Long-term dynamics and drivers of phytoplankton biomass in eutrophic Lake Taihu

The impacts of socioeconomic development and climate change on long-term nutrient dynamics: A case study in Poyang Lake

The anthropogenic activities associated with rapid socioeconomic development affect global climate change and the water quality of lake ecosystems. However, the impacts of socioeconomic and climate changes on lake nutrient dynamics require additional study. In this study, we used a long-term dataset (1987-2021) of Poyang Lake to identify the nutrient dynamics and assess the impacts of social and climatic factors on nutrient concentrations. The filtering trajectory method (FTM) suggested that in Poyang Lake, nutrients first increased and then decreased, with TP reaching its highest value of 157 μg/L in 2015. The study employs a combination of structural equation modeling (SEM) and FTM to identify the complex interactions between socio-economic and climatic factors affecting nutrient concentrations in Poyang Lake. The SEM results revealed that socioeconomic factors rather than climate change determined the long-term changes in TN and TP. Additionally, FTM results verified that GDP, urbanization (Ur) and P-fertilizer (Pfer) were the key drivers of TN; Ur, population (P), and sewerage treatment rate (STR) were the primary factors of TP. Through generalized additive models (GAMs), we observed that GDP accounted for 86 % of the temporal variability in TN and 45.7 % of that in TP, exhibiting inverted U-shaped relationships with both TN and TP. Air temperature (AT), a climatic factor accounted for only 44.6 % and 14.8 % of the variation in TN and TP, respectively. In addition, Pfer explained 66.0 % of the variation in TN, and STR explained 50.4 % of the variation in TP with a peak TP at the STR threshold of approximately 80 %. Our findings highlight the importance of Pfer and STR as critical indicators for watershed nutrient management. The identification of key temporal drivers and nutrient trajectories provides a scientific basis for developing management strategies. The results highlight coordinated control strategies for water pollution and carbon reduction as essential measures for mitigating climate change.

A comprehensive time-series dataset linked to cyanobacterial blooms in Lake Taihu

Lake Taihu has a history of recurrent harmful cyanobacterial blooms. There is a need to better understand the aquatic ecosystem of Lake Taihu in order to improve methods for controlling the cyanobacterial blooms. Based on the field measurement and satellite remote sensing, we produced and collected a time-series dataset, including the water quality, bio-optics, climate, and anthropogenic data of Lake Taihu (THQBCA), which could provide comprehensive information regarding cyanobacterial blooms. The THQBCA dataset contains 26 variables organized into four categories: water quality, bio-optics, climate, and anthropogenic data. The water quality and climate data are field measured data with sampling frequency from daily to quarterly, and bio-optics and anthropogenic data are satellite-derived annual data. The dataset spans more than 15 years (8 of which cover approximately 35 years, 4 of which cover 20 years), and the spatial resolutions of the satellite-derived data range from 30 m to 500 m. This dataset is expected to advance research on evaluating and predicting cyanobacterial blooms, and support science-based management decisions for sustainable ecological development.

Nutrient regeneration patterns for initiating and maintaining algae blooms-a case study of in Lake Taihu

In order to clarify the nitrogen (N) and phosphorus (P) regeneration patterns and internal mechanism for initiating and maintaining algal blooms in Lake Taihu, samples (including surface water and sediment) from 8 sites in Lake Taihu were collected for nine times from May 2010 to April 2011, and analyzed for total and labile organic matter, P fractionation and sorption behaviors, extracellular enzymatic activities (EEA), dehydrogenase activity, the respiratory electron transport system activity, and iron in sediment, EEA, N and P species and chlorophyll a (Chl. a) in surface water, as well as N and P species in interstitial water. In Lake Taihu, although severe blooms occurred in both Meiliang Bay and Zhushan Bay, the nutrient regeneration patterns stimulating the initiation and maintenance of algae blooms in these two bays were different. In Zhushan Bay with low EEA in surface water, abundant N and P flux from sediments, due to the degradation of organic matter and enzymatic hydrolysis in sediment, further stimulated the initiation and maintenance of algae blooms. In Meiliang Bay, in spite of lower nutrient supply from sediment, high EEA in surface water occurred later than the serious blooms, showing that the nutrient regeneration from sediment, not water body, was still the trigger for the start of the bloom, and sediment nutrient release and predominant surface water nutrient regeneration by abundant exoenzymes sustained the algal blooms. In the Western region, algal bloom started in the northern area and further spread in the remaining part of the lake; nutrient regeneration in the surface water sustained the slight bloom. In the East Bays, the decay and decomposition of macrophytes led to anaerobic conditions in sediments and high ammonia in interstitial water, but low iron bound phosphorus resulted in anaerobic release of very few P, thus showed extremely low Chl. a concentration.

Temporal shifts in the phytoplankton network in a large eutrophic shallow freshwater lake subjected to major environmental changes due to human interventions

Phytoplankton communities are crucial components of aquatic ecosystems, and since they are highly interactive, they always form complex networks. Yet, our understanding of how interactive phytoplankton networks vary through time under changing environmental conditions is limited. Using a 29-year (339 months) long-term dataset on Lake Taihu, China, we constructed a temporal network comprising monthly sub-networks using "extended Local Similarity Analysis" and assessed how eutrophication, climate change, and restoration efforts influenced the temporal dynamics of network complexity and stability. The network architecture of phytoplankton showed strong dynamic changes with varying environments. Our results revealed cascading effects of eutrophication and climate change on phytoplankton network stability via changes in network complexity. The network stability of phytoplankton increased with average degree, modularity, and nestedness and decreased with connectance. Eutrophication (increasing nitrogen) stabilized the phytoplankton network, mainly by increasing its average degree, while climate change, i.e., warming and decreasing wind speed enhanced its stability by increasing the cohesion of phytoplankton communities directly and by decreasing the connectance of network indirectly. A remarkable shift and a major decrease in the temporal dynamics of phytoplankton network complexity (average degree, nestedness) and stability (robustness, persistence) were detected after 2007 when numerous eutrophication mitigation efforts (not all successful) were implemented, leading to simplified phytoplankton networks and reduced stability. Our findings provide new insights into the organization of phytoplankton networks under eutrophication (or re-oligotrophication) and climate change in subtropical shallow lakes.

Diel and seasonal mixing patterns and water quality dynamics in a multipurpose tropical semiarid reservoir

Eutrophication has become a recurrent concern in reservoirs worldwide. This problem is intensified in tropical semiarid regions, where the reservoirs have high seasonal and annual variability of water level and volume. Therefore, an extensive understanding of the diel variation of water quality key-parameters can help improve management of such reservoirs. This study focuses on Castanhão reservoir with the largest multipurpose dam in the Brazilian semiarid. Its main water uses are irrigation, fish farming, and human supply. The reservoir faced a decline in water quality due to a prolonged drought period. While previous research has predominantly emphasized the seasonal dynamics of thermal and chemical stratification, our investigation provides diel assessments of multiple water quality parameters, including nutrient concentrations and phytoplankton abundance. Our primary objective is to compare seasonal and diel variations in stratification and nutrient distribution within the reservoir. Key findings reveal a diel cycle of thermal stratification, primarily during dry season, driven by higher wind speeds. This is corroborated by a significant negative correlation between wind speed and the relative water column stability index. In contrast, during the rainy season, the reservoir experiences continuous thermal stratification due to inflowing water being warmer than the reservoir's water temperature. Notably, a significant negative correlation between total phosphorus and chlorophyll-a, along with a two-fold increase of this nutrient throughout the day during the rainy season, underscores the influence of the phytoplankton community dynamics on the diel nutrient variation. Chemical stratification of dissolved oxygen occurred during dry and rainy seasons, indicating that even during the dry season, where there is no significant inflow, the internal nutrient loading can also significantly impact the water quality of a reservoir. This study advances the understanding of diel water quality dynamics in tropical semiarid reservoirs, shedding light on both climatic and anthropogenic influences on water resources.

