Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 169860, 8 pages
Research Article

Numerical Mesocosm Experimental Study on Harmful Algal Blooms of Two Algal Species in the East China Sea

Naval Architecture and Ocean Engineering R&D Center of Guangdong Province, South China University of Technology, Guangzhou 510640, China

Received 17 September 2014; Revised 9 December 2014; Accepted 11 December 2014

Academic Editor: Ming Zhao

Copyright © 2015 Liangsheng Zhu and Qing Wang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


From the results of algal culture and mesocosm experiments, a numerical mesocosm experiment is designed that accounts for the effect of the marine environment (sea currents, nutrient levels, and temperature) on the harmful algal bloom (HAB) processes of Skeletonema costatum and Prorocentrum donghaiense, two of the most frequent HAB-associated species in the East China Sea. Physical and ecological environment of the waters is simulated numerically by applying a hydrodynamic-ecological-one-way-coupled marine culture box model, which is semienclosed. The algal growth rate is digitalized by a temperature-factor-optimization Droop equation. A 90-mode-day numerical mesocosm experiment for the above two species is conducted. The species were found to alternately trigger algal blooms in the experimental waters, replicating the population succession phenomenon observed in the field and confirming that the two HAB species compete for nutrients. Deductively, the numerical result shows that both the Taiwan Warm Current and the eutrophication in the adjacent water of the Yangtze River Estuary contribute to the northward movement of algal concentration centers during HAB and also suggests that the lack of nutritious supplements in the open sea limits HAB occurrences in coastal waters.

1. Introduction

As a disaster phenomenon causing huge losses, harmful algal bloom (HAB) has significantly restricted coastal economic sustainable development in China and has become of great public and governmental concern [13]. Being characterized by seasonal and location-concentrated occurrence, HABs in certain sea areas frequently arise from only two or three causative species. In the East China Sea (ECS), Skeletonema costatum and Prorocentrum donghaiense appear to dominate HAB processes [4]. Primary ecophysiological characteristics have been described in culture experiments of both species. P. donghaiense belongs to a group of algae with specific nutritional needs, and its growth depends on the levels and ratios of nitrate and phosphate [5]. A high nitrogen to phosphorus ratio will significantly limit the multiplication of P. donghaiense [6, 7] and its particular phosphorus requirements ensure a long incubation period before P. donghaiense can bloom [8]. Nutrients exert a similarly large impact on the growth of S. costatum [9], as does light, temperature, salinity, and suspended matter [10, 11]. Compared with P. donghaiense, S. costatum has a better capacity for adapting to temperature changes and storing nutrients for later absorption [1214]. Culture experiments on the above-mentioned species confirm that both species enjoy a physiological advantage in an artificial ideal environment. Mesocosm experiments performed at specified marine locations provide a more realistic description of the algal growth characteristics and the interspecific competition mechanism in the nonideal environment. Field mesocosm experiments show that the temperature, salinity, nutrient concentrations, and light conditions in seawater exert varying degrees of impact on the growth of P. donghaiense and S. costatum, which to some extent reflects the competitive advantage of these red tide algae in different environments. Further mesocosm experiments [11, 15, 16], showing how seawater temperature, salinity, nutrient, light, and other field factors affect the growth of both species, essentially reveal a competitive advantage for either species under a particular marine condition. Clearly, most of the local marine environmental factors are inherently included in mesocosm experiments, from which more realistic conclusions can be drawn regarding the HAB mechanism. However, the single fixed locality of the experimental site, the limited mesocosm range, and the isolating nature of the device will largely restrict the impact of surrounding environment factors such as currents, nutrients, and temperature. Here, guided by the results of culture and mesocosm experiments [17, 18], a numerical mesocosm experiment on harmful algal blooms of two algal species in the ECS is conducted to account for multiple impacting factors on the process and dynamics of HAB. To achieve this, we apply a hydrodynamic-ecological coupled model combined with an improved algal growth model.

