The influence of water quality variables on cyanobacterial blooms and phytoplankton community composition in a shallow temperate lake

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.

Increasing cascade dams in the upstream area reduce nutrient inputs to the Three Gorges Reservoir in China

The upstream cascade dams play an essential role in the nutrient cycle in the Yangtze. However, there is little quantitative information on the effects of upstream damming on nutrient retention in the Three Gorges Reservoir (TGR) in China. Here, we aim to assess the impact of increasing cascade dams in the upstream area of the Yangtze on Dissolved Inorganic Nitrogen and Phosphorus (DIN and DIP) inputs to the TGR and their retention in the TGR and to draw lessons for other large reservoirs. We implemented the Model to Assess River Inputs of Nutrients to seAs (MARINA-Nutrients China-2.0 model). We ran the model with the baseline scenario in which river damming was at the level of 2009 (low) and alternative scenarios with increased damming. Our scenarios differed in nutrient management. Our results indicated that total water storage capacity increased by 98 % in the Yangtze upstream from 2009 to 2022, with 17 new large river dams (>0.5 km3) constructed upstream of the Yangtze. As a result of these new dams, the total DIN inputs to the TGR decreased by 15 % (from 768 Gg year-1 to 651 Gg year-1) and DIP inputs decreased by 25 % (from 70 Gg year-1 to 53 Gg year-1). Meanwhile, the molar DIN:DIP ratio in inputs to the TGR increased by 13 % between 2009 and 2022. In the future, DIN and DIP inputs to the TGR are projected to decrease further, while the molar DIN:DIP ratio will increase. The Upper Stem contributed 39 %-50 % of DIN inputs and 63 %-84 % of DIP inputs to the TGR in the past and future. Our results deepen our knowledge of nutrient loadings in mainstream dams caused by increasing cascade dams. More research is needed to understand better the impact of increased nutrient ratios due to dam construction.

Spatiotemporal dynamics of phytoplankton biomass and community succession for driving factors in a meso-eutrophic lake

Effects of climate change and nutrient load caused by human activities on lake phytoplankton blooms have attracted much attention globally. However, their roles and synergistic effects on phytoplankton biomass and community historical succession are not well understood, especially for meso-eutrophic plateau lakes. In this study, a multi-year (1997-2022) monthly dataset including hydro-chemical and meteorological indicators of the meso-eutrophic plateau lake Erhai in China, was used to explore the contributions of climate change and nutrients on phytoplankton biomass variation and community succession. Phytoplankton biomass increased from 1997 to 2006, slowly decreased from 2006 to 2015, then increased again from 2015 to 2022, according to a generalised additive model (GAM). Alongside warming, nitrogen, phosphorus and organic matter are key drivers of long-term interannual variation in phytoplankton biomass and historical succession of the phytoplankton community. The extensive blooms in recent years were strongly associated with both organic matter accumulation and global warming. Phytoplankton biomass in northern and southern districts was greater than in central areas, with Cyanophyta and Pyrrophyta dominating in the north and Chlorophyta prevalent in the south. Since 2015, phytoplankton diversity has increased significantly, and biomass has declined in the southern district but increased markedly in the northern district. Spatial heterogeneity was caused by the spatial distribution of nutrients and the buoyancy regulation capacity of cyanobacteria. The results demonstrate that bloom mitigation responds strongly to nitrogen and phosphorus control in meso-eutrophic lakes, therefore preventing and controlling blooms through nitrogen and phosphorus reduction is still an effective measure. Given the accumulation of organic matter in recent years, synergistic control of organic matter and total nitrogen and phosphorus could effectively reduce the risk of cyanobacterial and dinoflagellate blooms.

