Staniczenko, PPA;
Sivasubramaniam, P;
Suttle, KB;
Pearson, RG;
(2017)
Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks.
Ecology Letters
, 20
(6)
pp. 693-707.
10.1111/ele.12770.
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Abstract
Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub-disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species' presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change.
Type: | Article |
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Title: | Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks |
Location: | England |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1111/ele.12770 |
Publisher version: | http://doi.org/10.1111/ele.12770 |
Language: | English |
Additional information: | Copyright © 2017 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.This is an open access article under the terms of the Creative Commons Attribution License, which permits use,distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Bayesian networks, biotic interactions, climate change, community ecology, geographical range,networks, species distribution models. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/1555833 |
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