Clemento et al.: Evaluation of a single nucleotide polymorphism baseline for genetic stock identification of Oncorhynchus tshawytscha 127 
comparison of CWT with genetic assignments demon- 
strates that our baseline is capable of identifying fish 
to reporting unit with accuracy comparable to that of 
CWTs. Furthermore, the use of GSI can identify consid- 
erably more fish to reporting unit, including fish from 
natural stocks. Confident genetic assignments were ob- 
tained for -94% of fish from the 2010 fishery sample, 
but only 1052 of those fish carried CWTs and this num- 
ber is inflated partially because of oversampling of fish 
believed to carry CWTs. 
Fishery management decisions rely heavily on co- 
hort-based ocean harvest models (cf., O’Farrell et al., 
2012), which require information on both stock of ori- 
gin and age of fish impacted by fisheries. Because GSI 
does not provide the age of individuals, it is not by 
itself an adequate alternative to CWTs. Nonetheless, 
new statistical methods capable of integrating GSI, 
length data, and scale- or otolith-based age data have 
been developed recently, allowing managers to draw 
important inference about PFMC fisheries that are not 
possible with CWTs alone (Satterthwaite et ah, 2014). 
Moreover, pedigree-based genetic tagging does supply 
age for salmon (Anderson and Garza, 2006; Garza and 
Anderson 2 ). This method, termed “parentage-based tag- 
ging” (PBT), can identify the actual parents of a geno- 
typed individual through parentage analysis if they 
have been genotypecl with the same genetic markers. If 
the parents’ date of spawning is known, as it typically 
is in a hatchery, then the reconstructed pedigrees yield 
the offspring’s precise age and any associated parental 
spawning information. 
Importantly, both PBT and GSI can be undertaken 
with the same SNP genotypes, and the SNPs used in 
our GSI baseline are sufficiently powerful for PBT with 
Chinook Salmon from California to Washington (Ander- 
son, 2012). This interoperability of genotype data en- 
ables an integrated program that uses both GSI and 
PBT simultaneously, providing identification for all fish 
in a fishery or ecological sample and yielding signifi- 
cantly greater inference than either method alone. For 
example, GSI cannot distinguish between spring-run 
and fall-run fish from the Feather River Hatchery in 
California, but PBT distinguishes them, almost with- 
out error, from any mixture. Likewise, although it is 
difficult to implement PBT in natural populations, the 
same SNP genotypes used in a PBT analysis permit 
accurate identification (by GSI) of fish from the natu- 
rally spawning, ESA-listed “California Coastal Chinook 
Salmon Evolutionarily Significant Unit.” 
Conclusions 
The advent of high-throughput SNP genotyping al- 
ready has revolutionized human genetics (Jenkins 
and Gibson, 2002), providing previously unattainable 
resolution (e.g., Novembre et ah, 2008) and is poised 
to do the same for fisheries biology and management. 
As described here, we used a careful and statistically 
valid power analysis of SNP genotypes from a large 
number of Chinook Salmon populations concentrated 
at the southern end of the native range of this spe- 
cies to show that SNPs can provide a powerful baseline 
for genetic stock identification (see also Larson et ah, 
2013) in fisheries and ecological investigation in the 
California Current large marine ecosystem and its trib- 
utaries in California and Oregon. We predict that these 
advances in genetic resources and methods will foster 
fundamental improvements in the way salmon popula- 
tions are studied, monitored, and managed. 
Acknowledgments 
The authors would like to thank the entire Molecular 
Ecology and Genetic Analysis Team in the Fisheries 
Ecology Division of the Southwest Fisheries Science 
Center (SWFSC) for their invaluable assistance with 
genotyping and analyses. Of critical importance to the 
successful completion of this project were the baseline 
samples provided to us by the California Department of 
Fish and Game (now Wildlife; S. Harris), Hoopa Valley 
Tribal Fisheries Department (G. Kautsky), Oregon De- 
partment of Fish and Wildlife, Oregon State University 
Department of Fisheries and Wildlife (M. Banks), Ida- 
ho Department of Fish and Game (M. Campbell), Co- 
lumbia River Inter-Tribal Fish Commission (S. Narum), 
NOAA Northwest Fisheries Science Center (P. Moran), 
U.S. Fish and Wildlife Service (M. Brown, D. Hawkins, 
and C. Smith), Washington Department of Fish and 
Wildlife (S. Blankenship and K. Warheit), University of 
Washington School of Aquatic and Fishery Science (L. 
Seeb), Department of Fisheries and Oceans, Canada (T. 
Beacham), and Alaska Department of Fish and Game 
(W. Templin). Fishery samples were collected by the 
California Department of Fish and Game (now Wild- 
life) and provided to us by M. Heisdorf and M. Palmer- 
Zwahlen. We also thank T. Beacham and 2 anonymous 
referees for comments that improved the manuscript. 
This project received funding from NOAA’s Coopera- 
tive Fisheries Research Program and the SWFSC. A. 
Clemento also received support from a California Bay 
Delta Science Fellowship and the University of Califor- 
nia Coastal Environmental Quality Initiative. Many of 
the baseline samples were collected and DNA extracted 
with funds from the Pacific Salmon Commission. 
Literature cited 
Abadia-Cardoso, A., A. J. Clemento, and J. C. Garza. 
2011. Discovery and characterization of single nucleotide 
polymorphisms in steelhead/rainbow trout, Oncorhyn- 
chus mykiss. Mol. Ecol. Resour. 11 (suppl. sl):31-49. 
Abadia-Cardoso, A., E. C. Anderson, D. E. Pearse, and J C. 
Garza 
2013. Large-scale parentage analysis reveals repro- 
ductive patterns and heritability of spawn timing in 
