FISHERY BULLETIN: VOL, 77, NO. 4 



A VlBRlO-coho 



VIBRIO-steelhead 



100 -\ 



< 



50 



100 n 



i^o 



< 



SO- 



BS 



34 *- 



B VIBRIO coho 



GENOTYPE T t AC CC T T T 



STOCK ROGUE ROGUEIHI alSEA N SAN SILETZ 



D VIBRIO-steelhead 



100-1 



< 



50 



(J 



100 n 



Q 



< 



50- 



z 



LU 



o 



9 « 



39 50 T 



FIGURE 2— Percentages offish of different 

 stocks and transferrin genotypes that died 

 of vibriosis. A and B, coho salmon experi- 

 ments 1 and 2; C and D, steelhead trout 

 experiments 1 and 2 For interpretation of 

 other features see Figure 1 . 



GENOTYPE AA AC T 

 STOCK BIG CR 



AC CC I 

 ALSEA(H) 



GENOTYPE AA AC CC T 

 STOCK ROGUE (H) 



AC CC 1 I 



ALSEA(H1 NSANIHI 



involving hatchery-reared steelhead trout from 

 the Rogue, Alsea, and North Santiam, revealed 

 the same results as did the first, with respect to 

 transferrin genotypes. No differential resistance 

 was shovTO among genotypes, including the AA's, 

 within either the Alsea or Rogue stocks. Although 

 resistance to vibriosis among the three stocks was 

 similar, the North Santiam stock showed the 

 highest mortalities this time — which again em- 

 phasizes the importance of environmental factors 

 in the determination of resistance and the need for 

 eliminating environmental differences in making 

 genetic comparisons. There was a significant dif- 



ference in vertebral number between North San- 

 tiam steelhead trout reared at the hatchery and at 

 Smith Farm, indicating an environmental differ- 

 ence (our unpubl. data). The Rogue replicates in 

 this experiment were significantly different 

 (P<0.025) with respect to stock mortality; con- 

 sequently a genetic comparison was invalid. Ex- 

 cept for the hatchery-reared Rogue replicates in 

 the last vibriosis experiment using steelhead trout, 

 there were no significant differences between rep- 

 licates for stocks or genotypes in all four vibriosis 

 tests; consequently we combined replicates in the 

 data analysis. 



800 



