16
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      Spatial filtering to reduce sampling bias can improve the performance of ecological niche models

      , , ,
      Ecological Modelling
      Elsevier BV

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Related collections

          Most cited references18

          • Record: found
          • Abstract: not found
          • Article: not found

          ORIGINAL ARTICLE: Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Making better Maxentmodels of species distributions: complexity, overfitting and evaluation

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria.

              Maxent, one of the most commonly used methods for inferring species distributions and environmental tolerances from occurrence data, allows users to fit models of arbitrary complexity. Model complexity is typically constrained via a process known as L1 regularization, but at present little guidance is available for setting the appropriate level of regularization, and the effects of inappropriately complex or simple models are largely unknown. In this study, we demonstrate the use of information criterion approaches to setting regularization in Maxent, and we compare models selected using information criteria to models selected using other criteria that are common in the literature. We evaluate model performance using occurrence data generated from a known "true" initial Maxent model, using several different metrics for model quality and transferability. We demonstrate that models that are inappropriately complex or inappropriately simple show reduced ability to infer habitat quality, reduced ability to infer the relative importance of variables in constraining species' distributions, and reduced transferability to other time periods. We also demonstrate that information criteria may offer significant advantages over the methods commonly used in the literature.
                Bookmark

                Author and article information

                Journal
                Ecological Modelling
                Ecological Modelling
                Elsevier BV
                03043800
                March 2014
                March 2014
                : 275
                :
                : 73-77
                Article
                10.1016/j.ecolmodel.2013.12.012
                b4f57abd-254f-4a98-a36e-fd02592258f9
                © 2014

                Comments

                Comment on this article