta and Feyen (2019) show a disproportionate \r burden of drought impact on low-income countries, but with a clear \r decrease in global economic drought vulnerability between 1980-1989 \r and 2007-2016, including a convergence between lower-income and \r higher-income countries due to stronger vulnerability reduction in \r less-developed countries. Nevertheless, during 2007-2016, economic \r [...]"


id: 8ad84ddbea4e6756d1d0dee917904032
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 21598
content:
"[...] vulnerability to drought was twice as high in lower-income countries \r compared to higher-income countries (Formetta and Feyen, 2019)."


id: 4ee4c0c00cd9a09df2b5fa62058bf12d
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 11161
content:
"In addition, there is high confidence in anthropogenic influence on \r increased meteorological drought in southwestern Australia and \r medium confidence that recent drying and severe droughts in southern \r Africa and southwestern South America can be attributed to human \r influence. Increased agricultural/ecological and (or) meteorological and \r (or) hydrological drought is also seen with either medium confidence \r or high confidence in the trend but with low confidence on attribution \r to anthropogenic climate change in western, northeastern and central \r Africa; central, eastern and southern Asia; eastern Australia; southern \r and northeastern South America and the South American monsoon \r region; and western and central Europe. Finally, decreased drought in \r one or more categories is seen with medium confidence in western \r and eastern Siberia; northern and central Australia; southeastern South \r America; central North America and northern Europe, but with low \r [...]"


id: 9b5774e01e325fe952d628704d7d94b4
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 24579
content:
"[...] confidence in attribution to anthropogenic influence, except in northern \r Europe, where anthropogenic influence on decreased meteorological \r drought is assessed with medium confidence."


id: c804649b0331e850125c74ba7f0a2dd
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 32500
content:
"Globally, groundwater use has societal and economic benefits, providing \r a critical buffer against precipitation variability. Groundwater irrigation \r has ensured food security, livelihood support and poverty alleviation, \r for example, in India (Sekhri, 2014), Bangladesh (Salem et al., 2018) \r and sub-Saharan Africa (Taylor et al., 2013a; Cuthbert et al., 2019b). \r Groundwater is a safe drinking water source during natural hazard\u0002induced disasters (Richts and Vrba, 2016). However, groundwater over\u0002exploitation leads to the attenuation of societal benefits, including \r reduced agricultural production (Asoka and Mishra, 2020; Jain et al., \r 2021), decrease in adaptive capacity of communities (Blakeslee et al., \r 2020) and water quality deterioration (Mas-Pla and Mencio, 2019). \r Loss of traditional water systems based on groundwater, such as \r foggara in Tunisia (Mokadem et al., 2018), qanat in Pakistan (Mustafa \r and Usman Qazi, 2008), aflaj in Oman (Remmington, 2018) and spring \r [...]"


id: 607e8c8925dcb08fee58915f0c3136a7
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 14283
content:
"[...] boxes in the Himalayas (Kumar and Sen, 2018), also leads to loss of \r cultural values for local communities."


id: 592c9a8a18b37f0fb943f3883b3a96a5
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 12932
content:
"(Shamsudduha and Taylor, 2020) of GRACE satellite measurements \r (2002-2016) for the 37 world's large aquifer systems reveals that \r trends in groundwater storage are mostly nonlinear and declines are \r not secular (high confidence). There are strong statistical associations \r between changes in groundwater storage and extreme annual \r precipitation from 1901 to 2016 in the Great Artesian Basin (Australia) \r and the California Central Valley aquifer (USA). Groundwater recharge \r of high magnitudes can be generated from intensive precipitation \r events. On the other hand, recharge can become more episodic, mostly \r in arid to semiarid locations (robust evidence, medium agreement). For \r example, in central Tanzania, seven rainfall events between 1955 and \r 2010 generated 60% of total recharge (Taylor et al., 2013b). Similarly, \r in southern India (Asoka et  al., 2018) and the southwestern USA \r (Thomas et al., 2016), focused recharge via losses from ephemeral river \r [...]"


id: 7a662aae4338d38c031535ad8b184bd9
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 18730
content:
"Groundwater-dependent ecosystems (GDEs), such as terrestrial \r wetlands, stream ecosystems and estuarine and marine ecosystems \r (Klove et al., 2014), support wetlands and biodiversity, provide water \r supply and baseflows to rivers, offer recreational services and help \r control floods (Rohde et al., 2017). Globally, 10-23% of the watersheds \r have reached the environmental flow limits due to groundwater \r pumping (de Graaf et al., 2019). A recent study of 4.2 million wells \r across the USA shows that induced groundwater recharge in nearly \r two thirds of these wells could reduce stream discharges, thereby \r threatening GDEs (Jasechko et al., 2021). Work (2020) found reduced \r spring flow due to increased groundwater abstraction in 26 out of 56 \r springs studied in Florida (USA). GDEs in semiarid and arid regions \r tend to have much longer groundwater response times and may be \r more resilient to climate change than those in humid areas where \r [...]"


