Steinhorst et al.: Estimates of abundance for the run composition of salmonids 
7 
Table 3 
Sample size {n, number of steelhead), abundance estimate, and individual and joint 
confidence interval half-width (%) for groups of wild steelhead trout {Oncorhynchus 
mykiss) that spawned in 2011. Values are given for groups defined by sex, brood year 
(BY), or stock (identified by the location where the stock spawns). 
Group 
n 
Abundance 
Individual 
Joint 
Total wild fish 
4701 
44,133 
2.3 
2.8 
Females 
1466 
29,541 
2.4 
2.8 
Males 
732 
14,592 
2.8 
3.2 
BY2004 
38 
784 
8.4 
12.3 
BY2005 
520 
11,239 
3.6 
4.8 
BY2006 
994 
21,449 
2.6 
3.5 
BY2007 
473 
10,103 
3.7 
5.0 
BY2008 
26 
558 
10.1 
13.8 
Grande Ronde 
472 
9442 
7.1 
11.9 
Imnaha 
168 
3318 
11.9 
21.0 
Lower Clearwater 
173 
3421 
12.4 
20.3 
Lower Salmon 
98 
1941 
16.3 
26.5 
Lower Snake 
219 
4374 
10.3 
17.5 
Middle Fork Salmon 
214 
4312 
10.8 
15.9 
South Fork Clearwater 
233 
4228 
10.4 
15.8 
South Fork Salmon 
135 
2512 
13.8 
20.6 
Upper Clearwater 
215 
3885 
11.4 
18.2 
Upper Salmon 
340 
6699 
8.1 
12.8 
when numbers by age were estimated, but the asymp- 
totically normal CIs had poor coverage in one case for 
each estimator type. Average Cl coverage among stocks 
was similar between the pooled estimators: 87.7% for 
the pooled asymptotically normal estimator and 88.2% 
for the pooled bootstrap estimator. Average Cl coverage 
was slightly higher for the stratified estimators: 88.1% 
for the stratified asymptotically normal estimator and 
89.0% for the stratified bootstrap estimator. The pooled 
estimators had unacceptable bias and very poor Cl 
coverage for 3 of the 10 stocks, whereas the stratified 
estimators had acceptable accuracy for all stocks. Av- 
erage Cl coverage among stocks was similar for the 
pooled estimators: 81.5% for the pooled asymptotically 
normal estimator and 82.2% for the pooled bootstrap 
estimator. In contrast, average Cl coverage was higher 
for the stratified estimators, although it was similar 
between them: 88.4% for the stratified asymptotically 
normal estimator and 89.0% for the stratified bootstrap 
estimator. 
Problems with pooled estimators became even more 
prevalent when we addressed age by stock; however, 
the performance of the stratified estimators also began 
to suffer as the number of groups to be estimated in- 
creased to 50 (Table 2). The pooled estimators had un- 
acceptable levels of bias in 21 cases, whereas the strat- 
ified estimators had unacceptable bias in 3 cases. Poor 
performance was most common in groups composed of 
steelhead from the least abundant BYs. Instances of 
poor Cl coverage were usually, but not always, asso- 
ciated with unacceptably high bias. Overall, stratified 
estimators performed better than pooled estimators. 
Further, the bootstrap CIs had better coverage than 
the asymptotically normal CIs; in 3 instances, asymp- 
totically normal CIs had very poor coverage (<80%), 
but there were no such instances for the bootstrap CIs. 
For this reason, we applied the stratified bootstrap es- 
timator to the SY2011 data to develop guidelines for 
sampling and interpretation of such data. 
Application of the stratified bootstrap estimator to data 
from SY201 1 
During SY2011, 208,296 steelhead were counted at 
LGD. Of these fish, 44,133 steelhead were estimated to 
be wild (21.2%, Table 3). The 90% Cl was 43,152-45,140 
wild steelhead. There were approximately twice as 
many females as males. Sex ratio varies annually, but 
the ratios seen in 2011 were typical. The middle age 
groups had more returning fish than the youngest and 
oldest age groups. Stocks were not evenly represented 
(e.g., the GRR stock had almost 4 times the number 
as the LOS stock) (Table 4). There were 46 stock-by- 
age groups in SY2011; estimated abundance ranged 
from 4912 individuals in the GRR stock in BY2006 to 
21 individuals in the LSN stock in BY2004 (Table 4). 
The composition of a real steelhead run was not as bal- 
anced as that in the simplification used to generate the 
simulated data in this study, and this uneven distribu- 
tion was most apparent in the age-by-stock groups. 
Effects of using individual versus joint CIs depended 
on the complexity (i.e., number of groups) in the vari- 
