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      Differences between microhabitat and broad-scale patterns of niche evolution in terrestrial salamanders

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          Abstract

          The extent to which closely related species share similar niches remains highly debated. Ecological niches are increasingly analysed by combining distribution records with broad-scale climatic variables, but interactions between species and their environment often occur at fine scales. The idea that macroscale analyses correctly represent fine-scale processes relies on the assumption that average climatic variables are meaningful predictors of processes determining species persistence, but tests of this hypothesis are scarce. We compared broad- and fine-scale (microhabitat) approaches by analyzing the niches of European plethodontid salamanders. Both the microhabitat and the macroecological approaches identified niche differences among species, but the correspondence between micro- and macroecological niches was weak. When exploring niche evolution, the macroecological approach suggested a close relationship between niche and phylogenetic history, but this relationship did not emerge in fine-scale analyses. The apparent pattern of niche evolution emerging in broad-scale analyses likely was the by-product of related species having closely adjacent ranges. The environment actually experienced by most of animals is more heterogeneous than what is apparent from macro-scale predictors, and a better combination between macroecological and fine-grained data may be a key to obtain robust ecological generalizations.

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          Phylogenetic niche conservatism, phylogenetic signal and the relationship between phylogenetic relatedness and ecological similarity among species.

          Ecologists are increasingly adopting an evolutionary perspective, and in recent years, the idea that closely related species are ecologically similar has become widespread. In this regard, phylogenetic signal must be distinguished from phylogenetic niche conservatism. Phylogenetic niche conservatism results when closely related species are more ecologically similar that would be expected based on their phylogenetic relationships; its occurrence suggests that some process is constraining divergence among closely related species. In contrast, phylogenetic signal refers to the situation in which ecological similarity between species is related to phylogenetic relatedness; this is the expected outcome of Brownian motion divergence and thus is necessary, but not sufficient, evidence for the existence of phylogenetic niche conservatism. Although many workers consider phylogenetic niche conservatism to be common, a review of case studies indicates that ecological and phylogenetic similarities often are not related. Consequently, ecologists should not assume that phylogenetic niche conservatism exists, but rather should empirically examine the extent to which it occurs.
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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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              Microclimatic challenges in global change biology.

              Despite decades of work on climate change biology, the scientific community remains uncertain about where and when most species distributions will respond to altered climates. A major barrier is the spatial mismatch between the size of organisms and the scale at which climate data are collected and modeled. Using a meta-analysis of published literature, we show that grid lengths in species distribution models are, on average, ca. 10 000-fold larger than the animals they study, and ca. 1000-fold larger than the plants they study. And the gap is even worse than these ratios indicate, as most work has focused on organisms that are significantly biased toward large size. This mismatch is problematic because organisms do not experience climate on coarse scales. Rather, they live in microclimates, which can be highly heterogeneous and strongly divergent from surrounding macroclimates. Bridging the spatial gap should be a high priority for research and will require gathering climate data at finer scales, developing better methods for downscaling environmental data to microclimates, and improving our statistical understanding of variation at finer scales. Interdisciplinary collaborations (including ecologists, engineers, climatologists, meteorologists, statisticians, and geographers) will be key to bridging the gap, and ultimately to providing scientifically grounded data and recommendations to conservation biologists and policy makers. © 2013 John Wiley & Sons Ltd.
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                Author and article information

                Contributors
                francesco.ficetola@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                12 July 2018
                12 July 2018
                2018
                : 8
                : 10575
                Affiliations
                [1 ]ISNI 0000 0004 0609 8934, GRID grid.462909.0, University Grenoble Alpes, Laboratoire d’Écologie Alpine (LECA), ; F-38000 Grenoble, France
                [2 ]ISNI 0000 0004 0609 8934, GRID grid.462909.0, CNRS, Laboratoire d’Écologie Alpine (LECA), ; F-38000 Grenoble, France
                [3 ]ISNI 0000 0001 2174 1754, GRID grid.7563.7, Department of Earth and Environmental Sciences, , Università degli Studi di Milano-Bicocca, ; Piazza della Scienza 1, 20126 Milano, Italy
                [4 ]ISNI 0000 0004 1757 2822, GRID grid.4708.b, Department of Environmental Science and Policy, , Università degli Studi di Milano, ; Via Celoria 26, 20133 Milano, Italy
                [5 ]ISNI 0000 0001 2289 1527, GRID grid.12391.38, Universität Trier Fachbereich VI, Campus I, Gebäude N Universitätsring 15, ; 54286 Trier, Germany
                [6 ]Natural Oasis, Via di Galceti 141, 59100 Prato, Italy
                [7 ]ISNI 0000 0004 1757 2304, GRID grid.8404.8, Natural History Museum of the University of Florence, Section of Zoology “La Specola”, ; Via Romana 17, 50125 Firenze, Italy
                Author information
                http://orcid.org/0000-0003-3414-5155
                http://orcid.org/0000-0002-4228-2750
                Article
                28796
                10.1038/s41598-018-28796-x
                6043550
                30002477
                90d4dac6-bd6a-4a65-9228-a941b37bd268
                © 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/.

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                : 29 December 2017
                : 25 June 2018
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