id: 860fdeb1eac7c5b6b7f85949ed9213a3
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 20729
content:
"[...] groundwater occurrence is mostly at shallow levels (Cuthbert et al., \r 2019a; Opie et al., 2020). However, groundwater depletion impacts on \r the full range of ecosystem services remain understudied (Bierkens and \r Wada, 2019)."


id: 60c41664a335960180a02728e5c5926a
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 14322
content:
"aesthetic value, compromising recreational activities, reducing tourism \r and property values and creating challenges for management and \r drinking water treatment (Eves and Wilkinson, 2014; Khan et al., 2015; \r Walters et al., 2015).\r Between 2000 and 2010, ~10% of the global population faced \r adverse water quality issues (van Vliet et al., 2021). Adverse drinking \r water quality has been associated with extreme weather events \r in countries located in Asia, Africa and South and North America \r (Jagai et  al., 2015; Levy et  al., 2016; Huynh and Stringer, 2018; \r Leal Filho et al., 2018; Abedin et al., 2019) (medium evidence, high \r agreement). Dilution factors in 635 of 1049 US streams fell extremely \r low during drought conditions. Additionally, the safety threshold for \r endocrine-disrupting compound concentration exceeded in roughly \r a third of streams studied (Rice and Westerhoff, 2017). Natural acid \r rock drainage, which can potentially release toxic substances, has \r [...]"


id: 22a2d4a4e441ad82d2e3bae6ae333bd4
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 3310
content:
"[...] experienced intensification in an alpine catchment of the Central \r Pyrenees due to climate change and severe droughts in the last \r decade. River length affected by natural acid drainage increased \r from 5 km in 1945 to 35 km in 2018 (Zarroca et al., 2021). Threefold \r increases in contaminants and fivefold increases in nutrients have \r been observed in water sources after wildfires (Khan et al., 2015). Due \r to permafrost thawing, the concentration of major ions, especially \r SO4\r 2- in two high Arctic lakes, has rapidly increased up to 500% and \r 340% during 2006-2016 and 2008-2016, respectively (Roberts et al., \r 2017). The exports of dissolved organic carbon (DOC), particulate \r organic carbon and mercury in six Arctic rivers were reported to \r increase with significant deepening of active layers caused by climate \r warming during 1999-2015 (Mu et al., 2019). Sustained warming in \r Lake Tanganyika in Zambia during the last ~150 years reduced lake \r [...]"


id: 1bc459bb47691498cafb4d0bde19853
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 2071
content:
"[...] mixing, which has depressed algal production, shrunk the oxygenated \r benthic habitat by 38% and further reduced fish and mollusc yield \r (Cohen et  al., 2016). From 1994 to 2010, coastal benthos at King \r George Island in Antarctica have observed a remarkable shift primarily \r linked to ongoing climate warming and the increased sediment runoff \r triggered by glacier retreats (Sahade et al., 2015). The recovery time \r of macroinvertebrates from floods was found longer in cases of pre\u0002existing pollution problems (Smith et al., 2019a)."


id: 45f7a2ea47e6941eab4d3c2f65422679
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 9533
content:
"Climate change impacts soil erosion and sedimentation rates both \r directly from increasing rainfall or snowmelt intensity (Vanmaercke \r et al., 2014; Polyakov et al., 2017; Diodato et al., 2018; Golosov et al., \r 2018; Li et al., 2020a; Li et al., 2020b) and indirectly from increasing \r wildfires (Gould et al., 2016; Langhans et al., 2016; DeLong et al., 2018), \r permafrost thawing (Schiefer et al., 2018; Lafreniere and Lamoureux, \r 2019; Ward Jones et al., 2019) and vegetation cover changes (Micheletti \r et al., 2015; Potemkina and Potemkin, 2015; Carrivick and Heckmann, \r 2017; Beel et  al., 2018). In addition, accelerated soil erosion and \r sedimentation have severe societal impacts through land degradation, \r reduced soil productivity and water quality (Section 4.2.7), increased \r eutrophication and disturbance to aquatic ecosystems (Section 4.3.5), \r sedimentation of waterways and damage to infrastructure (Graves et al., \r [...]"


id: 6850c3e6a52c7d880afbe176b694639b
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 15620
content:
"[...] 2015; Issaka and Ashraf, 2017; Schellenberg et al., 2017; Hewett et al., \r 2018; Panagos et al., 2018; Sartori et al., 2019) (medium confidence)."


