Shallow Eutrophic Lake Research Articles

Effects of nutrient reduction and habitat heterogeneity on benthic macroinvertebrate assemblages in a large shallow eutrophic lake

The Taihu Lake ecosystem has been subjected to numerous anthropogenic stressors during the past decades, leading to substantial changes in nutrient dynamics and habitat quality. For instance, the northwestern lake bays receive large amounts of nutrient-rich wastewater and have frequently experienced algal blooms, while the eastern lake region is still dominated by submersed macrophytes. Such changes in environmental characteristics can greatly impact benthic macroinvertebrate communities. We used a 15-year monitoring data series collected by the Taihu Laboratory for Lake Ecosystem Research to examine the spatial and temporal variations of the benthic invertebrate fauna and evaluate its status and trends. We found that three major communities could be distinguished based on taxonomic group composition and abundance, and these corresponded well with three lake habitat types: algal-dominated, macrophyte-dominated, and open-lake zone. An analysis of temporal trends showed major changes in the macroinvertebrates during the study period, largely driven by a lake-wide and significant decline in the abundance of pollution-tolerant taxa. The spatial and temporal variations of macroinvertebrate communities were mainly explained by nutrients (e.g., total nitrogen and ammonium concentrations) and habitat factors (e.g., sediment substrates and macrophyte biomass) as indicated by Random Forests regression, but the major drivers of macroinvertebrate density differed among the three lake zones at the temporal scale. Moreover, our findings suggest that benthic invertebrates were more sensitive to the improvement of the lake's environmental conditions than the pelagic community was. This study provides insights into the responses of macroinvertebrates to ecological dynamics in lakes and highlights the importance of continued monitoring for tracking long-term changes.

A soft sensor for simulating algal cell density based on dynamic response to environmental changes in a eutrophic shallow lake

There is a great need for timely monitoring and rapid water quality assessment to control the algal blooms that often occur in eutrophic lakes. While algal cell density (ACD) is a critical indicator of algal growth, field monitoring is laborious and time-consuming, and rapid assessment of algal blooms based on ACD is often not possible. To address the limitations of conventional ACD detection, we proposed a soft sensor approach that uses surrogate indicators to simulate ACD in machine learning models. We conducted a case study using monitoring data from Chaohu Lake collected between 2016 and 2019. We found that ensemble learning models, especially extreme gradient boosting (XGBoost), outperformed traditional machine learning algorithms by comparing various machine learning algorithms. Also, considering the influence of input variable selection on model performance, we combined the results of different filter methods in the multi-stage variable selection process. Finally, we screened out seven key variables out of the 43 initial candidate variables, including dissolved oxygen (DO), chlorophyll-a (Chl-a), Secchi disk depth (SD), pH, permanganate index (CODMn), week of the year (WOY), and wind velocity (WV). Their inclusion substantially improved data accessibility and supported the development of a rapid simulation model. The final model was capable of reliable spatiotemporal generalization, with an overall R2 value of 0.761. On the theoretical side, our study makes a new attempt to simulate ACD values in a eutrophic lake. For practical purposes, the soft sensor can facilitate the rapid assessment of bloom conditions, which helps the local administration with emergency prevention and control.

Metagenomics reveals biogeochemical processes carried out by sediment microbial communities in a shallow eutrophic freshwater lake.

