Hanselman et al : Applications in adaptive cluster sampling of Gulf of Alaska rockfisfi 



509 



(Fujioka^) or a design called TAPAS that hydroacoustically 

 delineates clusters ( Everson et al., 1996). In other surveys, 

 it might be possible to detect the presence of the item of 

 interest without actually surveying the unit (as in aerial 

 surveys. ) 



An ACS design should not be attempted without some 

 prior knowledge of the population distribution. Populations 

 for which the design would be useful should have an aggre- 

 gated distribution that can be described by correlated varia- 

 tion with distance, not just a large variance in relation to the 

 mean. One way to examine the data is to fit variograms to 

 examine spatial autocorrelation (Hanselman et al., 2001). If 

 no prior data exist, it would not make sense to attempt ACS 

 as an initial sampling design. We have shown that a wide 

 range of criterion values can be used without considerable 

 differences in the results. Therefore, only enough prior data 

 are needed so that an adequate range of population density 

 can be estimated. If the criterion value chosen resulted in too 

 many or too few samples, the criterion could be adjusted, and 

 then the design stratified into two different areas. 



Most commercial fish species have survey data that can be 

 used to determine a fixed criterion. If possible, criterion val- 

 ues should be determined prior to the survey, so that maxi- 

 mum efficiency can be attained. We have shown that it may 

 be appropriate to choose a relatively high sampling criterion 

 such as the 80'^ percentile of past CPUE without sacrificing 

 estimation capabilities. This high sampling criterion has sev- 

 eral practical advantages. First, the design is attractive for 

 commercial boats to perform the adaptive phase at no-cost 

 because only large catches are sampled. The current design 

 does not use the fish sampled during the survey, which, in 

 the case of deepwater rockfish, would cause certain mortality. 

 Under an adaptive design, a commercial boat would take the 

 larger catches and could put them to use. Second, fewer over- 

 all networks would be sampled because the higher criterion 

 would evoke less adaptive sampling, which may mean less 

 overall sajnpling in the survey. Finally, precision would be 

 gained at a minimal cost and effort. Stopping rules would be 

 unnecessary, ensuring an unbiased estimate. However, clus- 

 ter sampling is most effective when the cluster samples are 

 as heterogeneous as possible. Therefore, caution is required 

 not to set the criterion too high, or the resulting clusters 

 will be either too homogeneous or contain only edge units, 

 leading to no improvement in the estimators. Similarly, if 

 there are large changes in density from year to year, a fixed 

 criterion may not be appropriate. In conclusion, adaptive 

 cluster sampling is appropriate for surveys of highly clus- 

 tered species with low temporal fluctuations, for which a 

 fixed criterion can be determined beforehand. 



Acknowledgments 



We thank the crew of the FV Unimak, in particular Cap- 

 tain Paul Ison and Production Manager Rob Elzig, for their 



3 Fujioka, J. 2001. Unpubl. manuscr. Using hydroacoustics 

 and double sampling to improve rockfish abundance estimation, 

 8 p. Auke Bay Laboratory, National Marine Fisheries Service, 

 NOAA, 11305 Glacier Hwy, Auke Bay, AK 99801. 



excellent cooperation in this study. We also acknowledge the 

 hard work of the scientists that participated in the cruise 

 and the NMFS personnel who prepared for the charter. 

 We greatly appreciate the helpful comments from three 

 anonymous reviewers that helped us refine the paper. 



This publication is the result of research sponsored by 

 Alaska Sea Grant with funds from the National Oceanic 

 and Atmospheric Administration, Office of Sea Grant, De- 

 partment of Commerce, under grant no. NA90AA-D- 

 SG066, project number R/31-04N, from the University 

 of Alaska with funds appropriated by the state. Further 

 support was provided by the Auke Bay Laboratory, Alaska 

 Fisheries Science Center, National Marine Fisheries Ser- 

 vice and by a Population Dynamics Fellowship to Hansel- 

 man through a cooperative program funded by Sea Grant 

 and NMFS. 



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