2. Scheme Design

A coupled hydrodynamical ecological model for regional shelf seas (COHERENS) [19] is used to construct the environmental background of this experiment.

The physical part, including seawater temperature, salinity, light, and current, is simulated by the physical module of COHERENS. This physical module is a baroclinic prognostic model [20] with complete forcing at sea surface and is governed by a general set of equations describing the momentum, the continuity, the thermohaline, and the density of the ambient seawater. The physical equations are discretized horizontally on a -grid and adopt the level 2.5 turbulence closure model (for details see [19]).

The biological module of COHERENS provides the ecological background in which organic carbon and nitrogen cycling is carried out within microplankton and detrital compartments, with associated changes in concentrations of dissolved nitrate, ammonium, and oxygen. The coupling between these two modules is rendered unidirectional by inputting the physical variable field calculations into the biological module for running the biochemical process and by outputting the distribution of each ecological state variable. In this one-way coupling mode, hydrodynamic conditions influence the distribution of ecological variables, while the ecosystem by no means affects the movement of sea water within or outside the mesocosm boundary. Such a semienclosed marine culture box mode is essentially equivalent to the marine environmental background of field mesocosm experiments.

The concentration of HAB algae added to the experimental waters is modeled by a general scalar convection-diffusion equation:where is the algal concentration (mmol m−3) and the algal source/sink process is considered as biomass variation caused by the algal net growth and grazing pressure. The algal growth is described by the Droop equation [21] modified by a temperature factor :where is the algal maximum growth rate, is the concentration of nutrient , and is the nutrient threshold required for algal growth. The temperature factor is parameterized by an improved form of the empirical formula specified in [22] as follows:where is an empirically determined coefficient, is the sea water temperature, and is the reference temperature. A simple nudging method [23] is introduced to configure the temperature and surface concentrations of nitrate, phosphate, and silicate in this numerical marine incubator. The default value of basal respiration rate for autotrophs is 0.05 day−1. It is a crucial assumption of this version of microplankton that the value of the heterotroph fraction does not change during a simulation and the default ratio of microheterotroph to microplankton carbon biomass is 0.3. A schematic of the numerical mesocosm experiment based on the above theory is shown in Figure 1.

Figure 1: Framework of the numerical mesocosm experiment.

To reduce the limitations on local conditions, the range of the numerical mesocosm experiment is extended from a specified locality to the Yangtze River Estuary and its adjacent waters (120°00′E–124°00′E, 27°00′N–30°45′N), where HABs occur frequently. The numerical resolution is set at in the horizontal and 11 sigma levels in the vertical. The bathymetry of the experimental region is shown in Figure 2.

Figure 2: Bathymetry (m) of the numerical experimental region.

The initial and open physical boundary conditions are obtained from baroclinic diagnostic simulations of a wider range of spring circulation encompassing the entire ESC, which is performed as described in [24], except that open boundary flux conditions are imposed on the spring in the COHERENS physical module [25]. The initial ecological variable fields are distributed according to a subset of chlorophyll data archived in the 2001 World Ocean Atlas [26]. Wind stress and surface fluxes of heat, salinity, and dissolved oxygen are input as sea surface forcing. A zero-flux condition is imposed on land boundary, but a certain amount of ecological exchange is allowed at the sea bottom. At the open boundary, a radiation condition is applied for horizontal currents and a zero gradient condition is chosen for scalar variables (for details see [19]). The latter is a feasible option given the lack of complete and continuous ecological survey data in the ESC, which also makes the values of each nutrient threshold and grazing pressure adjustable. The algal parameters are valued according to related research as follows: the maximum growth rate of P. donghaiense and S. costatum is separately 1.88 day−1 and 4.21 day−1 [17]; the reference temperature of P. donghaiense and S. costatum is separately 20°C and 17°C.

