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.

Spatiotemporal dynamics of 2-methylisoborneol produced by filamentous cyanobacteria and associated driving factors in Lake Taihu, China.

The proliferation of filamentous cyanobacteria in lakes can result in the generation of odor-causing compounds, predominantly 2-methylisoborneol (2-MIB), which pose odor-related challenges. In an effort to elucidate the spatiotemporal dynamics of 2-MIB and related influencing factors in East Lake Taihu, monthly investigations were undertaken from April 2022 to March 2023. In addition to the monthly survey, a whole-lake survey was conducted during the high-temperature period from July to September. The monthly survey revealed a distinct unimodal fluctuation in the concentration of 2-MIB in East Lake Taihu, with an average concentration at 297.0 ng/L during the high-temperature period. During the high-temperature period, the filamentous cyanobacterial communities detected in East Lake Taihu consisted primarily of species belonging to genera Leptolyngbya, Oscillatoria, Planktothricoides, and Pseudanabaena. However, no significant correlations were found between their densities and 2-MIB concentration. In addition, the mic gene was predominantly detected in genera Pseudanabaena and Planktothricoides, with the latter being the primary contributor to 2-MIB production. Furthermore, a succession of cyanobacteria capable of producing 2-MIB was detected, with water temperature and radiation intensity being identified as the primary driving factors. The temporal variation of 2-MIB concentration within East Lake Taihu during the whole year was primarily modulated by factors such as water temperature, water transparency, dissolved oxygen, and chlorophyll-a. During the high-temperature period, the 2-MIB concentration in the alga-dominated zone of East Lake Taihu was approximately 1.7 times greater than that in the macrophyte-dominated zone, with nutrient and transparency being identified as the main influencing factors. Consequently, our findings are of great significance for monitoring the sources and variation of 2-MIB in shallow lakes, providing a scientific foundation and theoretical guidance for odor management.

Long-term trend forecast of chlorophyll-a concentration over eutrophic lakes based on time series decomposition and deep learning algorithm.

Long-term trend forecast of chlorophyll-a concentration (Chla) holds significant implications for eutrophication management and pollution control planning on lakes, especially under the background of climate change. However, it is a challenging task due to the mixture of trend, seasonal and residual components in time series and the nonlinear relationships between Chla and the hydro-environmental factors. Here we developed a hybrid approach for long-term trend forecast of Chla in lakes, taking the Lake Taihu as an instantiation case, by the integration of Seasonal and Trend decomposition using Loess (STL), wavelet coherence, and Convolutional Neural Network with Bidirectional Long Short-Term Memory (CNN-BiLSTM). The results showed that long-term trends of Chla and the hydro-environmental factors could be effectively separated from the seasonal and residual terms by STL method, thereby enhancing the characterization of long-term variation. The resonance pattern and time lag between Chla and the hydro-environmental factors in the time-frequency domain were accurately identified by wavelet coherence. Chla responded quickly to variations in TP, but showed a time lag response to variations in WT in Lake Taihu. The forecasting method using multivariate and CNN-BiLSTM largely outperformed the other methods for Lake Taihu with regards to R2, RMSE, IOA and peak capture capability, owning to the combination of CNN for extracting local features and the integration of bidirectional propagation mechanism for the acquisition of higher-level features. The proposed hybrid deep learning approach offers an effective solution for the long-term trend forecast of algal blooms in eutrophic lakes and is capable of addressing the complex attributes of hydro-environmental data.

Cyanobacterial blooms in Lake Taihu: Temporal trends and potential drivers.

Lake Taihu, an inland lake, frequently experiences Cyanobacterial blooms that have historically posed severe threats to its aquatic ecosystem. Combining field observations and satellite remote-sensed data, factors that influence algal bloom intensity in Lake Taihu over an eight-year period, from 2016 to 2023, are examined, and changes in phytoplankton community composition, climate, water quality, economic activities, and food web dynamics are reported. Sentinel-2 MSI data analysis reveals a dramatic decrease in Cyanobacterial blooms in 2023, with a reduction in the annual maximum bloom area of 76.90 % from 2016 values. From 2016 to 2022, the ratio of Cyanobacteria to other phytoplankton ranged 82.09 %-98.29 %, but in 2023, this dropped to 60.98 %. Concurrently, Cyanobacteria density dropped to an historic low of 2.29 × 107 cells/L (16.4 % of 2021 peak values). Redundancy and random forest analyses indicated that nitrogen has a greater influence on phytoplankton than phosphorus, with temperature and permanganate index being the important parameters to affect phytoplankton community structure. We attribute the decrease in Cyanobacterial blooms in Lake Taihu in 2023 to be largely caused by shifts in phytoplankton community structure, particularly the sharp decline in Microcystis sp. density, a genus often linked to bloom formation. Meteorological conditions such as reduced rainfall and wind speed during the winter and spring of 2023 also contributed to diminishing Cyanobacterial blooms. Ongoing improvements in water quality, reduced economic activities because of pandemic restrictions, and implementation of a fishing ban since 2020 have likely further contributed to reductions in bloom frequency. These results improve our understanding of the processes that affect algal blooms in Lake Taihu, and potentially other eutrophic inland lakes.

