This project will reconstruct the total return of sockeye salmon to the Kvichak River to identify: 1) which of four stocks are most utilized by subsistence fisheries; 2) when these stocks migrate through the commercial fishery and escapement monitoring tower; and 3) if there are temporal trends in migration that may allow commercial fisheries managers to protect stocks important to subsistence fisheries. In addition, by building upon existing smolt stock composition data, this project will evaluate survival and productivity of brood years 2012–2015 at smolt and returning adult life stages.

Objective 1:
Subsistence sampling by Local Research Assistants
In each of the 5 study communities, 2 local research assistants (LRA’s) were hired to assist with genetic and ASL sampling effort. Project staff worked with the local tribal councils and other knowledgeable community members to identify potential LRA’s who would be interested in developing sockeye salmon sampling skills. Mr. Dann and Ms. Jones traveled to each community before the sockeye salmon season to conduct outreach and work closely with selected LRA’s to provide technical training and experience. LRA sampling began in 2017 and continue through 2019, although sampling of Nondalton and Pedro Bay harvests in 2017 was not successful. 

Sampling for age, sex and length
During commercial and escapement sampling, scales were removed from the preferred area of each fish and placed on an adhesive-coated card for subsequent ageing (Clutter and Whitesel 1956; Welander 1940). Otoliths were collected from subsistence harvests to determine age after reading by the Mark, Tag and Age Lab in Juneau, AK. Sex was identified from external morphometric characteristics (i.e., protruding ovipositor on females or a developing kype on males) or during salmon processing. Mid-eye to tail fork (METF) length will be measured to the nearest millimeter. Sockeye salmon were sampled for ASL composition without regard to size, sex, length, or location. ASL composition data wererecorded on data sheets and paired with tissue samples.

Tissue Sampling for MSA
All fish sampled for ASL were also sampled for tissues suitable for genetic analysis. A 1 ½ cm (half-inch) piece of the axillary process was removed from each fish and placed on a tissue card to be dried. Each tissue card was paired with a scale card; each had 48 gird spaces, holding up to 48 axillary fins, and the girds were sequentially numbered and gird numbers recorded on data sheets. All tissue cards were collected by the Commercial Fisheries and Subsistence division staff post season and provided to the ADF&G Gene Conservation Laboratory in Anchorage for analysis.

Objectives 2 and 3: 
Laboratory Analysis
Mixed stock analysis by the ADF&G Gene Conservation Laboratory followed standardized procedures similar to those previously applied in similar studies (Dann et al. 2012). The experimental design of the study analyzed mixtures of escapement and commercial and subsistence harvests in strata of 190 fish (Table 1). The design allowed for four temporal strata within the Naknek-Kvichak District plus one stratum to analyze the Kvichak Section setnet harvest separately in each year; this design parallels past MSA of commercial harvests and is appropriate for characterizing temporal changes in a large, temporally compressed harvest. Three temporal strata characterized temporal trends in escapement past the counting tower at Iguigig, while each village center was analyzed separately (Iliamna-Newhalen harvests combined as in Division of Subsistence studies). Samples of subsistence harvests were unavailable for 2016.

Table 1: Experimental design of proposed project to identify the stock composition of: subsistence fisheries in five village centers, the commercial harvest in five temporal strata in each year, and the escapement to the Kvichak River in three temporal strata in each year. Numbers represent the numbers of strata (before X) and individuals in each stratum (after X) for each analysis category in each of four years. Note that subsistence samples will be unavailable from 2016 but can be sampled from commercial harvest and escapement from existing sampling platforms.
Year    Escapement    Commercial     Subsistence    Total
2016          3 X 190           5 X 190    Unavailable    1,520
2017          3 X 190           5 X 190          5 X 190    2,470
2018          3 X 190           5 X 190          5 X 190    2,470
2019          3 X 190           5 X 190          5 X 190    2,470
Total              2,280               3,800             2,850    8,930

Genomic DNA was extracted from tissue samples using a NucleoSpin® 96 Tissue Kit by Macherey-Nagel (Düren, Germany). DNA was screened for 96 SNPs using a Fluidigm® platform. When necessary, SNPs were rescreened on an Applied Biosystems® platform as a backup method for assaying genotypes. Approximately 8% of individuals analyzed for this project were re-extracted and genotyped as a quality control measure to identify laboratory errors and to measure the background discrepancy rate of the genotyping process. Genotypes were imported and archived in the Gene Conservation Laboratory Oracle database, LOKI.

Statistical Analysis
Only individuals with high-quality data were included in MSA. Data quality control included identifying and removing individuals missing >20% genotypic data, duplicate individuals, and non-sockeye salmon. Stock composition for each stratum was estimated using the software package BAYES (Pella and Masuda 2001). A series of independent Markov Chain Monte Carlo (MCMC) chains with different starting values for each population was combined to form the posterior distribution describing the stock composition of each sample from a location-by-time strata. The analysis tabulated summary statistics from these distributions to describe stock compositions.

Stock composition estimates of commercial harvest and escapements were applied to observed harvest and escapement numbers to quantify stock-specific harvests and escapements through time within each season (2016–2019). Visualization of these abundances through time and simple time series models such as AR-1 were fit to observed stock-specific abundances in each location to characterize temporal trends in stock-specific abundances within seasons.

Please see associated "KvichakSockeyeReturnsreadme.txt" file for additional usage details.