Formation Of Algal Blooms Research Articles

Individual and combined effects of ionophore antibiotics monensin and lasalocid on growth, oxidative stress and antioxidant responses of Microcystis aeruginosa

ABSTRACT To assess the impact of monensin, lasalocid, and a 1:1 (w/w) mixture of monensin and lasalocid on the formation of Microcystis aeruginosa-based harmful algal blooms (HABs), laboratory experiments were conducted [temperature 20 ± 1°C, illumination PAR 30 ± 4 μmol/m2 ·s (12-h light/dark cycle), growth medium BG-11] at concentrations of 100, 200, 500, 1,000, and 2,000 μg/L. Measurements included optical density, cell protein content, chlorophyll ‘a’ (Chl. a) content, oxidative stress, catalase activity (CAT), and guaiacol peroxidase activity (GPX). Monensin treatment showed a dose-dependent positive effect on M. aeruginosa growth at concentrations ≤500 μg/L and a gradual dose-dependent growth inhibition at concentrations of 1,000 and 2,000 μg/L. The results indicated that monensin has a significant positive effect on the formation of HABs by M. aeruginosa. Lasalocid treatment showed a growth reduction of M. aeruginosa at concentrations ≤500 μg/L and a growth increase at higher concentrations (1,000 and 2,000 μg/L). The monensin and lasalocid 1:1 (w/w) mixture test showed an intermediate response, as indicated by the individual treatments signifying the potential interactive effects of these antibiotics on the growth of M. aeruginosa. Furthermore, alterations in Chl. ‘a’, oxidative stress, CAT, and GPX measurements provided evidence of the impact of these antibiotics on the existence of M. aeruginosa.

Estimates of Lake Nitrogen, Phosphorus, and Chlorophyll‐a Concentrations to Characterize Harmful Algal Bloom Risk Across the United States

AbstractExcess nutrient pollution contributes to the formation of harmful algal blooms (HABs) that compromise fisheries and recreation and that can directly endanger human and animal health via cyanotoxins. Efforts to quantify the occurrence, drivers, and severity of HABs across large areas is difficult due to the resource intensive nature of field monitoring of lake nutrient and chlorophyll‐a concentrations. To better characterize how nutrients interact with other environmental factors to produce algal blooms in freshwater systems, we used spatially explicit and temporally matched climate, landscape, in‐lake characteristic, and nutrient inventory data sets to predict nutrients and chlorophyll‐a across the conterminous US (CONUS). Using a nested modeling approach, three random forest (RF) models were trained to explain the spatiotemporal variation in total nitrogen (TN), total phosphorus (TP), and chlorophyll‐a concentrations across US EPA's National Lakes Assessment (n = 2,062). Concentrations of TN and TP were the most important predictors and, with other variables, the RF model accounted for 68% of variation in chlorophyll‐a. We then used these RF models to extrapolate lake TN and TP predictions to lakes without nutrient observations and predict chlorophyll‐a for ∼112,000 lakes across the CONUS. Risk for high chlorophyll‐a concentrations is highest in the agriculturally dominated Midwest, but other areas of risk emerge in nutrient pollution hot spots across the country. These catchment and lake‐specific results can help managers identify potential nutrient pollution and chlorophyll‐a hot spots that may fuel blooms, prioritize at‐risk lakes for additional monitoring, and optimize management to protect human health and other environmental end goals.

A sequence of weather‐driven hydrodynamic events stimulates the formation of harmful algal blooms on an oligotrophic lake

