On the issue of limiting nutrient and predictions of cyanobacteria in aquatic systems

Intensification of harmful cyanobacterial blooms in a eutrophic, temperate lake caused by nitrogen, temperature, and CO2

Warmer temperatures can significantly increase the intensity of cyanobacterial harmful algal blooms (CHABs) in eutrophic freshwater ecosystems. However, few studies have examined the effects of CO2 enrichment in tandem with elevated temperature and/or nutrients on cyanobacterial taxa in freshwater ecosystems. Here, we observed changes in the biomass of cyanobacteria, nutrients, pH, and carbonate chemistry over a two-year period in a shallow, eutrophic freshwater lake and performed experiments to examine the effects and co-effects of CO2, temperature, and nutrient enrichment on cyanobacterial and N2-fixing (diazotrophic) communities assessed via high throughput sequencing of the 16S rRNA and nifH genes, respectively. During both years, there were significant CHABs (50-500 μg cyanobacterial chlorophyll-a L-1) and lake CO2 levels were undersaturated (≤300 μatm pCO2). NH4+ significantly increased the net growth rates of cyanobacteria as well as the biomass of the diazotrophic cyanobacterial order Nostocales under elevated and ambient CO2 conditions. In a fall experiment, the N2 fixation rates of Nostocales were significantly higher when populations were enriched with CO2 and P, relative to CO2-enriched populations that were not amended with P. During a summer experiment, N2 fixation rates increased significantly under N and CO2 - enriched conditions relative to N-enriched and ambient CO2 conditions. Nostocales dominated the diazotrophic communities of both experiments, achieving the highest relative abundance under CO2-enriched conditions when N was added in the first experiment and when CO2 and temperature were elevated in the second experiment, when N2 fixation rates also increased significantly. Collectively, this study indicates that N promotes cyanobacterial blooms including those formed by Dolichospermum and that the biomass and N2 fixation rates of diazotrophic cyanobacterial taxa may benefit from enhanced CO2 levels in eutrophic lakes.

Regime shifts in shallow lakes explained by critical turbidity

Worldwide, water quality managers target a clear, macrophyte-dominated state over a turbid, phytoplankton-dominated state in shallow lakes. The competition mechanisms underlying these ecological states were explored in the 1990s, but the concept of critical turbidity seems neglected in contemporary water quality models. In particular, a simple mechanistic model of alternative stable states in shallow lakes accounting for resource competition mechanisms and critical turbidity is lacking. To this end, we combined Scheffer's theory on critical turbidity with insights from nutrient and light competition theory founded by Tilman, Huisman and Weissing. This resulted in a novel graphical and mathematical model, GPLake-M, that is relatively simple and mechanistically understandable and yet captures the essential mechanisms leading to alternative stable states in shallow lakes. The process-based PCLake model was used to parameterize the model parameters and to test GPLake-M using a pattern-oriented strategy. GPLake-M's application range and position in the model spectrum are discussed. We believe that our results support the fundamental understanding of regime shifts in shallow lakes and provide a starting point for further mechanistic and management-focused explorations and model development. Furthermore, the concept of critical turbidity and the relation between light-limited submerged macrophytes and nutrient-limited phytoplankton might provide a new focus for empirical aquatic ecological research and water quality monitoring programs.

Mine drainage precipitates attenuate and conceal wastewater-derived phosphate pollution in stream water

Hydrous ferric-oxide (HFO) coatings on streambed sediments may attenuate dissolved phosphate (PO₄) concentrations at acidic to neutral pH conditions, limiting phosphorus (P) transport and availability in aquatic ecosystems. Mesh-covered tiles on which "natural" HFO from abandoned mine drainage (AMD) had precipitated were exposed to treated municipal wastewater (MWW) effluent or a mixture of stream water and effluent. Between 42 and 99% of the dissolved P in effluent was removed from the water to a thin coating (~2 μm) of HFO on the mesh. Geochemical equilibrium model results predicted the removal of 76 to 99% of PO₄ from the water by adsorption to the HFO, depending on the HFO quantity, initial PO₄ concentration, and pH. The measurements and model results indicated the capacity for P removal decreased as the concentration of P associated with the HFO increased. Continuing accumulation of HFO from upstream AMD sources replenish the in-stream capacity for P attenuation below the MWW discharge. This indicates AMD pollution may conceal P inputs and limit the amount of dissolved P transported to downstream ecosystems. However, HFO-rich sediments also represent a potential source of "legacy" P that could confound management practices intended to decrease nutrient and metal loadings.

