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Assessing patterns of extinction risk amongst mammal species in Nigeria: A comparative analysis of human impact.

Created on 30 Aug 2026

Authors

Bernard Asanbe

Published in

Biodiversity data journal. Volume 14. Pages e191439. Epub Aug 21, 2026.

Abstract

This study aimed to evaluate how biological traits influence extinction risk amongst mammal species in Nigeria and how these traits interact with specific anthropogenic threats, such as agriculture, urbanisation and climate change. Focusing on mammal species in Nigeria, we used phylogenetic logistic regression to test the influence of five biological traits: body mass, brain mass, generation time, current geographic range and historical range contraction, on extinction risk across nine IUCN threat categories. Standardised models were used to compare trait sensitivity across threats. Brain mass emerged as the most consistent and influential predictor of extinction risk across threat categories, including agriculture, biological resource use, urban development and, notably, climate change, where it was the strongest predictor of all models. Species with larger brains, often primates and carnivores, were highly vulnerable. Geographic range size was a strong negative predictor of risk across most models, with range-restricted species more susceptible to habitat loss and fragmentation. Generation time was positively associated with risk under direct human pressures, but inversely linked under climate threats. Body mass showed weak and inconsistent effects overall, though it was significantly and negatively associated with extinction risk under agriculture and aquaculture. The number of species affected was highest under direct human pressures, compared to indirect anthropogenic threats, such as climate change and pollution. Extinction risk in Nigerian mammals is shaped by intrinsic traits that interact predictably with human pressures. Species with large brains, small ranges and slow reproduction are at greatest risk. Trait-based models can improve conservation planning by identifying vulnerable species before population declines become critical, especially in regions facing intensive land-use change.

PMID:
42668897
Bibliographic data and abstract were imported from PubMed on 30 Aug 2026.

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