id: edf2494e1d1e39c5b6ab3f3738704e9
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 39231
content:
"In the largest river basin of the Colombian Andes, regional climate change \r and land use activities (ploughing, grazing and deforestation) caused \r a 34% erosion rate increase over 10  years, with the anthropogenic \r soil erosion rate exceeding the climate-driven erosion rate (Restrepo \r and Escobar, 2018). Sedimentation increases due to soil erosion in \r mountainous regions burned by wildfires, as a result of warming and \r altered precipitation, is documented with high confidence in the USA \r (Gould et al., 2016; DeLong et al., 2018), Australia (Nyman et al., 2015; \r Langhans et al., 2016), China (Cui et al., 2014) and Greece (Karamesouti \r et al., 2016) and can potentially damage downstream aquatic ecosystems \r (Section 4.3.5) and water quality (Section 4.2.7) (Cui et al., 2014; Murphy \r et al., 2015; Langhans et al., 2016) (medium confidence). In Australia, for \r instance, sediment yields from post-fire debris flows (113-294 t ha-1) \r [...]"


id: 8d801f51e208773924c5fd5a85c9c147
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 22081
content:
"[...] are 2-3 orders of magnitude higher than annual background erosion \r rates from undisturbed forests (Nyman et al., 2015). The positive trend \r in sediment yield in small ponds in the semiarid southwestern USA over \r the last 90 years was not entirely related to the rainfall or runoff trends, \r but was a result of complex interaction between long-term changes in \r vegetation, soil and channel networks (Polyakov et al., 2017)."


id: 225263210639f650a9bf2982508dd8f1
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 3259
content:
"Regional climate changes (precipitation decrease) and human \r activities (landscape engineering, terracing, large-scale vegetation \r restoration, soil conservation) over the Loess Plateau (China) caused \r a distinct stepwise reduction in sediment loads from the upper-middle \r reach of the Yellow River, with 30% of the change related to climate \r change (Tian et al., 2019). Substantial increases in sediment flux were \r identified on the Tibetan Plateau (Li et al., 2020a; Li et al., 2021a), for \r example, the sediment load from the Tuotuohe headwater increased by \r 135% from 1985-1997 to 1998-2016, mainly due to climate change \r (Li et al., 2020a). In 1986-2015, the sedimentation rate in dry valley \r bottoms of the Southern Russian Plain was two-2-5 times lower than \r in 1963-1986 due to the warming-induced surface runoff reduction \r during spring snowmelt (Golosov et  al., 2018). Declining erosion \r trends are primarily associated with soil conservation management \r [...]"


id: 27b1979681469a4ca120374f3eaf2cf5
created_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 4166
content:
"[...] in northern Germany (Steinhoff-Knopp and Burkhard, 2018) and \r reforestation in southwestern China (Zhou et al., 2020)."


id: 55cfde8557beb2702e379d9390ee8f44
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 12369
content:
"Europe (Vanmaercke et al., 2014) and northern Africa (Achite and Ouillon, \r 2016). Still, such correlation is yet to be found for the other European \r rivers (Vanmaercke et  al., 2015). Increased sediment and particulate \r organic carbon fluxes in the Arctic regions are caused by permafrost \r warming (Schiefer et al., 2018; Lafreniere and Lamoureux, 2019; Ward \r Jones et al., 2019). Potemkina and Potemkin (2015) demonstrate that \r regional warming and permafrost degradation have contributed to an \r increased forested area over the last 40-70 years, reducing soil erosion \r in eastern Siberia. The sediment dynamics of small rivers in the eastern \r Italian Alps, depending on extreme floods, is sensitive to climate change \r (Rainato et  al., 2017). In the northeastern Italian Alps, precipitation \r change during 1986-2010 affected soil wetness conditions, influencing \r sediment load (Diodato et  al., 2018). Regional warming in northern \r [...]"


id: f7717a53a5bc65fa67cfb5eb1926d24b
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 40910
content:
"[...] Africa (Algeria) dramatically changed river streamflow and increased \r sediment load over four decades (84% more every decade compared to \r the previous) (Achite and Ouillon, 2016)."