Phosphate Adsorption onto an Al-Ti Bimetal Oxide Composite in Neutral Aqueous Solution: Performance and Thermodynamics

Phosphorus (P) pollution and phosphorus recovery are important issues in the field of environmental science. In this work, a novel Al-Ti bimetal composite sorbent was developed via a cost-effective co-precipitation approach for P removal from water. The adsorptive performance and characteristics of P onto Al-Ti sorbent were evaluated by batch adsorption experiments. The effects of Al:Ti molar ratio, initial P concentration and reaction temperature were investigated. The microstructural characteristics of the Al-Ti sorbent were confirmed by scanning electron microscopy (SEM), X-ray diffraction (XRD) analysis, Fourier transform infrared (FTIR) spectroscopy, and nitrogen adsorption-desorption measurements. Kinetic studies showed that the adsorption of P on Al-Ti oxide proceeds according to pseudo-second-order kinetics. The maximum adsorption capacity of phosphate on the Al-Ti oxide calculated from linear Langmuir models was 68.2 mg-P/g at pH 6.8. The Al-Ti oxide composite sorbent showed good potential for P recovery, owing to its large adsorption capacity and ease of regeneration.

Restoration, conservation and phytoplankton hysteresis

Phytoplankton growth depends not only upon external factors that are not strongly altered by the presence of phytoplankton, such as temperature, but also upon factors that are strongly influenced by activity of phytoplankton, including photosynthetically active radiation, and the availability of the macronutrients carbon, nitrogen, phosphorus and, for some, silicate. Since phytoplankton therefore modify, and to an extent create, their own habitats, established phytoplankton communities can show resistance and resilience to change, including managed changes in nutrient regimes. Phytoplankton blooms and community structures can be predicted from the overall biogeochemical setting and inputs, but restorations may be influenced by the physiological responses of established phytoplankton taxa to nutrient inputs, temperature, second-order changes in illumination and nutrient recycling. In this review we discuss the contributions of phytoplankton ecophysiology to biogeochemical hysteresis and possible effects on community composition in the face of management, conservation or remediation plans.

Development of a sub-seasonal cyanobacteria prediction model by leveraging local and global scale predictors

In recent decades, cultural eutrophication of coastal waters and inland lakes around the world has contributed to a rapid expansion of potentially toxic cyanobacteria, threatening aquatic and human systems. For many locations, a complex array of physical, chemical, and biological variables leads to significant inter-annual variability of cyanobacteria biomass, modulated by local and large-scale climate phenomena. Currently, however, minimal information regarding expected summertime cyanobacteria biomass conditions is available prior to the season, limiting proactive management and preparedness strategies for lake and beach safety. To address this, sub-seasonal (two-month) cyanobacteria biomass prediction models are developed, drawing on pre-season predictors including stream discharge, phosphorus loads, a floating algae index, and large-scale sea-surface temperature regions, with an application to Lake Mendota in Wisconsin. A two-phase statistical modeling approach is adopted to reflect identified asymmetric relationships between predictors (drivers of inter-annual variability) and cyanobacteria biomass levels. The model illustrates promising performance overall, with particular skill in predicting above normal cyanobacteria biomass conditions which are of primary importance to lake and beach managers.

Seasonal Distribution of Cyanobacteria in Three Urban Eutrophic Lakes Results from an Epidemic-like Response to Environmental Conditions

Cyanobacterial communities of three co-located eutrophic sandpit lakes were surveyed during 2016 and 2017 over season and depth using high-throughput DNA sequencing of the 16S rRNA gene. All three lakes were stratified except during April 2017 when the lakes were recovering from a strong mixing event. 16S rRNA gene V4 sequences were parsed into operational taxonomic units (OTUs) at 99% sequence identity. After rarefaction of 139 samples to 25,000 sequences per sample, a combined total of 921,529 partial 16S rRNA gene sequences were identified as cyanobacteria. They were binned into 19,588 unique cyanobacterial OTUs. Of these OTUs, 11,303 were Cyanobium. Filamentous Planktothrix contributed 1537 and colonial Microcystis contributed 265. The remaining 6482 OTUs were considered unclassified. For Planktothrix and Microcystis one OTU accounted for greater than 95% of the total sequences for each genus. However, in both cases the non-dominant OTUs clustered with the dominant OTUs by date, lake, and depth. All Planktothrix OTUs and a single Cyanobium OTU were detected below the oxycline. All other Cyanobium and Microcystis OTUs were detected above the oxycline. The distribution of Cyanobium OTUs between lakes and seasons can be explained by an epidemic-like response where individual OTUs clonally rise from a diverse hypolimnion population when conditions are appropriate. The importance of using 99% identity over the more commonly used 97% is discussed with respect to cyanobacterial community structure. The approach described here can provide another valuable tool for assessing cyanobacterial populations and provide greater insight into the controls of cyanobacterial blooms.

