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  • Ahn, C.-Y., A.-S. Chung, and H.-M. Oh (2002), Rainfall, phycocyanin, and N:P ratios related to cyanobacterial blooms in a Korean large reservoir, Hydrobiologia, 474(1–3), 117124.
  • Ahn, C.-Y., H.-M. Oh, and Y.-S. Park (2011), Evaluation of environmental factors on cyanobacteria bloom in eutrophic reservoir using artificial neural networks, J. Phycol., 47(3), 495504.
  • An, K.-G., and J. R. Jones (2000a), Factors regulating bluegreen dominance in a reservoir directly influenced by the Asian monsoon, Hydrobiologia, 432, 3748.
  • An, K.-G., and J. R. Jones (2000b), Temporal and spatial patterns in salinity and suspended solids in a reservoir influenced by the Asian monsoon, Hydrobiologia, 436(1–3), 179189.
  • Beaulieu, M., F. Pick, and I. Gregory-Eaves (2013), Nutrients and water temperature are significant predictors of cyanobacterial biomass in a 1147 lakes data set, Limnol. Oceanogr., 58(5), 17361746.
  • Brookes, J. D., and C. C. Carey (2011), Resilience to blooms, Science, 334(6052), 4647.
  • Carey, C. C., B. W. Ibelings, E. P. Hoffmann, D. P. Hamilton, and J. D. Brookes (2012), Eco-physiological adaptations that favour freshwater cyanobacteria in a changing climate, Water Res., 46(5), 13941407.
  • Carmichael, W. W., S. Azevedo, J. S. An, R. J. R. Molica, E. M. Jochimsen, S. Lau, K. L. Rinehart, G. R. Shaw, and G. K. Eaglesham (2001), Human fatalities from cyanobacteria: Chemical and biological evidence for cyanotoxins, Environ. Health Perspect., 109(7), 663668.
  • Carpenter, S. R., N. F. Caraco, D. L. Correll, R. W. Howarth, A. N. Sharpley, and V. H. Smith (1998), Nonpoint pollution of surface waters with phosphorus and nitrogen, Ecol. Appl., 8(3), 559568.
  • Codd, G. A., L. F. Morrison, and J. S. Metcalf (2005), Cyanobacterial toxins: Risk management for health protection, Toxicol. Appl. Pharmacol., 203, 264272.
  • Davis, T. W., D. L. Berry, G. L. Boyer, and C. J. Gobler (2009), The effects of temperature and nutrients on the growth and dynamics of toxic and non-toxic strains of Microcystis during cyanobacteria blooms, Harmful Algae, 8(5), 715725.
  • Downing, J. A., S. B. Watson, and E. McCauley (2001), Predicting cyanobacteria dominance in lakes, Can. J. Fish. Aquat. Sci., 58(10), 19051908.
  • Dyble, J., G. L. Fahnenstiel, R. W. Litaker, D. F. Millie, and P. A. Tester (2008), Microcystin concentrations and genetic diversity of Microcystis in the lower Great Lakes, Environ. Toxicol., 23(4), 507516.
  • Elliott, J. A. (2010), The seasonal sensitivity of cyanobacteria and other phytoplankton to changes in flushing rate and water temperature, Global Change Biol., 16(2), 864876.
  • Elliott, J. A. (2012), Is the future blue-green? A review of the current model predictions of how climate change could affect pelagic freshwater cyanobacteria, Water Res., 46(5), 13641371.
  • Freeman, K. S. (2011), Forecasts aid HABs response, Environ. Health Perspect., 119(12), a510.
  • Ghosh, S. K., P. Mukhopadhyay, and J.-C. Lu (2006), Bayesian analysis of zero-inflated regression models, J. Stat. Plann. Inference, 136(4), 13601375.
  • Glibert, P. M., J. Allen, A. Bouwman, C. W. Brown, K. J. Flynn, A. J. Lewitus, and C. J. Madden (2010), Modeling of HABs and eutrophication: Status, advances, challenges, J. Mar. Syst., 83(3), 262275.
  • Graham, J. L., J. R. Jones, S. B. Jones, J. A. Downing, and T. E. Clevenger (2004), Environmental factors influencing microcystin distribution and concentration in the Midwestern United States, Water Res., 38(20), 43954404.
