Abstract
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 behaviour 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 multiple biotelemetry data streams. Different biological latent states can be inferred by partitioning a time-series into multiple segments based on changes in modelled responses (e.g. their mean, variance, trend, degree of autocorrelation) and specifying a unique model structure for each interval. We provide six example applications highlighting a variety of taxonomic species, data streams, timescales and biological phenomena. These examples include a short-term behavioural response (flee and return) by a trumpeter swan Cygnus buccinator 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 signalled by changes in collar temperature and overall dynamic body acceleration; an unsupervised method for identifying the onset, return, duration and staging use of sandhill crane Antigone canadensis migration; and estimation of the transition between incubation and brood-rearing (i.e. hatching) for a breeding trumpeter swan. 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 criteria and cross-validation measures. These simple modelling approaches are accessible to a wide audience and offer a straightforward means of assessing a variety of biologically relevant changes in animal behaviour.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1755-1769 |
| Number of pages | 15 |
| Journal | Journal of Animal Ecology |
| Volume | 91 |
| Issue number | 9 |
| DOIs | |
| State | Published - Sep 2022 |
Bibliographical note
Funding Information:We thank Victoria Drake, Jon Dachenhaus, Emily Wells, Jeff Fox, John Moriarty, Steven Hogg and Kaia Hilgendorf‐Roost for assistance with fieldwork that resulted in the trumpeter swan and sandhill crane datasets used in the examples. We thank Mark Ditmer for access to black bear data and William Severud, Tyler Obermoller, Glenn DelGiudice and Michelle Carstensen for access to moose data. We thank Simona Picardi, Amy Davis, Althea Archer, one anonymous reviewer, and an associate editor for constructive comments that improved the manuscript. Funding support for David Wolfson was provided by the Minnesota Environmental and Natural Resources Trust Fund as recommended by the Legislative‐Citizen Commission on Minnesota Resources (LCCMR) and the U.S. Geological Survey, Minnesota Cooperative Fish and Wildlife Research Unit. John Fieberg received partial support from the Minnesota Agricultural Experimental Station. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government, the University of Minnesota, or the State of Minnesota.
Publisher Copyright:
© 2022 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.