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Negative Biotic Interactions Drive Predictions of Distributions for Species From a Grassland Community

Staniczenko, P; Suttle, B; Pearson, RG; (2018) Negative Biotic Interactions Drive Predictions of Distributions for Species From a Grassland Community. Biology Letters , 14 (11) , Article 20180426. 10.1098/rsbl.2018.0426. Green open access

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Abstract

Understanding the factors that determine species’ geographic distributions is important for addressing a wide range of biological questions, including where species will be able to maintain populations following environmental change. New methods for modelling species distributions include the effects of biotic interactions alongside more commonly used abiotic variables such as temperature and precipitation; however, it is not clear which types of interspecific relationship contribute to shaping species distributions and should therefore be prioritised in models. Even if some interactions are known to be influential at local spatial scales, there is no guarantee they will have similar impacts at macroecological scales. Here we apply a novel method based on information theory to determine which types of interspecific relationship drive species distributions. Our results show that negative biotic interactions such as competition have the greatest effect on model predictions for species from a California grassland community. This knowledge will help focus data collection and improve model predictions for identifying at-risk species. Furthermore, our methodological approach is applicable to any kind of species distribution model that can be specified with and without interspecific relationships.

Type: Article
Title: Negative Biotic Interactions Drive Predictions of Distributions for Species From a Grassland Community
Open access status: An open access version is available from UCL Discovery
DOI: 10.1098/rsbl.2018.0426
Publisher version: https://doi.org/10.1098/rsbl.2018.0426
Language: English
Additional information: © 2018 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
Keywords: Species geographic ranges, species distribution models, biotic interactions, model selection, normalized maximum likelihood, minimum description length principle
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.ucl.ac.uk/id/eprint/10059772
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