Over time, surface concentrations of nitrate, phosphate, and silicate are nudged towards their observed concentrations [27] during the process of HAB. The algal species cultured in this experiment are specified as S. costatum and P. donghaiense. From estimates of HAB sources [28] these two species are assumed initially to be located in the Zhejiang offshore area (121°30′E–123°00′E, 27°00′N–28°00′N), and the initial algal concentrations are distributed according to the tracking observations [29, 30]. The numerical mesocosm experimental period is set to 90 mode days.

3. Results and Discussion

Since the HAB in the ESC generally occurs in the coastal upper water column between 30 m and 60 m isobaths [31], the surface data alone from the mesocosm experimental results were used in the analysis. The physical fields were plotted at specified time intervals to view their dynamics throughout the experiment.

3.1. Currents

The surface currents plotted in Figure 3 indicate that the Kuroshio intrusion little affected the experimental region, while the southward Zhejiang coastal current (usually driven by northerly winds) gradually retreated northward, even tending directly towards north at late times. The Taiwan Warm Current, however, retained a northern flow throughout. The gradual strengthening of this flow over time was possibly the main reason for the northward migration of the HAB center.

Figure 3: Surface current fields in the experimental region (m/s).
3.2. Nutrients

Initially (Figure 4, Day 3), the specified high level of nutrient provided substantial sustenance for the blooming of numerically incubated S. costatum and P. donghaiense. More than half of the nutrients had been consumed within the first 37 days of the experiment, providing indirect evidence of an algal bloom, probably S. costatum one. Another algal bloom could be tracked by the nearly 50% reduction of nitrate and phosphate (but not silicate) during the next 48 days. Because P. donghaiense does not usually absorb silicate, this second bloom, with less nutrient consumption than the first, was assumed to be caused by P. donghaiense. By the final phase of the experiment, the phosphate concentration had descended to a very low level while the silicate concentration was raised, which suggests that the nudging approach had achieved moderate success.

Figure 4: Surface nutrient concentration (mmol/m3) of nitrate (a), phosphate (b), and silicate (c) in the experimental region.
3.3. Algal Concentration and Sea Surface Temperature

The initial concentration of S. costatum was set at twenty times that of P. donghaiense in accordance with previous analysis [29, 30], in which the concentration of P. donghaiense was apparently less than 0.1 mmol/m3 (Figure 5). The sea surface temperature (SST) on day 1 ranged from 13 to 17°C.

Figure 5: Surface concentrations (mmol/m3) of P. donghaiense and S. costatum algae and SST (°C) on day 1.

With a strong competition advantage in eutrophic waters, S. costatum reproduced at a high rate within the first few days of the experiment, culminating in a large-scale bloom on day 10 with maximum concentration exceeding 30 mmol/m3. The bloom center visibly moved northward, along the flow direction of the Taiwan Warm Current. Now the SST ranged from 15 to 19°C, consistent with the adaptive temperature range (15–25°C) of exponential growth in S. costatum [18]. Meanwhile, the surface concentration of P. donghaiense had remained below 0.1 mmol/m3, possibly because the SST was outside the adaptive temperature range of this organism.

The S. costatum bloom, which lasted for approximately 22 days, consumed a large quantity of nutrients in the experimental region. Eventually, the reduced nutrient levels could no longer sustain rapid S. costatum growth and, by day 33, the bloom had dissipated under the default pressures of respiration and grazing (Figure 6). However, P. donghaiense, with lower nutrient requirements than S. costatum, began to fill the depleted niche as the SST approached the P. donghaiense adaptive range (Figure 7).

Figure 6: Surface algal concentration (mmol/m3) of P. donghaiense and S. costatum algae and SST (°C) on day 10.
Figure 7: Surface algal concentration (mmol/m3) of P. donghaiense and S. costatum algae and SST (°C) on day 33.

When the SST had risen to between 19°C and 23°C inclusively (day 47), P. donghaiense bloomed within a wide-ranging area with maximum concentration exceeding 40 mmol/m3 (Figure 8). This was accompanied by an obvious northward migration of its bloom center. S. costatum declined rapidly in most areas, persisting at low levels solely around the Yangtze River Estuary, consistent with its strong dependence on nutrient availability.

