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      Juvenile honest food solicitation and parental investment as a life history strategy: A kin demographic selection model

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          Abstract

          Parent-offspring communication remains an unresolved challenge for biologist. The difficulty of the challenge comes from the fact that it is a multifaceted problem with connections to life-history evolution, parent-offspring conflict, kin selection and signalling. Previous efforts mainly focused on modelling resource allocation at the expense of the dynamic interaction during a reproductive season. Here we present a two-stage model of begging where the first stage models the interaction between nestlings and parents within a nest and the second stage models the life-history trade-offs. We show in an asexual population that honest begging results in decreased variance of collected food between siblings, which leads to mean number of surviving offspring. Thus, honest begging can be seen as a special bet-hedging against informational uncertainty, which not just decreases the variance of fitness but also increases the arithmetic mean.

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          Most cited references23

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          Biological signals as handicaps.

          An ESS model of Zahavi's handicap principle is constructed. This allows a formal exposition of how the handicap principle works, and shows that its essential elements are strategic. The handicap model is about signalling, and it is proved under fairly general conditions that if the handicap principle's conditions are met, then an evolutionarily stable signalling equilibrium exists in a biological signalling system, and that any signalling equilibrium satisfies the conditions of the handicap principle. Zahavi's major claims for the handicap principle are thus vindicated. The place of cheating is discussed in view of the honesty that follows from the handicap principle. Parallel signalling models in economics are discussed. Interpretations of the handicap principle are compared. The models are not fully explicit about how females use information about male quality, and, less seriously, have no genetics. A companion paper remedies both defects in a model of the handicap principle at work in sexual selection.
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            Hedging one's evolutionary bets, revisited.

            Evolutionary bet-hedging involves a trade-off between the mean and variance of fitness, such that phenotypes with reduced mean fitness may be at a selective advantage under certain conditions. The theory of bet-hedging was first formulated in the 1970s, and recent empirical studies suggest that the process may operate in a wide range of plant and animal species. Copyright © 1989. Published by Elsevier Ltd.
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              Signalling of need by offspring to their parents

              H. Godfray (1991)
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: SupervisionRole: Writing – original draft
                Role: Formal analysisRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Writing – review & editing
                Role: ConceptualizationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                1 March 2018
                2018
                : 13
                : 3
                : e0193420
                Affiliations
                [1 ] MTA-ELTE Research Group in Theoretical Biology and Evolutionary Ecology, Department of Plant Systematics, Ecology and Theoretical Biology, ELTE Eötvös Loránd University, Budapest, Hungary
                [2 ] Evolutionary Systems Research Group, MTA Centre for Ecological Research, Tihany, Hungary
                [3 ] Department of Probability Theory and Statistics, Eötvös Loránd University, Budapest, Hungary
                [4 ] Department of Mathematics, Szent István University, Gödöllő, Hungary
                [5 ] RECENS „Lendület” Research Group, MTA Centre for Social Science, Budapest, Hungary
                Universidad de Granada, SPAIN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-0860-2252
                http://orcid.org/0000-0002-7021-3162
                http://orcid.org/0000-0002-9328-7471
                http://orcid.org/0000-0003-2204-9705
                Article
                PONE-D-17-41680
                10.1371/journal.pone.0193420
                5832247
                29494630
                23fa1673-2c77-444f-af75-40327683623e
                © 2018 Garay et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 27 November 2017
                : 10 February 2018
                Page count
                Figures: 7, Tables: 0, Pages: 13
                Funding
                Funded by: Hungarian National Research, Development and Innovation Office NKFIH
                Award ID: OTKA K 125569
                Award Recipient :
                Funded by: Hungarian National Research, Development and Innovation Office NKFIH
                Award ID: OTKA K 108974
                Award Recipient :
                Funded by: Hungarian National Research, Development and Innovation Office NKFIH
                Award ID: OTKA K 119347
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100010661, Horizon 2020 Framework Programme;
                Award ID: 648693
                Funded by: Hungarian National Research, Development and Innovation Office NKFIH
                Award ID: GINOP 2.3.2-15-2016-00057
                This work was supported by the Hungarian National Research, Development and Innovation Office NKFIH: K 125569 (T.M.), K 108974 (J.G. and SZ.SZ), K 119347 (A.SZ) ( http://nkfih.gov.hu/english); European Structural and Investment Funds (ESIF) in Hungary (GINOP 2.3.2-15-2016-00057) ( https://www.palyazat.gov.hu/evaluation); and European Research Council (No 648693) ( https://erc.europa.eu/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Population Biology
                Population Metrics
                Fecundity
                Physical Sciences
                Mathematics
                Algebra
                Linear Algebra
                Eigenvalues
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Processes
                Kin Selection
                Physical Sciences
                Mathematics
                Probability Theory
                Probability Distribution
                Normal Distribution
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Birds
                Physical Sciences
                Mathematics
                Probability Theory
                Markov Models
                Biology and Life Sciences
                Genetics
                Phenotypes
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Processes
                Natural Selection
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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