Modelling animal contests based on spatio-temporal dynamics.

We present a general theoretical model for the spatio-temporal dynamics of animal contests. Inspired by interactions between physical particles, the model is formulated in terms of effective interaction potentials, which map typical elements of contest behaviour into empirically verifiable rules of contestant motion. This allows us to simulate the observable dynamics of contests in various realistic scenarios, notably in dyadic contests over a localized resource. Assessment strategies previously formulated in game-theoretic models, as well as the effects of fighting costs, can be described as variations in our model's parameters. Furthermore, the trends of contest duration associated with these assessment strategies can be derived and understood within the model. Detailed description of the contestants' motion enables the exploration of spatio-temporal properties of asymmetric contests, such as the emergence of chase dynamics. Overall, our framework aims to bridge the growing gap between empirical capabilities and theory in this widespread aspect of animal behaviour.

Ants resort to majority concession to reach democratic consensus in the presence of a persistent minority.

Social groups often need to overcome differences in individual interests and knowledge to reach consensus decisions. Here, we combine experiments and modeling to study conflict resolution in emigrating ant colonies during binary nest selection. We find that cohesive emigration, without fragmentation, is achieved only by intermediate-sized colonies. We then impose a conflict regarding the desired emigration target between colony subgroups. This is achieved using an automated selective gate system that manipulates the information accessible to each ant. Under this conflict, we find that individuals concede their potential benefit to promote social consensus. In particular, colonies resolve the conflict imposed by a persistent minority through "majority concession," wherein a majority of ants that hold first-hand knowledge regarding the superior quality nest choose to reside in the inferior one. This outcome is unlikely in social groups of selfish individuals and emphasizes the importance of group cohesion in eusocial societies. VIDEO ABSTRACT.

Spatiotemporal dynamics of animal contests arise from effective forces between contestants.

Competition among animals for resources, notably food, territories, and mates, is ubiquitous at all scales of life. This competition is often resolved through contests among individuals, which are commonly understood according to their outcomes and in particular, how these outcomes depend on decision-making by the contestants. Because they are restricted to end-point predictions, these approaches cannot predict real-time or real-space dynamics of animal contest behavior. This limitation can be overcome by studying systems that feature typical contest behavior while being simple enough to track and model. Here, we propose to use such systems to construct a theoretical framework that describes real-time movements and behaviors of animal contestants. We study the spatiotemporal dynamics of contests in an orb-weaving spider, in which all the common elements of animal contests play out. The confined arena of the web, on which interactions are dominated by vibratory cues in a two-dimensional space, simplifies the analysis of interagent interactions. We ask whether these seemingly complex decision-makers can be modeled as interacting active particles responding only to effective forces of attraction and repulsion due to their interactions. By analyzing the emergent dynamics of "contestant particles," we provide mechanistic explanations for real-time dynamical aspects of animal contests, thereby explaining competitive advantages of larger competitors and demonstrating that complex decision-making need not be invoked in animal contests to achieve adaptive outcomes. Our results demonstrate that physics-based classification and modeling, in terms of effective rules of interaction, provide a powerful framework for understanding animal contest behaviors.