Animal dispersal modelling: Handling landscape features and related animal choices

Abstract

Animal dispersal in a fragmented landscape depends on the complex interaction between landscape structure and animal behavior. To better understand how individuals disperse, it is important to explicitly represent the properties of organisms and the landscape in which they move. A common approach to modelling dispersal includes representing the landscape as a grid of equal sized cells and then simulating individual movement as a correlated random walk. This approach uses a priori scale of resolution, which limits the representation of all landscape features and how different dispersal abilities are modelled.We develop a vector-based landscape model coupled with an object-oriented model for animal dispersal. In this spatially explicit dispersal model, landscape features are defined based on their geographic and thematic properties and dispersal is modelled through consideration of an organism's behavior, movement rules and searching strategies (such as visual cues). We present the model's underlying concepts, its ability to adequately represent landscape features and provide simulation of dispersal according to different dispersal abilities. We demonstrate the potential of the model by simulating two virtual species in a real Swiss landscape. This illustrates the model's ability to simulate complex dispersal processes and provides information about dispersal such as colonization probability and spatial distribution of the organism's path.

Random walk models in biology

“…We have discussed very simple environmental interactions (relating to simple changes in transition probabilities in a RRW) but, in reality, most animals (and many micro-organisms) are highly developed and able to interact extensively with their environment to optimize search strategies. Furthermore, most of the simple models discussed here implicitly assume homogeneous (or at most very simple heterogeneous) environments, whereas most real environments are highly complicated with barriers and differential terrain over all three dimensions that will affect movement behaviour and speed (Vuilleumier & Metzger 2006). Distinguishing between changes in behaviour due to environmental or spatial interactions simply by observing and analysing movements will always be difficult without further biological information.…”

Modelling the Constraints of Spatial Environment in Fauna Movement Simulations: Comparison of a Boundaries Accurate Function and a Cost Function

“…For each unit, landscape elements are associated with a cost value and a function estimates the cost, or the facility, for individuals to move from a starting point towards various directions (La Morgia et al, 2011;Palmer et al, 2011). Object-oriented programming formalizes explicitly the characteristics and the properties of individuals as well as those of their environment (Vuilleumier & Metzger, 2006). What we called statistical approaches integrates equations that evaluate the probability of movement in a direction.…”

Where do we go from here? Dispersal simulations shed light on the role of landscape structure in determining animal redistribution after reintroduction

“…under the assumption of environmental homogeneity). In contrast, animal species can perceive the landscape structure and have complex strategies for foraging and dispersal (Gustafson and Gardner 1996;Vuilleumier and Metzger 2006). To tacke this and other issues, basic diffusion models have been widely extended, being actually able to incorporate information on biased/correlated movement directions, on interaction among individuals and in particular on habitat heterogeneity (Turchin 1998, Ovaskainen 2004.…”

“…Due to the difficulty in gathering data on animal dispersal, simulation models have become a cost-effective approach to understand dispersal dynamics (Vuilleumier and Metzger 2006). They can be based on the assumption of diffusive movement (Okubo 1980) and they can employ simple random walks, if simulations are preferred to analytical solutions.…”

“…We considered that both the perceptual range and the dispersal distance are important parameters in modelling animal dispersal (Vuilleumier and Metzger 2006). Taking into account deer biology and body size, we assumed that coupling our scale of resolution (250×250 m) with a perceptual distance of the eight nearest-neighbouring cells could be adequate for the analyses.…”