AbstractHarmful algal blooms (HABs) are common in many eutrophic lakes and frequently associated with nutrient excesses, warm waters, and calm conditions. While HABs can also occur in oligotrophic waterbodies, bloom‐stimulating factors remain elusive for these ecosystems. Here, using a high‐frequency sensor platform supported by hydrodynamic modeling, we document a clearly linked sequence of three hydrodynamic events that immediately preceded each HAB event on Skaneateles Lake, NY during 2018. HABs were first preceded by interactions between internal waves in the thermal structure of the lake with the northern slope of the lakebed. These interactions disturbed sediments resulting in upwelling of nutrient‐rich sediment and possibly cyanobacterial cells into the lower water column. Next, moderate winds stimulated Langmuir circulation which facilitated the transport of material from the lower water column to well‐lit surface waters. Finally, the sequence culminated with a calm wind period, which is often classically associated with surface HAB formation. While individual steps in this sequence occurred independently and repeatedly throughout the year, the complete sequence occurred only eight times, immediately preceding each of the eight documented HABs. We empirically derive thresholds for and timing of the sequence to independently predict HAB occurrence and elevated cyanobacteria levels in the lake. The discovery of this specific and repeated event sequence and the identified thresholds provides the potential for forecasting of HABs days in advance. Ongoing climate change impacts, including increasing water column thermal stratification and changing wind speeds may alter the frequency, timing, and duration of this sequence and consequent HAB formation.

Characterization of Taxonomic and Functional Dynamics Associated with Harmful Algal Bloom Formation in Recreational Water Ecosystems.

Harmful algal bloom (HAB) formation leads to the eutrophication of water ecosystems and may render recreational lakes unsuitable for human use. We evaluated the applicability and comparison of metabarcoding, metagenomics, qPCR, and ELISA-based methods for cyanobacteria/cyanotoxin detection in bloom and non-bloom sites for the Great Lakes region. DNA sequencing-based methods robustly identified differences between bloom and non-bloom samples (e.g., the relative prominence of Anabaena and Planktothrix). Shotgun sequencing strategies also identified the enrichment of metabolic genes typical of cyanobacteria in bloom samples, though toxin genes were not detected, suggesting deeper sequencing or PCR methods may be needed to detect low-abundance toxin genes. PCR and ELISA indicated microcystin levels and microcystin gene copies were significantly more abundant in bloom sites. However, not all bloom samples were positive for microcystin, possibly due to bloom development by non-toxin-producing species. Additionally, microcystin levels were significantly correlated (positively) with microcystin gene copy number but not with total cyanobacterial 16S gene copies. In summary, next-generation sequencing-based methods can identify specific taxonomic and functional targets, which can be used for absolute quantification methods (qPCR and ELISA) to augment conventional water monitoring strategies.

Control of Vibrio vulnificus proliferation in the Baltic Sea through eutrophication and algal bloom management

Due to climate change the pathogenic bacterium Vibrio vulnificus proliferates along brackish coastlines, posing risks to public health, tourism, and aquaculture. Here we investigated previously suggested regulation measures to reduce the prevalence of V. vulnificus, locally through seagrass and regionally through the reduction of eutrophication and consequential formation of algal blooms. Field samples collected in the summer of 2021 covered the salinity and eutrophication gradients of the Baltic Sea, one of the largest brackish areas worldwide. Physico-, biological- and hydrochemical parameters were measured and variables explaining V. vulnificus occurrence were identified by machine learning. The best V. vulnificus predictors were eutrophication-related features, such as particulate organic carbon and nitrogen, as well as occurrence of potential phytoplankton blooms and associated species. V. vulnificus abundance did not vary significantly between vegetated and non-vegetated areas. Thus, reducing nutrient inputs could be an effective method to control V. vulnificus populations in eutrophied brackish coasts.

Interactive Effects of Polyethylene Microplastics and Cadmium on Growth of Microcystis aeruginosa.

Polyethylene (PE) is a common component of microplastic pollution, and cadmium (Cd) is a prevalent pollutant in contaminated freshwater bodies in China. Among cyanobacteria, Microcystis aeruginosa (M. aeruginosa) plays a crucial role in the formation of algal blooms in these water systems. However, there has been limited research on how microplastics and heavy metals affect cyanobacteria ecologically. This study aimed to evaluate the physiological effects of individual and combined exposure to Cd pollutants and microplastics on M. aeruginosa. The solutions containing 13 µm and 6.5 µm PE particles (100 mg/L) with Cd were used in the research. The results indicated that the combined treatment led to a significant inhibition of chlorophyll a content, dropping to zero by day 5. The treated groups exhibited higher microcystins (MCs) content compared to the control group, suggesting increased MCs release due to pollutant exposure. Interestingly, the adsorption of heavy metals by microplastics partially alleviated the toxicity of heavy metals on algal cells. Moreover, the combined treatment significantly suppressed catalase (CAT) activity compared to Cd treatment, indicating a synergistic effect that led to greater oxidative stress. Overall, this study provides valuable insights into the impact of PE and Cd pollution on freshwater ecosystems, elucidates the physiological responses of cyanobacteria to these pollutants, and establishes a theoretical groundwork for addressing complex water pollution using cyanobacteria-based strategies.