id: d897d21ab73adb8b0bd95d0231299813
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 35398
content:
"Globally, 23% of croplands are irrigated, providing 34% of global calorie \r production. Of these lands, 68% experience blue water scarcity at the \r least one month yr-1 and 37% up to five months yr-1. Such agricultural \r water scarcity is experienced in mostly drought-prone areas in low\u0002income countries (Rosa et al., 2020a). Approximately three quarters of \r the global harvested areas (~454 million hectares) experienced drought\u0002induced yield losses between 1983 and 2009, and the cumulative \r production losses corresponded to USD 166 billion (Kim et al., 2019). \r Globally, droughts affected both harvested areas and yields, with a \r reported cereal production loss of 9-10% due to weather extremes \r between 1964 and 2007. Yield losses were greater by about 7% during \r recent droughts (1985-2007) due to greater damage--reducing \r harvested area--compared to losses from earlier droughts (1964-1984), \r with 8-11% greater losses in high-income countries than in low-income \r [...]"


id: 9bb84e070cfd9bd0cdd4972b07887d8
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
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index: climate_gpt_v2
vector_id: 24655
content:
"[...] ones (Lesk et al., 2016). Globally, between 1961 and 2006, it has been \r estimated that 25% yield loss occurred, with yield loss probability \r increasing by 22% for maize, 9% for rice and 22% for soybean under \r drought conditions (Leng and Hall, 2019). Mean climate and climate \r extremes are responsible for 20-49% of yield anomalies variance, with \r 18-45% of this variance attributable to droughts and heatwaves (Vogel \r et al., 2019). Drought has been singled out as a major driver of yield \r reductions globally (high confidence) (Lesk et  al., 2016; Meng et  al., \r 2016; Zipper et al., 2016; Anderson et al., 2019; Leng and Hall, 2019)."


id: a97ece55c07f91e5b0667edd19a4fb32
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 27042
content:
"Yields of major crops in semiarid regions, including the Mediterranean, \r sub-Saharan Africa, South Asia and Australia, are negatively affected \r by precipitation declines in the absence of irrigation (Iizumi et  al., \r 2018; Ray et al., 2019), but this trend is less evident in wetter regions \r (Iizumi et al., 2018). Precipitation and temperature changes reduced \r global mean yields of maize, wheat and soybeans by 4.1, 1.8 and \r 4.5%, respectively (Iizumi et  al., 2018). Of the global rice yield \r variability of ~32%, precipitation variability accounted for a larger \r share in drier South Asia than in wetter East and Southeast Asia \r (Ray et al., 2015). Between 1910 and 2014 agro-climatic conditions \r became more conducive to maize and soybean yield growth in the \r American Midwest due to increases in summer precipitation and \r cooling due to irrigation (Iizumi and Ramankutty, 2016; Mueller et al., \r 2016) (Box 4.3). In Australia, between 1990 and 2015, the negative \r [...]"


id: 4c226302fb49eba390fcb339d4839edc
created_at: 2023-04-19 13:22:53
updated_at: 2023-04-19 13:22:53
content_type: text
index: climate_gpt_v2
vector_id: 10654
content:
"[...] effects of reduced precipitation and rising temperature led to yield \r losses, but yield losses were partly avoided because of elevated \r CO2 atmospheric concentration and technological advancements \r (Hochman et  al., 2017a). Overall, temperature-only effects are \r stronger in wetter regions like Europe and East and Southeast Asia, \r and precipitation-only effects are stronger in drier regions (Iizumi \r et al., 2018; Ray et al., 2019) (medium evidence, high agreement). \r In Asia, the gap between rain-fed and irrigated maize yield widened "


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vector_id: 24266
content:
"from 5% in the 1980s to 10% in the 2000s (Meng et al., 2016). In \r North America, yields of maize and soybeans have increased (1958-\r 2007), yet meteorological drought has been associated with 13% of \r overall yield variability. However, yield variability was not a concern \r where irrigation is prevalent (Zipper et  al., 2016). However, when \r water scarcity has reduced irrigation, yields have been negatively \r impacted (Elias et  al., 2016). In Europe, yields have been affected \r negatively by droughts (Beillouin et  al., 2020), with losses tripling \r between 1964 and 2015 (Bras et al., 2021). In West Africa, between \r 2000 and 2009, drought, among other altered climate conditions, \r led to millet and sorghum yield reductions between 10 and 20% \r and 5 and 15%, respectively (Sultan et al., 2019). Between 2006 and \r 2016, droughts contributed to food insecurity and malnutrition in \r northern, eastern and southern Africa, Asia and the Pacific. In 36% of \r [...]"


id: 6c70861482000e2e3d3232123bf65492
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"[...] these nations--mainly in Africa--where severe droughts occurred, \r undernourishment increased (Phalkey et  al., 2015; Cooper et  al., \r 2019). An attribution study showed that anthropogenic emissions \r increased the chances of October-December droughts over the \r region by 1.4-4.3 times and resulted in below-average harvests in \r Zambia and South Africa (Nangombe et  al., 2020). Root crops, a \r staple in many tropics and subtropical countries, and vegetables are \r particularly prone to drought, leading to smaller fruits or crop failure \r (Daryanto et al., 2017; Bisbis et al., 2018). Livestock production has \r also been affected by changing seasonality, increasing frequency of \r drought, rising temperatures and vector-borne diseases and parasites \r through changes in the overall availability, as well as reduced \r nutritional value, of forage and feed crops (Varadan and Kumar, \r 2014; Naqvi et al., 2015; Zougmore et al., 2016; Henry et al., 2018; \r [...]"


