Final Report Summary - FORECOMM (FORECASTING COMMUNITY-LEVEL RESPONSES TO GLOBAL CHANGE)
Climatic change ranks amongst the greatest threats to biodiversity across the Earth’s biomes. This climatic change is accompanied by unprecedented anthropogenic impacts through habitat loss, overexploitation of natural resources, spread of invasive species and disease, which have reduced and homogenised biodiversity affecting ecosystem goods and services at regional and global scales. Predicting how natural communities will cope with anticipated changes is one of the greatest challenges for ecologists and has prompted them to develop predictive models that forecast changes in the geographic distribution of species, communities and phylogenetic diversity. Most predictive models, however, do not incorporate biotic interactions and thus are unlikely to be sufficiently equipped to make accurate ecological predictions of how natural communities will respond to climatic change. This is problematic because biotic interactions (e.g. predation, competition, resource-consumer interactions, host-parasite interactions, mutualism and facilitation) have been shown to affect large-scale distribution patterns of species and thus mediate their ability to cope with climatic change. The FORECOMM project aimed to will help address this gap by implementing a modelling framework to integrate existing data about climatic change, species distributions, community composition and biotic interactions to synthesize new understanding about how communities will respond to a changing world. This project contributed to the development of a conceptual framework to infer the backbone of biotic interaction networks within regional species pools which allowed to preliminary descriptions of food webs by integrating different sources of data. The predictive power of this framework was illustrate through the analysis of published food-web data. Further applications of this work resulted in a new study using functional traits as a proxy for trophic interactions. This resulted in a new collaboration to use a long-term dataset of lake communities in the Azorean Archipelago to test whether 1) individual species respond concordantly within trophic groups; 2) trophic groups respond concordantly to biogeographic and environmental gradients. This study revealed that spatial concordance in individual species distributions within trophic groups was always greater than expected by chance. Which has implications regarding the way modelling environmental change effects on biodiversity accounts for individualist responses to change. Collectively, this work supports the longstanding idea that communities might be modelled as a cohort if the functional resolution is appropriate. Future development of this work will aim to develop forecasts of community-level responses to environmental change.