Moving beyond just the environment – joint modeling to incorporate species interdependencies as well as environmental effects in multiple ecological systems 

We use species distribution models to understand the abundance and distribution of organisms, and these models are typically built by fitting each species independently to a combination of abiotic environmental variables. However, species abundances and distributions are influenced by abiotic environmental preferences as well as biotic interactions such as interspecific competition and predation. Even more, most species surveys contain information on multiple species, information we are completely ignoring in single species models. By modeling species jointly, we can account for the influence of one species on the occurrence of another, in addition to environmental responses, thus allowing managers to more accurately model current species distributions and evaluate the effects of future environmental change on a more community-oriented level. I apply a joint modeling methodology across ecological realms and show that incorporating species dependencies improves predictions and captures more biological reality than single species approaches. Spatial predictions improve for Atlantic cod when utilizing the residual correlation of other functionally similar species such as Haddock in addition to the environment. Bottlenose dolphin density estimates reveal a tight coupling between this top predator and drumming prey, which is essential for predicting dolphin responses to ocean change. Joint modeling of Breeding Bird Survey data allows us to identify bird species at risk of nest parasitism by Brown-headed Cowbirds. Finally, jointly modeling mammal species in the Duke Forest helps management identify important relationships between higher trophic level species (Cayote, Bobcats, and Foxes) and their prey. 

Hosted by: Dr. Nye