A physiologically-based model of a self-motivated hare in relation to its ecology

The use of individually-based, detail-rich, simulation models for the study of the behavioral ecology of wildlife is expanding for their ability to link evolutionary processes operating at the individual level (e.g. optimal foraging) to ecological and demographic processes usually described at the population level. Within this modelling framework, we tested the possibility of using artificial intelligence (AI) methods and object-oriented programming (OOP) to implement behavioral processes in a physiologically-based model of the hare (Lepus spp.). This approach is interesting and partly innovative because the behavioral rules which ‘move’ the animals are based on the simulation of the decision-making system itself. Moreover in this model both the landscape and the behavior of a predator species (the fox) are taken into account. The model is quite complex and its dynamics exhibits interesting emergent proprieties which have not been specifically wired in. It has been internally validated and a careful calibration of the different subsystems has been attempted with respect to the actual behavior of hares. The simulated hare exhibits a quite stable ethogram under variable environmental conditions and performs both state-conditioned activities and an adaptive behavioral strategy, where the animalʹs behavior is modified as a function of the environmental conditions in order to maintain a constant (and positive) fitness level.