Temporal patterns of algae in different urban lakes and their correlations with environmental variables in Xi'an, China

Urban lakes were critical in aquatic ecology environments, but how environmental factors affected the distribution and change characteristics of algal communities in urban lakes of Xi'an city was not clearly. Here, we investigated the algal community structure of six urban lakes in Xi'an and evaluated the effects of water quality parameters on algae. The results indicated that the significant differences on physicochemical parameters existed in different urban lakes. The maximum concentration of total phosphorus in urban lakes was (0.18 ± 0.01) mg/L and there was a phenomenon of phosphorus limitation. In addition, 51 genera of algae were identified and Chlorella sp. was the dominant algal species, which was affiliated with Chlorophyta. Network analysis elucidated that each lake had a unique algal community network and the positive correlation was dominant in the interaction between algae species, illustrating that mature microbial communities existed or occupied similar niches. Redundancy analysis illustrated that environmental factors explained 47.35% variance of algal species-water quality correlation collectively, indicating that water quality conditions had a significant influence on the temporal variations of algae. Structural equation model further verified that algal community structure was directly or indirectly regulated by different water quality conditions. Our study shows that temporal patterns of algal communities can reveal the dynamics and interactions of different urban ecosystem types, providing a theoretical basis for assessing eutrophication levels and for water quality management.

Self-optimization of training dataset improves forecasting of cyanobacterial bloom by machine learning

Data-driven model (DDM) prediction of aquatic ecological responses, such as cyanobacterial harmful algal blooms (CyanoHABs), is critically influenced by the choice of training dataset. However, a systematic method to choose the optimal training dataset considering data history has not yet been developed. Providing a comprehensive procedure with self-based optimal training dataset-selecting algorithm would self-improve the DDM performance. In this study, a novel algorithm was developed to self-generate possible training dataset candidates from the available input and output variable data and self-choose the optimal training dataset that maximizes CyanoHAB forecasting performance. Nine years of meteorological and water quality data (input) and CyanoHAB data (output) from a site on the Nakdong River, South Korea, were acquired and pretreated via an automated process. An artificial neural network (ANN) was chosen from among the DDM candidates by first-cut training and validation using the entire collected dataset. Optimal training datasets for the ANN were self-selected from among the possible self-generated training datasets by systematically simulating the performance in response to 46 periods and 40 sizes (number of data elements) of the generated training datasets. The best-performing models were screened to identify the candidate models. The best performance corresponded to 6-7 years of training data (∼18 % lower error) for forecasting 1-28 d ahead (1-28 d of forecasting lead time (FLT)). After the hyperparameters of the screened model candidates were fine-tuned, the best-performing model (7 years of data with 14 d FLT) was self-determined by comparing the forecasts with unseen CyanoHAB events. The self-determined model could reasonably predict CyanoHABs occurring in Korean waters (cyanobacteria cells/mL ≥ 1000). Thus, our proposed method of self-optimizing the training dataset effectively improved the predictive accuracy and operational efficiency of the DDM prediction of CyanoHAB.

Gloeotrichia pisum in Lake Kinneret: A successful epiphytic cyanobacterium

With climate change and re-oligotrophication of lakes due to restoration efforts, the relative importance of benthic cyanobacteria is increasing, but they are much less studied than their planktonic counterparts. Following a major water level rise event that inundated massive reed stands in Lake Kinneret, Israel, we discovered the appearance of a vast abundance of Gloeotrichia pisum (cyanobacteria). This provided an opportunity to investigate the biology and ecology of a benthic epiphytic colonial cyanobacterium, proliferating under altered environmental conditions, with possible toxin production potential and as a model for an invasive epiphyte. The species was identified by its typical morphology, and by sequencing its 16S rRNA gene and the intragenic space. We report on the abundance and spatial distribution of the detected colonies, their morphological characteristics, and pigment composition. High phycoerythrin content provides a brownish color and supports growth at low light levels. Genomic community composition analysis revealed that G. pisum colonies host a diverse microbial community of microalgae, cyanobacteria, bacteria, and archaea with a conserved and characteristic taxonomic composition. The Synechococcales order showed high relative abundance in the colony, as well as other prokaryotes producing secondary metabolites, such as the rhodopsin producer Pseudorhodobacter. The microbial consortium in the colonies performed nitrogen fixation. The diazotroph's phylogenetic relations were demonstrated. Tests for the presence of cyanotoxins (microcystin and cylindrospermopsin) proved negative. This study is the first documentation of this genus in Israel, providing insights into the invasive nature of G. pisum and the ecological implications of its appearance in a lake ecosystem.

