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Precision of Redd Based Escapement Estimates for Steelhead Bryce Glaser - WDFW Dan Rawding – WDFW Wan. Ying Chang - WDFW
OVERVIEW WDFW Steelhead Escapement Estimation Methodologies Focus on Redd Surveys Precision Goals for Monitoring Sources of Uncertainty in Redd Surveys Examples of Precision in LCR Estimates Conclusion/Implications
WDFW Steelhead Escapement Redd surveys - the most common method of estimating escapement used by WDFW. Census Counts - when possible weirs and/or barriers are used to census steelhead. Mark–Recapture - in other cases weirs, fish ladders, seining and/or snorkeling are used for mark-recapture programs.
Why Redd Surveys? Tradition Ease of implementation. Relatively inexpensive/Cost Effective. Provide a straight forward estimate of females. Provide an estimate of spawners, not run size as from mark-recapture. Other escapement methodologies may be more difficult. Provide the ability to estimate fine scale spatial structure if redd locations are GPS’d.
Downside to Redd Surveys: Relatively Imprecise Salmon & Steelhead Escapement Index
Redd Count Expansion Redd Count # of Females × Females / Redd × Adults/Female (Sex Ratio) ═ ═ # of Females Spawner Escapement Estimate
Redd Count Expansion Redd Count × Fish / Redd ═ Spawner Escapement Estimate
Redd Surveys Calibrated Survey – Escapement estimate and sex ratio is obtained from a weir or mark-recapture program. Females or fish per redd = Estimated #of females or fish/redd estimate. In years of no trapping or mark-recapture - the redd estimate is expanded by the females per redd estimate and sex ratio or simply by fish per redd to estimate escapement. Partially Calibrated Survey – Estimate of females per redd and sex ratios, or fish per redd obtained from another basin is used to expand the redd estimate for the population of concern. Uncalibrated Survey – professional judgment is used to estimate females or fish per redd.
Assumptions Calibrated Redd Surveys Redds are consistently identified and enumerated. Observer efficiency is incorporated into the females per redd estimate. Partially Calibrated Redd Surveys Above assumptions plus…. . Fish or females per redd estimate and observer efficiency is the same for the source population (calibrated) & the population where applied (partially calibrated surveys). Spatial distribution of spawning is known. Temporal spawning pattern is known. A statistically valid spatial and temporal study design is established if survey is not a census.
Precision Goals for Monitoring NOAA’s Draft Guidance for Monitoring Recovery of Pacific Northwest Salmon and Steelhead (Crawford & Rumsey 2009) CV on average of 15% or less for adult abundance. Robson & Regier (1964) Research Goal: 95% CI of + 10% of point estimate. Management goal: 95% CI of + 25% of point estimate. Cousens et al. (1982) 95% CI of + 20% of point estimate – considered to be good.
Sources of Uncertainty Females/Redd WDFW standard methodology - Snow Creek data. Sex Ratios WDFW standard methodology – Assumes 1: 1 ratio. Kalama River data Sampling Design Census – Example - Mill, Abernathy, Germany creeks Index/Supplemental – Examples - Coweeman and Elochoman rivers. Generalized random tessellation stratified (GRTS) sampling
Females per Redd Slope = 0. 001 Ho: slope = 0, not rejected p - value = 0. 545 Snow Creek estimate based on calibrated redd surveys compared to the weir count of females from 1977 -89. Mean =0. 804, SD = 0. 152, CV = 19% Females per redd is constant over the range of escapement.
Sex Ratio WDFW has historically used a 1: 1 sex ratio for expansions (= 2 fish per female). Kalama Winter Steelhead - Fish per female Kalama Falls Hatchery – operates a fish ladder trap and barrier falls. Mean fish per female = 1. 85 (54% females, 46% males). SD = 0. 109, CV = 6% Assume sex ratio is constant regardless of run size.
Sampling Design Census Entire spawning area is surveyed Index/Supplemental Indices in mainstem and tributaries are surveyed. At peak spawning time in index, a supplemental survey occurs in the remainder of the spawning area. Test for differences in % redds visible in tributaries vs. mainstem at the time of supplemental survey. Supplemental survey counts are expanded based on % redds visible in index areas. Generalized random tessellation stratified (GRTS) Spatially balanced designs (EMAP)
Escapement Estimates from Census Mill, Abernathy and Germany Creeks 2008
Escapement Estimates from Census • Sampling design is census: CV= 0 • Uncertainty from Females/Redd and Sex Ratio • CV = 20%; equivalent to 95% CI + 40%
Index/Supplemental –Coweeman River
Index/Supplemental –Coweeman River Sampling Design – Index/Supplemental: CV = 17% Uncertainty from sampling design, females/redd and sex ratio: CV=26%; 95% CI + 51% Escapement Estimate: 631 14% of the redds were in index surveys 86% of redds were in supplemental surveys Test for differences in mainstem vs. trib. indices. separate timing expansion for tributaries and mainstem was necessary (Chi-square test, p=0. 013)
Index/Supplemental –Elochoman River
Index/Supplemental –Elochoman River • Sampling Design – Index/Supplemental: CV = 5% • Uncertainty from sampling design, females/redd and sex ratio: CV=20%; 95% CI + 40% • Escapement Estimate: 286 • 42% of the redds were in index surveys • 58% of redds were in supplemental surveys • Test for differences in mainstem vs. trib. indices. • no difference (Chi-square test p=0. 97) • single timing expansion.
General random tessellation stratified (GRTS) designs Used extensively in Oregon Advantage – provides unbiased estimate ODFW Targeted Sampling Rate to achieve CV ≤ 15% Hypothetical Example: ODFW Targeted Sampling: CV = 15% WDFW Females per Redd: CV = 19% WDFW (Kalama) Sex Ratio: CV = 6% Escapement CV= 24%, 95% CI + 49%
Precision Comparison Sampling Design Census MAG CV 20% 95% CI + 40% Index/Supp. Coweeman Elochoman GRTS 26% 20% 24% + 51% + 40% + 49%
Summary Redd surveys are inexpensive, but also imprecise compared to other methods. Largest source of variation in redd based escapement estimates is from females or fish per redd estimates. Smallest source of variation is from sex ratios. CV for spatial sampling designs depends on effort. Escapement CV ranges from 20% for a census, to ~25% for GRTS and index/supplemental designs.
Summary If redd surveys are to be used to estimate escapement, WDFW needs additional calibrated studies to better estimate females or fish per redd. If redd based escapement estimates are not able to meet established ESA, Research and/or management precision goals for key populations, then alternate escapement methods should be considered. Mark-recapture or weirs for selected steelhead populations Possibly the use of imaging sonar for steelhead.
Acknowledgements Funding for LCR surveys: NOAA via Mitchell Act funds Washington State Salmon Recovery Funding Board Thom Johnson & Randy Cooper - Snow Cr. data. Cameron Sharpe and Kalama Research Team Kalama R. data. Biologists and technicians that conducted redd surveys.
Literature Cited Cousens, N. B. F. , G. A. Thomas, C. G. Swann, and M. C. Healy. 1982. A review of salmon escapement estimation techniques. Canadian Technical Report of Fisheries and Aquatic Sciences. 1108. Crawford, B. A. and S. Rumsey. 2009 (Draft). Guidance for monitoring recovery of Pacific Northwest salmon and steelhead listed under the Federal Endangered Species Act (Idaho, Oregon, and Washington). NOAA’s National Marine Fisheries Service – Northwest Region, Portland, OR. Robson, D. S. , and H. A. Regier. 1964. Sample size in Petersen mark-recapture experiments. Transactions of the American Fisheries Society 93: 215 -226.