FISHERY BULLETIN: VOL. 87. NO. 2, 1989 



Table 4.— Outline of frequency range for common alleles, heterozygosity, and diversity 

 for 25 polymorphic loci of Chinook salmon sampled from British Columbia through Cali- 

 fornia. Single entries for isoloci assume identical allele frequencies for individual loci. Loca- 

 tions and areas are based on map codes of Table 1 and Figure 1 . Only areas are iden- 

 tified when one or more populations of an area have a maximum value of 1.000. Both 

 locations and areas are identified for maximum values less than 1 .000. 



measures, and plots of principal component scores) 

 assist in identifying patterns of allelic variability. 

 The approximate location of each population is iden- 

 tified in Figure 2 on the basis of its inclusion in one 

 of eight clusters (diverging beyond a genetic dis- 

 tance of 0.01) or major subgroupings (below a 

 genetic distance of 0.01). A notable feature of Figure 



2 is the geographic basis for much of the aggrega- 

 tion. For instance, clusters 1 and 2 represent down- 

 stream populations of the Columbia River, cluster 



3 contains the two northernmost populations of 

 Georgia Strait, and cluster 4 is comprised of coastal 

 populations from Vancouver Island southward 

 through Oregon. The nine population units shown 

 in Figure 2 are explained in the following section 

 and represent a synthesis of possible relationships 

 among these 65 populations. 



The two plots of principal components (Fig. 3) pro- 

 vide an alternative picture of the allelic variation 

 based on different perspectives of the total variance 

 in a multidimensional space. The first four principal 

 components (PC), which account for almost 80% of 

 the total genetic variation, also project a geographic 

 picture of this variation in these plottings. Six of 

 nine population groupings (described in the next sec- 

 tion) are essentially resolved by PCI and PC2. Two 

 of the remaining units are resolved by PCS and PC4. 



We used three different hierarchies in the gene 

 diversity analysis to give a more detailed examina- 

 tion beyond the data on gene diversity presented 

 in Table 4 (Table 5). The hierarchies based on geo- 

 graphic and temporal clusters are discussed at this 

 point; the hierarchy based on population unit 

 clusters is discussed following the synthesis of these 

 units. The geographic hierarchy was based on the 

 locations of the samples using two regions (inland 

 and coastal) with six areas within the inland region 

 and seven areas wdthin the coastal region (see Table 



1). 



The within-population component of gene diver- 

 sity (i.e., the mean average heterozygosity) in each 

 hierarchy was 87.7% of the total diversity (i.e., the 

 expected heterozygosity based on the mean allele 

 frequencies). The remaining 12.3% of the total diver- 

 sity was the index of gene diversity, G(st) resulting 

 from population subdivision (see also Table 5). Most 

 of the gene diversity in the geographic hierarchy 

 was due to genetic differences between populations 

 within areas (4.6%) and areas within regions (6.2%). 

 The regional component contrasting inland popula- 

 tions of major drainages with populations from 

 downstream tributaries and coastal drainages 

 contributed only 1.5% of the total diversity. By far 

 the largest portion of subdivision in the temporal 



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