As the largest shallow freshwater lake in the North China Plain, Baiyangdian lake is essential for maintaining ecosystem functioning in this highly populated region. Sediments are considered to record the impacts of human activities. The abundance, diversity and metabolic pathways of microbial communities in sediments were studied by metagenomic approach to reveal patterns and mechanism of C, N, P and S cycling under the threat of lake eutrophication. Many genera, with plural genes encoding key enzymes involved in genes, belonging to Proteobacteria and Actinobacteria which were the most main phylum in bacterial community of Baiyangdian sediment were involved in C, N, S, P cycling processes, such as Nocardioides (Actinobacteria), Thiobacillus, Nitrosomonas, Rhodoplanes and Sulfuricaulis (Proteobacteria).For instance, the abundance of Nocardioides were positively correlated to TN, EC, SOC and N/P ratio in pathways of phytase, regulation of phosphate starvation, dissimilatory sulfate reduction and oxidation, assimilatory sulfate reduction, assimilatory nitrate reduction and reductive tricarboxylic acid (rTCA) cycle. Many key genes in C, N, P, S cycling were closely related to the reductive citrate cycle. A complete while weaker sulfur cycle between SO4 2- and HS- might occur in Baiyangdian lake sediments compared to C fixation and N cycling. In addition, dissimilatory nitrate reduction to ammonia was determined to co-occur with denitrification. Methanogenesis was the main pathway of methane metabolism and the reductive citrate cycle was accounted for the highest proportion of C fixation processes. The abundance of pathways of assimilatory nitrate reduction, denitrification and dissimilatory nitrate reduction of nitrogen cycling in sediments with higher TN content was higher than those with lower TN content. Besides, Nocardioides with plural genes encoding key enzymes involved in nasAB and nirBD gene were involved in these pathways. Nocardioides involved in the processes of assimilatory nitrate reduction, denitrification and dissimilatory nitrate reduction of nitrogen cycling may have important effects on nitrogen transformation.

Reconstructing eutrophication trends of a shallow lake environment using biomarker dynamics and sedimentary sterols

Major extractable lipid biomarkers (hydrocarbons, sterols and fatty acids) were assessed in Lake Seeburg, a shallow eutrophic lake that has increasingly been suffering from cyanobacterial blooms due to continued anthropogenic nutrient inputs over the last decades. Over the course of one year (2018/19), the distributions of these compounds were analyzed in the inflow, the lake water, and the topmost sediments (0–2 cm) to assess their origin and transfer into the lake deposits. Principal component analysis (PCA) was used to cluster the studied biomarkers into 5 groups with similar characteristics. These groups were comprised of (i) compounds delivered from external sources via the inflow, (ii) autochthonous compounds formed in the lake by eukaryotes or (iii) bacteria, (iv) compounds accumulating in the surface sediment, and (v) C27 to C29 stenols together with their degradation products, C27 to C29 5α(H)-stanols. Their seasonal partition clearly revealed that C27 stenols mainly derived from autochthonous sources within the lake, whereas C29 stenols largely reflect allochthonous material reaching the lake via the inflow. Analysis of stenol plus stanol concentrations with depth in two lake sediment cores (≈30 and 50 cm) found highest C27 to C29 ratios in surface sediments with lowest ratios at depth. These signals are interpreted to reflect the increasing trend of eutrophication of Lake Seeburg and, thus, enhanced autochthonous organic matter production in the lake over the last decades. The abundances of C27 vs. C29 stenols, summed with their respective degradation products, 5α(H)-stanols, are considered as suitable molecular indicators to qualitatively reconstruct historical eutrophication trends.

Synergistic warming- and catchment-driven mid-Holocene cyanobacterial development: Pigment evidence from shallow eutrophic Lake Mayinghai on the Chinese Loess Plateau

The current lake environmental problem of harmful cyanobacterial blooms cannot be mitigated effectively despite numerous eutrophication control strategies, and climate warming may have been considered as a potential key driver. However, it is still unclear how climate change and associated natural processes influence cyanobacterial development. Here we use a sedimentary pigment record from a remote, alpine, small and eutrophic lake (Lake Mayinghai) on the Chinese Loess Plateau and take the mid-Holocene as an analog to explore the possible influences of temperature, precipitation and terrestrial vegetation on in-lake and catchment processes, algal compositional changes and cyanobacterial development. The pigment data indirectly suggest that a distinctly low β-carotene to chlorophyll a ratio during the mid-Holocene is likely due to an increase in non-nitrogen-fixing colonial coccoid cyanobacteria at the expense of nitrogen-fixing filamentous cyanobacteria. There are two probable synergistic driving mechanisms, of which one is high temperatures and associated increased lake thermal stratification and the other is high inorganic nitrogen supply and resultant increased lake nitrogen to phosphorus ratio. This study provides implications for the potential influences of future climate change on cyanobacterial development under a warmer, wetter and re-forested environment on the Chinese Loess Plateau.

