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      Recent and rapid ecogeographical rule reversals in Northern Treeshrews

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          Abstract

          Two of the most-studied ecogeographical rules describe patterns of body size variation within species. Bergmann’s rule predicts that individuals have larger body sizes in colder climates (typically at higher latitudes), and the island rule predicts that island populations of small-bodied species average larger in size than their mainland counterparts (insular gigantism). These rules are rarely tested in conjunction or assessed across space and time simultaneously. We investigated these patterns in the Northern Treeshrew ( Tupaia belangeri) using museum specimens collected across a wide spatial and temporal range. Contrary to Bergmann’s rule, size increases with temperature in T. belangeri, a signal that is highly consistent across space and time. We also show that these rules are intertwined: Bergmann’s rule is reversed on the mainland but holds on islands, and therefore the island rule is upheld at higher, but not lower, latitudes. Moreover, we demonstrate a rapid reversal of both rules over time. The mechanism behind these inversions remains unclear, though temperature and precipitation are significant predictors of body size. Ecogeographical rules rely on the assumption of a constant relationship between size and the factors driving its variation. Our results highlight the need to question this assumption and reevaluate these rules in the context of accelerating and uneven climate change.

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              Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset

              CRU TS (Climatic Research Unit gridded Time Series) is a widely used climate dataset on a 0.5° latitude by 0.5° longitude grid over all land domains of the world except Antarctica. It is derived by the interpolation of monthly climate anomalies from extensive networks of weather station observations. Here we describe the construction of a major new version, CRU TS v4. It is updated to span 1901–2018 by the inclusion of additional station observations, and it will be updated annually. The interpolation process has been changed to use angular-distance weighting (ADW), and the production of secondary variables has been revised to better suit this approach. This implementation of ADW provides improved traceability between each gridded value and the input observations, and allows more informative diagnostics that dataset users can utilise to assess how dataset quality might vary geographically.
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                Author and article information

                Contributors
                maya.juman@aya.yale.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                29 November 2022
                29 November 2022
                2022
                : 12
                : 19689
                Affiliations
                [1 ]GRID grid.47100.32, ISNI 0000000419368710, Department of Ecology and Evolutionary Biology, , Yale University, ; New Haven, CT USA
                [2 ]GRID grid.70738.3b, ISNI 0000 0004 1936 981X, Department of Mammalogy, , University of Alaska Museum, University of Alaska Fairbanks, ; Fairbanks, AK USA
                [3 ]GRID grid.5335.0, ISNI 0000000121885934, Department of Veterinary Medicine, , University of Cambridge, ; Cambridge, UK
                [4 ]GRID grid.14709.3b, ISNI 0000 0004 1936 8649, Redpath Museum, , McGill University, ; Montreal, QC Canada
                [5 ]GRID grid.47100.32, ISNI 0000000419368710, Department of Anthropology, , Yale University, ; New Haven, CT USA
                [6 ]GRID grid.47100.32, ISNI 0000000419368710, Divisions of Vertebrate Zoology and Vertebrate Paleontology, , Yale Peabody Museum of Natural History, ; New Haven, CT USA
                [7 ]GRID grid.47100.32, ISNI 0000000419368710, Yale Institute for Biospheric Studies, ; New Haven, CT USA
                Author information
                http://orcid.org/0000-0002-0211-0655
                http://orcid.org/0000-0002-1390-766X
                http://orcid.org/0000-0002-2481-5701
                http://orcid.org/0000-0003-0424-3803
                Article
                23774
                10.1038/s41598-022-23774-w
                9708835
                36446809
                5b0fc009-4ec2-406a-b352-1db70326c8f6
                © 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
                : 9 September 2022
                : 4 November 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000865, Bill and Melinda Gates Foundation;
                Award ID: OPP1144
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000038, Natural Sciences and Engineering Research Council of Canada;
                Award ID: Discovery Grant 2017-03839
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: DEB-0542532/0542725
                Award ID: DEB-0542532/0542725
                Award Recipient :
                Funded by: Alaska EPSCoR
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                biogeography,climate-change ecology,evolution,zoology
                Uncategorized
                biogeography, climate-change ecology, evolution, zoology

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