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In the midst of the sixth mass extinction (Ceballos et al. 2017), sustainable use of the world's natural resources, including wildlife, fish stocks, and timber, has become critical (Di Minin et al. 2019, Ripple et al. 2019). Key to achieving sustainability is the development of flexible quantitative models with which to evaluate the consequences of alternative harvest management scenarios, and in turn support decision making and policy implementation (Shea and the NCEAS Working Group on Population Management 1998, Schmolke et al. 2010, Bunnefeld et al. 2017). Although there is now broad consensus that such models should integrate both the social and ecological processes inherent to resource management systems (Milner-Gulland 2012, Sayles et al. 2019, Schlüter et al. 2019a, b), the resulting complexity remains daunting (Folke et al. 2010, Bunnefeld et al. 2017). A major challenge concerns how to best integrate governance processes and human behavior into existing management models in a way that optimizes predictive accuracy whilst minimizing complexity (Müller-Hansen et al. 2017, Schlüter et al. 2019a, Travers et al. 2019a), and improves applicability to a broad spectrum of harvesting systems.
Governance relates to the societal context and processes that shape collective decision making and action (Bevir 2012). The term governance is used very broadly across disciplines, but within the context of natural resource use it typically describes the interactive processes occurring among different stakeholders through which decisions relating to resource harvest and management are made (Lockwood et al. 2010, Cox et al. 2016). Although collective governance, sometimes referred to as comanagement, is often sought (Armitage et al. 2009), this is often impeded by conflicts occurring among stakeholders with diverging interests (Redpath et al. 2013, Orach and Schlüter 2016, Bodin 2017, Cumming 2018), such as the exploitation versus the conservation of a natural resource (Benítez-López et al. 2017). Such conflicts are widespread and pose a major threat to the sustainable use of natural resources worldwide. In spite of this, our ability to integrate the governance processes through which conflicts operate into existing sustainable management frameworks is currently very limited.
A common symptom of conflicts surrounding the use of natural resources is illegal harvesting behavior, whereby resource users do not comply with harvesting rules and regulations, e.g., quotas. Although individual economic and social drivers of noncompliance have received increased attention over the last decade (Keane et al. 2008, Gavin et al. 2010, Solomon et al. 2015, Duffy et al. 2016, Travers et al. 2019b), the behavior of resource users in relation to other complex and dynamic governance processes currently lacks theoretical and empirical support. One such process is lobbying, through which interest groups seek to directly influence management decision making to bias outcomes in their favor (Baumgartner et al. 2009, Lute and Gore 2014, Meng and Rode 2019). Lobbying may attempt to advance the interests of natural resource users, for example, those of commercial industries in the case of marketable natural resources (Murray 2003). It may also serve the interests of parties seeking to restrict resource use, such as conservation organizations (Mace 2014, Adams 2017, Baynham-Herd et al. 2018, Challender and MacMillan 2019). In this latter case, lobbying to impose restrictions on the use of a natural resource could exacerbate illegal harvesting pressure (Di Minin et al. 2016), particularly if the resource is economically valuable, e.g. rhino horn (Biggs et al. 2013) or culturally important, e.g., agarwood from Aquilaria sinensis (Chen et al. 2019). In turn, noncompliance with harvesting rules may trigger more intense lobbying, not only from conservation interest groups, but also from resource user groups that do harvest legally, thereby creating feedback processes affecting resource management. Yet, despite the huge potential for the combined and interlinked effects of conflict, noncompliance, and lobbying to destabilize sustainable natural resource use, no modeling frameworks, to our knowledge, have explicitly accounted for them.
State-of-the-art modeling frameworks to optimize natural resource management have been particularly well developed in the context of commercial fisheries, where harvest allocation is typically based on close monitoring of fish stocks and catches (Audzijonyte et al. 2019). One such framework, known as management strategy evaluation (MSE; Smith et al. 1999, Punt et al. 2016, Stephenson et al. 2017), enables the entire management system, including stock dynamics and monitoring, management decisions, and harvesting activities, to be simulated in search of a strategy that best addresses management objectives. A key feature of MSE is its ability to explicitly model the uncertainty surrounding individual management components (Milner-Gulland and Shea 2017), such as stock stochasticity, monitoring error, decision biases, or illegal behavior by harvesters. Using a fisheries example, Armitage et al. (2019) recently advocated the widespread integration of governance processes into MSE frameworks, highlighting in particular the existence of decision-making thresholds (Harford et al. 2016).
In contrast, the development of flexible, MSE-based frameworks encompassing more realistic processes of decision making and human behavior has been largely absent from terrestrial harvesting systems (Bunnefeld et al. 2011, Bunnefeld and Milner-Gulland 2016, Moa et al. 2017). Indeed, modeling frameworks to date have focused disproportionately on the ecological dimension of terrestrial harvesting systems (Gamelon et al. 2019), such as the development of elaborate population and community response models, e.g. to trophy hunting (Whitman et al. 2007, Loveridge et al. 2016) or the assessment of harvest-induced evolution (Kuparinen and Festa-Bianchet 2017). Although often presented within an adaptive management framework (Kolbe et al. 2017, Andrén et al. 2020), these approaches tend to overlook how the implementation of management decisions can be perturbed by conflicts of interest. Predictive models that can include these governance processes are now sorely needed to guide the management of terrestrial harvesting systems (Bunnefeld et al. 2011, 2017, Dobson et al. 2019), in which mismanagement and overharvesting have become widespread (Díaz et al. 2019).
In this study, we develop a flexible and widely applicable form of MSE model in which the interests of three different stakeholders are considered: managers seeking sustainability, users seeking increases in quota, and conservationists seeking harvest restrictions. All stakeholder groups are able to influence management decisions and users can harvest illegally through the implementation of flexible and dynamic functions that govern lobbying and noncompliance processes. Unlike typical MSE models that represent human behavior through scenario-based and static actions, we optimize decision making through the use of a genetic algorithm, which allows stakeholders to respond to a dynamic social-ecological environment to satisfy their (potentially divergent) goals. Using this modeling framework, we first derive general predictions regarding natural resource management sustainability in the presence of stakeholder conflicts. We then demonstrate the ability of our model to predict population trend patterns observed across a range of harvested vertebrate species from terrestrial systems. By combining existing aspects of MSE models with functions describing governance processes driven by conflicting stakeholder goals, our framework enables comparison of management strategies within a more realistic and dynamic social-ecological setting.
Management strategy evaluation models typically comprise four submodels, each representing one component of the management system (Fig. 1a; Bunnefeld et al. 2011, Punt et al. 2016). In most cases, a population submodel, which simulates the dynamics of the natural resource population under harvest, produces a "true" value of resource abundance at time step t. A monitoring submodel subsequently simulates an observation process through which an estimate of resource abundance, along with associated uncertainty, is obtained. This estimate is then passed on to a manager submodel, whose role is to turn the observation into a harvesting policy that is aligned with the manager's objective (also called a performance metric). The resulting policy is then acted on by a harvesting submodel, which determines the final off-take from the resource population. This cycle can be repeated over a desired number of time steps, thus enabling dynamic processes to be considered when predicting management outcomes over both short and long time frames.
