Volume 40 Issue 8
Aug.  2021
Turn off MathJax
Article Contents
Li Gao, Yingbin Wang. Influences of environmental factors on the spawning stock-recruitment relationship of Portunus trituberculatus in the northern East China Sea[J]. Acta Oceanologica Sinica, 2021, 40(8): 145-159. doi: 10.1007/s13131-021-1801-7
Citation: Li Gao, Yingbin Wang. Influences of environmental factors on the spawning stock-recruitment relationship of Portunus trituberculatus in the northern East China Sea[J]. Acta Oceanologica Sinica, 2021, 40(8): 145-159. doi: 10.1007/s13131-021-1801-7

Influences of environmental factors on the spawning stock-recruitment relationship of Portunus trituberculatus in the northern East China Sea

doi: 10.1007/s13131-021-1801-7
Funds:  The National Key Research and Development Program of China under contract Nos 2017YFA0604902 and 2019YFD0901304; the Public Welfare Technology Application Research Project of Zhejiang under contract No. LGN21C190009.
More Information
  • Corresponding author: E-mail: yingbinwang@126.com
  • Received Date: 2020-04-23
  • Accepted Date: 2020-12-09
  • Available Online: 2021-07-07
  • Publish Date: 2021-08-31
  • Based on the Ricker-type models, the spawning stock-recruitment (S-R) relationship of Portunus trituberculatus was analysed under the impacts of environmental factors (including red tide area (AORT), sea level height (SLH), sea surface salinity (SSS) and typhoon landing times (TYP)) in the northern East China Sea in 2001 and 2014. Besides the traditional Ricker model, two other Ricker-type S-R models were built: Ricker model with ln-linear environmental impact (Ricker-type 2) and Ricker model with ln-quadratic polynomial environmental impact (Ricker-type 3). Results showed that AORT, SLH, SSS and TYP had great influences on the recruitment of P. trituberculatus. When SSS reached 29 and 31, recruitment decreased from 20.7×103 million to 8.3×103 million individuals. In this case, recruitment declined, whereas AORT and TYP increased. Analysis of the S-R model showed that the Akaike information criterion (AIC) value of the traditional Ricker model was 14.619, which remarkably decreased after addition of the environmental factors. Different numbers of environmental factors were added to the Ricker model, and the best result was obtained when four factors were added to the model together. Moreover, Ricker-type 2 model, with the AIC value of −5.307, was better than Ricker-type 3 model (add above four environmental factors at the same time). The findings indicated that the mechanisms by which various environmental factors affect the S-R relationship are different.
  • loading
  • [1]
    Anderson C I H, Rodhouse P G. 2001. Life cycles, oceanography and variability: ommastrephid squid in variable oceanographic environments. Fisheries Research, 54(1): 133–143. doi: 10.1016/s0165-7836(01)00378-2
    [2]
    Ariyama H, Secor D H. 2010. Effect of environmental factors, especially hypoxia and typhoons, on recruitment of the gazami crab Portunus trituberculatus in Osaka Bay, Japan. Fisheries Science, 76(2): 315–324. doi: 10.1007/s12562-009-0198-6
    [3]
    Arzul G, Gentien P, Crassous M P. 1994. A haemolytic test to assay toxins excreted by the marine dinoflagellate Gyrodinium cf. Aureolum. Water Research, 28(4): 961–965. doi: 10.1016/0043-1354(94)90105-8
    [4]
    Baylon J, Suzuki H. 2007. Effects of changes in salinity and temperature on survival and development of larvae and juveniles of the crucifix crab Charybdis feriatus (Crustacea: Decapoda: Portunidae). Aquaculture, 269(1–4): 390–401. doi: 10.1016/j.aquaculture.2007.03.024
