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Estuaries and Coasts

, Volume 30, Issue 6, pp 901–918 | Cite as

Trophic Assessment in Chinese coastal systems-review of methods and application to the Changjiang (Yangtze) Estuary and Jiaozhou Bay

  • Yongjin Xiao
  • João G. Ferreira
  • Suzanne B. Bricker
  • João P. Nunes
  • Mingyuan Zhu
  • Xuelei Zhang
Article

Abstract

Coastal eutrophication has become one of the main threats to Chinese coastal areas during the last two decades. High nutrient loads from human activities have modified the natural background water quality in coastal water bodies, resulting in a range of undesirable effects. There is a need to assess the eutrophic level in coastal systems and to identify the extent of this impact to guide development of appropriate management efforts. Traditional Chinese assessment methods are discussed and compared with other currently-used methods, such as the Oslo-Paris Convention for the Protection of the North Sea (OSPAR) Comprehensive Procedure and Assessment of Estuarine Trophic Status (ASSETS). The ASSETS method and two Chinese methods were tested on two Chinese systems: the Changjiang (Yangtze) Estuary and Jiaozhou Bay. ASSETS is process based, and uses a pressure-state-response model based on three main indices: Influencing Factors, Overall Eutrophic Condition, and Future Outlook. The traditional methods are based on a nutrient index. ASSETS was successfully applied to both systems, classifying the Changjiang Estuary as Bad (high eutrophication) and Jiaozhou Bay as High (low eutrophication). The traditional methods led to ambiguous results, particularly for Jiaozhou Bay, due to the high spatial variability of data and a failure to assess the role of shellfish aquaculture in nutrient control. An overview of the Chinese coastal zone identifies 50 estuaries and bays that should form part of a national assessment. A comparison of methods and results suggests that ASSETS is a promising tool for evaluating the eutrophication status of these systems.

Keywords

Water Quality Index Submerged Aquatic Vegetation Trophic State Index Export Coefficient Nutrient Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Literature Cited