Phycocyanin-rich Synechococcus dominates the blooms in a tropical estuary lake

Cyanobacterial blooms challenge the safe water supply in estuary reservoirs. Yet, data are limited for the variation of phytoplankton dynamics during an algal bloom event at refined scales, which is essential for interpreting the formation and cessation of blooms. The present study investigated the biweekly abundances and dynamics of pico- and nano-phytoplankton in a tropical estuary lake following a prolonged bloom event. Flow cytometry analysis resolved eight phenotypically distinct groups of phytoplankton assigned to nano-eukaryotes (nano-EU), pico/nano-eukaryotes (PicoNano-EU), cryptophyte-like cells (CRPTO), Microcystis-like cells (MIC), pico-eukaryotes (Pico-EU) and three groups of Synechococcus-like cells. Total phytoplankton abundance ranged widely from 2.4 × 104 to 2.8 × 106 cells cm-3. The phytoplankton community was dominated by Synechococcus-like cells with high phycocyanin content (SYN-PC). Temporal dynamics of the phytoplankton community was phytoplankton- and site-specific. Peak values were observed for SYN-PC, SYN-PE2 (Synechococcus-like cells with low levels of phycoerythrin) and Pico-EU, while the temporal dynamics of other groups were less pronounced. Redundancy analysis (RDA) showed the importance of turbidity as an abiotic factor in the formation of the current SYN-PC induced blooms, and Spearman correlation analysis suggested a competitive relationship between SYN-PC and Pico-EU.

Spatio-Temporal Dynamics in Physico-Chemical Properties, Phytoplankton and Bacterial Diversity as an Indication of the Bovan Reservoir Water Quality

The study aimed to investigate the physico-chemical properties as well as phytoplankton and bacterial community diversity of Bovan Lake reservoir in Serbia to gain insight into the seasonal dynamic of water quality. All analyses were performed at three localities and water depths in spring, summer, autumn, and winter 2019. Seven phytoplankton phyla comprising 139 taxa were detected at all three localities (Chlorophyta 58%, Bacillariophyta 14%, Cyanobacteria 9%, Chrysophyta 5%, Dinophyta 5%, Euglenophyta 5%, and Cryptophyta 4%). Winter 2019 was characterized by the presence of 36 unique species in all phyla except Euglenophyta. Bacterial diversity analyses showed that Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, and Verrucomicrobia dominated the water intake locality at all three water depths (0.5, 10, and 20 m below the surface). In general, the physico-chemical parameters, phytoplankton, and bacterial community composition depended on the season and the water depth and showed that Bovan Lake was of satisfactory ecological status and water quality at all localities, and meets the needs for all intended purposes.

Effects of Grazing and Nutrients on Phytoplankton Blooms and Microplankton Assemblage Structure in Four Temperate Lakes Spanning a Eutrophication Gradient

Phytoplankton assemblage dynamics are sensitive to biotic and abiotic factors, as well as anthropogenic stressors such as eutrophication, and thus are likely to vary between lakes of differing trophic state. We selected four lakes in Washington State, USA, ranging from oligo- to hypereutrophic, to study the separate and interactive effects of enhanced nutrient availability and zooplankton grazing on phytoplankton net growth rates and overall microplankton (phytoplankton and microzooplankton) assemblage structure. We collected water quality and plankton samples monthly in each lake from May to October 2014, and also conducted laboratory incubation experiments using ambient plankton assemblages from each lake with amendments of zooplankton grazers (5× ambient densities) and nutrients (Nitrogen + Phosphorus) in June, August, and October. In each set of monthly experiments, nested two-way ANOVAs were used to test the effects of enhanced grazers and nutrients on net chlorophyll a-based phytoplankton growth rates. Nested PERMANOVAs were used to test the effects of each factor on microplankton assemblage structure. Enhanced grazing reduced phytoplankton net growth in oligotrophic Cle Elum Lake and oligo-mesotrophic Lake Merwin in August (p < 0.001) and Merwin again in October (p < 0.05), while nutrient enhancement increased phytoplankton net growth in Lake Merwin in June (p < 0.01). Changes in microplankton assemblage composition were not detected as a result of either factor, but they were significantly different between sites (p < 0.001) during each month, and varied by month within each lake. Significant effects of both enhanced grazers and nutrients were detected in systems of low, but not high, trophic state, although this varied by season. We suggest that it is critical to consider trophic state when predicting the response of phytoplankton to bottom-up and top-down factors in lakes.