Editorial: The impacts of anthropogenic activity and climate change on the formation of harmful algal blooms (HABs) and its ecological consequence

Editorial: The impacts of anthropogenic activity and climate change on the formation of harmful algal blooms (HABs) and its ecological consequence

Weakened hydrological oscillation period increased the frequency of river algal blooms

The evolution of riverine aquatic ecosystems typically exhibits notable characteristic with cumulative, enduring, and hysteresis. Exploring the non-linear response of riverine ecology to long-term hydrological fluctuations become a major challenge in contemporary interdisciplinary research. In response to the critical issue of frequent river algal blooms in the lower Han River, which is impacted by Asian largest inter-basin water diversion project. We identified the non-linear response of eco-hydrology across various time scales through the integration of Continuous Wavelet Transform (CWT) and Inverse Wavelet Transform (IWT). Our study revealed that: 1) Over the past half century, the hydrological regime in the lower Han river showed a significant downward trend, and existed three significant hydrological oscillation periods (HOPs), including the short-scale Intra-AC (180 days), the medium-scale AC (365 days, the first major period), and the long-scale Inter-AC (2500 days), the variation of Inter-AC changed most dramatically. 2) We further found that the Inter-AC variation of hydrology is more closely related to the formation of river algal blooms in the Han River, and when the hydrological Inter-AC shows steady state or downward trend, the frequency of algal blooms in the lower Han River increases significantly. 3) The river algal blooms in the lower Han River is a cumulative consequence to the long-term hydrological influences. Weakened hydrological Inter-AC is more likely to increase the frequency of river algal blooms, and 10-years Inter-AC cumulation increased the frequency by 60%. Therefore, the weaken of long-scale HOP will significantly increase the frequency of river algal blooms in the future. This study received a critical scientific insight and aimed at provide guidance for the optimization of ecological management within the framework of national large-scale water conservation.

Synergistic controls of water column stability and groundwater phosphate on coastal algal blooms

Algal blooms have been identified as one major threat to coastal safety and marine ecosystem functioning, but the dominant mechanism regulating the formation of algal blooms remains controversial, ranging from physical control (via water column stability), the chemical control (via coastal nutrients) to joint control. Here we leveraged the unique data collected in the Hong Kong water over the annual cycle and past three decades, including direct observations of algal blooms and coastal nutrients and process model output of water column stability, and evaluated the differential competing hypotheses in regulating algal blooms. Our results demonstrate that the joint mechanism rather than the single mechanism effectively predicts all algal blooms. Meanwhile, we observed that the adequate nutrients (phosphate, PO43−) significantly originate from coastal groundwater. The production and fluctuation of PO43− in beach aquifers are primarily governed by groundwater temperature, leading to a sustained and sufficient supply of PO43− in a low groundwater temperature environment. Furthermore, along with submarine groundwater discharge (SGD), the ongoing release of PO43− in groundwater enters coastal waters and serves as sufficient nourishment for promoting algal blooms in coastal areas. These results highlight the importance of both physical and chemical mechanisms, as well as SGD, in regulating coastal algal blooms. These findings have practical implications for the prevention of coastal algal blooms and provide insights into mariculture, water security, and the sustainability of coastal ecosystems.

A laboratory study of the increasing competitiveness of Karenia mikimotoi under rising CO2 scenario

