Semester of Graduation

Spring 2019

Degree

Master of Science (MS)

Department

Renewable Natural Resources

Document Type

Thesis

Abstract

Avian reproduction is known to be a driver of population dynamics across species and systems. Behavioral decisions during incubation such as habitat selection and nest attentiveness are thought to affect nest success. The incubation process is a costly period during which individuals are sedentary and must balance survival with reproductive success and overall fitness. Current understanding of Eastern wild turkey incubation behavior provides a limited view of the incubation period. Using GPS data collected from Eastern wild turkeys (n = 220), I evaluated nest fate as it relates to recess frequency, distance travelled during recess, and habitat selection during the incubation period. My results differed from previous studies, whereas I show that individuals made daily recesses until the final day of the incubation period. I observed that individuals that made frequent long distance recess movements had a greater chance of having a successful nest, opposed to individuals that made infrequent recesses and moved short distances. My results suggest behavioral decisions are influencing trade‒offs during the incubation period to reduce the risk of predation, specifically adjusting the amount of time an individual spends on and off the nest.

Developing decision‒making tools that adequately and accurately describe the biological system are important to develop sound wildlife management strategies. Models that use regression analysis are important as they provide insight on a specific topic within the system. However, it is equally important to incorporate findings from a suite of studies into a conceptual framework in order to understand biological relationships within the system. Bayesian belief network allows me to integrate multiple studies into a meaningful biological framework. Constructing a framework based on biological causality, I evaluated how vegetation characteristics at the nest site, landscape attributes within the recess range, and behavioral decisions are linked within the system and collectively influence nest fate. I found that nest fate was influenced by incubation range, nest attentiveness, and ground cover. However, these variables were also influenced by underlying vegetation characteristics and landscape attributes. My conceptual model suggest that Bayesian belief networks are a graphical model that identifies uncertainty and allows for identification and enumeration of measurable variables in a more biological meaningful way.

Committee Chair

Collier, Bret

Available for download on Saturday, March 14, 2020

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