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      The dominant mesopredator and savanna formations shape the distribution of the rare northern tiger cat ( Leopardus tigrinus) in the Amazon

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          Abstract

          Understanding the distribution patterns of threatened species is central to conservation. The Amazonian distribution of the northern tiger cat (N-tiger cat, Leopardus tigrinus) and its interspecific relationship with the ocelot, its potential intraguild killer, are intriguing. Here, we combined presence/absence records with species distribution models (SDMs) to determine N-tiger cat occurrence in the Amazon. We also modeled ocelot density from 46 published estimates. The N-tiger cat’s presence in the Amazon was negatively influenced by ocelot density and net primary productivity and positively influenced by savannas and precipitation in the driest month. The best-fitting model predicted highly patchy N-tiger cat occurrence over an area of 236,238.67 km 2, almost exclusively in savanna enclaves. Additionally, 312,348 camera trap-days at 49 sites in the Amazon revealed no N-tiger cats. The ocelot densities were significantly higher in areas with denser vegetation cover and warmer habitats, with predicted densities ≥ 0.6 ind/km 2 throughout most of the biome. The lowest ocelot densities (≤ 0.06 ind/km 2) were observed along the predicted range of N-tiger cats. Our findings highlight that the N-tiger cat’s presence in the Amazon is restricted to savannas and highly influenced by ocelot density, emphasizing the importance of including species interactions in SDMs.

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          WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas

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            Terrestrial Ecoregions of the World: A New Map of Life on Earth

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              Present and future Köppen-Geiger climate classification maps at 1-km resolution

              We present new global maps of the Köppen-Geiger climate classification at an unprecedented 1-km resolution for the present-day (1980–2016) and for projected future conditions (2071–2100) under climate change. The present-day map is derived from an ensemble of four high-resolution, topographically-corrected climatic maps. The future map is derived from an ensemble of 32 climate model projections (scenario RCP8.5), by superimposing the projected climate change anomaly on the baseline high-resolution climatic maps. For both time periods we calculate confidence levels from the ensemble spread, providing valuable indications of the reliability of the classifications. The new maps exhibit a higher classification accuracy and substantially more detail than previous maps, particularly in regions with sharp spatial or elevation gradients. We anticipate the new maps will be useful for numerous applications, including species and vegetation distribution modeling. The new maps including the associated confidence maps are freely available via www.gloh2o.org/koppen.
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                Author and article information

                Contributors
                tadeu4@yahoo.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                4 November 2022
                4 November 2022
                2022
                : 12
                : 18697
                Affiliations
                [1 ]GRID grid.459974.2, ISNI 0000 0001 2176 7356, Departamento de Biologia, , Universidade Estadual do Maranhão (UEMA), Campus Paulo VI, ; Av. Lourenço Vieira da Silva 1000, Jardim São Cristóvão, São Luís, Maranhão 65055-310 Brazil
                [2 ]GRID grid.512275.6, Instituto Pró-Carnívoros, ; Av. Horácio Neto, 1020, Parque Edmundo Zanoni, Atibaia, São Paulo 12945-010 Brazil
                [3 ]GRID grid.459974.2, ISNI 0000 0001 2176 7356, Programa de Pós-Graduação em Ecologia e Conservação da Biodiversidade PPGECB/PPG Em Ciência Animal da Universidade Estadual Do Maranhão, , Cidade Universitária Paulo VI, ; Av. Lourenço Vieira da Silva, nº 1000 – Bairro, Jardim São Cristóvão, São Luís, MA CEP: 65055-310 Brazil
                [4 ]GRID grid.7450.6, ISNI 0000 0001 2364 4210, Department of Conservation Biology, , Georg-August Universität, ; Bürgerstrasse 50, 37073 Göttingen, Germany
                [5 ]GRID grid.452670.2, ISNI 0000 0004 6431 5036, Panthera, ; 8 W 40th St. 18th Floor, New York, NY 10018 USA
                [6 ]People and Wildlife Solutions, Manari, Region 9 Guyana
                [7 ]GRID grid.11899.38, ISNI 0000 0004 1937 0722, Departamento de Ciências Florestais, , Escola Superior de Agricultura Luiz de Queiroz, Universidade de São Paulo, ; Avenida Pádua Dias 11, Piracicaba, São Paulo 13418-900 Brazil
                Article
                21412
                10.1038/s41598-022-21412-z
                9636236
                36333380
                32a95ea8-6ded-4d6b-a09b-924f8139f892
                © The Author(s) 2022

                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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 14 March 2022
                : 27 September 2022
                Categories
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                © The Author(s) 2022

                Uncategorized
                ecology,zoology
                Uncategorized
                ecology, zoology

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