Ocean acidification (OA) driven by elevated carbon dioxide (CO2) levels is expected to disturb marine ecological processes, including the formation and control of harmful algal blooms (HABs). In this study, the effects of rising CO2 on the allelopathic effects of macroalgae Ulva pertusa to a toxic dinoflagellate Karenia mikimotoi were investigated. It was found that high level of CO2 (1000 ppmv) promoted the competitive growth of K. mikimotoi compared to the group of present ambient CO2 level (420ppmv), with the number of algal cell increased from 32.2 × 104 cells/mL to 36.75 × 104 cells/mL after 96 h mono-culture. Additionally, rising CO2 level weakened allelopathic effects of U. pertusa on K. mikimotoi, as demonstrated by the decreased inhibition rate (50.6 % under the original condition VS 34.3 % under the acidified condition after 96 h co-culture) and the decreased reactive oxygen species (ROS) level, malondialdehyde (MDA) content, antioxidant enzymes activity (superoxide dismutase (SOD), peroxidase (POD), glutathione peroxidase (GPX), glutathione reductase (GR) and catalase (CAT) and non-enzymatic antioxidants (glutathione (GSH) and ascorbic acid (ascorbate, vitamin C). Indicators for cell apoptosis of K. mikimotoi including decreased caspase-3 and -9 protease activity were observed when the co-cultured systems were under rising CO2 exposure. Furthermore, high CO2 level disturbed fatty acid synthesis in U. pertusa and significantly decreased the contents of fatty acids with allelopathy, resulting in the allelopathy weakening of U. pertusa. Collectively, rising CO2 level promoted the growth of K. mikimotoi and weakened allelopathic effects of U. pertusa on K. mikimotoi, indicating the increased difficulties in controlling K. mikimotoi using macroalgae in the future.

Variation of Local Wind Fields under the Background of Climate Change and Its Impact on Algal Blooms in Lake Taihu, China

Global climate change can greatly promote the continuing expansion of algal blooms in eutrophic inland lakes. Wind fields, an important climate factor, provide an external driving force for the movement of algal blooms. Based on algal bloom satellite imageries and wind observation data from 2003 to 2022, this study explored a quantitative assessment of the variations in surface wind fields and their impacts on the algal blooms in Lake Taihu, China. The results indicate that the mean wind speed at different time scales in the Lake Taihu area presents a continuous descending tendency in recent decades, which is the probable cause for the increasing frequency and severity of algal blooms in the lake. Wind fields affect the formation, location, and severity of algal blooms in diverse and complex ways. The area and frequency of algal blooms in Lake Taihu increase with the decrease in wind speed. The 6 h mean wind speed before 12:00 LT (Local Time) on the day of the algal bloom occurrence generally follows a Gaussian distribution, with a wind speed range of (0.6 m/s, 3.4 m/s) at the 95.5% confidence level. Accordingly, the wind speeds of 0.6 m/s and 3.4 m/s are identified to be the lower and upper critical wind speed indicators suitable for the formation of algal blooms, respectively. Another meaningful finding is that the outbreak of large-scale algal blooms requires stricter wind speed conditions, with a significantly lower wind speed threshold of around 2 m/s. Our study also demonstrates that the dominant wind direction of southeast in the region may be an important cause of the continuous water-quality decline and the high frequency and severity of algal blooms in the northwest waters of the lake. These findings will contribute to further studies on the dynamic mechanism of algal blooms and provide support for water environment management and algal bloom prevention and control.

DHESN: A deep hierarchical echo state network approach for algal bloom prediction

A deep hierarchical echo state network (DHESN) is designed for rectifying the shortcomings of the shallow coupled structure with less reservoir dynamics. This design is with reference to algal bloom which is a complex ecological phenomenon. Accurate prediction of algal bloom can reduce the environmental impact and economic loss. Since the formation of algal bloom has chaotic characteristics, the ESN has been employed to realize its prediction function. First, the candidate variables with strong causal relationship have been screened by transfer entropy, and the redundant variables is eliminated. Then, a hierarchical reservoir structure is established that is inspired by the hierarchical characteristics from the brain. The hierarchical reservoir has realized the connection between the representative nodes of each subreservoir, and improved the information processing ability of the reservoir. Finally, the pruning and compression of the output weights have been realized by the elastic regularization method, which improves the robustness of the prediction model. The simulation results demonstrate that the DHESN has appreciable prediction accuracy in both the chaotic and the public algal bloom datasets. The DHESN contains richer dynamic characteristics, and can realize the self-organization of the network structure. It provides a novel idea to realize the prediction model of algal bloom with a high accuracy and low complexity.

Indole-3-acetic acid as a cross-talking molecule in algal-bacterial interactions and a potential driving force in algal bloom formation.