Using Bayesian hierarchical modelling to capture cyanobacteria dynamics in Northern European lakes

Cyanobacteria blooms in lakes and reservoirs currently threaten water security and affect the ecosystem services provided by these freshwater ecosystems, such as drinking water and recreational use. Climate change is expected to further exacerbate the situation in the future because of higher temperatures, extended droughts and nutrient enrichment, due to urbanisation and intensified agriculture. Nutrients are considered critical for the deterioration of water quality in lakes and reservoirs and responsible for the widespread increase in cyanobacterial blooms. We model the response of cyanobacteria abundance to variations in lake Total Phosphorus (TP) and Total Nitrogen (TN) concentrations, using a data set from 822 Northern European lakes. We divide lakes in ten groups based on their physico-chemical characteristics, following a modified lake typology defined for the Water Framework Directive (WFD). This classification is used in a Bayesian hierarchical linear model which employs a probabilistic approach, transforming uncertainty into probability thresholds. The hierarchical model is used to calculate probabilities of cyanobacterial concentrations exceeding risk levels for human health associated with the use of lakes for recreational activities, as defined by the World Health Organization (WHO). Different TN and TP concentration combinations result in variable probabilities to exceed pre-set thresholds. Our objective is to support lake managers in estimating acceptable nutrient concentrations and allow them to identify actions that would achieve compliance of cyanobacterial abundance risk levels with a given confidence level.

Microbial community successions and their dynamic functions during harmful cyanobacterial blooms in a freshwater lake

The current study reports the community succession of different toxin and non-toxin producing cyanobacteria at different stages of cyanobacterial harmful algal blooms (CyanoHABs) and their connectivity with nitrogen and phosphorus cycles in a freshwater lake using an ecogenomics framework. Comprehensive high throughput DNA sequencing, water quality parameter measurements, and functional gene expressions over temporal and spatial scales were employed. Among the cyanobacterial community, the lake was initially dominated by Cyanobium during the months of May, June, and early July, and later primarily by Aphanizomenon and Dolichospermum depicting functional redundancy. Finally, Planktothrix appeared in late August and then the dominance switched to Planktothrix in September. Microcystis aeruginosa and Microcystis panniformis; two species responsible for cyanotoxin production, were also present in August and September, but in significantly smaller relative abundance. MC-LR (0.06-1.32 µg/L) and MC-RR (0.01-0.26 µg/L) were two major types of cyanotoxins detected. The presence of MC-LR and MC-RR were significantly correlated with the Microcystis-related genes (16SMic/mcyA/mcyG) and their expressions (r = 0.33 to 0.8, p < 0.05). The metabolic analyses further linked the presence of different cyanobacterial groups with distinct functions. The nitrogen metabolisms detected a relatively higher abundance of nitrite/nitrate reductase in early summer, indicating significant denitrification activity and the activation of N-fixation in the blooms dominated by Aphanizomenon/Dolichospermum (community richness) during nutrient-limited conditions. The phosphorus and carbohydrate metabolisms detected a trend to initiate a nutrient starvation alert and store nutrients from early summer, while utilizing the stored polyphosphate and carbohydrate (PPX and F6PPK) during the extreme ortho-P scarcity period, mostly in August or September. Specifically, the abundance of Aphanizomenon and Dolichospermum was positively correlated with the nitrogen-fixing nif gene and (p < 0.001) and the PPX enzyme for the stored polyphosphate utilization (r = 0.77, p < 0.001). Interestingly, the lake experienced a longer N-fixing period (2-3 months) before non-fixing cyanobacteria (Planktothrix) dominated the entire lake in late summer. The Provo Bay site, which is known to be nutrient-rich historically, had early episodes of filamentous cyanobacteria blooms compared to the rest of the lake.