id: e66680f838103ac1e7111f8df806cfbf
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"Floods have led to harvest failure and crop and fungal contamination \r (Liu et  al., 2013; Uyttendaele et  al., 2015). Globally, between 1980 \r and 2018, excess soil moisture has reduced rice, maize, soybean and \r wheat yields between 7 and 12% (Borgomeo et al., 2020). Changes \r in groundwater storage and availability, which are affected by the \r intensity of irrigated agriculture, also negatively impacted crop yields \r and cropping patterns (Section 4.2.6, Box 4.3, 4.7.2). Moreover, extreme \r precipitation can lead to increased surface flooding, waterlogging, \r soil erosion and susceptibility to salinisation (high confidence). For \r example, in Bangladesh, in March and April 2017, floods affected \r 220,000 ha of a nearly harvest-ready summer paddy crop and resulted \r in almost a 30% year-on-year increase in paddy prices. An attribution \r study of those pre-monsoon extreme rainfall events in Bangladesh \r concluded that anthropogenic climate change doubled the likelihood \r [...]"


id: 33155bfc53fe4729c627c8d296a3ed0d
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"[...] of the extreme rainfall event (Rimi et  al., 2019). Moreover, floods, \r extreme weather events and cyclones have led to animal escapes and \r infrastructure damage in aquaculture (Beveridge et al., 2018; Islam and \r Hoq, 2018; Naskar et al., 2018; Lebel et al., 2020) (see Section 5.9.1)."


id: ac5b139c655c19930a49de27e33e3bb6
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"Literature since AR5 confirms that temperature, precipitation and \r extreme weather events are linked to increased incidence and \r outbreaks of water-related and neglected tropical diseases (Colon\u0002Gonzalez et al., 2016; Levy et al., 2016; Azage et al., 2017; Harp et al., \r 2021) (high confidence). For example, the rainy season in Senegal has \r been associated with an 84% increase in relative risk of childhood \r diarrhoea, and an additional wet day per week was associated with \r up to 2% increases in diarrhoeal disease in Mozambique (Thiam et al., \r 2017; Horn et al., 2018). In Ecuador, increases of 1.5 cases of diarrhoea \r per 1000 were associated with heavy rainfall after dry periods, while \r a decrease of one case per 1000 was associated with heavy rain after \r wet periods (Carlton et al., 2014). Floods have been associated with \r 22% increases in relative risk of diarrhoea in China (Liu et al., 2018c). \r In addition, higher levels of faecal contamination of drinking water \r [...]"


id: da621539a186bf7645cbc27b82e08ef8
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"[...] and hands (i.e., lack of WaSH) has been statistically significantly \r associated with increased child diarrhoea (Goddard et al., 2020)."


id: e7fa734814123afdc795a8356e7d644
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content:
"In 2020, 2 billion people lacked access to uncontaminated water, while \r 771 million lacked basic sanitation services, primarily in sub-Saharan \r Africa and rural areas (WHO and UNICEF, 2021). Even in high-income \r countries, poor-quality drinking water can be a health issue (Murphy \r et al., 2014). For example, in a sampled population in Canada, reported \r exposure to exposure routes for waterborne illness included 7% from \r private wells and 71.8% from municipal water (David et  al., 2014). \r Drinking water treatment can be compromised by degraded source \r water quality and extreme weather events, including droughts, storms, \r ice storms and wildfires that overwhelm or cause infrastructure damage \r (Sherpa et al., 2014; Khan et al., 2015; Howard et al., 2016; White et al., \r 2017) (high confidence). Adverse health effects are exacerbated due to \r the absence of adequate WaSH, particularly in poorer households (Khan \r [...]"


id: e4227b5ca4f533c54d605cf3749c10eb
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"[...] et al., 2015; Kostyla et al., 2015; Cisse et al., 2016), WaSH infrastructure \r failure (Khan et  al., 2015; Wanda et  al., 2017) or inadequate WaSH \r facilities in emergency shelters (Alam and Rahman, 2014). For example, \r WaSH coverage decreased from 65% to 51% due to damage from floods \r and earthquakes in Malawi (Wanda et al., 2017). Loss of electricity also \r impacts WaSH service delivery (Cashman, 2014), and infrastructure \r damage caused by climate hazards may reverse progress on universal \r access to WaSH (Kohlitz et al., 2017) (limited evidence, high agreement). \r In addition, wastewater outflows have been associated with a 13% \r increased relative risk of gastrointestinal illness through contaminated \r drinking water sources (Jagai et  al., 2015) (limited evidence, high \r agreement). Harmful algal blooms represent an emerging health risk, \r but lack of monitoring and reporting prevent risk exposure assessments \r [...]"