Wind-driven post-bloom dispersion of Microcystis in a large shallow eutrophic lake: A case study in Lake Taihu.

To clarify the wind-driven post-bloom dispersion range of Microcystis, which originally clustered on the water surface, an Individual-Based Model (IBM) of Microcystis movement considering the combined effects of wind and light was developed based on actual hydrodynamic data and Microcystis biomass. After calibrating the effects of hydrodynamics and light, 66 cases of short-term (within a week) post-bloom with satellite images from 2011 to 2017 were simulated. The results showed that there were three short-term post-bloom types: vertical reduction (VR), horizontal reduction (HR) and mixed reduction (MR). For VR type, the cyanobacterial bloom reduction rate was rapid (>160 km2/day), but the dispersion range of Microcystis was limited (<2 km/day), and a larger bloom area was likely to form in the original location when wind speed decreased. For HR type, the cyanobacterial bloom reduction rate was slow (<10 km2/day), but Microcystis exhibited a broad dispersion range (>4 km/day), often leading to smaller, thicker, and longer-lasting cyanobacterial blooms downwind, albeit with a lower probability of occurrence. The characteristics of MR lay between the two aforementioned types.

Wind-driven hydrodynamic characteristics of Lake Taihu, a large shallow lake in China.

As an essential drinking water source and one of the largest eutrophic shallow lakes in China, the management of Lake Taihu requires an adequate understanding of its hydrodynamic characteristics. Studying the hydrodynamic characteristics of Lake Taihu based on field observations is limited owing to its large area and the lack of flow field stability. Previous studies using hydrodynamic models experienced challenges, such as dimensionality and lack of dynamic response analysis between flow field and realistic wind; therefore, the results were still inconclusive. In this study, a 3D model of Lake Taihu, calibrated and validated based on field observations, was used to simulate and compare three scenarios: windless, steady wind, and realistic wind. The hydrodynamic characteristics of Lake Taihu were analyzed as close to the actual conditions as possible. The results showed that wind-driven currents dominated the flow field in Lake Taihu, and the horizontal velocity driven by wind was more than 6 times that without wind. Observing a stable flow field in Lake Taihu was difficult because of the variability of realistic wind. The hydrodynamic characteristics of Lake Taihu were defined as "strongly affected by wind," "higher on the surface and smaller at the bottom," and "difference between the surface and the bottom." Vertical turbulent kinetic energy can be used to characterize the variable flow field of a wind-driven lake and has a positive correlation with wind speed. Therefore, it could be used as a key component to predict water blooms with practical implications.

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.

Variations of sediment organic phosphorus and organic carbon during the outbreak and decline of algal blooms in Lake Taihu, China.

In this study, sediment organic phosphorus (OP) and organic carbon (OC) in Lake Taihu, China, as well as their relationships, were analyzed during the outbreak and decline of algal blooms (ABs) over a five-month field study. The results showed synchronous temporal changes in the sediment OP and OC contents with the development of ABs. In addition, there was a significant positive correlation between the sediment OP and OC (p < 0.01), suggesting simultaneous deposition and consumption during the ABs outbreak. The sediment OP and OC contents decreased significantly at the early and last stages of the ABs outbreak and increased at the peak of the ABs outbreak and during the ABs decline. These temporal variation patterns suggest that the sediment OC and OP contents did not consistently increase during the ABs outbreak, even though algae are an important source of organic matter in sediments. The depletion or enrichment of OC and OP in sediments may also depend on the scale of the ABs outbreak. The obtained results revealed significant differences in the sediment OC and OP contents between the months (p < 0.05). In addition, OP in the sediments was dominated by orthophosphate diester (phospholipids and DNA-P) and orthophosphate monoester during the ABs outbreak and decline, respectively. The active OC contents and proportions in the sediments in the ABs outbreak were significantly lower than those observed in the ABs decline period, demonstrating the significant impacts of the ABs outbreak and decline on the sediment OC and OP in Lake Taihu.

