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      Environmental suitability models predict population density, performance and body condition for microendemic salamanders

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          Abstract

          Species can show strong variation of local abundance across their ranges. Recent analyses suggested that variation in abundance can be related to environmental suitability, as the highest abundances are often observed in populations living in the most suitable areas. However, there is limited information on the mechanisms through which variation in environmental suitability determines abundance. We analysed populations of the microendemic salamander Hydromantes flavus, and tested several hypotheses on potential relationships linking environmental suitability to population parameters. For multiple populations across the whole species range, we assessed suitability using species distribution models, and measured density, activity level, food intake and body condition index. In high-suitability sites, the density of salamanders was up to 30-times higher than in the least suitable ones. Variation in activity levels and population performance can explain such variation of abundance. In high-suitability sites, salamanders were active close to the surface, and showed a low frequency of empty stomachs. Furthermore, when taking into account seasonal variation, body condition was better in the most suitable sites. Our results show that the strong relationship between environmental suitability and population abundance can be mediated by the variation of parameters strongly linked to individual performance and fitness.

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          unmarked: AnRPackage for Fitting Hierarchical Models of Wildlife Occurrence and Abundance

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            Niches and distributional areas: concepts, methods, and assumptions.

            Estimating actual and potential areas of distribution of species via ecological niche modeling has become a very active field of research, yet important conceptual issues in this field remain confused. We argue that conceptual clarity is enhanced by adopting restricted definitions of "niche" that enable operational definitions of basic concepts like fundamental, potential, and realized niches and potential and actual distributional areas. We apply these definitions to the question of niche conservatism, addressing what it is that is conserved and showing with a quantitative example how niche change can be measured. In this example, we display the extremely irregular structure of niche space, arguing that it is an important factor in understanding niche evolution. Many cases of apparently successful models of distributions ignore biotic factors: we suggest explanations to account for this paradox. Finally, relating the probability of observing a species to ecological factors, we address the issue of what objects are actually calculated by different niche modeling algorithms and stress the fact that methods that use only presence data calculate very different quantities than methods that use absence data. We conclude that the results of niche modeling exercises can be interpreted much better if the ecological and mathematical assumptions of the modeling process are made explicit.
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              An approximate distribution of estimates of variance components.

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                Author and article information

                Contributors
                enrico.arti@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                14 May 2018
                14 May 2018
                2018
                : 8
                : 7527
                Affiliations
                [1 ]ISNI 0000 0001 2289 1527, GRID grid.12391.38, Biogeographie, , Universität Trier Fachbereich VI, Raum- und Umweltwissenschaften, ; Trier, Germany
                [2 ]Museo di Storia Naturale dell’Università degli Studi di Firenze, Sezione di Zoologia “La Specola”, Firenze, Italy
                [3 ]Natural Oasis, Prato, Italy
                [4 ]ISNI 0000 0004 1757 2822, GRID grid.4708.b, Department of Environmental Science and Policy, , Università degli Studi di Milano, ; Milano, Italy
                [5 ]Speleo Club Nuoro, Nuoro, Italy
                [6 ]ISNI 0000 0004 0609 8934, GRID grid.462909.0, University Grenoble Alpes, CNRS, , Laboratoire d’Écologie Alpine (LECA), ; F-38000 Grenoble, France
                Author information
                http://orcid.org/0000-0002-4228-2750
                http://orcid.org/0000-0001-6071-8194
                http://orcid.org/0000-0003-3414-5155
                Article
                25704
                10.1038/s41598-018-25704-1
                5951833
                29760473
                441fe28c-5321-4d33-abac-8c15118a758b
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 12 December 2017
                : 25 April 2018
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