Zooming in on mechanistic predator-prey ecology: Integrating camera traps with experimental methods to reveal the drivers of ecological interactions.

Camera trap technology has galvanized the study of predator-prey ecology in wild animal communities by expanding the scale and diversity of predator-prey interactions that can be analysed. While observational data from systematic camera arrays have informed inferences on the spatiotemporal outcomes of predator-prey interactions, the capacity for observational studies to identify mechanistic drivers of species interactions is limited. Experimental study designs that utilize camera traps uniquely allow for testing hypothesized mechanisms that drive predator and prey behaviour, incorporating environmental realism not possible in the laboratory while benefiting from the distinct capacity of camera traps to generate large datasets from multiple species with minimal observer interference.

Monitoring canid scent marking in space and time using a biologging and machine learning approach.

For canid species, scent marking plays a critical role in territoriality, social dynamics, and reproduction. However, due in part to human dependence on vision as our primary sensory modality, research on olfactory communication is hampered by a lack of tractable methods. In this study, we leverage a powerful biologging approach, using accelerometers in concert with GPS loggers to monitor and describe scent-marking events in time and space.