For the purpose of this study, the population submodel consists of a simple discrete logistic resource growth model of the form,
in which N(t) is the resource population size at time t, K its carrying capacity, r(t) its growth rate at t, and H(t) the total harvest at t (combining legal and illegal off-takes, see below). Stochasticity is included in the model by sampling from a normal distribution with mean r (the intrinsic growth rate of the population) and standard deviation σ. We further assume that the observation process as implemented within the observation submodel bears no error, i.e., the resource population size is estimated perfectly by the manager.
The observed resource population size N(t) is passed on to the manager submodel, whose role is to enact a harvesting quota Q(t) that best minimizes deviations from the manager-specific target abundance (NM). We choose here to focus on resource abundance as a performance metric because it is a common benchmark in the management of harvested species (Sanderson 2006, Serrouya et al. 2011, Blanchard et al. 2014), but also because it facilitates understanding of our model. Choice of harvest quota by the manager is implemented using a genetic algorithm that finds an adaptive, but not necessarily optimal, policy, thereby mimicking a goal-oriented process prone to human error (see Duthie et al. 2018 for more details). The resulting quota is then transferred to the harvest submodel, which also calls a genetic algorithm to determine a harvest that minimizes deviation from a user-specific target abundance (NU) whilst taking into account varying levels of user budget (Appendix 1, Fig. A1.1).
Conflict within our MSE model can be conceptualized as assigning different objectives between manager and users with respect to N(t), which the relevant submodels then attempt to optimize. To increase realism, however, we also include another key actor, conservation groups, whose primary interest in management scenarios is often to promote protection of the resource by restricting harvest. In particular, such groups may impose considerable pressure on decision makers in the form of lobbying (Sandbrook 2017). More specifically, we assume that (i) managers aim to maintain a sustainable population of a given natural resource over the period of management, i.e., achieve an average growth rate of zero, (ii) user groups seek unregulated harvest of the resource, prioritizing year on year versus long-term harvest, and (iii) conservation groups seek to ban harvesting altogether (Aryal et al. 2018), enabling the resource population to grow to carrying capacity. The objectives of users and conservationists represent opposed extremes, which is useful for conceptualizing conflicts related to natural resource use (Redpath et al. 2013). We note, however, that these can be adapted to any scenario at hand.
In the following sections, we detail how stakeholders in our model attempt to meet their respective objectives. To do this, we define two metrics that underlie levels of lobbying and illegal harvesting. The first is decision-making bias, defined as whether management decisions are biased in favor of user or conservation interests. The second is user compliance with harvesting rules, which governs the level of illegal harvesting. We note that our approach does not distinguish between the different drivers of user compliance, such as increased enforcement or monetary incentives (Cooney et al. 2017), but instead serves as a general model of behavioral change.
In the model, decision making by the manager can be affected by a lobbying process representing pressure from either conservation or user interest groups (Fig. 1b and c, respectively). Lobbying pressure at time t represents the probability that the manager will disregard the original, unbiased quota derived from the genetic algorithm, i.e., Q(t), and instead allow either unregulated harvesting (under user lobbying) or ban harvesting altogether (under conservationist lobbying). For simplicity, decision-making biases as a result of user and conservationist lobbying are simulated separately.
For conservationists, the probability of successful lobbying for a harvesting ban is modeled as a function of how far the observed resource abundance is from the stated conservation target (NC) and of fixed levels of decision-making bias (IC) toward conservation interests. IC can be varied between IC = 0 (manager completely biased) and IC = 1 (manager completely unbiased). We further assume that lobbying pressure is nonexistent when N(t) ≥ NC, but expect it to increase exponentially as the resource population approaches extinction (N(t) → 0). Thus, the probability of successful lobbying for a harvesting ban by conservation groups is defined as follows,
Q'(t), which represents Q(t) postlobbying, is then determined using a single Bernouilli trial X(t)~B(1,ΦConservation(t)) such that if X(t) = 0, Q'(t) = Q(t), and if X(t) = 1, Q'(t) = 0.
For users, the probability of successful lobbying for unregulated harvest is modeled as a function of how far the observed resource abundance is from the stated user target (NU) and, similarly to conservation lobbying, decision-making bias toward user interests (denoted as IU). We further assume that lobbying pressure is nonexistent when N(t) ≤ NU, but expect it to increase exponentially as the resource population approaches carrying capacity (N(t) → K). Thus, the probability of successful lobbying for unregulated harvest by user groups is defined as,
As above, Q'(t) is then determined with a Bernouilli trial X(t)~B(1,ΦUser(t)), such that if X(t) = 0, Q'(t) = Q(t), and if X(t) = 1 then Q'(t) = Hmax(t), where Hmax(t) is the maximum number of individual resources that can be harvested at time t given the user budget BU(t) and minimum cost of a harvest cmin, i.e.,
Q'(t) subsequently determines how many units of the resource population the user can harvest legally. Both NC and NU can be varied between zero and K, the resource population carrying capacity.
The user can then choose to either implement the legal quota or harvest illegally, depending on which option maximizes harvest (Fig. 1d). In a similar way to lobbying, illegal harvesting pressure represents the probability that the user will successfully remove one unit from the resource population, and is defined as,
E is user compliance with harvesting rules and is varied in simulations from E = 0 (no compliance) and E = 1 (complete compliance). A hypothetical illegal harvest, Y(t), is then derived from a Bernouilli trial Y(t)~B(Hmax,Ψ(t)). The user then implements a final harvest H(t), defined as the maximum of either Q'(t) or Y(t).
Model simulations were carried out in R (version 3.4.3) using the package GMSE (version 0.4.0.11; Duthie et al. 2018). The R code used to produce simulations is provided in Appendix 2, and the definition and values for set and derived parameters are presented in Appendix 3, Table A3.1. Resource population size at t = 0 was set to 1000 units and the carrying capacity at 2000. We ran simulations for three values of r—0.1, 0.2, and 0.3 (with σ = r/10 in all cases)—because these represented a range of commonly measured intrinsic growth rates in the harvested species considered in our empirical analysis (see below; Sibly and Hone 2002). We varied decision-making bias (I, separately for conservation and user groups) and user compliance levels (E) to control lobbying and illegal harvesting levels during each time step, respectively. For each combination, we ran 100 management iterations, each lasting 10 time-steps, i.e. years. We chose to carry out simulations over 10 time steps because this was representative of real-world management plans. In all simulations, the minimum cost of a harvest (cmin) was set to 10, the manager budget to 10,000, and the user budget was varied between 5000 and 10,000 (see Appendix 1, Fig. A1.1). Management effectiveness was assessed as the mean resource population growth at time step 10 across iterations. We then modeled management effectiveness as a function of decision-making bias and user compliance using generalized additive models (GAMs) with tensor product smooths (R package mgcv). We present our findings in the form of 2-dimensional contour surfaces.
As a control, we ensured that in the absence of disagreement among manager, user, and conservation objectives, the simulated resource population is managed effectively regardless of decision-making bias and user compliance levels. This was done by setting user, conservationist, and manager targets to 1000 resource units.
We compared predictions from our model against data on 206 terrestrial harvested species from the International Union for the Conservation of Nature's (IUCN) Red List of Threatened Species. We considered species belonging to the orders Anseriformes (geese and ducks, N = 37), Cetartiodactyla (even-toed ungulates, N = 90) and Carnivora (carnivores, N = 79) because these are commonly targeted by subsistence, recreational, and trophy hunting activities globally (Di Minin et al. 2019, Hill et al. 2019).