Most signaling molecules are involved in inter-or intra-species communication, and signaling involving cross-kingdom cell-to-cell communication is limited. Howerver, algae and bacteria exchange nutrients and information in a range of interactions in marine environments. Multiple signaling molecules exist between algae and bacteria, including quorum-sensing molecules, nitric oxide, and volatile organic compounds. Recently, indole-3-acetic acid (IAA), an auxin hormone that is a well-studied signaling molecule in terrestrial ecosystems, was found to act as a cue in cross-kingdom communication between algae and bacteria in aquatic environments. To increase understanding of the roles of IAA in the phycosphere, the latest evidence regarding the ecological functions of IAA in cross-kingdom communication between algae and bacteria has been compiled in this review. The pathways of IAA biosynthesis, effects of IAA on algal growth & reproduction, and potential mechanisms at phenotypic and molecular levels are summarized. It is proposed that IAA is an important molecule regulating algal-bacterial interactions and acts as an invisible driving force in the formation of algal blooms.

Bioavailable iron concentrations regulate phytoplankton growth and bloom formation in low-nutrient lakes

The growth of phytoplankton in lakes is thought to be primarily controlled by macronutrient concentrations, but the availability of trace metal micronutrients, such as iron (Fe), are increasingly recognised as important regulators of lake primary production. This study evaluates the role of Fe in regulating phytoplankton growth in lakes of different nutrient status in New Zealand. The results of this unique year-long study, combining highly sensitive trace metal concentration analysis of waters and particulates with advanced trace metal bioavailability and speciation modelling, constrains thresholds for bioavailable Fe and colloidal Fe of 0.8 nmol·L−1 and 30 nmol·L−1, respectively, below which phytoplankton growth-limitation occurs. These thresholds specifically control diatom bloom formation and termination in lakes, thereby exerting a strong influence on freshwater carbon sequestration, given the dominance of diatoms in lake bloom assemblages. Importantly, potentially toxic cyanobacteria thrived only after events of bottom water anoxia, when additional dissolved Fe in concentrations ≥4 nmol·L−1 was released into the water column. These new thresholds for bioavailable and colloidal Fe offer the potential to manage micronutrient levels in lakes for the purpose of regulating algal bloom formation and carbon sequestration, while at the same time, suppressing the formation of harmful cyanobacterial blooms.

Anthracene boronic acid functionalized activated screen-printed carbon electrode: A strategy for direct phosphate voltammetric detection

Phosphates (Pi) in water can be beneficial for aquatic plants and animals as they serve as a nutrient source. However, excess amounts of Pi in water can lead to eutrophication, a process that leads to excessive plant growth and oxygen depletion and, thus affects the aquatic ecosystem. Pi can also contribute to the formation of harmful algal blooms, which can produce toxins that are harmful to both humans and animals. Therefore, maintaining Pi amount within the safe range is important and through the aid of analytical tools the concentration level can be managed. Electrochemical sensors are versatile and powerful tools for environmental monitoring. We herein report a direct voltammetric sensing of Pi using a screen-printed carbon electrode functionalized with anthracene boronic acid (SPCE/ANBA). The complexation of ANBA with Pi through specific BA-Pi binding leads to the quinone formation that has been utilized for Pi detection in an electrochemical system for the first time. Under optimized conditions, the SPCE/ANBA modified electrode exhibited a wide linear range between 10 µM and 100 mM with high selectivity and sensitivity and a detection limit of 3.2 µM (S/N = 3). Finally, the SPCE/ANBA modified electrode was successfully tested with an environmental water sample (tap and lake) by using standard addition method. It was found that the system has satisfactory real sample results.