  1. Arheimer, B. andJ. Olsson. 2003. Integration and Coupling of Hydrological Models with Water Quality Models: Applications in Europe. RA VI-Europe working group on hydrology report, World Meteorological Organization, Geneva, SwitzerlandGoogle Scholar
  2. Bashford, K. E., K.J. Beven, andP. C. Young. 2002. Observational data and scale-dependent parameterizations: Explorations using a virtual hydrological reality.Hydrological Processes 16: 293–312.CrossRefGoogle Scholar
  3. Beaulac, M. N. andK. H. Reckhow. 1982. An examination of land use-nutrient export relationships.Water Resources Bulletin 18: 1013–1024.Google Scholar
  4. Bernal, S., A. Butturini, E. Nin, F. Sabater, andS. Sabater. 2003. Leaf litter dynamics and nitrous oxide emission in a Mediterranean riparian forest: Implications for soil nitrogen dynamics.Journal of Environmental Quality 32:191–197.Google Scholar
  5. Booij, M. J. 2003. Determination and integration of appropriate spatial scales for river basin modelling.Hydrological Processes 17: 2581–2598.CrossRefGoogle Scholar
  6. Bricker, S. B., C. G. Clement, D. E. Pirhalla, S. P. Orlando, andD. R. G. Farrow. 1999. National Estuarine Eutrophication Assessment. Effects of Nutrient Enrichment in the Nation’s Estuaries. National Oceanic and Atmospheric Administration, National Ocean Service, Special Projects Office and National Centers for Coastal Ocean Science, Silver Spring, Maryland.Google Scholar
  7. Bricker, S. B., J. G. Ferreira, andT. Simas. 2003. An integrated methodology for assessment of estuarine trophic status.Ecological Modelling 169:39–60.CrossRefGoogle Scholar
  8. Bricker, S. B., D. Lipton, A. Mason, M. Dionne, D. Keeley, C. Krahforst, J. Latimer, andJ. Pennock. 2006. Improving Methods and Indicators for Evaluating Coastal Water Eutrophication: A Pilot Study in the Gulf of Maine. National Centers for Coastal Ocean Science, Center for Coastal Monitoring and Assessment, Silver Spring, Maryland.Google Scholar
  9. Bricker, S. B., B. Longstaff, W. Dennison, A. Jones, J. Woerner, C. Wicks, andK. Boicourt. 2007. National Estuarine Eutrophication Assessment: Effects of Nutrient Enrichment in the Nation’s Estuaries 1999–2004. National Oceanic and Atmospheric Administration Coastal Ocean Program Decision Analysis Series No. 26. National Centers for Coastal Ocean Science, Silver Spring, Maryland.Google Scholar
  10. Burkholder, J. M., M. A. Mallin, And H. B. Glasgow, Jr. 1999. Fish kills, bottom water hypoxia and the toxicPfiesteria complex in the Neuse River and Estuary.Marine Ecological Progress Series 179:301–310.CrossRefGoogle Scholar
  11. Carlson, R. 1977. A trophic state index for lakes.Limnology and Oceanography 22:361–369.CrossRefGoogle Scholar
  12. Chai, C., Z. Yu, X. Song, andX. Cao. 2006. The status and characteristics of eutrophication in the Yangtze River (Changjiang) Estuary and the adjacent East China Sea, China.Hydrobiologia 563:313–328.CrossRefGoogle Scholar
  13. Chang, N. B., H. W. Chen, andS. K. Ning. 2001. Identification of river water quality using the Fuzzy Synthetic Evaluation approach.Journal of Environmental Management 63:293–305.CrossRefGoogle Scholar
  14. Chaplot, V. 2007. Water and soil resources response to rising levels of atmospheric CO2 concentration and to changes in precipitation and air temperature.Journal of Hydrology 337:159–171.CrossRefGoogle Scholar
  15. Che, Y., Q. He, andW. Q. Lin. 2003. The distributions of particulate heavy metals and its indication to the transfer of sediments in the Changjiang Estuary and Hangzhou Bay, China.Marine Pollution Bulletin 46:123–131.CrossRefGoogle Scholar
  16. Chen, J. Y. andS. L. Chen. 2003a. Ecological environmental changes in the Changjiang estuary and suggestions for countermeasure.Water Resources Hydropower Engineering 34:19–25.Google Scholar
  17. Chen, Q. andA. E. Mynett. 2003b. Integration of data mining techniques and heuristic knowledge in fuzzy logic modelling of eutrophication in Taihu Lake.Ecological Modelling 162:55–67.CrossRefGoogle Scholar