Microcystis blooms caused the decreasing richness of and interactions between free-living microbial functional genes in Lake Taihu, China.

Microcystis blooms have a marked effect on microbial taxonomical diversity in eutrophic lakes, but their influence on the composition of microbial functional genes is still unclear. In this study, the free-living microbial functional genes (FMFG) composition was investigated in the period before Microcystis blooms (March) and during Microcystis blooms (July) using a comprehensive functional gene array (GeoChip 5.0). The composition and richness of FMFG in the water column was significantly different between these two periods. The FMFG in March was enriched in the functional categories of nitrogen, sulfur, and phosphorus cycling, whereas the FMFG in July was enriched in carbon cycling, organic remediation, and metal homeostasis. Molecular ecological network analysis further demonstrated fewer functional gene interactions and reduced complexity in July than in March. Module hubs of the March network were mediated by functional genes associated with carbon, nitrogen, sulfur, and phosphorus, whereas those in July by a metal homeostasis functional gene. We also observed stronger deterministic processes in the FMFG assembly in July than in March. Collectively, this study demonstrated that Microcystis blooms induced significant changes in FMFG composition and metabolic potential, and abundance-information, which can support the understanding and management of biogeochemical cycling in eutrophic lake ecosystems.

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.

Simultaneous increases of filter-feeding fish and bivalves are key for controlling cyanobacterial blooms in a shallow eutrophic lake.

Eutrophication and cyanobacterial blooms have severely affected many freshwater ecosystems. We studied the effects of filter-feeding fish and bivalves on algal populations using a mesocosm experiment and long-term monitoring data from Lake Taihu (China). The mesocosm study, comprised of a two-way factorial design with the clam Corbicula fluminea and the fish Aristichthys nobilis at three biomass levels, resulted in lower chlorophyll a (Chl a) in high fish treatments, but no significant differences in the low and medium fish treatments. Chl a also decreased with an increase in clam biomass in the high fish treatments. Moreover, filter-feeding fish resulted in a decrease in algal sizes (e.g., the colony size of Microcystis aeruginosa was inversely related to fish biomass) which likely increased the filter-feeding efficiency of bivalves. Biomass of filter-feeding fish was found to be a key factor driving the synergistic effects of filter-feeding fish and bivalves in waters dominated by Microcystis colonies. Long-term monitoring revealed increasing trends in Chl a concentration, total fish catch per unit effort (TF-CPUE), and filter-feeding fish (FF-CPUE), and slightly decreasing trends in bivalve biomass and nitrogen to phosphorus ratios (N:P) from 2006 to 2016. Bivalve biomass and N:P were negatively correlated with Chl a, while FF-CPUE was not significantly related to Chl a. The current filter-feeding fish biomass in Lake Taihu is estimated to be too low to drive synergistic algal control effects together with bivalves. Furthermore, the lack of filter feeders in Lake Taihu may lead to top-down control by predators that cannot counteract the bottom-up effects of nutrients on phytoplankton. Collectively, these long-term monitoring and experimental data support the combined use filter-feeding fish and bivalves for managing cyanobacteria blooms in Lake Taihu.

[Influence of Denitrification on Cyanobacterial Blooms Trends in Lake Taihu, China].

Denitrification is a major process in aquatic ecosystems, and it competes with cyanobacterial growth for nitrogen. However, the effect of denitrification on cyanobacterial blooms under the background of climate change remains unclear. This study explored the interaction between lake denitrification and formation of cyanobacterial blooms, using the historical water quality monitoring data of North Lake Taihu over five years from 2017 to 2021 and via incubation experiments of cyanobacteria and sediment denitrification. The monitoring data showed that algal biomass (Chla as a proxy) primarily peaked during summer and autumn. The seasonal variations in total N concentration showed a completely opposite trend than that of algal biomass, which peaked in winter and spring. Nitrate was the major component of dissolved inorganic nitrogen, and the nitrate concentration was approximately zero in summer and autumn. The total phosphorus concentration varied in the same way as the Chla concentration. The experimental results showed that Cyanobacteria did not grow when the temperature was below 20℃. In comparison, denitrification showed a significant linear relationship with temperatures between 10-25℃ (R2=0.99) and reached the maximum value of (62.98±21.36) µmol·(kg·h)-1 in Lake Taihu at 25℃. Additionally, the nitrate concentration threshold at the maximum denitrification rate was 4 mg·L-1. Cyanobacteria assimilate nitrate for growth, thereby reducing the concentration of nitrate required for denitrification. This study indicated that the advance in lake temperature warming due to climate change may result in earlier growth of cyanobacteria, thereby leading to large amounts of N being assimilated by algae before denitrification, further affecting the dynamics of cyanobacterial blooms. The present results are scientifically important for explaining the mechanism of cyanobacterial bloom rebound in Lake Taihu under the background of recent climate changes.