    [5]
    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
    [6]
    Cao Jie, Feng Bo, Chen Xinjun. 2010. Optimizing stock-recruitment Ricker model for yellowfin tuna (Thunnus albacares) incorporated with average vertical sea temperature in the Indian Ocean. Transactions of Oceanology and Limnology, (1): 153–160
    [7]
    Chen D G. 2001. Detecting environmental regimes in fish stock-recruitment relationships by fuzzy logic. Canadian Journal of Fisheries and Aquatic Sciences, 58(11): 2139–2148. doi: 10.1139/f01-155
    [8]
    Chen Xiayue, Ren Yongkuan, Li Lianjun, et al. 2018. Effect of typhoon on the antioxidant system and Na+, K+-ATPase activity in Portunus trituberculatus. Journal of Marine Sciences, 36(3): 101–106
    [9]
    Costa M J, Costa J, de Almeida P R, et al. 1994. Do eel grass beds and salt marsh borders act as preferential nurseries and spawning grounds for fish? An example of the Mira estuary in Portugal. Ecological Engineering, 3(2): 187–195. doi: 10.1016/0925-8574(94)90045-0
    [10]
    Feng Bo, Chen Xinjun, Nishida T. 2010. Modeling on stock-recruitment relationship for Yellowfin Tuna (Thunnus albacares) in the Indian Ocean influenced by water temperature. Journal of Guangdong Ocean University, 30(3): 62–66
    [11]
    Flaherty K E, Landsberg J H. 2011. Effects of a persistent red tide (Karenia brevis) bloom on community structure and species-specific relative abundance of nekton in a Gulf of Mexico estuary. Estuaries and Coasts, 34(2): 417–439. doi: 10.1007/s12237-010-9350-x
    [12]
    Fu Dongyang, Luan Hong, Pan Delu, et al. 2016. Impact of two typhoons on the marine environment in the Yellow Sea and East China Sea. Chinese Journal of Oceanology and Limnology, 34(4): 871–884. doi: 10.1007/s00343-016-5049-6
    [13]
    Fu Xiumei, Zhang Mengqi, Liu Yang, et al. 2018. Protective exploitation of marine bioresources in China. Ocean & Coastal Management, 163: 192–204. doi: 10.1016/j.ocecoaman.2018.06.018
    [14]
    Fulford R S, Peterson M S, Wu W, et al. 2014. An ecological model of the habitat mosaic in estuarine nursery areas: Part II—Projecting effects of sea level rise on fish production. Ecological Modelling, 273: 96–108. doi: 10.1016/j.ecolmodel.2013.10.032
    [15]
    Galindo-Cortes G, De Anda-Montañez J A, Arreguín-Sánchez F, et al. 2010. How do environmental factors affect the stock–recruitment relationship? The case of the Pacific sardine (Sardinops sagax) of the northeastern Pacific Ocean. Fisheries Research, 102(1–2): 173–183. doi: 10.1016/j.fishres.2009.11.010
    [16]
    Giménez L. 2003. Potential effects of physiological plastic responses to salinity on population networks of the estuarine crab Chasmagnathus granulata . Helgoland Marine Research, 56(4): 265–273. doi: 10.1007/s10152-002-0127-x
    [17]
    Guan Weibing, Xuan Fujun. 2019. A research paradigm of climate impacting reproductive dynamics of fishery resources: A case study of Portunus trituberculatus population in the East China Sea. Modern Fisheries Information, 34(4): 279–285. doi: 10.13233/j.cnki.fishis.2019.04.007
    [18]
    Hall C J, Burns C W. 2003. Responses of crustacean zooplankton to seasonal and tidal salinity changes in the coastal Lake Waihola, New Zealand. New Zealand Journal of Marine and Freshwater Research, 37(1): 31–43. doi: 10.1080/00288330.2003.9517144
    [19]
    Harford W J, Grüss A, Schirripa M J, et al. 2018. Handle with care: establishing catch limits for fish stocks experiencing episodic natural mortality events. Fisheries Magazine, 43(10): 463–471. doi: 10.1002/fsh.10131
