bioRxiv | 2019
How to characterise shared space use networks
Abstract
Studying the social behaviour of small or cryptic species often relies on constructing space-sharing networks from sparse point-based observations of individuals. Such an approach assumes that individuals that have greater shared space use will also interact more. However, there is very little guidance on how much data are required to construct meaningful space-sharing networks, or on how to interpret the relationships generated from such networks. In this study, we quantify the robustness of space-sharing networks to different sampling regimes, providing much needed guidance for informing the choice of sampling regime when designing studies to accurately quantify space sharing. We then describe the characteristics of space use in a wild population of field voles (Microtus agrestis), and use this empirical dataset to develop a new method for generating shared space use networks which are generally more strongly correlated with the real network, differ less from the real network and are more powerful to detect effects present in the real network. Our method pools data among individuals to estimate a general home range profile for a given set of individuals.Combining these profiles with the individual-level observation data then allows us to better estimate their overlap in space and requires less data. Our new method provides the potential to generate meaningful space-sharing networks, and in doing so, to address a range of key questions in ecology and evolution, even when point-based observations of individuals are sparse.