Effects of environmental factors on catch variation of main species of stow net fisheries in East China Sea

Abstract

Abstract: Stow net fishery is one of the important fishing methods in the East China Sea.This paper used the generalized additive models (GAMs) to quantitatively describe the relationships between stow net catch and environmental factors (sea surface temperature SST,water depth,fishing position and tide) in the East China Sea.The results indicated that each factor had its own nonlinear effect on the catch per unit effort (CPUE) of haitail (Trichiurus japonicus),small yellow croaker (Larimichthys polyactis) and butter fish (Pampus spp.),and SST and water depth were the key factors.The GAMs' fitting results showed that SST had the strongest effect on the catch per unit effort of haitail,and water depth had the second one.The effects of fishing location and tide were very small.Water depth was the most influential variable when adjusted for the effects on small yellow croaker.SST,fishing location and tide had similar effects.Meanwhile,water depth and SST were the key factors affecting the catch per unit effort of butter fish.They had similar intensity.

Key words: Stow net, Generalized additive model, Environmental factor, Catch per unit effort (CPUE)

CLC Number:

S931

ZHOU Sufang, FAN Wei, CUI Xuesen, CHENG Yanhong . Effects of environmental factors on catch variation of main species of stow net fisheries in East China Sea[J]. Chinese Journal of Applied Ecology, 2004, (9): 1637-1640.

References

[1] Antoine G, Niklaus E. 2000. Predictive habitat distribution models in ecology. Ecol Model, 135:147～ 186
[2] Antoine G, Thomas CJr, et al. 2002. Generalized linear and generalized additive models in studies of species distributions: Setting the scene. Ecol Model, 157:89～ 100
[3] Beare D, Reid D. 2002. Investigating spatio-temporal change in spawning activity by atlantic mackerel between 1977 and 1998 using generalized additive models. ICES J Mar Sci, 59: 711 ～ 724
[4] Cheng J-H(程家骅),Chen X-Z(陈雪忠),Lin L-S(林龙山),et al. 2000. Dynamics analysis of available resource structure for stow net fisheries in East China Sea Region.J Fish Sci China(中国水产科学),7(2):64～68(in Chinese)
[5] Davis J, Eder B, Nychka D, et al. 1998. Modeling the effects of meteorology ozone in houston using cluster analysis and generalized additive models.Atmos Environ, 32(14/15) :2505～2520
[6] Fang S-M(方水美),Yang S-Y(杨圣云),Zhang C-M(张澄茂),et al. 2002. Effects of submarine topography and water depth on distribution of pelagic fish community in Minnan-Taiwan bank fishing ground.Chin J Appl Ecol(应用生态学报),13(11):1463～1467(in Chinese)
[7] Georgi D. 1999.Relating fish recruitment to stock biomass and physical environment in the Black Sea using generalized additive models. Fish Res, 41:1～23
[8] Hastie TJ, Tibshirani RJ. 1990. Generalized Additive Models. New York: Chapman and Hall.
[9] Li X-D(李雪渡).1982.Studies on the correlation between the temperature of sea water and fishing grounds.Acta Oceanol Sin(海洋学报),4(1):103～112(in Chinese)
[10] Mueter FJ, Norcross BL. 2002. Spatial and temporal patterns in the demersal fish community on the shelf and upper slope regions of the Gulf of Alaska. Fish Bull, 100:559～581
[11] Ni H-E(倪海儿),Lu J-H(陆杰华).2003.Present utilization situation of main fishery resources in Zhoushan fishing ground. Chin J Appl Ecol(应用生态学报),14(4):569～572(in Chinese)
[12] Olivier M, Didier G, Francis M, et al. 2001. Hierarchical interpretation of nonlinear relationships linking yellowfin tuna( Thunnusalbacares) distribution to the environment in the Atlantic Ocean. Can J Fish Aquat Sci, 58: 458～ 469
[13] Piet G. 2002. Using external information and GAMs to improve catch-at-age indices for North Sea plaice and sole. ICESJ Mar Sci,59: 624 ～ 632
[14] Su F-Z(苏奋振),Zhou C-H(周成虎),Liu B-Y(刘宝银),et al.2002. A spatio-temporal pattern extracting model for fishing ground.Acta Oceanol Sin(海洋学报),24(5):46～56(in Chinese)
[15] Su F-Z(苏奋振),Zhou C-H(周成虎),Du Y-Y(杜云艳),et al.2003. Spatio-temperoal problems of geographic information system in marinc fishery.Chin J Appl Ecol(应用生态学报),14(9):1569～1572(in Chinese)
[16] Su F-Z(苏奋振),Zhou C-H(周成虎),Zhang T-Y(仉天宇),et al. 2003. Spatial heterogeneity of pelagic fishery resources in the East China Sca.Chin J Appl Ecol(应用生态学报),14(11):1971～ 1975 (in Chinese)
[17] Swartzman G, Huang C, Kaluzny S. 1992. Spatial analysis of Bering Sea groundfish survey data using generalized additive models. Can J Fish Aquat Sci, 49:1366～ 1378
[18] Swartzman G, Stuetzle W, Kulman K, et al. 1994. Relating the distribution of pollock schools in the Bering Sea to environmental factors. ICES J Mar Sci, 51:481～492
[19] Swartzman G, Silverman E, Williamson N. 1995. Relating trends in walleye pollock Theragra chalcogramma abundance in the Bering Sea to environmental factors. Can J Fish Aquat Sci, 52:369～380
[20] Walsh WA, Kleiber P. 2001. Generalized additive model and regression tree analyses of blue shark(Prionace glauca) catch rates by the Hawaii-based commercial longline fishery. Fish Res, 53:115～ 131
[21] Yang H(杨红),Zhang S-Y(章守宇),Dai X-J(戴小杰),et al.2001. Characteristics of water masses and its influence on mackerel scad fishery in East China Sea in the Summer. J Fish China (水产学报),25(3):209～214(in Chinese)
[22] Zheng X, Pierce GJ, Reid DG, et al. 2002. Does the North Atlantic current affect spatialdistribution of whiting? Testing environmental hypotheses using statistical and GIS techniques. ICES J Mar Sci,59: 239 ～ 253
[23] Zhou W-X(周婉霞),Bo Z-L(薄治礼).1998.Monitoring report on recent fishery resource dynamic of sail stow net in Zhejiang sea water.J Zhejiang Coll Fish(浙江水产学院学报),17(4):259～268(in Chinese)