Integrating over uncertainty in spatial scale of response within multispecies occupancy models yields more accurate assessments of community composition

Species abundance and community composition are affected not only by the local environment, but also by broader landscape and regional context. Yet, determining the spatial scales at which landscapes affect species remains a persistent challenge, hindering our ability to understand how environmental gradients shape communities. This problem is amplified by data deficient species and imperfect species detection. Here, we present a Bayesian framework that allows uncertainty surrounding the “true” spatial scale of species’ responses (i.e., changes in presence/absence) to be integrated directly into a community hierarchical model. This scale-selecting multi-species occupancy model (ssMSOM) estimates the scale of response, and shows high accuracy and correct levels of uncertainty in parameter estimates across a broad range of simulation conditions. An ssMSOM can be run in a matter of minutes, as opposed to the many hours required to run normal multi-species occupancy models at all queried sp...