Comparative analysis of CPUE standardization of Chinese Pacific saury (<i>Cololabis saira</i>) fishery based on GLM and GAM

Hua Chuanxiang; Zhu Qingcheng; Shi Yongchuang; Liu Yu

doi:10.1007/s13131-019-1486-3

Article Contents

Article Navigation > Acta Oceanologica Sinica > 2019 > 38(10): 100-110

Hua Chuanxiang, Zhu Qingcheng, Shi Yongchuang, Liu Yu. Comparative analysis of CPUE standardization of Chinese Pacific saury (Cololabis saira) fishery based on GLM and GAM[J]. Acta Oceanologica Sinica, 2019, 38(10): 100-110. doi: 10.1007/s13131-019-1486-3

Citation:

Hua Chuanxiang, Zhu Qingcheng, Shi Yongchuang, Liu Yu. Comparative analysis of CPUE standardization of Chinese Pacific saury (Cololabis saira) fishery based on GLM and GAM[J]. Acta Oceanologica Sinica, 2019, 38(10): 100-110. doi: 10.1007/s13131-019-1486-3

Citation:

PDF( 1102 KB)

Comparative analysis of CPUE standardization of Chinese Pacific saury (Cololabis saira) fishery based on GLM and GAM

doi: 10.1007/s13131-019-1486-3

1.
College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;National Engineering Research Center for Pelagic Fishery, Shanghai 201306, China
2.
College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China

Received Date: 2018-11-02

Abstract

Abstract

Pacific saury is an important high-seas fishery resource in the Northwest Pacific Ocean for the Chinese Mainland. Reliable and accurate catch per unit effort (CPUE) plays a significant rule in Pacific saury stock assessment. Many statistical models have been used in the previous CPUE standardization research. Here, we compare the performance of Generalized Linear Models (GLMs) and Generalized Additive Models (GAMs) using CPUE data collected from Chinese saury fishery in the Northwest Pacific Ocean from 2003 to 2017 (excluding data from Chinese Taipei), and evaluate the influence of spatial, temporal, environmental variables and vessel length on CPUE. Optimal GLM/GAM models were selected using the Bayesian information criterion (BIC). Explained deviance and 5-fold bootstrap cross-validation results were used to compare the performance of the two model types. Fitted GLMs accounted for 21.57% of the total model-explained deviance, while GAMs accounted for 38.95%. Predictive performance metrics and 5-fold cross-validation results showed that the best GAM performed better than the best GLM. Therefore, we recommend GAM as the preferred model for standardizing CPUE of Pacific saury in the Northwest Pacific Ocean.
- Cololabis saira|CPUE standardization|generalized linear model|generalized additive model

FullText(HTML)

References(49)

References

Arlot S, Celisse A. 2010. A survey of cross-validation procedures for model selection. Statistics Surveys, 4: 40–79, doi: 10.1214/09-SS054

Campbell R A. 2004. CPUE standardisation and the construction of indices of stock abundance in a spatially varying fishery using general linear models. Fisheries Research, 70(2–3): 209–227, doi: 10.1016/j.fishres.2004.08.026

Chen Xinjun, Liu Bilin, Chen Yong. 2008. A review of the development of Chinese distant-water squid jigging fisheries. Fisheries Research, 89(3): 211–221, doi: 10.1016/j.fishres.2007.10.012

Denis V, Lejeune J, Robin J P. 2002. Spatio-temporal analysis of commercial trawler data using general additive models: patterns of Loliginid squid abundance in the north-east Atlantic. ICES Journal of Marine Science, 59(3): 633–648, doi: 10.1006/jmsc.2001.1178

Erisman B E, Allen L G, Claisse J T, et al. 2011. The illusion of plenty: hyperstability masks collapses in two recreational fisheries that target fish spawning aggregations. Canadian Journal of Fisheries and Aquatic Sciences, 68(10): 1705–1716, doi: 10.1139/f2011-090

Frescino T S, Edwards T C Jr, Moisen G G. 2001. Modeling spatially explicit forest structural attributes using generalized additive models. Journal of Vegetation Science, 12(1): 15–26, doi: 10.1111/j.1654-1103.2001.tb02613.x

Harley S J, Myers R A, Dunn A. 2001. Is catch-per-unit-effort proportional to abundance?. Canadian Journal of Fisheries and Aquatic Sciences, 58(9): 1760–1772, doi: 10.1139/f01-112

He Min, Song Wenling, Chen Xingfang. 1999. Typhoon activity in the Northwest Pacific in relation to El Niño/La nina events. Journal of Tropical Meteorology (in Chinese), 15(1): 17–25

Howell E A, Kobayashi D R. 2006. El Niño effects in the Palmyra Atoll region: oceanographic changes and bigeye tuna (Thunnus obesus) catch rate variability. Fisheries Oceanography, 15(2): 477–489