A systematic literature review of forecasting and predictive models for cyanobacteria blooms in freshwater lakes

Cyanobacteria harmful blooms (CyanoHABs) in lakes and reservoirs represent a major risk for water authorities globally due to their toxicity and economic impacts. Anticipating bloom occurrence and understanding the main drivers of CyanoHABs are needed to optimize water resources management. An extensive review of the application of CyanoHABs forecasting and predictive models was performed, and a summary of the current state of knowledge, limitations and research opportunities on this topic is provided through analysis of case studies. Two modelling approaches were used to achieve CyanoHABs anticipation; process-based (PB) and data-driven (DD) models. The objective of the model was a determining factor for the choice of modelling approach. PB models were more frequently used to predict future scenarios whereas DD models were employed for short-term forecasts. Each modelling approach presented multiple variations that may be applied for more specific, targeted purposes. Most models reviewed were site-specific. The monitoring methodologies, including data frequency, uncertainty and precision, were identified as a major limitation to improve model performance. A lack of standardization of both model output and performance metrics was observed. CyanoHAB modelling is an interdisciplinary topic and communication between disciplines should be improved to facilitate model comparisons. These shortcomings can hinder the adoption of modelling tools by practitioners. We suggest that water managers should focus on generalising models for lakes with similar characteristics and where possible use high frequency monitoring for model development and validation.

Effects of prolonged food limitation on energy metabolism and burrowing activity of an infaunal marine bivalve, Mya arenaria

Benthic organisms are subject to prolonged seasonal food limitation in the temperate shallow coastal waters that can cause energetic stress and affect their performance. Sediment-dwelling marine bivalves cope with prolonged food limitation by adjusting different physiological processes that might cause trade-offs between maintenance and other fitness-related functions. We investigated the effects of prolonged (42 days) food deprivation on bioenergetics, burrowing performance and amino acid profiles in a common marine bivalve, Mya arenaria collected in winter and spring. Food limitation of >15 days decreased respiration of the clams by 80%. Total tissue energy content was higher in spring-collected clams (reflecting higher lipid content) than in their winter counterparts. Prolonged food deprivation decreased the tissue energy content of clams, especially in winter. The levels of free amino acids transiently increased during the early phase of food deprivation possibly reflecting suppression of the protein synthesis or enhanced protein degradation. The levels of amino acids considered essential for bivalves were more tightly conserved than those of non-essential amino acids during starvation. The burrowing capacity of clams was negatively affected by food deprivation so that the time required for a burial cycle increased by 35-50% after 22-42 days of starvation. During the early phase of starvation, clams preferentially used lipids as fuel for burrowing, whereas carbohydrates were used at the later phase. These findings suggest that although M. arenaria can withstand prolonged food deprivation by lowering their basal maintenance costs and switching their fuel usage, their ecological functions (e.g. bioturbation and the energy transferable to the next trophic level) could be negatively impacted by starvation.

Quantifying the dependence of cyanobacterial growth to nutrient for the eutrophication management of temperate-subtropical shallow lakes

The increasing global occurrence of cyanobacterial blooms, attributed primarily to human-induced nutrient enrichment, significantly degrades freshwater ecosystems and poses serious risks to human health. The current study examined environmental variables and cyanobacterial biovolume (B_Cyano) of 28 shallow lakes in the eastern China plains during the spring and summer of 2018. We used a 95% quantile regression model to explore season-specific response of B_Cyano to total nitrogen (TN), or total phosphorus (TP), and robust linear relationships were observed between log(B_Cyano+0.001) and log(TN), or log(TP) in both spring and summer periods. Based on these regressions, regional-scale and season-specific TN and TP thresholds are proposed for these lakes to ensure the safety for recreational waters and drinking water source. However, actual B_Cyano for a given concentration of TN (or TP) for many observations were considerably lower than the results of the 95% regression model predict, indicating that other factors significantly modulated nutrient limitation of B_Cyano. Generalized additive model and quantile regression model were used together to explore potentially significant modulating factors, of which lake retention time, macrophytes cover and N: P ratio were identified as most important. Thus, it is necessary to develop type-specific nutrient thresholds with the consideration of these significant modulating factors. Furthermore, nutrient-B_Cyano relationships of our studied lakes with lake retention time>100 days and no macrophyte were further explored and nutrient thresholds of this lake type were proposed. Nutrient thresholds proposed in this study may play an essential role in achieving a cost-effective eutrophication management for shallow lakes both in the eastern China plains and elsewhere with similar climatic background. On a broader scale, the approaches and findings of this study may provide valuable reference to formulate reasonable nutrient reduction targets for other ecoregions with different climatic conditions.