Using the "advanced search" option on the IUCN Red List web site (https://www.iucnredlist.org/), we filtered species by criteria relating to Taxonomy ("Anseriformes," "Cetartiodactyla," and "Carnivora"), Red List Category ("NT or LR/nt" and "LC or LR/lc"), and Threats ("Intentional use (species is the target)"). We only considered species listed as Least Concern or Near Threatened so as to minimize confounding factors associated with threat status. Filtering resulted in a total of 206 species to which the classification of decision-making bias and user compliance shown in Appendix 4 (Fig. A4.1) was applied. More specifically, we classified each species according to (1) its stated population trend at the latest assessment (decreasing, stable, or increasing), (2) the type of harvesting it was most commonly under (unregulated, regulated, or banned), and (3) the level of illegal harvest most commonly reported for a population (low, medium, or high). We then used population trend as a measure of management outcome, harvesting type as a measure of decision-making bias (with unregulated and banned taken to reflect pro-user and pro-conservation biases), and illegal harvest level as a measure of user compliance. Classifications were carried out by two of the authors and subsequently compared to ensure consistency.
We derived the proportion of species showing a decreasing, stable, and increasing population trend for each of the different combinations of decision-making bias and user compliance. We also modeled population trend as a function of the interaction between decision-making bias and user compliance using a generalized additive model with Gaussian error structure and tensor product smooth. This resulted in an interpolated surface showing mean population trajectory (from -1 to 1) as a function of decision-making bias and user compliance classifications.
When simulated manager, user, and conservation objectives were identical, reflecting perfect agreement on target abundance for the harvested resource, mean population growth remained stable and on target over the course of 10 management years (Fig. 2). This parameterization is important because it verifies that the genetic algorithm is operating as intended by producing expected results of optimal (or near-optimal) harvest decisions over both short and long time frames. It also reflects a null model of effective management in the absence of conflicting stakeholder objectives, against which the effect of lobbying and illegal harvesting can be compared.
In the presence of conflicting stakeholder objectives, we find that management outcome is shaped by the interaction between decision-making bias and user compliance levels (Fig. 3). We make five predictions from our model. First, when lobbying has no effect on management decisions, a stable resource abundance is only achieved at high levels of user compliance (Fig. 3; I = 0 and E = 1). Second, as compliance decreases from high to moderate levels, i.e., increasing illegal harvest, stable and increasing resource population trends are possible to maintain if decision making by the manager is biased toward conservation objectives (Fig. 3; I > 0 and E > 0.5). Third, the combination of bias toward conservation objectives and low user compliance leads to both an increased risk of negative population growth rates and an increased probability of extinction (Fig. 3; I > 0 and E < 0.5). This arises because such decision making leads to a higher likelihood of harvesting being banned and consequently higher resource abundance, to which users respond by increasing illegal harvesting pressure when compliance is low. Fourth, as user compliance tends toward minimum levels, negative growth rates occur regardless of bias in decision making, although they are less severe if decision making is unaffected by lobbying (Fig. 3; cases when E < 0.5). Last, when management decisions are biased toward user interests, population abundance declines over the course of the management period (Fig. 3; cases when I < 0). In this case, compliance has little effect because lobbying already satisfies user interests. Importantly, these predicted patterns of management outcome were not sensitive to choice of resource population growth rate (Appendix 5, Fig. A5.1).
Of the 206 species considered, 26 (12.6%) showed an increasing population trend, while 61 (29.6%) and 119 (57.8%) exhibited stable and decreasing trends, respectively. The proportion of species showing a stable population trend was highest when user compliance was high (Fig. 4a-c, Appendix 6, Table A6.1), and particularly when harvest was regulated (47% stable trends), a finding that is consistent with our model results (Fig. 3). Species showing increasing population trends were most strongly associated with high compliance (23 out of 26 species), and either regulated (16 out of 23 species) or banned (5 out of 23 species) harvesting. Eighty-one percent of the species classified under regulated harvest and high compliance showed stable or increasing population trends.
In contrast, species populations were overwhelmingly decreasing when compliance with harvesting rules was low, regardless of decision-making bias (Fig. 4g-i). This mirrors the dominant effect of changes in illegal harvesting over lobbying in driving resource mismanagement, which our model also predicts. As user compliance decreased from high to low, however, species were more likely to exhibit stable and increasing population trends when harvest was characterized as regulated rather than unregulated or banned. Overall, predictions from our theoretical model were strongly correlated with those obtained from empirical data (Pearson's correlation corrected for autocorrelation: = 0.897, P < 0.05 for a simulated intrinsic growth rate of rmax = 0.1; = 0.853, P < 0.05 for rmax = 0.2; and = 0.821, P < 0.05 for rmax = 0.3, respectively; Appendix 7, Fig. A7.1).
Our work provides a holistic and versatile resource management framework that accounts for dynamic governance processes such as conflict, lobbying, and rule compliance. It highlights the complex interaction between lobbying and compliance in the presence of conflicts, and its substantial influence on the sustainability of natural resource use. Most notably, we find that lobbying for management decisions that favor conservation interests can offset medium levels of user noncompliance. Yet this comes at a risk of increased sensitivity to further reductions in user compliance, which results in higher probabilities of resource extinction relative to scenarios in which management decision making is unbiased. These theoretical predictions are well supported in real-world systems. Indeed, there is increasing evidence in the scientific literature that outright harvest bans can lead to increased levels of illegal harvest (Di Minin et al. 2016, Raithel et al. 2017). For example, bans on trophy hunting imports and activities without provision of viable land-use alternatives can lead to a rise in unregulated killing of wildlife (Lindsey et al. 2017, Dickman et al. 2019).
We also demonstrate the critical effect of changes in user compliance on sustainable resource use. Both our theoretical modeling and empirical analysis show that, when management decisions are unbiased, stable resource trends are most likely to be achieved when compliance is high. This finding may seem obvious, but broad consensus between conceptual models and empirical approaches that encompass a range of species and incorporate the link with lobbying has been lacking (Travers et al. 2019b). The pattern we observe arises because user actions have a direct effect on the resource population, whereas lobbying targets decision making by the manager. In other words, users have the "final say" on what harvest will be implemented in a given time step (Eriksen et al. 2018, Shirley and Gore 2019), thus emphasizing their potential power to drive resource populations trends. Increasing user compliance with harvesting rules should therefore be a priority when seeking to sustainably manage natural resource use. This could be achieved through increased enforcement or by reducing demand (Holden et al. 2019) and implementing bottom-up approaches to management (Duffy et al. 2016, Cooney et al. 2017), such as the development of comanagement plans that bring together all parties in search of an agreement on management targets prior to actions being carried out (Armitage et al. 2009, Young et al. 2016, Redpath et al. 2017). Our model parameterization in which all parties agree on a population target demonstrates the value of compromise in achieving sustainable natural resource use.