    [20]
    Hilborn R, Walters C J. 1992. Quantitative fisheries stock assessment: choice, dynamics and uncertainty. London, UK: Chapman & Hall
    [21]
    Ho C H, Yagi N, Tian Yongjun. 2020. An impact and adaptation assessment of changing coastal fishing grounds and fishery industry under global change. Mitigation and Adaptation Strategies for Global Change, 25(6): 1073–1102. doi: 10.1007/s11027-020-09922-5
    [22]
    Hobbs N T, Hilborn R. 2006. Alternatives to statistical hypothesis testing in ecology: a guide to self teaching. Ecological Applications, 16(1): 5–19. doi: 10.1890/04-0645
    [23]
    Jiao Min, Chen Xinjun, Gao Guoping. 2015. Research progress on the impact of climatic change on arctic fishery resources. Chinese Journal of Polar Research, 27(4): 454–462. doi: 10.13679/j.jdyj.2015.4.454
    [24]
    Johnson J B, Omland K S. 2004. Model selection in ecology and evolution. Trends in Ecology & Evolution, 19(2): 101–108. doi: 10.1016/j.tree.2003.10.013
    [25]
    Keyl F, Wolff M. 2008. Environmental variability and fisheries: what can models do?. Reviews in Fish Biology and Fisheries, 18(3): 273–299. doi: 10.1007/s11160-007-9075-5
    [26]
    Kim C, Lee Y, Park B U. 2001. Cook’s distance in local polynomial regression. Statistics & Probability Letters, 54(1): 33–40. doi: 10.1016/s0167-7152(01)00031-1
    [27]
    Kirkpatrick B, Fleming L E, Squicciarini D, et al. 2004. Literature review of Florida red tide: implications for human health effects. Harmful Algae, 3(2): 99–115. doi: 10.1016/j.hal.2003.08.005
    [28]
    Lin Qinqin, Chen Xinjun, Dai Libin. 2018. Comparative analysis of stock-recruitment model for Scomber japonicus in the Pacific based on environment factors. Marine Fisheries, 40(3): 279–286. doi: 10.13233/j.cnki.mar.fish.2018.03.003
    [29]
    Liu Shuang, Sun Jinsheng, Hurtado L A. 2013. Genetic differentiation of Portunus trituberculatus, the world’s largest crab fishery, among its three main fishing areas. Fisheries Research, 148: 38–46. doi: 10.1016/j.fishres.2013.08.003
    [30]
    Lou Xiulin, Huang Weigen, Mao Xianmou, et al. 2006. Satellite observation of a red tide in the East China Sea during 2005. In: Proceedings Volume 6406, Remote Sensing of the Marine Environment. Goa, India: SPIE, 6406, doi: 10.1117/12.693856
    [31]
    Lu Yunliang, Wang Fang, Zhao Zhuoying, et al. 2012. Effects of salinity on growth, molt and energy utilization of juvenile swimming crab Portunus trituberculatus. Fisheries Science, 13(4): 237–245. doi: 10.3724/sp.j.1118.2012.00237
    [32]
    Myers R A. 2002. Recruitment: understanding density-dependence in fish populations. In: Hart P J B, Reynolds J D, eds. Handbook of Fish Biology and Fisheries: Fish Biology. Malden, Maine: Blackwell Science Ltd., 123–148, doi: 10.1002/9780470693803.ch6
    [33]
    Myers R A, Hutchings J A, Barrowman N J. 1996. Hypotheses for the decline of cod in the North Atlantic. Marine Ecology Progress Series, 138: 293–308. doi: 10.3354/meps138293
    [34]
    Neely T, Campbell L. 2006. A modified assay to determine hemolytic toxin variability among Karenia clones isolated from the Gulf of Mexico. Harmful Algae, 5(5): 592–598. doi: 10.1016/j.hal.2005.11.006
    [35]
    Palacios D M, Bograd S J, Foley D G, et al. 2006. Oceanographic characteristics of biological hot spots in the North Pacific: a remote sensing perspective. Deep-Sea Research Part II:Topical Studies in Oceanography, 53(3–4): 250–269. doi: 10.1016/j.dsr2.2006.03.004
    [36]
