Elsevier

Science of The Total Environment

Volume 649, 1 February 2019, Pages 1553-1562
Science of The Total Environment

Succession and interaction of surface and subsurface cyanobacterial blooms in oligotrophic/mesotrophic reservoirs: A case study in Miyun Reservoir

https://doi.org/10.1016/j.scitotenv.2018.08.307Get rights and content

Highlights

  • High light and nutrient at pre-bloom stage are essential for surface cyanobacteria.

  • Surface cell decline enhanced underwater light thus promoted subsurface cyanobacteria.

  • Subsurface cyanobacteria prefer to grow in shallow oligotrophic/deep eutrophic water.

Abstract

Subsurface cyanobacterial blooms, are a significant source of odor problems in source water and have been recorded in many oligotrophic/mesotrophic drinking water reservoirs. In this study, we explored the key driving forces responsible for the succession between surface and subsurface cyanobacteria using ecological niche modelling based upon a case study in Miyun Reservoir, China. The results suggest a negative effect of water depth and surface light irradiance (I0) on subsurface Planktothrix sp. growth (p-values < 0.001), and a unimodal effect of surface water temperature (T0) with the optimum at 23 °C (p-value < 0.001). While the surface Microcystis spp. shows a strong positive relationship with temperature (T0; p-value < 0.001), and significant effects for the interaction between T0 and I0 (p- value < 0.01). In addition, we identified the extent and type of interaction between subsurface and surface cyanobacteria and conclude that the high irradiance surface water combined with sufficient nutrients at the pre-bloom stage are key factors responsible for the preferential growth of surface cyanobacteria, while the gradual decline of the surface cyanobacteria in post-bloom stage is associated with nutrient reduction. This decline and loss of surface populations enhanced underwater irradiance and thus promoted the growth and allowed for succession of subsurface cyanobacteria in deeper layers where the nutrient supply was still adequate. Based upon this, the growth potentials for the subsurface and surface cyanobacteria are different under different environmental conditions: the subsurface cyanobacteria have greater growth potential than surface cyanobacteria in shallow oligotrophic and deep eutrophic reservoirs during median light irrigation seasons.

Introduction

Cyanobacteria have developed advantages and strategies through evolution that allow them to flourish in aquatic environments, producing massive blooms, scums and mats (Huisman and Hulot, 2005). They also produce a diverse range of compounds that include tastes (Yang et al., 2008, Kehoe et al., 2015, Bai et al., 2017, U. S. Geological Survey et al., 2017) and toxins (MacKintosh et al., 1990, Molica et al., 2005, Dittmann et al., 2013, Buratti et al., 2017), which degrade water quality. For example, globally the two most prominent cyanobacteria that produce striking surface blooms: Microcystis spp. produces microcystin toxins, and Dolichospermum spp. (formerly named as Anabaena spp.) can produce both anatoxin and saxitoxin neurotoxins in addition to the earthy smelly odor compound geosmin; and attract extensive concern and attention (Acun̆a et al., 2012, Liu et al., 2011, Chia et al., 2018). Surface-living cyanobacteria are able to regulate their buoyancy and therefore maintain a particular vertical position according to their needs, which can potentially provide an advantageous competitive strategy over non-buoyant phytoplankton (Mur et al., 1999, Yao et al., 2017, Wang et al., 2017). However, aesthetic and toxin-induced water quality problems are known to occur in some drinking water reservoirs, sometimes with low nutrient concentrations, and are not always associated with or and explained by the occurrence of surface bloom-forming cyanobacteria.

Example of cyanobacterial blooms that are not strongly buoyant such as the filamentous types Oscillatoria spp., Phormidium spp., have been recorded in many reservoirs (AWWA, 2010, Dokulil and Teubner, 2012, Watson et al., 2016). These may have large biomass accumulations present either as mats on the sediment surface (Noffke et al., 2003) or are present as blooms deeper in the water column that produce high chlorophyll concentrations well below the epilimnion (Dokulil and Teubner, 2012). This behavior may seem paradoxical, since the surface-living cyanobacteria with access to sufficient irradiance would be expected to outcompete the types with a preference for living in a subsurface zone (Davis et al., 2003). For water quality management, it is important to understand the combination of conditions or environmental changes that allow subsurface cyanobacteria to outcompete surface cyanobacteria.

