Interactions between ecological, evolutionary and environmental processes unveil complex dynamics of insular plant diversity

Abstract

Aims Understanding how biodiversity emerges and how it varies in space and time requires integration of the underlying processes that affect biodiversity at different levels of ecological organization. We present BioGEEM (BioGeographical Eco-Evolutionary Model), a spatially explicit model that integrates theories and processes understood to drive biodiversity dynamics. We investigated the necessary degree of mechanistic complexity by exploring simulation experiments to evaluate the relative roles of the underlying processes across spatio-temporal scales and ecological levels (e.g. populations, species, communities). Location Hypothetical oceanic islands. Methods BioGEEM is stochastic and grid-based, and it integrates ecological (metabolic constraints, demography, dispersal and competition), evolutionary (mutation and speciation) and environmental (geo-climatic dynamics) processes. Plants on oceanic islands served as a model system. We ran the simulations both with all processes on and with selected processes switched off to assess the role of each process from the emergent patterns. Results The full model was able to generate patterns matching empirical evidence and theoretical expectations. Population sizes were largest on young islands, and species, particularly endemics, better filled their potential range on young and old islands due to limited area and reduced competition. Richness peaked at mid-elevations. The proportion of endemics was highest in old, large and isolated environments within the islands. Species and trait richness showed unimodal temporal trends. Switching off selected processes led to several unrealistic patterns, including the evolution of super-dominant species, extremely high richness and weakened spatial diversity gradients. Main conclusions The main predictions derived from BioGEEM are: Competition has cross-scale effects on diversity. Hump-shaped temporal dynamics can be obtained without speciation. Endemic species seem less susceptible to extinction than native non-endemic species. Endemism reflects stronger geographical and environmental isolation. Finally, only the integration of all implemented processes generates realistic spatio-temporal dynamics at population, species, community and assemblage levels.