Framework of wind joint analysis for different lake regions and its effects on the water quality.

Water quality of Lake Taihu (LT) is paid wide attention, and the wind field makes wind-induced flow, significantly impacting the water quality. As a wide lake, the wind field suffers spatial and temporal changes. The correlated relationship among the wind fields for different lake regions has not been studied, and the joint effects of wind field on the water quality is still unknown. Hence, this paper proposed a framework of wind joint analysis for different lake regions and modelling its effects on the water quality, including joint analysis of wind field for different lake regions using Copula function, random time series generation of wind field using Monte-Carlo simulation, and hydrodynamic and water quality numerical simulation. Taking the Lake Taihu (LT) as study case, the joint relationships of wind field for four lake regions were analyzed, and the CODMN, TP and TN distributions under different wind fields were simulated. This paper showed the following: (1) The relationship between the wind speed and direction was weak, and the correlated relationships among the wind fields for four lake regions were significant (ρ > 0.5). (2) The water quality of LT was more influenced by the wind direction rather than the wind speed, with an impacting ratio of ∼4.5. (3) The discharged weighted angle of runoff outflow (DWARO) was a practical index to improve the water quality. When regulating the input/output runoff discharge, water diversion project and water intakes in practice, the administrations should make the DWARO less than or equal to the average wind direction, to decrease the average pollutant concentration and improve the water quality of lake and intake. The proposed framework and results of LT could be extended to other wide shallow lakes to support the environmental management and basin runoff regulation.

How internal nutrient loading forms in shallow lakes: Insights from benthic organic matter mineralization.

Internal nutrient loading in shallow lakes has long been known as a key driver of eutrophication, especially after external loading reductions. Earlier efforts have been made to quantity the size and potential release of internal nutrient pools in lakes. Yet, links among substrates, microbial processes, and the size and actual release of internal nutrient pools remain largely unclear. To assess the links, sediment organic matter in Lake Taihu, China, was characterized by combining optical measurements, and lake-wide sediment gross nitrogen (N) transformations were measured using the stable isotope (15N) dilution technique. Meanwhile, respirations and nutrient fluxes across the sediment-water interface (SWI) were measured by conducting intact core continuous-flow incubations. The cause-effect relationships among sediment physicochemical parameters (especially organic matter properties), gross N transformations, extractable nutrient concentrations, and nutrient fluxes across the SWI were revealed by partial least square path models. Results showed that environmental controls on the N transformation rates at different seasons varied, with sediment-derived dissolved organic matter abundance being more important than other variables in driving the rates during summer blooms. This study put a step toward revealing the significant positive effects of sediment organic matter mineralization on porewater nutrient concentrations and then on nutrient fluxes across the SWI at late season. The significant positive correlation between the gross N mineralization rates and ammonium fluxes across the SWI and the estimated considerable volume of net N mineralization in summer further suggested that algal blooms can get substantial inorganic N from sediment N mineralization during the lake N limitation period. Overall, this paper presents new insights into the substrates- and microbial process-driven internal nutrient loading of shallow lakes, which is the fundamental driving force of internal nutrient loading formation.

Macroinvertebrate Response to Internal Nutrient Loading Increases in Shallow Eutrophic Lakes.

In eutrophic lakes, even if external loading is controlled, internal nutrient loading delays the recovery of lake eutrophication. When the input of external pollutants is reduced, the dissolved oxygen environment at the sediment interface improves in a season without algal blooms. As an important part of lake ecosystems, macroinvertebrates are sensitive to hypoxia caused by eutrophication; however, how this change affects macroinvertebrates is still unknown. In this study, we analysed the monitoring data of northern Lake Taihu from 2007 to 2019. After 2007, the external loading of Lake Taihu was relatively stable, but eutrophication began to intensify after 2013, and the nutrients in the sediments also began to decline, which was related to the efficient use of nutrients by algal blooms. The community structure and population density of macroinvertebrates showed different responses in different stages. In particular, the density of oligochaetes and the Shannon-Wiener index showed significant differences in their response to different stages, and their sensitivity to eutrophication was significantly reduced. Under eutrophication conditions dominated by internal loading, frequent hypoxia occurs at the sediment interface only when an algal bloom erupts. When there is no bloom, the probability of sediment hypoxia is significantly reduced under the disturbance of wind. Our results indicate that the current method for evaluating lake eutrophication based on oligochaetes and the Shannon-Wiener diversity index may lose its sensitivity.

