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Ecosystem dynamics in Tokyo Bay with a focus on high trophic levels using Ecopath with Ecosim

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Abstract

The present study aimed to investigate ecosystem dynamics in Tokyo Bay, a semi-enclosed bay surrounded by the Tokyo metropolitan area in Japan, which is one of the largest and most populous industrialized areas in the world. The bay has been subject to eutrophication since the 1960s, and excessive increase in phytoplankton biomass has led to hypoxia. Ecopath with Ecosim was used to simulate the phytoplankton dynamics, and it could closely reproduce the observed relative biomass. To evaluate the impacts of phytoplankton dynamics, hypoxia, and fishing on the dynamics, with a focus on high trophic levels (up to fish), 3 scenarios, “Yearly constant phytoplankton biomass,” “No hypoxia,” and “No fishing,” were tested. Comparisons with the “Control” scenario without any modifications suggested that (1) the dynamics was controlled by phytoplankton (bottom-up control), (2) hypoxia did not have a serious effect on the past dynamics, and (3) stopping fishing would not contribute to recover of the biomass of exploited fish. Predictions for future dynamics under the scenarios “DO deteriorated” and “DO unchanged” suggest that if DO deteriorates strongly enough to decrease the survival of most benthos, the ecosystem might undergo a non-negligible transformation through extinction or biomass decrease of some benthos.

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References

  1. Yoshikawa K (2011) Drainage basin of Tokyo Bay. In: Committee on Marine Environmental Studies in Tokyo Bay (ed) Tokyo Bay. Kouseisha-kouseikaku, Tokyo, pp 2–9 (in Japanese)

  2. Okada T, Nakayama K, Takao T, Furukawa K (2011) Influence of freshwater input and bay reclamation on long-term changes in seawater residence times in Tokyo bay, Japan. Hydrol Process 25:2694–2702

    Article  Google Scholar 

  3. Yamaguchi S (2011) Photosynthetic activity and primary productivity. In: Committee on Marine Environmental Studies in Tokyo Bay (ed) Tokyo Bay. Kouseisha-Kouseikaku, Tokyo, pp 109–110 (in Japanese)

  4. Kohno H (2006) Natural history of fish in Tokyo Bay. Heibonsha, Tokyo (in Japanese)

    Google Scholar 

  5. Kodama K, Aoki I, Shimizu M, Taniguchi T (2002) Long-term changes in the assemblage of demersal fishes and invertebrates in relation to environmental variations in Tokyo Bay, Japan. Fish Manag Ecol 9:303–313

    Article  Google Scholar 

  6. Diaz RJ, Rosenberg R (1995) Marine benthic hypoxia: a review of its ecological effects and the behavioral responses of benthic macro fauna. Oceanogr Mar Biol Annu Rev 33:245–303

    Google Scholar 

  7. Ishii M, Ohata S (2010) Variations in water quality and hypoxic water mass in Tokyo Bay. Bull Coast Oceanogr 48:37–44

    Google Scholar 

  8. Kazama M, Ando H (2010) The actual conditions of nitrogen pollution in the coastal sea area of Tokyo. Glob Environ Res 15:171–178 (in Japanese)

    Google Scholar 

  9. Sohma A, Sekiguchi Y, Kuwae T, Nakamura Y (2008) A benthic–pelagic coupled ecosystem model to estimate the hypoxic estuary including tidal flat—model description and validation of seasonal/daily dynamics. Ecol Model 215:10–39

    Article  Google Scholar 

  10. Sasaki N, Tabeta S, Kitazawa D (2009) Long-term simulations of the ecosystem in Tokyo Bay considering changes of terrestrial load and topography. J Coast Zone Stud 21:27–38 (in Japanese)

    Google Scholar 

  11. Christensen V, Pauly D (1992) Ecopath: software for balancing steady state ecosystem models and calculating network characteristics. Ecol Model 61:169–185

    Article  Google Scholar 

  12. Christensen V, Walters C (2004) Ecopath with Ecosim: methods, capabilities and limitations. Ecol Model 172:109–139

    Article  Google Scholar 

  13. Shimizu M (1993) Tokyo Bay. In: Yoshida Y (ed) N:P ratio in the aquatic environment and aquatic organisms. Kouseisha-Kouseikaku, Tokyo, pp 73–83 (in Japanese)

    Google Scholar 

  14. Williams RB (1971) Computer simulation of energy flow in cedar bog lake, Minnesota based on the classical studies of Lindeman. In: Patten BC (ed) Systems analysis and simulation in ecology 1. Academic Press, London and NY, pp 543–582

    Chapter  Google Scholar 

  15. Masui T (1943) Benthic community in Tokyo Bay. J Oceanogr Soc Jpn 3:130–141 (in Japanese)

    Google Scholar 

  16. Keister JE, Houde ED, Breitburg DL (2000) Effects of bottom-layer hypoxia on abundances and depth distributions of organisms in Patuxent River, Chesapeake Bay. Mar Ecol Prog Ser 205:43–59

    Article  Google Scholar 

  17. Ando H, Kawai T (2007) Data analysis of habitat environment of benthos in the coastal sea of Tokyo. Annual report of the Tokyo Metropolitan Research Institute for Environmental Protection, pp 77–84 (in Japanese)

