Repurposing Bird Bycatch From Camera Traps in Urban Landscapes: A Correlate of Avian and Mammalian Richness?

ABSTRACT Camera traps are extensively used to monitor medium-and large-bodied mammals, but the avian bycatch they generate remains largely untapped in biodiversity assessments. This underuse is particularly evident in urban ecosystems, despite the growing application of camera trapping in cities. Here, we evaluated the ecological value of bird detections obtained opportunistically from camera traps by comparing them with standardized point count surveys conducted in 2023–2024, across the metropolitan area of Firenze, central Italy, and explored their potential to indicate broader urban biodiversity patterns through cross-taxa relationship with mammal richness. Combining both methods, we recorded 72 bird species, with camera traps detecting two-thirds of total richness. Bird species richness estimated from camera traps was strongly and positively correlated with richness derived from point counts across sampling stations, indicating that camera-trap bycatch captures consistent spatial patterns in avian diversity. Bird communities detected by the two methods showed a high degree of species overlap (70%), although modest but significant differences in community composition were observed, reflecting method-specific detection biases. Using camera-trap data, we detected a positive association between mammal and bird richness values across sites. This relationship was confirmed after accounting for variation in sampling effort and seasonal effects, suggesting that local areas supporting a higher diversity of birds also tend to support a richer mammal community. Overall, our results show that avian bycatch from camera traps provides meaningful information on bird diversity and complements traditional survey methods, while also offering potential insights into multi-taxon biodiversity patterns. Repurposing existing camera-trap datasets can therefore enhance the efficiency and taxonomic breadth of urban biodiversity monitoring programs.