Relationships between nutrient, chlorophyll a and Secchi depth in lakes of the Chinese Eastern Plains ecoregion: Implications for eutrophication management

Eutrophication and associated algal blooms are principal environmental challenges confronting lakes in China, particularly in the Eastern Plains ecoregion. The empirical relationships between nutrient and chlorophyll a (Chla) level and Secchi depth (SD) are widely used as a theoretical basis for lake eutrophication management. However, these relationships are largely influenced by hydromorphological conditions and biogeochemical processes. Thus, there is a need to establish a type-specific understanding of these interactions. In the current study, lakes in the Chinese Eastern Plains ecoregion were subdivided into four lake types according to water retention time (LRT), water depth, and water area. Regression analyses indicated that the impacts of nutrient (total nitrogen, TN; total phosphorus, TP) concentrations on summer Chla were significantly reduced in lakes with high inorganic suspended solids (ISS) (P<0.05). Meanwhile, the decrease in SD in these lakes were found to relate mainly to non-algal turbidity. In lakes characterized by both short LRT and high ISS content, the Chla exhibited limited response to nutrients. In contrast, in lakes with low ISS content and long LRT, the observed slopes of both Chla=f(TP) and SD=f(Chla) were significantly steeper (P < 0.05). The factors limiting summer algal growth and the development of type-specific nutrient criteria (TN and TP) of all four investigated lake types in the Eastern Plains ecoregion are discussed in the context of specific nutrients. Based on these results, we establish type-specific eutrophication assessment equations of TN, TP, Chla, and SD in our study lakes. Our results may provide essential information for achieving the cost-effective eutrophication management of lakes both in the Eastern Plains ecoregion and elsewhere with similar climatic and hydromorphological conditions. Moreover, we believe that the subdivision of lakes to allow type-specific eutrophication management framework may prove valuable for other ecoregions where the interpretation of empirical nutrient-Chla and SD relationships suffer from similar serious limitations.

Cyanobacterial Blooms in Lake Varese: Analysis and Characterization over Ten Years of Observations

Cyanobacteria blooms are a worldwide concern for water bodies and may be promoted by eutrophication and climate change. The prediction of cyanobacterial blooms and identification of the main triggering factors are of paramount importance for water management. In this study, we analyzed a comprehensive dataset including ten-years measurements collected at Lake Varese, an eutrophic lake in Northern Italy. Microscopic analysis of the water samples was performed to characterize the community distribution and dynamics along the years. We observed that cyanobacteria represented a significant fraction of the phytoplankton community, up to 60% as biovolume, and a shift in the phytoplankton community distribution towards cyanobacteria dominance onwards 2010 was detected. The relationships between cyanobacteria biovolume, nutrients, and environmental parameters were investigated through simple and multiple linear regressions. We found that 14-days average air temperature together with total phosphorus may only partly explain the cyanobacteria biovolume variance at Lake Varese. However, weather forecasts can be used to predict an algal outbreak two weeks in advance and, eventually, to adopt management actions. The prediction of cyanobacteria algal blooms remains challenging and more frequent samplings, combined with the microscopy analysis and the metagenomics technique, would allow a more conclusive analysis.

Catchment land use predicts benthic vegetation in small estuaries

Many estuaries are becoming increasingly eutrophic from human activities within their catchments. Nutrient loads often are used to assess risk of eutrophication to estuaries, but such data are expensive and time consuming to obtain. We compared the percent of fertilized land within a catchment, dissolved inorganic nitrogen loads, catchment to estuary area ratio and flushing time as predictors of the proportion of macroalgae to total vegetation within 14 estuaries in south-eastern Australia. The percent of fertilized land within the catchment was the best predictor of the proportion of macroalgae within the estuaries studied. There was a transition to a dominance of macroalgae once the proportion of fertilized land in the catchment exceeded 24%, highlighting the sensitivity of estuaries to catchment land use.