Re-oligotrophication and warming stabilize phytoplankton networks

Phytoplankton taxa are strongly interconnected as a network, which could show temporal dynamics and non-linear responses to changes in drivers at both seasonal and long-term scale. Using a high quality dataset of 20 Danish lakes (1989-2008), we applied extended Local Similarity Analysis to construct temporal network of phytoplankton communities for each lake, obtained sub-network for each sampling month, and then measured indices of network complexity and stability for each sub-network. We assessed how lake re-oligotrophication, climate warming and grazers influenced the temporal dynamics on network complexity and stability of phytoplankton community covering three aspects: seasonal trends, long-term trends and detrended variability. We found strong seasonality for the complexity and stability of phytoplankton network, an increasing trend for the average degree, modularity, nestedness, persistence and robustness, and a decreasing trend for connectance, negative:positive interactions and vulnerability. Our study revealed a cascading effect of lake re-oligotrophication, climate warming and zooplankton grazers on phytoplankton network stability through changes in network complexity characterizing diversity, interactions and topography. Network stability of phytoplankton increased with average degree, modularity, nestedness and decreased with connectance and negative:positive interactions. Oligotrophication and warming stabilized the phytoplankton network (enhanced robustness, persistence and decreased vulnerability) by enhancing its average degree, modularity, nestedness and by reducing its connectance, while zooplankton richness promoted stability of phytoplankton network through increases in average degree and decreases in negative interactions. Our results further indicate that the stabilization effects might lead to more closed, compartmentalized and nested interconnections especially in the deeper lakes, in the warmer seasons and during bloom periods. From a temporal dynamic network view, our findings highlight stabilization of the phytoplankton community as an adaptive response to lake re-oligotrophication, climate warming and grazers.

Weakened casual feedback loops following intensive restoration efforts and climate changes in a large shallow freshwater lake

Understanding how phytoplankton interacts with local and regional drivers as well as their feedbacks is a great challenge, and quantitative analyses of the regulating role of human activities and climate changes on these feedback loops are also limited. By using monthly monitoring dataset (2000-2017) from Lake Taihu and empirical dynamic modelling to construct causal networks, we quantified the strengths of causal feedbacks among phytoplankton, local environments, zooplankton, meteorology as well as global climate oscillation. Prevalent bidirectional causal linkages between phytoplankton biomass (chlorophyll a) and the tested drivers were found, providing holistic and quantitative evidence of the ubiquitous feedback loops. Phytoplankton biomass exhibited the highest feedbacks with total inorganic nitrogen and ammonia and the lowest with nitrate. The feedbacks between phytoplankton biomass and environmental factors from 2000 to 2017 could be classified into two groups: the local environments (e.g., nutrients, pH, transparency, zooplankton biomass)-driven enhancement loops promoting the response of the phytoplankton biomass, and the climate (e.g., wind speed)-driven regulatory loops suppressing it. The two counterbalanced groups modified the emergent macroecological patterns. Our findings revealed that the causal feedback networks loosened significantly after 2007 following nutrient loading reduction and unsuccessful biomanipulation restoration attempts by stocking carp. The strength of enhancement loops underwent marked decreases leading to reduced phytoplankton responses to the tested drivers, while the climate (decreasing wind speed, warming winter)-driven regulatory loops increased- like a tug-of-war. To counteract the self-amplifying feedback loops, the present eutrophication mitigation efforts, especially nutrient reduction, should be continued, and introduction of alternative measures to indirectly regulate the critical components (e.g., pH, Secchi depth, zooplankton biomass) of the loops would be beneficial.

Spatial and temporal patterns of phytoplankton community succession and characteristics of realized niches in Lake Taihu, China

Understanding the dynamics and succession of phytoplankton in large lakes can help inform future lake management. The study analyzed phytoplankton community variations in Lake Taihu over a 21-year period, focusing on realized niches and their impact on succession. The study developed a niche periodic table with 32 niches, revealing responses to environmental factors and the optimal number of niches. Results showed that the phytoplankton in Lake Taihu showed significant spatial and temporal heterogeneity, with biomass decreasing as one moved from the northwest to the southeast and expanding towards central lake area, and towards autumn and winter. Different phytoplankton groups in Lake Taihu occupied realized niches shaped by temperature, nitrate, and phosphate. To predict the response of eutrophic freshwater lake ecosystems to human activities and climate change, it is critical to interpret the law of phytoplankton bloom and niche succession.

Hydrological regimes and water quality variations in the Yangtze River basin from 1998 to 2018

Understanding the long-term variations in basins that undergo large-scale hydroelectric projects is crucial for effective dam operation and watershed management. In this study, comprehensive analyses were conducted on a dataset spanning over 20 years (1998-2018) of hydrological regime and physicochemical parameters from the Yangtze River basin to evaluate the potential impacts of the Three Gorges Dam. Water level significantly increased from 128.75±58.18 m in 2002 to 136.78±55.05 m in 2005, and the mean flow velocity significantly decreased from 2004 to 2010. However, no significant change in the flow was observed in the basin. Meanwhile, remarkable fluctuations in physicochemical parameters, including dissolved oxygen, chemical oxygen demand, conductivity, hardness, and alkalinity, were mainly observed during impoundment (2003-2009). After that, the above parameters tended to stabilize, and some even returned to their original levels. The dam's retention effect significantly reduced the suspended solids (SS) in both up- and downstream, to only one-third of the pre-operation level. And total phosphorus and chemical oxygen demand also significantly decreased with the decline of SS. Particularly, ammonium also showed a significant downward trend, with the up- and downstream of the dam falling by 36.8 % and 26.1 %, respectively. However, the increasing total nitrogen (7.5 % and 20.0 % up- and downstream of the dam, respectively) still threatened the water quality of the basin, especially in the estuaries. Additionally, the significant decline in dissolved oxygen downstream (from 8.53±1.08 mg/L to 8.11±1.36 mg/L) also exacerbated the hypoxia in the Yangtze River estuary. The results demonstrated the long-term impact of the construction of the Three Gorges Dam on the environmental elements of the Yangtze River basin, which provides reference data and guidance for the construction of big dams in major rivers in the future.

Vertical distribution rules and factors influencing phytoplankton in front of a drinking water reservoir outlet

The phenomenon of algal blooms caused by the excessive proliferation of phytoplankton in drinking water reservoirs is becoming increasingly frequent, seriously endangering water quality, ecosystems, water safety, and people's health. Thus, there is urgent need to conduct research on the distribution rules and factors influencing phytoplankton in drinking water reservoirs. Given that the outflows from reservoirs usually come from the middle and lower layers of the water column and the current studies on phytoplankton in drinking water reservoirs are usually carried out on the surface, an 8-month monitoring of vertical phytoplankton and the corresponding influencing factors in front of the outlet in a drinking water reservoir was conducted. Based on the monitoring results, the distribution rules of phytoplankton and the associated factors were analyzed. The results showed that phytoplankton biomass significantly decreased with increasing water depth, but the biomass near the outlet (40 m depth) still reached the WHO level 2 warning threshold for algal blooms multiple times. During the monitoring period, Cyanophyta, Chlorophyta and Bacillariophyta dominated. The selected multisource environmental factors explained 60.5 % of the spatiotemporal changes in phytoplankton, with thermal intensity (water temperature and thermal stratification intensity) being the driving factor. Meanwhile, excessive TN and TP provided necessary conditions for the growth of phytoplankton. Based on influencing factors, reducing upstream nutrient inflows and thermal stratification intensity are recommended as measures to prevent and control algal blooms. This study provides insights into the vertical distribution rules and factors influencing phytoplankton in a drinking water reservoir, which can provide a reference for the management of drinking water reservoirs and the prevention and control of algal blooms.

