2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Hematocrit, age, and survival in a wild vertebrate population

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Understanding trade‐offs in wild populations is difficult, but important if we are to understand the evolution of life histories and the impact of ecological variables upon them. Markers that reflect physiological state and predict future survival would be of considerable benefit to unraveling such trade‐offs and could provide insight into individual variation in senescence. However, currently used markers often yield inconsistent results. One underutilized measure is hematocrit, the proportion of blood comprising erythrocytes, which relates to the blood's oxygen‐carrying capacity and viscosity, and to individual endurance. Hematocrit has been shown to decline with age in cross‐sectional studies (which may be confounded by selective appearance/disappearance). However, few studies have tested whether hematocrit declines within individuals or whether low hematocrit impacts survival in wild taxa. Using longitudinal data from the Seychelles warbler ( Acrocephalus sechellensis), we demonstrated that hematocrit increases with age in young individuals (<1.5 years) but decreases with age in older individuals (1.5–13 years). In breeders, hematocrit was higher in males than females and varied relative to breeding stage. High hematocrit was associated with lower survival in young individuals, but not older individuals. Thus, while we did not find support for hematocrit as a marker of senescence, high hematocrit is indicative of poor condition in younger individuals. Possible explanations are that these individuals were experiencing dehydration and/or high endurance demands prior to capture, which warrants further investigation. Our study demonstrates that hematocrit can be an informative metric for life‐history studies investigating trade‐offs between survival, longevity, and reproduction.

          Abstract

          Using long‐term data we investigated the association between haematocrit, longitudinal age and survival in a wild vertebrate population—the Seychelles warbler ( Acrocephalus sechellensis). Haematocrit exhibited a distinctive age‐dependent pattern within‐individuals, and young individuals with high haematocrit had poorer survival prospects. This study highlights a novel physiological change with age that is indicative of individual condition in wild populations.

          Related collections

          Most cited references102

          • Record: found
          • Abstract: not found
          • Article: not found

          Fitting Linear Mixed-Effects Models Usinglme4

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            A simple method for distinguishing within- versus between-subject effects using mixed models

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Repeatability for Gaussian and non-Gaussian data: a practical guide for biologists.

              Repeatability (more precisely the common measure of repeatability, the intra-class correlation coefficient, ICC) is an important index for quantifying the accuracy of measurements and the constancy of phenotypes. It is the proportion of phenotypic variation that can be attributed to between-subject (or between-group) variation. As a consequence, the non-repeatable fraction of phenotypic variation is the sum of measurement error and phenotypic flexibility. There are several ways to estimate repeatability for Gaussian data, but there are no formal agreements on how repeatability should be calculated for non-Gaussian data (e.g. binary, proportion and count data). In addition to point estimates, appropriate uncertainty estimates (standard errors and confidence intervals) and statistical significance for repeatability estimates are required regardless of the types of data. We review the methods for calculating repeatability and the associated statistics for Gaussian and non-Gaussian data. For Gaussian data, we present three common approaches for estimating repeatability: correlation-based, analysis of variance (ANOVA)-based and linear mixed-effects model (LMM)-based methods, while for non-Gaussian data, we focus on generalised linear mixed-effects models (GLMM) that allow the estimation of repeatability on the original and on the underlying latent scale. We also address a number of methods for calculating standard errors, confidence intervals and statistical significance; the most accurate and recommended methods are parametric bootstrapping, randomisation tests and Bayesian approaches. We advocate the use of LMM- and GLMM-based approaches mainly because of the ease with which confounding variables can be controlled for. Furthermore, we compare two types of repeatability (ordinary repeatability and extrapolated repeatability) in relation to narrow-sense heritability. This review serves as a collection of guidelines and recommendations for biologists to calculate repeatability and heritability from both Gaussian and non-Gaussian data. © 2010 The Authors. Biological Reviews © 2010 Cambridge Philosophical Society.
                Bookmark

                Author and article information

                Contributors
                tom.j.brown@uea.ac.uk
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                21 December 2020
                January 2021
                : 11
                : 1 ( doiID: 10.1002/ece3.v11.1 )
                : 214-226
                Affiliations
                [ 1 ] School of Biological Sciences University of East Anglia Norwich UK
                [ 2 ] Groningen Institute for Evolutionary Life Sciences University of Groningen Groningen The Netherlands
                [ 3 ] School of Biology Faculty of Biological Sciences University of Leeds Leeds UK
                [ 4 ] Nature Seychelles Victoria Mahé Seychelles
                Author notes
                [*] [* ] Correspondence

                Thomas J. Brown, School of Biological Sciences, University of East Anglia, Norwich NR4 7TJ, UK.

                Email: tom.j.brown@ 123456uea.ac.uk

                Author information
                https://orcid.org/0000-0002-4235-0856
                https://orcid.org/0000-0002-6638-820X
                https://orcid.org/0000-0002-3858-0712
                https://orcid.org/0000-0001-8769-0099
                https://orcid.org/0000-0002-9241-0124
                https://orcid.org/0000-0001-7226-9074
                Article
                ECE37015
                10.1002/ece3.7015
                7790625
                33437424
                a693de71-4f4b-4bc6-a8ad-c879d2c81c43
                © 2020 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
                : 09 September 2020
                : 23 October 2020
                Page count
                Figures: 5, Tables: 3, Pages: 13, Words: 10711
                Funding
                Funded by: Nederlandse Organisatie voor Wetenschappelijk Onderzoek , open-funder-registry 10.13039/501100003246;
                Award ID: 823.01.014
                Award ID: 854.11.003
                Award ID: 863.15.020
                Award ID: NE/I021748/1
                Award ID: NER/I/S/2002/00712
                Award ID: NWO‐ALW 823.01.014
                Funded by: Natural Environment Research Council , open-funder-registry 10.13039/501100000270;
                Award ID: NE/F02083X/1
                Award ID: NE/K005502/1
                Funded by: Biotechnology and Biological Sciences Research Council , open-funder-registry 10.13039/501100000268;
                Award ID: BB/M011216/1
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                January 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.6 mode:remove_FC converted:07.01.2021

                Evolutionary Biology
                aging,biomarkers,birds,condition markers,hematocrit,life history,senescence,survival,trade‐offs,wild populations

                Comments

                Comment on this article