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Comprehensive evaluation of the potential risk from cyanobacteria blooms in Poyang Lake based on nutrient zoning

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Abstract

The potential risk from cyanobacteria blooms is the basis for predicting, preventing, and managing eutrophication. Poyang Lake lies on the southern bank of the middle and lower reaches of the Yangtze River. This lake is a large shallow lake connected to the Yangtze River and is affected by monsoon. The comprehensive evaluation index system, evaluation model, and method of the potential risk from cyanobacteria blooms were constructed based on the nutrient zoning in Poyang Lake, and the potential risk from cyanobacteria blooms was evaluated in 2013. (1) The evaluation index system comprises physical, chemical, and biological indicators. The physical indicators consist of blocking degree, lake region location, transparency (Secchi disk depth, SD), and temperature; the chemical indicators consist of total nitrogen (TN) and total phosphorus (TP); and the biological indicators consist of chlorophyll a (Chla) and phytoplankton biomass. Among the indicators, blocking degree and lake region location along with the prevailing wind direction were selected to represent the indicators affected by water retention time and wind direction. (2) We established a comprehensive evaluation method for assessing the potential risk from cyanobacteria blooms by adopting both analytic hierarchy process weighting and a comprehensive evaluation method. (3) Results show that the high-risk periods for cyanobacteria blooms were August, July, and December, and the high-risk regions were in the Northeastern Lake Region, Western Lake Region and Northern Lake Region. The Northeastern Lake Region is particularly in high risk in August and July. These cyanobacteria blooms presented heavy risk or close to heavy risk. Based on the risk evaluation indicators, outbreaks of cyanobacteria blooms are limited by temperature and location. Chla and phytoplankton biomass were the key indices affecting the level of potential risk from cyanobacteria blooms during the high-water-level period (July and August). In contrast, TN and TP are the key indices affecting the level of harm during the low-water-level period. Within a year, Chla, phytoplankton biomass, and TP are key indicators for the prediction of cyanobacteria blooms in Poyang Lake.

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References

  • Ananda J, Herath G (2008) Multi-attribute preference modelling and regional land-use planning. Ecol Econ 65:325–335

    Article  Google Scholar 

  • Burford MA, Webster IT, Revill AT, Kenyon RA, Whittle M, Curwen G (2012) Controls on phytoplankton productivity in a wet–dry tropical estuary. Estuar Coast Shelf Sci 113:141–151

    Article  Google Scholar 

  • Chapman BR, Fery BW, Ford TW (1998) Phytoplankton communities in water bodies at Dungeness, UK: analysis of seasonal changes in response to environment factors. Hydrobiologia 362:161–170

    Article  Google Scholar 

  • Cracknell AP, Newcombe SK, Black AF, Kirby NE (2001) The ABDMAP (algal bloom detection, monitoring and prediction) concerted action. Int J Remote Sens 22(2–3):205–247

    Article  Google Scholar 

  • Dai GF, Zhang W, Peng NY, Lou Q, Zhong JY (2015) Study on distribution of N and P pollutants and risk of cyanobacteria Bloom in Poyang Lake and waters around the lake during drought periods. Ecol Environ Sci 24(5):838–844

    Google Scholar 

  • Duan HT, Zhang SX, Zhang YZ (2008) Cyanobacteria bloom monitoring with remote sensing in Lake Taihu. J Lake Sci 20(2):145–152

    Article  Google Scholar 

  • Gao L, Atakelty H (2012) Ranking management strategies with complex outcomes: an AHP-fuzzy evaluation of recreational fishing using an integrated agent-based model of coral reef ecosystem. Environ Model Softw 31:3–18

    Article  Google Scholar 

  • Gao YX, Zhang YC (2006) Influences of hydrometeorologic factor on algae bloom. Water Sci Eng Technol 2:10–13

    Google Scholar 

  • Hu W, Wu WY, Kong QX, Xun SP, Wang YL (2002) Research on estimating the concentrations of chlorophyll-a in Chaohu Lake using FY-1C/CAVHRR data. J Nanjing Inst Meteorol 25(1):124–128

    Google Scholar 

  • Hu WP, Sven EJ, Zhang FB (2006) A vertical-compressed three-dimensional ecological model in Lake Taihu, China. Ecol Model 190(3–4):367–398

    Article  Google Scholar 

  • Huang Y (2001) Water environment and pollution control of Taihu Lake. Science Press, Beijing

    Google Scholar 

  • Huang H, Wen JH, Si RJ, Yin ZE (2008) International natural disaster risk assessment program: overview II—Assessment methods. J Catastrophol 23:96–101

