Clustering through pair interactions in swimming zooplankton

TL;DR

This paper models how pair interactions among swimming zooplankton can lead to clustering, combining random movement and attraction, supported by analysis of real copepod trajectory data.

Contribution

It introduces a particle interaction model that explains zooplankton clustering and validates it with empirical 3D trajectory data.

Findings

Model supports clustering similar to colloid aggregation

Empirical data aligns with the model's predictions

Pair interactions promote mating aggregates overcoming diffusive search

Abstract

This work focuses on the formation of mating aggregates in zooplankton. In particular, sexual encounters are behaviourally supported by males actively swimming in search for females, and approaching them for mating once they are found. While the random search leads to a diffusive flux of individuals, the approaching for encounter supports attraction. Thus, we ask whether these competing mechanisms of diffusion and attraction can support aggregation and lead to the formation of mating clusters. To answer our question we formulate a model in which particles performing random walks can briefly make contact with other particles if they are found within a particular distance from each other. Our analysis shows that this model supports clustering in a way analogous to the process of colloid aggregation. Following that, we analyze a dataset of 3D trajectories of swimming copepods and show that the results compare well with our model. These results support the hypothesis that pair-interactions promote mating aggregates in zooplankton and are sufficient to overcome the diffusive nature of their mate searching behavior. Our results are useful for understanding small-scale clustering of zooplankton, which is crucial for predicting encounter rates and reproduction rates in the ocean.