Biogeographic distribution patterns of algal community in different urban lakes in China: Insights into the dynamics and co-existence

Urban lake ecosystems are significant for social development, but currently we know little about the geographical distribution of algal community in urban lakes at a large-scale. In this study, we investigated the algal community structure in different areas of urban lakes in China and evaluated the influence of water quality parameters and geographical location on the algal community. The results showed that obvious differences in water quality and algal communities were observed among urban lakes in different geographical areas. Chlorophyta was the dominant phylum, followed by cyanobacteria in all areas. The network analysis indicated that algal community composition in urban lakes of the western and southern area showed more variations than the eastern and northern areas, respectively. Redundancy analysis and structural equation model revealed that nutrients and pH were dominant environmental factors that affected the algal community, and they showed higher influence than that of iron, manganese and COD _Mn concentration. Importantly, algal community and density exhibited longitude and latitude relationship. In general, these results provided an ecological insight into large-scale geographical distributions of algal community in urban lakes, thereby having potential applications for management of the lakes.

Intraseasonal variation of phycocyanin concentrations and environmental covariates in two agricultural irrigation ponds in Maryland, USA

Recently, cyanobacteria blooms have become a concern for agricultural irrigation water quality. Numerous studies have shown that cyanotoxins from these harmful algal blooms (HABs) can be transported to and assimilated into crops when present in irrigation waters. Phycocyanin is a pigment known only to occur in cyanobacteria and is often used to indicate cyanobacteria presence in waters. The objective of this work was to identify the most influential environmental covariates affecting the phycocyanin concentrations in agricultural irrigation ponds that experience cyanobacteria blooms of the potentially toxigenic species Microcystis and Aphanizomenon using machine learning methodology. The study was performed at two agricultural irrigation ponds over a 5-month period in the summer of 2018. Phycocyanin concentrations, along with sensor-based and fluorometer-based water quality parameters including turbidity (NTU), pH, dissolved oxygen (DO), fluorescent dissolved organic matter (fDOM), conductivity, chlorophyll, color dissolved organic matter (CDOM), and extracted chlorophyll were measured. Regression tree analyses were used to determine the most influential water quality parameters on phycocyanin concentrations. Nearshore sampling locations had higher phycocyanin concentrations than interior sampling locations and "zones" of consistently higher concentrations of phycocyanin were found in both ponds. The regression tree analyses indicated extracted chlorophyll, CDOM, and NTU were the three most influential parameters on phycocyanin concentrations. This study indicates that sensor-based and fluorometer-based water quality parameters could be useful to identify spatial patterns of phycocyanin concentrations and therefore, cyanobacteria blooms, in agricultural irrigation ponds and potentially other water bodies.

