Energy flow characteristics of the food web in the northern waters of Jiangsu Province based on LIM-MCMC model

Zhang Hu; Li Pengcheng; Hu Haisheng; Xue Ying; Yuan Jianmei; Ben Chengkai; Zhu Chaowen; Xiao Yueyue; Zu Kaiwei

doi:10.12284/hyxb2023120

Volume 45 Issue 9

Sep. 2023

Turn off MathJax

Article Contents

Article Navigation > Haiyang Xuebao > 2023 > 45(9): 105-118

Zhang Hu，Li Pengcheng，Hu Haisheng, et al. Energy flow characteristics of the food web in the northern waters of Jiangsu Province based on LIM-MCMC model[J]. Haiyang Xuebao，2023, 45(9)：105–118 doi: 10.12284/hyxb2023120

Citation:

PDF( 1183 KB)

Energy flow characteristics of the food web in the northern waters of Jiangsu Province based on LIM-MCMC model

doi: 10.12284/hyxb2023120

1.
Jiangsu Marine Fisheries Research Institute, Nantong 226007, China
2.
Fisheries College, Ocean University of China, Qingdao 266003, China

Received Date: 2023-03-17
Rev Recd Date: 2023-04-23

Available Online: 2023-08-24

Publish Date: 2023-09-30

Abstract

Abstract

Study on the structure and energy flow of food webs is important for maintaining the stability of structure and function of marine ecosystems, which will contribute to the in-depth understanding of the complex processes of marine ecosystems. Based on the seasonal bottom trawl survey data in the northern waters of Jiangsu Province from 2019−2021, a linear inverse models using a Monte Carlo method coupled with Markov chain model combined with ecological network analysis (ENA) were used to explore the status of the ecosystem and energy flow characteristics of the food web in this area. The results showed that there were 299 energy flow paths in the ecosystem, which showed a typical pyramid structure. In addition, the energy consumed by respiration and the energy flowing into the detritus of each functional group remains synchronized. Compared with other sea areas, connectance (C) and system omnivory index (SOI) were 0.40 and 0.22, respectively, which were at relatively high levels, indicating that organisms from different trophic levels in this ecosystem were closely connected. It has a relatively complex food web structure, which can resist external disturbance. Total primary production/total respiration (TPP/TR) and Finn’s cycling index (FCI) were 1.05 and 5.76%, respectively, indicating that the ecosystem was relatively mature and used energy efficiently. In addition, constraint efficiency (CE), extent of development (AC), synergism index (b/c) and dominance indirect effects (i/d) also indicated high potential for development and regeneration. This study will provide a theoretical basis for the restoration and sustainable utilization of fishery resources in the northern waters of Jiangsu Povince, and provide a scientific basis for the implementation of Ecosystem-based fishery management in this area.
- linear inverse models using a Monte Carlo method coupled with Markov chain,
- ecological network analysis,
- energy flows,
- ecosystem characteristics,
- food web

FullText(HTML)

References(47)