  • Hamilton, G., R. McVinish, and K. Mengersen (2009), Bayesian model averaging for harmful algal bloom prediction, Ecol. Appl., 19(7), 18051814.
  • Heilbron, D. C. (1994), Zero-altered and other regression models for count data with added zeros, Biometrical. J., 36(5), 531547.
  • Hu, M.-C., M. Pavlicova, and E. V. Nunes (2011), Zero-inflated and hurdle models of count data with extra zeros: Examples from an HIV-risk reduction intervention trial, Am. J. Drug Alcohol Abuse, 37(5), 367375.
  • Jöhnk, K. D., J. E. F. Huisman, J. Sharples, B. E. N. Sommeijer, P. M. Visser, and J. M. Stroom (2008), Summer heatwaves promote blooms of harmful cyanobacteria, Global Change Biol., 14(3), 495512.
  • Jones, I. A. N., G. George, and C. Reynolds (2005), Quantifying effects of phytoplankton on the heat budgets of two large limnetic enclosures, Freshwater Biol., 50(7), 12391247.
  • Jung, Y. (2009), Management plan for the control of eutrophication in Lake Paldang, South Korea, Policy Res. Rep. 2009-43, Gyeonggi Res. Inst., Suwon, South Korea.
  • Kim, J., M.-S. Han, W. Jheong, and J. Park (2005), Correlation between phytoplankton dynamics and water quality in Paldang Reservoir, Korean J. Limnol., 38(2), 217224.
  • Kim, J., S. Lee, H. Bang, and S. Hwang (2009), Characteristics of algae occurrence in Lake Paldang, J. Korean Soc. Environ. Eng., 31(5), 325331.
  • Knoll, L. B., O. Sarnelle, S. K. Hamilton, C. E. H. Kissman, A. E. Wilson, J. B. Rose, and M. R. Morgan (2008), Invasive zebra mussels (Dreissena polymorpha) increase cyanobacterial toxin concentrations in low-nutrient lakes, Can. J. Fish. Aquat. Sci., 65(3), 448455.
  • Komárek, J. (1991), A review of water-bloom forming Microcystis species, with regard to populations from Japan, Algol. Stud./Archiv für Hydrobiologie, 64, 115127.
  • Kosten, S., et al. (2012), Warmer climates boost cyanobacterial dominance in shallow lakes, Global Change Biol., 18(1), 118126.
  • Lambert, D. (1992), Zero-inflated Poisson regression, with an application to defects in manufacturing, Technometrics, 34(1), 114.
  • Levine, S. N., and D. W. Schindler (1999), Influence of nitrogen to phosphorus supply ratios and physicochemical conditions on cyanobacteria and phytoplankton species composition in the Experimental Lakes Area, Canada, Can. J. Fish. Aquat. Sci., 56(3), 451466.
  • Lunn, D. J., A. Thomas, N. Best, and D. Spiegelhalter (2000), WinBUS—A Bayesian modelling framework: Concepts, structure, and extensibility G, Stat. Comput., 10, 325337.
  • Lürling, M., F. Eshetu, E. J. Faassen, S. Kosten, and V. L. M. Huszar (2013), Comparison of cyanobacterial and green algal growth rates at different temperatures, Freshwater Biol., 58(3), 552559.
  • Markensten, H., K. Moore, and I. Persson (2010), Simulated lake phytoplankton composition shifts toward cyanobacteria dominance in a future warmer climate, Ecol. Appl., 20(3), 752767.
  • Martin, T. G., B. A. Wintle, J. R. Rhodes, P. M. Kuhnert, S. A. Field, S. J. Low-Choy, A. J. Tyre, and H. P. Possingham (2005), Zero tolerance ecology: improving ecological inference by modelling the source of zero observations, Ecol. Lett., 8(11), 12351246.
  • McQueen, D. J., and D. R. S. Lean (1987), Influence of water temperature and nitrogen to phosphorus ratios on the dominance of blue-green algae in Lake St. George, Ontario, Can. J. Fish. Aquat. Sci., 44(3), 598604.
