Skip to main content

Advertisement

SpringerLink
Log in

Spatial difference in net growth rate of Yesso scallop Patinopecten yessoensis revealed by an aquaculture ecosystem model

  • Aquaculture and Fisheries
  • Published:
Journal of Oceanology and Limnology Aims and scope Submit manuscript

Abstract

Identifying the main factors on spatial differences in net growth rate of Yesso scallop (Patinopecten yessoensis) in culture system is the key to effective aquaculture management and development. Coupling a 3D ecosystem model (ROMS-CoSiNE) with a dynamic energy budget model for scallops, a Yesso scallop culture ecosystem (YeSCE) model was established with which scallop growth was simulated with real seeding density and juvenile size from local aquaculture experiments from December 1, 2012 to November 30, 2013. Results show that the YeSCE model has reasonably simulated the environmental variation and scallop net growth rate in the Changhai sea area. The growth of scallops was slow in winter and midsummer and was limited mainly by temperature. Food availability was a key factor that contributed to the fast growth of the scallops during spring to early summer and in autumn. Generally, the scallops cultured in the north part of the Changhai sea area grew faster than those in the south; and the net growth rate for scallops cultured near the island was significantly higher compare to the others, which is probably correlated to the spatial distribution of food availability. Based on the correlation analysis, the spatial differences of the net growth rate were largely affected by the length of the match timing of temperatures and food availability. The results of this study provide a scientific support for optimizing bottom culture planning and adjusting bottom culture methods.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Data Availability Statement

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  • Aya F A, Kudo I. 2010. Isotopic shifts with size, culture habitat, and enrichment between the diet and tissues of the Japanese scallop Mizuhopecten yessoensis (Jay, 1857). Marine Biology, 157(10): 2 157–2 167, https://doi.org/10.1007/s00227-010-1480-y.

    Article  Google Scholar 

  • Bourlès Y, Alunno-Bruscia M, Pouvreau S, Tollu G, Leguay L, Arnaud C, Goulletquer P, Kooijman S A L M. 2009. Modelling growth and reproduction of the Pacific oyster Crassostrea gigas: advances in the oyster-DEB model through application to a coastal pond. Journal of Sea Research, 62(2–3): 62–71, https://doi.org/10.1016/j.seares.2009.03.002.

    Article  Google Scholar 

  • Boyer T, Locarnini R A, Zweng M M, Mishonov A V, Reagan J R, Antonov J I, Garcia H E, Baranova O K, Johnson D R, Seidov D, Biddle M M, Hamilton M. 2015. Changes to calculations of the World Ocean Atlas 2013 for version 2. http://data.nodc.noaa.gov/woa/WOA13/DOC/woa13v2_changes.pdf. Accessed on 2020-02-23.

  • Chen C T A. 2009. Chemical and physical fronts in the Bohai, Yellow and East China seas. Journal of Marine Systems, 78(3): 394–410, https://doi.org/10.1016/j.jmarsys.2008.11.016.

    Article  Google Scholar 

  • Chen J Y. 2019. Seize opportunities to accelerate the green development of aquaculture. China Fishery Quality and Standards, 9(4): 1–4. (in Chinese with English abstract)

    Google Scholar 

  • Cloern J E, Grenz C, Vidergar-Lucas L. 1995. An empirical model of the phytoplankton chlorophyll: carbon ratio-the conversion factor between productivity and growth rate. Limnology and Oceanography, 40(7): 1 313–1 321, https://doi.org/10.4319/lo.1995.40.7.1313.

    Article  Google Scholar 

  • Cummings J A. 2005. Operational multivariate ocean data assimilation. Quarterly Journal of the Royal Meteorological Society, 131(613): 3 583–3 604, https://doi.org/10.1256/qj.05.105.

    Article  Google Scholar 

  • Dee D P, Uppala S M, Simmons A J, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda M A, Balsamo G, Bauer B, Bechtold P, Beljaars A C M, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer A J, Haimberger L, Healy S B, Hersbach H, Hólm E V, Isaksen L, Kållberg P, Köhler M, Matricardi M, McNally A P, Monge-Sanz B M, Morcrette J J, Park B K, Peubey C, de Rosnay P, Tavolato C, Thépaut J N, Vitart F. 2011. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656): 553–597, https://doi.org/10.1002/qj.828.

    Article  Google Scholar 

  • FAO. 2020. The state of world fisheries and aquaculture 2020. http://www.fao.org/state-of-fisheries-aquaculture/en/.

