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      The global distribution of tetrapods reveals a need for targeted reptile conservation

      , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,  
      Nature Ecology & Evolution
      Springer Science and Business Media LLC

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          Local Indicators of Spatial Association-LISA

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            The status of the world's land and marine mammals: diversity, threat, and knowledge.

            Knowledge of mammalian diversity is still surprisingly disparate, both regionally and taxonomically. Here, we present a comprehensive assessment of the conservation status and distribution of the world's mammals. Data, compiled by 1700+ experts, cover all 5487 species, including marine mammals. Global macroecological patterns are very different for land and marine species but suggest common mechanisms driving diversity and endemism across systems. Compared with land species, threat levels are higher among marine mammals, driven by different processes (accidental mortality and pollution, rather than habitat loss), and are spatially distinct (peaking in northern oceans, rather than in Southeast Asia). Marine mammals are also disproportionately poorly known. These data are made freely available to support further scientific developments and conservation action.
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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

                Contributors
                Journal
                Nature Ecology & Evolution
                Nat Ecol Evol
                Springer Science and Business Media LLC
                2397-334X
                November 2017
                October 09 2017
                : 1
                : 11
                : 1677-1682
                Article
                10.1038/s41559-017-0332-2
                28993667
                7f7e02db-71a2-40f4-a67d-996863c6d7f1
                © 2017

                https://www.springernature.com/gp/researchers/text-and-data-mining

                https://www.springernature.com/gp/researchers/text-and-data-mining

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