Nitrogen loading increases both algal and non-algal turbidity in subtropical shallow mesocosms: Implication for nutrient management

Excess nitrogen (N) loading in summer often boosts phytoplankton growth and increase algal turbidity. In eutrophic shallow lakes, the increased algal production may also augment the abundance of deposit-feeding tubificid worms and thereby sediment resuspension and non-algal turbidity. However, few studies have explored the effects of high N loading on this benthic process in eutrophic shallow lakes. Here, we conducted an outdoor mesocosm experiment in a summer-winter season (177 days) on the shore of subtropical Lake Taihu, China. Each mesocosm contained a 10 cm layer of lake sediment and 450 L of lake water. Nitrate was added weekly to three of the mesocosms, while another three functioned as controls. Our results showed that N addition significantly increased algal particles as water chlorophyll a (Chl-a) increased significantly following N addition. Moreover, significantly higher levels of inorganic suspended solids (ISS) were observed in the mesocosms with added N, indicating elevation of non-algal turbidity as well by the N addition. We attribute the latter to increased sediment resuspension as the abundance of tubificid worms was significantly higher in the N addition mesocosms. Accordingly, our study indicates that high N loading in subtropical shallow lakes may boost both algal and non-algal turbidity in part via benthic-pelagic coupling processes. Our results suggest that alleviation of eutrophication in shallow eutrophic lakes may require a strategic approach to adequately control both N and phosphorus.

Large Methane Emission from the River Inlet Region of Eutrophic Lake: A Case Study of Lake Taihu

Lakes are important natural sources of atmospheric methane (CH4), which should be considered in global CH4 budget estimations. However, the CH4 emissions from lakes can be highly variable, and the emissions from the river inlet region were less studied, which seriously hamper our understanding of CH4 budget estimates of lakes. Here, field measurements from over six years (2012 to 2017) at Lake Taihu, a large eutrophic shallow lake with a complicated river network, were conducted to address the issue. Results show that the river inlet region of the lake was a hot spot of CH4 emission. The CH4 emission at the river inlet region with an annual mean value of 0.183 mmol m−2 d−1 was seven times higher than that at pelagic region (0.028 mmol m−2 d−1). Peak CH4 emission occurred in warm seasons, and the lowest in cold seasons at the pelagic region, but peak emission occurred in cold seasons at the river inlet region. The seasonal CH4 emission at the pelagic region can be explained by water temperature; however, less temperature dependency of CH4 emission at the river inlet region was found. The variability of CH4 emission was linked to pollution loadings, and CH4-rich water in the inflowing river likely sustained the large CH4 emission of river inlet region.

Three-dimensional observations of particulate organic carbon in shallow eutrophic lakes from space

Particulate organic carbon (POC) storage play an essential role in determining carbon sinks and water quality in shallow eutrophic lakes. Although satellite data have been adopted to observe surface POC content, the previous remote sensing results cannot indicate water column-integrated POC storage in shallow eutrophic lakes with vertically nonuniform POC profiles. Based on 272 in-situ POC profiles collected from 19 shallow eutrophic lakes in China's Yangtze-Huai Plain (YHP), this study developed a novel process-oriented method to derive water column-integrated POC storage from OLCI/Sentinel-3A satellite data. The method included three critical steps: remotely estimating surface POC contents, identifying POC profile types (uniform, exponential decay, or power decay) through a binary decision tree, and parameterizing POC profiles using surface POC concentrations. The developed algorithms showed a bias of -25.79% for in-situ match-ups from 15 lakes (N = 88). The POC in the eutrophic lakes was mainly produced by phytoplankton (R2 = 0.87). As a result, the surface POC content presented a unimodal peak in summer. However, in addition to air temperature regulations (0.52 – 68.53%), the water level also showed apparent effects on increasing POC storage, with relative contributions of 29.29 – 95.51% for the six largest lakes. Therefore, multisource satellite data are needed to derive POC storage in global eutrophic lakes remotely. This study is the first attempt to three-dimensionally observe lake POC contents from space and is important for understanding the carbon cycle in shallow eutrophic lakes.

Response of zooplankton to nutrient reduction and enhanced fish predation in a shallow eutrophic lake.

