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An Approach for Developing Biological Reference Points for Steelhead Populations in the Lower Columbia Region. Bryce Glaser Dan Rawding (WDFW). Biological Reference Points (BRP) ≠ Escapement Goals. BRP are quantitative Spawners at Maximum Sustainable Yield (MSY)
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An Approach for Developing Biological Reference Points for Steelhead Populations in the Lower Columbia Region Bryce Glaser Dan Rawding (WDFW)
Biological Reference Points (BRP) ≠ Escapement Goals • BRP are quantitative • Spawners at Maximum Sustainable Yield (MSY) • Spawners needed to seed habitat • Based on current data not on future expectations • Escapement goals are from policy-technical interaction and ideally are based on fish management philosophy • should include quantitative analysis • risk to persistence • fishery stability or maximization of catch • uncertainty
Overview • Background/Available Data • Approach & Analysis • Initial Results/ Model Performance • Development of BRP • Escapement Goals for LCR Steelhead • Summary/Implications • Questions
Lower Columbia Region (LCR) • Four summer and fourteen winter steelhead populations in Washington • Iteroparous with repeat spawner rate of 5% to 15% • Hatchery releases beginning in 1950’s with Mitchell Act program • Different populations have different levels of hatchery influence and broodstock types
Hatcheries • Hatchery program • Chambers Cr winters (Puget Sound origin) • Skamania summers (Washougal origin) • Local broodstocks (Cowlitz, Kalama, Abernathy) • Relative Reproductive Success (RRS) to smolt stage • Chambers (6%) measured in Forks Creek, • Skamania (30-35%)Kalama & Clackamas River, • Wild Broodstock (>80% -adult stage Hood & Kalama)
Harvest • Mainstem Columbia River - Mixed Stock Fisheries • commercial fisheries- managed for < 2% incidental catch • Stock composition of steelhead catch in both commercial and Treaty fisheries (above BON) is unknown • Sport fisheries have been operated under wild steelhead release since 1984
Mark/Re-sight via Snorkeling Adult Trapping Redd Surveys Juvenile Trapping
LCR Steelhead Challenges • Short data series and high measurement error for redd counts (coefficient of variation ~ 30%) • Standard salmon spawner to adult recruit relationships do not account for iteroparity • Ocean survival has varied over 10-fold in the LCR introducing much variation in adult recruits • Different proportions of hatchery spawners with limited measurements of RRS
Approach • Standardized spawners into wild equivalents using appropriate RRS estimates to discount hatchery spawners to the smolt stage • Standardized SR data into fish density (fish per square kilometer of drainage area) • Developed spawner to smolt relationships to reduce environmental variation caused by 10-fold changes in marine survival and lack of mainstem Columbia River catch estimates by stock • Autocorrelation is not an issue using spawner and smolts • Hierarchical modeling (meta-analysis) using different spawner-smolt-relationships (SRR)
Hierarchical Modeling • Borrow strength from other curves - from those with more data • Estimates shrink towards the mean, which yields improved precision of individual BRP • Compromise between individual and fully pooled estimates • Reduces overfitting of individual curves • Allows individual curves to be fit in cases, where there are few data points, outliers, etc.
Common set of steelhead spawner to smolt relationships • Spawner to smolt functions come from a random sample of S/R distributions that can be hierarchically modeled.
Analysis • Barrowman, N.J., R.A. Meyers, R. Hilborn, D.G. Kehler, and C.A. Field. The variability among populations of coho salmon in maximum reproductive rate and depensation. Ecological Applications 2003:784-793. (used km available) • Smolts and spawners per sq. kmof drainage area, with spawners adjusted for RRS data • Bayesian hierarchical analysis using WinBUGS with Lognomal error • Vague priors similar to Barrowman so the results are data driven not prior driven • Checked convergence with Brooks-Gelman-Ruben (BGR) statistics.
Smolts per Square Kilometer Hierarchical BH R HS Wild Equivalent Spawners per Square Kilometer
Results • Deviance Information Criteria (DIC) is a Bayesian analog for Akiake Information Criteria (AIC) • Using DIC for model selection BH and HS models were preferred over Ricker model. • These results are consistent with other analysis for yearling anadromous salmonids, that dome shape models (Ricker) do not fit this life history type well.
Model Performance • Yellow Line- drainage area only • Fitting a curve with no S/R data • Pink Line – Individual estimate
Basin Model w/95%CI Superimposed over PNW Population outside LCR Smol ts per Sq km Wild Equivalent Spawners per Sq. KM
Biological Reference Points B = spawners needed to produce 50% of asymptotic smolt estimate S* = inflection point in curve, spawners needed to seed habitat MSP = spawners needed to produce maximum smolt production K = smolt capacity estimate Productivity = slope of curve at origin; est. of population resiliency.
Seeding Levels = 0.4 to 1.7 • Wild Equiv.Spawners per KM^2 • Smolt Capacity = 43 to 55smoltsper KM^2 • Productivity = 66 to 137 smolts • per KM^2
Historic Escapement Goals • Best professional opinion • US v. Oregon TAC recommended 1000 steelhead spawners for the Wind River. • Application of Boldt Case (Puget Sound & Washington Coast) Potential Parr Production model to LCR • Lucas and Nawa (1985) recommended 1400 steelhead spawners for the Wind River Hierarchical Modeling Approach • Using BRP - ~500 spawners for the Wind River (using HS model)
Summary & Implications • BRP are quantitative • useful in developing Escapement Goals. • Hierarchical Model Approach can provide estimates of BRP even for populations with little or no SR data. • Individual curves are improved when data is available. • Basin model sensitive to RRS and HOS estimates, and when spawners use a low fraction of drainage area (Mill-LCR, NF Scappoose) • Basin model potentially useful outside LCR except very small tributaries (OR coast) • Next Steps – model improvement by incorporating steelhead distribution and/or GIS attributes
Summary & Implications • In LCR populations – it appears we have been achieving seeding levels or higher in most years. • In LCR - 12/95 (13%) spawner points < S* • Reassessment of current Escapement Goals for LCR steelhead populations is likely warranted. • If LCR steelhead recovery requires improvement in adult abundance: • increase habitat capacity because we are seeding habitat. • and increase wild stock productivity by decreasing pHOS
Acknowledgements Multiple funding sources NOAA through Mitchell Act, Bonneville Power Administration WDFW Data Asotin – Mark Schuck (WDFW) OR Coast – Eric Suring (ODFW) Snow Ck – Randy Cooper (WDFW) WDFW KRT - Coweeman and Kalama WSPE - Mill, Abernathy, Germany, NF Toutle Region 5 Fish Mgt - Grays, Cedar, EF Lewis, Wind, & Trout Many techs and bios who collected 95 spawner and smolt points since 1977.