文章基本信息

标题：Climate variability and conflict risk in East Africa, 1990–2009
本地全文：下载
作者：John O’Loughlin ; Frank D. W. Witmer ; Andrew M. Linke 等
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2012
卷号：109
期号：45
页码：18344-18349
DOI：10.1073/pnas.1205130109
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：Recent studies concerning the possible relationship between climate trends and the risks of violent conflict have yielded contradictory results, partly because of choices of conflict measures and modeling design. In this study, we examine climate-conflict relationships using a geographically disaggregated approach. We consider the effects of climate change to be both local and national in character, and we use a conflict database that contains 16,359 individual geolocated violent events for East Africa from 1990 to 2009. Unlike previous studies that relied exclusively on political and economic controls, we analyze the many geographical factors that have been shown to be important in understanding the distribution and causes of violence while also considering yearly and country fixed effects. For our main climate indicators at gridded 1{degrees} resolution ([~]100 km), wetter deviations from the precipitation norms decrease the risk of violence, whereas drier and normal periods show no effects. The relationship between temperature and conflict shows that much warmer than normal temperatures raise the risk of violence, whereas average and cooler temperatures have no effect. These precipitation and temperature effects are statistically significant but have modest influence in terms of predictive power in a model with political, economic, and physical geographic predictors. Large variations in the climate-conflict relationships are evident between the nine countries of the study region and across time periods.
关键词：social instability ; standard precipitation index ; generalized additive modeling ; negative binomial modeling ; disaggregated spatial analysis