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      <title>SSDM : an R package to predict distribution of species richness and composition based on stacked species distribution models</title>
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    <abstract>1. There is growing interest among conservationists in biodiversity mapping based on stacked species distribution models (SSDMs), a method that combines multiple individual species distribution models to produce a community-level model. However, no user-friendly interface specifically designed to provide the basic tools needed to fit such models was available until now. 2. The ssdm package is a computer platform implemented in r providing a range of methodological approaches and parameterisation at each step in building the SSDM: e.g. pseudo-absence selection, variable contribution and model accuracy assessment, inter-model consensus forecasting, species assembly design, and calculation of weighted endemism. 3. The object-oriented design of the package is such that: users can modify existing methods, extend the framework by implementing new methods, and share them to be reproduced by others. 4. The package includes a graphical user interface to extend the use of SSDMs to a wide range of conservation scientists and practitioners.</abstract>
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    <subject>
      <topic>bioinformatics</topic>
      <topic>community ecology</topic>
      <topic>conservation</topic>
      <topic>habitats</topic>
      <topic>modelling</topic>
      <topic>software</topic>
    </subject>
    <subject authority="local">
      <geographic>MONDE</geographic>
      <geographic>NOUVELLE CALEDONIE</geographic>
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    <classification authority="local">020</classification>
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      <titleInfo>
        <title>Methods in Ecology and Evolution</title>
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        <detail type="volume">
          <number>8</number>
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        <detail type="volume">
          <number>12</number>
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        <extent unit="pages">
          <list> 1795-1803</list>
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        <dateIssued>2017</dateIssued>
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      <identifier type="issn">2041-210X</identifier>
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    <identifier type="uri">https://www.documentation.ird.fr/hor/fdi:010071870</identifier>
    <identifier type="doi">10.1111/2041-210x.12841</identifier>
    <identifier type="issn">2041-210X</identifier>
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