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BackgroundIn animal ecology, inter-individual encounters are often investigated using automated proximity loggers. However, data acquired are typically spatially implicit, i.e. the question ‘Where did the contact occur?’ remains unanswered. To resolve this issue, recent advancements in Wireless Sensor Network technology have facilitated the geo-referencing of animal contacts. Among these, WildScope devices integrate GPS-based telemetry within fully distributed networks, allowing contact-triggered GPS location acquisition. In this way, the ecological context in which contacts occur can be assessed. We evaluated the performance of WildScope in close-to-real settings, whilst controlling for movement of loggers and obstacles, performing field trials that simulated: (1) different scenarios of encounters between individuals (mobile–mobile contacts) and (2) patterns of individual focal resource use (mobile–fixed contacts). Each scenario involved one to three mobile and two fixed loggers and was replicated at two different radio transmission powers. For each scenario, we performed and repeated a script of actions that corresponded to expected contact events and contact-triggered GPS locations. By comparing expected and observed events, we obtained the success rate of: (1) contact detection and (2) contact-triggered GPS location acquisition. We modelled these in dependence on radio power and number of loggers by means of generalized linear mixed models.ResultsOverall we found a high success rate of both contact detection (88–87%: power 3 and 7) and contact-triggered GPS location acquisition (85–97%: power 3 and 7). The majority of errors in contact detection were false negatives (66–69%: power 3 and 7). Number of loggers was positively correlated with contact success rate, whereas radio power had little effect on either variable.ConclusionsOur work provides an easily repeatable approach for exploring the potential and testing the performance of WildScope GPS-based geo-referencing proximity loggers, for studying both animal-to-animal encounters and animal use of focal resources. However, our finding that success rate did not equal 100%, and in particular that false negatives represent a non-negligible proportion, suggests that validation of proximity loggers should be undertaken in close-to-real settings prior to field deployment, as stochastic events affecting radio connectivity (e.g. obstacles, movement) can bias proximity patterns in real-life scenarios.

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