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      Distribution modelling of the Pudu deer (Pudu puda) in southern Chile

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      Nature Conservation

      Pensoft Publishers

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          Abstract

          The Pudu deer (Pudu puda) is endemic to the temperate rainforest of Chile and Argentina and currently faces serious conservation problems related to habitat loss. However, studies undertaken on this species are not sufficient to identify suitable areas for conservation purposes across its distribution range. In order to estimate the current and future distribution of the Pudu deer in southern Chile, we modelled the potential distribution of this species, based on occurrence points taken from seven contiguous provinces of this area using the Maxent modelling method. The Pudu deer distribution covered an estimated area of 17,912 km2 (24.1% of the area analysed), using a probability of occurrence above 0.529, according to the threshold that maximises the sum of sensitivity and specificity. In contrast to the Andes mountain range, areas with higher probabilities of occurrence were distributed mainly on the eastern and western slopes of the Coastal Mountain Range, where extensive coverage of native forest persists, as occurs in the provinces of Ranco, Osorno and Llanquihue. Projections to 2070, with global warming scenarios of 2.6 and 8.5 rcp, revealed that large areas will conserve their habitability, especially in the Coastal mountain range. Our results reveal that the Coastal mountain range has a high current and future habitability condition for the Pudu deer, a fact which may have conservation implications for this species.

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          Most cited references 36

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          An Overview of CMIP5 and the Experiment Design

          The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades and the future to year 2035. These “decadal predictions” are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, the limitations of the models and experiment design are described.
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            ORIGINAL ARTICLE: Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar

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              The Global 200: A Representation Approach to Conserving the Earth's Most Biologically Valuable Ecoregions

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                Author and article information

                Journal
                Nature Conservation
                NC
                Pensoft Publishers
                1314-3301
                1314-6947
                August 28 2020
                August 28 2020
                : 41
                : 47-69
                Article
                10.3897/natureconservation.41.53748
                © 2020

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