Figure 8: Surface algal concentration (mmol/m3) of P. donghaiense and S. costatum algae and SST (°C) on day 47.

The P. donghaiense bloom was sustained for 40 days, fading away on day 88 to concentrations below 0.5 mmol/m3 in most areas (Figure 9). Multiplication of both algal species was not further increased by ascending concentration of silicate. The decay of the P. donghaiense bloom and the further reduction in S. costatum concentration were both influenced by the increasing SST, indicating that this numerical experiment is relatively sensitive to temperature.

Figure 9: Surface algal concentration (mmol/m3) of P. donghaiense and S. costatum algae and SST (°C) on day 88.

4. Conclusions and Discussion

4.1. Conclusions

Results from indoor culture [18] and field mesocosm experiments [17] show that S. costatum has a competitive advantage in a rich nutrient environment; it proliferates rapidly and thus blooms within a shorter period than its competitor. Conversely, P. donghaiense can survive in a low nutrient environment and maintains a long bloom period if sea temperature is favorable. The mechanism by which S. costatum and P. donghaiense compete was unveiled in the numerical mesocosm experiment. This experiment confirmed that both the Taiwan Warm Current and the eutrophication in the adjacent water of Yangtze River Estuary contribute to the northward moving of the HAB center and also suggested that the lack of nutrient supplement in the open sea limits HAB occurrences in coastal waters.

4.2. Discussion

By comparing the three types of experiment (Table 1), we note that some ecological parameters in the numerical mesocosm can be directly determined from the results of indoor culture and field mesocosm, which are represented in turn by those of the numerical experiment. The equivalency between them confirms that the parameters of bioexperiments, whether indoor or field, are the preconditions and the important bases of numerical ones.

Table 1: Comparison between indoor culture, field mesocosm, and numerical mesocosm.

Although the numerical mesocosm is less restricted by temporal and spatial constraints than physical systems, large calculation errors arise because of the incomplete understanding of marine ecological mechanisms and the uncertainty of ecological parameters. Consequently, the numerical experiment results cannot be quantitatively validated in this study. More accurate results of the numerical mesocosm experiment can be obtained only through a complete marine ecological investigation and a thorough understanding of the marine ecosystem.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.


This study was financially supported by National 973 Project “Key Physical Processes and Numerical Modeling of HAB in the Typical Eutrophication Seas,” Project no. 2010CB428704. The authors are grateful to the anonymous referee for careful checking of the details and for helpful comments that improved this paper.


