Emergent copepod communities in an adaptive trait-structured model

Population dynamics for the most dominant copepod species have to some degree a mechanistic underpinning grounded in theory. However, important ecosystem shifts involve whole communities of species. Algorithms adopted from evolutionary computation provide one avenue for understanding community-level properties. We developed a pelagic copepod community model based on ecological tradeoffs in trait space, with a focus on development and growth rates, which determine fundamental properties such as size and generation length. The model is generalized to represent a broad range of possible copepod taxa. We used this framework in an adaptive-computing context to examine the different communities that assemble under different temperature and food regimes across a latitudinal gradient. Emergent communities resembled observed communities in structure and biodiversity, and showed life history strategies with clear analogs to real species.