  • Filgueira R, Guyondet T, Comeau L A, Grant J. 2014. A fully-spatial ecosystem-DEB model of oyster (Crassostrea virginica) carrying capacity in the Richibucto Estuary, Eastern Canada. Journal of Marine Systems, 136: 42–54, https://doi.org/10.1016/jjmarsys.2014.03.015.

    Article  Google Scholar 

  • Fishery Administration Bureau of Ministry of Agriculture and Rural Areas, National Aquatic Technology Promotion Center, China Fisheries Society. 2019. China Fishery Statistical Yearbook of 2019. China Agriculture Press, Beijing, China. p.1–172. (in Chinese)

    Google Scholar 

  • Guan B X. 1963. A preliminary study of the temperature variations and the characteristics of the circulation of the Cold Water Mass of the Yellow Sea. Oceanologia et Limnologia Sinica, 5(4): 255–284. (in Chinese)

    Google Scholar 

  • Guyondet T, Roy S, Koutitonsky V G, Grant J, Tita G. 2010. Integrating multiple spatial scales in the carrying capacity assessment of a coastal ecosystem for bivalve aquaculture. Journal of Sea Research, 64(3): 341–359, https://doi.org/10.1016/j.seares.2010.05.003.

    Article  Google Scholar 

  • Helm M. 2005. Cultured aquatic species information programme. Patinopecten yessoensis (Jay, 1857). http://www.fao.org/fishery/culturedspecies/Patinopecten_yessoensis/en. Accessed on 2020-02-23.

  • Jiang W W, Lin F, Du M R, Fang J G, Fang J H, Gao Y P, Wang X Q, Li F X, Dong S P, Hou X, Jiang Z J. 2020. Simulation of Yesso scallop, Patinopecten yessoensis, growth with a dynamic energy budget (DEB) model in the mariculture area of Zhangzidao Island. Aquaculture International, 28(1): 59–71, https://doi.org/10.1007/s10499-019-00447-6.

    Article  Google Scholar 

  • Jiang W W, Lin F, Fang J G, Gao Y P, Du M R, Fang J H, Li W H, Jiang Z J. 2018. Transcriptome analysis of the Yesso scallop, Patinopecten yessoensis gills in response to water temperature fluctuations. Fish & Shellfish Immunology, 80: 133–140, https://doi.org/10.1016/j.fsi.2018.05.038.

    Article  Google Scholar 

  • Jiang X. 2013. Study on the Growth, Food Source, Oxygen Consumption and Ammonia Excretion of Scallop Patinopecten Yessoensis Jay. Nanjing Agricultural University, Nanjing, China. (in Chinese)

    Google Scholar 

  • Kooijman S A L M. 2010. Dynamic Energy Budget Theory for Metabolic Organisation. Cambridge University Press, Cambridge. p.1–514.

    Google Scholar 

  • Laurel B J, Hurst T P, Ciannelli L. 2011. An experimental examination of temperature interactions in the match-mismatch hypothesis for Pacific cod larvae. Canadian Journal of Fisheries and Aquatic Sciences, 68(1): 51–61, https://doi.org/10.1139/F10-130.

    Article  Google Scholar 

  • Lavaud R, La Peyre M K, Casas S M, Bacher C, La Peyre J F. 2017. Integrating the effects of salinity on the physiology of the eastern oyster, Crassostrea virginica, in the northern Gulf of Mexico through a Dynamic Energy Budget model. Ecological Modelling, 363: 221–233, https://doi.org/10.1016/j.ecolmodel.2017.09.003.

    Article  Google Scholar 

  • Li H B, Liang Y B, Yuan X T. 2012. The effect of raft-culture on distribution of Synchococcus in Changhai waters, Liaoning. Acta Oceanologica Sinica, 34(5): 221–225. (in Chinese with English abstract)

    Google Scholar 

  • Liu S M, Hong G H, Zhang J, Ye X W, Jiang X L. 2009. Nutrient budgets for large Chinese estuaries. Biogeosciences, 6(10): 2 245–2 263, https://doi.org/10.5194/bg-6-2245-2009.

    Article  Google Scholar 

  • Liu Y, Saitoh S I, Radiarta I N, Igarashi H, Hirawake T. 2014. Spatiotemporal variations in suitable areas for Japanese scallop aquaculture in the Dalian coastal area from 2003 to 2012. Aquaculture, 422-423: 172–183, https://doi.org/10.1016/j.aquaculture.2013.11.033.