    Google Scholar 

  • Jiangxi Water Resources Department (2009) Jiangxi rivers and lakes encompassing. Yangtze River Press, Wuhan, pp 419–482

    Google Scholar 

  • Jin XC, Tu QY (1990) Rules of eutrophication investigation in lake. China Environmental Science Press, Beijing, pp 286–302

    Google Scholar 

  • Johnk KD, Huisman J, Sharples J, Sommeijer B, Visser PM, Stroom JM (2008) Summer heat waves promote blooms of harmful cyanobacteria. Glob Change Biol 14:495–512

    Article  Google Scholar 

  • Kong FX, Gao G (2005) Hypothes is on cyanobacteria bloom-forming mechanism in large shallow eutrophic lakes. Acta Ecol Sin 25:589–595

    Google Scholar 

  • Kong FX, Song LR (2011) Algal blooms process and its environmental characteristics. Science Press, Beijing, p 43

    Google Scholar 

  • Kong FX, Ma RH, Gao JF, Wu XD (2009) The theory and practice of prevention, forecast and warning on cyanobacteria bloom in Lake Taihu. J Lake Sci 21:314–328

    Article  Google Scholar 

  • Kordi M, Brandt SA (2012) Effects of increasing fuzziness on analytic hierarchy process for spatial multicriteria decision analysis. Comput Environ Urban Syst 36:43–53

    Article  Google Scholar 

  • Li YX, Rao BQ, Wang ZC, Qin HJ, Zhang L, Li DH (2012) Spatial-temporal distribution of phytoplankton in bloom-accumulation area in Lake Chaohu. Resources and environment in the Yangtz Basin 21(Z2):25–31

    Google Scholar 

  • Liu JT (2010) Study on the disaster of cyanobacteria bloom and it’s risk assessment in Taihu Lake. Nanjing Institute of Geography and Limnology Chinese Academy of Sciences, Nanjing, pp 1–2

    Google Scholar 

  • Liu JT, Yang YS, Jiang JH, Gao JF (2011a) Risk evaluation method of cyanobacteria bloom hazard in Taihu Lake. China Environ Sci 31:498–503

    Google Scholar 

  • Liu JT, Yang YS, Jiang JH, Gao JF (2011b) Comprehensive evaluation method of cyanobacteria bloom hazard in Lake Taihu. J Lake Sci 23:334–338

    Article  Google Scholar 

  • Liu JT, Zhong JY, Fu M, Wu T (2014) Study on the characteristics and impact of rural living area pollution in Poyang Lake Basin. Resour Environ Yangtze Basin 23:970–976

    Google Scholar 

  • Lorenzen CJ (1967) Determination of chlorophyll and pheo-pigments: spectrophotometric equations. Limnol Oceanogr 12:343–346

    Article  Google Scholar 

  • Ma RH, Dai JF (2005) Quantitative estimation of chlorophyll-a and total suspended matter concentration with Landsat ETM based on field spectral features of Lake Taihu. J Lake Sci 17(2):97–103

    Article  Google Scholar 

  • Ma RH, Kong WJ, Duan HT, Zhang SX (2009) Quantitative estimation of phycocyanin concentration using MODIS imagery during the period of cyanobacterial blooming in Taihu Lake. China Environ Sci 29:254–260

    Google Scholar 

  • Noges T, Noges P, Laugaste R (2003) Water level as the mediator between climate change and phytoplankton composition in a large shallow temperate lake. Hydrobiologia 506:257–263

    Article  Google Scholar 

  • Ochumba PBO, Kibaara DI (1989) Observations on blue-green algal blooms in the open waters of Lake Victoria, Kenya. Afr J Ecol 27(1):23–34

    Article  Google Scholar 

  • Organization for Economic Cooperation and Development (OECD) (1982) Eutrophication of water: monitoring, assessment and control. Organization for Economic Cooperative Development, Paris

    Google Scholar 

  • Paerl WH, Huisman J (2009) Climate change: a catalyst for global expansion of harmful cyanobacterial blooms. Environ Microbiol Rep 1:27–37

    Article  Google Scholar 

  • Qin BQ, Gao G, Zhu GW, Zhang YL, Song YZ, Tang XM, Xu H, Deng JM (2013) Lake eutrophication and its ecosystem response. Chin Sci Bull 58:855–864

    Google Scholar 

  • Razieh M, Jan W, Rodger T, Hamid M (2015) Comparison of Fuzzy-AHP and AHP in a spatial multi-criteria decision making model for urban land-use planning. Comput Environ Urban Syst 49:54–65

