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      Where to Dig for Fossils: Combining Climate-Envelope, Taphonomy and Discovery Models

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          Abstract

          Fossils represent invaluable data to reconstruct the past history of life, yet fossil-rich sites are often rare and difficult to find. The traditional fossil-hunting approach focuses on small areas and has not yet taken advantage of modelling techniques commonly used in ecology to account for an organism’s past distributions. We propose a new method to assist finding fossils at continental scales based on modelling the past distribution of species, the geological suitability of fossil preservation and the likelihood of fossil discovery in the field, and apply it to several genera of Australian megafauna that went extinct in the Late Quaternary. Our models predicted higher fossil potentials for independent sites than for randomly selected locations (mean Kolmogorov-Smirnov statistic = 0.66). We demonstrate the utility of accounting for the distribution history of fossil taxa when trying to find the most suitable areas to look for fossils. For some genera, the probability of finding fossils based on simple climate-envelope models was higher than the probability based on models incorporating current conditions associated with fossil preservation and discovery as predictors. However, combining the outputs from climate-envelope, preservation, and discovery models resulted in the most accurate predictions of potential fossil sites at a continental scale. We proposed potential areas to discover new fossils of Diprotodon, Zygomaturus, Protemnodon, Thylacoleo, and Genyornis, and provide guidelines on how to apply our approach to assist fossil hunting in other continents and geological settings.

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          Most cited references30

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          Spatial prediction of species distribution: an interface between ecological theory and statistical modelling

          M.P Austin (2002)
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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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              The importance of biotic interactions for modelling species distributions under climate change

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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, CA USA )
                1932-6203
                30 March 2016
                2016
                : 11
                : 3
                : e0151090
                Affiliations
                [1 ]The Environment Institute and School of Biological Sciences, The University of Adelaide, Adelaide, South Australia, Australia
                [2 ]Institute for Ecosystem Research, Kiel University, Kiel, Schleswig-Holstein, Germany
                Penn State University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: SB FS MRR CJAB. Performed the experiments: SB. Analyzed the data: SB FS. Contributed reagents/materials/analysis tools: MRR CJAB. Wrote the paper: SB FS MRR DAF IU CJAB.

                [¤]

                Current address: Department of BioSciences, College of Science, Swansea University, Swansea, United Kingdom

                Article
                PONE-D-16-02102
                10.1371/journal.pone.0151090
                4814095
                27027874
                ae752a58-b372-4c1b-aa6d-10f7371c8ebe
                © 2016 Block 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
                : 16 January 2016
                : 23 February 2016
                Page count
                Figures: 4, Tables: 2, Pages: 16
                Funding
                SB was financially supported by the European Commission through the program Erasmus Mundus Master Course—International Master in Applied Ecology (EMMC-IMAE) (FPA 2023-0224 / 532524-1-FR-2012-1-ERA MUNDUS-EMMC; http://eacea.ec.europa.eu/erasmus_mundus/). The Australian Research Council (ARC; http://www.arc.gov.au/) supported FS, MRR (DP130103842) and CJAB & DAF (FT110100306 and FT140101192, respectively).
                Categories
                Research Article
                Biology and Life Sciences
                Paleontology
                Fossils
                Earth Sciences
                Paleontology
                Fossils
                Earth Sciences
                Atmospheric Science
                Climatology
                Paleoclimatology
                Biology and Life Sciences
                Paleontology
                Paleoclimatology
                Earth Sciences
                Paleontology
                Paleoclimatology
                Biology and Life Sciences
                Paleontology
                Fossils
                Fossil Record
                Earth Sciences
                Paleontology
                Fossils
                Fossil Record
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Forecasting
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Forecasting
                Earth Sciences
                Atmospheric Science
                Climatology
                Climate Modeling
                People and Places
                Geographical Locations
                Oceania
                Australia
                Biology and Life Sciences
                Organisms
                Animals
                Prehistoric Animals
                Diprotodon
                Biology and Life Sciences
                Paleontology
                Prehistoric Animals
                Diprotodon
                Earth Sciences
                Paleontology
                Prehistoric Animals
                Diprotodon
                Biology and Life Sciences
                Ecology
                Paleoecology
                Ecology and Environmental Sciences
                Ecology
                Paleoecology
                Biology and Life Sciences
                Paleontology
                Paleobiology
                Paleoecology
                Earth Sciences
                Paleontology
                Paleobiology
                Paleoecology
                Custom metadata
                All fossil record data are available in the FosSahul database, stored in the Australian Ecological Knowledge and Observation System (doi: 10.4227/05/564E6209C4FE8). Palaeoclimate data are from Singarayer JS and Valdes PJ. 2010. High-latitude climate sensitivity to ice-sheet forcing over the last 120 kyr. Quat Sci Rev. 2010;29: 43–55. doi: 10.1016/j.quascirev.2009.10.011. Joy .S. Singarayer may be contacted at joy.singarayer@ 123456bris.ac.uk Topographical data of Australia was obtained from Geoscience Australia, and is available at http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_63999 The digital elevation model used to calculate slope was obtained from Geoscience Australia and is available at http://www.ga.gov.au/metadata- gateway/metadata/record/gcat_66006 Annual rainfall and average days of rain data come from the Australian Bureau of Meteorology, available at http://www.bom.gov.au/jsp/ncc/climate_averages/rainfall/index.jsp and http://www.bom.gov.au/jsp/ncc/climate_averages/raindays/index.jsp, respectively. Vegetation cover data come from Geoscience Australia, available at http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_a05f7892-dba5-7506-e044- 00144fdd4fa6/Vegetation+-+Post-European+Settlement+%281988%29 Lithological data come from Geoscience Australia, available at http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_b4088aa1-f875-2444-e044-00144fdd4fa6/Surface+Geology+of+Australia+1%3A2.5+million+scale+dataset+2012+edition Urban localities and population density data come from the Australian Bureau of Statistics ( http://www.abs.gov.au/).

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