id: 7409c74935fdf1c70c33f08fcda0e1e9
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"[...] (Carmichael and Boyer, 2016; Nichols et  al., 2018) (limited evidence, \r high agreement). Chemical contaminants (e.g., nitrates, arsenic) have \r been linked to non-communicable diseases, including neurological \r disorders, liver and kidney damage, and cancers (Jones Rena et  al., \r 2016), and to some water-related diseases (e.g., schistosomiasis) (low \r evidence, medium agreement)."


id: d068bd5ee835c998d02da78d1c4f8c93
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"disproportionately impact women and girls. The necessity of water \r collection takes away time from income-generating activities, child care \r and education (Yadav and Lal, 2018; Schuster et  al., 2020) (medium \r evidence, medium agreement). Consumption of larger volumes of \r water is essential for healthy women during pregnancy, lactation and \r caregiving, which increases the amount of water that has to be fetched. \r Fetching of water is associated with increased risk of sexual abuse, \r demand for sexual favours at controlled water collection points, physical \r injuries (e.g., musculoskeletal or from animal attacks), domestic violence \r for not completing daily water-related domestic tasks (limited evidence, \r high agreement), and poorer maternal and child health (Mercer and \r Hanrahan, 2017; Pommells et al., 2018; Anwar et al., 2019; Collins et al., \r 2019a; Geere and Hunter, 2020; Venkataramanan et al., 2020) (medium \r [...]"


id: c61551da35315cbaad849b24c4ac3656
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"[...] evidence, high agreement). Menstrual hygiene management is a public \r health issue but poorly linked to climate change, despite relationships \r between lack of adequate WaSH, poor menstrual hygiene, and urinary \r tract infections (Ellis et al., 2016; Pouramin et al., 2020). Water insecurity \r also affects emotional, spiritual and cultural relationships that are often \r critical to Indigenous health (Wilson et al., 2019) (limited evidence, high \r agreement)."


id: ec6d8b5fe18556f6fb69ecd1c59afddb
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"Advances in the attribution of extreme weather events have made \r it possible to determine the causal relationship between droughts, \r floods and climate change for some cities, particularly those with \r long hydro-meteorological records (Bader et  al., 2018; Otto et  al., \r 2020). Attribution analysis shows that urbanisation contributed to the \r increase in both frequencies of local and abrupt heavy rainfall events \r in the city, at a rate of 1.5 and 1.8 10 yr-1, respectively (Liang and \r Ding, 2017). A multi-method attribution showed that the likelihood \r of prolonged rainfall deficit in Cape Town (South Africa) during \r 2015-2017 was made more likely by a factor of 3.3 (1.4-6.4) due \r to anthropogenic climate change (Otto et  al., 2018). These results \r show that climate change has impacted the return time of extreme \r droughts in the Western Cape, exceeding the capacity of the existing \r water supply system to cope (Otto et  al., 2018) (Box  9.4; 9.8.2). \r [...]"


id: c6946b7bf38c787d09e7ff72443982d2
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"[...] In Baton Rouge (USA), a rapid attribution study showed that the \r probability of an event such as the intense precipitation and flash \r flooding of August 2016 has increased by at least a factor of 1.4 \r due to radiative forcing (USA) (van der Wiel et al., 2017). In Houston \r (USA), a study found that the combination of urbanisation and climate \r change nearly doubled peak discharge (84%) during Hurricane Harvey \r (August 2017), suggesting that land use change magnified the effects \r of climate change on catchment response to extreme precipitation \r events (Sebastian et  al., 2019) (14.4.3.1; Box  14.5 The Economic \r Consequences of Climate Change in North America, Cross-Chapter \r Box DISASTER in Chapter 4). According to a multi-method approach, \r the 2014/2015 drought event in Sao Paulo (Brazil) was more likely to \r have been driven by water use changes and population growth than \r climate change (Otto et  al., 2015) (Cross-Chapter Box  DISASTER in \r Chapter 4)."