References

[1]	刘尊雷, 程家骅, 李圣法, 等. 江苏近岸海域鱼类群落结构的变化[J]. 中国水产科学, 2009, 16(2): 274−281. doi: 10.3321/j.issn:1005-8737.2009.02.016 Liu Zunlei, Cheng Jiahua, Li Shengfa, et al. Changes of fish community structure in Jiangsu, China offshore areas[J]. Journal of Fishery Sciences of China, 2009, 16(2): 274−281. doi: 10.3321/j.issn:1005-8737.2009.02.016
[2]	田丰歌, 徐兆礼. 春夏季苏北浅滩大丰水域浮游动物生态特征[J]. 海洋环境科学, 2011, 30(3): 316−320. doi: 10.3969/j.issn.1007-6336.2011.03.003 Tian Fengge, Xu Zhaoli. Ecological characters of zooplankton in middle area of Subei Shoal in spring and summer[J]. Marine Environmental Science, 2011, 30(3): 316−320. doi: 10.3969/j.issn.1007-6336.2011.03.003
[3]	Vasslides J M, Jensen O P. Quantitative vs. Semiquantitative ecosystem models: comparing alternate representations of an estuarine ecosystem[J]. Journal of Coastal Research, 2017, 78(10078): 287−296.
[4]	任晓明, 刘阳, 徐宾铎, 等. 基于Ecopath模型的海州湾及邻近海域生态系统结构研究[J]. 海洋学报, 2020, 42(6): 101−109. Ren Xiaoming, Liu Yang, Xu Binduo, et al. Ecosystem structure in the Haizhou Bay and adjacent waters based on Ecopath model[J]. Haiyang Xuebao, 2020, 42(6): 101−109.
[5]	徐从军, 隋昊志, 徐宾铎, 等. 基于LIM-MCMC模型研究海州湾食物网能量流动特征[J]. 中国水产科学, 2021, 28(1): 66−78. Xu Congjun, Sui Haozhi, Xu Binduo, et al. Energy flows in the Haizhou Bay food web based on the LIM-MCMC model[J]. Journal of Fishery Sciences of China, 2021, 28(1): 66−78.
[6]	Malaterre C, Dussault A C, Rousseau-Mermans S, et al. Functional diversity: an epistemic roadmap[J]. BioScience, 2019, 69(10): 800−811. doi: 10.1093/biosci/biz089
[7]	Vézina A F, Platt T. Food web dynamics in the ocean. I. Best-estimates of flow networks using inverse methods[J]. Marine Ecology Progress Series, 1988, 42(3): 269−287.
[8]	Niquil N, Saint-Béat B, Johnson G A, et al. Inverse modeling in modern ecology and application to coastal ecosystems[J]. Treatise on Estuarine and Coastal Science, 2011, 9: 115−133.
[9]	Kones J K, Soetaert K, Van Oevelen D, et al. Gaining insight into food webs reconstructed by the inverse method[J]. Journal of Marine Systems, 2006, 60(1/2): 153−166.
[10]	Johnson R W, McElhaney J. Postherpetic neuralgia in the elderly[J]. The International Journal of Clinical Practice, 2009, 63(9): 1386−1391. doi: 10.1111/j.1742-1241.2009.02089.x
[11]	Savenkoff C, Castonguay M, Chabot D, et al. Changes in the northern Gulf of St. Lawrence ecosystem estimated by inverse modelling: evidence of a fishery-induced regime shift?[J]. Estuarine, Coastal and Shelf Science, 2007, 73(3/4): 711−724.
[12]	Chaalali A, Saint-Béat B, Lassalle G, et al. A new modeling approach to define marine ecosystems food-web status with uncertainty assessment[J]. Progress in Oceanography, 2015, 135: 37−47. doi: 10.1016/j.pocean.2015.03.012
[13]	Nogues Q, Raoux A, Araignous E, et al. Cumulative effects of marine renewable energy and climate change on ecosystem properties: sensitivity of ecological network analysis[J]. Ecological Indicators, 2021, 121: 107128. doi: 10.1016/j.ecolind.2020.107128
[14]	Tecchio S, Chaalali A, Raoux A, et al. Evaluating ecosystem-level anthropogenic impacts in a stressed transitional environment: the case of the Seine Estuary[J]. Ecological Indicators, 2016, 61: 833−845. doi: 10.1016/j.ecolind.2015.10.036
[15]	Van Oevelen D, Van den Meersche K, Meysman F J R, et al. Quantifying food web flows using linear inverse models[J]. Ecosystems, 2010, 13(1): 32−45. doi: 10.1007/s10021-009-9297-6
[16]	欧阳力剑, 郭学武. 东、黄海主要鱼类Q/B值与种群摄食量研究[J]. 渔业科学进展, 2010, 31(2): 23−29. doi: 10.3969/j.issn.1000-7075.2010.02.004 Ouyang Lijian, Guo Xuewu. Studies on the Q/B values and food consumption of major fishes in the East China Sea and the Yellow Sea[J]. Progress in Fishery Sciences, 2010, 31(2): 23−29. doi: 10.3969/j.issn.1000-7075.2010.02.004