Our theoretical predictions provided a strong quantitative match to those obtained from our analysis of IUCN red list data, thus demonstrating the broad applicability of our approach. Yet the importance of considering the interaction between decision-making bias and user compliance can also be emphasized through a more qualitative assessment of real-world case studies. Many ungulate and carnivore species are killed illegally in response to crop damage or livestock depredation, respectively, leading to declining populations despite high levels of international and national protection (Soofi et al. 2019). For example, Suutarinen and Kojola (2017) show how the illegal hunting of protected grey wolves (Canis lupus) in Finland increases with population size and strongly regulates population trends, despite the existence of "exceptional permits" to hunt wolves that cause damage to livestock. Here, strong protection laws that have enabled the wolf population to grow may have also influenced rates of illegal harvesting. In this case, our model could help highlight the damaging effect of conflict on sustainable management, and adjust legal harvest quotas based on quantified or expected rates of illegal harvesting, i.e., compliance.
Similarly, many species of herbivorous waterfowl in Europe and North America have experienced exponential increases in population size partly because of pro-conservation, protective legislation and high user compliance, yet this trend has started to occur at the detriment of agricultural crop production on which these species have become reliant (Lefebvre et al. 2017, Cusack et al. 2019). On the island of Islay in Scotland, legal harvesting of the wintering Greenland Barnacle Goose (Branta leucopsis) population, a species protected under EU law, has now been enforced because of lobbying pressure from agricultural interest groups, whose livelihoods are affected by goose grazing and damage to livestock pastures (McKenzie and Shaw 2017). However, the lack of evidence-based decision making relating to hunting quotas has been criticized by conservation organizations, which have brought forth lawsuits in an attempt to minimize culling. Although recent work has been used to derive more sustainable harvesting quotas based on the GMSE approach (Bunnefeld et al. 2020), it remains unclear how lobbying by both conservation and agricultural interests will affect manager decision making. Our approach could contribute to evidence-based decision making to minimize the risk of conflict escalation and dangerous tipping points in goose population trends due to overharvesting.
The relevance of our model goes beyond the orders considered in our IUCN analysis. The management of populations of birds of prey, for example, is also prone to conflict and governance issues. In the UK, the Hen Harrier (Circus cyaneus) is of high conservation concern and, although strictly protected, its population continues to be heavily impacted by illegal killing (Ludwig et al. 2017). Hen Harriers prey on Red Grouse (Lagopus lagopus scotica), a species whose populations and moorland habitat are intensively managed for shooting. The protection of the Hen Harrier is viewed as a threat to the Red Grouse shooting industry, resulting in widespread illegal killing of the raptor species on grouse moors (Murgatroyd et al. 2019). Here, our model could help explore how a healthy Hen Harrier population could be achieved despite conflicting stakeholder population targets, low compliance, and strong conservation pressure to ban legal harvesting (Redpath and Thirgood 2009).
Our approach aims to portray the functioning of complex and dynamic harvesting systems often characterized by high levels of uncertainty (Bunnefeld et al. 2011). In doing so, we have made a number of assumptions about the ecological and social components of these systems. In a first instance, we have implemented a simple logistic population growth model to define the general trajectory of resource abundance. Such a model provides a heuristic platform on which to evaluate population trends whilst minimizing biological complexity (Milner-Gulland 2011). We stress that the GMSE approach used in this study also enables the application of more elaborate resource growth models (see Duthie et al. 2018), which may be better suited to particular case studies, such as a population of a species in a given area, or be parameterized to include more or less demographic and environmental stochasticity (Fryxell et al. 2010, Milner-Gulland 2011). Like the assumption of perfect observation, an unlikely characterization of real-world systems, the simplicity of our population model allows us to isolate the effect of governance processes above and beyond structural and measurement uncertainties (Bunnefeld et al. 2011).
Our approach employs a genetic algorithm to optimize goal-oriented quota decision making, which provides a more rapid alternative to a trial and error method whereby a range of quota levels are tested sequentially (Duthie et al. 2018). Although the resulting quotas are derived with a level of variation that is realistic of management decisions, this variation remains random and we do not explicitly model the mechanisms driving decision making for a given manager, e.g., inherent biases. Similarly, subsequent lobbying actions, i.e., external pressures, affect the decision provided by the genetic algorithm, but not the simulated selection process itself. Even though our goal-oriented decision makers in the model do not reflect the entire complexity of people in the real world, our approach represents an important step forward compared to error-free and static decisions used in more standard harvesting models (Dobson et al. 2019).
Despite their evident potential for influencing sustainable use, reliable measures of decision-making bias and its relationship with lobbying pressure, as well as of user compliance, are sorely lacking for most harvested species. For instance, the link between social norms and illegal behavior has received little attention in the literature (Nyborg et al. 2016). Although the simulations presented here assume both lobbying pressure and illegal harvesting increase exponentially as resource abundance deviates from a stakeholder's goal, these functions should be modified and parameterized based on available real-world data or more detailed qualitative assessments of social norms and values. Last, our approach makes the key assumption that resource user behavior is driven by a desire to maximize harvest in the short term given a resource abundance goal, i.e., economic gain. Although this extreme is used to illustrate the breadth of our approach, we acknowledge that many factors, such as cultural norms and traditions, can promote self-sustaining harvesting systems (Ostrom 2009, Struebig et al. 2018). We note that, as a start, our approach can accommodate social norms by allowing the goal of resource users to be greater than population extinction, indicating a desire to maintain abundance in the long term.
Although MSE models are often tailored to specific case studies, our analysis reveals general patterns across theoretical and empirical analyses. Specifically, although lower compliance may be offset by increased decision bias toward conservation goals, extinction risk increases when high levels of such bias are combined with low user compliance. In addition, management decisions free from any influence of lobbying can only successfully achieve sustainable harvesting given low levels of illegal harvesting and thus buy-in from stakeholders. Given this balancing act, there is an urgent need for management approaches that address the underlying social conflicts over the sustainable use of biodiversity. Such approaches should seek where possible to promote consensus between stakeholders on population targets, for instance by investing in detailed assessments of the views and needs of each interest group, and their overlap. In cases where consensus proves challenging to achieve, our modeling approach could help simulate and predict how the resulting governance processes through which divergence is expressed could affect the sustainability of harvested populations. In turn, this would allow management decisions to anticipate the effects of potential lobbying and noncompliance. Importantly, use of the proposed approach need not be restricted to natural resource management. Indeed, individual responses (including compliance) to conflict, policy, and lobbying are of high relevance to issues such as climate change mitigation (Chakra et al. 2018) and sustainable wildlife trade (Nuno et al. 2018), in which the power of consumers (of carbon and wildlife, respectively) is likely to be high.
Data Availability Statement
The data and code are available in the manuscript supporting information.
This study received funding from the European Research Council under the European Union's H2020/ERC grant agreement no. 679651 (ConFooBio) to N.B. A.B.D. is supported by a Leverhulme Trust Early Career Fellowship. We are grateful to Tim Coulson and E.J. Milner-Gulland for comments on previous versions of this manuscript. All authors conceived the study, developed the underlying theory and software, discussed the results, and wrote the manuscript. J.J.C. carried out the simulations and analyzed the data.
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text:
Violent crime
Violence is a major public health issue that is linked with significant costs to health and social care as well as lost output associated with absence from work. Amongst victims, it is linked with an increased risk of health-damaging lifestyle behaviours such as smoking, alcohol and drug abuse. Violent crime can range from minor assaults (such as pushing and shoving), harassment and abuse (that result in no physical harm) through to wounding and homicide. It also includes sexual offences such as rape and sexual assault (Office for National Statistics, 2018).
