“Perchance to dream?”: Assessing the effects of dispersal strategies on the fitness of expanding populations

Unraveling the patterns of animals’ movements is crucial to understanding the basics of biogeography, tracking range shifts resulting from climate change, and predicting and preventing biological invasions. Many researchers have modeled animals’ dispersal under the assumptions of various movement strategies, either predetermined or directed by external factors, but none have compared the effects of different movement strategies on population survival and fitness. In this paper, using an agent-based model with a landscape divided into cells of varying quality, we compare the ecological success of three movement and habitat selection strategies (MHSSs): (i) Smart, in which animals choose the locally optimal cell; (ii) Random, in which animals move randomly between cells without taking into account their quality; (iii) Dreamer, in which animals attempt to find a habitat of dream whose quality is much higher than that of the habitat available on the map. We compare the short-term success of these MHSSs in good, medium and bad environments. We also assess the effect of temporal variation of habitat quality (specifically, winter harshness) on the success of each MHSS. Success is measured in terms of survival rate, dispersal distance, accumulated energy and quality of settled habitat. The most general conclusion is that while survival rate, accumulated energy and quality of settled habitat are affected primarily by overall habitat composition (proportions of different habitat types in the landscape), dispersal distance depends mainly on the MHSS. In medium and good environments, the Dreamer strategy is highly successful: it simultaneously outperforms the Smart strategy in dispersal distance and the Random strategy in terms of the other metrics.