Distributions of Lake Fishes in the Northeast: II. The Minnows (Cyprinidae)

Whittier, Thomas R.; Halliwell, David B.; Daniels, Robert A.

doi:10.2307/3858647

Cited by 12 publications

(16 citation statements)

References 12 publications

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“…Pairs of golden shiners were placed in a large shallow tank and filmed from above at high spatial and temporal resolution. Shoals were approximately two-dimensional, which is appropriate as shiners often occupy shallow lakes in the wild (38,39). In order to quantify fish behavior, we used custom tracking software to convert over 13 h of video data per group size for 2-and 3-fish shoals and over 6 h of video data per group size for 10-and 30-fish shoals into trajectories consisting of the center-of-mass positions of each fish at each point in time (see SI Materials and Methods).…”

Section: Resultsmentioning

confidence: 99%

Inferring the structure and dynamics of interactions in schooling fish

Katz

Tunstrøm

Ioannou

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

855

896

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Determining individual-level interactions that govern highly coordinated motion in animal groups or cellular aggregates has been a long-standing challenge, central to understanding the mechanisms and evolution of collective behavior. Numerous models have been proposed, many of which display realistic-looking dynamics, but nonetheless rely on untested assumptions about how individuals integrate information to guide movement. Here we infer behavioral rules directly from experimental data. We begin by analyzing trajectories of golden shiners (Notemigonus crysoleucas) swimming in two-fish and three-fish shoals to map the mean effective forces as a function of fish positions and velocities. Speeding and turning responses are dynamically modulated and clearly delineated. Speed regulation is a dominant component of how fish interact, and changes in speed are transmitted to those both behind and ahead. Alignment emerges from attraction and repulsion, and fish tend to copy directional changes made by those ahead. We find no evidence for explicit matching of body orientation. By comparing data from two-fish and three-fish shoals, we challenge the standard assumption, ubiquitous in physics-inspired models of collective behavior, that individual motion results from averaging responses to each neighbor considered separately; three-body interactions make a substantial contribution to fish dynamics. However, pairwise interactions qualitatively capture the correct spatial interaction structure in small groups, and this structure persists in larger groups of 10 and 30 fish. The interactions revealed here may help account for the rapid changes in speed and direction that enable real animal groups to stay cohesive and amplify important social information.A fundamental problem in a wide range of biological disciplines is understanding how functional complexity at a macroscopic scale (such as the functioning of a biological tissue) results from the actions and interactions among the individual components (such as the cells forming the tissue). Animal groups such as bird flocks, fish schools, and insect swarms frequently exhibit complex and coordinated collective behaviors and present unrivaled opportunities to link the behavior of individuals with dynamic group-level properties. With the advent of tracking technologies such as computer vision and global positioning systems, group behavior can be reduced to a set of trajectories in space and time. Consequently, in principle, it is possible to deduce the individual interaction rules starting from the observed kinematics. However, calculating interindividual interactions from trajectories means solving a fundamental inverse problem that appears universally in many-body systems. In general, such problems are very hard to solve and, even if they can be solved, their solution is often not unique.To avoid solving these inverse problems (and because detailed kinematic data were not available until recently), many attempts have been made to replicate the patterns observed in animal groups by...

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Section: Resultsmentioning

confidence: 99%

Inferring the structure and dynamics of interactions in schooling fish

Katz

Tunstrøm

Ioannou

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

855

896

View full text Add to dashboard Cite

show abstract

“…We studied free-swimming groups of juvenile golden shiners (Notemigonus crysoleucas), a widespread species of freshwater fish that swims close to the water surface (30) and whose schooling behavior is well characterized by vision (16) [in this species, the lateral line is thought to contribute minimally to schooling (31,32)]. Like many juvenile fish (33), shiners experience very high mortality due to predation; abundance is limited by predation rather than food availability (34).…”