The Serious Violence Strategy (Home Office, 2018) reports increases in some types of violent crime such as knife crime, gun crime and homicide at a national level since late 2014. It emphasises the importance of partnerships across different sectors such as education, health, housing and social services. In Derby, there were 20.3 violent offences per 1,000 population (n=5,190) in 2017/18. This needs analysis considers violence in its widest sense, and includes domestic violence, hospital admissions for violence and anti-social behaviour.
Research demonstrates that there is a clear link between childhood adversity and victimisation and criminality in adulthood. The evidence suggests that by targeting those most at risk of experiencing adversity in childhood and supporting people in the criminal justice system who have been affected by adverse childhood experiences, agencies can reduce re-offending and prevent intergenerational crime and victimisation (Scottish Government, 2012).
Unmet need and gaps
Reports suggest that 67% of the population have at least one adverse childhood experience (ACE). Those who experience 4 or more adverse childhood experiences are at a significantly greater risk of the following (Bellis et al 2012):
Local Council services are not designed to address violent crime per se but do seek to address the wider health and social inequalities experienced as a result of childhood adversity.
The Public Health nursing service delivers universal services to all children in the city aged 0 – 19 years alongside early intervention children's social care services. These are ideally placed to identify children and families deemed to be at risk. Schools and exclusion units have a key role in identifying children experiencing trauma within the family home.
Children and adult safeguarding services are designed to adopt a multi-disciplinary approach to sharing risk information. They aim to bring together the key partners required to protect children and adults from harm.
Specialist Public Health services are also ideally placed to identify at-risk adults who access these services. Illicit drug use, problematic alcohol use and/or risky sexual behaviour in adulthood are often symptomatic of childhood trauma.

subset: commoncrawl


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"We have a shortage of multi-lingual poll workers in the State of California. It's a fact," he said. "We will have a greater shortage going forward as our demographics continue to change and shift. And there must be language access for voters at the polls. And that's what this bill provides."
Supporters point out there would be limits on how many permanent residents could volunteer and what their duties would include.
Critics say non-citizens should not be involved in the voting process. And they doubt whether permanent residents would help with language barriers since they are not allowed to actually help people vote.
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Much colder weather and a thin coating of ice blasted into southern Denton County early Thursday, and temps will struggle to get above the freezing mark until as least Saturday, according to the National Weather Service.
Here are some tips to help prevent frozen water pipes and keep safe during this bout of bitter cold weather:
Be sure to disconnect all outside water hoses. This will prevent an overnight freeze from bursting either the faucet or the pipe it is connected to.
Insulate pipes or faucets in unheated areas with pipe wrapping materials that are available at hardware stores.
Locate your shut-off valve. Some homes have accessible valves, while others only have shut-off valves in the meter boxes. Keep your town's Utility Service number handy, so that you may contact them in the event of an emergency.
Any plumbing inside your home that is facing an outside wall should be considered during winter months. To help prevent pipes from freezing, open the cabinets to expose the pipes to the warm inside.
- If the pipes freeze, remove any insulation or layers of newspapers and wrap pipes in rags. Completely open all faucets and pour hot water over the pipes, starting where they were most exposed to the cold (or where the cold was most likely to penetrate).
- Conserve fuel, if necessary, by keeping your residence cooler than normal. Temporarily close off heat to some rooms.
- Maintain ventilation when using kerosene heaters to avoid build-up of toxic fumes. Refuel kerosene heaters outside and keep them at least three feet from flammable objects.
- Watch for signs of frostbite. These include loss of feeling and white or pale appearance in extremities such as fingers, toes, ear lobes, and the tip of the nose. If symptoms are detected, get medical help immediately.
- Watch for signs of hypothermia. These include uncontrollable shivering, memory loss, disorientation, incoherence, slurred speech, drowsiness, and apparent exhaustion.
- If symptoms of hypothermia are detected: get the victim to a warm location, remove wet clothing, put the person in dry clothing and wrap their entire body in a blanket, warm the center of the body first, give warm, non-alcoholic or non-caffeinated beverages if the victim is conscious, and get medical help as soon as possible.
Source: City of Highland Village and Town of Flower Mound


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The Good, The Bad and Espresso
Ever wished crisp, highly-flavored, appetizing coffee but haven't got the counterspace, the cash or electrical energy nearby? Espresso – The bottom from which all speciality coffees are made – Scorching water is forced via finely floor espresso to provide a maximum of 1 to 1.5 fluid ounces of beverage. I have been given chocolate covered espresso beans before and even purchased some myself. I was thrilled with the concept but have never enjoyed the products. I was given some Dilettante this year and they are wonderful! The beans are reliably tasty and the chocolate is actually chocolate, not a discount chocolate lookalike. Even if you have tried a product like these before you need to try Dilettante. However when the researchers put together a mathematical mannequin to explain the extraction yield primarily based on the components below a barista's management-options such as the lots of water and dry espresso, the fineness or coarseness of the grounds, and the water pressure-and compared its predictions to brewing experiments, it turned clear that the real relationship was extra complicated. Bring your clean, fresh water to 195 levels Fahrenheit. While this can be a decrease temperature than I usually counsel, right here it's appropriate. Since you are going to apply as much strain as you can when the time is up, reducing your water temperature gives you somewhat wiggle room so you don't unintentionally over extract.
Whether or not you're looking out for a caffeinated drink in the most convenient and less-expensive approach, there are tons of options accessible for you. But when your major objective is to pay money for the old and conventional cup of espresso, specially brewed and served, well, that might be one more story. Certainly, the area-age AeroPress espresso is taking on, whereas the tang of the traditional espresso remainsin antiquity. Some Aeropress recipes highlight the sweetness of a coffee higher than others. These recipes are perfect for gentle-roasted coffees which are acidic and fruity. Coffees with these flavor characteristics can come from wherever in the world, but most are related to coffee from east African countries like Ethiopia and Kenya, as well as natural†processed coffees. The darker roast of espresso beans offers an advantage to cappuccinos or lattes as it can 'cut through' the creaminess of the milk. The easiest way to check for a dark bean is to look for an oily surface on the outer of the bean. If the surface of the bean is shiny with oil, then it is usually an Italian or French style roast whereas if the bean is dry yet still dark it will be a Full City roast.
So that would not be terribly efficient when you get to the strive it at a couple of totally different yields†because you'd have to adjust the grinder for each one. I often discover all of my espressos are someplace in the 2-2.5 a number of vary. So I will pull one shot, see what time is. If the time is in the zone (25-35sec) I'll try it. If not, I'll transfer the time into the center of the zone (aiming for 30sec). Then I can modify yield without time escaping the zone and be able to transfer round really simply. On 27 September, 36 residence and professional brewers will battle it out, armed with sizzling water, a bespoke coffee blend, a piece of plastic that looks like a plumber's offcut, and a little bit of fastidiously timed elbow grease. Add espresso beans to the melted chocolate, a handful at a time, stirring until the beans are well-coated. I received my aeropress per week in the past and already have a Hario mini mill. I would learn that "click" nine was a superb starting point. I attempted that with Hasbean's Limoncillo (a bean I'd not really enjoyed as an espresso) and a few minutes later I used to be having fun with most likely the nicest filter coffee I would ever had. How's that for a learning curve! Still need to nail my brew yet although, I think I have been using too much coffee (two scoops of beans and water just past the 4 mark). I attempted the inverted methodology as shown on the Hasbean and James Hoffman's information, however discovered it a bit "skinny" for my tastes.
