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      Behaviourally mediated predation avoidance in penguin prey: in situ evidence from animal-borne camera loggers

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          Abstract

          Predator dietary studies often assume that diet is reflective of the diversity and relative abundance of their prey. This interpretation ignores species-specific behavioural adaptations in prey that could influence prey capture. Here, we develop and describe a scalable biologging protocol, using animal-borne camera loggers, to elucidate the factors influencing prey capture by a seabird, the gentoo penguin ( Pygoscelis papua). From the video evidence, we show, to our knowledge for the first time, that aggressive behavioural defence mechanisms by prey can deter prey capture by a seabird. Furthermore, we provide evidence demonstrating that these birds, which were observed hunting solitarily, target prey when they are most discernible. Specifically, birds targeted prey primarily while ascending and when prey were not tightly clustered. In conclusion, we show that prey behaviour can significantly influence trophic coupling in marine systems because despite prey being present, it is not always targeted. Thus, these predator–prey relationships should be accounted for in studies using marine top predators as samplers of mid- to lower trophic-level species.

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          Most cited references34

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          The Role of Time and Energy in Food Preference

          J. Emlen (1966)
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            Continuous-time correlated random walk model for animal telemetry data.

            We propose a continuous-time version of the correlated random walk model for animal telemetry data. The continuous-time formulation allows data that have been nonuniformly collected over time to be modeled without subsampling, interpolation, or aggregation to obtain a set of locations uniformly spaced in time. The model is derived from a continuous-time Ornstein-Uhlenbeck velocity process that is integrated to form a location process. The continuous-time model was placed into a state-space framework to allow parameter estimation and location predictions from observed animal locations. Two previously unpublished marine mammal telemetry data sets were analyzed to illustrate use of the model, by-products available from the analysis, and different modifications which are possible. A harbor seal data set was analyzed with a model that incorporates the proportion of each hour spent on land. Also, a northern fur seal pup data set was analyzed with a random drift component to account for directed travel and ocean currents.
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              Putting predators back into behavioral predator–prey interactions

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                Author and article information

                Journal
                R Soc Open Sci
                R Soc Open Sci
                RSOS
                royopensci
                Royal Society Open Science
                The Royal Society
                2054-5703
                August 2018
                22 August 2018
                22 August 2018
                : 5
                : 8
                : 171449
                Affiliations
                [1 ]DST/NRF Centre of Excellence at the FitzPatrick Institute of African Ornithology, Department of Zoology, Nelson Mandela University , South Campus, Port Elizabeth 6031, South Africa
                [2 ]Falklands Conservation , PO Box 26, Stanley FIQQ 1ZZ, Falkland Islands
                [3 ]Department of Integrative Biology, University of Colorado Denver , PO Box 173364, Denver, CO 80217, USA
                Author notes
                Author for correspondence: Jonathan M. Handley e-mail: jonorow@ 123456gmail.com

                Electronic supplementary material is available online at https://dx.doi.org/10.6084/m9.figshare.c.4183355.

                Author information
                http://orcid.org/0000-0001-6468-338X
                Article
                rsos171449
                10.1098/rsos.171449
                6124084
                017cb589-0f45-4541-bde0-d15c8b42c618
                © 2018 The Authors.

                Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

                History
                : 23 September 2017
                : 19 July 2018
                Funding
                Funded by: John Cheek Trust, http://dx.doi.org/10.13039/100009480;
                Funded by: Nelson Mandela Metropolitan University Research Capacity Department;
                Funded by: Rufford Foundation, http://dx.doi.org/10.13039/100007463;
                Award ID: 12372-1
                Funded by: Falkland Islands Environmental Planning Department;
                Categories
                1001
                14
                60
                42
                Biology (Whole Organism)
                Research Article
                Custom metadata
                August, 2018

                seabird,penguin,animal-borne camera,predator–prey,confusion effect,indicator species

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