Abstract
Given that armed conflict has been seriously impeding sustainable development, reducing the frequency and intensity of armed conflicts has become an explicit goal and a common theme of the 2030 Sustainable Development Goals. Determining the factors shaping armed conflict risks in different regions could support formulating region-specific strategies to prevent armed conflicts. A machine learning approach was applied to reveal the drivers of, and especially the impact of climatic conditions on, armed conflict in Sub-Saharan Africa, the Middle East, and South Asia and characterizes their changes over time. The analyses show a rising impact of climatic conditions on armed conflict risk over the past decades, although the influences vary regionally. The overall percentage increases in the contribution of climatic conditions to conflict risks over the last 30 years in Sub-Saharan Africa, the Middle East, and South Asia are 4.25, 4.76, and 10.65 percentage points, respectively. Furthermore, it is found that the Climatic–Social–Geographical (“C–S–G”) patterns that characterize armed conflict risks vary across the three studied regions, while each regional pattern remains relatively stable over time. These findings indicate that when devising defenses against conflicts, it is required to adapt to specific situations in each region to more effectively mitigate the risk of armed conflict and pursue Sustainability Development Goals.
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