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HIGH-FREQUENCY ACCELEROMETER RECORDING OF KEY PREDATORY BEHAVIORS IN VIPERS: A CASE STUDY WITH TIMBER RATTLESNAKES (CROTALUS HORRIDUS)**

Abstract

Tri-axial accelerometers (ACTs) are becoming increasingly common in studies of animal behavior wherein direct observation of subjects in nature is constrained or impossible. ACTs are small (< 1 g) piezo-electric (spring-like) sensors that measure three-dimensional acceleration (upward, downward, and side-to-side) derived from subject motion. When leveraged with advanced machine learning techniques, these data can enable precise automated classification of a wide range of movement-mediated behaviors. Until recently, ACTs were largely reserved for larger-bodied organisms or those most amenable to the temporary external attachment of devices. Ongoing ACT miniaturization has now expanded the breadth of organisms amenable to these methods. This project aims to expand on a recently developed framework for ACT monitoring in wild-ranging snakes, a group that has been mostly overlooked in biologging applications. We have completed extensive captive ACT validation trials with timber rattlesnakes (Crotalus horridus) and have used these datasets in the training and testing of robust classification models of foraging behaviors, i.e. strike and swallowing of prey items. Using AcceleRater, a free online service available to the community, we trained, tested and compared linear SVM, decision tree, and random forest classification models for strike, movement, and stillness using a window size of 0.4 seconds. Separate linear SVM, decision tree and random forest models were trained, tested, and compared with a window size of three seconds for swallowing behaviors. Following validation of these models, we translated this method to the field with a population of C. horridus in the lower Piedmont of middle Georgia to evaluate the efficacy of externally attached ACTs for remote and continuous monitoring of predatory behaviors by wild-ranging vipers.

Acknowledgements

Georgia College & State University

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