  1. M. J. Zhou and M. Y. Zhu, “Progress of the project ‘ecology and oceanography of harmful algal blooms in China’,” Advances in Earth Science, vol. 21, no. 7, pp. 673–679, 2006. View at Google Scholar
  2. P. M. Glibert, “Harmful algal blooms in Asia: an insidious and escalating water pollution phenomenon with effects on ecological and human health,” ASIA Network Exchange, vol. 21, no. 1, pp. 52–68, 2014. View at Google Scholar
  3. H.-M. Li, H.-J. Tang, X.-Y. Shi, C.-S. Zhang, and X.-L. Wang, “Increased nutrient loads from the Changjiang (Yangtze) River have led to increased harmful algal blooms,” Harmful Algae, vol. 39, pp. 92–101, 2014. View at Publisher · View at Google Scholar
  4. D. Lu, Y. Qi, H. Gu et al., “Causative species of harmful algal blooms in Chinese coastal waters,” Algological Studies, vol. 145, no. 1, pp. 145–168, 2014. View at Publisher · View at Google Scholar
  5. J. H. Wang, H. J. Tang, X. L. Wang, and C. J. Zhu, “Effects of nitrate and phosphate on growth and nitrate reductase activity of Prorocentrum donghaiense,” Chinese Journal of Applied and Environmental Biology, vol. 14, no. 5, pp. 620–623, 2008. View at Publisher · View at Google Scholar · View at Scopus
  6. S. H. Lv and M. S. Ou, “Effects of different nitrogen sources and N/P ratios on the growth of a marine dinoflagellate Prorocentrum donghaiense,” Marine Environmental Science, vol. 25, no. 2, pp. 33–36, 2006. View at Google Scholar
  7. M. S. Ou and S. H. Lv, “Effects of different inorganic nitrogen sources on the growth of Prorocentrum donghaiense,” Ecologic Science, vol. 25, no. 1, pp. 28–31, 2006. View at Google Scholar
  8. Y. Li, S. H. Lv, N. Xu, and L. C. Xie, “The utilization of Prorocentrum donghaiense to four different types of phosphorus,” Ecologic Science, vol. 24, no. 4, pp. 314–317, 2005. View at Google Scholar
  9. Y. D. Liu, J. Sun, T. Z. Chen, and T. D. Wei, “Effect of N/P ratio on the growth of a red tide diatom Skeletonema costatum,” Transaction of Oceanology and Limnology, vol. 2, pp. 39–44, 2002. View at Google Scholar
  10. J. T. Li, W. H. Zhao, D. F. Yang, and J. T. Wang, “Effect of turbid water in Changjiang (Yangtze) estuary on the growth of Skeletonema costatum,” Marine Sciences, vol. 29, no. 1, pp. 34–37, 2005. View at Google Scholar
  11. B.-Y. Sun, S.-K. Liang, C.-Y. Wang, X.-B. Wang, X.-L. Wang, and Y.-B. Li, “Role of irradiance on the seasonality of Skeletonema costatum cleve blooms in the coastal area in East China Sea,” Environmental Science, vol. 29, no. 7, pp. 1849–1854, 2008. View at Google Scholar · View at Scopus
  12. B. Z. Chen, Z. L. Wang, M. Y. Zhu, and R. X. Li, “Effects of temperature and salinity on growth of Prorocentrum dentatum and comparisons between growths of Prorocentrum dentatum and Skeletonema costatum,” Advances in Marine Science, vol. 23, no. 1, pp. 60–64, 2005. View at Google Scholar
  13. S.-H. Lu and Y. Li, “Nutritional storage ability of four harmful algae from the east China sea,” The Chinese Journal of Process Engineering, vol. 6, no. 3, pp. 439–444, 2006. View at Google Scholar · View at Scopus
  14. Y. F. Zhao, Z. M. Yu, X. X. Song, and X. H. Cao, “Effects of different phosphorus substrates on the growth and phosphatase activity of Skeletonema costatum and Prorocentrum donghaiense,” Environmental Science, vol. 30, no. 3, pp. 693–699, 2009. View at Google Scholar · View at Scopus
  15. J. L. Hou, C. S. Zhang, X. Y. Shi, R. Lu, and X. L. Wang, “Effect on phosphate on two typical HAB species in East China Sea by mesocosm experiments,” Periodical of Ocean University of China, vol. 36, no. 3, pp. 163–169, 2006. View at Google Scholar
  16. B.-Y. Sun, X.-L. Wang, Y.-B. Li et al., “Effects of irradiance on blooms of the dinoflagellate Prorocentrum donghaiense Lu in the coastal area in East China Sea,” Environmental Science, vol. 29, no. 2, pp. 362–367, 2008. View at Google Scholar · View at Scopus
