350 
Fishery Bulletin 113(3) 
However, these inferences may not adequately describe 
the pattern of SRWC contacts in these early months. 
Given the data available, we were unable to make 
management-area-specific inferences of recreational 
contact rates per unit of effort for February and March; 
yet for later months, the estimated contact rates per 
unit of effort tended to be considerably higher in MO 
than in SF. Additionally, estimates of fishing effort for 
1971-1972 do not exist; therefore, we assumed that the 
monthly distribution of effort in those years was simi- 
lar to the distribution during the years 1978-1983. If 
substantial differences in effort occurred between these 
2 periods, those differences would contribute to errors 
in the inferred recreational contact rates per unit of ef- 
fort for February and March. Nonetheless, the monthly 
harvest estimates for 1971-1972 represent the only 
information on the temporal patterns of recreational 
harvest over the protracted seasons that characterized 
historical fishing. 
To account for uncertainty in the hindcasts of im- 
pact rates, we incorporated the variation in estimates 
of contact rates per unit of effort using the bootstrap 
method. Although this approach did not account for 
the full spectrum of uncertainty (e.g., natural mortal- 
ity rate and fishing effort), it is likely that variation 
in the estimated contact rates per unit of effort rep- 
resents the dominant uncertainty because of the high 
level of variability across years and the strong effect 
that contact rates have on impact-rate projections. 
Characterizing uncertainty in contact rates per unit of 
effort by randomly resampling values for month, area, 
and sector strata, however, may have led to admitting 
excess uncertainty into the impact-rate hindcasts. For 
example, in years with extremely high fishing effort 
(e.g., 1995), a few replications produced unrealistic 
estimates where fishery impacts exceeded ocean abun- 
dance. This outcome was caused by randomly sampling 
a very high estimate of contact rate per unit of effort 
that was then multiplied by a very high, stratum-spe- 
cific effort estimate. This outcome is clearly not tenable 
and correlations may exist between the contact rate 
per unit of effort and fishing effort that would prevent 
extinction by ocean fishing. However, strong evidence of 
correlations between contact rate per unit of effort and 
fishing effort were not observed (senior author, unpubl. 
data), and no covariance structure was incorporated 
into the simulation framework. 
Ultimately, there is a need to understand the effects 
of all sources of mortality on the dynamics of the en- 
dangered SRWC population to better explain its popu- 
lation dynamics. Winship et al. (2014) estimated low 
overall productivity for SRWC, likely owing to low fe- 
cundity and low juvenile survival rates, which result- 
ed in low sustainable fishing mortality rates. In the 
absence of hatchery supplementation, Winship et al. 
(2014) estimated a median maximum sustainable level 
of fishing mortality (analogous to maximum sustain- 
able yield) at an impact rate of 0.17, as well as a rate 
of 0.25 under recent levels of hatchery supplementa- 
tion. Regular hatchery supplementation began in 1998 
at the SRWC-dedicated Livingston Stone National Fish 
Hatchery, with little or no hatchery-origin contribu- 
tions to the population in prior years. 
Given the low sustainable impact rates estimated 
by Winship et al. (2014), and the relatively high me- 
dian impact rates inferred for the 1980s and 1990s, it 
is likely that impact rates exceeded maximum sustain- 
able fishing mortality levels and that they could have 
reached levels identified as unsustainable under condi- 
tions with no hatchery supplementation. However, we 
note that there was substantial uncertainty estimated 
for both the maximum sustainable impact rates in 
Winship et al. (2014) and the historical impact rates 
inferred here. In addition, the results of Winship et 
al. (2014) were derived with contemporary (post- 1998) 
data, and it is not known whether the estimated pro- 
ductivity, and, therefore, sustainable impact rates, are 
applicable for earlier time periods. 
Although we present a specific case study for SRWC, 
our ability to hindcast exploitation rates (for years be- 
fore the existence of sufficient data that would have 
allowed direct estimation of exploitation rates) should 
be useful for other fishery applications. The use of for- 
ward projection models in a hindcasting mode can help 
with a better understanding of the relative effects of 
past fisheries and management actions on fish stocks. 
Approaches such as the one developed here have the 
potential to be useful for integrating long-term records 
with existing stock assessments and for performing 
retrospective evaluations of the effectiveness of man- 
agement measures in data-limited situations. 
Acknowledgments 
We would like to thank A. Grover for sharing his insight 
into historical salmon fisheries and fishery sampling in 
California. We are also grateful for the thoughtful and 
thorough reviews provided by M. Mohr, N. Hendrix, 
and 3 anonymous reviewers. 
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Grover, A. M., M. S. Mohr, and M. L. Palmer- Zwahlen. 
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