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      Sexual segregation results in pronounced sex-specific density gradients in the mountain ungulate, Rupicapra rupicapra

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          Abstract

          Sex-specific differences in habitat selection and space use are common in ungulates. Yet, it is largely unknown how this behavioral dimorphism, ultimately leading to sexual segregation, translates to population-level patterns and density gradients across landscapes. Alpine chamois ( Rupicapra rupicapra r.) predominantly occupy habitat above tree line, yet especially males may also take advantage of forested habitats. To estimate male and female chamois density and determinants thereof, we applied Bayesian spatial capture-recapture (SCR) models in two contrasting study areas in the Alps, Germany, during autumn. We fitted SCR models to non-invasive individual encounter data derived from genotyped feces. Sex-specific densities were modeled as a function of terrain ruggedness, forest canopy cover, proportion of barren ground, and site severity. We detected pronounced differences in male and female density patterns, driven primarily by terrain ruggedness, rather than by sex-specific effects of canopy cover. The positive effect of ruggedness on density was weaker for males which translated into a higher proportion of males occupying less variable terrain, frequently located in forests, compared to females. By estimating sex-specific variation in both detection probabilities and density, we were able to quantify and map how individual behavioral differences scale up and shape spatial patterns in population density.

          Abstract

          Non-invasive fecal genotyping on Alpine chamois ( Rupicapra rupicapra) in combination with spatial capture recapture models reveal sex-specific density patterns, which are driven by environmental features.

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          Inference from Iterative Simulation Using Multiple Sequences

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            Collinearity: a review of methods to deal with it and a simulation study evaluating their performance

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              The ecology of individuals: incidence and implications of individual specialization.

              Most empirical and theoretical studies of resource use and population dynamics treat conspecific individuals as ecologically equivalent. This simplification is only justified if interindividual niche variation is rare, weak, or has a trivial effect on ecological processes. This article reviews the incidence, degree, causes, and implications of individual-level niche variation to challenge these simplifications. Evidence for individual specialization is available for 93 species distributed across a broad range of taxonomic groups. Although few studies have quantified the degree to which individuals are specialized relative to their population, between-individual variation can sometimes comprise the majority of the population's niche width. The degree of individual specialization varies widely among species and among populations, reflecting a diverse array of physiological, behavioral, and ecological mechanisms that can generate intrapopulation variation. Finally, individual specialization has potentially important ecological, evolutionary, and conservation implications. Theory suggests that niche variation facilitates frequency-dependent interactions that can profoundly affect the population's stability, the amount of intraspecific competition, fitness-function shapes, and the population's capacity to diversify and speciate rapidly. Our collection of case studies suggests that individual specialization is a widespread but underappreciated phenomenon that poses many important but unanswered questions.
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                Author and article information

                Contributors
                hendrik.edelhoff@lwf.bayern.de
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                25 September 2023
                25 September 2023
                2023
                : 6
                : 979
                Affiliations
                [1 ]GRID grid.500073.1, ISNI 0000 0001 1015 5020, Wildlife Biology and Management Research Unit, , Bavarian State Institute of Forestry, ; Freising, Germany
                [2 ]Faculty of Environmental Management and Natural Resource Management, Norwegian University of Life Sciences, ( https://ror.org/04a1mvv97) Ås, Norway
                [3 ]Seq-IT GmbH & Co.KG, Department Wildlife Genetics, Kaiserslautern, Germany
                [4 ]GRID grid.500073.1, ISNI 0000 0001 1015 5020, Department of Conservation and Biodiversity, , Bavarian State Institute of Forestry, ; Freising, Germany
                [5 ]Wildlife Biology and Management Unit, Technical University of Munich, ( https://ror.org/02kkvpp62) Freising, Germany
                Author information
                http://orcid.org/0000-0001-6354-8952
                http://orcid.org/0000-0002-1267-9183
                Article
                5313
                10.1038/s42003-023-05313-z
                10520025
                37749272
                994242f5-8271-4b76-86ae-3d33579868e7
                © Springer Nature Limited 2023

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

                History
                : 12 August 2022
                : 1 September 2023
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100010269, Bayerisches Staatsministerium für Ernährung, Landwirtschaft und Forsten (Bavarian Ministry of Food, Agriculture and Forestry);
                Award ID: JA14
                Award ID: ST360
                Award ID: ST360
                Award ID: JA14
                Award ID: ST360
                Award ID: ST360
                Award ID: JA14
                Award ID: ST360
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100005416, Norges Forskningsråd (Research Council of Norway);
                Award ID: NFR:286886
                Award ID: NFR:286886
                Award ID: NFR:286886
                Award Recipient :
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                © Springer Nature Limited 2023

                behavioural ecology,ecological modelling
                behavioural ecology, ecological modelling

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