Eger2017766

Référence

Eger, A.M., Curtis, J.M.R., Fortin, M.-J., Côté, I.M. and Guichard, F. (2017) Transferability and scalability of species distribution models: A test with sedentary marine invertebrates. Canadian Journal of Fisheries and Aquatic Sciences, 74(5):766-778. (Scopus )

Résumé

We found the predictive accuracy of species distribution models (SDMs) for sedentary marine invertebrates to be dependent on the methodology of their application. We explored three applications of SDMs: first a model tested at a scale smaller than at which it was trained (downscaled), second a model tested at scale larger than its training scale (upscaled), and third a model tested at the same scale but outside the extent for which it was trained (transferred). The accuracies of these models were compared with the “reference”? models that were trained and tested at the same scale and extent. We found that downscaled SDMs had higher predictive accuracy than reference SDMs. Transferred and upscaled models had lower predictive accuracy than their reference counterparts but still performed better than random, making them potentially acceptable alternatives where information is lacking for imminent decisions or in cost-restricted scenarios. Our results provide insights into the techniques available for researchers and managers developing SDMs at varying scales, with different species, and with different levels of initial information. © 2017, Canadian Science Publishing. All rights reserved.

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@ARTICLE { Eger2017766,
    AUTHOR = { Eger, A.M. and Curtis, J.M.R. and Fortin, M.-J. and Côté, I.M. and Guichard, F. },
    TITLE = { Transferability and scalability of species distribution models: A test with sedentary marine invertebrates },
    JOURNAL = { Canadian Journal of Fisheries and Aquatic Sciences },
    YEAR = { 2017 },
    VOLUME = { 74 },
    NUMBER = { 5 },
    PAGES = { 766-778 },
    NOTE = { cited By 0 },
    ABSTRACT = { We found the predictive accuracy of species distribution models (SDMs) for sedentary marine invertebrates to be dependent on the methodology of their application. We explored three applications of SDMs: first a model tested at a scale smaller than at which it was trained (downscaled), second a model tested at scale larger than its training scale (upscaled), and third a model tested at the same scale but outside the extent for which it was trained (transferred). The accuracies of these models were compared with the “reference”? models that were trained and tested at the same scale and extent. We found that downscaled SDMs had higher predictive accuracy than reference SDMs. Transferred and upscaled models had lower predictive accuracy than their reference counterparts but still performed better than random, making them potentially acceptable alternatives where information is lacking for imminent decisions or in cost-restricted scenarios. Our results provide insights into the techniques available for researchers and managers developing SDMs at varying scales, with different species, and with different levels of initial information. © 2017, Canadian Science Publishing. All rights reserved. },
    AFFILIATION = { Department of Biology, McGill University, Montreal, QC, Canada; Pacific Biological Station, Fisheries and Oceans Canada, 3190 Hammond Bay Road, Nanaimo, BC, Canada; Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada; Earth to Ocean Research Group, Department of Biological Sciences, Simon Fraser University, Burnaby, BC, Canada; Department of Biology, University of Victoria, Simon Fraser University, Victoria, BC, Canada },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1139/cjfas-2016-0129 },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021139804&doi=10.1139%2fcjfas-2016-0129&partnerID=40&md5=7d19a8e08656bf72dfc01906eaf40879 },
}

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