Section: Resultsmentioning

confidence: 99%

Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion

Rosenthal¹,

Twomey

Hartnett³

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

423

453

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Coordination among social animals requires rapid and efficient transfer of information among individuals, which may depend crucially on the underlying structure of the communication network. Establishing the decision-making circuits and networks that give rise to individual behavior has been a central goal of neuroscience. However, the analogous problem of determining the structure of the communication network among organisms that gives rise to coordinated collective behavior, such as is exhibited by schooling fish and flocking birds, has remained almost entirely neglected. Here, we study collective evasion maneuvers, manifested through rapid waves, or cascades, of behavioral change (a ubiquitous behavior among taxa) in schooling fish (Notemigonus crysoleucas). We automatically track the positions and body postures, calculate visual fields of all individuals in schools of ∼150 fish, and determine the functional mapping between socially generated sensory input and motor response during collective evasion. We find that individuals use simple, robust measures to assess behavioral changes in neighbors, and that the resulting networks by which behavior propagates throughout groups are complex, being weighted, directed, and heterogeneous. By studying these interaction networks, we reveal the (complex, fractional) nature of social contagion and establish that individuals with relatively few, but strongly connected, neighbors are both most socially influential and most susceptible to social influence. Furthermore, we demonstrate that we can predict complex cascades of behavioral change at their moment of initiation, before they actually occur. Consequently, despite the intrinsic stochasticity of individual behavior, establishing the hidden communication networks in large self-organized groups facilitates a quantitative understanding of behavioral contagion.T he social transmission of behavioral change is central to collective animal behavior. For many mobile groups, such as schooling fish and flocking birds, social contagion can be fast, resulting in dramatic waves of response (1-6). Such waves are evident in particular when individuals are under threat of attack from predators (1). Despite the ubiquity and importance of behavioral contagion, and the fact that survival depends on how individual interactions scale to collective properties (2), we still know very little about the sensory basis and mechanism of such coordinated collective response.In the early 20th century, Edmund Selous proposed that rapid waves of turning in large flocks of birds resulted from a direct transference of thoughts among animals: "They must think collectively, all at the same time. . . a flash out of so many brains" (3). By the mid-1950s, however, attention had turned from telepathy to synchrony arising from the rapid transmission of local behavioral response to neighbors, with some of the first experimental studies of cascading behavioral change undertaken by Dimitrii Radakov (4). Radakov (4) hand-traced the paths of each fish, frame-by-fram...

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“…Here we investigate the emergence of macroscopic collective states under highly controlled laboratory conditions using schooling fish (golden shiner, Notemigonus crysoleucas ). This is a convenient model system for investigating collective behavior since individuals are relatively small (average length approximately 5 cm in our study), and naturally form highly cohesive schools in very shallow and still water [21]. Digital tracking of fish in a range of group sizes (from 30 to 300 fish) allows us to obtain detailed data regarding the individual positions and velocities of schooling fish over long periods of time.…”

Section: Introductionmentioning

confidence: 99%

Collective States, Multistability and Transitional Behavior in Schooling Fish

et al. 2013

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The spontaneous emergence of pattern formation is ubiquitous in nature, often arising as a collective phenomenon from interactions among a large number of individual constituents or sub-systems. Understanding, and controlling, collective behavior is dependent on determining the low-level dynamical principles from which spatial and temporal patterns emerge; a key question is whether different group-level patterns result from all components of a system responding to the same external factor, individual components changing behavior but in a distributed self-organized way, or whether multiple collective states co-exist for the same individual behaviors. Using schooling fish (golden shiners, in groups of 30 to 300 fish) as a model system, we demonstrate that collective motion can be effectively mapped onto a set of order parameters describing the macroscopic group structure, revealing the existence of at least three dynamically-stable collective states; swarm, milling and polarized groups. Swarms are characterized by slow individual motion and a relatively dense, disordered structure. Increasing swim speed is associated with a transition to one of two locally-ordered states, milling or highly-mobile polarized groups. The stability of the discrete collective behaviors exhibited by a group depends on the number of group members. Transitions between states are influenced by both external (boundary-driven) and internal (changing motion of group members) factors. Whereas transitions between locally-disordered and locally-ordered group states are speed dependent, analysis of local and global properties of groups suggests that, congruent with theory, milling and polarized states co-exist in a bistable regime with transitions largely driven by perturbations. Our study allows us to relate theoretical and empirical understanding of animal group behavior and emphasizes dynamic changes in the structure of such groups.

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Distributions of Lake Fishes in the Northeast: II. The Minnows (Cyprinidae)

Cited by 12 publications

References 12 publications

Inferring the structure and dynamics of interactions in schooling fish

Inferring the structure and dynamics of interactions in schooling fish

Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion

Collective States, Multistability and Transitional Behavior in Schooling Fish

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