  18. Chen, B., J. Wang, J. Tang, andS. Wen. 2002. Prediction to trend of nutrient status in Meizhou Bay, Fujian.Journal of Oceanography in Taiwan Strait 21:322–327.Google Scholar
  19. Chen, X. andY Zhong. 1999. Major impacts of sea-level rise on agriculture in the Yangtze delta area around Shanghai.Applied Geography 19:69–84.CrossRefGoogle Scholar
  20. Clesceri, N. L., S. J. Curran, andR. I. Sedlak. 1986. Nutrient loads to Wisconsin lakes: Part I. Nitrogen and phosphorus export coefficients.Water Resources Bulletin 22:983–989.Google Scholar
  21. Cloern, J. E. 2001. Our evolving conceptual model of the coastal eutrophication problem.Marine Ecology Progress Series 210:223–253.CrossRefGoogle Scholar
  22. Dettmann, E. H. 2001. Effect of water residence time on annual export and denitrification of nitrogen in estuaries: A model analysis.Estuaries 24:481–490.CrossRefGoogle Scholar
  23. Editorial Board of Bays in China. 1993. Bays in China. Ocean Press, Beijing, China.Google Scholar
  24. Editorial Board of Bays in China. 1998. Bays in China. Ocean Press, Beijing, China.Google Scholar
  25. Endreny, T. A. andE. F. Wood. 2003. Watershed weighting of export coefficients to map critical phosphorous loading areas.Journal of the American Water Resources Association 39:165–181.CrossRefGoogle Scholar
  26. European Community. 2000. Directive of the European Parliament and of the Council 2000/60/EC, establishing a Framework for Community Action in the Field of Water Policy.Google Scholar
  27. Ferreira, J. G., S. B. Bricker, andT. C. Simas. 2007a. Application and sensitivity testing of a eutrophication assessment method on coastal systems in the United States and European Union.Journal of Environmental Management 82:433–445.CrossRefGoogle Scholar
  28. Ferreira, J. G., A. J. S. Hawkins, andS. B. Bricker. 2007b. Management of productivity, environmental effects and profitability of shellfish aquaculture-the Farm Aquaculture Resource Management (FARM) model.Aquaculture 264:160–174.CrossRefGoogle Scholar
  29. Ferreira, J. G., T. Simas, A. Nobre, M. C. Silva, K. Schifferegger, andJ. Lencart-Silva. 2003. Identification of Sensitive Areas and Vulnerable Zones in Transitional and Coastal Portuguese Systems. Application of the United States National Estuarine Eutrophication Assessment to the Minho, Lima, Douro, Ria de Aveiro, Mondego, Tagus, Sado, Mira, Ria Formosa: and Guadiana systems, IMAR Institute of Marine Research, Lisbon, Portugal.Google Scholar
  30. Ferreira, J. G., W. J. Wolff, T. C. Simas, andS. B. Bricker. 2005. Does biodiversity of estuarine phytoplankton depend on hydrology?Ecological Modelling 187:513–523.CrossRefGoogle Scholar
  31. Fisher, P., R. J. Abrahart, andW. Herbinger. 1997. The sensitivity of two distributed non-point source pollution models to the spatial arrangement of the landscape.Hydrological Processes 11: 241–252.CrossRefGoogle Scholar
  32. Frink, C. R. 1991. Estimating nutrient exports to estuaries.Journal of Environmental Quality 20:717–724.CrossRefGoogle Scholar
  33. Grayson, R. andG. Blöschl. 2001. Spatial Patterns in Catchment Hydrology-Observations and Modelling. Cambridge University Press, Cambridge, Massachusetts.Google Scholar
  34. Guan, D. M. andX. W. Zhan. 2003. Red tide disaster in coastal water of China and its prevention suggestions.Marine Environmental Science 22:60–63.Google Scholar
  35. Guo, W., X. Zhang, Y. Yang, andM. Hu. 1998. Potential eutrophication assessment for Chinese coastal waters.Journal of Oceanography in Taiwan Strait 17:64–70.Google Scholar
  36. Han, X. F. andR Wang. 2001. The grazing impact and regulation effects of zooplankton on phytoplankton bloom.Marine Sciences (in Chinese) 25:31–33.Google Scholar
  37. Han, X. T., J. Z. Zou, andY S. Zhang. 2004. Harmful algae bloom species in Jiaozhou Bay and the features of distribution.Marine Sciences (in Chinese) 28:49–54.Google Scholar
