Project Information

Title: Assessment of Genetic Stock Structure of Salmonids R059

Project Year and Number: 1992: R059

Other Fiscal Years and Numbers for this Project: None

Principal Investigator (PI): Lisa Seeb (Alaska Department of Fish & Game)

Managing Agency: ADFG

Assisting Personnel: Richard Gates, Chris Habicht, Jim Seeb

Research Location: KEN

Restoration Category: Damage Assessment

Injured Resources Addressed: Pink Salmon, Sockeye Salmon

Abstract: The overescapement that occurred after the Exxon Valdez oil spill is expected to cause a severe decline in adult returns in 1993 and 1994. Total closure or severe reduction of the commercial and sport sockeye fisheries may be necessary in those years to enable recovery of this species. Genetic stock identification (GSI) techniques will be implemented to manage the harvest of these spill injured stocks in Cook Inlet mixed harvest areas. GSI has only recently been applied as an in season management tool, and it has proven to be extremely effective for allocating and adjusting the harvest of stocks intercepted in stock mixtures such as those that occur in Cook Inlet (e.g., White and Shaklee 1991). Starting in 1992, baseline genetic data will be collected from 28 subpopulations from the Kenai, Kasilof, and Susitna Rivers. Samples from the Cook Inlet commercial harvest will be analyzed and reduced to stock components using these data and GSI techniques in subsequent years. Area managers will use this information to modify fishing areas and openings in order to facilitate harvest of the surplus Kasilof River and Susitna River stocks while protecting the oil spill injured Kenai River stocks. Fishing time in the Upper Cook Inlet area was greatly reduced in 1989 due to the presence of oil from the Exxon Valdez oil spill. As a direct result, sockeye salmon spawning in the Kenai River system exceeded optimal escapement goals by three times. This extremely high escapement may have produced enough fry to not only deplete invertebrate prey populations and cause high fry mortality, but also to alter the species composition and productivity of prey populations for several years. Controlling sockeye salmon fry production by closely regulating the number of spawning adults may be the only way to restore the productivity of these rearing areas. Attempts to use stock identification to manage harvest of Cook Inlet sockeye salmon relied on scale growth patterns in the past. Alaska Department of Fish and Game (ADF&G) evaluated both scale pattern analysis and GSI during the mid-1970's, and at that time, with only three genetic markers and limited baseline data available (e.g., see Grant et al. 1980), decided to pursue the use of data from scales. However, the accuracy and precision of the scale technique alone has not been great and it is insufficient to permit the in season protection of the injured Kenai River stocks. Fortunately, GSI analyses have proven extremely effective for stock management in recent years (Seeb et al. 1986, 1990, Shaklee and Phelps 1990, White and Shaklee 1991), and many additional genetic markers have been found which discriminate stocks of sockeye salmon (e.g., Wilmot and Burger 1985, Tony Gharrett and Paul Aebersold, NMFS, personal communication). Seeb and Wishard (1977) found five marker loci which resolved mixed stock samples of sockeye salmon from the Lake Washington drainage; Grant et al. (1980) showed a high degree of success using the three markers to classify samples from the Kasilof and Susitna drainages, but incomplete baseline data confounded the Kenai River classifications. Strong supporting evidence (described above and including sockeye salmon data from Bob Davis, ADF&G, unpublished; and Richard Wilmott USFWS, unpublished) indicate that GSI analyses including many marker loci and complete baseline data will provide accurate estimates of stock composition for in season protection of the Kenai River stocks. Additionally, ADF&G and NMFS personnel recently discovered that parasite data may provide stock discriminating power for Cook Inlet stocks (Tarbox et al. 1991). The ADF&G plans to evaluate the use of all possible techniques to maximize the accuracy and precision of stock identification analyses (cf., Wood et al. 1989, R-53) and will incorporate parasite data into the GSI models.


Proposal: Not Available

Reports:
Final Report: View (5,490 KB)

Publications from this Project: None Available