Prospecting and informed dispersal: Understanding and predicting their joint eco-evolutionary dynamics

Active breeding seabirds prospect alternative breeding colonies

Compared to other animal movements, prospecting by adult individuals for a future breeding site is commonly overlooked. Prospecting influences the decision of where to breed and has consequences on fitness and lifetime reproductive success. By analysing movements of 31 satellite- and GPS-tracked gull and tern populations belonging to 14 species in Europe and North America, we examined the occurrence and factors explaining prospecting by actively breeding birds. Prospecting in active breeders occurred in 85.7% of studied species, across 61.3% of sampled populations. Prospecting was more common in populations with frequent inter-annual changes of breeding sites and among females. These results contradict theoretical models which predict that prospecting is expected to evolve in relatively predictable and stable environments. More long-term tracking studies are needed to identify factors affecting patterns of prospecting in different environments and understand the consequences of prospecting on fitness at the individual and population level.

Importance of interindividual interactions in eco-evolutionary population dynamics: The rise of demo-genetic agent-based models

The study of eco-evolutionary dynamics, that is of the intertwinning between ecological and evolutionary processes when they occur at comparable time scales, is of growing interest in the current context of global change. However, many eco-evolutionary studies overlook the role of interindividual interactions, which are hard to predict and yet central to selective values. Here, we aimed at putting forward models that simulate interindividual interactions in an eco-evolutionary framework: the demo-genetic agent-based models (DG-ABMs). Being demo-genetic, DG-ABMs consider the feedback loop between ecological and evolutionary processes. Being agent-based, DG-ABMs follow populations of interacting individuals with sets of traits that vary among the individuals. We argue that the ability of DG-ABMs to take into account the genetic heterogeneity-that affects individual decisions/traits related to local and instantaneous conditions-differentiates them from analytical models, another type of model largely used by evolutionary biologists to investigate eco-evolutionary feedback loops. Based on the review of studies employing DG-ABMs and explicitly or implicitly accounting for competitive, cooperative or reproductive interactions, we illustrate that DG-ABMs are particularly relevant for the exploration of fundamental, yet pressing, questions in evolutionary ecology across various levels of organization. By jointly modelling the effects of management practices and other eco-evolutionary processes on interindividual interactions and population dynamics, DG-ABMs are also effective prospective and decision support tools to evaluate the short- and long-term evolutionary costs and benefits of management strategies and to assess potential trade-offs. Finally, we provide a list of the recent practical advances of the ABM community that should facilitate the development of DG-ABMs.