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that the highest gains in efficiency for the TAPAS de- 
sign, compared with SRS in simulations, were achieved 
when the spatial correlation of fish density was low and 
there was a large number of patches of small size. Such 
circumstances resulted in the TAPAS design sampling 
a high proportion of the total area of patches in the 
population. In addition, Spencer et al. (2012) showed 
that a modified TAPAS design, in which every third 
patch was sampled, resulted in higher efficiency than 
did an SRS design. However, the situations in Spencer 
et al. (2012) where there were significant gains in per- 
formance relative to SRS occurred only when there was 
a strong relationship between S v and CPUE. Everson 
et al. (1996) showed that precision could be most im- 
proved when patches were smallest and they were a low 
proportion of the total survey area such that the prob- 
ability of sampling high-CPUE areas during a random 
survey was low. These results indicate that the TAPAS 
design may show greater gains in precision for biomass 
estimates of a stock that is even more concentrated into 
small areas than is POP. 
For these rockfish stocks, the greatest improvement 
in precision of trawl-survey indices of biomass can be 
achieved by increasing the overall sample size in the 
narrow depth band where they are most abundant. 
The ACS and TAPAS designs are useful frameworks 
for efficiently adding samples in abundant areas, and 
they also can serve to improve the NMFS trawl index 
in specific high-variability strata. Clearly, these designs 
should be applied only in depths and areas of known 
high abundance and variability of a species of interest, 
and the design should use a high threshold for invoking 
additional sampling. 
For the TAPAS design to be applied efficiently, the 
specific acoustic backscatter characteristics of a target 
species need to be well known so that the relationships 
between patch definition, patch length, and CPUE are 
strong. Under these conditions (e.g., a patch station reli- 
ably has high CPUE), it might be beneficial to obtain an 
additional commercial vessel to follow the primary sur- 
vey vessel, sample patch stations, and retain the catch, 
while the primary survey vessel continues to sample 
planned stations. These cost-recovery surveys (e.g., 
Hanselman et al. 2003) have been useful in Alaska as 
zero- or low-cost alternatives to the normal practice of 
discarding catch on purely random surveys. 
Even if a design that combines acoustic surveys and 
trawl surveys could provide superior estimates of bio- 
mass, in practice, such a design would have to be modi- 
fied to a context of a multispecies groundfish survey in 
most situations. Such adaptation is an additional com- 
plication in the use of novel sampling designs, given the 
competing sampling goals and limited resources of fish- 
eries monitoring. In a multispecies context, the TAPAS 
design may be a way to add more sampling effort for 
major species groups that occupy a similar depth or 
area when differentiation of backscatter is difficult (as 
it is for rockfishes and walleye pollock). An avenue of 
future research would be to examine the precision of 
biomass estimates determined with the TAPAS design 
for multiple species that produce significant acoustic 
backscatter. 
Conclusions 
Our work shows that sampling fish populations with 
high spatial variability remains a challenge. To more 
accurately understand acoustic and spatial patterns for 
POP and other rockfishes, it may be necessary to con- 
sider more quantitative acoustic or geostatistical meth- 
ods and to move away from the traditional paradigm of 
bottom trawl surveys (Godp, 2009). However, in areas 
that are fortunate enough to have a long time series 
of standardized fishery-independent surveys, it is rare 
and, perhaps, unwise to make changes to the sampling 
design or the sampling method. TAPAS and analogous 
designs could be used to increase sampling intensity for 
specific stocks, without necessarily creating a break in a 
biomass time series. The potential improvement in the 
precision of biomass estimates through the use of the 
TAPAS design when a strong relationship exists between 
S v and CPUE (Spencer et al., 2012) offers motivation for 
continuing to refine our understanding of acoustic and 
spatial patterns and the methods used to define high- 
CPUE patches. 
Acknowledgments 
This work was supported in part by a grant from the 
North Pacific Research Board (NPRB), project 809, and 
we are grateful to the NPRB for support of this project. 
We thank the crew of the FV Sea Storm, B. VanWinkle, 
and C. Conrath for excellent fieldwork. We thank the 3 
anonymous reviewers who helped to greatly improve the 
manuscript. We also thank P. Hulson and T. Quinn for 
helpful discussions, K. Shotwell for GIS support, and 
G. Fleischer and D. King for their logistical support of 
this project. 
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