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Leveraging big data to uncover the eco-evolutionary factors shaping behavioural development.
Ehlman, Sean M; Scherer, Ulrike; Bierbach, David; Francisco, Fritz; Laskowski, Kate L; Krause, Jens; Wolf, Max.
Afiliação
  • Ehlman SM; SCIoI Excellence Cluster, 10587 Berlin, Germany.
  • Scherer U; Faculty of Life Sciences, Humboldt University, 10117 Berlin, Germany.
  • Bierbach D; Department of Fish Biology, Fisheries, and Aquaculture, Leibniz Institute of Freshwater Ecology and Inland Fisheries, 12587 Berlin, Germany.
  • Francisco F; SCIoI Excellence Cluster, 10587 Berlin, Germany.
  • Laskowski KL; Faculty of Life Sciences, Humboldt University, 10117 Berlin, Germany.
  • Krause J; Department of Fish Biology, Fisheries, and Aquaculture, Leibniz Institute of Freshwater Ecology and Inland Fisheries, 12587 Berlin, Germany.
  • Wolf M; SCIoI Excellence Cluster, 10587 Berlin, Germany.
Proc Biol Sci ; 290(1992): 20222115, 2023 02 08.
Article em En | MEDLINE | ID: mdl-36722081
Mapping the eco-evolutionary factors shaping the development of animals' behavioural phenotypes remains a great challenge. Recent advances in 'big behavioural data' research-the high-resolution tracking of individuals and the harnessing of that data with powerful analytical tools-have vastly improved our ability to measure and model developing behavioural phenotypes. Applied to the study of behavioural ontogeny, the unfolding of whole behavioural repertoires can be mapped in unprecedented detail with relative ease. This overcomes long-standing experimental bottlenecks and heralds a surge of studies that more finely define and explore behavioural-experiential trajectories across development. In this review, we first provide a brief guide to state-of-the-art approaches that allow the collection and analysis of high-resolution behavioural data across development. We then outline how such approaches can be used to address key issues regarding the ecological and evolutionary factors shaping behavioural development: developmental feedbacks between behaviour and underlying states, early life effects and behavioural transitions, and information integration across development.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Evolução Biológica / Big Data Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Evolução Biológica / Big Data Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2023 Tipo de documento: Article