McInturf, A.G., Cantor, M., Bouyoucos, I.A., Chapple, T.K., Debaere, S.F., Eustache, K., Mourier, J., Planes, S., Sulikowski, J.A., Zillig, K.W., Fangue, N.A., and Rummer, J.L. (2025) Catch Data Can Unravel Elasmobranch Aggregation Dynamics and Group Behaviours. Ecology and Evolution, 15 (4). e71107.

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Abstract

Elasmobranchs (i.e., sharks, skates, rays), known for their cognitive abilities and complex behaviours, often form aggregations that are thought to be crucial for their survival and evolutionary success. However, understanding the drivers behind these aggregations remains challenging due to the dynamism of the marine environment and the difficulty of observing these species directly. Here, we aim to address these challenges by introducing a methodological framework for analysing catch data to infer aggregation behaviour. Within this framework, we outline key metrics to explore, such as the number and density of individuals captured, phenotypic traits, drivers of co-occurrence, individual identification, and kin structure. We then demonstrate how to use this framework in a case study of juvenile blacktip reef sharks (Carcharhinus melanopterus) in Moorea, French Polynesia, to determine its real-world application and identify potential limitations. Our results reveal that juvenile blacktip reef sharks around Moorea tend to aggregate during early life stages and that these aggregations appear non-social, indicative of environmental rather than social drivers. We also find that, while catch data can provide valuable insights into elasmobranch aggregations, they must be complemented with targeted research methods to maximise the available data advised within our framework. As findings from our case study demonstrate, this framework has the capacity to broaden our knowledge of elasmobranch aggregations and social behaviours, underscoring the importance of dedicated efforts in research and conservation to manage these vulnerable species effectively.

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