Date of Award

2022

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Natural Resources

First Advisor

Brittany Mosher

Abstract

Effective conservation is becoming more difficult as threats to wildlife increase. Natural resource managers are pressured to make difficult decisions with limited resources, and in many instances, some degree of uncertainty. Scientists and managers tasked with the conservation of a species need tools to help guide efficient decision making. Often, information for management decisions is insufficient. Tools that help to inform decision makers and address uncertainty will be invaluable to effective conservation initiatives. Here, we create two models to help managers navigate the complexities associated with decision making. The objective our first study was to create a model to best predict Eastern red-spotted newt (Notophthalamus viridescens viridescen; ERSN) breeding occurrence across the northeastern United States. We estimated relationships between breeding ERSN field survey data and landscape-level covariates. We then used those relationships to map predictions of ERSN breeding occupancy across the northeastern U.S. Our estimates accounted for imperfect detection and were used to make spatial predictions of occupancy. This analysis will provide a foundational tool upon which managers can develop management strategies for ERSN. Our second model is a Bayesian belief network intended to guide decision making for wood frog (Lithobates sylvaticus) persistence when two pathogens, ranavirus and Batrachochytrium dendrobaditis, are present within a pool. Both models help to inform and guide managers faced with the difficult task of managing wildlife populations in the face of multiple threats.

Language

en

Number of Pages

67 p.

Available for download on Friday, December 09, 2022

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