CoExist: Monitoring environmental-related transhumance patterns and assessing the risk for population displacement

Introduction

In cooperation with the International Organization of Migration (DLR), RSS has successfully completed the project CoExist, which was funded by the German Aerospace Center (DLR) through the Federal Ministry for Economic Affairs and Energy (BMWK). The project outcome included a publication on environmental suitability maps for transhumance to support the planning of corridors and conflict prevention in the Sahel.

Background

Conflicts between farmers and semi-nomadic livestock herders (transhumance) have increased over the past two decades and continue to be a major challenge in sub-Saharan Africa. Especially farmer-herder conflicts in relation to drought and water tensions have become widespread in the Sahel and East Africa. Transhumance often occurs across different agro-ecological regions and country boundaries, can flexibly and quickly adapt to major seasonal and interannual variations of natural resources and thus provides resilience to climatic events such as droughts. With increasing number of extreme weather events and increasing cropland expansion, local subsistence farmers and seasonally migrating pastoralists are more and more competing for the same natural resources such as water and grazing land. Such conflicts have increased in both number and severity, often result in violent clashes and with the effect of forced displacement of communities or some populations groups.

Goals

The project aimed at holistically assessing the main environmental parameters that influence the patterns of seasonal migratory movements (transhumance) in a transboundary area in the southern Republic of Chad and northern Central African Republic through a broad set of Earth observation (EO) data and data from the Transhumance Tracking Tool. Relevant parameters such as the availability of surface water and its temporal dynamics, productivity of pasture, extent of various agricultural systems, drought indicators, and burned areas are derived from EO data. This allows us to analyze the spatio-temporal dynamics of transhumance and the associated risks of conflicts and population displacement. By combining these EO based datasets with data from the “Transhumance Tracking Tool” and conflict location data from the Armed Conflict Location and Events Data (ACLED), the project aimed at providing a better understanding of the patterns of transhumance and identifying potential areas of conflict. This can help to plan effective, conflict-sensitive solutions by governmental and civil actors