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      Separating the effects of paternal age and mating history: Evidence for sex‐specific paternal effect in eastern mosquitofish

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          Abstract

          Paternal age and past mating effort by males are often confounded, which can affect our understanding of a father's age effects. To our knowledge, only a few studies have standardized mating history when testing for effects of paternal age, and none has simultaneously disentangled how paternal age and mating history might jointly influence offspring traits. Here, we experimentally manipulated male mating history to tease apart its effects from those of paternal age on female fertility and offspring traits in the eastern mosquitofish ( Gambusia holbrooki). Male age did not affect female fertility. However, males with greater past mating effort produced significantly larger broods. Paternal age and mating history interacted to affect sons' body size: sons sired by old‐virgin males were larger than those sired by old‐mated males, but this was not the case for younger fathers. Intriguingly, however, sons sired by old‐virgin males tended to produce fewer sperms than those sired by old‐mated males, indicating a potential trade‐off in beneficial paternal effects. Finally, neither paternal age nor mating history affected daughter's fitness. Our results highlight that variation in offspring traits attributed to paternal age effect could partly arise due to a father's mating history, and not simply to his chronological age.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Fitting Linear Mixed-Effects Models Using lme4

            Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer. Journal of Statistical Software, 67 (1) ISSN:1548-7660
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              The adaptive significance of maternal effects

              T Mousseau (1998)
              Recently, the adaptive significance of maternal effects has been increasingly recognized. No longer are maternal effects relegated as simple `troublesome sources of environmental resemblance' that confound our ability to estimate accurately the genetic basis of traits of interest. Rather, it has become evident that many maternal effects have been shaped by the action of natural selection to act as a mechanism for adaptive phenotypic response to environmental heterogeneity. Consequently, maternal experience is translated into variation in offspring fitness.
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                Author and article information

                Contributors
                aich.aich49@gmail.com
                Journal
                Evolution
                Evolution
                10.1111/(ISSN)1558-5646
                EVO
                Evolution; International Journal of Organic Evolution
                John Wiley and Sons Inc. (Hoboken )
                0014-3820
                1558-5646
                18 May 2022
                July 2022
                : 76
                : 7 ( doiID: 10.1111/evo.v76.7 )
                : 1565-1577
                Affiliations
                [ 1 ] Division of Ecology & Evolution Research School of Biology The Australian National University Canberra Australia
                [ 2 ] School of Biological Sciences Monash University Clayton Victoria Australia
                [ 3 ] School of Biological Sciences University of Queensland Saint Lucia Queensland Australia
                Author notes
                Author information
                https://orcid.org/0000-0003-2576-0922
                https://orcid.org/0000-0003-2936-5786
                https://orcid.org/0000-0001-9221-2788
                Article
                EVO14498
                10.1111/evo.14498
                9543789
                35544673
                e9e948e9-1e83-4e14-b986-694ff9740eb6
                © 2022 The Authors. Evolution published by Wiley Periodicals LLC on behalf of The Society for the Study of Evolution.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 20 March 2022
                : 12 September 2021
                : 23 March 2022
                Page count
                Figures: 4, Tables: 0, Pages: 13, Words: 10924
                Funding
                Funded by: Australian Research Council Discovery Project
                Award ID: DP160100285
                Award ID: DP190100279.
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                July 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.0 mode:remove_FC converted:07.10.2022

                Evolutionary Biology
                Evolutionary Biology

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