Document Type


Publication Date

Spring 3-27-2022


High-frequency accelerometer recording of key predatory behaviors in vipers: validation and case study with Timber Rattlesnakes (Crotalus horridus)

Morgan Thompson, Richard H. Adams, Anna F. Tipton, and Dominic L. DeSantis

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 are currently conducting extensive captive validation trials for robust model training and testing to enable classification of predatory behaviors, including striking and ingestion of prey items, in Timber Rattlesnakes (Crotalus horridus). Following captive validation, we will translate 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. We envision validation of this technique carrying significant conservation and management implications; real-time monitoring of foraging efficiency in the field opens the door to improved interpretation of the causes and consequences of variation in individual behavior and performance, and its ultimate effects on population trajectories.



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