Variable promotion of algae and macrophyte organic matter on methanogenesis in anaerobic lake sediment.

Shallow lakes are an important natural source of atmospheric methane (CH4), and the input of autochthonous organic matter (OM) into their sediments encourages methanogenesis. Although algal- and macrophytic-originated OM in these lakes are expected to have different impacts on methanogenesis and methanogenic archaeal communities in lake sediments owing to their various properties, their specific influence and role in sediment remain unclear. In this study, a 148-day incubation was carried out by adding algal- and macrophytic-OM to the sediments of shallow eutrophic Lake Chaohu and Lake Taihu in China. CH4 was periodically monitored, while the methanogens were examined via qPCR and high-throughput sequencing at the end of incubation. Algal-OM stimulated CH4 production more than macrophytic-OM in both sediments, with the rates initially increasing and then decreasing before reaching a relative constant. Macrophytic-OM promoted CH4 production to a comparable extent in both lakes, while algal-OM promoted greater CH4 in Lake Chaohu than in Lake Taihu. However, algal-OM did not significantly increase mcrA gene copies, while macrophytic-OM did by 17.0-20.1-fold. Algal-OM potentially promoted the methylotrophic pathway in Lake Taihu but did not change the methanogenic structure in Lake Chaohu. Comparatively, macrophytic-OM promoted CH4 production mainly by acetoclastic methanogen proliferation in both lakes. More CH4 release with algal-OM compared to macrophytic-OM deserves further attention owing to the prevailing increasing algal blooms and the declining macrophyte population in lakes.

The unprecedented 2022 extreme summer heatwaves increased harmful cyanobacteria blooms.

Heatwaves are increasing and expected to intensify in coming decades with global warming. However, direct evidence and knowledge of the mechanisms of the effects of heatwaves on harmful cyanobacteria blooms are limited and unclear. In 2022, we measured chlorophyll-a (Chla) at 20-s intervals based on a novel ground-based proximal sensing system (GBPSs) in the shallow eutrophic Lake Taihu and combined in situ Chla measurements with meteorological data to explore the impacts of heatwaves on cyanobacterial blooms and the potential relevant mechanisms. We found that three unprecedented summer heatwaves (July 4-15, July 22-August 16, and August 18-23) lasting a total of 44 days were observed with average maximum air temperatures (MATs) of 38.1 ± 1.9 °C, 38.7 ± 1.9 °C, and 40.2 ± 2.1 °C, respectively, and that these heatwaves were characterized by high air temperature, strong PAR, low wind speed and rainfall. The daily Chla significantly increased with increasing MAT and photosynthetically active radiation (PAR) and decreasing wind speed, revealing a clear promotion effect on harmful cyanobacteria blooms from the heatwaves. Moreover, the combined effects of high temperature, strong PAR and low wind, enhanced the stability of the water column, the light availability and the phosphorus release from the sediment which ultimately boosted cyanobacteria blooms. The projected increase in heatwave occurrence under future climate change underscores the urgency of reducing nutrient input to eutrophic lakes to combat cyanobacteria growth and of improving early warning systems to ensure secure water management.

Burial or mineralization: Origins and fates of organic matter in the water-suspended particulate matter-sediment of macrophyte- and algae-dominated areas in Lake Taihu.

Increased algal blooms and loss of aquatic vegetation are critical environmental issues associated with shallow lakes worldwide. The increase in organic matter (OM) in both macrophyte-dominated areas (MDAs) and algae-dominated areas (ADAs) has exacerbated these problems. Most OM in water is concentrated as suspended particulate matter (SPM), which eventually migrates to the sediment. However, the detailed origins and fates of OM in water-SPM-sediment systems with coexisting MDAs and ADAs remain unclear. Therefore, in this study, we conducted monthly field investigations in Lake Taihu, focusing on OM-migration patterns in an MDA and an ADA. The C/N mass ratios, δ13C contents, and OM compositions of the water, SPM, and sediment were analyzed. Our findings revealed that autochthonous sources of OM prevailed in water, whereas terrestrial sources prevailed in SPM and sediment. Rapid decomposition processes of microbial- and algae-derived dissolved OM were discovered along the water-SPM-sediment pathways in both areas. A trend towards a shift from macrophytes to algae in the MDA was also discovered. Overall, the entire lake underwent a burial process of OM in both types of areas, with mineralization mostly occurring during the algal-bloom seasons and more strongly in the ADA. Furthermore, we deduced that a decrease in the OM-burial rate, but an increase in the mineralization rate, might occur after a complete shift from a macrophyte- to an algae-dominated status. Such a shift might change the carbon-cycle process in eutrophic shallow lakes and should be given more attention in future research.