If you aren't sure what flavors you will or will not like in your espresso, you should start with something single origin. Single origin coffees genuinely emphasize certain clear flavors, making them invaluable tools for people looking to figure out exactly what they like. The Classic Italian Espresso blend gets an 8 out of 10 in body fullness and 9 out of 10 in richness. This dark roast also makes for a thick crema on top. It's also possible to toss it in a drawer or cupboard once you aren't utilizing it. You'd be well advised not to toss an espresso machine wherever. Nespresso VertuoLine capsules—a set of 30 best-selling coffee blends are included in this bundle—top your cup off with a rich crema that's become the brand's trademark. The machine itself has a modern, minimalist design you rarely see in affordable at-home units. All you need to do now is work on your cappuccino art, and you'll be open for business. 7. Now using the brush for your espresso machine, clean any residue from under the brewing group. Once complete, turn it on to give the group head another rinse.
Krups service department didn't fare much better with reviewers. All in all, the machine is ahead of steam driven machines but espresso enthusiasts will want to opt for a more reliable, albeit more expensive model. Labeling beans as espresso or drip is nothing more than a recommendation from the roaster on how to bring out the flavor of the beans. Of course, there are different roasts and coffee beans—two species actually, Arabica and Robusta, as well as varietals bred from these species—but each is still a coffee bean that can be used in a variety of methods. Now for the Championships, always accepted by the Aerobie Company, opponents compete utilizing the same coffee and roast, not being allowed to add anything to the espresso however authorised water. They get eight minutes to create their Aeropress brewed coffee, and current their coffee to a 3 headed jury. The jury tastes the coffee blind, not knowing who brewed which espresso how. The competitors consists of a number of rounds, and makes use of a throwdown system, where 2 compete in opposition to one another. The best of the 2 advances to the following spherical, till 1 winner is left.


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- Understanding the Difference Between an Inflatable Paddle Board and Hard Paddle Board
- 🏄♀Inflatable Paddle Boards are Proven to be More Durable than Hard Paddle Boards
- 🏄♀Inflatable SUPs will not hurt you that much in case you fall on them
- 🏄♀Reduces fatigue because of the soft deck
- 🏄♀ A lighter board gets used more
- 🏄♀ You can check in an inflatable paddle board in an airplane
- 🏄♀ An inflatable SUP may not be suitable for competition
- How do Inflatable Paddle Boards Work? Inflatable SUP Pros And Cons
- How to Make your Inflatable Paddle Board Last Longer
- Tips when Buying An Inflatable Paddle Board
- Final Words
A lot of people are arguing which one is better, inflatable paddle board or hard paddle board. The answer is simple. If you are hunting for an all-around paddle board that you can use for several different activities, and inflatable stand up paddle board is the best option. What makes them so popular these days are their durability, versatility, weight, portability, and injury prevention. Aside from, they are also much cheaper compared to a hard paddle board. Also, one of the reasons why there are several people who do not buy an inflatable SUP is because they do not know how do inflatable paddle boards work.
If you are thinking of buying an inflatable SUP and you want to know how do inflatable paddle boards work, then you are on the right article. We will walk you through the pros and cons of inflatable paddle boards, how do inflatable paddle boards work, and some tips when buying an inflatbale SUP. To know more about this, just keep on reading.
Understanding the Difference Between an Inflatable Paddle Board and Hard Paddle Board
Before we tackle and try to understand how do inflatable paddle boards work, it is important to determine how an inflatable SUP and hard paddle board differ from one another. We will also when it the best time to use an inflatable and a hard paddle board.
An inflatable stand up paddle board is considered as unique and advantageous among SUPs. They are becoming more and more popular each day primarily because they got more advanced in terms of features, materials, structure, and design. It is no wonder why people who used to be fond of hard paddle board prefer to use an inflatable SUP instead.
If you are still in the process of thinking which type of SUP to buy, here are some comparisons to consider.
🏄♀Inflatable Paddle Boards are Proven to be More Durable than Hard Paddle Boards
I know that you find this really surprising. As a matter of fact, you will not believe it. Whatever you are thinking right now, or whether you believe it or not, inflatables are not subject to the vulnerabilities of a solid one. In addition to that, if a hard paddle board need special repair, the ding and holes are quite expensive. On the other hand, an inflatable SUPs is not that difficult and expensive to repair.
That is one of the reasons why inflatable are starting to outnumber the paddle boards in the river. Also, SUP schools and rental agencies prefer to use an inflatable SUPs so as to decrease the board damage due to the careless handling of the students and other renters.
🏄♀Inflatable SUPs will not hurt you that much in case you fall on them
Of course, since it is inflatable where it material inside is air and not a solid material, you will not get hurt even if you fall on it. On the other hand, falling on solid board can be painful and it will not be easy for the body of the rider and anyone else the board may get in contact with.
🏄♀Reduces fatigue because of the soft deck
Standing on a high quality inflatable paddle board is like standing on a luxury rubber mat that are commonly utilized in a commercial setting to lessen fatigue With inflatable paddle board, you will not get easily tired even though you stand for several hours. You will be surprised that your feet still feel comfortable and relaxed primarily because of the decreased contact pressure. In addition to that, not only your feet will benefit from it, but also your knees, back, and even your neck.
🏄♀ A lighter board gets used more
Since an inflatable SUP is lighter, it gets used more often. It is easy to bring anywhere because its size is small when deflated. Not only that, it is also easier to navigate in the water.
An inflatable SUP normally weighs half the weight of a hard paddle board making it much easier to get in the water.
🏄♀ You can check in an inflatable paddle board in an airplane
If you are someone who is fond of going to other places to do water activities, an inflatable SUP is your best choice. When deflated, it can be rolled up to fit in you bag that you can place in the trunk of your car or checked in on an airplane.
In addition to that, taking an SUP with you during vacaction will save you a huge chunk of money since you do not need to pay for paddle board rentals. Also, you are free to use the paddle board whenever you feel like using it.
🏄♀ An inflatable SUP may not be suitable for competition
If you are a professional surfer and you want to join a competition, it is best to use a solid paddle board. It comes in different sizes and normally, the small ones are the best size for competition because they are faster and easy to operate.
How do Inflatable Paddle Boards Work? Inflatable SUP Pros And Cons
Pros of Inflatable Paddle Board
✔Easy to bring anytime, anywhere
The most common reason of people wanting to buy an inflatable SUP is because it is compact when deflated. This makes them easy to with your on your trips. With its size when deflated, you can just easily rolled it and place inside your bag.
In addition to that, you do not need a roof rack on your car when bringing your inflatable paddle board with you. All you need is a durable carrier for your inflatable SUP.
Basically, inflatable paddle boards are easy to bring anywhere. As a matter of fact, I know plenty of people who bring their inflatable SUPs wiht them on a cruise ship which is really great.
✔ Improved stability
What plenty of people do not know about inflatable paddle boards is that they are more stable than hard SUP. People who have inflatable SUP said they find it easier to learn compared to a hard shell one.
You might be wondering, how do inflatable paddle boards work and why are they more stable. One possible factor that contributes to its stability is because the thickness is consistent across the length and width of the paddle board. As a result, there is more buoyancy most specifically at the nose, tail, and edges.