MODIS Terra and Aqua images bring non-negligible effects to phytoplankton blooms derived from satellites in eutrophic lakes

Phytoplankton-induced lake eutrophication has drawn ongoing interest on a global scale. One of the most popular remote sensing satellite data for observing long-term dynamic changes in phytoplankton is Moderate-resolution Imaging Spectroradiometer (MODIS). However, it is worth noting that MODIS provides two images with different transit times: Terra (local time, about 10:30 am) and Aqua (local time, about 1:30 pm), which may result in a considerable bias in monitoring phytoplankton bloom areas due to the rapid migration of phytoplankton under wind or hydrodynamic conditions. To analyze this quantitatively, we selected MODIS Terra and Aqua images to generate datasets of phytoplankton bloom areas in Lake Taihu from 2003 to 2022. The results showed that Terra more frequently detected larger ranges of phytoplankton blooms than Aqua, whether on daily, monthly, or annual scales. In addition, long-term trend changes, seasonal characteristics, and abrupt years also varied with different transit times. Terra detected mutation years earlier, while Aqua displayed more pronounced seasonal characteristics. There were also differences in sensitivity to climate factors, with Terra being more responsive to temperature and wind speed on monthly and annual scales, while Aqua was more sensitive to nutrient and meteorological factors. These conclusions have also been further confirmed in Lake Chaohu, Lake Dianchi, and Lake Hulun. In conclusion, our findings strongly advocate for a linear relationship to fit Terra to Aqua results to mitigate long-term monitoring errors of phytoplankton blooms in inland lakes (R2 = 0.70, RMSE = 101.56). It is advised to utilize satellite data with transit times between 10 am and 1 pm to track phytoplankton bloom changes and to consider the diverse applications resulting from the transit times of Terra and Aqua.

Investigation of phytoplankton community structure and formation mechanism: a case study of Lake Longhu in Jinjiang

In order to explore the species composition, spatial distribution and relationship between the phytoplankton community and environmental factors in Lake Longhu, the phytoplankton community structures and environmental factors were investigated in July 2020. Clustering analysis (CA) and analysis of similarities (ANOSIM) were used to identify differences in phytoplankton community composition. Generalized additive model (GAM) and variance partitioning analysis (VPA) were further analyzed the contribution of spatial distribution and environmental factors in phytoplankton community composition. The critical environmental factors influencing phytoplankton community were identified using redundancy analysis (RDA). The results showed that a total of 68 species of phytoplankton were found in 7 phyla in Lake Longhu. Phytoplankton density ranged from 4.43 × 105 to 2.89 × 106 ind./L, with the average density of 2.56 × 106 ind./L; the biomass ranged from 0.58-71.28 mg/L, with the average biomass of 29.38 mg/L. Chlorophyta, Bacillariophyta and Cyanophyta contributed more to the total density, while Chlorophyta and Cryptophyta contributed more to the total biomass. The CA and ANOSIM analysis indicated that there were obvious differences in the spatial distribution of phytoplankton communities. The GAM and VPA analysis demonstrated that the phytoplankton community had obvious distance attenuation effect, and environmental factors had spatial autocorrelation phenomenon, which significantly affected the phytoplankton community construction. There were significant distance attenuation effects and spatial autocorrelation of environmental factors that together drove the composition and distribution of phytoplankton community structure. In addition, pH, water temperature, nitrate nitrogen, nitrite nitrogen and chemical oxygen demand were the main environmental factors affecting the composition of phytoplankton species in Lake Longhu.

Characterization of lacustrine harmful algal blooms using multiple biomarkers: Historical processes, driving synergy, and ecological shifts

Harmful algal blooms (HABs) producing toxic metabolites are increasingly threatening environmental and human health worldwide. Unfortunately, long-term process and mechanism triggering HABs remain largely unclear due to the scarcity of temporal monitoring. Retrospective analysis of sedimentary biomarkers using up-to-date chromatography and mass spectrometry techniques provide a potential means to reconstruct the past occurrence of HABs. By combining aliphatic hydrocarbons, photosynthetic pigments, and cyanotoxins, we quantified herein century-long changes in abundance, composition, and variability of phototrophs, particularly toxigenic algal blooms, in China's third largest freshwater Lake Taihu. Our multi-proxy limnological reconstruction revealed an abrupt ecological shift in the 1980s characterized by elevated primary production, Microcystis-dominated cyanobacterial blooms, and exponential microcystin production, in response to nutrient enrichment, climate change, and trophic cascades. The empirical results from ordination analysis and generalized additive models support climate warming and eutrophication synergy through nutrient recycling and their feedback through buoyant cyanobacterial proliferation, which sustain bloom-forming potential and further promote the occurrence of increasingly-toxic cyanotoxins (e.g., microcystin-LR) in Lake Taihu. Moreover, temporal variability of the lake ecosystem quantified using variance and rate of change metrics rose continuously after state change, indicating increased ecological vulnerability and declined resilience following blooms and warming. With the persistent legacy effects of lake eutrophication, nutrient reduction efforts mitigating toxic HABs probably be overwhelmed by climate change effects, emphasizing the need for more aggressive and integrated environmental strategies.

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 (COD_Mn), 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.

Intensified sensitivity and adaptability of zooplankton Bosminidae in subtropical shallow freshwater lakes with increasing trophic level

The deterioration in lake water environments, especially increasing lake eutrophication, is prevalent all over the world, which has seriously affected the balance and stability of the internal ecosystem of lakes. In this study, modern water and sediment samples were collected from three subtropical freshwater lakes with significant differences in nutrient levels to analyze the concentration of the zooplankton Cladocera Bosminidae and its relationship with lakes’ ecological changes. The results show that the deterioration in lake water environments caused by increasing eutrophication limits the survival of most zooplankton. However, the Bosminidae shows a positive adaptability to eutrophication and high sensitivity to the changes in the lake environment. In addition, the lake eutrophication process caused by the intensification of human activities enhances the survival advantage of Bosminidae with more food sources, which is more conducive to its rapid reproduction.

Assessing temporal variability of lake turbidity and trophic state of European lakes using open data repositories

Water turbidity is one of the more important water quality parameters that is strictly linked with the productivity of the lake and is commonly used as an indicator of the trophic state. However, limited field data availability across wide geographic gradients may hinder the conduction of large scale longitudinal studies. In this study, time series of lake turbidity and trophic state index (TSI) between 2002 and 2012 were obtained from the Copernicus Lake Water products to create a large longitudinal dataset of lake variables for 22 European lakes. The dataset was combined with estimates of nutrient concentrations and surface water temperature obtained from the Hydrological Predictions for the Environment (HYPE) and ERA5-Land data repositories, that were used as environmental predictors. Hence, the validity of the lake water quality parameters was tested by a) exploring their spatial and temporal variability and b) identifying associations with the environmental predictors. For this purpose, seasonal Mann-Kendall tests were applied to find significant inter-annual trends of turbidity and TSI for each lake, and generalized additive models (GAMs) were employed to identify the main parameters that shape their temporal dynamics. Although we did not find significant inter-annual changes, our findings highlighted the strong influence of seasonality and surface water temperature in defining the temporal variability patterns in most of the lakes. In addition, the importance of nutrients varied among lakes as several lakes exhibited narrow nutrient gradients reflecting relatively stable nutrient conditions during the examined period. Other lake intrinsic factors, such as local climate and biotic interactions, are important drivers of shaping turbidity and nutrient dynamics. This study highlighted the usefulness of combining lake data from large repositories in conducting large scale spatial studies as a valuable asset for future lake research and management purposes.

