A new method for characterising shared space use networks using animal trapping data

• DOI: 10.1007/s00265-022-03222-5
• Publication Date: 2022-08-26T08:03:09Z
• Authors: Klara M. Wanelik; Damien R. Farine
• Keywords: Animal ecology; Shared space; Trap (plumbing)

Studying the social behaviour of small or cryptic species often relies on constructing networks from sparse point-based observations individuals (e.g. live trapping data). A common approach assumes that have been detected sequentially in same location will also be more likely to come into indirect and/or direct contact. However, there is very little guidance how much data are required for making robust such data. In this study, we highlight sequential trap sharing broadly capture shared space use (and, hence, potential contact) and it may parsimonious directly model use. We first empirical show characteristics animals can help us establish new ways then a method explicitly models individuals' home ranges subsequent overlap among (spatial networks) requires fewer inferring observed strongly correlated with true network (relative networks). Furthermore, based estimating spatial powerful detecting biological effects. Finally, discuss when appropriate make inferences about interactions Our study confirms using address range important questions ecology evolution.Characterising animal repeated (co-)observations individuals. Collecting sufficient characterise connections represents major challenge studying organisms-such as rodents. This draws existing mark-recapture inspire an constructs by (representing contact). simulations demonstrate provides consistently higher correlations between inferred (or observed) underlying compared current approaches reach correlations. further these improvements translate greater accuracy power statistical hypothesis testing.The online version contains supplementary material available at 10.1007/s00265-022-03222-5.