ShipleyBelluauKuhnEtAl2017

Référence

Shipley, B., Belluau, M., Kuhn, I., Soudzilovskaia, N.A., Bahn, M., Penuelas, J., Kattge, J., Sack, L., Cavender-Bares, J., Ozinga, W.A., Blonder, B., van Bodegom, P.M., Manning, P., Hickler, T., Sosinski, E., Pillar, V.D.P., Onipchenko, V., Poschlod, P. (2017) Predicting habitat affinities of plant species using commonly measured functional traits. Journal of Vegetation Science, 28(5):1082-1095. (Scopus )

Résumé

Questions: Heinz Ellenberg classically defined “indicator”� scores for species representing their typical positions along gradients of key environmental variables, and these have proven very useful for designating ecological distributions. We tested a key tenent of trait-based ecology, i.e. the ability to predict ecological preferences from species’ traits. More specifically, can we predict Ellenberg indicator scores for soil nutrients, soil moisture and irradiance from four well-studied traits: leaf area, leaf dry matter content, specific leaf area (SLA) and seed mass? Can we use such relationships to estimate Ellenberg scores for species never classified by Ellenberg?. Location: Global. Methods: Cumulative link models were developed to predict Ellenberg nutrients, irradiance and moisture values from Ln-transformed trait values using 922, 981 and 988 species, respectively. We then independently tested these prediction equations using the trait values of 423 and 421 new species that occurred elsewere in Europe, North America and Morocco, and whose habitat affinities we could classify from independent sources as three-level ordinal ranks related to soil moisture and irradiance. The traits were SLA, leaf dry matter content, leaf area and seed mass. Results: The four functional traits predicted the Ellenberg indicator scores of site fertility, light and moisture with average error rates of <2 Ellenberg ranks out of nine. We then used the trait values of 423 and 421 species, respectively, that occurred (mostly) outside of Germany but whose habitat affinities we could classify as three-level ordinal ranks related to soil moisture and irradiance. The predicted positions of the new species, given the equations derived from the Ellenberg indices, agreed well with their independent habitat classifications, although our equation for Ellenberg irrandiance levels performed poorly on the lower ranks. Conclusions: These prediction equations, and their eventual extensions, could be used to provide approximate descriptions of habitat affinities of large numbers of species worldwide. © 2017 International Association for Vegetation Science

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@ARTICLE { ShipleyBelluauKuhnEtAl2017,
    AUTHOR = { Shipley, B. and Belluau, M. and Kuhn, I. and Soudzilovskaia, N.A. and Bahn, M. and Penuelas, J. and Kattge, J. and Sack, L. and Cavender-Bares, J. and Ozinga, W.A. and Blonder, B. and van Bodegom, P.M. and Manning, P. and Hickler, T. and Sosinski, E. and Pillar, V.D.P. and Onipchenko, V. and Poschlod, P. },
    TITLE = { Predicting habitat affinities of plant species using commonly measured functional traits },
    JOURNAL = { Journal of Vegetation Science },
    YEAR = { 2017 },
    VOLUME = { 28 },
    NUMBER = { 5 },
    PAGES = { 1082-1095 },
    NOTE = { cited By 0 },
    ABSTRACT = { Questions: Heinz Ellenberg classically defined “indicator”� scores for species representing their typical positions along gradients of key environmental variables, and these have proven very useful for designating ecological distributions. We tested a key tenent of trait-based ecology, i.e. the ability to predict ecological preferences from species’ traits. More specifically, can we predict Ellenberg indicator scores for soil nutrients, soil moisture and irradiance from four well-studied traits: leaf area, leaf dry matter content, specific leaf area (SLA) and seed mass? Can we use such relationships to estimate Ellenberg scores for species never classified by Ellenberg?. Location: Global. Methods: Cumulative link models were developed to predict Ellenberg nutrients, irradiance and moisture values from Ln-transformed trait values using 922, 981 and 988 species, respectively. We then independently tested these prediction equations using the trait values of 423 and 421 new species that occurred elsewere in Europe, North America and Morocco, and whose habitat affinities we could classify from independent sources as three-level ordinal ranks related to soil moisture and irradiance. The traits were SLA, leaf dry matter content, leaf area and seed mass. Results: The four functional traits predicted the Ellenberg indicator scores of site fertility, light and moisture with average error rates of <2 Ellenberg ranks out of nine. We then used the trait values of 423 and 421 species, respectively, that occurred (mostly) outside of Germany but whose habitat affinities we could classify as three-level ordinal ranks related to soil moisture and irradiance. The predicted positions of the new species, given the equations derived from the Ellenberg indices, agreed well with their independent habitat classifications, although our equation for Ellenberg irrandiance levels performed poorly on the lower ranks. Conclusions: These prediction equations, and their eventual extensions, could be used to provide approximate descriptions of habitat affinities of large numbers of species worldwide. © 2017 International Association for Vegetation Science },
    AFFILIATION = { Département de biologie, Université de Sherbrooke, Sherbrooke, QC, Canada; Department of Community Ecology, Helmholtz Centre for Environmental Research GmbH - UFZ, Theodor-Lieser-Str. 4, Halle, Germany; Conservation Biology Department, Institute of Environmental Sciences, CML, Leiden University, Einsteinweg 2, Leiden, Netherlands; Institute of Ecology, University of Innsbruck, Sternwartestr. 15, Innsbruck, Austria; CSIC, Global Ecology Unit CREAF-CSIC-UAB, Cerdanyola del Vallès (Catalonia), Spain; CREAF, Cerdanyola del Vallès, Barcelona, Catalonia, Spain; Max Planck Institute for Biogeochemistry, Hans Knöll Str. 10, Jena, Germany; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, Leipzig, Germany; Department of Ecology and Evolutionary Biology, University of California, Los Angeles, 621 Charles E. Young Drive South, Los Angeles, CA, United States; Department of Ecology, Evolution and Behavior, University of Minnesota, Saint Paul, MN, United States; Team Vegetation, Forest and Landscape Ecology, Alterra, Wageningen UR, PO Box 47, Wageningen, Netherlands; Environmental Change Institute, School of Geography and the Environment, University of Oxford, South Parks Road, Oxford, United Kingdom; Institute of Environmental Sciences, CML, Leiden University, Einsteinweg 2, Leiden, Netherlands; Senckenberg Gesellschaft für Naturforschung, Biodiversity and Climate Research Centre (BiK-F), Senckenberganlage 25, Frankfurt, Germany; Senckenberg Biodiversity and Climate Research Centre (BiK-F), Senckenberganlage 25, Frankfurt am Main, Germany; Department of Physical Geography, Geosciences, Goethe-University, Frankfurt am Main, Germany; Embrapa Clima Temperado, Pelotas, RS, Brazil; Department of Ecology, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil; Geobotany Department, Lomonosov Moscow State University, Moscow, Russian Federation; Institute of Plant Sciences, Faculty of Biology & Preclinical Medicine, University of Regensburg, Regensburg, Germany },
    AUTHOR_KEYWORDS = { Environmental gradients; Habitat affinities; Habitat fertility; Leaf dry matter content; Leaf size; Seed size; Shade; Soil moisture; Soil nutrients; Specific leaf area; Understorey plants; Wetlands },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1111/jvs.12554 },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-85023647440&doi=10.1111%2fjvs.12554&partnerID=40&md5=e8aaa7281deac81aeb598610fd3c68ed },
}

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