  • Michalak, A. M., et al. (2013), Record-setting algal bloom in Lake Erie caused by agricultural and meteorological trends consistent with expected future conditions, Proc. Natl. Acad. Sci. U. S. A., 110(16), 64486452.
  • Millie, D. F., G. R. Weckman, W. A. Young II, J. E. Ivey, H. J. Carrick, and G. L. Fahnenstiel (2012), Modeling microalgal abundance with artificial neural networks: Demonstration of a heuristic ‘Grey-Box’ to deconvolve and quantify environmental influences, Environ. Modell. Software, 38, 2739.
  • Millie, D. F., G. R. Weckman, W. A. Young II, J. E. Ivey, D. P. Fries, E. Ardjmand, and G. L. Fahnenstiel (2013), Coastal ‘Big Data’ and nature-inspired computation: Prediction potentials, uncertainties, and knowledge derivation of neural networks for an algal metric, Estuarine Coastal Shelf Sci., 125, 5767.
  • Mitrovic, S. M., B. C. Chessman, L. C. Bowling, and R. H. Cooke (2006), Modelling suppression of cyanobacterial blooms by flow management in a lowland river, River Res. Appl., 22(1), 109114.
  • Mullahy, J. (1986), Specification and testing of some modified count data models, J. Econometrics, 33(3), 341365.
  • Na, E. H., and S. S. Park (2005), A hydrodynamic modeling study to determine the optimum water intake location in Lake Paldang, Korea, J. Am. Water Resour. Assoc., 41(6), 13151332.
  • Na, E. H., and S. S. Park (2006), A hydrodynamic and water quality modeling study for spatial and temporal patterns of phytoplankton growth in a stratified lake with buoyant incoming flow, Ecol. Modell., 199, 298314.
  • Neelon, B. H., A. J. O'Malley, and S.-L. T. Normand (2010), A Bayesian model for repeated measures zero-inflated count data with application to outpatient psychiatric service use, Stat. Modell., 10(4), 421439.
  • Neelon, B. H., P. Ghosh, and P. F. Loebs (2013), A spatial Poisson hurdle model for exploring geographic variation in emergency department visits, J. R. Stat. Soc.: Ser. A, 176(2), 389413.
  • O'Brien, K. R., D. L. Meyer, A. M. Waite, G. N. Ivey, and D. P. Hamilton (2004), Disaggregation of Microcystis aeruginosa colonies under turbulent mixing: Laboratory experiments in a grid-stirred tank, Hydrobiologia, 519(1–3), 143152.
  • Paerl, H. W. (1988), Nuisance phytoplankton blooms in coastal, estuarine, and inland waters, Limnol. Oceanogr., 33(4), 823847.
  • Paerl, H. W., and J. Huisman (2008), Blooms like it hot, Science, 320(5872), 5758.
  • Paerl, H. W., and J. T. Scott (2010), Throwing fuel on the fire: Synergistic effects of excessive nitrogen inputs and global warming on harmful algal blooms, Environ. Sci. Technol., 44(20), 77567758.
  • Paerl, H. W., and V. J. Paul (2012), Climate change: Links to global expansion of harmful cyanobacteria, Water Res., 46(5), 13491363.
  • Paerl, H. W., N. S. Hall, and E. S. Calandrino (2011a), Controlling harmful cyanobacterial blooms in a world experiencing anthropogenic and climatic-induced change, Sci. Total Environ., 409(10), 17391745.
  • Paerl, H. W., H. Xu, M. J. McCarthy, G. Zhu, B. Qin, Y. Li, and W. S. Gardner (2011b), Controlling harmful cyanobacterial blooms in a hyper-eutrophic lake (Lake Taihu, China): The need for a dual nutrient (N & P) management strategy, Water Res., 45(5), 19731983.
  • Park, H.-K., H.-J. Lee, E.-K. Kim, and D.-I. Jung (2005), Characteristics of algal abundance and statistical analysis of environmental factors in Lake Paldang, Korean Soc. Water Qual., 21(6), 584594.
  • Phillips, G., A. Kelly, J.-A. Pitt, R. Sanderson, and E. Taylor (2005), The recovery of a very shallow eutrophic lake, 20 years after the control of effluent derived phosphorus, Freshwater Biol., 50(10), 16281638.
