Using Piecewise Regression to Identify Biological Phenomena in Biotelemetry Datasets

Technological advances in the field of animal tracking have greatly expanded the potential to remotely monitor animals, opening the door to exploring how animals shift their behavior over time or respond to external stimuli. A wide variety of animal-borne sensors can provide information on an animal's location, movement characteristics, external environmental conditions, and internal physiological status. Here, we demonstrate how piecewise regression can be used to identify the presence and timing of potential shifts in a variety of biological responses using GPS telemetry and other biologging data streams. Different biological latent states can be inferred by partitioning a time-series into multiple segments based on changes in modeled responses (e.g., their mean, variance, trend, degree of autocorrelation) and specifying a unique model structure for each interval. We provide five example applications highlighting a variety of taxonomic species, data streams, timescales, and biological phenomena. These examples include a short-term behavioral response (flee and return) by a trumpeter swan (Cygnus buccinator) immediately following a GPS collar deployment; remote identification of parturition based on movements by a pregnant moose (Alces alces); a physiological response (spike in heart-rate) in a black bear (Ursus americanus) to a stressful stimulus (presence of a drone); a mortality event of a trumpeter swan signaled by changes in collar temperature and Overall Dynamic Body Acceleration; and an unsupervised method for identifying the onset, return, duration, and staging use of sandhill crane (Antigone canadensis) migration. We implement analyses using the mcp package in R, which provides functionality for specifying and fitting a wide variety of user-defined model structures in a Bayesian framework and methods for assessing and comparing models using information criterion and cross-validation measures. This approach uses simple modeling approaches that are accessible to a wide audience and is a straightforward means of assessing a variety of biologically relevant changes in animal behavior.

Trumpeter Swan (Cygnus buccinator) behaviour, interactions with Snapping Turtles (Chelydra serpentina), and their Pleistocene history

Snapping Turtles (Chelydra serpentina) prey on and injure Trumpeter Swan (Cygnus buccinator) cygnets. Adult Trumpeter Swans stamp on and attack turtles, and this sometimes saves the lives of cygnets. Stamping behaviour, duetting, clamouring, and mobbing are directed at predators. The stamping behaviour may be derived from the water treading display. During the Pleistocene ice sheet maxima, all Trumpeter Swans east of the Rockies nested within the range of the Snapping Turtle. Snapping Turtle predation may have selected for the stamping behaviour.