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Predicting future coexistence in a N orth A merican ant community
Author(s) -
Bewick Sharon,
Stuble Katharine L.,
Lessard JeanPhillipe,
Dunn Robert R.,
Adler Frederick R.,
Sanders Nathan J.
Publication year - 2014
Publication title -
ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.17
H-Index - 63
ISSN - 2045-7758
DOI - 10.1002/ece3.1048
Subject(s) - climate change , ecology , abiotic component , niche , context (archaeology) , ecological niche , interspecific competition , global warming , community , phenology , biology , ecosystem , habitat , paleontology
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 N orth A merica. 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.

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