Catch Data Can Unravel Elasmobranch Aggregation Dynamics and Group Behaviours DOI Creative Commons
Alexandra G. McInturf, Maurício Cantor, Ian A. Bouyoucos

et al.

Ecology and Evolution, Journal Year: 2025, Volume and Issue: 15(4)

Published: March 30, 2025

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

Language: Английский

Catch Data Can Unravel Elasmobranch Aggregation Dynamics and Group Behaviours DOI Creative Commons
Alexandra G. McInturf, Maurício Cantor, Ian A. Bouyoucos

et al.

Ecology and Evolution, Journal Year: 2025, Volume and Issue: 15(4)

Published: March 30, 2025

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

Language: Английский

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