As a key link between top-down regulators and bottom-up factors, zooplankton responds sensitively to environmental variations and provides information on the ecological state of freshwater systems. Although the response of zooplankton to anthropogenic pressures and fluctuating natural conditions, such as nutrient loading and climate change, has been extensively examined, findings have varied markedly. The mechanistic basis for the correlation between environmental variability and the zooplankton community is still debated, particularly for subtropical eutrophic lakes. We used two methods to analyze physicochemical and selected biological variables derived from long-term monitoring of Lake Taihu, a subtropical shallow lake in China. We first applied random forest regression to examine how changes in zooplankton were related to a set of environmental variables on interannual time scales. Then we used the results to guide the construction of a conceptual model for piecewise structural equation modeling (pSEM) to quantify more precisely the zooplankton-environment relationship. Zooplanktivorous fish and nutrient concentrations were the most important predictors of long-term trends in zooplankton in RF regression. Intensification of planktivorous fish predation led to a lower zooplankton biomass and smaller individuals through the removal of larger crustaceans. Moreover, suppression of zooplankton can in part be explained by increases in inedible algae, triggered by a combination of reduced nutrient concentrations and weakened grazer control. These results were also confirmed in the pSEM, which further indicated that top-down regulators might be more important than bottom-up factors for the zooplankton community in Lake Taihu. Our results suggest that stocking of filter-feeding fish in the lake did not meet the expectation that they would control algae, but that the use of biomanipulation measures considering both water quality and fishery management seems promising. This study offers insights into how indicator metrics of zooplankton can improve our understanding of the associations between plankton communities and ecosystem alterations.

In situ remediation mechanism of internal nitrogen and phosphorus regeneration and release in shallow eutrophic lakes by combining multiple remediation techniques

Large anthropogenic inputs of N and P alter the nutrient cycle and exacerbate global eutrophication problems in aquatic ecosystems. This study in Lake Datong, China, investigates the remediation mechanism of multiple remediation technique combinations (dredging, adsorbent amendment, and planting aquatic vegetation) on sediment N and P loads based on two high-resolution sampling techniques (HR-Peeper and DGT) and P sequential extraction procedures. The results showed that high temperature and low dissolved oxygen considerably enhanced pore water dissolved reactive P (DRP) and NH4+ concentrations attributable to abundant Fe-P and organic matter content in the sediment. Fe reduction is critical for regulating pore water DRP release and promoting N removal. Overall, for Lake Datong, combining multiple remediation techniques is more effective in controlling sediment P loads (pore water DRP, P fluxes, forms of P, and labile P), from a long-term perspective, than a single remediation. Lanthanum-modified bentonite (LMB) inactivation treatment can transfer mobile P in the surface sediment into more refractory forms over time, thereby reducing the risk of sediment labile P release. However, it is difficult to effectively remediate internal P loads owing to inappropriate dredging depths and low biomass of aquatic vegetation. Future lake restoration practices should optimize the selection of different remediation technique combinations based on internal N and P pollution characteristics, while reducing external wastewater input. These results are important for understanding the remediation mechanisms of internal N and P and provide suggestions for sediment management of shallow eutrophic lakes.

Simulating oligotrophication in a eutrophic shallow lake to assess the effect of periphyton bioreactor on phytoplankton and epipelon.

We evaluated the effects of a periphyton bioreactor on phytoplankton by experimentally simulating oligotrophication in a shallow eutrophic system. The experiment had two 50% diluted treatments with and without a periphyton bioreactor. Sampling was performed on days 6, 9, 12, 15, and 20 of the experimental period. The periphyton bioreactor accumulated biomass (chlorophyll-a, AFDM) and TP during the experimental period. Despite the biomass and TP loss due to periphyton detachment from the substrate after community reaching the algal biomass peak, the gains exceeded the losses, and the net rate was positive for all attributes in the bioreactor. Based on the average, our findings suggest that periphyton bioreactors negatively affected the phytoplankton total biovolume. Cyanobacteria were the most abundant phytoplankton group. However, the periphyton bioreactor caused the biomass loss of the Raphidiopsis raciborskii in phytoplankton. Our results suggest that bioreactor influenced the phytoplankton structure, reducing cyanobacterial biomass, especially Raphidiopsis raciborskii. However, the bioreactor did not reflect a significant increase in the epipelon biomass during the experimental period. We conclude that the periphyton bioreactor has the potential to assist in the maintenance of restored shallow lakes and reservoirs, especially in controlling phytoplankton growth.