    Paulay G. 1990. Effects of late Cenozoic sea-level fluctuations on the bivalve faunas of tropical oceanic islands. Paleobiology, 16(4): 415–434. doi: 10.1017/s0094837300010162
    [37]
    Pécuchet L, Nielsen J R, Christensen A. 2015. Impacts of the local environment on recruitment: a comparative study of North Sea and Baltic Sea fish stocks. ICES Journal of Marine Science, 72(5): 1323–1335. doi: 10.1093/icesjms/fsu220
    [38]
    Rashed-Un-Nabi M, Ee L S, Hoque M A, et al. 2010. Effects of red tide on physico-chemical properties of water and phytoplankton assemblage in Sepanggar Bay, Sabah, Malaysia. International Journal of Ecology & Enviromental Sciences, 36(4): 245–251
    [39]
    Romano N, Zeng Chaoshu. 2006. The effects of salinity on the survival, growth and haemolymph osmolality of early juvenile blue swimmer crabs, Portunus pelagicus. Aquaculture, 260(1–4): 151–162. doi: 10.1016/j.aquaculture.2006.06.019
    [40]
    Sakuramoto K. 2005. Does the Ricker or Beverton and Holt type of stock-recruitment relationship truly exist?. Fisheries Science, 71(3): 577–592. doi: 10.1111/j.1444-2906.2005.01002.x
    [41]
    Sakuramoto K. 2013. A recruitment forecasting model for the Pacific stock of the Japanese sardine (Sardinops melanostictus) that does not assume density-dependent effects . Agricultural Sciences, 4(6A): 1–8. doi: 10.4236/as.2013.46a001
    [42]
    Schaaf A. 1996. Sea level changes, continental shelf morphology, and global paleoecological constraints in the shallow benthic realm: a theoretical approach. Palaeogeography, Palaeoclimatology, Palaeoecology, 121(3–4): 259–271. doi: 10.1016/0031-0182(95)00085-2
    [43]
    Shentu Jikang, Xu Yongjian, Ding Zhangni. 2015. Effects of salinity on survival, feeding behavior and growth of the juvenile swimming crab, Portunus trituberculatus (Miers, 1876) . Chinese Journal of Oceanology and Limnology, 33(3): 679–684. doi: 10.1007/s00343-015-4218-3
    [44]
    Shih C L, Chen Y H, Hsu C C. 2014. Modeling the effect of environmental factors on the ricker stock-recruitment relationship for North Pacific albacore using generalized additive models. Terrestrial, Atmospheric and Oceanic Sciences Journal, 25(4): 581–590. doi: 10.3319/tao.2014.01.27.01(oc
    [45]
    Song Chao, Hou Junli, Zhao Feng, et al. 2017. Macrobenthos community structure and its relationship with environment factors in the offshore wind farm of the East China Sea Bridge in spring and autumn. Marine Fisheries, 39(1): 21–29. doi: 10.3969/j.issn.1004-2490.2017.01.003
    [46]
    Song Haitang, Yu Cungen, Xue Lijian. 2012. The East China Sea Economic Crustacean Fisheries Biology (in Chinese). Beijing: China Ocean Press
    [47]
    Sun Jie, Wang Yingbin, Wang Xiaogang. 2018. Effects of three major marine disasters on recruitment of swimming crab portunus trituberculatus in sea area of northern Zhejiang province. Fisheries Science, 37(6): 728–734. doi: 10.16378/j.cnki.1003-1111.2018.06.002
    [48]
    Teal J M. 1958. Distribution of fiddler crabs in Georgia salt marshes. Ecology, 39(2): 185–193. doi: 10.2307/1931862
    [49]
    Wang Zhaohui, Chen Jufang, Xu Ning, et al. 2001. Relationship between seasonal variations in Gymnodinium spp. population and environmental factors in Daya Bay, the South China Sea. Acta Ecologica Sinica, 21(11): 1825–1832
    [50]
    Wang Yanjun, Liu Qun, Ren Yiping. 2005. Comparision of AIC and BIC in the selection of stock-recruitment relationships. Periodical of Ocean University of China, 35(3): 397–403. doi: 10.16441/j.cnki.hdxb.2005.03.009
    [51]
    Wang Xuming, Wang Weiqi, Tong Chuan. 2016. A review on impact of typhoons and hurricanes on coastal wetland ecosystems. Acta Ecologica Sinica, 36(1): 23–29. doi: 10.1016/j.chnaes.2015.12.006
