Abstract
Abstract Behavioural events that are important for understanding sociobiology and movement ecology are often rare, transient and localised, but can occur at spatially distant sites e.g. territorial incursions and co‐locating individuals. Existing animal tracking technologies, capable of detecting such events, are limited by one or more of: battery life; data resolution; location accuracy; data security; ability to co‐locate individuals both spatially and temporally. Technology that at least partly resolves these limitations would be advantageous. European badgers (Meles meles L.), present a challenging test‐bed, with extra‐group paternity (apparent from genotyping) contradicting established views on rigid group territoriality with little social‐group mixing. In a proof of concept study we assess the utility of a fully automated active‐radio‐frequency‐identification (aRFID) system combining badger‐borne aRFID‐tags with static, wirelessly‐networked, aRFID‐detector base‐stations to record badger co‐locations at setts (burrows) and near notional border latrines. We summarise the time badgers spent co‐locating within and between social‐groups, applying network analysis to provide evidence of co‐location based community structure, at both these scales. The aRFID system co‐located animals within 31.5 m (adjustable) of base‐stations. Efficient radio transmission between aRFIDs and base‐stations enables a 20 g tag to last for 2–5 years (depending on transmission interval). Data security was high (data stored off tag), with remote access capability. Badgers spent most co‐location time with members of their own social‐groups at setts; remaining co‐location time was divided evenly between intra‐ and inter‐social‐group co‐locations near latrines and inter‐social‐group co‐locations at setts. Network analysis showed that 20–100% of tracked badgers engaged in inter‐social‐group mixing per week, with evidence of trans‐border super‐groups, that is, badgers frequently transgressed notional territorial borders. aRFID occupies a distinct niche amongst established tracking technologies. We validated the utility of aRFID to identify co‐locations, social‐structure and inter‐group mixing within a wild badger population, leading us to refute the conventional view that badgers (social‐groups) are territorial and to question management strategies, for controlling bovine TB, based on this model. Ultimately aRFID proved a versatile system capable of identifying social‐structure at the landscape scale, operating for years and suitable for use with a range of species.
Highlights
Locating animals relative to one another is fundamental to understanding sociobiology, gene-flow, dispersal patterns, and disease epidemiology, inter alia (Hansson 1991; Kappeler et al 2013; Woodroffe et al 2016), because co-location provides opportunities for animals to interact directly or indirectly
By recording badger co-locations at a relatively few, important, fixed locations we reveal the extent to which: i) badgers co-located with members of their own social-group – an ‘easy test’, and with extra-group members, a ‘hard test’; ii) any inter-group co-locations occurred at setts or at ‘notional’ territorial border latrines; iii) gender affected co-location patterns
System performance Compared to other technologies (Table 1), aRFID: (i) had a detection range of
Summary
Locating animals relative to one another (co-location) is fundamental to understanding sociobiology, gene-flow, dispersal patterns, and disease epidemiology, inter alia (Hansson 1991; Kappeler et al 2013; Woodroffe et al 2016), because co-location provides opportunities for animals to interact directly or indirectly Such insights are essential to designing effective wildlife management strategies (Carter et al 2007; Woodroffe et al 2016). Conventional reliance on observation, or coarse-scale tracking technologies, can lead to misinterpretation of animal societies, especially when the study species is rare, elusive, cryptic and/or nocturnal, and less amenable to surveillance (Wilson & Delahay 2001). These issues are compounded further in high-density populations and in social-systems involving hierarchies. When the spatial scale of studies is restricted, rare, long distance animal movements (affording opportunities for landscape scale gene flow and disease spread) can go unobserved (Byrne et al 2014)
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