Temporal characteristics and trends of nitrogen loadings in lake Taihu, China and its influencing mechanism at multiple timescales.

Climate warming impact on excessive nitrogen (N) load in sediment favours cyanobacterial blooms in eutrophic waters. The nitrate (NO3--N) and ammonium (NH4+-N) are two forms of N loads that contribute to algae blooms. However, little attention is paid to the impact of environmental factors on N loads variations at different time scales. This paper used a well-calibrated and validated EFDC model to investigate the temporal patterns and trends of ammonium and nitrate from June 2016 to June 2017. This paper presented the relationship and effects between these variations and environmental factors using data from satellite and reanalysis-based observations obtained for six meteorological parameters. The relationship and effects between these variations and environmental factors were also examined at different timescales (i.e., daily, monthly and seasonal scales). Model calibration results indicated that measured values reasonably matched simulated values. The validation results revealed that relative error (RE) values were within an acceptable range. The REs of ammonium at East Taihu (S12) and Xu Lake (S23) sampling sites were 55.83% and 57.61%, while that of nitrate was 24.37% (S12) and 41.08%, respectively. The daily analysis of NH4+-N and NO3--N variations was 7.318 ± 3.876 (g/m2/day) and 0.0275 ± 0.222 (g/m2/day), respectively. The monthly analysis showed NH4+-N and NO3-N range from 2.04 to 12.04 (g/m2/day) and 0.0008 to 0.064 (g/m2/day), respectively. The magnitude NH4+-N and NO3--N varied and showed distinct inter-monthly variations. , The relationship between sediment fluxes and meteorological parameters showed the magnitude of correlation coefficient (r) and strength of correlation varied significantly. At daily scales, the relationship of NH4+-N and NO3--N had a significant positive correlation with all meteorological parameters. At monthly, the correlation coefficient (r) of NH4+-N and NO3-N were heterogenous. At daily and monthly scales, air temperature and wind speed are the main drivers affecting sediment N loads' dynamics; however, the influence of relative humidity, precipitation, and evaporation on N loads are smaller. The study demonstrates the contribution of meteorological conditions to the magnitude and timing of N loadings variability in water bodies. The findings provide more insight into lake ecosystem protection and environmental remediation.

Contributions of meteorology and nutrient to the surface cyanobacterial blooms at different timescales in the shallow eutrophic Lake Taihu.

Quantitative assessments of the contributions of various environmental factors to cyanobacterial blooms at different timescales are lacking. Here, the hourly cyanobacterial bloom intensity (CBI) index, a proxy for the intensity of surface cyanobacterial biomass, was obtained from the geostationary satellite sensor Geostationary Ocean Color Imager (GOCI) over the years 2011-2018. Generalized additive model was applied to determine the responses of monthly and hourly CBI to the perturbations of meteorological factors, water stability and nutrients, with variation partitioning analysis used to analyze the relative importance of the three groups of variables to the inter-monthly variation of diurnal CBI in each season. The effects of environmental factors on surface cyanobacterial blooms varied at different timescales. Hourly CBI increased with increasing air temperature up to 18 °C but decreased sharply above 18 °C, whereas monthly CBI increased with increasing air temperature up to 30 °C and stabilized thereafter. Among all the environmental factors, air temperature had the largest contribution to the intra-daily variation in CBI; water stability had the highest explanation rate for the inter-monthly variation of diurnal CBI during summer (42.3 %) and autumn (56.9 %); total phosphorus explained the most variation in monthly CBI (18.5 %). Compared with cyanobacterial biomass (CB) in the water column, high light and low wind speed caused significantly lower CBI in July and higher CBI in November respectively. Interestingly, cyanobacterial blooms at the hourly scale were aggravated by climate warming during winter and spring but inhibited during summer and autumn. Collectively, this study reveals the effects of environmental factors on surface cyanobacterial blooms at different timescales and suggests the consideration of the hourly effect of air temperature in short-term predictions of cyanobacterial blooms.