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      Applying surrogate species presences to correct sample bias in species distribution models: a case study using the Pilbara population of the Northern Quoll

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      Nature Conservation

      Pensoft Publishers

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          Abstract

          The management of populations of threatened species requires the capacity to identify areas of high habitat value. We developed a high resolution species distribution model (SDM) for the endangered Pilbara northern quoll Dasyurus hallucatus, population using MaxEnt software and a combined suite of bioclimatic and landscape variables. Once common throughout much of northern Australia, this marsupial carnivore has recently declined throughout much of its former range and is listed as endangered by the IUCN. Other than the potential threats presented by climate change, and the invasive cane toad Rhinella marina (which has not yet arrived in the Pilbara). The Pilbara population is also impacted by introduced predators, pastoral and mining activities. To account for sample bias resulting from targeted surveys unevenly spread through the region, a pseudo-absence bias layer was developed from presence records of other critical weight-range non-volant mammals. The resulting model was then tested using the biomod2 package which produces ensemble models from individual models created with different algorithms. This ensemble model supported the distribution determined by the bias compensated MaxEnt model with a covariance of of 86% between models with both models largely identifying the same areas as high priority habitat. The primary product of this exercise is a high resolution SDM which corroborates and elaborates on our understanding of the ecology and habitat preferences of the Pilbara Northern Quoll population thereby improving our capacity to manage this population in the face of future threats.

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          Most cited references 26

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          Selecting pseudo-absences for species distribution models: how, where and how many?

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

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              Is my species distribution model fit for purpose? Matching data and models to applications

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                Author and article information

                Journal
                Nature Conservation
                NC
                Pensoft Publishers
                1314-3301
                1314-6947
                May 09 2017
                May 09 2017
                : 18
                : 25-46
                Article
                10.3897/natureconservation.18.12235
                © 2017

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