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Abstract:
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Understanding how communities respond to environmental change is frustrated by the fact that both species interactions and movement affect biodiversity in unseen ways. Dynamic models that are capable of capturing non-linear responses to the environment and the redistribution of species across a spatial range are required. We develop a time-series framework that models the effects of environment-species interactions as well as species-species interactions on population growth within a community. We adopt a hierarchical Bayesian approach, allow for species redistribution across a spatial region, and address the issue of zero inflation. To evaluate the impacts of interactions and movement on population growth, we apply our model using citizen science data through eBird, a global citizen science database dedicated to birds. Using an illustrative region in North Carolina, we model a community of six bird species. The results provide evidence of non-linear responses to interactions with the environment and other species, and demonstrate a pattern of strong intraspecific competition coupled with many weak interspecific species interactions.
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