Shotgun metagenomics reveals seasonal variation in the diet of American black bears (Ursus americanus) in West Texas

Résumé fourni par la source

Understanding the dietary requirements of wildlife is essential for elucidating trophic interactions and informing targeted conservation and management strategies, including habitat improvement, human–wildlife conflict mitigation, and supplemental feeding program design. Direct observation of wildlife feeding is often challenging; however, non-invasively collected fecal samples provide a valuable means of reconstructing diet in elusive species. Here, we used shotgun metagenomic sequencing of 134 fecal samples collected in the Trans-Pecos ecoregion of West Texas to characterize the diet of American black bears ( Ursus americanus ) and evaluate seasonal variation in dietary composition. Diets were dominated by plant material (71.0%), with animal-derived sequences comprising 12.7% and 16.3% unclassified. Significant seasonal variation was detected across both alpha and beta diversity metrics. Dietary richness (Hill 0 ) was highest during summer, whereas dietary diversity (Hill 1 ) was highest in spring. Permutational analyses indicated that diet composition varied significantly among seasons (Bray–Curtis: R² = 9.4%, p = 0.013; Jaccard: R² = 7.2%, p = 0.04). Differential abundance analyses revealed distinct seasonal patterns in dominant taxa, including pricky pear cactus ( Opuntia ) in summer, oak ( Quercus ) in fall, physic nut ( Jatropha ) in spring, and sotol ( Dasylirion ) in winter. Genera associated with anthropogenic food subsidies, including crabgrass ( Digitaria ), sorghum ( Sorghum ) and corn ( Zea ) were also detected, indicating dietary exposure to human-modified food resources. These findings demonstrate the utility of shotgun metagenomics for non-invasive dietary monitoring and provide insights into seasonal resource use by black bears, with direct implications for managing human–bear interactions, prioritizing habitat conservation, and monitoring recolonizing populations in human-modified landscapes.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.