  38. Hao, J., W. Huo, andZ. Yu. 2000. Preliminary study on red tide occurrence in relation to nutritional condition in aquaculture seawater of Jiaozhou Bay.Marine Sciences (in Chinese) 24:37–41.Google Scholar
  39. Harmel, D., S. Potter, P. Casebolt, K. Reckhow, C. Green, andR Haney. 2006. Compilation of measured nutrient load data for agricultural land uses in the United States.Journal of the American Water Resources Association 42:1163–1178.CrossRefGoogle Scholar
  40. Harrison, P. J., M. H. Hu, Y. P. Yang, andX. Lu. 1990. Phosphate limitation in estuarine and coastal waters of China.Journal of Experimental Marine Biology Ecology 140:79–87.CrossRefGoogle Scholar
  41. Hauxwell, J., J. Cebrian, andI. Valiela. 2003. Eelgrass(Zostera marina) loss in temperate estuaries: Relationships to land-derived nitrogen loads and effect of light limitation imposed by algae.Marine Ecological Progress Series 247:59–73.CrossRefGoogle Scholar
  42. Huang, X. P., L. M. Huang, andW. Z. Yue. 2003. The characteristics of nutrients and eutrophication in the Pearl River estuary, South China.Marine Pollution Bulletin 47: 30–36.CrossRefGoogle Scholar
  43. Huo, W. Y., Z. M. Yu, J. Z. Zou, X. X. Song, andJ. H. Hao. 2001. Outbreak ofSkeletonema costatum red tide and its relations to environmental factors in Jiaozhou Bay.Ocenologia et Limnologia Sinica 32:311–318.Google Scholar
  44. Johnes, P. J. 1996. Evaluation and management of the impact of land use on the nitrogen and phosphorus load delivered to surface waters: The export coefficient modelling approach.Journal of Hydrology 183:323–349.CrossRefGoogle Scholar
  45. Johnes, P. J. andA. L. Heathwaite. 1997. Modeling the impact of land use change on water quality in agricultural catchments.Hydrological Processes 11:269–286.CrossRefGoogle Scholar
  46. Kompare, B., I. Bratko, F. Steinman, andS. Dzeroski. 1994. Using machine learning techniques in the construction of models I. Introduction.Ecological Modelling 75:617–628.CrossRefGoogle Scholar
  47. Kung, H., L. Ying, andY C. Liu. 1992. A complementary tool to water quality index: Fuzzy clustering analysis.Water Resources Bulletin 28:525–534.Google Scholar
  48. Li, D. andD. Daler. 2004. Ocean pollution from land-based sources: East China Sea, China.Ambio 33:107–112.CrossRefGoogle Scholar
  49. Li, D., J. Zhang, D. Huang, Y .WU, andJ. Liang. 2002. Oxygen depletion off the Changjiang (Yangtze River) Estuary.Science in China 45:1137–1146.Google Scholar
  50. Li, C. L., F. Zhang, X. Shen, B. Yang, Z. L. Shen, andS. Sun. 2005. Concentration, distribution and annual fluctuation of chlorophyll-a in the Jiaozhou Bay.Oceanologia et Limnologia Sinica 36: 499–506.Google Scholar
  51. Lin, R. 1996. Review of assessing methods for coastal eutrophication.Marine Environmental Science 15:28–31.Google Scholar
  52. Lin, X., C. Huang, F. Lin, andX. Chen. 2004. Principal component-cluster analysis method for the assessment of seawater eutrophication.Mathematics in Practice and Theory 34: 69–74.Google Scholar
  53. Lindahl, O., R. Hart, B. Hernroth, S. Kollberg, L. Loo, L. Olrog, A. Rehnstam-Holm, J. Svensson, S. Svensson, andU. Syversen. 2005. Improving marine water quality by mussel farming: A profitable solution for Swedish society.Ambio 34: 131–138.CrossRefGoogle Scholar
  54. Line, D. E., N. M. White, D. L. Osmond, G. D. Jennings, andC. B. Mojonnier. 2002. Pollutant export from various land uses in the Upper Neuse River Basin.Water Environment Research 74: 100–108.CrossRefGoogle Scholar
  55. Liu, Z., H. Wei, G. Liu, andJ. Zhang. 2004. Simulation of water exchange in Jiaozhou Bay by average residence time approach.Estuarine, Coastal and Shelf Science 61:25–35.CrossRefGoogle Scholar
  56. Lu, R. S. andS. L. Lo. 2002. Diagnosing reservoir water quality using self-organizing maps and fuzzy theory.Water Research 36: 2265–2274.CrossRefGoogle Scholar