[17]	林群, 王俊, 李忠义, 等. 黄河口邻近水域贝类生态容量[J]. 应用生态学报, 2018, 29(9): 3131−3138. doi: 10.13287/j.1001-9332.201809.039 Lin Qun, Wang Jun, Li Zhongyi, et al. Ecological carrying capacity of shellfish in the Yellow River Estuary and its adjacent waters[J]. Chinese Journal of Applied Ecology, 2018, 29(9): 3131−3138. doi: 10.13287/j.1001-9332.201809.039
[18]	张硕, 王腾, 符小明, 等. 连云港海州湾渔业生态修复水域生态系统能量流动模型初探[J]. 海洋环境科学, 2015, 34(1): 42−47. doi: 10.13634/j.cnki.mes.2015.01.008 Zhang Shuo, Wang Teng, Fu Xiaoming, et al. A primary study on the energy flow in the ecosystem of fishery ecological restoration area in Haizhou Bay, Lianyungang[J]. Marine Environmental Science, 2015, 34(1): 42−47. doi: 10.13634/j.cnki.mes.2015.01.008
[19]	王腾, 张贺, 张虎, 等. 基于营养通道模型的海州湾中国明对虾生态容纳量[J]. 中国水产科学, 2016, 23(4): 965−975. Wang Teng, Zhang He, Zhang Hu, et al. Ecological carrying capacity of Chinese shrimp stock enhancement in Haizhou Bay of East China based on Ecopath model[J]. Journal of Fishery Sciences of China, 2016, 23(4): 965−975.
[20]	徐超, 王思凯, 赵峰, 等. 基于Ecopath模型的长江口生态系统营养结构和能量流动研究[J]. 海洋渔业, 2018, 40(3): 309−318. doi: 10.3969/j.issn.1004-2490.2018.03.006 Xu Chao, Wang Sikai, Zhao Feng, et al. Trophic structure and energy flow of the Yangtze Estuary ecosystem based on the analysis with Ecopath model[J]. Marine Fisheries, 2018, 40(3): 309−318. doi: 10.3969/j.issn.1004-2490.2018.03.006
[21]	王远超, 梁翠, 线薇微, 等. 基于生态通道模型的长江口及邻近海域生态系统能流动态分析[J]. 海洋科学, 2018, 42(5): 54−67. doi: 10.11759/hykx20170816001 Wang Yuanchao, Liang Cui, Xian Weiwei, et al. Ecopath based dynamic analyses of energy flows of Yangtze Estuary and its adjacent waters[J]. Marine Sciences, 2018, 42(5): 54−67. doi: 10.11759/hykx20170816001
[22]	王玮, 王俊杰, 左平, 等. 基于Ecopath模型的西南黄海生态系统结构和能量流动分析[J]. 应用海洋学学报, 2019, 38(4): 528−539. doi: 10.3969/J.ISSN.2095-4972.2019.04.008 Wang Wei, Wang Junjie, Zuo Ping, et al. Analysis of structure and energy flow in southwestern Yellow Sea ecosystem based on Ecopath model[J]. Journal of Applied Oceanography, 2019, 38(4): 528−539. doi: 10.3969/J.ISSN.2095-4972.2019.04.008
[23]	Han Dongyan, Xue Ying, Zhang Chongliang, et al. A mass balanced model of trophic structure and energy flows of a semi-closed marine ecosystem[J]. Acta Oceanologica Sinica, 2017, 36(10): 60−69. doi: 10.1007/s13131-017-1071-6
[24]	Hoshiba Y, Hirata T, Shigemitsu M, et al. Biological data assimilation for parameter estimation of a phytoplankton functional type model for the western North Pacific[J]. Ocean Science, 2018, 14(3): 371−386. doi: 10.5194/os-14-371-2018
[25]	林群, 金显仕, 张波, 等. 基于营养通道模型的渤海生态系统结构十年变化比较[J]. 生态学报, 2009, 29(7): 3613−3620. Lin Qun, Jin Xianshi, Zhang Bo, et al. Comparative study on the changes of the Bohai Sea ecosystem structure based on Ecopath model between ten years[J]. Acta Ecologica Sinica, 2009, 29(7): 3613−3620.
[26]	程济生, 朱金声. 黄海主要经济无脊椎动物摄食特征及其营养层次的研究[J]. 海洋学报, 1997, 19(6): 102−108. Cheng Jisheng, Zhu Jinsheng. The study on feeding characteristics and trophic levels of main economic invertebrates in the Yellow Sea[J]. Haiyang Xuebao, 1997, 19(6): 102−108.
[27]	杨纪明. 渤海鱼类的食性和营养级研究[J]. 现代渔业信息, 2001, 16(10): 10−19. Yang Jiming. A study on food and trophic levels of Baohai Sea fish[J]. Modern Fisheries Information, 2001, 16(10): 10−19.
[28]	Froese R, Pauly D. FishBase. World Wide Web electronic publication[EB/OL]. [2023−02−17]. http://www.fishbase.org.
[29]	Soetaert K, Van Oevelen D. LIM: linear inverse model examples and solution methods[EB/OL]. [2022−05−11]. https://cran.r-project.org/web/packages/LIM/index.html.
