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Study predicts collision risk for vultures in Zambia, highlighting intervention needs for energy infrastructure.
Biodiversity is in rapid decline, and Africa's vultures, keystone obligate scavengers, are among the most threatened groups, with declines driven mainly by poisoning, belief-based uses and expanding energy infrastructure. This thesis assembles the scientific and applied context for mitigating wind turbine and power line collisions to vultures and then delivers a Zambia-focused spatial assessment to guide action. Chapters 1-4 synthesize (i) the biodiversity crisis and why birds are sensitive indicators; (ii) vulture taxonomy, ecology, services, and principal threats; (iii) the effects of wind turbines and power lines on birds and available mitigation measures; and (iv) the evolution, capabilities, and limits of modern bird telemetry, establishing the analytical foundations used here. The core of the thesis (Chapter 5) presents the first region-specific, spatially explicit prediction of collision risk for White-backed Vultures (Gyps africanus) across Zambia and adjoining regions. Using GPS telemetry from 58 individuals, exposure (space-use intensity) was quantified with dynamic Brownian Bridge Movement Models (5×5 km grid) and combined with vulnerability, defined as the proportion of flights within collision relevant heights for wind turbines (35-203 m AGL) and power lines (7-50 m). Where flight height data was unavailable, heights were modelled from speed and environmental covariates with Generalized Additive Models. The composite surface revealed key collision hotspots, mainly around the Luangwa Valley, Lower Zambezi, Kafue (including links into Chisamba/Lusaka), Nsumbu, Liuwa Plain-Barotse Floodplain, and the Bangweulu-Kasanka-Mkushi-Chisamba corridor. The prediction is intended for relative (not absolute) risk prioritization, given known vertical-error constraints and modest height-model fit. The resulting risk maps should inform vulture-sensitive siting of new wind turbines and transmission lines and guide targeted mitigation on existing high-risk grid segments (e.g. line-marking diverters, retrofits, and insulation) where collision risk is elevated.
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Tom Riffel (2025) studied this question.
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