Processing and visualising association data from animal-borne proximity loggers

Abstract

Background: With increasing interest in animal social networks, field biologists have started exploring the use of advanced tracking technologies for mapping social encounters in free-ranging subjects. Proximity logging, which involves the use of animal-borne tags with the capacity for two-way communication, has attracted particular attention in recent years. While the basic rationale of proximity logging is straightforward, systems generate very large datasets which pose considerable challenges in terms of processing and visualisation. Technical aspects of data handling are crucial for the success of proximity-logging studies, yet are only rarely reported in full detail. Here, we describe the procedures we employed for mining the data generated by a recent deployment of a novel proximitylogging system, "Encounternet", to study social-network dynamics in tool-using New Caledonian crows.Results: Our field deployment of an Encounternet system produced some 240,000 encounter logs for 33 crows over a 19-day study period. Using this dataset, we illustrate a range of procedures, including: examination of tag reciprocity (i.e. whether both tags participating in an encounter detected the encounter and, if so, whether their records differed); filtering of data according to a predetermined signal-strength criterion (to enable analyses that focus on encounters within a particular distance range); amalgamation of temporally clustered encounter logs (to remove data artefacts and to enable robust analysis of biological patterns); and visualisation of dynamic network data as timeline plots (which can be used, among other things, to visualise the simulated diffusion of information). Conclusions:Researchers wishing to study animal social networks with proximity-logging systems should be aware of the complexities involved. Successful data analysis requires not only a sound understanding of hardware and software operation, but also bioinformatics expertise. Our paper aims to facilitate future projects by explaining in detail some of the subtleties that are easily overlooked in first-pass analyses, but are key for reaching valid biological conclusions. We hope that this work will prove useful to other researchers, especially when read in conjunction with three recently published companion papers that report aspects of system calibration and key results.

Optimizing the use of biologgers for movement ecology research

“…There are two main approaches to remotely record the social contact between free-ranging animals: indirect and direct encounter mapping (see Bettaney, James, St Clair, & Rutz, 2015;Krause et al, 2013). Indirect encounter mapping can be achieved either with high-resolution tracking of subjects, or with the use of tags that transmit to, or that are detected by, fixed receiver stations at specific locations (e.g., coded VHF radio-tags or PIT/ RFID tags).…”

“…or camera tags (Hooker, Barychka, Jessopp, & Staniland, 2015), to create reciprocal records of social encounters (Bettaney et al, 2015;Krause et al, 2013). Proximity loggers can be used for addressing a variety of biological questions and have the advantage over cameras (e.g.…”

Understanding and geo-referencing animal contacts: proximity sensor networks integrated with GPS-based telemetry

“…In this way, studies on spatially explicit contact detection can be combined with 'traditional' movement research [25]. The flexible scheduling of both contact-triggered and independent (periodic) GPS location acquisition allows the user to adjust the tool in accordance with study-specific requirements.…”

“…Social Network Analysis [6,12]), where the sampling units are the contacts between individuals (or 'edges') rather than the individuals wearing the devices. The value of proximity information can be further enhanced by making animal-to-animal contacts spatially explicit [25], providing ecologists with the added value of knowing where animal encounters occur. Thus, the ecological context of a given contact can be inferred (e.g.…”

Performance of proximity loggers under controlled field conditions: an assessment from a wildlife ecological and epidemiological perspective

“…Several studies have assessed the effect of different factors over the radio transmission of each device individually. The distance between PLs has been adjusted according to the specific interests of the study, covering distances from less than 1 m [1,8] up to approximately 50 m [9]. However, the potential of PLs to record contacts over longer distances has not been further evaluated, even when it may be relevant for ecology in, for instance, studies related to avoiding behaviours in preypredator systems or in territoriality related behaviours (but see [2]).…”