The relationships of meteorological factors and nutrient levels with phytoplankton biomass in a shallow eutrophic lake dominated by cyanobacteria, Lake Dianchi from 1991 to 2013

Long-term interannual (1991-2013) and monthly (1999-2013) data were analyzed to elucidate the effects of meteorological factors and nutrient levels on phytoplankton biomass in the cyanobacteria-dominated Waihai basin of Lake Dianchi. The interannual ln(chl. a) exhibited positive correlations with the mean air temperature, mean minimum air temperature, and mean maximum air temperature; in addition, a positive relationship between Δln(chl. a) and ΔTP was observed throughout the period. Additionally, ln(chl. a) exhibited a positive correlation with the TP concentration, negative correlations with the sunshine hours and wind speed during the dry season, and positive correlations with the TN and TP concentrations during the rainy season. Furthermore, TP was the most influential factor affecting cyanobacterial bloom dynamics throughout the entire period and during the dry season, and TN and TP were the most important factors during the rainy season, as determined by relative importance analysis. The results of this study based on interannual analysis demonstrated that both meteorological factors and nutrient levels have important roles in controlling cyanobacterial bloom dynamics. The relative importance of these factors may change according to precipitation patterns. Thus, climate change regulation and eutrophication management should be considered in strategies for bloom control. Decreasing the TP load should be prioritized throughout the entire period and during the dry season, and decreasing the TN and TP loads should be considered initially during the rainy season. In addition, further studies of more frequent and complete data acquired over a longer period of time should be conducted in the future.

Productivity and sea surface temperature are correlated with the pelagic larval duration of damselfishes in the Red Sea

We examined the variation of pelagic larval durations (PLDs) among three damselfishes, Dascyllus aruanus, D. marginatus, and D. trimaculatus, which live under the influence of an environmental gradient in the Red Sea. PLDs were significantly correlated with latitude, sea surface temperature (SST), and primary production (CHLA; chlorophyll a concentrations). We find a consistent decrease in PLDs with increasing SST and primary production (CHLA) towards the southern Red Sea among all species. This trend is likely related to higher food availability and increased metabolic rates in that region. We suggest that food availability is a potentially stronger driver of variation in PLD than temperature, especially in highly oligotrophic regions. Additionally, variations in PLDs were particularly high among specimens of D. marginatus, suggesting a stronger response to local environmental differences for endemic species. We also report the first average PLD for this species over a broad geographic range (19.82 ± 2.92 days).

How rising CO2 and global warming may stimulate harmful cyanobacterial blooms

Climate change is likely to stimulate the development of harmful cyanobacterial blooms in eutrophic waters, with negative consequences for water quality of many lakes, reservoirs and brackish ecosystems across the globe. In addition to effects of temperature and eutrophication, recent research has shed new light on the possible implications of rising atmospheric CO₂ concentrations. Depletion of dissolved CO₂ by dense cyanobacterial blooms creates a concentration gradient across the air-water interface. A steeper gradient at elevated atmospheric CO₂ concentrations will lead to a greater influx of CO₂, which can be intercepted by surface-dwelling blooms, thus intensifying cyanobacterial blooms in eutrophic waters. Bloom-forming cyanobacteria display an unexpected diversity in CO₂ responses, because different strains combine their uptake systems for CO₂ and bicarbonate in different ways. The genetic composition of cyanobacterial blooms may therefore shift. In particular, strains with high-flux carbon uptake systems may benefit from the anticipated rise in inorganic carbon availability. Increasing temperatures also stimulate cyanobacterial growth. Many bloom-forming cyanobacteria and also green algae have temperature optima above 25°C, often exceeding the temperature optima of diatoms and dinoflagellates. Analysis of published data suggests that the temperature dependence of the growth rate of cyanobacteria exceeds that of green algae. Indirect effects of elevated temperature, like an earlier onset and longer duration of thermal stratification, may also shift the competitive balance in favor of buoyant cyanobacteria while eukaryotic algae are impaired by higher sedimentation losses. Furthermore, cyanobacteria differ from eukaryotic algae in that they can fix dinitrogen, and new insights show that the nitrogen-fixation activity of heterocystous cyanobacteria can be strongly stimulated at elevated temperatures. Models and lake studies indicate that the response of cyanobacterial growth to rising CO₂ concentrations and elevated temperatures can be suppressed by nutrient limitation. The greatest response of cyanobacterial blooms to climate change is therefore expected to occur in eutrophic and hypertrophic lakes.