  57. Marchini, A. andC. Marchini. 2006. A fuzzy logic model to recognise ecological sectors in the lagoon of Venice based on the benthic community.Ecological Modelling 193:105–118.CrossRefGoogle Scholar
  58. Mattikalli, N. M. andK. S. Richards. 1996. Estimation of surface water quality changes in response to land use change: Application of the export coefficient model using Remote Sensing and Geographic Information System.Journal of Environmental Management 48:263–282.CrossRefGoogle Scholar
  59. May, C. L., J. R. Koseff, L. V. Lucas, J. E. Cloern, andD. H. Schoellhamer. 2003. Effects of spatial and temporal variability of turbidity on phytoplankton blooms.Marine Ecological Progress Series 254:111–128.CrossRefGoogle Scholar
  60. Metternicht, G. 2001. Assessing temporal and spatial changes of salinity using fuzzy logic, remote sensing and GIS. Foundations of an expert system.Ecological Modelling 144:163–179.CrossRefGoogle Scholar
  61. Mississippi River / Gulf of Mexico Watershed Nutrient Task Force. 2001. Action Plan for Reducing, Mitigating, and Controlling Hypoxia in the Northern Gulf of Mexico. Mississippi River / Gulf of Mexico Watershed Nutrient Task Force, Washington, D.C.Google Scholar
  62. Morihiro, A., A. Outoski, T. Kawai, M. Hosome, andK. Muraoka. 1981. Application of modified Carlson’s trophic state index to Japanese lakes and its relationship to other parameters related to trophic state.Research Report of National Institute of Environmental Studies 23:12–30.Google Scholar
  63. Muttiah, R. S. andR A. Wurbs. 2002. Scale-dependent soil and climate variability effects on watershed water balance of the SWAT model.Hydrological Processes 256:264–285.Google Scholar
  64. Neitsch, S. L., J. C. Arnold, J. R Kiniry, andJ. R. Williams. 2002. Soil and Water Assessment Tool User’s Manual: Version 2000. Blackland Research Center, Texas Agricultural Experiment Station, Temple, Texas.Google Scholar
  65. Nunes, J. P., J. G. Ferreira, F. Gazeau, J. Lencart-Silva, X. L. Zhang, M. Y. Zhu, andJ. G. Fang. 2003. A model for sustainable management of shellfish polyculture in coastal bays.Aquaculture 219:257–277.CrossRefGoogle Scholar
  66. Okaichi, T. 2004. Red Tides. Terra Scientific Publishing Company, Tokyo, Japan.Google Scholar
  67. OSPAR Commission. 2003. OSPAR Integrated Report 2003 on the Eutrophication Status of the OSPAR Maritime Area Based Upon the First Application of the Comprehensive Procedure. OSPAR Commission, London, U.K. http://www.ospar.org/documents/ dbase/publications/p00189_Eutrophication%20Status%20Report %202003.pdf.Google Scholar
  68. Parinet, B., A. Lhote, andB. Legube. 2004. Principal component analysis: An appropriate tool for water quality evaluation and management—application to a tropical lake system.Ecological Modelling 178:295–311.CrossRefGoogle Scholar
  69. Pei, H. andJ. Ma. 2002. Study on the algal dynamic model for West Lake, Hangzhou.Ecological Modelling 148:67–77.CrossRefGoogle Scholar
  70. Peng, Y. H. andZ. D. Wang. 1991. Assessment of the eutrophication level in the estuary of Zhujiang River.Marine Environmental Science 10:7–13.Google Scholar
  71. P.R.C. National Bureau of Statistics. 2001. Major Figures on 2000 Population Census of China. China Statistics Press, Beijing, China.Google Scholar
  72. P.R.C. State Oceanic Administration. 2007. The Official Gazettes of Environment Quality of China Sea in 2006. http:// www.soa.gov.cnGoogle Scholar
  73. Rabalais, N. N., R E. Turner, andD. Scavia. 2002. Beyond science into policy: Gulf of Mexico hypoxia and the Mississippi River.Bioscience 52:129–142.CrossRefGoogle Scholar
  74. Reckhow, K. H., M. N. Beaulac, andJ. T. Simpson. 1980. Modeling Phosphorus Loading and Lake Response under Uncertainty: A Manual and Compilation of Export Coefficients. Michigan State University, East Lansing, Michigan.Google Scholar
  75. Reckhow, K. H. andJ. T. Simpson. 1980. A procedure using modelling and error analysis for the prediction of lake phosphorous concentration from land use information.Canadian Journal of Fisheries and Aquatic Science 37:1439–1448.CrossRefGoogle Scholar
