Linking Moral Obligations, Assumption-based Research, and Structured Decision Making to Inform Bull Trout Recovery Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/j67316995

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  • More than 1500 species of plants and animals in the United States are listed as threatened or endangered under the Endangered Species Act (ESA). The U.S. Departments of Interior and Commerce are required, under Section 4(f)(1) of the ESA, to develop recovery plans for ESA-listed species under the respective agency jurisdictions. However, developing recovery plans that are both scientifically defensible and consistent with a diversity of stakeholder (e.g., states, tribes, private landowners) values is often difficult. Structured decision making is a framework that resource managers can use to integrate diverse, and often conflicting, stakeholder value systems into species recovery planning. Within this framework difficult decisions are deconstructed into the three basic components: 1) explicit, quantifiable objectives that represent stakeholder values; 2) mathematical models used to predict the effect of management decisions on the outcome of objectives; and 3) management alternatives or actions. The goal of my dissertation was to acknowledge and understand the uncertainty of bull trout Salvelinus confluentus reintroduction strategies and provide an ethical and scientific foundation for an enduring and biologically sound conservation program. My objectives were to (1) describe how incorporating stakeholder values into scientifically defensible recovery planning using structured decision making will fulfill legal and moral obligations to recover species, (2) determine how captive rearing environments affect the development and survival behaviors of bull trout and how these effects may influence the efficacy and ultimate success of reintroduction and recovery programs, and (3) use structured decision making to evaluate the tradeoffs of alternative bull trout reintroduction decisions. I developed this research project to be multifaceted by incorporating components of philosophy (Chapter 2), assumption-based research (Chapter 3), and statistical modeling (Chapter 4). The collective results my research should serve as an example of how to incorporate diverse stakeholder value systems, assumption-based research, and evaluations of alternative management actions into species recovery and reintroduction decisions. This approach promotes transparency and consensus in decision making. Recognizing these benefits, the U.S. Fish and Wildlife Service has adopted a similar approach to manage species and their habitats into the future (i.e., Strategic Habitat Conservation). The impediments to species recovery are numerous. Some of the biggest impediments to recovery planning are conflicting values and interests among stakeholders. I believe that these types of conflicts and related issues are best addressed by integrating the diverse values and interests of stakeholders with the best scientific information available, and doing so in a clear and transparent manner that will broaden acceptance for enduring recovery planning. Science, in and of itself, cannot dictate which management decisions ought to be made; it purely offers a biological and physical basis for estimating the outcomes of decisions. An understanding of humanities is needed to provide context for the myriad of societal obligations. Three moral philosophies; consequentialism, deontology, and virtue theory, suggest that structured decision making is a justified method that can guide natural resource decisions in the future, and will honor legal and moral obligations to recover ESA listed species and their habitats. The ability to recover and delist species in the future depends on an increased understanding of natural ecosystems through scientific discovery and the ability to incorporate stakeholder values into the recovery planning process in a manner that is objective, systematic, and transparent. Animals reared in barren captive environments exhibit different development and behaviors than wild counterparts. Hence, the captive phenotypes may influence the success of reintroduction and recovery programs for threatened and endangered species. I collected wild bull trout embryos from the Metolius River Basin, Oregon and reared them in differing environments to better understand how captivity affects the bull trout phenotype to aide in the development of informed recovery strategies for the species. I compared the development of the brain and eye lens, and boldness and prey acquisition behaviors of bull trout reared in conventional barren and more structurally complex captive environments with that of wild fish. I found that wild bull trout exhibited a greater level of boldness and prey acquisition ability, followed by captive reared bull trout from complex habitats, and finally fish reared in conventional captive environments. In addition, the eye lens of conventionally reared bull trout was larger than complex reared captive fish or that of wild fish. Unexpectedly, I detected wild fish had a smaller relative cerebellum than either captive reared treatment. My results add to the existing literature that suggests rearing fish in more complex captive environments can create a more wild-like phenotype than conventional rearing practices. Rearing fish in captivity is an important tool that can be used to accomplish a suite of management objectives including providing fish for research and reintroduction programs, or in worst case scenarios maintaining refuge populations. An understanding of the effects of captivity on the development and behavior of bull trout is important if life in captivity is the only option to ensure existence of some populations, and can inform rearing and reintroduction programs through prediction of the performance of released individuals. Stakeholders can be divided on what is the optimal reintroduction strategy to use (i.e., translocation, captive rearing, or artificial production) or how many individuals to collect for a program. These decisions are further complicated by a limited understanding of how captivity affects an animal’s phenotype and how well animals will survive upon release. Structured decision making allows natural resource decisions to be made in spite of uncertainty by linking reintroduction goals with alternative management actions through predictive models of ecological processes. Predictive models represent competing hypothesis that describe the belief of the structure and function of the ecological system and can be updated as new information is generated by monitoring and research (i.e., adaptive management). I developed a structured decision model to evaluate the tradeoffs between six bull trout reintroduction alternatives with the goal of maximizing the number of adults in the recipient population, up to 300 individuals, without reducing the donor population to an unacceptable state. The six alternative decisions that were evaluated are to 1) do-nothing, 2) translocate 1000 juveniles, 3) translocate 60 adults, 4) translocate 1000 juveniles and 40 adults, 5) captive rear 20,000 wild embryos, or 6) artificial production of 60 wild adults. The model was parameterized with published demographic parameters where available and consists of three stage-based Leslie matrix models that represent the donor, captive, and recipient populations. A state dependent policy was created that identifies the optimal decision over a combination of possible donor and recipient adult abundance states. One-way sensitivity analysis suggests that the value of the decision outcome was most influenced by survival parameters that resulted in increased adult abundance in the recipient population, and increased juvenile survival in the donor and recipient populations. The decision outcome was also sensitive to small and large adult fecundity rates and sex ratio. The outcome was least sensitive to survival parameters associated with the captive population, a survival reduction of naive reintroduced individuals, and juvenile carrying capacity of the reintroduced population. Two-way sensitivity analysis with all combinations of model parameters identified interactions that influence the decision outcome and identity. For example, a comparison of the juvenile density dependent parameters for the donor population indicated that when above a maximum egg survival of 0.14, the juvenile carrying capacity had a greater influence on the expected outcome of the decision. When juvenile carrying capacity in the donor population was less than ~5500 individuals, the optimal strategy was to do nothing, which most likely avoided an unacceptable reduction in the donor population. Whereas, translocating adults was the optimal decision when both density dependent parameters (i.e., juvenile carrying capacity, maximum egg survival) were in the upper end of their range and resulted in a decision outcome of greater than 60 adults in the recipient population. The optimal decision was to captive rear embryos when there was minimal effect of captive rearing and translocation on the survival of released fish. Whereas, translocating adults was the optimal decision when the probability of survival was less than 0.75 for captive reared fish as compared to translocated fish. As the survival penalty for captive reared fish neared 1.00, which indicated little to no effects of captivity on a fish’s survival after release, artificial production became the optimal decision regardless of the effects of a translocation on post-release survival. This model and sensitivity analyses can serve as the foundation for formal adaptive management and improved effectiveness, efficiency, and transparency of bull trout reintroduction decisions. Ongoing bull trout reintroductions and research will continue to lessen uncertainty and new information can be incorporated into decision models to guide future reintroduction decisions and maximize the benefit from limited resources available for bull trout recovery.
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