Appendix A. A table showing thermocycler profiles, PCR reagents, and multiplex combinations for Camp Creek coastal cutthroat trout DNA amplification.

A table showing thermocycler profiles, PCR reagents, and multiplex combinations for Camp Creek coastal cutthroat trout DNA amplification

Quantifying the Uncertainty of a Juvenile Chinook Salmon Race Identification Method for a Mixed-Race Stock

<div><p><i></i>Expected daily FL ranges (length at date) of juvenile Chinook Salmon <i>Oncorhynchus tshawytscha</i> have been used throughout California's Central Valley to identify federally listed winter-run and spring-run juveniles in a mixed four-race stock. Accurate race identification is critical both to species recovery and to management of the water supply for 25 million people and a multibillion-dollar agricultural industry. We used genetic race assignment of 11,609 juveniles sampled over 6 years to characterize the accuracy of the length-at-date approach, specifically by testing two of its central assumptions: (1) juvenile FL distributions do not overlap between races on a daily basis; and (2) the growth rates that are used to project FL at date are accurate. We found that 49% of FLs for genetically identified juveniles occurred outside the expected length-at-date ranges for their respective races, and we observed a high degree of overlap in FL ranges among the four races. In addition, empirical growth rates were well below those from which length-at-date criteria were derived. Given the high degree of FL overlap between races, we conclude that modification of the length-at-date method will not substantially reduce identification error. Thus, we recommend that genetic assignment be used at least as a supplemental approach to improve Central Valley Chinook Salmon race identification, research, and management.</p><p>Received January 7, 2014; accepted July 22, 2014</p></div

Appendix B. A table showing microsatellite locus summary for Camp Creek coastal cutthroat trout populations (including subsamples from age groups and sample years).

A table showing microsatellite locus summary for Camp Creek coastal cutthroat trout populations (including subsamples from age groups and sample years)

DPJ_ FRH09 9Msats and 7 genes (07 19 12)rev

Excel file containing genotype data for Feather River Chinook salmon. Individuals are identified by population in each row: Fall, Spring and FRS (fall return spring). Loci are designated by column with the nine microsatellite listed followed by seven adaptive markers

S.diploproa_referencePop_genotypes

Microsatellite (20 loci) genotipe data of 94 adult Sebastes diploproa collected off the Oregon Coast in May-July 2015

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

<div><p>Understanding seasonal migration and localized persistence of populations is critical for effective species harvest and conservation management. Pacific salmon (genus <i>Oncorhynchus</i>) 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 (<i>O</i>. <i>tshawytscha</i>) 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.</p></div

Comparison of catch per unit effort (CPUE) for non-retention and retention fisheries sampling techniques.

<p>Comparison between CPUE (vessel-day fishing effort) for individual areas sampled using non-retention and retention techniques. Difference in CPUE was evaluated using a log-linear negative binomial model, rejecting the null hypothesis of no difference between CPUE at a probability of p < 0.05 (Fishery R; shown in bold). In areas San Francisco (SF-n, -s) and Monterey (MO-n, -s) the July 1–4 and 8–11 retention fishery was compared to the July 12–31 non-retention fishery. For area Fort Bragg (FB), the retention fishery conducted on July days 1–4, 8–11, and 15–29 was compared to the June non-retention fishery.</p><p>Comparison of catch per unit effort (CPUE) for non-retention and retention fisheries sampling techniques.</p

Numbers of sub-legal and legal-sized Chinook salmon encounters.

<p>¹ Eight fish encounters were excluded from CPUE calculations (see text for details).</p><p>² Open July 1–4, 8–11, 15–29, and all of August.</p><p>³ Open July 1–4, 8–11.</p><p>Monthly numbers of sub-legal and legal-sized Chinook salmon encounters recorded at-sea during 2010. Area abbreviations (also see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131276#pone.0131276.g001" target="_blank">Fig 1</a>): North Oregon Coast (NO), Central Oregon Coast (CO), Oregon Klamath Zone (KO), California Klamath Zone-north (KC-n), Fort Bragg (FB), San Francisco north (SF-n) and south (SF-s), Monterey north (MO-n) and south (MO-s). Retention fishery sampling is indicated by bold, mixed retention/non-retention fisheries sampling by italic, and non-retention fisheries by regular text.</p><p>Numbers of sub-legal and legal-sized Chinook salmon encounters.</p

Mean catch per unit effort and 95% confidence intervals.

<p>Mean catch per unit effort (CPUE) was modeled for nine area strata using a negative binomial model CPUE ~ month x area. CPUE is the number of legal-sized fish caught per vessel-day fishing effort. Area abbreviations (also see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131276#pone.0131276.g001" target="_blank">Fig 1</a>): North Oregon Coast (NO), Central Oregon Coast (CO), Oregon Klamath Zone (KO), California Klamath Zone-north (KC-n), Fort Bragg (FB), San Francisco north (SF-n) and south (SF-s), Monterey north (MO-n) and south (MO-s).</p

Contour plots of Chinook salmon log-catch per unit effort and genetic stock composition.

<p>Log catch per vessel-day fishing effort (CPUE) (a–d) and stock composition estimates (e–h) are presented for nine area (y-axis) and five month (x-axis) strata. Results are shown for all stocks (CPUE only), and for stock groupings Columbia River/Snake complex, Klamath, and California Central Valley fall. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0131276#pone.0131276.g001" target="_blank">Fig 1</a> and text for area abbreviations and sampling details. No sampling was conducted in KO/May and KC-n/May and KC-s, all season.</p