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A method to detect sub-communities from multivariate spatial associations

Flugge, AJ; Olhede, SC; Murrell, DJ; (2014) A method to detect sub-communities from multivariate spatial associations. Methods in Ecology and Evolution , 5 (11) pp. 1214-1224. 10.1111/2041-210X.12295. Green open access

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Abstract

1.Species are seldom distributed randomly across a community, but instead show spatial structure that is determined by environmental gradients and/or biotic interactions. Analysis of the spatial co-associations of species may therefore reveal information on the processes that helped to shape those patterns. 2.We propose a multivariate approach that uses the spatial co-associations between all pairs of species to find sub-communities of species whose distribution in the study area are positively correlated. Our method, which begins with the patterns of individuals, is particularly well-suited for communities with large numbers of species, and gives rare species an equal weight. We propose a method to quantify a maximum number of sub-communities that are significantly more correlated than expected under a null model of independence. 3.Using data on the distribution of tree and shrub species from a 50 ha forest plot on Barro Colorado Island (BCI), Panama, we show that our method can be used to construct biologically meaningful sub-communities that are linked to the spatial structure of the plant community. As an example, we construct spatial maps from the sub-communities that closely follow habitats based on environmental gradients (such as slope) as well as different biotic conditions (such as canopy gaps). 4.We discuss extensions and adaptations to our method that might be appropriate for other types of spatially referenced data and for other ecological communities. We make suggestions for other ways to interpret the sub-communities using phylogenetic relationships, biological traits, and environmental variables as covariates, and note that sub-communities that are hard to interpret may suggest groups of species and/or regions of the landscape that warrant further attention.

Type: Article
Title: A method to detect sub-communities from multivariate spatial associations
Open access status: An open access version is available from UCL Discovery
DOI: 10.1111/2041-210X.12295
Publisher version: http://dx.doi.org/10.1111/2041-210X.12295
Language: English
Additional information: © 2014 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. 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: Barro Colorado Island (BCI), community ecology, spatial pattern, niche theory, neutral theory, clustering, point process
UCL classification: UCL > Provost and Vice Provost Offices
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
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: http://discovery.ucl.ac.uk/id/eprint/1455993
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