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XU Luoliang, CHEN Xinjun, GUAN Wenjiang, TIAN Siquan, CHEN Yong. The impact of spatial autocorrelation on CPUE standardization between two different fisheries[J]. Journal of Oceanology and Limnology, 2018, 36(3): 973-980 |
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The impact of spatial autocorrelation on CPUE standardization between two different fisheries |
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| XU Luoliang1,2,3, CHEN Xinjun1,2,3, GUAN Wenjiang1,2,3, TIAN Siquan1,2,3, CHEN Yong4,1 |
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1 College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;
2 Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources(Shanghai Ocean University), Ministry of Education, Shanghai 201306, China;
3 National Engineering Research Center for oceanic Fisheries, Shanghai Ocean University, Shanghai 201306, China;
4 School of Marine Sciences, University of Maine, Orono, ME 04469, USA |
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| Abstract: |
| Catch per unit of effort (CPUE) data can display spatial autocorrelation. However, most of the CPUE standardization methods developed so far assumes independency of observations for the dependent variable, which is often invalid. In this study, we collected data of two fisheries, squid jigging fishery and mackerel trawl fishery. We used standard generalized linear model (GLM) and spatial GLMs to compare the impact of spatial autocorrelation on CPUE standardization for different fisheries. We found that spatialGLMs perform better than standard-GLM for both fisheries. The overestimation of precision of CPUE estimates was observed in both fisheries. Moran's I was used to quantify the level of autocorrelation for the two fisheries. The results show that autocorrelation in mackerel trawl fishery was much stronger than that in squid jigging fishery. According to the results of this paper, we highly recommend to account for spatial autocorrelation when using GLM to standardize CPUE data derived from commercial fisheries. |
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| Key words:
spatial autocorrelation|catch per unit effort (CPUE) standardization|squid jigging fishery|mackerel trawl fishery
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| Received: 2016-11-12 Revised: |
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