Global change community ecology beyond species-sorting: a quantitative framework based on mediterranean-biome examples

Abstract

Aim: Species-sorting predicts the influences of the environment on ecosystem composition across heterogeneous landscapes. It assumes that extinction and adaptation are negligible at ecological scales. Meanwhile, shifts associated with global change have been observed in metacommunity composition (species pools affected by extinctions and introductions) and in phenotypes. This suggests that predictions of future composition must move beyond re-sorting present-day species with fixed traits. We extend plant species-sorting concepts to consider biogeography and demography. We give an empirical context, highlighting the influences of biogeography, species-sorting and adaptation on community composition. Location: Global; case studies focus on the terrestrial mediterranean biome. Methods: We review case studies of empirical approaches that have examined community composition at various scales. We develop a mathematical model based on community mechanics that incorporates species-sorting with shifting phenotypes and species pools. Results: As illustrated by real examples, community composition is influenced by factors such as history, modern extinction risk, species-sorting, biotic interactions, adaptation and ecological drift. There is ample evidence that species pools and phenotypes are not constant at ecological scales in the context of global change. Any implicit assumption in community analysis that they are constant should therefore be revisited. Our model breaks down shifting community constraints into intraspecific components – including genotype sorting, selection and plasticity – and interspecific components, including changes in relative abundance and species replacement from a shifting metacommunity. Main conclusions: Predictions of community composition could benefit from extending species-sorting, to allow species pools and species traits to shift through time, as dealt with explicitly in our framework. The model predicts that responses to a shifting community constraint can be more diverse than deterministic species re-sorting. Consequently, the rate of species replacement depends on factors such as species adaptive capacity, competition, physical disturbance and habitat fragmentation.