[30]	Soetaert K, Van den Meersche K, Van Oevelen D, et al. limSolve: solving linear inverse models[EB/OL]. [2022−10−13]. https://cran.r-project.org/web//packages/limSolve/limSolve.pdf.
[31]	Saint-Béat B, Vézina A F, Asmus R, et al. The mean function provides robustness to linear inverse modelling flow estimation in food webs: a comparison of functions derived from statistics and ecological theories[J]. Ecological Modelling, 2013, 258: 53−64. doi: 10.1016/j.ecolmodel.2013.01.023
[32]	Proulx S R, Promislow D E L, Phillips P C. Network thinking in ecology and evolution[J] Trends in Ecology & Evolution, 2005, 20(6): 345−353.
[33]	Heymans J J, Guénette S, Christensen V. Evaluating network analysis indicators of ecosystem status in the gulf of Alaska[J]. Ecosystems, 2007, 10(3): 488−502. doi: 10.1007/s10021-007-9034-y
[34]	Latham II L G. Network flow analysis algorithms[J]. Ecological Modelling, 2006, 192(3/4): 586−600.
[35]	Odum E P. The strategy of ecosystem development: an understanding of ecological succession provides a basis for resolving man’s conflict with nature[J]. Science, 1969, 164(3877): 262−270. doi: 10.1126/science.164.3877.262
[36]	陈作志, 邱永松. 南海北部生态系统食物网结构、能量流动及系统特征[J]. 生态学报, 2010, 30(18): 4855−4865. Chen Zuozhi, Qiu Yongsong. Assessment of the food-web structure, energy flows, and system attribute of northern South China Sea ecosystem[J]. Acta Ecologica Sinica, 2010, 30(18): 4855−4865.
[37]	Finn J T. Flow analysis of models of the Hubbard Brook ecosystem[J]. Ecology, 1980, 61(3): 562−571. doi: 10.2307/1937422
[38]	Latham II L G, Scully E P. Quantifying constraint to assess development in ecological networks[J]. Ecological Modelling, 2002, 154(1/2): 25−44.
[39]	Ulanowicz R E. Ascendency: a measure of ecosystem performance[M]//Jørgensen S E, Müeller F. Handbook of Ecosystem Theories and Management. Boca Raton: Lewis Publishers, 2000: 303−315.
[40]	Fath B D. Distributed control in ecological networks[J]. Ecological Modelling, 2004, 179(2): 235−245. doi: 10.1016/j.ecolmodel.2004.06.007
[41]	李永刚, 汪振华, 章守宇. 嵊泗人工鱼礁海区生态系统能量流动模型初探[J]. 海洋渔业, 2007, 29(3): 226−234. doi: 10.3969/j.issn.1004-2490.2007.03.006 Li Yonggang, Wang Zhenhua, Zhang Shouyu. A preliminary approach on the ecosystem model of the artificial reef in Shengsi[J]. Marine Fisheries, 2007, 29(3): 226−234. doi: 10.3969/j.issn.1004-2490.2007.03.006
[42]	赵静, 章守宇, 许敏. 枸杞海藻场生态系统能量流动模型初探[J]. 上海海洋大学学报, 2010, 19(1): 98−104. Zhao Jing, Zhang Shouyu, Xu Min. The primary research of the energy flow in Gouqi kelp bed ecosystem[J]. Journal of Shanghai Ocean University, 2010, 19(1): 98−104.
[43]	Tong Ling, Tang Qisheng, Pauly D. A preliminary approach on mass-balance ecopath model of the Bohai Sea[J]. Chinese Journal of Applied Ecology, 2000, 11(3): 435−440.
[44]	Navia A F, Maciel-Zapata S R, González-Acosta A F, et al. Importance of weak trophic interactions in the structure of the food web in La Paz Bay, southern Gulf of California: a topological approach[J]. Bulletin of Marine Science, 2019, 95(2): 199−215. doi: 10.5343/bms.2018.0043
[45]	Parmesan C. Ecological and evolutionary responses to recent climate change[J]. Annual Review of Ecology Evolution, and Systematics, 2006, 37: 637−669. doi: 10.1146/annurev.ecolsys.37.091305.110100
[46]	Planque B, Primicerio R, Michalsen K, et al. Who eats whom in the Barents Sea: a food web topology from plankton to whales[J]. Ecology, 2014, 95(5): 1430. doi: 10.1890/13-1062.1
[47]	Benoit D M, Jackson D A, Chu C. Partitioning fish communities into guilds for ecological analyses: an overview of current approaches and future directions[J]. Canadian Journal of Fisheries and Aquatic Sciences, 2021, 78(7): 984−993. doi: 10.1139/cjfas-2020-0455