Environmentally driven risk assessment for algal bloom occurrence in shallow lakes

An algal bloom is a complex hydro-biological phenomenon driven by multi-attribute environmental processes and thus is still difficult to predict. In this paper, a comprehensive modelling framework for forecasting algal bloom risks in shallow lakes is presented, which is based on long-term field observation and modelling of eutrophic shallow lakes. In the procedure, the major factors and their suitable ranges are investigated, and the individual influence of various driving factors is evaluated quantitatively, using an integrated approach of orthogonal design and regression analysis. By analysing the possible combined effects of the major driving factors and the relationship between algal bloom risk and major bloom-driving factors, a cost-effective environmentally driven risk assessment model is developed to forecast the likelihood of algal bloom occurrence, through a parameter optimization and prediction comparison routine. The risk model has been calibrated and validated against long-term field observations of algal blooms in Taihu Lake, with the prediction accuracy higher than 70%, which only requires readily available meteorological and water quality data. It is noted that for the closed shallow lake, the influence of hydrodynamics can be indirectly reflected by the variation of wind speed; and, total phosphorus, water temperature, photosynthetically active radiation, and average wind speed could be used as major bloom-driving factors in Taihu Lake generally. This study provides a practical framework for the development of algal bloom early warning schemes for shallow lakes and helps to understand the combined function of complex bloom-driving factors.

Spatiotemporal variability and diffusive emissions of greenhouse gas in a shallow eutrophic lake in Inner Mongolia, China

Aquatic ecosystems are globally significant sources of greenhouse gases (GHG) to the atmosphere, offsetting the terrestrial sinks. A one-year field study was carried out in a shallow eutrophic Lake Wuliangsuhai, Inner Mongolia (draining waters from one of the largest irrigation areas in China), to estimate diffusive GHG fluxes and their relative importance in global warming potential (GWP). Our results showed high spatiotemporal variation in dissolved CO2, CH4 and N2O concentrations, while they did not differ significantly between the bottom and surface layers of the shallow waterbody. In general, GHG concentrations and diffusive fluxes were higher in the north part of the lake than in the south. GHG concentrations in the water under the ice were significantly higher than those during the open-water period. Spatial variability of GHG concentrations varied with the bathymetry of the lake. The location of study sites relative to the main inflow and abundance of submerged macrophytes were the main controlling factors of GHG concentrations, as indicated by the consistency of GHG concentrations at the sampling sites, particularly for N2O. The total diffusive GHG emission from Lake Wuliangsuhai was 76.9 ± 5.4 Gg CO2 equivalents yr−1, with CO2, CH4 and N2O contributing 16 %, 83 %, and 1 %, respectively. Overall, the results suggest that shallow lakes in mid-latitude arid areas with cold winters can be potentially important GHG sources. However, those lakes are insufficiently represented in the scientific literature, and therefore they deserve more research attention.

Whole-Genome Sequence of Sediminibacterium sp. Strain TEGAF015, Isolated from a Shallow Eutrophic Freshwater Lake in Japan.

The genus Sediminibacterium comprises bacteria representing the ubiquitous taxa of freshwater bacterioplankton. Here, we report the whole-genome sequence of Sediminibacterium sp. strain TEGAF015, isolated from a shallow eutrophic freshwater lake in Japan.

Contrasting diversity patterns and community assembly mechanisms of bacterioplankton among different aquatic habitats in Lake Taihu, a large eutrophic shallow lake in China