Effect of Water Column Stability on Surface Chlorophyll and Time Lags under Different Nutrient Backgrounds in a Deep Reservoir

Hydrodynamic conditions are considered to be very important in the control of algal blooms. Weekly or daily measurements may miss some important events in the hydrodynamic process, resulting in inaccurate evaluations of the impacts of hydrodynamics on phytoplankton. In this study, high-frequency (15-min interval) measurements were used to analyze the effect of water column stability on surface chlorophyll a (Chl a) and lag time under different nutrient backgrounds during a cyanobacterial bloom in the Three Gorges Reservoir, China. Cross-correlation analysis between the relative water column stability (RWCS) and Chl a was performed at different stages. The results showed that the RWCS above the euphotic depth influenced the surface Chl a concentration most significantly. A lower RWCS (<20) limited the increase in the Chl a concentration, and a higher RWCS caused a significant increase in Chl a only when nutrients were not limited (TN/TP < 29) and light and temperature conditions were suitable. It took a short time for a higher RWCS to significantly increase the surface Chl a concentration compared with a lower RWCS. When the waterbody had a very low Chl a concentration (almost 0), approximately 2 days were needed to significantly increase the Chl a concentration, while approximately only half an hour was needed when the background concentration of Chl a was slightly higher. During the bloom period, a decline in the RWCS significantly decreased the Chl a in a very short time (approximately half an hour). Reducing the water column stability could be a good approach to control cyanobacterial blooms.

Phytoplankton nutrient dynamics and flow cytometry based population study of a eutrophic wetland habitat in eastern India, a Ramsar site

Phytoplankton diversity, their abundance based on flow cytometric (FCM) analysis and seasonal nutrient dynamics were investigated from a waste water fed wetland of Eastern India (88° 24.641'E and 22° 33.115'N). The primary objective of the study was to correlate the seasonal fluctuations in phytoplankton abundance to the environmental variables. Total chlorophyll content and FCM based cell counts were used to characterize and quantify the phytoplankton population. Multivariate statistical methods were employed in predicting the possible relationships between biotic and abiotic variables. Distinct seasonal variations characterized by high abundance during the pre-summer period compared to other seasons were detected. The results indicated that environmental factors like water temperature and nutrients, such as various forms of nitrogen and phosphate, influenced the seasonal phytoplankton accumulation. Cluster analysis and non-metric multidimensional scaling helped analyze the seasonal distribution of phytoplankton based on their composition. The dominant genera among the entire phytoplankton community were Scenedesmus spp. of Chlorophyta, followed by Merismopedia spp. of Cyanoprokaryota. Around 3.7 × 105 phytoplankton mL-1 were recorded during the study period. Due to the very high count of individual species in the community, FCM based counting was applied for determination of Species Diversity Index. The entire population was divided into 13 subpopulations based on the cell sorting method and the seasonal abundance in each sub-population was illustrated.

Algal Blooms and Cyanotoxins in Jordan Lake, North Carolina

The eutrophication of waterways has led to a rise in cyanobacterial, harmful algal blooms (CyanoHABs) worldwide. The deterioration of water quality due to excess algal biomass in lakes has been well documented (e.g., water clarity, hypoxic conditions), but health risks associated with cyanotoxins remain largely unexplored in the absence of toxin information. This study is the first to document the presence of dissolved microcystin, anatoxin-a, cylindrospermopsin, and β-N-methylamino-l-alanine in Jordan Lake, a major drinking water reservoir in North Carolina. Saxitoxin presence was not confirmed. Multiple toxins were detected at 86% of the tested sites and during 44% of the sampling events between 2014 and 2016. Although concentrations were low, continued exposure of organisms to multiple toxins raises some concerns. A combination of discrete sampling and in-situ tracking (Solid Phase Adsorption Toxin Tracking [SPATT]) revealed that microcystin and anatoxin were the most pervasive year-round. Between 2011 and 2016, summer and fall blooms were dominated by the same cyanobacterial genera, all of which are suggested producers of single or multiple cyanotoxins. The study's findings provide further evidence of the ubiquitous nature of cyanotoxins, and the challenges involved in linking CyanoHAB dynamics to specific environmental forcing factors are discussed.