The synergistic effect of rising temperature and declining light boosts the dominance of bloom-forming cyanobacteria in spring

Global warming and eutrophication result in rising temperature and declining underwater light, respectively, which affect the shift of the phytoplankton community in spring. However, knowledge of how temperature and light synergistically impact phytoplankton community shifts and cyanobacterial dominance is limited. In this study, we performed a long-term data analysis and an outdoor mesocosm experiment to detect the synergistic effect of temperature and light on shift of phytoplankton community and dominance of bloom-forming cyanobacteria in Lake Taihu, China. The results showed that cyanobacterial biomass was boosted alone and jointly by increased temperature and decreased light levels (sunshine hours and light intensity), and the interaction might be more important than temperature or light levels independently. Chlorophyta biomass was driven by the joint effect of temperature and light levels. Bacillariophyta biomass was mainly affected by light levels, and decreased with declining light levels. Our results emphasize that the interactions of temperature and light have an important impact on the shift of the phytoplankton community in spring. Increasing temperature and declining underwater light boosted the flourishing of cyanobacteria, especially Microcystis, and were adverse to the development of diatoms in spring. Our findings contribute to an increased understanding of the effects of temperature and light on phytoplankton composition shifts and the development of cyanobacterial dominance in spring.

A modified cyanobacteria prediction model based on cellular automata model using N and P concentration reverse data: a case study in Taihu Lake

The problem of algal bloom caused by eutrophication has attracted global attention. Many scholars have studied the problem associated with algae bloom, but few have carried out dynamic monitoring, instead focusing on the formation mechanism of cyanobacteria. For our study of the Taihu Lake in China, we used Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat remote sensing image data from 2017 to establish a prediction model. First, we used MODIS data to retrieve the concentration of N, P, and chlorophyll a in water. Then, we applied the analytic hierarchy process (AHP) model to the inversion results to construct the diffusion potential index. Finally, we used C# to compile the cellular automata (CA) model. We found that the distribution of cyanobacteria predicted by our method was consistent with the algal bloom situation of Taihu Lake in 2017. The results showed that the method effectively predicts the dynamic transfer of cyanobacteria from outbreak to diffusion in a short period of time, which can help decision-makers monitor lake health.

Nitrogen concentration response to the decline in atmospheric nitrogen deposition in a hypereutrophic lake

Atmospheric nitrogen (N) deposition is becoming an increasingly important factor affecting the nutrient level of lakes, especially considering the long-term control measures for external N inputs in developed regions. However, few studies have investigated the effects of atmospheric N deposition and the respective ecological significance in eutrophic waters. In this study, bulk and wet deposition rates of all N species and water N concentrations in Lake Taihu were determined based on the long-term (2010-2018) high-resolution (weekly or monthly) systematic observations. The results indicated that the decline in wind speed and change in land-use type likely decreased the N deposition rate. The bulk N deposition rates decreased from 45.77 kg N ha^-1 yr^-1 in 2012 to 22.06 kg N ha^-1 yr^-1 in 2018, which could account for decrease of 1.01 mg N L^-1 in the lake N concentrations via a rough estimation, and this value was close to the actual variation in N concentration in Lake Taihu. The correlation between N concentrations and atmospheric deposition fluxes was stronger than that between N concentrations and riverine N inputs or lake storage, which further indicated that change in atmospheric N deposition was the key reason for the variation in N concentrations. The direct bulk N deposition into Lake Taihu accounted for 17.5% and 51.4% of the riverine N inputs and lake N inventory, respectively. Moreover, atmospheric N deposition was concentrated in summer, which was dominated by reduced N, and it may be important for the duration of algal blooms. Therefore, external N inputs, including atmospheric N deposition, should be further controlled for an effective mitigation of eutrophication and algal blooms in Lake Taihu.

Linking human activities and global climatic oscillation to phytoplankton dynamics in a subtropical lake

Human activities and climate change are two major stressors affecting lake ecosystems as well as phytoplankton communities worldwide. However, how the temporal dynamics of phytoplankton are directly or indirectly linked to anthropogenic activities and climatic oscillation remains unclear. We assessed the annual trends (1988-2018) in phytoplankton abundance (PA) in Lake Dongting, China and related it to five groups of variables characterizing human activities, global climate oscillation, water nutrients, hydrology, and meteorology. We found a significant increase in PA, urbanization (Upop), total nitrogen (TN), fertilizer application (FA), number of summer days (SU), and the warm speed duration index (WSDI) and a significant decrease in the water discharge of three inlets (TIWD) and the sediment discharge of three inlets (TISD) and four tributaries (FTSD) and the net sediment deposition (NSD). However, no significant annual trends were observed for the number of rainstorm days (R50mm), the simple precipitation intensity index (SDII) and yearly anomalies of El Niño-Southern oscillation events (ENSOi). Cross-correlation Function analyses demonstrated that the operation of the Three George Dam (TGD) strengthened the effects of hydrology, rainfall patterns and ENSOi on phytoplankton, but strongly weakened the association between water nutrients, human activities and phytoplankton abundance. Path analysis revealed that TP, TN, FA, R50 mm as well as WSDI had a direct positive effect on PA, while a direct negative effect was found for ENSO_i, NSD and TISD. Human activities (Upop and FA), warming (WSDI and SU), and rainfall patterns (SDII and R50 mm) exerted indirect controls on phytoplankton through changes in water nutrients and hydrology. Climate change (ENSOi) had a direct effect on PA, but also showed twelve indirect pathways via changes in hydrology and meteorology (both positive and negative effects were found). Overall, meteorology contributed most markedly to the variations of PA (29.3%), followed by hydrology (25.3%), human activities (24%), water nutrients (10.5%), and ENSOi (1.9%). Our results highlight a strongly causal connection between human activities as well as global climate change and phytoplankton and the benefits of considering multiple environmental drivers in determining the temporal dynamics of lake biotic communities.

Atmospheric Stilling Promotes Summer Algal Growth in Eutrophic Shallow Lakes

Simple Summary

The variability of chlorophyll a yields per unit nitrogen (Chla/TN), or phosphorus (Chla/TP) and its influencing factors were evaluated in eutrophic shallow Lake Taihu, China. The results indicated warming and longer sunshine hours promoted Chla/TN and Chla/TP in winter months from 2005 to 2017, which may cause severer blooms in winter and spring. However, a more stable water column due to atmospheric stilling and water level elevation mainly led to the increasing Chla/TN and Chla/TP in remaining months from 2005 to 2017, allowing algae to grow better. The results also indicated that water stability promotes algal growth mainly due to improved light availability. As atmospheric stilling is an aspect of global climate changes, this study would affect future algal bloom mitigation efforts in shallow lakes worldwide.

Abstract

Algal blooms are environmental challenges confronting lakes worldwide and are significantly influenced by chlorophyll a yields per unit phosphorus (Chla/TP), or nitrogen (Chla/TN). Here, the influence of inter-annual hydrometeorological variations on Chla/TP and Chla/TN were evaluated in eutrophic shallow Lake Taihu, China. Our results demonstrated significant increases (p < 0.001) in both Chla/TN and Chla/TP from 2005 to 2017, and increased Chla yields during the winter months were mainly correlated with higher water temperature and longer sunshine hours, which may cause severer blooms in winter and spring. In remaining months from 2005 to 2017, typical associations between atmospheric stilling (or water level elevation) and higher Chla yields were observed. The results also indicate that atmospheric stilling and water level elevation significantly (p < 0.001) decreased background turbidity and promoted buoyant cyanobacterial biomass, alleviating phytoplankton light limitation. Given the subtropical location, eutrophic status, and high background turbidity of Lake Taihu, light may be the critical limiting factor for summer phytoplankton growth; thus, improved light availability would promote Chla yields until self-shading caused further light limitations. If the mechanism is general, promoting the effect of atmospheric stilling on annual peak Chla in shallow lakes may be greatly underestimated, and our finding will affect future bloom mitigation efforts in such systems.