    Article  Google Scholar 

  • Reynolds CS (1984) The ecology of freshwater phytoplankton. Cambridge University Press, London

    Google Scholar 

  • Reynolds CS (1987) Cyanobacteria water blooms. In: Callow JA (ed) Advances in botanical research, vol 13. Academic Press, London, pp 67–143

    Google Scholar 

  • Reynolds CS (2006) Ecology of phytoplankton (ecology, biodiversity and conservation). Cambridge Univ. Press, Cambridge

    Book  Google Scholar 

  • Saaty TL, Vargas LG (2001) Models, methods, concepts and applications of the analytic hierarchy process. Springer, New York

    Book  Google Scholar 

  • Schindler DW (1977) Evolution of phosphorus limitation in lakes. Science 195:260–262

    Article  Google Scholar 

  • Shwetank A, Rajeev J, Mishra PK (2014) A Kano model, AHP and M-TOPSIS method-based technique for disassembly line balancing under fuzzy environment. Appl Soft Comput 25:519–529

    Article  Google Scholar 

  • Smith VH (1983) Low nitrogen to phosphorus ratio s favor dominance by blue green algae in lake phytoplankton. Science 221:669–671

    Article  Google Scholar 

  • Tang XM, Gao G, Chao JY, Wang XD, Zhu GW, Qin BQ (2010) Dynamics of organic-aggregate-associated bacterial communities and related environmental factors in Lake Taihu, a large eutrophic shallow lake in China. Limnol Oceanogr 55:469–480

    Article  Google Scholar 

  • Wan JB, Yan WW (2007) Evaluation methods application in and probing into eutrophication of Poyang Lake area. J Jiangxi Norm Univ (Nat Sci Ed) 31:210–214

    Google Scholar 

  • Wang J (2005) The ecological engineering of HAB: prevention, control and mitigation of harmful algal blooms. Electron J Biol 1(2):27–30

    Google Scholar 

  • Wang MW (2011) Research on factors, control and management system of cyanobacteria blooming in water source in Shanghai. East China Normal University, Shanghai

    Google Scholar 

  • Wang YB (2014) Study on the temporal and spatial distribution of algae in Poyang Lake. Hunan Agriculture University, Changsha

    Google Scholar 

  • Water Resources of Jiangxi Province (JXWR) (2000–2013) Jiang Xi water resources bulletin, Jiangxi

  • Wen SY, Zhao DL, Zhang FS, Ma XF, Yang F (2009) Risk assessment method of harmful algal bloom hazard. Journal of Natural Disasters 18:106–111

    Google Scholar 

  • Wu QL, Xie P, Yang LY, Gao G, Liu ZW, Pan G, Zhu BZ (2008) Ecological consequences of cynobacetrial blooms in lakes and their countermeasures. Adv Earth Sci 23:115–123

    Google Scholar 

  • Wu ZS, Cai YJ, Liu X, Xu CP, Chen YW, Zhang L (2013) Temporal and spatial variability of phytoplankton in Lake Poyang: the largest freshwater lake in China. J Great Lakes Res 39:476–483

    Article  Google Scholar 

  • Wu ZS, He H, Cai YJ, Zhang L, Chen YW (2014) Spatial distribution of chlorophyll a and its relationship with the environment during summer in Lake Poyang: a Yangtze-connected lake. Hydrobiologia 732:61–70

    Article  Google Scholar 

  • Xiong Y, Zeng GM, Chen GQ, Tang L, Wang KL, Huang DY (2007) Combining AHP with GIS in synthetic evaluation of eco-environment quality—A case study of Hunan Province, China. Ecol Model 209:97–109

    Article  Google Scholar 

  • Zhao XX (2013) The phytoplankton community dynamics and driving factors during bloom forming period in Taihu Lake, China. Anhui University, Hefei, pp 5–9

    Google Scholar 

Download references

Acknowledgements

Thanks are extended to Jiangxi Provincial Key Laboratory of Water Resources and Environment of Poyang Lake for providing the foundation for the experiment. We are also grateful to Wei Zhang for the samples and making the map. This study was financially supported by National Natural Science Foundation (Grants 51409133, 51369011) and Science and Technology Project of Jiangxi Province (Grants KT201605, KT201613, KT201510, KT201504, KT201503, KT201406).

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Correspondence to Shaowen Fang.

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Liu, J., Fang, S. Comprehensive evaluation of the potential risk from cyanobacteria blooms in Poyang Lake based on nutrient zoning. Environ Earth Sci 76, 342 (2017). https://doi.org/10.1007/s12665-017-6678-6

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