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      Social and ecological factors alter stress physiology of Virunga mountain gorillas ( Gorilla beringei beringei)

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          Abstract

          Living in a rapidly changing environment can alter stress physiology at the population level, with negative impacts on health, reproductive rates, and mortality that may ultimately result in species decline. Small, isolated animal populations where genetic diversity is low are at particular risks, such as endangered Virunga mountain gorillas ( Gorilla beringei beringei). Along with climate change‐associated environmental shifts that are affecting the entire population, subpopulations of the Virunga gorillas have recently experienced extreme changes in their social environment. As the growing population moves closer to the forest's carrying capacity, the gorillas are coping with rising population density, increased frequencies of interactions between social units, and changing habitat use (e.g., more overlapping home ranges and routine ranging at higher elevations). Using noninvasive monitoring of fecal glucocorticoid metabolites (FGM) on 115 habituated Virunga gorillas, we investigated how social and ecological variation are related to baseline FGM levels, to better understand the adaptive capacity of mountain gorillas and monitor potential physiological indicators of population decline risks. Generalized linear mixed models revealed elevated mean monthly baseline FGM levels in months with higher rainfall and higher mean maximum and minimum temperature, suggesting that Virunga gorillas might be sensitive to predicted warming and rainfall trends involving longer, warmer dry seasons and more concentrated and extreme rainfall occurrences. Exclusive use of smaller home range areas was linked to elevated baseline FGM levels, which may reflect reduced feeding efficiency and increased travel efforts to actively avoid neighboring groups. The potential for additive effects of stress‐inducing factors could have short‐ and long‐term impacts on the reproduction, health, and ultimately survival of the Virunga gorilla population. The ongoing effects of environmental changes and population dynamics must be closely monitored and used to develop effective long‐term conservation strategies that can help address these risk factors.

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          Most cited references63

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          How Do Glucocorticoids Influence Stress Responses? Integrating Permissive, Suppressive, Stimulatory, and Preparative Actions

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            Physiological stress in ecology: lessons from biomedical research.

            Increasingly, levels of the 'stress hormones' cortisol and corticosterone are being used by ecologists as indicators of physiological stress in wild vertebrates. The amplitude of hormonal response is assumed to correlate with the overall health of an animal and, by extension, the health of the population. However, much of what is known about the physiology of stress has been elucidated by the biomedical research community. I summarize five physiological mechanisms that regulate hormone release during stress that should be useful to ecologists and conservationists. Incorporating these physiological mechanisms into the design and interpretation of ecological studies will make these increasingly popular studies of stress in ecological settings more rigorous.
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              Conclusions beyond support: overconfident estimates in mixed models

              Mixed-effect models are frequently used to control for the nonindependence of data points, for example, when repeated measures from the same individuals are available. The aim of these models is often to estimate fixed effects and to test their significance. This is usually done by including random intercepts, that is, intercepts that are allowed to vary between individuals. The widespread belief is that this controls for all types of pseudoreplication within individuals. Here we show that this is not the case, if the aim is to estimate effects that vary within individuals and individuals differ in their response to these effects. In these cases, random intercept models give overconfident estimates leading to conclusions that are not supported by the data. By allowing individuals to differ in the slopes of their responses, it is possible to account for the nonindependence of data points that pseudoreplicate slope information. Such random slope models give appropriate standard errors and are easily implemented in standard statistical software. Because random slope models are not always used where they are essential, we suspect that many published findings have too narrow confidence intervals and a substantially inflated type I error rate. Besides reducing type I errors, random slope models have the potential to reduce residual variance by accounting for between-individual variation in slopes, which makes it easier to detect treatment effects that are applied between individuals, hence reducing type II errors as well.
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                Author and article information

                Contributors
                weckardt@gorillafund.org
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                01 April 2019
                May 2019
                : 9
                : 9 ( doiID: 10.1002/ece3.2019.9.issue-9 )
                : 5248-5259
                Affiliations
                [ 1 ] Dian Fossey Gorilla Fund Atlanta Georgia
                [ 2 ] Departmet of Anthropology Northwestern University Evanston Illinois
                [ 3 ] Davee Center for Epidemiology and Endocrinology Lincoln Park Zoo Chicago Illinois
                Author notes
                [*] [* ] Correspondence

                Winnie Eckardt, The Dian Fossey Gorilla Fund International, Karisoke Research Center, Musanze, Rwanda.

                Email: weckardt@ 123456gorillafund.org

                Author information
                https://orcid.org/0000-0003-4590-4559
                Article
                ECE35115
                10.1002/ece3.5115
                6509442
                31110676
                80b61a89-e4a1-44df-9a50-6db6798d30cb
                © 2019 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 20 October 2018
                : 05 February 2019
                : 01 March 2019
                Page count
                Figures: 3, Tables: 2, Pages: 12, Words: 9659
                Funding
                Funded by: United States Fish and Wildlife Service
                Award ID: F12AP01120
                Funded by: Wenner‐Gren Foundation
                Award ID: 20110146
                Funded by: National Science Foundation Doctoral Dissertation Improvement Grant
                Award ID: 1122321
                Funded by: Leakey Foundation
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                ece35115
                May 2019
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.6.2.1 mode:remove_FC converted:10.05.2019

                Evolutionary Biology
                fecal glucocorticoid metabolites,group density,home range,rainfall,temperature

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