Hua Chuanxiang, Zhu Qingcheng, Xu Wei. 2010. Fishing ground distribution of cololabis saira in the Northwestern Pacific. Shandong Fisheries (in Chinese), 27(10): 10–13

Huang Hongliang, Zhang Xun, Xu Baosheng, et al. 2005. Preliminary analysis on the fishing grounds of Cololabis saira in the North Pacific Ocean. Marine Fisheries, 27(3): 206–212

Kohavi R. 2001. A study of cross-validation and bootstrap for accuracy estimation and model selection. International Joint Conference on Artificial Intelligence. Stanford, CA:Morgan Kaufmann Publishers Inc

Lin Longshan. 2003. Fishery survey of Stick-held Net for Cololabis saira in Taiwan. Marine Fisheries (in Chinese), (4): 200–203

Martínez-Rincón R O, Ortega-García S, Vaca-Rodríguez J G. 2012. Comparative performance of generalized additive models and boosted regression trees for statistical modeling of incidental catch of wahoo (Acanthocybium solandri) in the Mexican tuna purse-seine fishery. Ecological Modelling, 233: 20–25, doi: 10.1016/j.ecolmodel.2012.03.006

Maunder M, Punt A E. 2004. Standardizing catch and effort data: a review of recent approaches. Fisheries Research, 70(2–3): 141–159, doi: 10.1016/j.fishres.2004.08.002

Maunder M N, Start P J. 2003. Fitting fisheries models to standardised CPUE abundance indices. Fisheries Research, 63(2): 43–50

Menard SW. 1995. Applied Logistic Regression Analysis. Thousand Oaks, CA: SAGE

Nishida T, Chen Dinggeng. 2004. Incorporating spatial autocorrelation into the general linear model with an application to the yellowfin tuna (Thunnus albacares) longline CPUE data. Fisheries Research, 70(2–3): 265–274, doi: 10.1016/j.fishres.2004.08.008

Ortiz M, Arocha F. 2004. Alternative error distribution models for standardization of catch rates of non-target species from a pelagic longline fishery: billfish species in the Venezuelan tuna longline fishery. Fisheries Research, 70(2–3): 275–297, doi: 10.1016/j.fishres.2004.08.028

Quinn G P, Keough M J. 2002. Experimental Design and Data Analysis for Biologists. Cambridge: Cambridge University Press

Rodríguez-Marín E, Arrizabalaga H, Ortiz M, et al. 2003. Standardization of bluefin tuna, (Thunnus thynnus) catch per unit effort in the baitboat fishery of the Bay of Biscay (Eastern Atlantic). ICES Journal of Marine Science, 60(1): 1216–1231

Shen Jianhua, Han Shixin, Fan Wei, et al. 2004. Saury Resource and Fishing Grounds in the Northwest Pacific. Marine Fisheries (in Chinese), 26(1): 61–65

Shono H. 2005. Is model selection using Akaike’s information criterion appropriate for catch per unit effort standardization in large samples?. Fisheries Science, 71(5): 978–986, doi: 10.1111/j.1444-2906.2005.01054.x

Stephens A, Maccall A. 2004. A multispecies approach to subsetting logbook data for purposes of estimating CPUE. Fisheries Research, 70(2–3): 299–310, doi: 10.1016/j.fishres.2004.08.009

Sun Manchang, Ye Xuchang, Zhang Jian, et al. 2003. Probe into Pacific saury fisheries in the northwest Pacific Ocean. Marine Fisheries (in Chinese), 25(3): 112–115

Takasuka A, Kuroda H, Takeshi O, et al. 2014. Occurrence and density of Pacific saury Cololabis saira larvae and juveniles in relation to environmental factors during the winter spawning season in the Kuroshio Current system. Fisheries Oceanography, 23(4): 304–321, doi: 10.1111/fog.12065

Tian Y J, Akamine T, Suda M. 2003. Variations in the abundance of Pacific saury (Cololabis saira) from the Northwestern Pacific in relation to oceanic-climate changes. Fisheries Research, 60(2–3): 439–454, doi: 10.1016/S0165-7836(02)00143-1

Tian Y J, Ueno Y, Suda M, et al. 2004. Decadal variability in the abundance of Pacific saury and its response to climatic/oceanic regime shifts in the northwestern subtropical Pacific during the last half century. Journal of Marine Systems, 52: 235–257, doi: 10.1016/j.jmarsys.2004.04.004

Tien B D, Lofman O, Revhaug I, et al. 2011. Landslide susceptibility analysis in the Hoa Binh province of Vietnam using statistical index and logistic regression. Natural Hazards, 59(3): 1413–1444, doi: 10.1007/s11069-011-9844-2

Tseng C T, Su N J, Sun C L, et al. 2013. Spatial and temporal variability of the Pacific saury (Cololabis saira) distribution in the northwestern Pacific Ocean. ICES Journal of Marine Science, 70(5): 991–999, doi: 10.1093/icesjms/fss205

