Collaborative Research: Group Structure, Hydrodynamics, and Sensing of Squids during Collective Swimming

This study focuses on understanding the potential hydrodynamic benefits of moving in groups (schooling and shoaling) in squids (Cephalopod Mollusks). Squids are ideal for this investigation because they form groups that vary greatly in size and in the degree of coordinated movements, use both a pulsed jet and dynamic fin movements for propulsion, swim forward or backward with ease, and have distinctive sensory capabilities. Organization into groups such as schools and shoals is a common feature of many aquatic animals. Although longstanding research has shown that the value of such group behaviors may include improved foraging, more rapid communication, and heightened predator detection and avoidance, the energetic costs of swimming may also be reduced. Using 3D body tracking, volumetric flow imaging, and advanced analysis tools, three different species of squids will be studied swimming in nature, against currents in water tunnels, and while sensory systems have been temporarily disabled. The goal is to identify organizational patterns and flow conditions that improve swimming efficiency in squid schools and shoals, and to determine how sensory input is used to achieve and maintain positioning within a group. In addition to providing tools and techniques for the development of swarms of underwater autonomous vehicles, the project will train a post-doctoral fellow and undergraduate and graduate students, provide hands-on experiences for middle- and high-school students, and facilitate public education through collaborations with aquariums and science communicators. Despite the significance of schooling and shoaling in aquatic animals and the importance of cephalopods to food web dynamics and global fisheries, surprisingly little is known about how squids position themselves relative to neighbors and neighbor-induced flows in schools, whether energetic costs are reduced in schools, or what role that sensing systems play in these configurations. This study seeks to: (1) quantify squid aggregations in nature using 3D tracking cameras and software, focusing on how positioning changes with group speed and species; (2) correlate the 3D positions of animals in the group with 3D flow fields recorded from squids swimming in water tunnels and nature, with the goal of identifying propulsively efficient configurations and tracking how these integrated elements change with group speed and across species; and (3) examine the relative importance of vision and vibration-sensing via epidermal hairs for collective behaviors. Integral to these aims is the implementation of graph matching and cluster analyses to characterize animal positions and wake features. The project will be the first to quantify squid group behaviors and integrate 3D spatial tracking with 3D velocimetry to understand how group dynamics change according to speed-specific gaits. This project will address an important understudied hydrodynamic aspect of swimming – pulsed jetting and finning within aggregations – and examine whether vision and/or vibration-sensing are required for group structure. Furthermore, the project promises to develop powerful, empirical tools for identifying baseline principles for schooling across multiple taxa. The techniques developed and data collected in this project can be applied to bioinspired underwater robot swarm development, information sharing routines for autonomous systems, and graph-matching applications in artificial intelligence (AI) and social network analysis. The research and training activities align with both Biotechnology and AI priorities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.