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Abstract:
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Occupancy models are increasingly being used in ecology to model the spatial distribution of imperfectly detected species. These models allow researchers to study the effect that covariates have on the probability of presence, while accounting for imperfect detection and spatial dependence. Recently, bivariate extensions to these models have been proposed to better understand interactions among various species. In this work, we analyze data from Snapshot Serengeti, a camera-trap survey with 225 cameras covering a 1000 sq km grid over five years in Serengeti National Park in northern Tanzania, a region that has faced severe declines in large herbivore and carnivore populations. We develop a bivariate Bayesian occupancy model to study the predator/prey dynamics in response to the dramatic shifts in vegetation observed in this savanna ecosystem.
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