✔ Safe for dogs
Good news for dog lovers out there. You can go paddling with your canine using a inflatable SUP. There are plenty of inflatable paddle board that are suitable for dogs. They are more stable and it lets your sit without his paws sliding through the surface.
Cons of Inflatable Paddle Board
In knowing how do inflatable paddle boards work, it is also important to understand its cons.
An inflatable paddle board is not that easy to maneuver unlike the hard shell ones. The latter can be sleek and shape for easy and fast maneuverability.
A lot of people I know said that inflatable SUP do not easily turn or respond as fast as hard paddle boards.
✘ Rigidity
If you are able to properly inflate the paddle board, then they will perform well. On the other hand, it is still not as rigid as those of hard shell paddle boards.
✘ The majority of the models are expensive
Believe it or not, inflatable paddle boards are more expensive than hard paddle boards. This is contrary to what most people think. This is because most of them are made of high quality materials. But of course, you will get what you pay for.
One of the most common concerns on inflatable paddle boards are its possibility of sinking in the middle of the board. If you fail to buy good quality, you will really get frustrated with it because the middle part of the board will jeopardize the board's performance. As a result, it will just ruin your experience.
It was discovered that this happens because they were not bale to have the board inflated on its maximum level. If you take and time and effort in properly inflating the board, you will not experience this kind of problem. Remember, the heavier the user is, the more pressure the more air pressure your board requires.
How to Make your Inflatable Paddle Board Last Longer
The most important thing that you can do in order to experience the most out of your inflatable SUP is to focus on proper care and maintenance. It is not that difficult at all to maintain your boards as long as you know exactly what to do and what not to do.
Follow the steps below to make sure you board will last longer
1.Always rinse off your inflatable paddle board after using
After using the board, do not just deflate it and put it inside your bag. This is important especially if you are fond of paddle boarding in the ocean. Salt water can be really dangerous for your board. It can easily ruin the coating of your paddle board which is why you have to make sure to rinse it properly with warm water after using.
Even after using it in freshwater, you still have to clean it so as to remove unnecessary dirt and grime
2. Properly dry your board
After rinsing off your board, you just do not rolled it up, you have to wait for it to dry completely before placing inside the bag. Also,when drying, it is best to leave it in a spot that is shaded. Make sure not to expose it on direct sunlight primarily because UV rays might cause your board to fade. Most importantly, it can degrade the PVC material. This may result to tears and punctures that will make your board risky to use.
3. Store your inflatable paddle board
After drying your inflatable paddle board, properly store it. While they are easy to transport and use, you have to make sure to do it the right way.
First, make sure that it is completely dry before storing. Check the air valves for possible debris and moisture. If there is any, you can just clean it out using a quick jet of air from an air pump. Also, you can use a ear swab cotton to get rid of the dirt.
Unfix the fins from your board before you store it. Fins should be placed separately from your board. Always make use of the carrying case that came with your inflatable SUP – you could damage it if you force it to place it into a bag that is too tiny for its size.
4.Seasonal Scrub
Give your paddle board an intensive cleaning at least once a year, using a mild detergent and a freshwater rinse. Majority of paddle boarders see that dish detergent works fine, but you can also use a specially made paddle board cleaning product.
5. Repair Damage Instantly
It's not uncommon for your paddle board to get a bit ruined and scraped up throughout a season. This kind of damage is normally very solvable, but it's important to fix such damage as soon as you discover it. If you don't make an action, a tiny puncture could instantly shift into a long tear, which may not be as simple to fix.
The majority of cuts and punctures are simple to fix with some Epoxy sealant. All you need to do is apply a small amount of sealant to the leak and allow it dry totally for a minimum of 24 hours. You will have to make sure that your inflatable SUP is tidy and carefully dry before you do any repairs. If your board has a lot of problems, you may have to get it professionally repaired.
Tips when Buying An Inflatable Paddle Board
✰ Do your research
Don't immediately purchase the first board you see. Do your assignment by doing research and buy from a well known brand that you've heard about and trust. As inflatable SUPs become more in dmeana, more brands are starting to appear on the market each day. But just because they make inflatable SUPs doesn't always mean they produce quality iSUPs!
We see different kinds of kit and some iSUPs you wouldn't try to stand on, on dry land especially on the water! So talk to other experts to hear their advice.
✰Try before you purchase
This is the perfect way to not only see what the model actually looks like but also how you operate and maneuver it. A high quality inflatable SUP must not look like a banana or get your feet moist while you are standing on it! It must feel perfectly rigid and if the perfect size not difficult to paddle.
✰Don't just buy it because it's cheap!
Prices of inflatable SUPs vary greatly. And there is usually a perfect reason for this! Less expensive inflatable SUPs are normally made with fragile materials, and as a result, models are not durable, less rigid and often hard to get spare parts for. Don't be too shocked if they look like a banana and feel hard to maneuver too! With that, don't think of buying a cheap board you've never tried or heard of before. But by conducting some research you may land on some less expensive brands that do make quality inflatable SUPs for their price tag, but they may have a less durable bag etc.
✰Feel the weight
Inflatable SUPs not only differ in weight because of their size, but also because of the materials and construction system used. A 10'5 inflatable SUP might weigh anything from 8kg to 14kg. It may not seem much but you'll certainly feel how they differ in your arms when bringing it down the beach with you.
So if you're hunting for an compact board to bring and place on the roof of your car, a light board to bring with you on your trips abroad then make sure you consider how heavy the boards. Nevertheless it's also worth remembering that the reason boards are heavier is because most of the time they are produced with more material which will have the advantage of typically being long lasting.
Final Words
In knowing how do inflatable paddle boards work, it is important to know what it is, what makes them popular, and its cons and pros. Aside from that, it is also important to know how to properly take care of it so as to last for a long time.


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Why We Empower
Why We Do What We Do
Meaningful Spare Time
How It All Began
Team Players
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Play and learn
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Use tab to navigate through the menu items.
Career Help
Work Shadow is an initiative aimed at assisting to prepare for work life and adulthood by offering a theoretical part where we teach the participants everything around preparing for work, applying for work, and how to conduct themselves at the workplace. This part is then coupled with a practical part where the youth receive experience through an internship.
Project Playground values the strengths in shared knowledge and have therefore partnered with organisations who bridge the gap into the labor market.


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Join us for a holiday celebration featuring many Small Works from more than 40 resident Tree's artists and several invited guests!
Opening Reception November 29th from 5 - 7pm. On view from November 29th - December 31st. Open to the public.
The best way to stay informed via our periodic event announcements.
You will receive a confirmation email sent to the email address you submitted. If you do not, please feel free to get in touch via phone.
Thank you for your interest...we hope to see you soon.
- Tree's Place×


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We are on a mission to change how you view hostels. And we're proud to have created the kind of place we would ourselves want to stay. There's always something to do if you fancy a night in from exploring. If your travel bug is calling, we know the best places to visit. We have tours and events happening all the time.
The Safestay hostel location is important to us. It needs to be a central, close to transport, good access, great building and most importantly close to the coolest spots in the city!


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Many industries share common problems that can be lumped into a focus on process efficiency and effectiveness. Decision Management Systems, by handling critical decisions in those processes, can make a big difference on both counts. Some examples follow.