  17. R. X. Li, M. Y. Zhu, Z. L. Wang, X. Y. Shi, and B. Z. Chen, “Mesocosm experiment on competition between two HAB species in East China Sea,” Chinese Journal of Applied Ecology, vol. 14, no. 7, pp. 1049–1054, 2003. View at Google Scholar · View at Scopus
  18. Z. L. Wang, R. X. Li, M. Y. Zhu, B. Z. Chen, and Y. J. Hao, “Study on population growth processes and interspecific competition of Prorocentrum donghaiense and Skeletonema costatum in semi-continuous dilution experiments,” Advances in Marine Science, vol. 24, no. 4, pp. 495–503, 2006. View at Google Scholar
  19. P. Luyten J, J. Jones E, R. Proctor, A. Tabor, P. Tett, and K. Wild-Allen, “COHERENS—a coupled hydrodynamical-ecological model for regional and shelf seas: user documentation,” MUMM Report, Management Unit of the Mathematical Models of the North Sea, 1999. View at Google Scholar
  20. Q. Wang and L. Zhu, “Numerical simulation study on physical background information field of East China Sea with complete forcing at sea surface,” Journal of Information and Computational Science, vol. 11, no. 3, pp. 745–754, 2014. View at Publisher · View at Google Scholar · View at Scopus
  21. M. R. Droop, M. J. Mickelson, J. M. Scott, and M. F. Turner, “Light and nutrient status of algal cells,” Journal of the Marine Biological Association of the United Kingdom, vol. 62, no. 2, pp. 403–434, 1982. View at Publisher · View at Google Scholar · View at Scopus
  22. R. W. Eppley, “Temperature and phytoplankton growth in the sea,” United States Fisheries and Wildlife Service Bulletin, vol. 70, no. 4, pp. 1063–1085, 1972. View at Google Scholar
  23. J. Wang, “A newcast/forecast system for coastal ocean circulation using simple nudging data assimilation,” Journal of Atmospheric and Oceanic Technology, vol. 18, no. 6, pp. 1037–1047, 2001. View at Publisher · View at Google Scholar · View at Scopus
  24. K. Wang, S. Z. Feng, and X. H. Shi, “A 3-D baroclinic model of summer circulation in the Bohai, Yellow and East China Seas,” Oceanologia et Limnologia Sinica, vol. 32, no. 5, pp. 551–560, 2001. View at Google Scholar
  25. B. R. Zhao and G. H. Fang, “Water flux estimate of main waterways in the East China Sea,” Acta Oceanologica Sinica, vol. 13, no. 2, pp. 169–178, 1991. View at Google Scholar
  26. M. E. Conkright, R. A. Locarnini, H. E. Garcia et al., World Ocean Atlas 2001: Objective Analyses, Data Statistics, and Figures, CD-ROM Documentation, National Oceanographic Data Center, Silver Spring, Md, USA, 2002.
  27. C. S. Zhang, J. T. Wang, D. D. Zhu, X. L. Wang, and J. Li, “The preliminary analysis of nutrients in harmful algal blooms in the East China Sea in the spring and summer of 2005,” Acta Oceanologica Sinica, vol. 30, no. 2, pp. 153–159, 2008. View at Google Scholar
  28. X.-H. Chen, L.-S. Zhu, and H.-S. Zhang, “Numerical simulation of summer circulation in the East China Sea and its application in estimating the sources of red tides in the Yangtze River estuary and adjacent sea areas,” Journal of Hydrodynamics, vol. 19, no. 3, pp. 272–281, 2007. View at Publisher · View at Google Scholar · View at Scopus
  29. H. L. Chen, S. H. Lv, C. S. Zhang, and D. D. Zhu, “A survey on the red tide of Prorocentrum donghaiense in East China Sea, 2004,” Ecologic Science, vol. 25, no. 3, pp. 226–230, 2006. View at Google Scholar
  30. W. L. Xie, Community Structure and Dynamics of Planktonic Diatoms in Typical Areas of East China Sea, Xiamen Universtity, Xiamen, China, 2006.
  31. D. Tang, B. Di, G. Wei, I. H. Ni, S. O. Im, and S. Wang, “Spatial, seasonal and species variations of harmful algal blooms in the South Yellow Sea and East China Sea,” Hydrobiologia, vol. 568, no. 1, pp. 245–253, 2006. View at Publisher · View at Google Scholar · View at Scopus