Ecosphere (Apr 2023)
Noninvasive camera data and spatial capture–recapture models reveal strong temporal variation in fawn survival
Abstract
Abstract In south Florida, white‐tailed deer (Odocoileus virginianus) are the primary prey of the endangered Florida panther (Puma concolor coryi). Deer populations in some regions of south Florida have declined in recent years, and the role of fawn survival and recruitment in these declines is unknown. Determining known‐fate survival of fawns is challenging, requires invasive and costly methods, and often has a limited geographic scope. We deployed 180 cameras throughout the Florida Panther National Wildlife Refuge and the Big Cypress National Preserve to understand how environmental variables influence fawn survival. We identified 271 fawns from 12,715 photographs in 2015 and 2016. We utilized a noninvasive sampling method coupled with a spatial capture–recapture model to estimate the number of fawns born, the spatial distribution of birth locations, and the number of fawns that survived to recruitment (180 days old) during two fawning seasons. We found strong evidence of temporal variation in survival, but little evidence of spatial variation. Within the 10,941‐ha study area, we estimated that 305 (95% CI: 245–385) fawns were born in 2015 and 278 (212–381) fawns were born in 2016. In 2015, 36% (110) of the estimated 305 fawns survived to 180 days. However, in 2016, only 13% (36) of the estimated 278 fawns survived to 180 days. The large difference in recruitment between years was likely driven by record flooding in 2016. Our data suggest that extreme weather events, coupled with high adult mortality, likely contributed to recent deer population decline in south Florida through reduced fawn recruitment. Unlike studies of known‐fate fawn survival that require labor‐intensive and invasive capture of both adults and neonates, our approach relies exclusively on camera data, which makes it possible to conduct studies over broad spatiotemporal scales in challenging environments to illuminate the drivers of variation in juvenile survival.
Keywords