  76. Salski, A. 1992. Fuzzy knowledge-based models in ecological research.Ecological Modelling 63:103–112.CrossRefGoogle Scholar
  77. Santhi, C., R. Srinivasan, J. G. Arnold, andJ. R. Williams. 2006. A modeling approach to evaluate the impacts of water quality management plans implemented in a watershed in Texas.Environmental Modelling and Software 21:1131–1157.Google Scholar
  78. Scavia, D. andS. B. Bricker. 2006. Coastal eutrophication assessment in the United States.Biogeochemistry 79:187–208.CrossRefGoogle Scholar
  79. SCIRUS. 2007. Scientific Research Website. Amsterdam, The Netherlands. http://www.scirus.com/Google Scholar
  80. Shastri, Y. andU. Diwekar. 2006. Sustainable ecosystem management using optimal control theory: Part 1 (deterministic systems).Journal of Theoretical Biology 241:506–521.CrossRefGoogle Scholar
  81. Shen, Z. L. 2001. Historical changes in nutrient structure and its influences on phytoplankton composition in Jiaozhou Bay.Estuarine, Coastal and Shelf Science 52:211–224.CrossRefGoogle Scholar
  82. Shen, Z. L., Q. Liu, Y. L. Wu, andY Yao. 2006. Nutrient structure of seawater and ecological responses in Jiaozhou Bay, China.Estuarine, Coastal and Shelf Science 69:299–307.CrossRefGoogle Scholar
  83. Stevenson, J. C., L. W. Staver, andK. W. Staver. 1993. Water quality associated with survival of submersed aquatic vegetation along an estuarine gradient.Estuaries 16:346–361.CrossRefGoogle Scholar
  84. Strain, P. M. andP. A. Yeats. 1999. The relationships between chemical measures and potential predictors of the eutrophication status of inlets.Marine Pollution Bulletin 38: 1163–1170.CrossRefGoogle Scholar
  85. Tett, P., L. Gilpin, H. Svendsen, C. P. Erlandsson, U. Larsson, S. Kratzer, E. Fouilland, C. Janzen, J. Lee, C. Grenz, A. Newton, J. G. Ferreira, T. Fernandes, andS. Scory. 2003. Eutrophication and some European waters of restricted exchange.Continental Shelf Research 23:1635–1671.CrossRefGoogle Scholar
  86. Tett, P., R. Gowen, D. Mills, T. Fernandes, L. Gilpin, M. Huxham, K. Kennington, P. Read, M. Service, M. Wilkinson, andS. Malcolm. 2007. Defining and detecting undesirable disturbance in the context of marine eutrophication.Marine Pollution Bulletin 55:282–297.CrossRefGoogle Scholar
  87. Tomasko, D. A., D. L. Bristol, andJ. A. Ott. 2001. Assessment of present and future nitrogen loads, water quality, and seagrass (Thalassia testudinum) depth distribution in Lemon Bay, Florida.Estuaries 24:926–938.CrossRefGoogle Scholar
  88. Turner, R. E., N. N. Rabalais, andD. Justic. 2006. Predicting summer hypoxia in the northern Gulf of Mexico: Riverine N, P and Si loading.Marine Pollution Bulletin 52:139–148.CrossRefGoogle Scholar
  89. U.S. Environmental Protection Agency (USEPA). 2005. National Coastal Condition Report II. USEPA, Washington, D.C.Google Scholar
  90. Venohr, M., H. Behrendt, andW. Kluge. 2005. The effects of different input data and their spatial resolution on the results obtained from a conceptual nutrient emissions model: The River Stör case study.Hydrological Processes 19: 3501–3515.CrossRefGoogle Scholar
  91. Vollenweider, R A. 1968. The scientific basis for lake and stream eutrophication with particular reference to phosphorus and nitrogen as eutrophication factors. Technical Report DAS/ DS1/68.27, Organization for Economic Co-operation and Development, Paris, France.Google Scholar
  92. Vollenweider, R A. 1975. Input-output models with special reference to the phosphorus loading concept in limnology.Schweizerische Zeitschrift fur Hydrologie 37:53–84.CrossRefGoogle Scholar
  93. Wade, A. J., C. Neal, P. G. Whitehead, andN. J. Flynn. 2005. Modelling nitrogen fluxes from the land to the coastal zone in European systems: A perspective from the INCA project.Journal of Hydrology 304:413–429.CrossRefGoogle Scholar
