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Fishery Bulletin 107(3) 
equals 10% of the slope at the origin (F 0 Gulland 
and Boerema, 1973) and the fishing mortality rate cor- 
responding to a specific percentage ( x % ) of the spawn- 
ing biomass per recruit at the unfished level (F SSBx ) 
for the eastern Taiwan sailfish stock. The status of the 
fishery for this stock could be examined by comparing 
the fishing mortality at the current level (F CUR ) with 
the biological reference points. 
A per-recruit analysis requires information on growth, 
mortalities, and selectivity of fishing gear. Catch curve 
analysis (Ricker, 1975) is the most common method 
employed for estimating total mortality when data on 
the age composition of catch are available. For a speci- 
fied natural mortality, F CUR could be computed simply 
by subtracting the natural mortality from the total 
mortality. However, in most cases large uncertainty is 
associated with the estimation of natural mortality and 
other life history parameters, which can lead to large 
uncertainty in the estimation of F CUR and biological 
reference points. 
The objective of this study was to evaluate the cur- 
rent status of the sailfish fishery in waters off eastern 
Taiwan by comparing the current fishing mortality 
rate (estimated from analyzing length composition data 
collected from the fishery) with the biological reference 
points derived from the per-recruit analyses (Butter- 
worth et al., 1989; Sun et al., 2002, 2005). In addi- 
tion, a Monte Carlo simulation study was conducted for 
evaluating the influence of uncertainty associated with 
mortalities and the age at first catch ( t c ) on the estima- 
tion of biological reference points. This study provides 
an approach that can be used to assess the status of 
fisheries for which limited information does not allow 
us to conduct a full stock assessment. 
Materials and methods 
Length and age composition of the catch 
Length composition data were obtained by measuring 
sailfish landed at the Shinkang fish market in eastern 
Taiwan (Fig. 1) during the period from July 1998 to July 
2005. Specimens were randomly selected from the land- 
ings and measured for their lengths and weights. The 
sex of each specimen was identified from the appearance 
of its gonads. Samples of the first dorsal fin were taken 
from 1166 of the sampled individuals for which lengths 
were measured and used to age the sailfish (Chiang et al. 
2004). These subsampled fish were used to construct sex- 
specific age-length keys, which in turn were used to con- 
vert the length-frequency data into age-composition data. 
Estimating mortality rates 
For each sex, the dynamics of a simulated year class can 
be projected forward from one year to another by using 
the exponential survival equation (Ricker, 1975): 
N t+1 = N t e~ (M+FSt) , (1) 
Figure 1 
The fishing grounds where sailfish ( Istiophorus 
platypterus) are caught as bycatch in the gill- 
net, harpoon, and longline fisheries based at the 
Shinkang fishing port of Taiwan. Crosshatched 
area is where the gillnet and harpoon fisheries 
take place and the longline fishery takes place in 
larger area indicated by oblique lines. Samples 
were collected during the period from July 1998 
to July 2005 to estimate biological metrics for per- 
recruit analyses. 
where N t 
t\ 
M 
F 
S t 
the number of fish at the beginning of age 
the instantaneous natural mortality rate; 
t the fishing mortality of fully-recruited fish; 
and 
the fishing gear selectivity of fish at age t. 
Selectivity is the relative vulnerability of different age or 
size classes to the fishing gear. In this study, we assumed 
that the selectivity follows a dome-shaped distribution 
because our length-frequency data were mostly col- 
lected from gill nets. This dome-shaped selectivity can 
be quantified with the following normal distribution 
density function: 
S t = 
W 
e 2ct2 , 
( 2 ) 
