346 
Fishery Bulletin 1 13(3) 
Table 1 
Estimates of the mean (p) and standard deviation (a) of 
the size-at-age distribution, by month, and the resulting 
proportion of legal-size fish (p) under three commonly 
employed minimum size limits (/). Size units are total 
length in inches. 
P 
Year 
Month 
P 
o 
1= 20 
1= 24 
1=26 
y 
Feb 
19.74 
1.66 
0.438 
0.035 
0.035 
Mar 
20.77 
1.70 
0.674 
0.035 
0.035 
Apr 
21.85 
1.79 
0.849 
0.115 
0.035 
May 
22.94 
1.88 
0.941 
0.286 
0.052 
Jun 
24.02 
1.97 
0.979 
0.504 
0.157 
Jul 
25.10 
2.06 
0.993 
0.704 
0.331 
Aug 
26.20 
2.15 
0.998 
0.847 
0.537 
Sep 
27.28 
2.24 
0.999 
0.929 
0.717 
Oct 
28.37 
2.33 
1.000 
0.970 
0.846 
Nov 
29.45 
2.41 
1.000 
0.988 
0.923 
Dec 
29.72 
2.44 
1.000 
0.991 
0.937 
y + 1 
Jan 
29.21 
2.40 
1.000 
0.985 
0.910 
each replication, an estimate of contact rate per unit 
of effort was sampled independently for each month, 
management area, and sector in the period 2000-2012 
and applied to the years 1978-2012. For the inferred 
contact rate per unit of effort in February and March 
for the recreational fishery, the root-finding procedure 
was performed as previously described in each of the 
20,000 replications. Impact-rate uncertainty was char- 
acterized by the 0.68 percentile interval of the 20,000 
replication bootstrap distribution (Efron and Tibshi- 
rani, 1993). For a normally distributed estimator, the 
0.68 percentile interval corresponds to the mean ± 1 
standard error (Zar, 1999). 
Results 
Model results provide evidence that the highest im- 
pact rates occurred between the mid-1980s and the 
mid-1990s followed by a substantial decrease (Fig. 3). 
For several years in the period 1985-1995, the lower 
bound of the 0.68 percentile interval exceeded the up- 
per bound of the 0.68 percentile interval for the post- 
2000 period. The hindcasts from the impact-rate model 
generally captured the variation in the impact rates 
estimated directly from coded-wire tag data by using 
cohort reconstruction methods in recent years. 
There was evidence for a substantial difference in 
1980 1985 1990 
1995 
Year 
2000 2005 2010 
Figure 3 
Time series of hindcast impact rates for the years 1978-2012 for 
Sacramento River winter Chinook salmon (Oncorhynchus tshawyts- 
cha) south of Point Arena, California. The black line represents the 
median, and the shaded area indicates the 0.68 percentile interval 
of the bootstrap distribution. The dots indicate estimates of the im- 
pact rate derived with cohort reconstruction methods. 
the impact-rate trajectories between the 
commercial and recreational sectors (Fig. 
4A). The impact-rate time series for the 
commercial sector showed a nearly mono- 
tonic decline from 1978 through 2012. In 
contrast, the impact rate for the recreational 
sector exhibited much more variation, and 
maximum impact rates occurred in the mid- 
dle of the time series. This pattern of sector- 
specific impact rates led to divergence in the 
proportions of the impact rate attributable 
to the 2 sectors over time (Fig. 4B). In the 
early portion of the time series (before the 
mid-1980s), the commercial and recreational 
sectors contributed approximately equally 
to the total impact rate. Subsequently, the 
share of the impact rate attributed to the 
recreational sector increased and stabilized 
at approximately 80% of the overall impact 
rate. 
Estimates of contact rates per unit of ef- 
fort that were used to inform the impact-rate 
hindcasts differed across fishery sectors and 
management areas (Fig. 5). Distributions of 
month-specific contact rates per unit of ef- 
fort in most cases were skewed, with the 
mean exceeding the median. This pattern 
was most evident in the MO management 
area where the maximum contact rates per 
unit of effort in both the commercial and 
recreational sectors were much higher than 
the corresponding sectors in the SF manage- 
