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This study focused on the quantitative evaluation of the impact of the spatio-temporal scale used in data collection and grouping on the standardization of CPUE(catch per unit effort).We used the Chinese squid-jigging fishery in the northwestern Pacific Ocean as an example to evaluate 24 scenarios at different spatio-temporal scales,with a combination of four levels of temporal scale(weekly,biweekly,monthly,and bimonthly)and six levels of spatial scale(longitude×latitude:0.5°×0.5°,0.5°×1°,0.5°×2°,1°×0.5°,1°×1°,and 1°×2°).We applied generalized additive models and generalized linear models to analyze the24 scenarios for CPUE standardization,and then the differences in the standardized CPUE among these scenarios were quantified.This study shows that combinations of different spatial and temporal scales could have different impacts on the standardization of CPUE.However,at a fine temporal scale(weekly)different spatial scales yielded similar results for standardized CPUE.The choice of spatio-temporal scale used in data collection and analysis may create added uncertainty in fisheries stock assessment and management.To identify a cost-effective spatio-temporal scale for data collection,we recommend a similar study be undertaken to facilitate the design of effective monitoring programs.
This study focused on the quantitative evaluation of the impact of the spatio-temporal scale used in data collection and grouping on the standardization of CPUE (catch per unit effort). We used the Chinese squid-jigging fishery in the northwestern Pacific Ocean as an example to evaluate 24 scenarios at different spatio-temporal scales, with a combination of four levels of temporal scale (weekly, biweekly, monthly, and bimonthly) and six levels of spatial scale (longitude × latitude: 0.5 ° × 0.5 °, 0.5 ° × 1 °, 0.5 ° × 2 °, 1 ° × 0.5 °, 1 ° × 1 °, and 1 ° × 2 °). We applied generalized additive models and generalized linear models to analyze the 24 scenarios for CPUE standardization, and then the differences in the standardized CPUE among these scenarios were quantified. This study shows that combinations of different spatial and temporal scales could have different impacts on the standardization of CPUE.However, at a fine temporal scale (weekly) different spatial scales yielded similar similar for for CPU E. The choice of spatio-temporal scale used in data collection and analysis may create uncertainty in fisheries stock assessment and management. To identify a cost-effective spatio-temporal scale for data collection, we recommend a similar study be undertaken to facilitate the design of effective monitoring programs.