Assessing the potential to use CDOM as an indicator of water quality for the sediment-laden Yellow river, China

Chromophoric dissolved organic matter (CDOM) in rivers is mainly affected by natural conditions and human activities and can reflect the watershed pollution status to a certain extent. The Yellow River is one of the largest contributors to the global riverine sediment flux from the land to ocean, and there is a paucity of information on how the optical properties of CDOM have the potential to serve as an indicator of water quality for the sediment-laden Yellow River. In this study, a three-dimensional fluorescence parallel factor (PARAFAC) analysis method was applied to investigate the seasonal and spatial variations in CDOM fluorescence components and spectral characteristics from the source region to the estuary in the mainstream of Yellow River. The relationships of CDOM with water quality indicators and trophic state were also analyzed. Six PARAFAC components (C1-C6) were identified and grouped into two categories: humic-like components (C1-C4), which accounted for 85.8 %, and protein-like components (C5 and C6), which accounted for only 14.2 %. The CDOM components, spectral parameters, and their clear correlations with the main ions (Na⁺ and Cl^-) all indicated that the humic-like components may be primarily derived from nonpoint source erosion, and the protein-like components were mainly derived from point source discharges in the watershed. The combination of the CDOM absorption coefficient at 254 nm (a(254)), spectral slope ratio (S_R), specific UV absorbance SUVA_254, and fluorescence index (FI) had a good predictive ability for the key water quality indicators (total nitrogen (TN), dissolved total nitrogen (DTN), total phosphorus (TP), dissolved total phosphorus (DTP), and chlorophyll a (Chl a)) and trophic state index (TSI). Therefore, some fluorophores and UV spectral parameters of CDOM in the Yellow River can be used for rapid water quality monitoring and pollution source indication, especially pollutants related to nitrogen and phosphorus nutrients in the basin.

Detecting Climate Driven Changes in Chlorophyll-a Using High Frequency Monitoring: The Impact of the 2019 European Heatwave in Three Contrasting Aquatic Systems

The frequency of heatwave events in Europe is increasing as a result of climate change. This can have implications for the water quality and ecological functioning of aquatic systems. We deployed three spectroradiometer WISPstations at three sites in Europe (Italy, Estonia, and Lithuania/Russia) to measure chlorophyll-a at high frequency. A heatwave in July 2019 occurred with record daily maximum temperatures over 40 °C in parts of Europe. The effects of the resulting storm that ended the heatwave were more discernable than the heatwave itself. Following the storm, chlorophyll-a concentrations increased markedly in two of the lakes and remained high for the duration of the summer while at one site concentrations increased linearly. Heatwaves and subsequent storms appeared to play an important role in structuring the phenology of the primary producers, with wider implications for lake functioning. Chlorophyll-a peaked in early September, after which a wind event dissipated concentrations until calmer conditions returned. Synoptic coordinated high frequency monitoring needs to be advanced in Europe as part of water management policy and to improve knowledge on the implications of climate change. Lakes, as dynamic ecosystems with fast moving species-succession, provide a prism to observe the scale of future change.

Hot moments and hotspots of cyanobacteria hyperblooms in the Curonian Lagoon (SE Baltic Sea) revealed via remote sensing-based retrospective analysis

A temporally and spatially detailed historical (1985-2018) analysis of cyanobacteria blooms was performed in the Curonian Lagoon (Lithuania, Russia), the largest coastal lagoon in the Baltic Sea. Satellite data allowed the mapping of cyanobacteria surface accumulations, so-called "scums", and of chlorophyll-a concentration. The 34-year time series shows a tendency towards later occurrence (October-November) of the cyanobacteria scum presence, whereas the period of its onset (June-July) remains relatively constant. The periods when scums are present, "hot moments", have been consistently increasing in duration since 2008. The differences in the starting, ending and annual duration of cyanobacteria blooms have been significantly altered by hydro-meteorological conditions (river discharge, water temperature, and wind conditions) and their year-round patterns. The most important environmental factors that determined the temporal changes of the scum presence and area were the standing stock of cyanobacteria and the ambient wind conditions. The "hotspots", the areas where the blooms most likely occur, were distributed in the south-southwestern and central parts of the lagoon. The least affected areas were the northern part, which is connected to the coastal waters of the Baltic Sea, and the Nemunas River delta region. The longstanding, well-established spatial patterns of cyanobacteria blooms were linked to hydrodynamic features, namely water renewal time and current patterns, and to potential nutrient sources that included muddy sediments and the locations of colonies of piscivorous birds. Our findings confirmed that the annual and seasonal variations of cyanobacteria blooms and their regulation are a complex issue due to interactions between multiple factors over spatially and temporally broad scales. Despite great progress in the prevention and control of eutrophication and cyanobacteria blooms, the lagoon is still considered to be in a poor ecological status. This work provides a new and missing understanding on the spatial and temporal extent of cyanobacteria blooms and the factors that govern them. Such an understanding can help in planning management strategies, forecasting the magnitude and severity of blooms under changing nutrient loads and potential climate scenarios.

Wind Effects for Floating Algae Dynamics in Eutrophic Lakes

Wind-speed decline is an important impact of climate change on the eastern Asian atmospheric circulation. Although wind does not determine algae biomass in eutrophic lakes, it is a decisive factor in the formation and severity of algae blooms. Based on 2000–2018 MODIS images, this study compared the effects of wind speed on algal blooms in three typical eutrophic lakes in China: Lake Taihu, Lake Chaohu and Lake Dianchi. The results indicate that climate change has different effects on the wind speed of the three lakes, but a common effect on the vertical distribution of algae. A wind speed of 3.0 m/s was identified as the critical threshold in the vertical distribution of chlorophyll-a concentrations in the three study lakes. The basic characteristics of the periodic variation of wind speed were different, but there was a significant negative correlation between wind speed and floating algal bloom area in all three lakes. In addition, considering lake bathymetry, wind direction could be used to identify locations that were particularly susceptible to algae blooms. We estimated that algal bloom conditions will worsen in the coming decades due to the continuous decline of wind, especially in Lake Taihu, even though the provincial and national governments have made major efforts to reduce eutrophication drivers and restore lake conditions. These results suggest that early warning systems should include a wind-speed threshold of 3.0 m/s to improve control and mitigation of algal blooms on these intensively utilized lakes.

Seasonal and long-term trends in the spatial heterogeneity of lake phytoplankton communities over two decades of restoration and climate change

World-wide, reducing the external nutrient loading to lakes has been the primary priority of lake management in the restoration of eutrophic lakes over the past decades, and as expected this has resulted in an increase in the local environmental heterogeneity, and thus biotic heterogeneity, within lakes. However, little is known about how the regional spatial heterogeneity of lake biotic communities changes with restoration across a landscape. Using a long-term monitoring dataset from 20 Danish lakes, we elucidated the seasonal and long-term trends in the spatial heterogeneity of climate, local abiotic variables and phytoplankton communities over two decades of restoration and climate change at landscape level. We found significant seasonality in the spatial heterogeneity of most climatic and local drivers as well as in the total beta diversity (Sørensen coefficient) and its turnover components (Simpson coefficient) of phytoplankton communities among the lakes. The seasonality tended to be less marked in deep than in shallow lakes. We found significant spatial homogenisation of most local drivers (except for alkalinity) and phytoplankton communities after two decades of restoration and that turnover dominated the temporal responses of the total beta diversity of phytoplankton communities. Path analyses showed that the homogenisation of phytoplankton communities was mainly due to a decrease in spatial heterogeneity of total phosphorus and Schmidt stability in shallow lakes and to a decrease in spatial total phosphorus and total nitrogen heterogeneity in deep lakes. However, albeit weakly, the spatial heterogeneity of the phytoplankton communities was affected indirectly by climatic warming in both shallow and deep lakes and directly by wind speed in shallow lakes. We conclude that restoration of eutrophic lakes may lead to an increase in the local heterogeneity of phytoplankton communities at lake scale and an increase in homogeneity at landscape scale.

