Broennimann2012481

Référence

Broennimann, O., Fitzpatrick, M.C., Pearman, P.B., Petitpierre, B., Pellissier, L., Yoccoz, N.G., Thuiller, W., Fortin, M.-J., Randin, C., Zimmermann, N.E., Graham, C.H. and Guisan, A. (2012) Measuring ecological niche overlap from occurrence and spatial environmental data. Global Ecology and Biogeography, 21(4):481-497. (Scopus )

Résumé

Aim Concerns over how global change will influence species distributions, in conjunction with increased emphasis on understanding niche dynamics in evolutionary and community contexts, highlight the growing need for robust methods to quantify niche differences between or within taxa. We propose a statistical framework to describe and compare environmental niches from occurrence and spatial environmental data. Location Europe, North America and South America. Methods The framework applies kernel smoothers to densities of species occurrence in gridded environmental space to calculate metrics of niche overlap and test hypotheses regarding niche conservatism. We use this framework and simulated species with pre-defined distributions and amounts of niche overlap to evaluate several ordination and species distribution modelling techniques for quantifying niche overlap. We illustrate the approach with data on two well-studied invasive species. Results We show that niche overlap can be accurately detected with the framework when variables driving the distributions are known. The method is robust to known and previously undocumented biases related to the dependence of species occurrences on the frequency of environmental conditions that occur across geographical space. The use of a kernel smoother makes the process of moving from geographical space to multivariate environmental space independent of both sampling effort and arbitrary choice of resolution in environmental space. However, the use of ordination and species distribution model techniques for selecting, combining and weighting variables on which niche overlap is calculated provide contrasting results. Main conclusions The framework meets the increasing need for robust methods to quantify niche differences. It is appropriate for studying niche differences between species, subspecies or intra-specific lineages that differ in their geographical distributions. Alternatively, it can be used to measure the degree to which the environmental niche of a species or intra-specific lineage has changed over time. © 2011 Blackwell Publishing Ltd.

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@ARTICLE { Broennimann2012481,
    AUTHOR = { Broennimann, O. and Fitzpatrick, M.C. and Pearman, P.B. and Petitpierre, B. and Pellissier, L. and Yoccoz, N.G. and Thuiller, W. and Fortin, M.-J. and Randin, C. and Zimmermann, N.E. and Graham, C.H. and Guisan, A. },
    TITLE = { Measuring ecological niche overlap from occurrence and spatial environmental data },
    JOURNAL = { Global Ecology and Biogeography },
    YEAR = { 2012 },
    VOLUME = { 21 },
    NUMBER = { 4 },
    PAGES = { 481-497 },
    NOTE = { cited By 256 },
    ABSTRACT = { Aim Concerns over how global change will influence species distributions, in conjunction with increased emphasis on understanding niche dynamics in evolutionary and community contexts, highlight the growing need for robust methods to quantify niche differences between or within taxa. We propose a statistical framework to describe and compare environmental niches from occurrence and spatial environmental data. Location Europe, North America and South America. Methods The framework applies kernel smoothers to densities of species occurrence in gridded environmental space to calculate metrics of niche overlap and test hypotheses regarding niche conservatism. We use this framework and simulated species with pre-defined distributions and amounts of niche overlap to evaluate several ordination and species distribution modelling techniques for quantifying niche overlap. We illustrate the approach with data on two well-studied invasive species. Results We show that niche overlap can be accurately detected with the framework when variables driving the distributions are known. The method is robust to known and previously undocumented biases related to the dependence of species occurrences on the frequency of environmental conditions that occur across geographical space. The use of a kernel smoother makes the process of moving from geographical space to multivariate environmental space independent of both sampling effort and arbitrary choice of resolution in environmental space. However, the use of ordination and species distribution model techniques for selecting, combining and weighting variables on which niche overlap is calculated provide contrasting results. Main conclusions The framework meets the increasing need for robust methods to quantify niche differences. It is appropriate for studying niche differences between species, subspecies or intra-specific lineages that differ in their geographical distributions. Alternatively, it can be used to measure the degree to which the environmental niche of a species or intra-specific lineage has changed over time. © 2011 Blackwell Publishing Ltd. },
    AFFILIATION = { Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland; University of Maryland Center for Environmental Science, Appalachian Lab., Frostburg, MD 21532, United States; Swiss Federal Research Institute WSL, 8903 Birmensdorf, Switzerland; Department of Arctic and Marine Biology, University of Tromsø, 9037 Tromsø, Norway; Laboratoire d'Ecologie Alpine, University Joseph Fourier, 38041 Grenoble, France; Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, M5S 1A1, Canada; Institute of Botany, University of Basel, 4056 Basel, Switzerland; Department of Ecology and Evolution, SUNY, Stony Brook, NY 11794, United States },
    AUTHOR_KEYWORDS = { Centaurea stoebe; Ecological niche model; Kernel density; Niche conservatism; Niche equivalency; Niche similarity; Ordination; Solenopsis invicta; Species distribution model; Virtual species },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1111/j.1466-8238.2011.00698.x },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-84858073352&doi=10.1111%2fj.1466-8238.2011.00698.x&partnerID=40&md5=9c3d60fbaa0816dc85b0765a419738cb },
}

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