The competitive exclusion principle (Hardin, 1960) has long been the tenet for predicting outcomes of competition between algal populations (Klausmeier and Litchman, 2001, Rothhaupt, 1996, Tilman et al., 1982). Huisman et al. (1999), have demonstrated that the species with “minimal resource requirements” should be the superior competitor. Dynamic competition models built around this principle and based upon differential equations usually work well for controlled conditions, and have been extensively used to explain competitive relationships among algal species in experimental laboratory systems (Huisman and Weissing, 1995, Huisman et al., 1999, Rothhaupt, 1996). However, with regard to the natural environment, the models are not necessarily applicable where the resources for their growth vary spatially and also seasonally. The application of mechanistic models in field studies can be challenging owing to the complex interplay between physical and chemical properties of the aquatic environment and the responsiveness of the individual species (Huisman and Hulot, 2005). By contrast ecological niche models utilize associations between environmental variables and known species' occurrence localities to define abiotic conditions within which populations can be maintained (Guisan and Thuiller, 2005), and have already been integrated into a broad variety of research disciplines (reviewed by Raxworthy et al., 2007). The niche hypervolume, defines the multi-dimensional space of resources (e.g., light irradiance, nutrients, temperature) available to (and specifically used by) organisms (Hutchinson, 1957) is constrained by a multivariate species' response function of the habitat vector. McKane et al. (2002) successfully used resource-based niches to analyze the plant species diversity and dominance in arctic tundra.

In this investigation we attempt to extend the niche space to include time scales, and hence integrate all the spatial and seasonally dependent vectors into a unified niche space. Since the organisms response at each point in the niche is specified, it is possible to model interspecies competition by comparing response vectors of competing species at points of niche overlap (Wuenscher, 1969). In this study, the niche concept is employed to evaluate and determine the driving forces responsible for the seasonal succession between the surface and subsurface cyanobacteria, using ecological niche modelling (Generalized Additive Models, a non-parametric statistical method; Hastie and Tibshirani, 1990) in a major Chinese drinking water reservoir. This is a novel and unique application of the niche concept model to achieve improved understanding of the behavior of cyanobacteria for source water management.

Miyun Reservoir, the most important surface water resource for the city of Beijing, has been subject to major taste & odor problems for several years due to the development of subsurface-living blooms of Planktothrix sp. (Su et al., 2015). Hereby we perform niche modelling by using the long-term monitoring data in Miyun Reservoir, to assess the seasonal dynamics of surface and subsurface cyanobacteria, and identify the environmental constraints responsible for their seasonal succession. This can be used for the development of possible strategies for the prevention of subsurface cyanobacteria based upon their ecological niche in various environment conditions.

Section snippets

Study area and sampling strategy

The Miyun Reservoir is situated in the northeastern part of Beijing, China (40°30N, 116°55E, Fig. A1). It was initially constructed for flood control, irrigation and fisheries, but is now the major water source for the city of Beijing. The reservoir encompasses a large area, with a total storage capacity of 437.5 GL and a surface area of 188 km2, as well as a complex bathymetry classified as a mountain valley reservoir type (Su et al., 2014). Miyun Reservoir's major natural replenishment is

Temporal-spatial patterns of environmental conditions

The nutrient concentrations indicate that Miyun Reservoir is mesotrophic with a total dissolved nitrogen (total N, TN) concentration of 967±317 μg L−1 (mean ± Variance, N = 1447), ammonia (NH4) concentration of 250±142 μg L−1 (N = 1447), total phosphorus (total P, TP) concentration of 14±11 μg L−1 (N = 1447) and water transparency Secchi depth (SD) of 2.34±0.86 m (N = 1465). Most limnological parameters in the Miyun Reservoir showed significant temporal variation (Fig. 1), but with “rugs” in

Discussion

The Microcystis seasonal patterns show growth as early as April and it becomes the dominant species by July (data not shown). Planktothrix is rarely observed before August and its growth is the greatest at a time that Microcystis is declining. Our findings indicate that ammonia, water depth, surface water temperature and irradiance are the essential predictors of Microcystis and Planktothrix, but they act in different ways. For example, elevated ammonia can be regarded as being both a cause and

Conclusion

In this study, the main mechanisms driving the succession and interaction between the surface and subsurface cyanobacteria in a major Chinese Reservoir have been proposed based upon the ecological niche concept derived from the GAM modelling. Underwater light irradiance, controlled by both surface light irradiance and water column transparency, is regarded as a critical factor to control the growth of subsurface cyanobacteria in this reservoir, and might be perhaps also applied to other shallow

Acknowledgements

We would like to thank Dr. Marcia Kyle for the linguistic improvements and English corrections. This work was financially supported by the National Natural Science Foundation of China (51508549), the Funds for Major Science and Technology Program for Water Pollution Control and Treatment (2015ZX07406001, 2017ZX07108002).

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