Adaptive aggregation behavior of the scallop Mizuhopecten yessoensis in response to predation risk

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Abstract

Aggregation behavior in scallops, beyond known individual escape responses, may serve as an active defense against predators. We investigated this possibility in the scallop Mizuhopecten yessoensis facing the predatory sea star Distolasterias nipon. Using controlled tank experiments with varying scallop and predator densities, we analyzed individual spatial distribution, activity levels, and aggregation dynamics via automated video tracking and Bayesian statistical modeling. Results revealed density-dependent baseline spatial patterns (uniform spacing and aggregation at low and high densities, respectively) While predator presence and higher scallop density generally increased aggregation frequency, aggregation "maintenance" was distinctly controlled by different mechanisms: group size strongly promoted maintenance duration, whereas the number of predators destabilized aggregations. Complexity emerged at high density, where a single predator paradoxically induced uniform spacing, potentially via disturbance-driven dispersion, while two predators induced strong aggregation. A key finding supporting active strategic adjustment was a non-linear relationship between predator disturbance level and aggregation maintenance duration, peaking at moderate disturbance levels ("optimal disturbance hypothesis"). Furthermore, a separate experiment confirmed that scallops possess the ability to recognize and approach conspecifics via chemical signals under predation risk, suggesting a foundation for active aggregation mechanisms. Collectively, our findings demonstrate that scallop aggregation is not merely passive assembly but a complex and active adaptive strategy, dynamically adjusted based on assessments of conspecific density, group dynamics, and nuanced predation risk (presence, number, and disturbance levels). This study enhances our understanding of complex bivalve behavior and predator-prey interactions, offering new insights for resource management.

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