Implementing geostatistical analysis to study spatio-temporal distribution patterns of swimming crabs (<i>Portunus trituberculatus</i>)

Wenbin Zhu; Kaner Lu; Zhanhui Lu; Qian Dai; Zhenghua Li; Yongdong Zhou; Siqi Huang; Haichen Zhu; Guocheng Cui

doi:10.1007/s13131-021-1788-0

Volume 40 Issue 6

Jun. 2021

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Wenbin Zhu, Kaner Lu, Zhanhui Lu, Qian Dai, Zhenghua Li, Yongdong Zhou, Siqi Huang, Haichen Zhu, Guocheng Cui. Implementing geostatistical analysis to study spatio-temporal distribution patterns of swimming crabs (Portunus trituberculatus)[J]. Acta Oceanologica Sinica, 2021, 40(6): 67-74. doi: 10.1007/s13131-021-1788-0

Citation:

Wenbin Zhu, Kaner Lu, Zhanhui Lu, Qian Dai, Zhenghua Li, Yongdong Zhou, Siqi Huang, Haichen Zhu, Guocheng Cui. Implementing geostatistical analysis to study spatio-temporal distribution patterns of swimming crabs (Portunus trituberculatus)[J]. Acta Oceanologica Sinica, 2021, 40(6): 67-74. doi: 10.1007/s13131-021-1788-0

Citation:

Wenbin Zhu, Kaner Lu, Zhanhui Lu, Qian Dai, Zhenghua Li, Yongdong Zhou, Siqi Huang, Haichen Zhu, Guocheng Cui. Implementing geostatistical analysis to study spatio-temporal distribution patterns of swimming crabs (Portunus trituberculatus)[J]. Acta Oceanologica Sinica, 2021, 40(6): 67-74. doi: 10.1007/s13131-021-1788-0

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Implementing geostatistical analysis to study spatio-temporal distribution patterns of swimming crabs (Portunus trituberculatus)

doi: 10.1007/s13131-021-1788-0

Wenbin Zhu^{1, 2, 3},
Kaner Lu^{1, 2, 3, 5
,
,},
Zhanhui Lu^{1, 2, 3},
Qian Dai^{1, 2, 3},
Zhenghua Li^{1, 2, 3},
Yongdong Zhou^{1, 2, 3},
Siqi Huang^{1, 4},
Haichen Zhu^{1, 4},
Guocheng Cui^{1, 3}

1.
Zhejiang Marine Fisheries Research Institute, Zhoushan 316021, China
2.
Scientific Observing and Experimental Station of Fishery Resources, Key Fishing Grounds of Ministry of Agriculture, Zhoushan 316021, China
3.
Key Laboratory of Sustainable Utilization of Marine Fishery Resources of Zhejiang Province, Zhoushan 316021, China
4.
Zhejiang Ocean University, Zhoushan 316021, China
5.
Geological Environment Monitoring Center of Zhejiang Province, Hangzhou 310007, China

More Information

Corresponding author: E-mail: vinson873@126.com
Received Date: 2020-05-15
Accepted Date: 2020-06-29

Available Online: 2021-07-07

Publish Date: 2021-06-01

Abstract

Abstract

This study attempted to compare the performance of local polynomial interpolation, inverse distance weighted interpolation, and ordinary kriging in studying distribution patterns of swimming crabs. Cross-validation was used to select the optimum method to get distribution results, and kriging was used for making spatial variability analysis. Data were collected from 87 sampling stations in November of 2015 (autumn) and February (winter), May (spring) and August (summer) of 2016. Results indicate that swimming crabs widely distributed in autumn and summer: in the summer, they were more spatially independent, and resources in each sampling station varied a lot; in the winter and spring, the abundance of crabs was much lower, but the individual crab size was bigger, and they showed the patchy and more concentrative distribution pattern, which means they were more spatially dependent. Distribution patterns were in accordance with ecological migration features of swimming crabs, which were affected by the changing marine environment. This study could infer that it is applicable to study crab fishery or even other crustacean species using geostatistical analysis. It not only helps practitioners have a better understanding of how swimming crabs migrate from season to season, but also assists researchers in carrying out a more comprehensive assessment of the fishery. Therefore, it may facilitate advancing the implementation in the pilot quota management program of swimming crabs in northern Zhejiang fishing grounds.
- swimming crabs (Portunus trituberculatus),
- geostatistical analysis,
- ordinary kriging,
- spatio-temporal distributions,
- Zhejiang coastal waters of China

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References(44)

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