  94. Wade, A. J., P. G. Whitehead, H. P. Jarvie, C. Neal, H. Prior, andP. J. Johnes. 2004. Nutrient monitoring, simulation and management within a major lowland UK river system: The Kennet.Mathematics and Computers in Simulation 64:307–317.CrossRefGoogle Scholar
  95. Wang, B. D. 2005b. Eutrophication assessment models for estuarine and coastal waters.Advances in Marine Science 23:82–86.Google Scholar
  96. Wang, B. 2006. Cultural eutrophication in the Changjiang (Yangtze River) plume: History and perspective.Estuarine, Coastal and Shelf Science 69:471–477.CrossRefGoogle Scholar
  97. Wang, X. L., K Q. Li, andX. Y Shi. 2006. The Marine Environmental Carrying Capacity of Major Pollutants in Jiaozhou Bay. Science Press, Beijing, China.Google Scholar
  98. Wazniak, C. E. andP. M. Glibert. 2004. Potential impacts of brown tide,Aureococcus anophagefferens, on juvenile hard clams,Mercenaria mercenaria, in the coastal bays of Maryland, USA.Harmful Algae 3:321–329.CrossRefGoogle Scholar
  99. Whitall, D., S. B. Bricker, J. G. Ferreira, A. M. Nobre, T. Simas, andM. C. Silva. 2007. Assessment of Eutrophication in Estuaries: Pressure-State-Response and Nitrogen Source Apportionment.Environmental Management 40:678–690.CrossRefGoogle Scholar
  100. Worrall, F. andT. P. Burt. 1999. The impact of land-use change on water quality at the catchment scale: The use of export coefficient and structural models.Journal of Hydrology 221:75–90.CrossRefGoogle Scholar
  101. Xiong, D. Q. andS. Y Chen. 1993. Theoretical fuzzy model for the eutrophication assessment in seawater.Marine Environmental Science 12:104–110.Google Scholar
  102. Yan, T., M. J. Zhou, and J. Z. Zou. 2002. National Report of HABs in China. www.pices.int/publications/scientific_reports/Report23/ HAB_China.pdfGoogle Scholar
  103. Yao, Y. andZ. Shen. 2005. A review on eutrophication research of coastal waters.Marine Sciences (in Chinese) 29:53–57.Google Scholar
  104. Zhang, J., Z. G. Yu, J. T. Wang, J. L. Ren, H. T. Chen, H. Xiong, L. X. Dong, andW. Y .Xu. 1999a. The subtropical Zhujiang (Pearl River) estuary: Nutrient, trace species and their relationship to photosynthesis.Estuarine, Coastal and Shelf Science 49:385–400.CrossRefGoogle Scholar
  105. Zhang, J., Z. F. Zhang, S. M. Liu, Y. Wu, H. Xiong, andH. T. Chen. 1999b. Human impacts on the large world rivers: Would the Changjiang (Yangtze River) be an illustration?Global Biogeochemical Cycles 13:1099–1105.CrossRefGoogle Scholar
  106. Zhou, Y., H. Yang, H. Hu, Y. Liu, Y. Mao, H. Zhou, X. Xu, andF. Zhang. 2006. Bioremediation potential of the macroalgaGracilaria lemaneiformis (Rhodophyta) integrated into fed fish culture in coastal waters of north China.Aquaculture 252:264–276.CrossRefGoogle Scholar
  107. Zhou, W., X. Yuan, W. Huo, andK. Yin. 2004. Distribution of chlorophylla and primary productivity in the adjacent sea area of Changjiang River Estuary.Acta Oceanologica Sinica 26:143–150.Google Scholar
  108. Zou, J., L. Dong, andB. Qin. 1985. Preliminary studies on eutrophication and red tide problems in Bohai Bay.Hydro-biologia 127:27–30.Google Scholar

Source of Unpublished Materials

  1. Hawkins, A. J. S. personal communication. Plymouth Marine Laboratory, The Hoe, Plymouth PL1 3DH, Devon, U.K.Google Scholar

Copyright information

© Estuarine Research Federation 2007

Authors and Affiliations

  • Yongjin Xiao
    • 1
  • João G. Ferreira
    • 1
  • Suzanne B. Bricker
    • 2
  • João P. Nunes
    • 1
  • Mingyuan Zhu
    • 3
  • Xuelei Zhang
    • 3
  1. 1.Center for Ocean and Environment, Departmento Ciências e Eng. Ambiente, Fac. Ciências e TecnologiaIMAR-Institute of Marine ResearchQta TorreMonte de Caparica, Portugal
  2. 2.National Ocean Service, National Center for Coastal Ocean ScienceNational Oceanic and Atmospheric AdministrationSilver Spring
  3. 3.Research Center for Marine Ecology, First Institute of OceanographyState Oceanic AdministrationQingdaoChina

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