Using tri-axial acceleration data to identify behavioral modes of free-ranging animals: general concepts and tools illustrated for griffon vultures
Top Cited Papers
- 15 March 2012
- journal article
- review article
- Published by The Company of Biologists in Journal of Experimental Biology
- Vol. 215 (6), 986-996
- https://doi.org/10.1242/jeb.058602
Abstract
Integrating biomechanics, behavior and ecology requires a mechanistic understanding of the processes producing the movement of animals. This calls for contemporaneous biomechanical, behavioral and environmental data along movement pathways. A recently formulated unifying movement ecology paradigm facilitates the integration of existing biomechanics, optimality, cognitive and random paradigms for studying movement. We focus on the use of tri-axial acceleration (ACC) data to identify behavioral modes of GPS-tracked free-ranging wild animals and demonstrate its application to study the movements of griffon vultures (Gyps fulvus, Hablizl 1783). In particular, we explore a selection of nonlinear and decision tree methods that include support vector machines, classification and regression trees, random forest methods and artificial neural networks and compare them with linear discriminant analysis (LDA) as a baseline for classifying behavioral modes. Using a dataset of 1035 ground-truthed ACC segments, we found that all methods can accurately classify behavior (80–90%) and, as expected, all nonlinear methods outperformed LDA. We also illustrate how ACC-identified behavioral modes provide the means to examine how vulture flight is affected by environmental factors, hence facilitating the integration of behavioral, biomechanical and ecological data. Our analysis of just over three-quarters of a million GPS and ACC measurements obtained from 43 free-ranging vultures across 9783 vulture-days suggests that their annual breeding schedule might be selected primarily in response to seasonal conditions favoring rising-air columns (thermals) and that rare long-range forays of up to 1750 km from the home range are performed despite potentially heavy energetic costs and a low rate of food intake, presumably to explore new breeding, social and long-term resource location opportunities.Keywords
This publication has 55 references indexed in Scilit:
- Flight Modes in Migrating European Bee-Eaters: Heart Rate May Indicate Low Metabolic Rate during Soaring and GlidingPLOS ONE, 2010
- Distinguishing technology from biology: a critical review of the use of GPS telemetry data in ecologyPhilosophical Transactions Of The Royal Society B-Biological Sciences, 2010
- Stochastic modelling of animal movementPhilosophical Transactions B, 2010
- Pushed for time or saving on fuel: fine-scale energy budgets shed light on currencies in a diving birdProceedings. Biological sciences, 2009
- Can Ethograms Be Automatically Generated Using Body Acceleration Data from Free-Ranging Birds?PLOS ONE, 2009
- New frontiers in biologging scienceBiology Letters, 2009
- Multiple movement modes by large herbivores at multiple spatiotemporal scalesProceedings of the National Academy of Sciences of the United States of America, 2008
- A framework for generating and analyzing movement paths on ecological landscapesProceedings of the National Academy of Sciences of the United States of America, 2008
- Trends and missing parts in the study of movement ecologyProceedings of the National Academy of Sciences of the United States of America, 2008
- A movement ecology paradigm for unifying organismal movement researchProceedings of the National Academy of Sciences of the United States of America, 2008