Venables W N, Dichmont C M. 2004. GLMs, GAMs and GLMMs: an overview of theory for applications in fisheries research. Fisheries Research, 70(2–3): 319–337, doi: 10.1016/j.fishres.2004.08.011

Walsh W A, Kleiber P. 2001. Generalized additive model and regression tree analyses of blue shark (Prionace glauca) catch rates by the Hawaii-based commercial longline fishery. Fisheries Research, 53(2): 115–131, doi: 10.1016/S0165-7836(00)00306-4

Wang Zhizu, Zuo Juncheng, Chen Meixiang, et al. 2012. Relationship between El Niño and sea surface temperature variation in coastal region of Yellow Sea and East China Sea. Journal of Hohai University (Natural Sciences) (in Chinese), 40(4): 461–468

Ward H G M, Askey P J, Post J R. 2013. A mechanistic understanding of hyperstability in catch per unit effort and density-dependent catchability in a multistock recreational fishery. Canadian Journal of Fisheries and Aquatic Sciences, 70(10): 1542–1550, doi: 10.1139/cjfas-2013-0264

Watanabe K, Tanaka E, Yamada S, et al. 2006. Spatial and temporal migration modeling for stock of Pacific saury Cololabis saira (Brevoort), incorporating effect of sea surface temperature. Fisheries Science, 72(6): 1153–1165, doi: 10.1111/j.1444-2906.2006.01272.x

Wood S N. 2006. Generalized Additive Models: An Introduction with R. London: Chapman and Hall/CRC, 410

Wu Yue, Huang Hongliang, Liu Jian, et al. 2015. Spatiotemporal distribution pattern of saury fishing grounds and catch yield per unit effort in the Northern Pacific high sea in 2014. Fishery Modernization (in Chinese), 42(3): 61–64

Xia Hui. 2008. The illumination distribution model of the pacific saury (Cololabis saira) stick-held dip net fishing (in Chinese) [dissertation]. Shanghai: Shanghai Ocean University, 1-54

Xu Wei, Zhu Qingcheng, Zhang xiancun, et al. 2005. Bouke net fishing technology of Pacific saury in the Northweatern Pacific. Shangdong Fisheries (in Chinese), 22(10): 43–46

Yan Lei. 2012. The Relationship between the distribution of saury fishing ground and its environmental factors (in Chinese) [dissertation]. Shanghai: Shanghai Ocean University, 1–51

Yan Lei, Zhu Qingcheng, Zhang Yang, et al. 2012. Fishing ground distribution of saury and its correlation with SST in the Northern Pacific high sea in 2010. Journal of Shanghai Ocean University (in Chinese), 21(4): 609–615

Yang Xiulan, Wang Pengfei, Jiao Yulong, et al. 2005. Study on the culture technique in the middle stage and the growing character of Apostichopus japonicus. Shandong Fishery (in Chinese), 22(10): 43–46

Yu Hao, Jiao Yan, Carstensen L W. 2013. Performance comparison between spatial interpolation and GLM/GAM in estimating relative abundance indices through a simulation study. Fisheries Research, 147: 186–195, doi: 10.1016/j.fishres.2013.06.002

Yu Yuefeng, Zhang Xun, Huang Hongliang, et al. 2006. Study on attracting fish method of stick-held net for Cololabis saira. Journal of Zhejiang Ocean University (Natural Science) (in Chinese), 25(2): 154–156

Zhang Xiaomin, Zhu Qingcheng, Hua Chuanxiang. 2015. Fishing ground distribution of saury and its correlation with marine environment factors in the Northern Pacific high sea in 2013. Journal of Shanghai Ocean University (in Chinese), 24(5): 773–782

Zhang Yang, Zhu Qingcheng, Yan Lei, et al. 2013. Preliminary study on biological characteristics of Cololabis Saira in the Northwest Pacific ocean in Spring. Transactions of Oceanology and Limnology (in Chinese), (1): 53–60

Zhu Qingcheng, Hua Chuanxiang, Xu Wei, et al. 2006a. The fishing ground distribution of Cololabis saira and its relationship with water temperature factors in the Northwestern Pacific from July to September. Marine Fisheries (in Chinese), 28(3): 228–233

Zhu Guoping, Zhu Qingcheng, Chen Jintao, et al. 2006b. Preliminary study on relationship between Cololabis saira fishing ground and temperature factor in the Northern Pacific Ocean. Marine Sciences (in Chinese), 30(7): 91–96

Zou Xiaorong, Zhu Qingcheng. 2006. Preliminary analysis on the relationship between the distribution of fishing ground of pacific saury (Cololabis saira) and SST in northwest pacific. Journal of Zhanjiang Ocean University (in Chinese), 26(6): 26–30

Relative Articles

Supplements(0)

Cited By

Proportional views