Spatial eco-evolutionary feedbacks mediate coexistence in prey-predator systems

Eco-evolutionary dynamics of cooperation in the presence of policing

Ecology and evolution are inherently linked, and studying a mathematical model that considers both holds promise of insightful discoveries related to the dynamics of cooperation. In the present article, we use the prisoner's dilemma (PD) game as a basis for long-term apprehension of the essential social dilemma related to cooperation among unrelated individuals. We upgrade the contemporary PD game with an inclusion of evolution-induced act of punishment as a third competing strategy in addition to the traditional cooperators and defectors. In a population structure, the abundance of ecologically-viable free space often regulates the reproductive opportunities of the constituents. Hence, additionally, we consider the availability of free space as an ecological footprint, thus arriving at a simple eco-evolutionary model, which displays fascinating complex dynamics. As possible outcomes, we report the individual dominance of cooperators and defectors as well as a plethora of mixed states, where different strategies coexist followed by maintaining the diversity in a socio-ecological framework. These states can either be steady or oscillating, whereby oscillations are sustained by cyclic dominance among different combinations of cooperators, defectors, and punishers. We also observe a novel route to cyclic dominance where cooperators, punishers, and defectors enter a coexistence via an inverse Hopf bifurcation that is followed by an inverse period doubling route.

Eco-Evolutionary Feedbacks and the Maintenance of Metacommunity Diversity in a Changing Environment

The presence and strength of resource competition can influence how organisms adaptively respond to environmental change. Selection may thus reflect a balance between two forces, adaptation to an environmental optimum and evolution to avoid strong competition. While this phenomenon has previously been explored in the context of single communities, its implications for eco-evolutionary dynamics at the metacommunity scale are largely unknown. We developed a simulation model for the evolution of a quantitative trait that influences both an organism's carrying capacity and its intra- and interspecific competitive ability. In the model, multiple species inhabit a three-patch landscape, and we investigated the effect of varying the connectivity level among patches, the presence and pace of directional environmental change, and the strength of competition between the species. Our model produced some patterns previously observed in evolving metacommunity models, such as species sorting and community monopolization. However, we found that species sorting was diminished even at low rates of dispersal and was influenced by competition strength, and that monopolization was observed only when environmental change was very rapid. We also detected an eco-evolutionary feedback loop between local phenotypic evolution at one site and competition at another site, which maintains species diversity in some conditions. The existence of a feedback loop maintained by dispersal indicates that eco-evolutionary dynamics in communities operate at a landscape scale.

How range residency and long-range perception change encounter rates

Encounter rates link movement strategies to intra- and inter-specific interactions, and therefore translate individual movement behavior into higher-level ecological processes. Indeed, a large body of interacting population theory rests on the law of mass action, which can be derived from assumptions of Brownian motion in an enclosed container with exclusively local perception. These assumptions imply completely uniform space use, individual home ranges equivalent to the population range, and encounter dependent on movement paths actually crossing. Mounting empirical evidence, however, suggests that animals use space non-uniformly, occupy home ranges substantially smaller than the population range, and are often capable of nonlocal perception. Here, we explore how these empirically supported behaviors change pairwise encounter rates. Specifically, we derive novel analytical expressions for encounter rates under Ornstein-Uhlenbeck motion, which features non-uniform space use and allows individual home ranges to differ from the population range. We compare OU-based encounter predictions to those of Reflected Brownian Motion, from which the law of mass action can be derived. For both models, we further explore how the interplay between the scale of perception and home-range size affects encounter rates. We find that neglecting realistic movement and perceptual behaviors can lead to systematic, non-negligible biases in encounter-rate predictions.