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      Climatic Associations of British Species Distributions Show Good Transferability in Time but Low Predictive Accuracy for Range Change

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          Abstract

          Conservation planners often wish to predict how species distributions will change in response to environmental changes. Species distribution models (SDMs) are the primary tool for making such predictions. Many methods are widely used; however, they all make simplifying assumptions, and predictions can therefore be subject to high uncertainty. With global change well underway, field records of observed range shifts are increasingly being used for testing SDM transferability. We used an unprecedented distribution dataset documenting recent range changes of British vascular plants, birds, and butterflies to test whether correlative SDMs based on climate change provide useful approximations of potential distribution shifts. We modelled past species distributions from climate using nine single techniques and a consensus approach, and projected the geographical extent of these models to a more recent time period based on climate change; we then compared model predictions with recent observed distributions in order to estimate the temporal transferability and prediction accuracy of our models. We also evaluated the relative effect of methodological and taxonomic variation on the performance of SDMs. Models showed good transferability in time when assessed using widespread metrics of accuracy. However, models had low accuracy to predict where occupancy status changed between time periods, especially for declining species. Model performance varied greatly among species within major taxa, but there was also considerable variation among modelling frameworks. Past climatic associations of British species distributions retain a high explanatory power when transferred to recent time – due to their accuracy to predict large areas retained by species – but fail to capture relevant predictors of change. We strongly emphasize the need for caution when using SDMs to predict shifts in species distributions: high explanatory power on temporally-independent records – as assessed using widespread metrics – need not indicate a model’s ability to predict the future.

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          Most cited references53

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          Measuring the accuracy of diagnostic systems.

          J Swets (1988)
          Diagnostic systems of several kinds are used to distinguish between two classes of events, essentially "signals" and "noise". For them, analysis in terms of the "relative operating characteristic" of signal detection theory provides a precise and valid measure of diagnostic accuracy. It is the only measure available that is uninfluenced by decision biases and prior probabilities, and it places the performances of diverse systems on a common, easily interpreted scale. Representative values of this measure are reported here for systems in medical imaging, materials testing, weather forecasting, information retrieval, polygraph lie detection, and aptitude testing. Though the measure itself is sound, the values obtained from tests of diagnostic systems often require qualification because the test data on which they are based are of unsure quality. A common set of problems in testing is faced in all fields. How well these problems are handled, or can be handled in a given field, determines the degree of confidence that can be placed in a measured value of accuracy. Some fields fare much better than others.
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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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              Rapid responses of British butterflies to opposing forces of climate and habitat change.

              Habitat degradation and climate change are thought to be altering the distributions and abundances of animals and plants throughout the world, but their combined impacts have not been assessed for any species assemblage. Here we evaluated changes in the distribution sizes and abundances of 46 species of butterflies that approach their northern climatic range margins in Britain-where changes in climate and habitat are opposing forces. These insects might be expected to have responded positively to climate warming over the past 30 years, yet three-quarters of them declined: negative responses to habitat loss have outweighed positive responses to climate warming. Half of the species that were mobile and habitat generalists increased their distribution sites over this period (consistent with a climate explanation), whereas the other generalists and 89% of the habitat specialists declined in distribution size (consistent with habitat limitation). Changes in population abundances closely matched changes in distributions. The dual forces of habitat modification and climate change are likely to cause specialists to decline, leaving biological communities with reduced numbers of species and dominated by mobile and widespread habitat generalists.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                5 July 2012
                : 7
                : 7
                : e40212
                Affiliations
                [1 ]Division of Ecology and Evolution, Imperial College London, Ascot, Berkshire, United Kingdom
                [2 ]Biological Records Centre, Centre for Ecology and Hydrology, Wallingford, Oxfordshire, United Kingdom
                [3 ]Grantham Institute for Climate Change, Imperial College London, London, United Kingdom
                [4 ]British Trust for Ornithology, Thetford, Norfolk, United Kingdom
                [5 ]Butterfly Conservation, Wareham, Dorset, United Kingdom
                [6 ]Botanical Society of the British Isles, Harrogate, North Yorkshire, United Kingdom
                University of Western Australia, Australia
                Author notes

                Conceived and designed the experiments: GR DR AP. Analyzed the data: GR. Wrote the paper: GR. Provided data for analysis: SG RF KW.

                Article
                PONE-D-12-07415
                10.1371/journal.pone.0040212
                3390350
                22792243
                777d6e15-5e74-490d-bf94-b8cf971abb8b
                Rapacciuolo et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 12 March 2012
                : 4 June 2012
                Page count
                Pages: 11
                Categories
                Research Article
                Biology
                Ecology
                Community Ecology
                Ecological Risk
                Niche Construction
                Ecological Environments
                Terrestrial Environments
                Ecological Metrics
                Extinction Risk
                Species Diversity
                Species Richness
                Ecosystems
                Ecosystem Modeling
                Plant Ecology
                Plant-Environment Interactions
                Biodiversity
                Biogeography
                Conservation Science
                Global Change Ecology
                Macroecology
                Population Ecology
                Spatial and Landscape Ecology
                Species Extinction

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                Uncategorized

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