Modeling cyanobacterial blooms in tropical reservoirs: The role of physicochemical variables and trophic interactions

Understanding the importance of environmental variables on the dominance of cyanobacteria is crucial for appropriately managing water resources. Although studies about temperate and subtropical regions show a high influence of nutrients and temperature on blooms, this relationship is still unclear for the tropics. Accordingly, we hypothesized that nutrients and temperature are the main factors driving cyanobacterial blooms in tropical reservoirs, and those relationships are intensified by the zooplankton. To test these hypotheses, we constructed a structural equation model based on the monitoring of ten reservoirs from Northeast Brazil. We analyzed the effects of physicochemical variables and zooplankton on cyanobacterial blooms and the biomass of four morphotypes. Cyanobacterial biomass varied within the reservoirs, with bloom records (0.2-268.4 mg L^-1) in all of them, primarily constituted by the colonial morphotype, followed by picocyanobacteria, heterocyted, and non-heterocyted filaments. The cyanobacterial community was driven mainly by chemical variables (55.14% of the variation), followed by physical (48.28%), and zooplankton (39.47%). Through the structural equation model, we demonstrated that total cyanobacterial biomass, as well as the morphotypes, were mainly influenced by omnivorous crustaceans and total dissolved phosphorus. Solar radiation, air temperature, mixing zone, and salinity were important to explain the biomass of the morphotypes. The model explained most of the variation in the picocyanobacterial blooms (79.8%), followed by total cyanobacteria (62.4%), heterocyted filaments (59.1%), non-heterocyted filaments (58.2%), and coccoids (55.1%). Zooplankton groups were also influenced by the physicochemical variables, which presented direct and indirect effects on cyanobacteria. Given the predictions of increased eutrophication, warming, and salinization, cyanobacterial blooms will become more intense in tropical reservoirs. Thus, restoring measures must be adopted to reduce bloom development, such as external phosphorus and salt loadings, and biomanipulation.

Application of subfossil Bosmina and its δ13C values in tracing the long-term food web dynamics of shallow eutrophic lakes: A case in Taihu Lake, southeast China

Cladoceran subfossil assemblages have been used successfully to trace the signals of long-term changes in lake eutrophication. However, their potential for reconstructing food webs has not yet been explored extensively. Here, we assess whether the stable carbon isotope analysis (SCIA) of subfossil Bosmina can be used to reconstruct the eutrophication and food web history of a shallow lake in southeast China. Two ²¹⁰Pb-dated sediment cores were collected from the western and central parts of Taihu Lake, one of the largest eutrophic lakes in the region. Multiproxy analyses of the cores were performed, including of the subfossil Bosmina assemblages, stable carbon isotopes of subfossil Bosmina (δ¹³C_s-bos) and bulk sediment (δ¹³C_org), total organic carbon (TOC), loss on ignition (LOI), C/N, total nitrogen (TN), and total phosphorous (TP). Stable carbon isotopes of living algae (δ¹³C_alg) and Bosmina (δ¹³C_l-bos) were also measured at the same sampling locations. The δ¹³C_s-bos gradually declined over time with reciprocal increases in the assemblages of subfossil Bosmina and total cladocerans and in the TOC, LOI, TN and TP in both cores. The δ¹³C_alg and δ¹³C_l-bos values further revealed depleted ¹³C. The changes in the δ¹³C_s-bos in relation to the other proxies indicated rapid nutrient enrichment and a possible shift in the food web in Taihu Lake, providing new insight into the reconstruction of food webs and eutrophication in shallow lakes in southeast China.

Response of Scenedesmus quadricauda (Chlorophyceae) to Salt Stress Considering Nutrient Enrichment and Intracellular Proline Accumulation

Aquatic organisms are exposed to a wide range of salinity, which could critically affect their survival and growth. However, their survival and growth response to salinity stress remain unclear. This study evaluates the growth response and intracellular proline accumulation of green algae, Scenedesmus quadricauda, isolated from brackish water, against dissolved salts stress with N and P enrichment. We tested a hypothesis that nutrient enrichment can relieve the dissolved salts stress of algae by accumulating intracellular proline, thereby improving survival and growth. Four levels of salinity (0, 3, 6, 12 psu) were experimentally manipulated with four levels of nutrient stoichiometry (N:P ratio = 2, 5, 10, 20) at constant N (1 mgN/L) or P levels (0.05 and 0.5 mgP/L). In each set of experiments, growth rate and intracellular proline content were measured in triplicate. The highest level of salinity inhibited the growth rate of S. quadricauda, regardless of the nutrient levels. However, with nutrient enrichment, the alga showed tolerance to dissolved salts, reflecting intracellular proline synthesis. Proline accumulation was most prominent at the highest salinity level, and its maximum value appeared at the highest N:P ratio (i.e., highest N level) in all salinity treatments, regardless of P levels. Therefore, the effects of P and N on algal response to salt stress differ.

Towards the comprehensive water quality control in Lake Taihu: Correlating chlorphyll a and water quality parameters with generalized additive model

In this study, the generalized additive model (GAM) was used to analyze seasonal monitoring data from Lake Taihu, collected from 2010 to 2014, with the aim to explore the correlation between chlorophyll a (Chla) and other water quality parameters. The selected optimal multivariable GAM could effectively explain the concentration variation of Chla occurring during each season, and the interpretation degree followed the order: summer > autumn > spring > winter. The fitting results indicated that the concentration variation of Chla could reflect that of biochemical oxygen demand and chemical oxygen demand in all seasons. In addition, the total phosphorus showed strong ability to explain the concentration change of Chla in spring and summer, as the growth of algae would be affected when the concentration of phosphorus shifted high or low. Nitrogen showed strong ability to explain the variations in Chla concentration in autumn. The conclusions of the optimal multivariable GAM could provide decision basis for the eutrophication control. In other words, the prevention of eutrophication outbreaks could be carried out via the targeted control of key water pollutants. According to these results, the concentration of Chla was higher in northern and western lake during summer and autumn, the management should focus on nutrient input of adjacent rivers.

Calcium promotes formation of large colonies of the cyanobacterium Microcystis by enhancing cell-adhesion

Large Microcystis colonies can lead to the rapid formation of surface accumulations, which are a globally significant environmental issue. Laboratory studies have shown that Ca²⁺ can quickly promote non-classical Microcystis colony formation via cell-adhesion, but our knowledge of the changes in the morphology of these colonies during subsequent long-term culture with Ca²⁺ is limited. In this study, a 72-day cultivation experiment was conducted to determine the long-term effects of Ca²⁺ on Microcystis colony formation. Laboratory results indicate that Ca²⁺ causes Microcystis to rapidly aggregate and form a colony through cell adhesion, then colony formation by cell-adhesion lost dominance, owing to the decrease in Ca²⁺ concentrations caused by precipitation/complexation. Although the initial colony morphology by cell adhesion is sparse, the newly divided cells, without separating from the mother cells, constantly fill the gaps in the original colony at Ca²⁺ concentrations >40 mg L^-1 for a long time, which creates colonies on day 72 with a morphology similar to that of M. ichthyoblabe in Lake Taihu. If the Ca²⁺ levels in Lake Taihu continue to increase, Microcystis growth rate will decrease only slightly, while the colony proportion of total biovolume and biomass will increase. Moreover, higher Ca²⁺ concentrations do not affect microcystin content, but promote the content of bound extracellular polysaccharides (bEPS), enabling formation of larger colonies, which may promote Microcystis surface accumulation.

