<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are an expert on climate change, human mobility and migration. Answer the question truthfully.<|eot_id|><|start_header_id|>user<|end_header_id|>Here are the title and abstract of a scientific paper probably related to climate change, human mobility and migration..
Title:"Enhancing early warning in the light of migration and environmental shocks."
Abstract:"Early Warning Systems (EWS) are key elements of risk reduction and adaptation strategies to extreme events. Until now, most EWS have focused mainly on hazard detection and the immediate warning and evacuation processes with an effort of saving lives in the context of an extreme event; however, in the light of climate change and migration more attention must also be paid to the question of how EWS can improve livelihood security. On the one hand, migration patterns, urbanization and population growth are important factors that will modify and in most cases increase exposure, and in some cases increase vulnerability. On the other hand, migration in the context of extreme events and sea level rise might also be an important adaptation strategy. The paper deals with the concept of people-centred early warning and examines how aspects of the so-called Last Mile can be better taken into account. In this regard, the framework conditions and the governance context of early warning are discussed and analysed. Strategies on how to enhance EWS are outlined, particularly regarding the nexus between migration, urbanization, daily mobility and early warning. Up to now, most EWS do not sufficiently consider migration and daily mobility patterns within the information or warning chain. Therefore, the paper examines the importance of migration, urbanization and daily mobility patterns for effective early warning. On the basis of this discussion, the paper identifies new challenges for early warning in the context of climate change and deals with the potential constraints of integrative EWS. Finally, the paper derives conclusions and recommendations on not only how to better account for migration in EWS, but also how to improve the consideration of early warning in migration and adaptation strategies. (C) 2012 Elsevier Ltd. All rights reserved.."
I have six questions you need to answer.
Q1: Is this article is about 'human migration mobility': 1 = yes; 0 = no. Answer with a number. Do not give a textual explanation.

Q2: What drivers of migration and mobility does the article study? 0 = 'other', 1 = 'climate', 2 = 'environment', 3 = 'economic', 4 = 'conflict', 5 = 'political', 6 = 'social', 7 = 'family'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q3: What is the overall sentiment of the article?:0 = 'neutral', 1 = 'negative', 2 = 'positive'. Answer with a number. Do not give a textual explanation.

Q4: What type of climate or environmental keywords are explicitly mentioned?:  0 = 'none', 1 = 'algal blooms', 2 = 'infestation', 3 = 'infectious diseases', 4 = 'ocean acidification', 5 = 'sea ice', 6 = 'acid rain', 7 = 'drought', 8 = 'cold wave', 9 = 'heat wave', 10 = 'glacial', 11 = 'wildfire', 12 = 'air pollution', 13 = 'biodiversity loss', 14 = 'coastal erosion', 15 = 'land degradation', 16 = 'deforestation', 17 = 'desertification', 18 = 'water pollution', 19 = 'diebacks', 20 = 'permafrost loss', 21 = 'sand mining', 22 = 'sea level rise', 23 = 'earthquake', 24 = 'tsunami', 25 = 'volcanic', 26 = 'flood', 27 = 'avalanche', 28 = 'landslide', 29 = 'downburst', 30 = 'thunderstorm', 31 = 'sandstorm', 32 = 'haze', 33 = 'storm', 34 = 'cyclone', 35 = 'blizzard', 36 = 'hail', 37 = 'snow', 38 = 'tornado', 39 = 'wind', 40 = 'hurricane', 41 = 'typhoon', 42 = 'other'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q5: What discipline does the article belong to?: 0 = 'other', 1 = 'social science', 2 = 'natural science', 3 = 'arts and humanities', 4 = 'multidiscipline and interdiscipline'. Answer with a number. Do not give a textual explanation.

Q6: Does the article apply quantitative and/or statistical analysis?: 0 = 'no', 1 = 'yes'. Answer with a number. Do not give a textual explanation.

Use the following template: 

Q1 = [];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [];
Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [1];
Q2 = [2];
Q3 = [2];
Q4 = [22];
Q5 = [];
Q6 = [1].
Enhancing early warning in the light of migration and environmental shocks
Early Warning Systems (EWS) are key elements of risk reduction and adaptation strategies to extreme events. Until now, most EWS have focused mainly on hazard detection and the immediate warning and evacuation processes with an effort of saving lives in the context of an extreme event; however, in the light of climate change and migration more attention must also be paid to the question of how EWS can improve livelihood security. On the one hand, migration patterns, urbanization and population growth are important factors that will modify and in most cases increase exposure, and in some cases increase vulnerability. On the other hand, migration in the context of extreme events and sea level rise might also be an important adaptation strategy. The paper deals with the concept of people-centred early warning and examines how aspects of the so-called Last Mile can be better taken into account. In this regard, the framework conditions and the governance context of early warning are discussed and analysed. Strategies on how to enhance EWS are outlined, particularly regarding the nexus between migration, urbanization, daily mobility and early warning. Up to now, most EWS do not sufficiently consider migration and daily mobility patterns within the information or warning chain. Therefore, the paper examines the importance of migration, urbanization and daily mobility patterns for effective early warning. On the basis of this discussion, the paper identifies new challenges for early warning in the context of climate change and deals with the potential constraints of integrative EWS. Finally, the paper derives conclusions and recommendations on not only how to better account for migration in EWS, but also how to improve the consideration of early warning in migration and adaptation strategies. (C) 2012 Elsevier Ltd. All rights reserved.