Predicting future coexistence in a North American ant community |
| |
Authors: | Sharon Bewick Katharine L. Stuble Jean‐Phillipe Lessard Robert R. Dunn Frederick R. Adler Nathan J. Sanders |
| |
Affiliation: | 1. Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, Tennessee;2. National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, Tennessee;3. Center for Macroecology, Evolution and Climate, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark;4. Quebec Centre for Biodiversity Science, Department of Biology, McGill University, Montreal, Quebec, Canada;5. Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina;6. Department of Mathematics, University of Utah, Salt Lake City, Utah;7. Department of Biology, University of Utah, Salt Lake City, Utah |
| |
Abstract: | Global climate change will remodel ecological communities worldwide. However, as a consequence of biotic interactions, communities may respond to climate change in idiosyncratic ways. This makes predictive models that incorporate biotic interactions necessary. We show how such models can be constructed based on empirical studies in combination with predictions or assumptions regarding the abiotic consequences of climate change. Specifically, we consider a well‐studied ant community in North America. First, we use historical data to parameterize a basic model for species coexistence. Using this model, we determine the importance of various factors, including thermal niches, food discovery rates, and food removal rates, to historical species coexistence. We then extend the model to predict how the community will restructure in response to several climate‐related changes, such as increased temperature, shifts in species phenology, and altered resource availability. Interestingly, our mechanistic model suggests that increased temperature and shifts in species phenology can have contrasting effects. Nevertheless, for almost all scenarios considered, we find that the most subordinate ant species suffers most as a result of climate change. More generally, our analysis shows that community composition can respond to climate warming in nonintuitive ways. For example, in the context of a community, it is not necessarily the most heat‐sensitive species that are most at risk. Our results demonstrate how models that account for niche partitioning and interspecific trade‐offs among species can be used to predict the likely idiosyncratic responses of local communities to climate change. |
| |
Keywords: | Ant communities climate change differential equations mechanistic models species interactions |
|
|