Inferring the rules of interaction of shoaling fish

Abstract

Collective motion, where large numbers of individuals move synchronously together, is achieved when individuals adopt interaction rules that determine how they respond to their neighbors' movements and positions. These rules determine how group-living animals move, make decisions, and transmit information between individuals. Nonetheless, few studies have explicitly determined these interaction rules in moving groups, and very little is known about the interaction rules of fish. Here, we identify three key rules for the social interactions of mosquitofish (Gambusia holbrooki): (i) Attraction forces are important in maintaining group cohesion, while we find only weak evidence that fish align with their neighbor's orientation; (ii) repulsion is mediated principally by changes in speed; (iii) although the positions and directions of all shoal members are highly correlated, individuals only respond to their single nearest neighbor. The last two of these rules are different from the classical models of collective animal motion, raising new questions about how fish and other animals self-organize on the move.collective animal behavior | fish shoals | group motion | self-propelled particles | self-organization C ollective motion of animal groups occurs when multiple individuals move synchronously, producing large scale "flocking" patterns (1-5). Numerous models have been developed to describe patterns of collective motion in terms of interactions between individuals (6-9). These simulation models usually assume that individuals move at a constant speed and their interactions are mediated through direction changes (1). Often these models use zonal rules, where individuals move away from neighbors at close distances and align and/or move toward neighbors at greater distances. Interactions can be with either all neighbors within some zone (7) or with a set of n nearest neighbors (10). These and other models have succeeded in reproducing qualitatively similar patterns to those seen in the collective motion of animal groups in nature.It remains unclear, however, whether the interaction rules implemented in models are the ones used by animals. Indeed, many collective motion patterns observed in nature can be simulated by models using very different interaction rules (1). We are only now beginning to accumulate evidence about which interaction rules are used. There has been recent identification of zones of repulsion and alignment in surf scoters (11). The structure of starling flocks is consistent with topological interactions between the birds (10). Homing pigeons appear to have hierarchical interactions such that birds with higher route-following fidelity act as leaders (12)(13)(14)(15). Partridge showed that lateral line and vision are both important in producing directional alignment in Gadid fish (16). Nonetheless, there remain a large number of open questions about the interactions of fish. For example, do fish adopt attraction and alignment within distinct zones as purported in most models? How many neighbors do fish ...

Shoal size as a key determinant of vulnerability to capture under a simulated fishery scenario

“…Another possibility is that some level of sensory saturation occurred constraining decision‐making and therefore affecting the rate of capture. Even in large moving shoals fish are known to limit their interactions to a few neighbors in their vicinity (Herbert‐Read et al., 2011; Tien, Levin, & Rubenstein, 2004). In our study, the greater number of individuals in IND +6 , rapidly moving and offering simultaneous and contrasting information in proximity of the trap possibly led to a plateau in capture efficiency.…”

The role of individuality in collective group movement

“…From these data, we calculated each fish's median speed, variance in speed and median turning speed across each trial (see electronic supplementary material, figure S1 for details of calculations and average values for different group sizes). We chose to measure these parameters (i) because they are associated with behaviours such as exploration, navigation and foraging [27,28], (ii) because they are important in the social interactions between shoaling fish [2,4], and (iii) because they are easily quantifiable between the two contexts of interest. We calculated each group's average polarization [9] over the course of the trial (see electronic supplementary material).…”

“…This in turn allows groups to maintain their coherence and enables group members to realize the benefits of group living [7]. To date, however, most studies of collective behaviour have assumed that group members are identical in their movements and responses to their neighbours [2][3][4] (but see [8][9][10] for theoretical predictions and [11,12] for empirical observations about individual differences in groups). This common assumption of homogeneity contrasts with a large and growing body of work documenting consistent inter-individual differences in behaviour [13][14][15][16][17][18] and evidence that differences in the social affiliations between group members, and individual differences, can affect leadership and the collective decision-making process [12,19,20].…”

“…Group-level properties, such as the collective movements of animal groups, emerge when individuals respond to the location and movements of their near neighbours [2][3][4]. This responsiveness to the behaviour of neighbours allows consensus to be reached over the timing and direction of group movements [5,6].…”

Automated image-based tracking and its application in ecology

“…Recent break throughs in remote quantification of physical landscapes [58 60] and 3D imaging [29] should be especially helpful for these questions. Second, collective behavior in animal groups [1,26,33,38,40,43,45,62,82,83], including understanding how information about the physical and biological environment transfers between individuals. Generally, this research centers on intraspecific groups comprising large numbers of similar sized individuals.…”