Multivariate analyses of the effect of an urban wastewater treatment plant on spatial and temporal variation of water quality and nutrient distribution of a tropical mid-order river

Freshwater resources are increasingly scarce due to human activities, and the understanding of water quality variations at different spatial and temporal scales is necessary for adequate management. Here, we analyze the hypotheses that (1) the presence of a wastewater treatment plant (WWTP) and (2) a polluted tributary that drains downstream from the WWTP change the spatial patterns of physicochemical variables (pH, turbidity, dissolved oxygen, and electrical conductivity) and nutrient concentrations (reactive soluble phosphorus, total phosphorus, nitrogen series, total nitrogen, and total dissolved carbon) along a mid-order river in SE Brazil and that these effects depend on rainfall regime. Six study sites were sampled along almost 4 years to evaluate the impacts of human activities, including sites upstream (1-3) and downstream (5-6) from the WWTP. The impacts were observed presenting an increasing trend from the source (site 1) towards Água Quente stream (site 4, the polluted tributary), with signs of attenuation at site 5 (downstream from both WWTP and site 4) and the river mouth (site 6). Input of nutrients by rural and urban runoff was observed mainly at sites 2 and 3, respectively. At sites 4 and 5, the inputs of both untreated and treated wastewaters increased nutrient concentrations and changed physicochemical variables, with significant impacts to Monjolinho River. Seasonal variations in the measured values were also observed, in agreement with the pluviometric indexes of the region. Univariate analyses suggested no effect of the WWTP for most variables, with continued impacts at sites downstream, but non-parametric multivariate analysis indicated that these sites were recovering to chemical characteristics similar to upstream sites, apparently due to autodepuration. Therefore, multivariate methods that allow rigorous tests of multifactor hypotheses can greatly contribute to determine effects of both point and non-point sources in river systems, thus contributing to freshwater monitoring and management.

Environmental drivers that influence microalgal species in fullscale wastewater treatment high rate algal ponds

In the last decade, studies have focused on identifying the most suitable microalgal species for coupled high rate algal pond (HRAP) wastewater treatment and resource recovery. However, one of the challenges facing outdoor HRAP systems is maintaining microalgal species dominance. By increasing our understanding of the environmental drivers of microalgal community composition within the HRAP environment, it may be possible to manipulate the system in such a way to favour the growth of desirable species. In this paper, we investigate the microalgal community composition in two full-scale HRAPs over a 23-month period. We compare wastewater treatment performance between dominant species and identify the environmental drivers that trigger change in community composition. A total of 33 microalgal species were identified over the 23-month period but species richness (the number of species present at any given time) was low and was not related to either productivity or nutrient removal efficiency. Species turnover of the dominant microalgae happened rapidly, typically <1 week. Changes in the influent NH₄-N concentration and zooplankton grazer numbers were significantly associated with species turnover, accounting for 80% of the changes in dominant species throughout the 23-month study period. Both nutrient removal and biomass production did not differ between the two HRAPs when the dominant species was the same or differed in the two ponds. These results suggest that microalgal functional groups are more important than individual species for full-scale HRAP performance. This study has increased our understanding of some of the environmental drivers of the microalgae within the HRAP environment, which may assist with improving wastewater treatment and resource recovery.

Temporal patterns of phyto- and bacterioplankton and their relationships with environmental factors in Lake Taihu, China

Phytoplankton and bacterioplankton are integral components of aquatic food webs and play essential roles in the structure and function of freshwater ecosystems. However, little is known about how phyto- and bacterioplankton may respond synchronously to changing environmental conditions. Thus, we analyzed simultaneously the composition and structure of phyto- and bacterioplankton on a monthly basis over 12 months in cyanobacteria-dominated areas of Lake Taihu and compared their responses to changes in environmental factors. Metric multi-dimensional scaling (mMDS) revealed that the temporal variations of phyto- and bacterioplankton were significant. Time lag analysis (TLA) indicated that the temporal pattern of phytoplankton tended to exhibit convergent dynamics while bacterioplankton showed highly stable or stochastic variation. A significant directional change was found for bacterioplankton at the genus level and the slopes (rate of change) and regression R² (low stochasticity or stability) were greater if Cyanobacteria were included, suggesting a higher level of instability in the bacterial community at lower taxonomy level. Consequently, phytoplankton responded more rapidly to the change in environmental conditions than bacterioplankton when analyzed at the phylum level, while bacterioplankton were more sensitive at the finer taxonomic resolution in Lake Taihu. Redundancy analysis (RDA) results showed that environmental variables collectively explained 51.0% variance of phytoplankton and 46.7% variance of bacterioplankton, suggesting that environmental conditions have a significant influence on the temporal variations of phyto- and bacterioplankton. Furthermore, variance partitioning indicated that the bacterial community structure was largely explained by water temperature and nitrogen, suggesting that these factors were the primary drivers shaping bacterioplankton.