The co-adsorption of Cu2+ and Zn2+ with adsorption sites surface-lattice reforming on calcined layered double hydroxides

The picture shows that how the CLDHs recover into the hydrotalcite structure in the process of adsorption of Cu²⁺ and Zn²⁺.

Input and dispersion of nutrients from the Jeddah Metropolitan Area, Red Sea

Large amounts of waste water are discharged from the Jeddah Metropolitan Area into the Red Sea. Daily loads of total nitrogen (TN) and phosphorus (TP) amount to 6564 kg and 2241 kg, respectively, comprising 83% of dissolved inorganic nitrogen and 33% of dissolved phosphate. Steep gradients prevail nearshore, ranging from 2000 μM TN and 250 μM TP in the hypertrophic city lagoons to 6 μM TN and 0.4 μM TP in the adjacent oligotrophic water. Sewage inputs from Al Khumra, Jeddah's main outfall, cause a widespread but moderate increase in surface nutrient concentrations due to the submerged diffuser. The nutrient pool in the oligotrophic water is dominated by dissolved organic and particulate forms, with nitrate frequently below the detection limit, indicating rapid transformation of inorganic nutrients. N:P ratios, as well as half-saturation constants for phytoplankton growth, suggest that nitrogen is the limiting factor restricting primary production in the area.

Monitoring approaches for a toxic cyanobacterial bloom

Cyanobacterial blooms, dominated by Microcystis sp. and associated microcystin variants, have been implicated in illnesses of humans and animals. Little is known regarding the formation of blooms and the presence of cyanotoxin variants in water bodies. Furthermore, the role played by ecological parameters, in regulating Microcystis blooms is complicate and diverse. Local authorities responsible for water management are often faced with the challenging task of dealing with cyanobacterial blooms. Therefore, the development of suitable monitoring approaches to characterize cyanobacterial blooms is an important goal. Currently, various biological, biochemical and physicochemical methods/approaches are being used to monitor cyanobacterial blooms and detect microcystins in freshwater bodies. Because these methods can vary as to the information they provide, no single approach seemed to be sufficient to accurately monitor blooms. For example, immunosensors are more suited for monitoring the presence of toxins in clear water bodies while molecular methods are more suited to detect potentially toxic strains. Thus, monitoring approaches should be tailored for specific water bodies using methods based on economic feasibility, speed, sensitivity and field applicability. This review critically evaluates monitoring approaches that are applicable to cyanobacterial blooms, especially those that focus on the presence of Microcystis, in freshwater bodies. Further, they were characterized and ranked according to their cost, speed, sensitivity and selectivity. Suggested improvements were offered as well as future research endeavors to accommodate anticipated environmental changes.

Cyanobacteria and cyanotoxins: the influence of nitrogen versus phosphorus

The importance of nitrogen (N) versus phosphorus (P) in explaining total cyanobacterial biovolume, the biovolume of specific cyanobacterial taxa, and the incidence of cyanotoxins was determined for 102 north German lakes, using methods to separate the effects of joint variation in N and P concentration from those of differential variation in N versus P. While the positive relationship between total cyanobacteria biovolume and P concentration disappeared at high P concentrations, cyanobacteria biovolume increased continually with N concentration, indicating potential N limitation in highly P enriched lakes. The biovolumes of all cyanobacterial taxa were higher in lakes with above average joint NP concentrations, although the relative biovolumes of some Nostocales were higher in less enriched lakes. Taxa were found to have diverse responses to differential N versus P concentration, and the differences between taxa were not consistent with the hypothesis that potentially N₂-fixing Nostocales taxa would be favoured in low N relative to P conditions. In particular Aphanizomenon gracile and the subtropical invasive species Cylindrospermopsis raciborskii often reached their highest biovolumes in lakes with high nitrogen relative to phosphorus concentration. Concentrations of all cyanotoxin groups increased with increasing TP and TN, congruent with the biovolumes of their likely producers. Microcystin concentration was strongly correlated with the biovolume of Planktothrix agardhii but concentrations of anatoxin, cylindrospermopsin and paralytic shellfish poison were not strongly related to any individual taxa. Cyanobacteria should not be treated as a single group when considering the potential effects of changes in nutrient loading on phytoplankton community structure and neither should the N₂-fixing Nostocales. This is of particular importance when considering the occurrence of cyanotoxins, as the two most abundant potentially toxin producing Nostocales in our study were found in lakes with high N relative to P enrichment.

