Emergence of collective changes in travel direction of starling flocks from individual birds fluctuations

One of the most impressive features of moving animal groups is their ability to perform sudden coherent changes in travel direction. While this collective decision can be a response to an external perturbation, such as the presence of a predator, recent studies show that such directional switching can also emerge from the intrinsic fluctuations in the individual behaviour. However, the cause and the mechanism by which such collective changes of direction occur are not fully understood yet. Here, we present an experimental study of spontaneous collective turns in natural flocks of starlings. We employ a recently developed tracking algorithm to reconstruct three-dimensional trajectories of each individual bird in the flock for the whole duration of a turning event. Our approach enables us to analyze changes in the individual behavior of every group member and reveal the emergent dynamics of turning. We show that spontaneous turns start from individuals located at the elongated edges of the flocks, and then propagate through the group. We find that birds on the edges deviate from the mean direction of motion much more frequently than other individuals, indicating that persistent localized fluctuations are the crucial ingredient for triggering a collective directional change. Finally, we quantitatively show that birds follow equal radius paths during turning allowing the flock to change orientation and redistribute risky locations among group members. The whole process of turning is a remarkable example of how a self-organized system can sustain collective changes and reorganize, while retaining coherence.Comment: 18 pages, 2 Videos adde

Flocking with Obstacle Avoidance

In this paper, we provide a dynamic graph theoretical framework for flocking in presence of multiple obstacles. In particular, we give formal definitions of nets and flocks as spatially induced graphs. We provide models of nets and flocks and discuss the realization/embedding issues related to structural nets and flocks. This allows task representation and execution for a network of agents called alpha-agents. We also consider flocking in the presence of multiple obstacles. This task is achieved by introducing two other types of agents called beta-agents and gamma-agents. This framework enables us to address split/rejoin and squeezing maneuvers for nets/flocks of dynamic agents that communicate with each other. The problems arising from switching topology of these networks of mobile agents make the analysis and design of the decision-making protocols for such networks rather challenging. We provide simulation results that demonstrate the effectiveness of our theoretical and computational tools

Flocking Behaviour: Agent-Based Simulation and Hierarchical Leadership

We have studied how leaders emerge in a group as a consequence of interactions among its members. We propose that leaders can emerge as a consequence of a self-organized process based on local rules of dyadic interactions among individuals. Flocks are an example of self-organized behaviour in a group and properties similar to those observed in flocks might also explain some of the dynamics and organization of human groups. We developed an agent-based model that generated flocks in a virtual world and implemented it in a multi-agent simulation computer program that computed indices at each time step of the simulation to quantify the degree to which a group moved in a coordinated way (index of flocking behaviour) and the degree to which specific individuals led the group (index of hierarchical leadership). We ran several series of simulations in order to test our model and determine how these indices behaved under specific agent and world conditions. We identified the agent, world property, and model parameters that made stable, compact flocks emerge, and explored possible environmental properties that predicted the probability of becoming a leader.Flocking Behaviour; Hierarchical Leadership; Agent-Based Simulation; Social Dynamics

Methods of quantitative and qualitative analysis of bird migration with a tracking radar

Methods of analyzing bird migration by using tracking radar are discussed. The procedure for assessing the rate of bird passage is described. Three topics are presented concerning the grouping of nocturnal migrants, the velocity of migratory flight, and identification of species by radar echoes. The height and volume of migration under different weather conditions are examined. The methods for studying the directions of migration and the correlation between winds and the height and direction of migrating birds are presented

Short-range interaction vs long-range correlation in bird flocks

Bird flocks are a paradigmatic example of collective motion. One of the prominent experimental traits discovered about flocks is the presence of long range velocity correlations between individuals, which allow them to influence each other over the large scales, keeping a high level of group coordination. A crucial question is to understand what is the mutual interaction between birds generating such nontrivial correlations. Here we use the Maximum Entropy (ME) approach to infer from experimental data of natural flocks the effective interactions between birds. Compared to previous studies, we make a significant step forward as we retrieve the full functional dependence of the interaction on distance and find that it decays exponentially over a range of a few individuals. The fact that ME gives a short-range interaction even though its experimental input is the long-range correlation function, shows that the method is able to discriminate the relevant information encoded in such correlations and single out a minimal number of effective parameters. Finally, we show how the method can be used to capture the degree of anisotropy of mutual interactions.Comment: 21 pages, 7 figures, 1 tabl

The Fast Wandering of Slow Birds

I study a single "slow" bird moving with a flock of birds of a different, and faster (or slower) species. I find that every "species" of flocker has a characteristic speed $\gamma\ne v_0$, where $v_0$ is the mean speed of the flock, such that, if the speed $v_s$ of the "slow" bird equals $\gamma$, it will randomly wander transverse to the mean direction of flock motion far faster than the other birds will: its mean-squared transverse displacement will grow in $d=2$ with time $t$ like $t^{5/3}$, in contrast to $t^{4/3}$ for the other birds. In $d=3$, the slow bird's mean squared transverse displacement grows like $t^{5/4}$, in contrast to $t$ for the other birds. If $v_s\neq \gamma$, the mean-squared displacement of the "slow" bird crosses over from $t^{5/2}$ to $t^{4/3}$ scaling in $d=2$, and from $t^{5/4}$ to $t$ scaling in $d=3$, at a time $t_c$ that scales according to $t_c \propto|v_s-\gamma|^{-2}$.Comment: 10 pages; 5 pages of which did not appear in earlier versions, but were added in response to referee's suggestion

Finite-size scaling as a way to probe near-criticality in natural swarms

Collective behaviour in biological systems is often accompanied by strong correlations. The question has therefore arisen of whether correlation is amplified by the vicinity to some critical point in the parameters space. Biological systems, though, are typically quite far from the thermodynamic limit, so that the value of the control parameter at which correlation and susceptibility peak depend on size. Hence, a system would need to readjust its control parameter according to its size in order to be maximally correlated. This readjustment, though, has never been observed experimentally. By gathering three-dimensional data on swarms of midges in the field we find that swarms tune their control parameter and size so as to maintain a scaling behaviour of the correlation function. As a consequence, correlation length and susceptibility scale with the system's size and swarms exhibit a near-maximal degree of correlation at all sizes.Comment: Selected for Viewpoint in Physics; PRL Editor's Suggestio

Symmetry-breaking phase-transitions in highly concentrated semen

New experimental evidence of self-motion of a confined active suspension is presented. Depositing fresh semen sample in an annular shaped micro- fluidic chip leads to a spontaneous vortex state of the fluid at sufficiently large sperm concentration. The rotation occurs unpredictably clockwise or counterclockwise and is robust and stable. Furthermore, for highly active and concentrated semen, richer dynamics can occur such as self-sustained or damped rotation oscillations. Experimental results obtained with systematic dilution provide a clear evidence of a phase transition toward collective motion associated with local alignment of spermatozoa akin to the Vicsek model. A macroscopic theory based on previously derived Self-Organized Hydrodynamics (SOH) models is adapted to this context and provides predictions consistent with the observed stationary motion