AI-based satellite survey offers independent assessment of migratory wildebeest numbers in the Serengeti

The Great Wildebeest Migrationin the Serengeti-Mara ecosystem is a globally iconic wildlife phenomenon that supports the health and biodiversity of the region by supporting predator populations, regulating herbivore densities, and driving nutrient cycling. This study presents the first AI-powered satellite survey, using two deep learning-based models (U-Net and YOLOv8) to detect and count wildebeest over more than 4,000 km² across two consecutive years in August 2022 and 2023 with F1 scores reaching 0.830 (Precision: 0.832, Recall: 0.838). The satellite-based results show fewer than 600,000 individuals-approximately half the widely cited estimate of 1.3 million wildebeest, which has remained largely unchanged since the 1970s. While some variation may arise from differences in spatial and temporal coverage between survey methods, the satellite approach employs rigorously validated AI models with demonstrated accuracy. Rather than undermining previous methods, this discrepancy underscores the importance of using independent and complementary monitoring tools to refine population estimates and improve our understanding of wildebeest movement dynamics.

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Publication Details

Journal
PNAS Nexus
Published
2025-08-30
DOI
https://doi.org/10.1093/pnasnexus/pgaf264
Citations
3
Primary Topic
Wildlife Ecology and Conservation
Type
article
Field-Weighted Citation Impact
5.15
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article

AI-based satellite survey offers independent assessment of migratory wildebeest numbers in the Serengeti

Stephen J. Lee, Isla Duporge, Zijing Wu, Daniel I. Rubenstein et al.
3 citations
PNAS Nexus
Wildlife Ecology and Conservation
5.15
article

AI-based satellite survey offers independent assessment of migratory wildebeest numbers in the Serengeti

Stephen J. Lee, Isla Duporge, Zijing Wu, Daniel I. Rubenstein, Peng Gong, David W. Macdonald, Simon A. Levin, Tiejun Wang, Zeyu Xu, A. R. E. Sinclair
article en
3 citations

Abstract

The Great Wildebeest Migrationin the Serengeti-Mara ecosystem is a globally iconic wildlife phenomenon that supports the health and biodiversity of the region by supporting predator populations, regulating herbivore densities, and driving nutrient cycling. This study presents the first AI-powered satellite survey, using two deep learning-based models (U-Net and YOLOv8) to detect and count wildebeest over more than 4,000 km² across two consecutive years in August 2022 and 2023 with F1 scores reaching 0.830 (Precision: 0.832, Recall: 0.838). The satellite-based results show fewer than 600,000 individuals-approximately half the widely cited estimate of 1.3 million wildebeest, which has remained largely unchanged since the 1970s. While some variation may arise from differences in spatial and temporal coverage between survey methods, the satellite approach employs rigorously validated AI models with demonstrated accuracy. Rather than undermining previous methods, this discrepancy underscores the importance of using independent and complementary monitoring tools to refine population estimates and improve our understanding of wildebeest movement dynamics.

PNAS NexusVol. 4(9)
Hong Kong Baptist University (HK), University of British Columbia (CA), Sun Yat-sen University (CN), Princeton University (US), University of Oxford (GB), Education University of Hong Kong (HK), Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (CN), Department of Chemistry and Earth Sciences (BY), United States Army Research Office (US), University of Hong Kong (HK)
Openalex Percentile: Top 5%
Wildlife Ecology and Conservation
5.15
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