id: 96ec8ab7d4dbd86181e2255f36612583
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content:
"The science of weather event attribution requires high-quality \r observational data and climate models that are currently available \r only in highly developed countries (Otto et  al., 2020). In addition, \r further research is necessary to determine the impacts of climate \r change on water-related extremes in the urban areas of developing \r countries (Bai et  al., 2018). For example, a combination of \r observational analysis and global coupled climate models showed \r that the 2015 flooding event in Chennai (India) could not be attributed \r to anthropogenic climate change, with the effects of that being \r relatively small in the region due to the impact of GHG increases \r being largely counteracted by those of aerosols (van Oldenborgh \r et  al., 2017a) (Section  4.2.5). Further research is also required to \r determine the impacts of climate change on water-related extremes \r in informal settlements where vulnerability to water insecurity is high \r [...]"


id: f3f19f87ca9f1999f0be71a47534c8e4
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"[...] due to poverty, overcrowding, poor-quality housing and lack of basic \r infrastructure (Scovronick et al., 2015; Grasham et al., 2019; Williams \r et al., 2019; Satterthwaite et al., 2020)."


id: 55ad5ffcb4dd5ca3c62a9d8a091fa4b
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"Some extreme weather events are increasing in frequency and (or) severity as a result of climate change (Seneviratne et al., 2021) (high \r confidence). These include extreme rainfall events (Roxy et al., 2017; Myhre et al., 2019; Tabari, 2020); extreme and prolonged heat leading \r to catastrophic fires (Bowman et al., 2017; Krikken et al., 2019; van Oldenborgh et al., 2020); and more frequent and stronger cyclones/\r hurricanes and resulting extreme rainfall (Griego et al., 2020). These extreme events, coupled with high vulnerability and exposure in \r many parts of the world, turn into disasters and affect millions of people every year. New advances enable the detection and attribution \r of these extreme events to climate change (Otto et al., 2016; Seneviratne et al., 2021), with the most recent study saying that heavy rains \r leading to devastating floods in western Europe that captured the world's attention in July 2021 were made more likely due to climate \r [...]"


id: ea3a2c18799ba3eeb3083d5ca9ad1851
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"[...] change (Kreienkamp et al., 2021). Most WGII chapters (this volume) report various extreme event-induced disasters and their societal \r impacts. This cross-chapter box brings together authors from WGI and WGII to emphasise that disasters following extreme events have \r become the most visible and public face of climate change (Solecki and Rosenzweig, 2014). These disasters reflect immediate societal and \r political implications of rising risks (high confidence), but also provide windows of opportunity to raise awareness about climate change \r and to implement disaster-reduction policies and strategies (high confidence) (Albright, 2020; Boudet et al., 2020)."


id: 6af27d0b827e68d240fbd8a76c284edb
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"While individual events alone can lead to major disasters, when several events occur in close spatial and temporal proximity, impacts \r get compounded, with catastrophic results (Zscheischler et al., 2018; Zscheischler et al., 2020). In March 2019, Cyclone Idai (category \r 2) was the deadliest storm on record to strike the African continent, with the coastal city of Beira in Mozambique being particularly \r hard hit with at least 602 deaths (CRED, 2019; Zehra et al., 2019; Phiri et al., 2020). Nationally, Idai caused massive housing, water \r supply, drainage and sanitation destruction, but its impact extended to South Africa through disruption of the regional electricity grid \r (Yalew et al., 2020). In April 2019, amidst heightened vulnerabilities in the aftermath of cyclone Idai, cyclone Kenneth (category 4) hit \r the country, affecting 254,750 people and destroying more than 45,000 homes (Kahn et al., 2019). These circumstances caused the \r [...]"


id: 6bb457fbeaa5d302bf073e0c7ea2cdc6
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"[...] rapid spread of cholera, which triggered a massive vaccination programme to control the epidemic (Kahn et al., 2019; Lequechane et al., \r 2020). While there were no specific detection and attribution studies for Idai and Kenneth, overall, there is high confidence that the \r rainfall associated with tropical cyclones is more intense because of global warming. However, there remain significant uncertainties \r about the impact of climate change on the numbers and strength of tropical cyclones per se (Walsh et al., 2019; Zhang G. et al., 2020)."


id: e2ffa33f5a383c828c167dca9312f08c
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"Cyclone Amphan hit coastal West Bengal and Bangladesh on 20 May 2020. It was the first supercyclone to form in the Bay of Bengal since \r 1999 and one of the fiercest to hit West Bengal, India, in the last 100 years. The cyclone intensified from a cyclonic storm (category 1) to \r a supercyclone (category 5) in less than 36 hours (Balasubramanian and Chalamalla, 2020). Several hours before and on 20 May, extreme \r rain events resulted in heavy cumulative rainfall, flash flooding and landslides in several adjoining districts (Mishra and Vanganuru, 2020). \r As per the initial estimates, about 1600 km2\r  area in the mangrove forests of Sundarbans were damaged, and over 100 lives were lost. \r Earlier cyclones in the region have shown that impacts of these events are gendered (Roy, 2019). The cyclone damage was somewhat \r lessened due to the delta's mangroves (Sen, 2020). The estimated damage was USD 13.5 billion. Cyclone Amphan was the largest source \r [...]"