Biosorbent, a promising material for remediation of eutrophic environments: studies in microcosm

Eutrophication is considered a global environmental problem that causes economic and biodiversity loss. Together with excess phosphorus in some aquatic environments, there is the depletion of phosphate rock deposits, which can directly affect fertilizer production and therefore global food security. Thus, the present work aimed to study a new remediation technique for eutrophic environments that enables the recovery of these environments through phosphorus adsorption in sawdust, creating the possibility to apply the phosphorus-enriched material as an agricultural fertilizer. The study was conducted in 36 microcosm flasks with water and sediment samples from a eutrophic reservoir in Ibirité/MG. The experiment was carried out using 18 control flasks and 18 others as treatment, consisting of water and eutrophic environment sediment and, additionally, two bags, containing 10 g of sawdust in each bag. The phosphorus adsorption on sawdust was more intense after 49 days of immersion in the microcosm, and reductions of 90% in the concentration of reactive soluble phosphorus were observed in the water column of the microcosm treatment at 159 days of the experiment. Based on the results, it can be concluded that, although the phosphorus concentration adsorbed on sawdust (16.2 μg g^-1) is considered low, the use of the biosorbent is a particularly promising technique for remediation of eutrophic environments, as well as the possible reuse of the adsorbed phosphorus as a fertilizer in agriculture.

Succession of Phytoplankton and Zooplankton Communities Coupled to Environmental Factors in the Oligo-mesotrophic Nabhana Reservoir (Semi Arid Mediterranean Area, Central Tunisia)

Ikbel Sellami, Asma Hamza, Monia El Bour, Mohammed Alaoui Mhamdi, Bernadette Pinel-alloul, and Habib Ayadi (2016) The occurrence of plankton seasonal dynamics in Mediterranean shallow lakes is characterised by a marked interannual variability, which makes it difficult to establish reliable predictions on the dynamics and functioning of plankton in these ecosystems based on the Plankton Ecology Group (PEG) model. In the present paper we study the succession of the phytoplankton and zooplankton communities in the semi-arid Mediterranean Nabhana reservoir (Central Tunisia) and its relationships with environmental factors during the period from May 2005 to January 2006 in the deepest area of this oligo-mesotrophic reservoir. Water temperature was a keystone factors in the seasonal dynamics of zooplankton. Cyanobacteria dominated the phytoplankton community throughout the study year 2005-2006 (94-99%) and Microcystis aeruginosa contributed for 93% of the total cyanobacteria abundance. The zooplankton community was dominated by copepods (66%) and cladocerans (28%). The dominant species was Copidodiaptomus numidicus (66% of total zooplankton) followed by Diaphanosoma brachyurum (22% of the total zooplankton). In addition, our results showed that the peak of phytoplankton abundance (5.6 ×106 cells l-1, June) coincided with that of zooplankton abundance (2.1 ×102 ind l-1, June) contrary to the clear-water phase model. The cyanobacteria and copepods were responsible for these exceptional peaks that occurred in June, accounting respectively for 99% of the total phytoplankton and 82% of the total zooplankton. In the Nabhana reservoir, the trophic relationship between phytoplankton and zooplankton were implicated in the phytoplankton abundance and dynamics. The occurrence of cyanobacterial blooms is determined by biotic and abiotic factors. The dynamics between cyanobacteria and their grazers may emerge as a regulator of blooms.