Eutrophication leads to the degradation of lake habitat types from macrophyte-dominated habitats (MDH) to algae-dominated habitats (ADH), which is a common environmental problem faced by many lakes. However, the variations in diversities and community assembly processes of bacterioplankton in the process of lake eutrophication have not been thoroughly elucidated. Here, we contrasted bacterial diversity patterns and processes of community assembly among ADH, MDH, and other habitats (OH) of Lake Taihu, a large shallow eutrophic lake in China with strong wind-induced disturbances. We found that the bacterial diversity patterns and potential functions between ADH and MDH were significantly different. Moreover, the contributions of purely environmental variables to the bacterial diversity patterns of all habitat types were much higher than those of spatial variables. However, the relative importance of stochasticity in the bacterial community assembly of each habitat type was much higher than that of determinism. Intriguingly, ‘undominated’ stochastic processes shape the diversity patterns of bacterioplankton in ADH, MDH, and OH of Lake Taihu. These findings demonstrate that the degradation of lake habitats caused by eutrophication can profoundly change the diversity and potential function patterns of the bacterioplankton community in lake ecosystems. Although the distinct diversity patterns of the bacterioplankton among the different aquatic habitats in Lake Taihu can be affected by deterministic processes (local environmental variables), they were dominated by stochastic processes (drift). Our study confirms that strong, disordered, wind-induced disturbances in shallow lakes could lead to strong hydrologic mixing, thus increasing the randomness of bacterial community assembly in each habitat.

Response of planktonic diversity and stability to environmental drivers in a shallow eutrophic lake

Plankton is an important component of a healthy shallow lake aquatic system, and the diversity and stability of its community structure are impacted by numerous environmental factors. However, knowledge about the relative importance of these factors is limited. This study presents a case study conducted in semi-arid, shallow eutrophic lakes in China to evaluate the relative importance of physical, chemical, and nutritional characteristics of water quality and light effects on the spatiotemporal distributions of diversity and stability of plankton communities. The findings showed that the plankton community was the least diverse in winter and the most stable during the spring-to-summer transition. The results of partition variation showed that physical and chemical indicators, nutritional parameters, and light effects explained >70 % of the zooplankton community dynamics, compared with 37 % for phytoplankton. For phytoplankton community composition, physical and chemical parameters, followed by light, had the greatest influence. Further analysis showed that phytoplankton were influenced primarily by nutrients, water depth, and pH. Similarly, the diversity and stability of the zooplankton exhibited physical and chemical parameter responses, and the influence of nutrients also played a significant role. Structural equation modelling showed that light had minimal direct effect on the plankton and affected the plankton indirectly through changes in total nitrogen and NO3-N. This study estimates the distribution of plankton community in a shallow eutrophic lake, quantifying the relative effects of different environmental drivers on plankton diversity and stability, and provides an in-depth understanding for improving the lake water quality and controlling nutrients pollution.

The role of nutrients, wind speed, and rainfall in determining the composition of the algal community of shallow lakes in the Taoge water system, upstream from Lake Taihu, China.

Gaining a deeper understanding of factors that influence changes in phytoplankton community has significant implications for shallow lake management. The present study examined changes in the algae community of three shallow eutrophic lakes of the Taoge water system between 2008 and 2018 and the related factors influencing these changes. The composition of the algal community varied significantly during this period with the relative diatom biomass in lakes Changdanghu and Gehu increasing between 2014 and 2016 and again decreasing after 2017. However, relative cyanobacteria biomass initially decreased and later increased; meanwhile, the proportion of biomass of other phyla decreased continuously in the study period. Lake Zhushanhu showed similar trends, although it eventually returned to its initial state with absolute Microcystis dominance. Furthermore, the analysis of driving factors revealed that the concentrations of total nitrogen (TN), nitrate (NO3), and orthophosphate (PO4) were significantly associated with a significant increase in Microcystis biomass. Meteorological conditions also influenced changes in total algal and diatom biomasses, which were inversely related to the daily mean and daily maximum wind speeds. Monthly cumulative precipitation was only significantly associated with diatom biomass. Meanwhile, rainfall primarily affected the algal community structure between 2013 and 2017; an increase in the relative biomass of diatoms coincided with increased precipitation. Coordinating nitrogen and phosphorous use within the Taoge water system should improve lake habitat management; a broader perspective in attempts to control global and regional climate change may be needed.

Phosphorus removal by aquatic vegetation in shallow eutrophic lakes: a laboratory study.