  18. Ichimura S, Kobayashi H (1964) Primary production in Tokyo Bay. Inform Bull Plamktol Jpn 11:6–8

    Google Scholar 

  19. Bureau of Environment Tokyo metropolitan government (1987) Survey reports for aquatic organisms (in Japanese)

  20. Allen KR (1971) Relation between production and biomass. J Fish Res Board Can 28:1573–1581

    Article  Google Scholar 

  21. Pauly D (1980) On the interrelationships between natural mortality, growth parameters, and mean environmental temperature in 175 fish stocks. J Cons 39:175–192

    Article  Google Scholar 

  22. Chistensen V, Walters C, Pauly D (2005) Ecopath with Ecosim: a user’s guide. Univ. B.C. Fish. Cent, Vancouver, November 2005 edition

  23. Palomares MLD, Pauly D (1989) A multiple regression model for predicting the food consumption of marine fish populations. Aust J Mar Freshw Res 40:259–273

    Article  Google Scholar 

  24. Palomares MLD, Pauly D (1998) Predicting food consumption of fish populations as functions of mortality, food type, morph metrics, temperature, and salinity. Mar Freshw Res 49:447–453

    Article  Google Scholar 

  25. Kozuki Y, Yamanaka R, Matsushige M, Saitoh A, Otani S, Ishida T (2013) The after-effects of hypoxia exposure on the clam Ruditapes philippinarum in Omaehama Beach, Japan. Est Coast Shelf Sci 116:50–56

    Article  Google Scholar 

  26. Hamano T, Yamamoto K (2005) Research on two factors, rheotaxis, and tolerance to hypoxia, which influences distribution of the squilla in a fishery. J Natl Fish Univ 53:117–129 (in Japanese)

    Google Scholar 

  27. Warren L (1977) The ecology of Capitella carpitata in British waters. J Mar Biol Assoc UK 57:151–159

    Article  Google Scholar 

  28. Buszowski J, Christensen V, Gao F, Hui J, Lai S, Steenbeek J, Walters W (2009) Ecopath with Ecosim 6

  29. Kodama K, Oyama M, Lee J, Kume G (2010) Drastic and synchronous changes in megabenthic community structure concurrent with environmental variations in a eutrophic coastal bay. Prog Oceanogr 87:157–167

    Article  Google Scholar 

  30. Matsumura T, Nomura H (2003) Recovery goal of water quality that assumes the elimination of hypoxic water. Kaiyo Monthly 35:464–469 (in Japanese)

    Google Scholar 

  31. Kakino J (1986) The mortality of Japanese Littleneck Clam Ruditapes phillippinarum in Tokyo Bay about influence of hypoxia. Fish Eng 23:41–47

    Google Scholar 

  32. Wessel P, Smith WHF (1991) Free software helps map and display data. Eos Trans Am Geophys Union 72:441–446

    Article  Google Scholar 

  33. Duan LJ, Li SY, Liu Y, Moreau J, Christensen V (2009) Modeling changes in the coastal ecosystem of the Pearl River Estuary from 1981 to 1998. Ecol Model 220:2802–2818

    Article  Google Scholar 

  34. Konuma S, Goshima Y, Nakamura Y (2002) Estimation of ingestions rate by bivalves in Banzu Tidal Flat, Tokyo Bay using growth model. Proc Coast Eng 49:1126–1130

    Article  Google Scholar 

  35. Yokoyama H (1988) Effects of temperature on the feeding activity and growth rate of the spionid polychaete Paraprionospio sp. (form A). J Exp Mar Biol Ecol 123:41–60 (in Japanese)

    Article  Google Scholar 

  36. Yamazaki M (1985) Food consumption of the mantis shrimp, Oratosquilla oratoria (De Haan). Bull Fac Fish Hokkaido Univ 36:177–181 (in Japanese)

    Google Scholar 

  37. Hatanaka M, Sekino K (1962) Ecological studies on the Japanese sea-bass. Bull Jpn Soc Sci Fish 28:857–861 (in Japanese)

    Article  Google Scholar 

  38. Hosokawa Y, Horie T (1989) Tolerance of Paraprions pio sp. To low DO concentration and condition on summer defaunation due to oxygen depletion in inner Bay. Tech Note Port Harb Res Inst Minist Transp Jpn 643: 39 (in Japanese)

  39. Science and Technology Agency (1985) The studies on production of marine bioresearches and environment, 396 (in Japanese)

  40. Miyazaki I (1940) Studies on the Japanese common goby, Acanthogobius Flavimanus (TEMMINCK et SCHLEGEL). Bull Jpn Soc Sci Fish 9:159–180 (in Japanese)

    Article  Google Scholar 

Download references

Acknowledgments

We thank the members of the Fish Population Dynamics Laboratory, Atmosphere and Ocean Research Institute. The regional map was produced using Generic Mapping Tools [32].

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Authors and Affiliations

  1. Graduate School of Frontier Sciences/Atmosphere and Ocean Research Institute, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8564, Japan

    Ayaka Sakamoto & Kunio Shirakihara

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  1. Ayaka Sakamoto
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  2. Kunio Shirakihara
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Correspondence to Ayaka Sakamoto.

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Sakamoto, A., Shirakihara, K. Ecosystem dynamics in Tokyo Bay with a focus on high trophic levels using Ecopath with Ecosim. J Mar Sci Technol 22, 1–10 (2017). https://doi.org/10.1007/s00773-016-0388-8

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  • DOI: https://doi.org/10.1007/s00773-016-0388-8

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