    Article  Google Scholar 

  • Luo C Y, Nie H T, Zhang H Y. 2019. Spatial variability of parameter sensitivity in the ecosystem simulation of the Bohai Sea and Yellow Sea. Haiyang Xuebao, 41(8): 85–96. (in Chinese with English abstract)

    Google Scholar 

  • Nan X L, Wei H, Fan R F, Yang W. 2020. Rapid changes in the near-bottom temperature of the bottom aquaculture area around the Zhangzi Island in summer. Acta Oceanologica Sinica, 39(5): 46–54, https://doi.org/10.1007/s13131-020-1605-1.

    Article  Google Scholar 

  • Person R, Aumont O, Madec G, Vancoppenolle M, Bopp L, Merino N. 2019. Sensitivity of ocean biogeochemistry to the iron supply from the Antarctic Ice Sheet explored with a biogeochemical model. Biogeosciences, 16(18): 3 583–3 603, https://doi.org/10.5194/bg-16-3583-2019.

    Article  Google Scholar 

  • Pouvreau S, Bourles Y, Lefebvre S, Gangnery A, Alunno-Bruscia M. 2006. Application of a dynamic energy budget model to the Pacific oyster, Crassostrea gigas, reared under various environmental conditions. Journal of Sea Research, 56(2): 156–167, https://doi.org/10.1016/j.seares.2006.03.007.

    Article  Google Scholar 

  • Redfield A C, Ketchum B H, Richards F A. 1963. The influence of organisms on the composition of seawater. In: Hill M N ed. The Composition of Seawater: Comparative and Descriptive Oceanography. The Sea: Ideas and Observations on Progress in the Study of the Seas, 2. Interscience Publishers, New York. p.26–77.

    Google Scholar 

  • Rico-Villa B, Pouvreau S, Robert R. 2009. Influence of food density and temperature on ingestion, growth and settlement of Pacific oyster larvae, Crassostrea gigas. Aquaculture, 287(3–4): 395–401, https://doi.org/10.1016/j.aquaculture.2008.10.054.

    Article  Google Scholar 

  • Scharf I, Braf H, Ifrach N, Rosenstein S, Subach A. 2015. The effects of temperature and diet during development, adulthood, and mating on reproduction in the red flour beetle. PLoS One, 10(9): e0136924, https://doi.org/10.1371/journal.pone.0136924.

    Article  Google Scholar 

  • Shchepetkin A F, McWilliams J C. 2005. The regional oceanic modeling system (ROMS): a split-explicit, free-surface, topography-following-coordinate oceanic model. Ocean Modelling, 9(4): 347–404, https://doi.org/10.1016/j.ocemod.2004.08.002.

    Article  Google Scholar 

  • Stavrakidis-Zachou O, Papandroulakis N, Lika K. 2019. A DEB model for European sea bass (Dicentrarchus labrax): parameterisation and application in aquaculture. Journal of Sea Research, 143: 262–271, https://doi.org/10.1016/j.seares.2018.05.008.

    Article  Google Scholar 

  • Taylor K E. 2001. Summarizing multiple aspects of model performance in a single diagram. Journal of Geophysical Research: Atmospheres, 106(D7): 7 183–7 192, https://doi.org/10.1029/2000JD900719.

    Article  Google Scholar 

  • Tong Y D, Zhao Y, Zhen G C, Chi J, Liu X H, Lu Y R, Wang X J, Yao R H, Chen J Y, Zhang W. 2015. Nutrient loads flowing into coastal waters from the main rivers of China (2006-2012). Scientific Reports, 5(1): 16678, https://doi.org/10.1038/srep16678.

    Article  Google Scholar 

  • Troost TA, Wijsman J W M, Saraiva S, Freitas V 2010. Modelling shellfish growth with dynamic energy budget models: an application for cockles and mussels in the Oosterschelde (southwest Netherlands). Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1557): 3 567–3 577, https://doi.org/10.1098/rstb.2010.0074.

    Article  Google Scholar 

  • van der Meer J, Kooijman S A L M. 2014. Inference on energetics of deep-sea fish that cannot be aged: the case of the hagfish. Journal of Sea Research, 94: 138–143, https://doi.org/10.1016/j.seares.2014.07.007.

    Article  Google Scholar 

  • van der Meer J. 2006. An introduction to Dynamic Energy Budget (DEB) models with special emphasis on parameter estimation. Journal of Sea Research, 56(2): 85–102, https://doi.org/10.1016/j.seares.2006.03.001.

