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Leveraging big data to uncover the eco-evolutionary factors shaping behavioural development.

Sean M EhlmanUlrike SchererDavid BierbachFritz A FranciscoKate L LaskowskiJens KrauseMax Wolf
Published in: Proceedings. Biological sciences (2023)
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.
Keyphrases
  • big data
  • high resolution
  • artificial intelligence
  • machine learning
  • early life
  • healthcare
  • genome wide
  • mass spectrometry
  • risk assessment
  • climate change
  • gene expression
  • deep learning