Thomas C. Wainwright

Effects of Climate Change on Oregon Coast Coho Salmon: Habitat and Life-Cycle Interactions

Abstract Coho salmon (Oncorhynchus kisutch) populations that spawn in the coastal rivers of Oregon, U.S.A., formerly supported robust fisheries but are now listed as a “threatened species” under the U.S. Endangered Species Act. Climate change is an increasing concern in salmon conservation, and we assess the effects of climate change on sustainability of this population group. Four distinct habitats are important to different life-history stages of coho salmon: terrestrial forests, freshwater rivers and lakes, estuaries, and the ocean. Each of these habitats is affected by multiple aspects of climate change, resulting in a complex web of pathways influencing sustainability. We summarize regional climate change studies to predict future climate patterns affecting these habitats, identify the ecological pathways by which these patterns affect coho salmon, and review coho salmon ecology to assess the likely direction and magnitude of population response. Despite substantial uncertainties in specific effects and variations in effects among populations, the preponderance of negative effects throughout the life cycle indicates a significant climate-driven risk to future sustainability of these populations. We recommend that management policies for all four habitats focus on maximizing resilience to the effects of climate change as it interacts with other natural and anthropogenic changes.

A Practical Comparison of Viability Models Used for Management of Endangered and Threatened Anadromous Pacific Salmonids

Abstract This study considered whether different population viability analyses give similar estimates of extinction risk across management contexts. We compared the performance of population viability analyses developed by numerous scientific teams to estimate extinction risk of anadromous Pacific salmonids listed under the U.S. Endangered Species Act and challenged each analysis with data from 34 populations. We found variation in estimated extinction risk among analytical techniques, which was driven by varying model assumptions and the inherent uncertainty of risk forecasts. This result indicates that the scientific teams developed techniques that perform differently. We recommend that managers minimize uncertainty in risk estimates by using multiple models tailored to the local ecology. Assessment of relative extinction risk was less sensitive to model assumptions than was assessment of absolute extinction risk. Thus, the former method is better for comparing population status and raises caution about...

Use of population viability analysis models for Atlantic and Pacific salmon recovery planning

Uncertainty and risk abound in making natural resource management decisions. Population viability analysis (PVA) includes a variety of qualitative or quantitative analyses to predict the future status of a population or collection of populations and to predict the risk of extinction (or quasi-extinction) over time given some assumptions of the factors driving population dynamics. In this paper, we review the various PVA models applied to Atlantic and Pacific salmon for determination of listing under the Endangered Species Act and in planning recovery actions. We also review the numerous cautions involved in developing PVA models and in interpreting their results. There have been a larger number of PVA models applied to Pacific salmon compared to Atlantic salmon due to the greater geographic range and number of species of Pacific salmon. Models for both Atlantic and Pacific salmon have ranged from simple models that view populations as simply a number of organisms to complex age- or stage-structured models depending on the purpose of the model and available data for model parameterization. The real value of PVA models to salmon conservation is not in making absolute predictions of the risk of extinction, but rather in evaluating relative effects of management alternatives on extinction risk and informing decision making within an adaptive management framework. As computing power, quantitative techniques, and knowledge of mechanistic linkages between terrestrial, freshwater, and marine environments advance, PVA models will become an even more powerful tool in conservation planning for salmon species.

Effect of forecast skill on management of the Oregon coast coho salmon (Oncorhynchus kisutch) fishery

Better fisheries management is often given as one justification for research on improving forecasts of fish sur- vival. However, the value gained from expected improvements in forecast skill in terms of achieving management goals is rarely quantified as part of research objectives. Using Monte Carlo simulations of population dynamics, we assessed the ef- fect of forecast skill under two strategies for managing Oregon coast natural (OCN) coho salmon (Oncorhynchus kisutch). The first, or status quo, strategy is currently being used to rebuild threatened OCN coho populations. This strategy deter- mines harvest based on both a forecasted marine survival rate and parental spawner abundance. The second strategy relies on a forecast of preharvest adult abundance to achieve a constant spawner escapement target. Performance of the status quo strategy was largely insensitive to forecast skill, while the second strategy showed sensitivity that varied with escapement target and specific performance metric. The results imply that effort towards improving forecasts is not justifiable solely on the basis of improved management under the status quo strategy, though it may be were the management strategy altered.

Measuring Biological Sustainability via a Decision Support System: Experiences with Oregon Coast Coho Salmon

Conservation of Pacific salmon (Oncorhynchus spp.) has become increasingly important as major populations have declined in abundance to the point of being listed under the U.S. Endangered Species Act. The complex life-history of Pacific salmon species and the diversity of habitats they occupy require multifaceted recovery efforts, and the metrics needed to evaluate species status and progress toward recovery are necessarily complex. Formal decision support systems (DSS) are designed to assist decision-makers in integrating and evaluating many factors. We describe a knowledge-based DSS for evaluating the biological status of Oregon coast coho salmon (O. kisutch). We then compare our DSS to similar tools and consider its advantages and disadvantages. We show how the DSS can provide a transparent and logical framework linking multiple criteria across geographic scales for a unified assessment. Once constructed, the DSS can serve as an institutional knowledge base, codifying the pathways from data to criteria evaluation and supporting consistent future status evaluations with a path to incorporating new knowledge over time. The DSS was not trivial to implement, nor is it easy to explain to resource managers, and we offer suggestions to address these problems. The DSS was particularly helpful in providing a logical and reproducible way to quantify multiple risks and assess progress toward recovery across multiple spatial and temporal scales. Development of this DSS is an important step in the evolution of assessment tools for salmon conservation.