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"[...] of displacement in 2020, with 2.4 million displacements in India alone, of which 800,000 were pre-emptive evacuations by authorities "


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"Hurricane Harvey, a category 4 hurricane, made landfall on Texas and Louisiana in August 2017, causing catastrophic flooding and 80 deaths \r and inflicting $125 billion (2017 USD) in damage, of which $67 billion (2017 USD) was attributable to climate change (Frame et al., 2020). \r Several studies estimated the return period of the rainfall associated with this event and assessed that human-induced climate change \r increased the likelihood by a factor of approximately three using a combination of observations and climate models (Risser and Wehner, \r 2017; van Oldenborgh et al., 2017b). The impacts of Hurricane Harvey were exacerbated by extensive residential development in flood-prone \r locations. A study showed that urbanisation increased the probability of such extreme flood events several folds (Zhang W. et al., 2018) \r through the alteration of ground cover and disruption and redirection of water flow. Water quality in cities also deteriorated (Horney et al., \r [...]"


id: a4b217fa88e25542d8cea0da386f76a
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"[...] 2018; Landsman et al., 2019), and 85% of flooded land subsided at a rate of 5 mm yr-1 following the event (Miller and Shirzaei, 2019). \r Notably, the impacts of Harvey were unequally distributed along racial and social categories in the greater Houston area. Neighbourhoods \r with larger Black, Hispanic and disabled populations were the worst affected by the flooding following the storm and rainfall (Chakraborty \r et al., 2018; Chakraborty et al., 2019; Collins et al., 2019b). In addition, racial and ethnic disparities were shown to impact post-disaster needs, \r ranging from household damage to mental health and recovery (Collins et al., 2019b; Flores et al., 2020; Griego et al., 2020)."


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content:
"The Coastal Nino event of 2017 led to extreme rainfall in Peru, which was made more likely by at least 1.5 times as compared to pre\u0002industrial times due to anthropogenic climate change and Coastal Nino (Christidis et al., 2019) and comparable to the El Nino events of \r 1982-1983 and 1997-1998 (Poveda et al., 2020). This event showed evidence of larger anomalies in flood exposure (Muis et al., 2018; \r Christidis et al., 2019; Rodriguez-Morata et al., 2019) and sediment transport (Morera et al., 2017). In Peru, this Nino event led to USD \r 6 to 9 billion of monetary losses, more than a million inhabitants were affected, 6614 km of roads were damaged, 326 bridges were \r destroyed, 41,632 homes were damaged or became uninhabitable and 2150 schools and 726 health posts were damaged (French and \r Mechler, 2017; French et al., 2020), leaving half of the country in a state of emergency (Christidis et al., 2019). Furthermore, institutional \r [...]"


id: 5d6cc864dd7e0d159608dbc5e98c62c5
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content:
"[...] and systemic sociocultural and political conditions at multiple levels significantly worsened disaster risk management which hampered \r response and recovery (French et al., 2020). Citizens and zero-order responders proved to be more effective and quicker than national \r disaster risk management response (Briones et al., 2019)."


id: da87af42b57bbcda0e0e4c36ca104e90
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index: climate_gpt_v2
vector_id: 35748
content:
"The mega-fire that occurred in Chile in January 2017 had the highest severity recorded on the planet (CONAF, 2017), burning in three \r weeks an area close to 350,000 hectares in south-central Chile. These events have been associated with the prolonged ongoing drought \r that has persisted for more than one decade and with the increase in heat waves (Gonzalez et al., 2018; Miranda et al., 2020). This \r extreme drought and the total burned area of the last decades have been attributed to anthropogenic climate change in at least 25% \r and 20% of their severity, respectively (Boisier et al., 2016). The mega-fire of summer 2017 resulted in 11 deaths, more than 1500 houses \r burned and the destruction of the small town of Santa Olga. The smoke from these fires exposed 9.5 million people to air pollution, \r causing an estimated 76 premature deaths (Bowman et al., 2017; Gonzalez et al., 2020). The direct costs incurred by the State exceeded \r [...]"


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content:
"[...] USD 360  million (Gonzalez et  al., 2020). The 2017 mega-fires led to a series of institutional responses such as management plans \r that include preventive forestry techniques, regulatory plans containing rural-urban interface areas, an emergency forest fire plan, and \r promotion of native species (Gonzalez et al., 2020)."