Development of chemically engineered porous metal oxides for phosphate removal

In this study, the application of ordered mesoporous silica (OMS) doped with various metal oxides (Zr, Ti, Fe and Al) were studied for the removal of (ortho) phosphate ions from water by adsorption. The materials were characterized by means of N(2) physisorption (BET), powder X-ray diffraction (PXRD) and transmission electron microscopy (TEM). The doped materials had surface areas between 600 and 700 m(2)g(-1) and exhibited pore sizes of 44-64 Å. Phosphate adsorption was determined by measurement of the aqueous concentration of orthophosphate using ultraviolet-visible (UV-vis) spectroscopy before and after extraction. The effects of different metal oxide loading ratios, initial concentration of phosphate solution, temperature and pH effects on the efficiency of phosphate removal were investigated. The doped mesoporous materials were effective adsorbents of orthophosphate and up to 100% removal was observed under appropriate conditions. 'Back extracting' the phosphate from the doped silica (following water treatment) was also investigated and shown to have little adverse effect on the adsorbent.

Are known cyanotoxins involved in the toxicity of picoplanktonic and filamentous North Atlantic marine cyanobacteria?

Eight marine cyanobacteria strains of the genera Cyanobium, Leptolyngbya, Oscillatoria, Phormidium, and Synechococcus were isolated from rocky beaches along the Atlantic Portuguese central coast and tested for ecotoxicity. Strains were identified by morphological characteristics and by the amplification and sequentiation of the 16S rDNA. Bioactivity of dichloromethane, methanol and aqueous extracts was assessed by the Artemia salina bioassay. Peptide toxin production was screened by matrix assisted laser desorption/ionization time of flight mass spectrometry. Molecular analysis of the genes involved in the production of known cyanotoxins such as microcystins, nodularins and cylindrospermopsin was also performed. Strains were toxic to the brine shrimp A. salina nauplii with aqueous extracts being more toxic than the organic ones. Although mass spectrometry analysis did not reveal the production of microcystins or other known toxic peptides, a positive result for the presence of mcyE gene was found in one Leptolyngbya strain and one Oscillatoria strain. The extensive brine shrimp mortality points to the involvement of other unknown toxins, and the presence of a fragment of genes involved in the cyanotoxin production highlight the potential risk of cyanobacteria occurrence on the Atlantic coast.

Determination of the optimal parameters in regression models for the prediction of chlorophyll-a: a case study of the Yeongsan Reservoir, Korea

Statistical regression models involve linear equations, which often lead to significant prediction errors due to poor statistical stability and accuracy. This concern arises from multicollinearity in the models, which may drastically affect model performance in terms of a trade-off scenario for effective water resource management logistics. In this paper, we propose a new methodology for improving the statistical stability and accuracy of regression models, and then show how to cope with pitfalls in the models and determine optimal parameters with a decreased number of predictive variables. Here, a comparison of the predictive performance was made using four types of multiple linear regression (MLR) and principal component regression (PCR) models in the prediction of chlorophyll-a (chl-a) concentration in the Yeongsan (YS) Reservoir, Korea, an estuarine reservoir that historically suffers from high levels of nutrient input. During a 3-year water quality monitoring period, results showed that PCRs could be a compact solution for improving the accuracy of the models, as in each case MLR could not accurately produce reliable predictions due to a persistent collinearity problem. Furthermore, based on R(2) (goodness of fit) and F-overall number (confidence of regression), and the number of explanatory variables (R-F-N) curve, it was revealed that PCR-F(7) was the best model among the four regression models in predicting chl-a, having the fewest explanatory variables (seven) and the lowest uncertainty. Seven PCs were identified as significant variables, related to eight water quality parameters: pH, 5-day biochemical oxygen demand, total coliform, fecal indicator bacteria, chemical oxygen demand, ammonia-nitrogen, total nitrogen, and dissolved oxygen. Overall, the results not only demonstrated that the models employed successfully simulated chl-a in a reservoir in both the test and validation periods, but also suggested that the optimal parameters should cautiously be considered in the design of regression models.