  • Plummer, M. (2008), Penalized loss functions for Bayesian model comparison, Biostatistics, 9(3), 523539.
  • R Development Core Team (2012), R: A Language and Environment for Statistical Computing, R Found. for Stat. Comput., Vienna.
  • Reckhow, K. H., and S. C. Chapra (1983), Engineering Approaches for Lake Management, Volume 1: Data Analysis and Empirical Modeling, Butterworths, Boston, Mass.
  • Reynolds, C. S. (2006), Ecology of Phytoplankton, Cambridge Univ. Press, Cambridge, U. K.
  • Romo, S., J. Soria, F. FernÁNdez, Y. Ouahid, and Á. BarÓN-SolÁ (2013), Water residence time and the dynamics of toxic cyanobacteria, Freshwater Biol., 58(3), 513522.
  • Scheffer, M., S. Rinaldi, A. Gragnani, L. R. Mur, and E. H. v. Nes (1997), On the dominance of filamentous cyanobacteria in shallow, turbid Lakes, Ecology, 78(1), 272282.
  • Serizawa, H., T. Amemiya, A. Rossberg, and K. Itoh (2008), Computer simulations of seasonal outbreak and diurnal vertical migration of cyanobacteria, Limnology, 9(3), 185194.
  • Smith, V. H. (1983), Low nitrogen to phosphorus ratios favor dominance by blue-green algae in lake phytoplankton, Science, 221(4611), 669671.
  • Smith, V. H. (1986), Light and nutrient effects on the relative biomass of blue-green algae in lake phytoplankton, Can. J. Fish. Aquat. Sci., 43(1), 148153.
  • Soranno, P. A. (1997), Factors affecting the timing of surface scums and epilimnetic blooms of blue-green algae in a eutrophic lake, Can. J. Fish. Aquat. Sci., 54, 19651975.
  • Stumpf, R. P., T. T. Wynne, D. B. Baker, and G. L. Fahnenstiel (2012), Interannual variability of cyanobacterial blooms in Lake Erie, PloS One, 7(8), e42444.
  • Vanderploeg, H. A., T. H. Johengen, and J. R. Liebig (2009), Feedback between zebra mussel selective feeding and algal composition affects mussel condition: Did the regime changer pay a price for its success?, Freshwater Biol., 54(1), 4763.
  • Visser, P., B. A. S. Ibelings, B. Van Der Veer, J. A. N. Koedood, and R. Mur (1996), Artificial mixing prevents nuisance blooms of the cyanobacterium Microcystis in Lake Nieuwe Meer, the Netherlands, Freshwater Biol., 36(2), 435450.
  • Visser, P. M., B. W. Ibelings, and L. R. Mur (1995), Autunmal sedimentation of Microcystis spp. as result of an increase in carbohydrate ballast at reduced temperature, J. Plankton Res., 17(5), 919933.
  • Wagner, C., and R. Adrian (2009), Cyanobacteria dominance: Quantifying the effects of climate change, Limnol. Oceanogr., 54(6), 24602468.
  • White, G. C., and R. E. Bennetts (1996), Analysis of frequency count data using the negative binomial distribution, Ecology, 77(8), 25492557.
  • Wood, S. A., M. J. Prentice, K. Smith, and D. P. Hamilton (2010), Low dissolved inorganic nitrogen and increased heterocyte frequency: Precursors to Anabaena planktonica blooms in a temperate, eutrophic reservoir, J. Plankton Res., 32(9), 13151325.
  • Wynne, T. T., R. P. Stumpf, M. C. Tomlinson, D. J. Schwab, G. Y. Watabayashi, and J. D. Christensen (2011), Estimating cyanobacterial bloom transport by coupling remotely sensed imagery and a hydrodynamic model, Ecol. Appl., 21(7), 27092721.
  • Wynne, T. T., R. P. Stumpf, and T. O. Briggs (2013), Comparing MODIS and MERIS spectral shapes for cyanobacterial bloom detection, Int. J. Remote Sens., 34, 66686678.
  • Zhang, H., W. Hu, K. Gu, Q. Li, D. Zheng, and S. Zhai (2013), An improved ecological model and software for short-term algal bloom forecasting, Environ. Modell. Software, 48, 152162.