Eutrophication in inland lakes is occurring frequently with the rapid urbanization, the increases in human population, and the intensive agricultural activities. Traditional management programs focusing on external nutrient reduction failed in recovery of certain aquatic environments where internal nutrient releases are substantial. In this study, we evaluated the effects of aquatic vegetation in altering the phosphorus concentrations in a shallow, eutrophic lake through laboratory flume experiments. Our measurements demonstrated that aquatic vegetation could effectively lower the phosphorus levels in the water column, and the average reduction reached 90% for submerged vegetation and 80% for emergent vegetation. The experimental results showed that the submerged vegetation was effective to reduce phosphorus concentrations in the top and mid layers of pore waters and sediments. Differently, the emergent vegetation would assimilate more phosphorus in the bottom layer due to its deep root distributions. The flowing-water environment favored phosphorus removal for emergent vegetation, while the submerged vegetation was more functional in static waters according to our observations. The flux results showed that phosphorus transports from water columns to leaves, roots to leaves, and sediments to roots were all inhibited in flowing-water environments for submerged vegetation. Oppositely, the fluxes of emergent vegetation groups were all enhanced in flowing waters. Our experiments could inform ecosystem management concerning the potentials of aquatic vegetation in nutrient removal at regional and lake-wide scales.

Variation in Spectral Characteristics of Dissolved Organic Matter and Its Relationship with Phytoplankton of Eutrophic Shallow Lakes in Spring and Summer

The compositional characteristics of dissolved organic matter (DOM) have important implications for lake water quality and aquatic ecology. Seasonal changes of dissolved organic matter (DOM) as well as phytoplankton abundance and composition in Shahu Lake from April to July were characterized by three-dimensional fluorescence spectroscopy (3DEEMs) combined with parallel factor (PARAFAC) analysis. The relationship between the response of components of the DOM and phytoplankton abundance were explored via Pearson correlation and redundancy analysis (RDA) in the overlying water. The results showed that the DOM was composed mainly of tryptophan-like (C2+C4), fulvic-acid-like (C3), humic-acid-like (C1), and tyrosine-like (C5) compounds that accounted for 44.47%, 20.18%, 20.04%, and 15.31%, respectively, of the DOM. The DOM was derived from both endogenous and terrestrial sources. With seasonal changes, endogenous DOM produced by phytoplankton growth and metabolism gradually increased. In spring and summer (April–July), Chl-a concentrations were significantly correlated with C3 (p < 0.01) and C5 (p < 0.05). The concentration of protein-like fractions (C2+C4, C5) were correlated with Cyanobacteria abundance, and the concentrations of humic-like component content (C1, C3) were correlated with the abundance of Xanthophyta, Chlorophyta, and Cryptophytes. Overall, phytoplankton density and Chl-a content increased by 125% and 197%, respectively, and the abundance of C3 and C5 in the DOM increased by 7.7% and 22.15% in parallel. Thus, seasonal phytoplankton growth had an important influence on the composition of the DOM.

Developing cyanobacterial bloom predictive models using influential factor discrimination approach for eutrophic shallow lakes

Harmful cyanobacterial blooms damage aquatic ecosystems and pose a threat to human health. To identify key factors causing cyanobacterial blooms in eutrophic shallow lakes, we analyzed cyanobacterial and physicochemical water samples of 12 sites collected monthly from December 2012 to December 2019 in Dianshan Lake. We found that the rapid growth of cyanobacteria was limited by a temperature threshold. When the air temperature was below 18 °C, the sampled physicochemical factors could not make difference in cyanobacterial abundance regardless the values of these parameters. However, when the air temperature was above 18 °C, the measured physicochemical factors played important roles in influencing cyanobacterial abundance. We developed a data-driven predictive model for cyanobacterial blooms based on seven-year data from Dianshan Lake using multiple logistic regression. Such a model could be easily used to predict cyanobacterial blooms. Our weight analysis of model parameters indicated that dissolved substances other than TN and TP are the key factor determining cyanobacterial blooms in nitrogen and phosphorus rich shallow freshwater lakes once air temperature is above 18 °C. Eutrophic shallow lakes are prone to cyanobacterial blooms, and unwashed data analysis may mask key factors determining cyanobacterial blooms, which obscures the prediction of cyanobacteria blooms. Our results are helpful to uncover the real causes of the blooms of eutrophic shallow lakes in China and elsewhere, and hence improve the understanding and management in controlling cyanobacterial blooms.