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HIGH-FREQUENCY ACCELEROMETER MONITORING OF FORAGING AND MOVEMENT BEHAVIOR IN A SECRETIVE PREDATOR (CENTRAL RAT SNAKES, PANTHEROPHIS ALLEGHENIENSIS)**

Abstract

Advancements in bio-logging technology have transformed study of animals in nature. Among the many bio-loggers available, accelerometers (ACTs) are becoming increasingly common in studies of animal behavior. ACTs are small (<1 g) piezo-electric (spring-like) sensors capable of measuring three-dimensional acceleration derived from subject-motion, and advanced machine learning techniques enable automated classification of distinct behavioral states from these data. While ACTs were previously utilized in the investigation of larger organisms and those most compliant to the temporary attachment of external devices, smaller dimensions have expanded the breadth of organisms amenable to these methods. The goal of this project is to expand a novel framework for ACT monitoring in snakes, a group of smaller vertebrates that have been previously absent in biologging applications. We will conduct comprehensive captive validation trials for robust machine learning model training and testing for accurate classification of key behaviors in Rat Snakes (Pantherophis allegheniensis), including full-body movement, immobility, predatory strikes, constriction, and ingestion of prey items. All classification model procedures will be conducted with open-source software specifically designed for acceleration data processing, demonstrating the increasing accessibility and feasibility of ACT studies. Following captive validation, this method will be applied to the field using a population of P. allegheniensis located in the lower Piedmont of middle Georgia to provide continuous and remote field-monitoring of activity patterns and key predatory behaviors. We envision validation of this technique carrying significant conservation and management implications. Real-time monitoring of foraging efficiency in the field facilitates 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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