T. Malinen et H. Peltonen, OPTIMAL SAMPLING AND TRADITIONAL VERSUS MODEL-BASED DATA-ANALYSIS IN ACOUSTIC FISH STOCK ASSESSMENT IN LAKE-VESIJARVI, Fisheries research, 26(3-4), 1996, pp. 295-308
Optimal sampling strategy and data analysis methods were studied for p
elagic fish stock assessment in eutrophic Lake Vesijarvi in southern F
inland based on 10 surveys conducted in 1993. The systematic sampling
scheme was applied with parallel transects. The precision of the fish
density estimates in unstratified and post-stratified sampling were co
mpared with each other and with the precision that could be obtained b
y an optimum effort allocation. Because the frequency distribution of
fish density in the primary sampling units is typically skewed, a mode
l-based estimation was also applied in which the distribution is appro
ximated with a known distribution. The best normalizing transformation
was found with Box's and Cox's test. These model-based estimates were
compared with the estimates derived from non-transformed data. Post-s
tratified sampling by depth areas produced more precise estimates than
unstratified sampling (reduction in the variances about 40%), reduced
the bias caused by spatial autocorrelation and eliminated the bias ca
used by unproportional sampling of depth areas. The most precise estim
ates (reduction in the variances compared with post-stratification abo
ut 50%) would be given by optimum allocation, which suggests that more
effort should be allocated to the deep areas. The optimal fraction of
sample size to deep areas increased in the course of the summer (abou
t 20% in June and over 50% in August). The model-based estimation prod
uced a slight gain in precision with the post-stratified data. But, su
rprisingly, with unstratified data and with optimum allocation more pr
ecise estimates were given by initial untransformed data. In conclusio
n, we do not recommend the model-based estimation (including logarithm
ic transformation) in lakes if a suitable survey time is restricted by
fish behaviour (diel migrations, schooling behaviour), because of dif
ficulties in obtaining adequate sample size to determine appropriate t
ransformation.