Peter W. Lawson

Genetic population structure of central Oregon Coast coho salmon (Oncorhynchus kisutch)

We surveyed microsatellite variation from 22 spawning populations of coho salmon (Oncorhynchus kisutch) from the Oregon Coast to help identify populations for conservation planning. All of our samples were temporally replicated, with most samples obtained in 2000 and 2001. We had three goals: (1) to confirm the status of populations identified on the basis of spawning location and life history; (2) to estimate effective population sizes and migration rates in order to determine demographic independence at different spatial scales; and (3) to determine if releases of Washington hatchery coho salmon in the 1980s into Oregon Coast streams resulted in measurable introgression into nearby wild Oregon Coast coho populations. For the last question, our study included a hatchery broodstock sample from 1985, after the Puget Sound introduction, and a 1975 sample taken from the same area prior to the introduction. Our results generally supported previously hypothesized population structure. Most importantly, we found unique lake-rearing groups identified on the basis of a common life-history type were genetically related. Estimates of immigrant fraction using several different methods also generally supported previously identified populations. Estimates of effective population size were highly correlated with estimates of spawning abundance. The 1985 hatchery sample was genetically similar to contemporary Washington samples, and the contemporary Oregon Coast samples were similar to the 1975 Oregon Coast sample, suggesting that introductions of Washington coho salmon did not result in large scale introgression into Oregon populations.

Use of Genetic Stock Identification Data for Comparison of the Ocean Spatial Distribution, Size at Age, and Fishery Exposure of an Untagged Stock and Its Indicator: California Coastal versus Klamath River Chinook Salmon

AbstractManaging weak stocks in mixed-stock fisheries often relies on proxies derived from data-rich indicator stocks, although there have been limited tests of the appropriateness of such proxies. For example, full cohort reconstruction of tagged Klamath River fall-run Chinook Salmon Oncorhynchus tshawytscha of northern California enables the use of detailed models to inform management. Information gained from this stock is also used in the management of the untagged, threatened California Coastal Chinook Salmon (CCC) stock, where it is assumed that a cap on Klamath harvest rates effectively constrains impacts on CCC to acceptable levels. To evaluate use of this proxy, we used a novel approach based on genetic stock identification (GSI) data to compare the two stocks’ size at age and ocean distribution (as inferred from spatial variation in CPUE), two key factors influencing fishery exposure. We developed broadly applicable methods to account for both sampling and genetic assignment uncertainty in estima...

End-to-End eScience: Integrating Workflow, Query, Visualization, and Provenance at an Ocean Observatory

Data analysis tasks at an Ocean Observatory require integrative and and domain-specialized use of database, workflow, visualization systems. We describe a platform to support these tasks developed as part of the cyberinfrastructure at the NSF Science and Technology Center for Coastal Margin Observation and Prediction integrating a provenance-aware workflow system, 3D visualization, and a remote query engine for large-scale ocean circulation models. We show how these disparate tools complement each other and give examples of real scientific insights delivered by the integrated system. We conclude that data management solutions for eScience require this kind of holistic, integrative approach, explain how our approach may be generalized, and recommend a broader, application-oriented research agenda to explore relevant architectures.

Geo-Referenced, Abundance Calibrated Ocean Distribution of Chinook Salmon ( Oncorhynchus tshawytscha ) Stocks across the West Coast of North America

Understanding seasonal migration and localized persistence of populations is critical for effective species harvest and conservation management. Pacific salmon (genus Oncorhynchus) forecasting models predict stock composition, abundance, and distribution during annual assessments of proposed fisheries impacts. Most models, however, fail to account for the influence of biophysical factors on year-to-year fluctuations in migratory distributions and stock-specific survival. In this study, the ocean distribution and relative abundance of Chinook salmon (O. tshawytscha) stocks encountered in the California Current large marine ecosystem, U.S.A were inferred using catch-per-unit effort (CPUE) fisheries and genetic stock identification data. In contrast to stock distributions estimated through coded-wire-tag recoveries (typically limited to hatchery salmon), stock-specific CPUE provides information for both wild and hatchery fish. Furthermore, in contrast to stock composition results, the stock-specific CPUE metric is independent of other stocks and is easily interpreted over multiple temporal or spatial scales. Tests for correlations between stock-specific CPUE and stock composition estimates revealed these measures diverged once proportional contributions of locally rare stocks were excluded from data sets. A novel aspect of this study was collection of data both in areas closed to commercial fisheries and during normal, open commercial fisheries. Because fishing fleet efficiency influences catch rates, we tested whether CPUE differed between closed area (non-retention) and open area (retention) data sets. A weak effect was indicated for some, but not all, analyzed cases. Novel visualizations produced from stock-specific CPUE-based ocean abundance facilitates consideration of how highly refined, spatial and genetic information could be incorporated in ocean fisheries management systems and for investigations of biogeographic factors that influence migratory distributions of fish.

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...

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.