Benthic cyanobacterial detritus mats in lacustrine sediment: Characterization and odorant producing potential

Eutrophic freshwater lake ecosystems are receiving increasing public attention due to a global increase in large-scale harmful cyanobacterial blooms in surface waters. However, the contribution of phytodetritus accumulation in benthic sediments post-bloom remains unclear. In this study, field investigations were performed using microsensors to evaluate benthic phytodetritus mats by measuring TOC/TN ratios, pigments, biodegradable compounds and odorants as descriptive parameters. Results show that the massive amount of phytodetritus trapped by aquatic plants gradually evolved into benthic cyanobacterial detritus mats, which were characterized as anoxic, reductive and low pH. It was confirmed that the occurrence of odorants is more serious in the detritus mats due to decay and decomposition of the accumulated phytodetritus. The mean odorant content in the vegetated zones was 3-52 times higher than that in the unvegetated zones. The dominant odorants were dimethyl trisulfide (DMTS), β-ionone and β-cyclocitral, with mean contents of 52.38 ng·(g·dw)-1, 162.20 ng·(g·dw)-1 and 307.51 ng·(g·dw)-1, respectively, in the sediment. In addition, odorant production appears to be associated with the distribution of biodegradable compounds in the sediment. This is supported by the marked correlation observed between biodegradable compounds and odorants. Multiple regression analysis showed that biodegradable compounds can be used as indicators to predict odorant content in the sediment. It is noteworthy that the odorant trend in the water column and sediment is symmetrical, indicating a risk of diffusion from the sediment to the water column. This study helps to clarifying the contributions of benthic cyanobacterial detritus mats to odorant production in shallow eutrophic lakes. The information provided herein may also be useful for future management of aquatic ecosystems.

Response of Submerged Aquatic Vegetation to Water Depth in a Large Shallow Lake after an Extreme Rainfall Event

Submerged aquatic vegetation (SAV) is an important part of lake ecosystems, and a proper SAV community structure is the key factor in keeping a clear-water state. Although the response of SAV to water depth has been widely studied in different aquatic environments, little is known about the response of the SAV community to changes in water depth of a large lake after an extreme rainfall event. To examine this question, 780 samples were collected from Lake Taihu, China, between 2013 and 2017 to analyze the variations in SAV and water depth. The water level of the lake ranged from 2.75 to 4.87 m, and the water depth at sampling sites ranged from 1.07 to 3.31 m. The SAV biomass at the sampling sites ranged from 0 to 17.61 kg/m2. The influence of water depth on SAV biomass and frequency of occurrence differed by seasons and by species. The adaptation of SAV species to increasing water depth is a key element for community dynamics, which in turn contributes to water level regulation. A new method was proposed to identify the optimal water depth for SAV biomass accumulation based on calculation of the cumulative probability and probability density.

Allelopathy appraisal of worm metabolites in the synergistic effect between Limnodrilus hoffmeisteri and Potamogeton malaianus on algal suppression

In Chinese Lake Taihu, the algal quantity was significantly larger in summer than late spring (p < 0.01). In summer, compared with the dredged area including neither zoobenthos nor submerged macrophytes, the algal biomass and density were significantly lower in the area filled with the submerged macrophytes. Interestingly, the minimum algal bloom was observed in the combined area containing submerged macrophytes and zoobenthos, which was due to the synergistic interaction between the zoobenthos and the macrophytes. The metabolite extracts from the numerically dominant zoobenthos Limnodrilus hoffmeisteri had significant algal inhibitory effects of Microcystis aeruginosa, and displayed stimulatory effects on seed germination, seedling growth, and peroxidase activity of the prevalent submerged macrophyte Potamogeton malaianus. 27 active compounds in the worm metabolites were identified by gas chromatography-mass spectrometry (GC-MS). Among these compounds three chemicals arachidonic acid, eicosapentaenoic acid, and linoleic acid with concentrations of 13.92 ± 1.11, 10.57 ± 2.52, 2.75 ± 0.73 mg/kg dry weight, respectively, were confirmed as the typical allelochemicals with algal inhibition potential. In short, the metabolites allelopathy of L. hoffmeisteri can form and assist the synergistic effect between L. hoffmeisteri and P. malaianus on algal suppression. Thus, it is feasible to simultaneously restore submerged macrophytes and zoobenthos community in the disturbed eutrophic lakes for removing harmful algae.

Estimation of Kd(PAR) in inland waters across China in relation to the light absorption of optically active components

The comprehensive analysis of the relationships between the attenuation of photosynthetic active radiation (K_d(PAR)) and light absorption is an imperative requirement to retrieve K_d(PAR) from remote sensing data for aquatic environments. The spatial distributions of the K_d(PAR) and light absorption of optically active components (a_OACs) were routinely estimated in China lakes and reservoirs. Spatial K_d(PAR) was relatively dependent on the inorganic particles (average relative contribution of 57.95%). The a_OACs could explain 70-87% of K_d(PAR) variations. A linear model is used to predict K_d(PAR), as a function of light absorption coefficient of phytoplankton (a_phy), colored dissolved organic matter (a_CDOM), and inorganic particles (a_NAP): K_d(PAR) = 0.41 + 0.57 × a_CDOM + 0.96 × a_NAP + 0.57 × a_phy (R² = 0.87, n = 741, p < 0.001). In the lakes with low TSM concentration and non-eutrophic lakes with high TSM, a_CDOM was the most powerful predicting factor on K_d(PAR). In eutrophic lakes with high TSM, a_NAP had the most significant impact on K_d(PAR). This study allowed K_d(PAR) to be predicted from a_OACs values in the inland waters.

Long-Term Spatial and Temporal Monitoring of Cyanobacteria Blooms Using MODIS on Google Earth Engine: A Case Study in Taihu Lake

As cyanobacteria blooms occur in many types of inland water, routine monitoring that is fast and accurate is important for environment and drinking water protection. Compared to field investigations, satellite remote sensing is an efficient and effective method for monitoring cyanobacteria blooms. However, conventional remote sensing monitoring methods are labor intensive and time consuming, especially when processing long-term images. In this study, we embedded related processing procedures in Google Earth Engine, developed an operational cyanobacteria bloom monitoring workflow. Using this workflow, we measured the spatiotemporal patterns of cyanobacteria blooms in China’s Taihu Lake from 2000 to 2018. The results show that cyanobacteria bloom patterns in Taihu Lake have significant spatial and temporal differentiation: the interannual coverage of cyanobacteria blooms had two peaks, and the condition was moderate before 2006, peaked in 2007, declined rapidly after 2008, remained moderate and stable until 2015, and then reached another peak around 2017; bays and northwest lake areas had heavier cyanobacteria blooms than open lake areas; most cyanobacteria blooms primarily occurred in April, worsened in July and August, then improved after October. Our analysis of the relationship between cyanobacteria bloom characteristics and environmental driving factors indicates that: from both monthly and interannual perspectives, meteorological factors are positively correlated with cyanobacteria bloom characteristics, but as for nutrient loadings, they are only positively correlated with cyanobacteria bloom characteristics from an interannual perspective. We believe reducing total phosphorous, together with restoring macrophyte ecosystem, would be the necessary long-term management strategies for Taihu Lake. Our workflow provides an automatic and rapid approach for the long-term monitoring of cyanobacteria blooms, which can improve the automation and efficiency of routine environmental management of Taihu Lake and may be applied to other similar inland waters.

