Building the bridge between animal movement and population dynamics

TLDR

Although animal movement is clearly linked to population dynamics, it remains unclear when movement data are essential for predicting dynamics, and movement patterns influence mixing rates that affect intra‑ and interspecific interactions. The study aims to use GPS and other tracking technologies to develop spatially informed movement models that incorporate behavior, individual condition, social structure, and memory to better link movement to survival, reproduction, and population dynamics. The authors employ GPS and other tracking technologies to build spatially informed movement models that integrate behavior, physiology, social dynamics, and memory, linking time allocation to survival and reproduction.

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.