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      No evidence for a signal in mammalian basal metabolic rate associated with a fossorial lifestyle

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          Abstract

          A vast array of challenging environments are inhabited by mammals, such as living in confined spaces where oxygen levels are likely to be low. Species can exhibit adaptations in basal metabolic rate (BMR) to exploit such unique niches. In this study we use 801 species to determine the relationship between BMR and burrow use in mammals. We included pre-existing data for mammalian BMR and 16 life history traits. Overall, mammalian BMR is dictated primarily by environmental ambient temperature. There were no significant differences in BMR of terrestrial, semi-fossorial and fossorial mammals, suggesting that species occupying a subterranean niche do not exhibit baseline metabolic costs on account of their burrowing lifestyle. Fossorial mammals likely show instantaneous metabolic responses to low oxygen in tunnels, rather than exhibit adaptive long-term responses in their BMR.

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

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            MCMC Methods for Multi-Response Generalized Linear Mixed Models: TheMCMCglmmRPackage

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              Multimodel inference in ecology and evolution: challenges and solutions.

              Information theoretic approaches and model averaging are increasing in popularity, but this approach can be difficult to apply to the realistic, complex models that typify many ecological and evolutionary analyses. This is especially true for those researchers without a formal background in information theory. Here, we highlight a number of practical obstacles to model averaging complex models. Although not meant to be an exhaustive review, we identify several important issues with tentative solutions where they exist (e.g. dealing with collinearity amongst predictors; how to compute model-averaged parameters) and highlight areas for future research where solutions are not clear (e.g. when to use random intercepts or slopes; which information criteria to use when random factors are involved). We also provide a worked example of a mixed model analysis of inbreeding depression in a wild population. By providing an overview of these issues, we hope that this approach will become more accessible to those investigating any process where multiple variables impact an evolutionary or ecological response. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.
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                Author and article information

                Contributors
                Hana.Merchant.2020@live.rhul.ac.uk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                17 May 2024
                17 May 2024
                2024
                : 14
                : 11297
                Affiliations
                [1 ]Department of Biological Sciences, School of Life and Environmental Sciences, Royal Holloway University of London, ( https://ror.org/04g2vpn86) Egham, Surrey TW20 0EX UK
                [2 ]Department of Biology, University of Oxford, ( https://ror.org/052gg0110) OX1 3SZ Oxford, United Kingdom
                Article
                61595
                10.1038/s41598-024-61595-1
                11101413
                38760353
                dc5819b5-46da-48f6-9b46-e52f0b9b1ce6
                © The Author(s) 2024

                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 October 2023
                : 7 May 2024
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000270, Natural Environment Research Council;
                Award ID: NE\L002485\1
                Award Recipient :
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                © Springer Nature Limited 2024

                Uncategorized
                ecophysiology,evolutionary ecology
                Uncategorized
                ecophysiology, evolutionary ecology

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