Determining causes and processes underlying wildlife population declines

• Applicant: Dr. Joseph Ochieng Ogutu
• Subject Area: Ecology and Biodiversity of Animals and Ecosystems, Organismic Interactions ; Ecology of Land Use
• Term: from 2014 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 257734638

Biodiversity and its contributions to ecosystem goods and services are essential for human well-being and for sustaining human civilization and prosperity. However, largely due to human dominance, biodiversity is declining markedly, and often catastrophically, in many ecosystems worldwide. The losses incur extinction debts and, for many vertebrate populations, are already so extreme as to qualify as biological annihilation. Consequently, the most pressing issue in conservation research today should thus be to assess how human influences drive wildlife population declines. However, this has not been done for most declining populations. We aim to clarify processes causing wildlife population losses using the example of Kenya’s drylands. We will overcome a key limitation to most previous studies that have assessed causal drivers of population losses. This limitation is that population monitoring programs rarely collect detailed contemporaneous data on covariates needed to discern causes of population declines and how they operate. We will do statistical assessments to obtain critical inferences on factors that best explain historic patterns of wildlife population abundance and species diversity and the relative influences of key drivers of wildlife losses. We will use the established relationships to project future wildlife population and species diversity dynamics. We will use existing aerial survey data on wildlife and livestock counts and associated covariates collected at 5 x 5 km resolution from 1977 to 2017 in Kenya’s drylands. We prepared and verified this database for accuracy in phase 1 of the project. These fine resolution data sets open the door to extending and deepening the analyses we did in phase 1 of this project that used wildlife population estimates at the political county level only. This will be the first study to use these long-term fine-scale records of animal counts and covariates to infer processes that govern wildlife declines. The long-term fine-scale data and robust analytical approaches will allow us to intensely explore processes causing wildlife population declines in protected and human-dominated landscapes. This was not possible with the coarse scale data available to us in phase 1 of this project. Findings will contribute to development of possible solutions of wildlife population and species diversity declines.

• DFG Programme: Research Grants