Building the bridge between animal movement and population dynamics

Abstract

While the mechanistic links between animal movement and population dynamics are ecologically obvious, it is much less clear when knowledge of animal movement is a prerequisite for understanding and predicting population dynamics. GPS and other technologies enable detailed tracking of animal location concurrently with acquisition of landscape data and information on individual physiology. These tools can be used to refine our understanding of the mechanistic links between behaviour and individual condition through 'spatially informed' movement models where time allocation to different behaviours affects individual survival and reproduction. For some species, socially informed models that address the movements and average fitness of differently sized groups and how they are affected by fission-fusion processes at relevant temporal scales are required. Furthermore, as most animals revisit some places and avoid others based on their previous experiences, we foresee the incorporation of long-term memory and intention in movement models. The way animals move has important consequences for the degree of mixing that we expect to find both within a population and between individuals of different species. The mixing rate dictates the level of detail required by models to capture the influence of heterogeneity and the dynamics of intra- and interspecific interaction.

Figure 1.

Redistribution kernels. (a) Three different individuals start moving at random from the centre of the plot; the trajectories look different, but they are governed by the same stochastic rules. Given a known starting point, the expected location of an individual at a given time, or a collection of individuals such as those simulated in (b), can be described by a redistribution kernel (c). For simple random walks as those shown here, the redistribution kernel is approximated by the solution of a diffusion equation. That is, a bivariate Gaussian with variance parameters that depend on the rate of movement and time.

Figure 2.

Sketch for developing mechanistic links between animal movement and population dynamics. We consider a catch-all, and usually unobserved, individual internal state that integrates body condition (reserves, reproductive status, etc.). Several factors affect the dynamics of this internal state, including social interactions with conspecifics, trophic or other interaction with other species and surrounding landscape attributes. Internal state dynamics determines the organism's time allocation to different behaviours such as food acquisition, predator avoidance, homing, landscape exploration and so on, but this is also modulated by previous experiences and phenotypic traits such as behavioural predispositions. As these different behaviours imply different movement strategies, the time budget determines the properties of the redistribution kernel that describes space use. Time allocation to different behaviours will also affect individual survival and reproduction and thus overall population dynamics.