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ORCID

https://orcid.org/0009-0008-6569-1566

Access Type

Open Access Thesis

Document Type

thesis

Embargo Period

9-1-2024

Degree Program

Environmental Conservation

Degree Type

Master of Science (M.S.)

Year Degree Awarded

2023

Month Degree Awarded

September

Abstract

Over the last few decades, freshwater turtles have become more common in the global illegal wildlife trade because of the growing demand in the pet trade. Illegally traded turtles may be intercepted and deposited by a number of agencies. However, when turtles are confiscated, many uncertainties and risks make releasing them back to the wild difficult. Therefore, we used tools from decision analysis to achieve the following three objectives: (1) to identify points of intervention in illegal turtle trade using conceptual models, (2) to outline the linked decisions for turtle confiscation and repatriation using decision trees, and (3) to evaluate the decision trees for two example scenarios, one with complete information and one with uncertainty. We used the wood turtle (Glyptemys insculpta) as a case study, which is a species of conservation concern, in part due to illegal wildlife trafficking. We conducted informational interviews of biologists, law enforcement, land managers, and zoo staff, which we refer to as a decision makers. Interviews revealed that decisions regarding the disposition of confiscated turtles are complicated by uncertainty in disease status and potential differences in origin and confiscation locations. Decision makers that handle confiscated turtles also recognize that their decisions are linked, where linkages rely on personal contacts. In evaluating our decision trees, we found that despite different amounts and kinds of uncertainties, release of the confiscated wood turtles to the wild provided the highest conservation value. Collectively, our research shows how the use of decision trees can help improve decision making in the face of uncertainty.

DOI

https://doi.org/10.7275/35916260.0

First Advisor

Graziella V. DiRenzo

Available for download on Sunday, September 01, 2024

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