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RESEARCH ARTICLE
Contents Vol 60(12)

Impacts of spatial scales of fisheries and environmental data on catch per unit effort standardisation

Siquan Tian A B C , Yong Chen A C , Xinjun Chen A B D , Liuxiong Xu A B and Xiaojie Dai A B
+ Author Affiliations
- Author Affiliations

A Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, China, and Key Laboratory of Shanghai Education Commission for Oceanic Fisheries Resources Exploitation, Shanghai Ocean University, Shanghai 201306, China.

B College of Marine Sciences, Shanghai Ocean University, 999 Huchenghuan Avenue, Lingang New City, Shanghai 201306, China.

C School of Marine Sciences, University of Maine, Orono, ME 04469, USA.

D Corresponding author. Email: xjchen@shou.edu.cn

Marine and Freshwater Research 60(12) 1273-1284 https://doi.org/10.1071/MF09087
Submitted: 15 April 2009  Accepted: 13 May 2009   Published: 17 December 2009

Abstract

Spatial scale is an important factor that needs to be considered in data collection and analysis in ecological studies. Studies focusing on the quantitative evaluation of impacts of spatial scales are, however, limited in fisheries. Using the Chinese squid-jigging fishery in the north-western Pacific Ocean as an example, we evaluated impacts of spatial scale used in grouping fisheries and environmental data on the standardisation of fisheries catch per unit effort (CPUE). We developed 18 scenarios of different spatial scales with a combination of three latitudinal levels (0.5°, 1° and 2°) and six longitudinal levels (0.5°, 1°, 2°, 3°, 4° and 5°) to aggregate the data. We then applied generalised additive models to analyse the 18 scenarios of data for the CPUE standardisation, and quantified differences among the scenarios. This study shows that longitudinal and latitudinal spatial scale and size of the spatial area for data aggregation can greatly influence the standardisation of CPUE. We recommend that similar studies be undertaken whenever possible to evaluate the roles of spatial scales and to identify the optimal spatial scale for data aggregations in the standardisation of CPUE and fisheries stock assessment.

Additional keywords: CPUE standardisation, environmental variables, generalised additive models, north-western Pacific Ocean, Ommastrephes bartramii.


Acknowledgements

We thank the Chinese squid-jigging technology group for providing fisheries data and the IRI/LDEO Climate Data Library of Columbia University for providing the environmental data. We thank the three anonymous referees and Editor for their comments, which greatly improved the quality of the paper. Comments from Sam Truesdell on editorial changes are also greatly appreciated. This study is supported by the Program for New Century Excellent Talents in University (NCET-06–0437), Shanghai Leading Academic Discipline Project (Project # S30702) and Excellent Young Teacher Fund of Shanghai Education Commission.


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