Has enough information been entered? Does it match other information available and is it internally consistent? This kind of rules-based validation is common to many processes and using a Decision Management System to automate this check speeds processing and reduces manual overhead.
Completeness and readiness
Many processes have steps that are more expensive, such as conducting an inspection or writing a contract. By automating a check to see if the process is ready to go to the next step—do we have all the information needed to effectively inspect this ship or building, to put a contract together for this deal or annuity—Decision Management Systems ensure that processes only move on when it makes sense to do so.
An interesting variation comes in situations where only a human can really tell if something is true or not, such as a customs declaration. A Decision Management System might use rules and analytics to determine how plausible such a declaration is, helping focus limited resources where they will do the most good.
Assignment or allocation
Many processes involve assignments and allocations: decisions about who to make responsible, how to allocate the work involved, and who should do what. When processing speed is important, or when consistency and traceability are a must, a Decision Management System can provide rapid, agile, compliant processing.
Sequencing and Adaptive Case Management
Many processes are increasingly modeled using a more adaptive approach. Instead of laying out all the steps and branches, different clusters or groups of tasks are identified that may need to be handled for a particular transaction or case. Deciding which need to be included, and when, is a task ideally handled by a Decision Management System that is monitoring the case and constantly evaluating the most appropriate and necessary steps for the case.
Dynamic forms
Collecting data from people is a constant challenge. While sometimes a simple form or a form with a few options works well, sometimes it is very difficult for a user to determine what data is required. Each question they answer drives the need to answer, or not answer, subsequent questions. This kind of dynamic questioning is another good user case for Decision Management Systems.
Dynamic Checklists
Checklists are a powerful tool for improving the effectiveness of staff members. But to work a checklist must be very specific. Trying to handle even a small number of situations with a single checklist can make for complex checklists with lots of navigational instructions to make sure the right items are checked at the right times. Instead a Decision Management System can be used to drive dynamic checklist. Very specific checklists generated for each circumstance. All the checks needed for that circumstance but only the ones needed.
Read more in our Decision Management Systems Platform Technologies Report.


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The Kootenai County Social Security Office is a local branch of the Federal Social Security Administration, which provides financial support to retired workers and disabled workers in Kootenai County, Idaho. Workers are eligible for Social Security assistance if they meet certain age and work history requirements, or if they have suffered a long-term disability and are unable to work. Social Security Offices provide assistance in enrolling for Kootenai County Social Security benefits and disability insurance (SSDI), processing and distributing financial stipends, and planning for retirement needs.
Coeur D Alene Social Security Office Coeur d'Alene ID 623 East Wallace Avenue 83814 866-931-2523
The Kootenai County Unemployment Office is a government agency at the state, county, or local level that provides support to people who are unemployed in Kootenai County, Idaho. Unemployment Offices provide support services for people applying for Kootenai County employment benefits, including help with obtaining healthcare and other benefits, and process and submit unemployment insurance payments. Kootenai County Unemployment Offices also offer job training services and provide assistance in finding employment.
Post Falls Unemployment Office Post Falls ID 600 North Thornton Street 83854 208-457-8789


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A highly stable Retinol serum formulated at a concentration perfectly suited for skin that is new to retinoids. Retinol, a vitamin A derivative, is effective for ageing, acne and dark spot concerns. Retinol inhibits collagen breakdown that causes elastosis, unclogs blocked pores, reducing acne breakouts. Promotes cell turnover, encouraging new cell growth for a more even complexion.
Limit initial use to three times per week, applying only in the evening after cleansing. Water based serums should be applied first and a moisturiser after this serum if need be. Gradually increase the frequency of application to every night.
Price: R240.00
Availability: www.skinfunctional.com


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It's Amputee August and today we want to share some fun Tripawd cat exercise tips!
Your guide is Dr. Amber Callaway Lewis, founder of Treasure Coast Animal Rehabilitation in Vero Beach, Florida. We spoke with Dr. Lewis in a recent Tripawds Facebook Live about rehab therapy for amputee cats and dogs. Here's her two fun exercise tips for three-legged cats:
Two Fun Ways to Exercise a Three-Legged Cat
The word "cats" plus "exercise" don't seem to go together, do they? Well, according to Dr. Lewis, they do! Start by using food as a training tool, she suggests. One way or another, food gets most felines motivated enough to burn extra calories.
Fun with Cat Kibble, Part 1
Kick start an exercise session by diving up one cup of cat kibble into a few small bowls. Then place them all around the house.
"There's no reason your cat who sleeps all day can't walk to get their food!" says Dr. Lewis.
Great places to put your kitty's food include a low step, or on the couch so your Tripawd cat has to actively step or reach up to get it.
Whatever you do, don't hide your cat's food. That's not motivating at all!
Fun with Cat Kibble, Part 2
Next, Dr. Lewis suggests putting your Tripawd cat's normal amount of kibble into your pocket.
Then, drop one kibble at a time while making sure your cat sees you do it. Walk all over your home, dropping a little kibble here and a little kibble there. This should motivate your three-legged cat to walk around and burn calories.
Remember to Add Traction
These Tripawd cat exercise tips are great, but they work even better if your home has lots of traction for your kitty. Always make sure your cat has safe, slip-proof places to walk. Get carpet runners or yoga mats and place them in areas that make it easy for your amputee cat to go from one room to another.
"Once they know they're secure on three legs," says Dr. Lewis, "you can just grow together from there."
If you live near Vero Beach Florida, be sure to stop by Dr. Lewis' clinic, Treasure Coast Animal Rehab and Fitness. She's got lots of exciting Tripawd deals going on this month!
And if you're not in Florida, you can get more great Tripawd cat exercise tips in Cool Tips for Tripawd Cats, our feline amputation handbook.


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Popular Landlord-Tenant Guide Updated
The California Department of Real Estate recently released the updated version of "California Tenants: A Guide to Residential Tenants' and Landlords' Rights and Responsibilities." The popular guide was last published by the California Department of Consumer Affairs in 2012 but became somewhat obsolete in the last few years.
Numerous substantive changes to landlord-tenant law are included in the new version of "California Tenants." The 2019 Tenant Protection Act (known as AB 1482) provides protections for certain long-term tenants by limiting rent increases and requiring landlords to state a cause for termination in certain cases (and sometimes even paying relocation benefits).
The publication also alerts consumers of emergency legislation due to the Covid-19 pandemic. On August 31, 2020, the California legislature passed the "Tenant, Homeowner, and Small Landlord Relief and Stabilization Act of 2020 (known as AB 3088)," which included the COVID-19 Tenant Relief Act of 2020. Tenants who experience financial distress due to the pandemic (e.g. income loss) may have eviction protections under the Tenant Relief Act or a nationwide order issued on September 4, 2020 by the CDC (Centers for Disease Control and Prevention).
In addition to the major updates listed above, other parts of California landlord-tenant law have changed as well. The California Tenants booklet is currently available online, and it is expected to be available in print later this year.
To review the revised California Tenants guide, visit the Dept. of Real Estate's Housing is Key website at https://landlordtenant.dre.ca.gov/resources/guidebook/index.html
If you are a landlord or tenant (aged 60+) who needs help navigating the complex California landlord-tenant laws, please contact our office for a review of your specific situation.


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