A novel framework for modeling the evolution of cross-scale ecological assembly

Community assembly can be driven by species responses to environmental gradients, and interactions within (e.g., competition) and across (e.g., herbivory) clades. These ecological dynamics are mediated by species traits, which are in turn shaped by past evolution. As such, identifying the drivers of species assembly is made difficult by the differing temporal and spatial scales of ecological and evolutionary dynamics. Two recent advances have emerged to address the cross-scale challenge of modeling species assembly: phylogenetic generalized linear mixed modeling (PGLMM) and earth observation networks (EONs). PGLMM integrates through time by modeling the evolution of trait-based community assembly, while EONs synthesize across space by placing standardized site-level species occurrence data within their regional context. Here we describe a framework for combining these tools to investigate the drivers of species assembly, and so address three outstanding questions: (1) Does evolution adapt or constrain regional-scale environmental responses? (2) Do evolved responses to past competition minimize or enhance present-day competition? (3) Are species cross-clade associations evolutionarily constrained? We provide a conceptual overview of how PGLMM and EONs can be synthesized to answer these questions, and provide exemplar Bayesian PGLMM code. Finally, we describe the capacity of these tools to aid in conservation and natural resource management, including predicting future colonization by rare and invasive species, vulnerable mutualisms, and pest and pathogen outbreaks.