    Article  Google Scholar 

  • van der Veer H W, Cardoso J F M F, van der Meer J. 2006. The estimation of DEB parameters for various Northeast Atlantic bivalve species. Journal of Sea Research, 56: 107–124, https://doi.org/10.1016/j.seares.2006.03.005.

    Article  Google Scholar 

  • Wang J N, Yan W J, Chen N W, Li X Y, Liu L S. 2015. Modeled long-term changes of DIN: DIP ratio in the Changjiang River in relation to Chl-a and DO concentrations in adjacent estuary. Estuarine, Coastal and Shelf Science, 166: 153–160, https://doi.org/10.1016/j.ecss.2014.11.028.

    Article  Google Scholar 

  • Xiu P, Chai F. 2014. Connections between physical, optical and biogeochemical processes in the Pacific Ocean. Progress in Oceanography, 122: 30–53, https://doi.org/10.1016/j.pocean.2013.11.008.

    Article  Google Scholar 

  • Yuan X T, Zhang M J, Liang Y B, Liu D, Guan D M. 2010. Self-pollutant loading from a suspension aquaculture system of Japanese scallop (Patinopecten yessoensis) in the Changhai sea area, Northern Yellow Sea of China. Aquaculture, 304(1–4): 79–87, https://doi.org/10.1016/j.aquaculture.2010.03.026.

    Article  Google Scholar 

  • Zhang J H, Wu W G, Liu Y, Lin F, Wang W, Niu Y L. 2017. A dynamic energy budget (DEB) growth model for Japanese scallop Patinopecten yessoensis cultured in China. Journal of Fishery Sciences of China, 24(3): 497–506. (in Chinese with English abstract).

    Article  Google Scholar 

  • Zhang J H, Wu W G, Xu D, Ren L H, Niu Y L, Zhao X W. 2016. The estimation of Dynamic Energy Budget (DEB) model parameters for scallop Patinopecten yessoensis. Journal of Fisheries of China, 40(5): 703–710. (in Chinese with English abstract)

    Google Scholar 

  • Zhang J. 1996. Nutrient elements in large Chinese estuaries. Continental Shelf Research, 16(8): 1 023–1 045, https://doi.org/10.1016/0278-4343(95)00055-0.

    Article  Google Scholar 

  • Zhao Y X, Zhang J H, Lin F, Ren J S, Sun K, Liu Y, Wu W G, Wang W. 2019. An ecosystem model for estimating shellfish production carrying capacity in bottom culture systems. Ecological Modelling, 393: 1–11, https://doi.org/10.1016/j.ecolmodel.2018.12.005.

    Article  Google Scholar 

  • Zhou F, Chai F, Huang D J, Xue H J, Chen J F, Xiu P, Xuan J L, Li J, Zeng D Y, Ni X B, Wang K. 2017. Investigation of hypoxia off the Changjiang Estuary using a coupled model of ROMS-CoSiNE. Progress in Oceanography, 159: 237–254, https://doi.org/10.1016/j.pocean.2017.10.008.

    Article  Google Scholar 

Download references

Acknowledgment

The transect observations were collected onboard of R/V Dongfanghong 2 implementing the open research cruise NORC2017-01 supported by the NSFC Ship-time Sharing Project. We acknowledge the crew members of R/V Liaokeyu 19 from the Zhangzi Island group for their support. We appreciate the help of Simeng QIAN, Chenyi LUO, and Guangyue ZHANG in the preparation of the ecosystem model.

Author information

Authors and Affiliations

  1. School of Marine Science and Technology, Tianjin University, Tianjin, 300072, China

    Xueliang Nan, Hao Wei, Haiyan Zhang & Hongtao Nie

Authors
  1. Xueliang Nan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hao Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Haiyan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hongtao Nie
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hongtao Nie.

Additional information

Supported by the National Key Research and Development Program of China (Nos. 2017YFC1404403, 2016YFC1401602), the National Natural Science Foundation of China (No. 41806018), and the Strategic Priority Research Program of the Chinese Academy of Sciences (No. XDA23050502)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nan, X., Wei, H., Zhang, H. et al. Spatial difference in net growth rate of Yesso scallop Patinopecten yessoensis revealed by an aquaculture ecosystem model. J. Ocean. Limnol. 40, 373–387 (2022). https://doi.org/10.1007/s00343-021-0423-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00343-021-0423-4

Keyword

Search

Navigation