An Enhanced System with Macrophytes and Polyurethane Sponge as an Eco-Technology for Restoring Eutrophic Water: A Pilot Test

Water eutrophication is one of the most serious environmental problems in urban lakes and ponds due to the excessive nutrients. To deal with this problem, the development of methods for supporting ecological rehabilitation has been undertaken. Meanwhile, the trophic interactions during rehabilitation also have been analyzed. In this study, a new technique was employed to solve the water eutrophication problems in an urban pond. To evaluate the water eutrophication at a pilot scale, an enhanced artificial floating-type biological treatment system (FBTS) composed of a floating bed, macrophyte, artificial biofilm carrier (polyurethane sponge) and aerator could be used as equipment for urban pond remediation. In addition, FBTS was employed to decrease the total nitrogen (TN), ammonia-nitrogen (NH3-N), total phosphorus (TP) and chemical oxygen demand (COD) in water. Meanwhile, the changes of water qualities were monitored in the remediation process, and differences in phytoplankton functional group diversity were also registered. Cyanobacteria would decrease after the removal of P, and the diatom assemblage composition changed. The dominant species Cyanophyta were transformed to co-existed with Bacillariophyta, Pyrrophyta and Chlorophyta due to the improvement of water quality. Consequently, this new FBTS could be a promising eco-technology for the removal of nitrogen and phosphorus from eutrophic water, and even could promote the phytoplankton succession.

Seasonal succession and spatial distribution of bacterial community structure in a eutrophic freshwater Lake, Lake Taihu

In aquatic ecosystems, both phytoplankton and bacteria play pivotal roles. Based on 16S rRNA gene sequencing, considerable research focused on phytoplankton colony attached and free-living bacteria has revealed the close relationship between them, and indicated that the entire bacterial community mediates crucial biogeochemical processes in aquatic ecosystems. However, our understanding of their distribution patterns and response to environmental factors remains poor. Besides, picocyanobacteria, which were omitted from attached bacteria analysis, were reported to be important in cyanobacterial blooms. To explore the spatiotemporal variation of the entire bacterial community with their driving environmental factors and detect the relationships among them, we collected 61 water samples spanning one year and the entire Lake Taihu regions for surveying the entire bacterial community. Our results indicated: 1) seasonal variation of the bacterial community composition was stronger than spatial variation due to the clearly seasonal variation of Microcystis, Synechococcus (pico-cyanobacteria) and other bacteria (Actinomycetales, Pirellulaceae and Sphingobacteriaceae); 2) the spatial distribution of the bacterial community showed that different phyla were dominant in different regions; 3) the bacterial co-occurrence networks varied seasonally and were dominated by Microcystis, ACK-M1, Chthoniobacteraceae, Synechococcus, Pirellulaceae and Pelagibacteraceae; 4) phytoplankton density, chlorophyll a, water temperature and total nitrogen were the major factors that drove the spatiotemporal variation of bacterial community composition. This study revealed the seasonal succession and spatial distribution of the entire bacterial community in Lake Taihu, providing new insights into the relationship between water bloom-forming cyanobacterial species and other bacteria, and their response to environmental factors in eutrophic freshwater ecosystem.

Excess nutrient loads to Lake Taihu: Opportunities for nutrient reduction

Intensive agriculture and rapid urbanization have increased nutrient inputs to Lake Taihu in recent decades. This resulted in eutrophication. We aim to better understand the sources of river export of total dissolved nitrogen (TDN) and phosphorus (TDP) to Lake Taihu in relation to critical nutrient loads. We implemented the MARINA-Lake (Model to Assess River Inputs of Nutrients to seAs) model for Lake Taihu. The MARINA-Lake model quantifies river export of dissolved inorganic and organic N and P to the lake by source from sub-basins. Results from the PCLake model are used to identify to what extent river export of nutrients exceeds critical loads. We calculate that rivers exported 61 kton of TDN and 2 kton of TDP to Lake Taihu in 2012. More than half of these nutrients were from human activities (e.g., agriculture, urbanization) in Sub-basins I (north) and IV (south). Most of the nutrients were in dissolved inorganic forms. Diffuse sources contributed 90% to river export of TDN with a relatively large share of synthetic fertilizers. Point sources contributed 52% to river export of TDP with a relatively large share of sewage systems. The relative shares of diffuse and point sources varied greatly among nutrient forms and sub-basins. To meet critical loads, river export of TDN and TDP needs to be reduced by 46-92%, depending on the desired level of chlorophyll-a. There are different opportunities to meet the critical loads. Reducing N inputs from synthetic fertilizers and P from sewage systems may be sufficient to meet the least strict critical loads. A combination of reductions in diffuse and point sources is needed to meet the most strict critical loads. Combining improved nutrient use efficiencies and best available technologies in wastewater treatment may be an effective opportunity. Our study can support the formulation of effective solutions for lake restoration.

Anaerobic ammonium oxidation coupled to ferric iron reduction in the sediment of a eutrophic lake

Anaerobic ammonium oxidation coupled to ferric iron reduction (Feammox) has been assumed to play an important role in nitrogen removal from ecosystems. This study assessed the potential role of Feammox in nitrogen transformation in eutrophic lake sediment using an isotope tracing technique in sediment slurry incubation experiments. Feammox was discovered in eutrophic lake sediment. A significant correlation was found between Feammox rates and iron-reducing rates. Furthermore, the positive correlations between the abundance of iron-reducing bacteria (FeRB), such as Geobacteraceae spp. and Shewanella spp., and Feammox rates indicate that Feammox was mediated by FeRB. The potential rate of Feammox in the isotopic tracer incubation treatment was 0.23-0.43 mg N kg^-1 day^-1. The estimated nitrogen loss caused by Feammox accounts for 5.0-9.2% of the human-induced N input annually into the eutrophic lake. Feammox alone or coupled with anaerobic ammonium oxidation (anammox) and/or denitrification may have an essential role in the nitrogen cycle within eutrophic lake sediment.

Highly time-resolved analysis of seasonal water dynamics and algal kinetics based on in-situ multi-sensor-system monitoring data in Lake Taihu, China

Predicting algal blooms is challenging due to rapid growth rates under suitable conditions and the complex physical, chemical, and biological processes involved. Physico-chemical parameters, monitored in this study by a high-resolution in-situ multi-sensor system and derived from lab-based water sample analyses, show the seasonal variation and have different degrees of vertical gradients across the water column. Through analyzing the changes and relations between multi-factors, we reveal pictures of water quality dynamics and algal kinetics. Nitrate has regular seasonal changes different to the seasonal patterns of total dissolved Phosphorus. Positive correlations are found between Chlorophyll a fluorescence and temperature, wind-induced resuspension and mixing promote the augment of Cyanobacteria fluorescence (Phycocyanin) signal. While the resuspension can also result in the increase of turbidity and affect the light environment for hydrophytes, the algal scums are the main reason for the high turbidity on the surface, which lower the illumination radiation in the water body. Those parameters are the primary dominants responsible for the change of algae from our monitoring data, which could be used as indicators for the dynamic changes of algae in the future.

Identifying multiple stressors that influence eutrophication in a Finnish agricultural river

In Finland, a recent ecological classification of surface waters showed that the rivers and coastal waters need attention to improve their ecological state. We combined eco-hydrological and empirical models to study chlorophyll-a concentration as an indicator of eutrophication in a small agricultural river. We used a modified story-and-simulation method to build three storylines for possible changes in future land use due to climate change and political change. The main objective in the first storyline is to stimulate economic activity but also to promote the sustainable and efficient use of resources. The second storyline is based on the high awareness but poor regulation of environmental protection, and the third is to survive as individual countries instead of being part of a unified Europe. We assumed trade of agricultural products to increase to countries outside Europe. We found that chlorophyll-a concentration in the river depended on total phosphorus concentration. In addition, there was a positive synergistic interaction between total phosphorus and water temperature. In future storylines, chlorophyll-a concentration increased due to land use and climate change. Climate change mainly had an indirect influence via increasing nutrient losses from intensified agriculture. We found that well-designed agri-environmental measures had the potential to decrease nutrient loading from fields, as long as the predicted increase in temperature remained under 2 °C. However, we were not able to achieve the nutrient reduction stated in current water protection targets. In addition, the ecological status of the river deteriorated. The influence of temperature on chlorophyll-a growth indicates that novel measures for shading rivers to decrease water temperature may be needed in the future.