    [52]
    Wang Yingbin, Wang Xiaogang, Ye Ting, et al. 2017a. Spawner-recruit analysis of portunus (Portunus) Trituberculatus (Miers, 1876) in the case of stock enhancement implementation: a case study in Zhejiang Sea Area, China. Turkish Journal of Fisheries and Aquatic Sciences, 17(2): 293–299. doi: 10.4194/1303-2712-v17_2_08
    [53]
    Wang Yingbin, Ye Ting, Wang Xiaogang, et al. 2017b. Impact of main factors on the catch of Portunus trituberculatus in the northern East China Sea. Pakistan Journal of Zoology, 49(1): 13–17. doi: 10.17582/journal.pjz/2017.49.1.13.17
    [54]
    Whitehead J C, Poulter B, Dumas C F, et al. 2009. Measuring the economic effects of sea level rise on shore fishing. Mitigation and Adaptation Strategies for Global Change, 14(8): 777. doi: 10.1007/s11027-009-9198-1
    [55]
    Yan Wenchao. 2019. Study on the relationship between the catch fluctuation of Portunus trituberculatus and the human disturbance and environment factors in Zhejiang fishery (in Chinese) [dissertation]. Zhoushan: Zhejiang Ocean University
    [56]
    Ye Haijun, Tang Danlig, Pan Gang. 2014. The contribution of typhoon Megi on phytoplankton and fishery productivity in the South China Sea. Ecological Science, 33(4): 657–663. doi: 10.14108/j.cnki.1008-8873.2014.04.005
    [57]
    Yu Jie, Chen Guobao, Chen Zuozhi, et al. 2015. Theimpacts of typhoon "Kai-tak" on fishery in west Guangdong fishing ground. Marine Environmental Science, 34(3): 411–419. doi: 10.13634/j.cnki.mes.2015.03.016
    [58]
    Yu Cungen, Song Haitang, Yao Guangzhan, et al. 2003. Study on rational utilization of crab resources in the inshore waters of Zhejiang. Marine Fisheries, 25(3): 136–141. doi: 10.3969/j.issn.1004-2490.2003.03.008
    [59]
    Yuan Wei, Jin Xianshi, Shan Xiujuan. 2016. Population biology and relationship with environmental factors of swimming crab in the Changjiang River Estuary and adjacent waters. Fisheries Science, 35(2): 105–110. doi: 10.16378/j.cnki.1003-1111.2016.02.002
    [60]
    Zhan Bingyi. 1995. Fish Stock Assessment (in Chinese). Beijing: China Agriculture Press
    [61]
    Zhang Debo, Li Aiguo. 1992. The study of salinity and suitable salinity of the survival lower limit of Portunus trituberculatus zoea larva . Marine Science, 16(1): 8–10
    [62]
    Zhao X, Hamre J, Li F, et al. 2003. Recruitment, sustainable yield and possible ecological consequences of the sharp decline of the anchovy (Engraulis japonicus) stock in the Yellow Sea in the 1990s. Fisheries Oceanography, 12(4–5): 495–501. doi: 10.1046/j.1365-2419.2003.00262.x
    [63]
    Zheng Jie, Kruse G H. 2003. Stock-recruitment relationships for three major Alaskan crab stocks. Fisheries Research, 65(1–3): 103–121. doi: 10.1016/j.fishres.2003.09.010
    [64]
    Zheng Fang, Liu Qun, Wang Yanjun. 2008. Study of impacts of environmental factors on stock and recruitment relationship of the anchovy stock in the Yellow Sea. South China Fisheries Science, 4(2): 15–20. doi: 10.3969/j.issn.2095-0780.2008.02.003
    [65]
    Zhu Dadi, Lu Douding, Wang Yunfeng, et al. 2009. The low temperature characteristics in Zhejiang coastal region in the early spring of 2005 and its influence on harmful algae bloom occurrence of Prorocentrum donghaiense. Haiyang Xuebao, 31(6): 31–39. doi: 10.3321/j.issn:0253-4193.2009.06.004
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(13)  / Tables(5)

    Article Metrics

    Article views (94) PDF downloads(17) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return