Climate change expected to increase conflict risks over the next decades across sub-Saharan Africa

<p>While climate change is increasingly recognized as a driver of conflict risks, most research focuses on past correlations, hence limiting our ability to project future climate-related security risks. We use machine learning techniques to predict the spatiotemporal dynamics of conflict risks and estimate the human population that would be exposed to these risks in the 2030s, 2040s, and 2050s. Our results demonstrate that climate change is associated with increasing risks of conflict over the next decades and that the change of projected spatial and temporal distribution of conflict risk will be heterogeneous, depending on conflict types and climate scenarios. We estimate that 0.5-1.7 billion people may live at high risk zones of conflict across sub-Saharan Africa by the 2050s, which is an increase of at least 391 million compared to today. Detecting such risks early provides sufficient time to plan ahead and implement mitigation strategies.</p>

Authors

Publication Details

Journal
The Innovation Geoscience
Published
2025-01-01
DOI
https://doi.org/10.59717/j.xinn-geo.2025.100139
Citations
1
Primary Topic
Transboundary Water Resource Management
Type
article
Field-Weighted Citation Impact
4.20
Controls
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article

Climate change expected to increase conflict risks over the next decades across sub-Saharan Africa

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1 citations
The Innovation Geoscience
Transboundary Water Resource Management
4.20
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Climate change expected to increase conflict risks over the next decades across sub-Saharan Africa

Z. X. Meng, Lei Liu, Kai Sun, Tingting Kang, Tobias Ide, Xiaolan Xie, Jürgen Scheffran, Dong Jiang, Liqiang Zhang, Shuai Chen, Mengmeng Hao, Yongqing Bai, Zhenyu Wang, Tian Ma, Chao Yang, Qian Wang, Hou Jiang, Wenxiang Wu, Jiping Dong, F. Ding, Jun Zhuo, Jiajie Wu, Ling Yao, Jean-Fran ccedil ois Maystadt
article en
1 citations

Abstract

<p>While climate change is increasingly recognized as a driver of conflict risks, most research focuses on past correlations, hence limiting our ability to project future climate-related security risks. We use machine learning techniques to predict the spatiotemporal dynamics of conflict risks and estimate the human population that would be exposed to these risks in the 2030s, 2040s, and 2050s. Our results demonstrate that climate change is associated with increasing risks of conflict over the next decades and that the change of projected spatial and temporal distribution of conflict risk will be heterogeneous, depending on conflict types and climate scenarios. We estimate that 0.5-1.7 billion people may live at high risk zones of conflict across sub-Saharan Africa by the 2050s, which is an increase of at least 391 million compared to today. Detecting such risks early provides sufficient time to plan ahead and implement mitigation strategies.</p>

The Innovation GeoscienceVol. 3(3)
Openalex Percentile: Top 6%
Transboundary Water Resource Management
4.20
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