Improving Spaceborne GNSS-R Algal Bloom Detection with Meteorological Data

Algal bloom has become a serious environmental problem caused by the overgrowth of plankton in many waterbodies, and effective remote sensing methods for monitoring it are urgently needed. Global navigation satellite system-reflectometry (GNSS-R) has been developed rapidly in recent years, which offers a new perspective on algal bloom detection. When algal bloom emerges, the water surface will turn smoother, which can be detected by GNSS-R. In addition, meteorological parameters, such as temperature, wind speed and solar radiation, are generally regarded as the key factors in the formation of algal bloom. In this article, a new algal bloom detection method aided by machine learning and auxiliary meteorological data is established. This work employs the Cyclone GNSS (CYGNSS) data and the fifth generation European Reanalysis (ERA-5) data with the application of the random under sampling boost (RUSBoost) algorithm. Experiments were carried out for Taihu Lake, China, over the period of August 2018 to May 2022. During the evaluation stage, the test true positive rate (TPR) of 81.9%, true negative rate (TNR) of 82.9%, overall accuracy (OA) of 82.9% and the area under (receiver operating characteristic) curve (AUC) of 0.88 were achieved, with all the GNSS-R observables and meteorological factors being involved. Meanwhile, the contribution of each meteorological factor and the error sources were assessed, and the results indicate that temperature and solar radiation play a prominent role among other meteorological factors in this research. This work demonstrates the capability of CYGNSS as an effective tool for algal bloom detection and the inclusion of meteorological data for further enhanced performance.

Evaluation of the Effects of Different Phosphorus Sources on Microcystis aeruginosa Growth and Microcystin Production via Transcriptomic Surveys

Microcystis aeruginosa (M. aeruginosa) is a dominant species among frequent cyanobacterial blooms and is well known for its toxin-producing ability. Phosphorus (P) is a typical growth-limiting element for M. aeruginosa. Although alterations in physiological reactions have been documented in response to various P sources, the underlying molecular processes and transcriptional patterns remain poorly understood. This study evaluated the physiological and molecular responses of M. aeruginosa to different P sources. The growth of M. aeruginosa was promoted by both dissolved inorganic phosphorus (DIP) and dissolved organic phosphorus (DOP) at a concentration of 0.4 mg/L with an initial cell density of 1.50 (±0.05) × 106 cells/mL. The cell density reached 1.38 (±0.05) × 107 cells/mL in the DIP group on day 14, a value which was higher than that in the DOP group. Most photosynthesis genes had higher levels of upregulated expression in the DIP group. For instance, gene psbA was upregulated by 0.45 Log2Fold Change (Log2FC). In the DOP group, it is interesting that the Pi (PO4-P) concentration increased to 0.09 mg/L on day 14. Meanwhile, the expression of the gene encoding alkaline phosphatase-like protein was significantly upregulated, with a value of 1.56 Log2FC, and the alkaline phosphatase concentration increased in the DOP group. The intracellular microcystin (IMC) concentration decreased with time in both groups. However, the concentration of extracellular microcystins (EMCs) increased with incubation time in both groups. Phosphorus participates in the regulation of microcystin synthesis, mainly by regulating ATP synthesis. Based on the physiological and molecular investigations in this study, the results provide crucial insights into the physiological adaptations and the role of P in modulating harmful algal bloom formation, microcystin synthesis, and potential molecular responses of M. aeruginosa.

Quantitative discrimination of algae multi-impacts on N2O emissions in eutrophic lakes: Implications for N2O budgets and mitigation

It is generally accepted that eutrophic lakes significantly contribute to nitrous oxide (N2O) emissions. However, how these emissions are affected by the formation, disappearance, and mechanisms of algal blooms in these lakes has not been systematically investigated. This study examined and determined the relative contribution of spatiotemporal N2O production pathways in hypereutrophic Lake Taihu. Synchronously, the multi-impacts of algae on N2O production and release potential were measured in the field and in microcosms using isotope ratios of oxygen (δ18O) and bulk nitrogen (δ15N) to N2O and to intramolecular 15N site preference (SP). Results showed that N2O production in Lake Taihu was derived from microbial effects (nitrification and incomplete denitrification) and water air exchanges. N2O production was also affected by the N2O reduction process. The mean dissolved N2O concentrations in the water column during the pre-outbreak, outbreak, and decay stages of algae accumulation were almost the same (0.05 μmol·L–1), which was 2–10 times higher than in lake areas algae was not accumulating. However, except for the central lake area, all surveyed areas (with and without accumulated algae) displayed strong release potential and acted as the emission source because of dissolved N2O supersaturation in the water column. The mean N2O release fluxes during the pre-outbreak, outbreak, and decay stages of algae accumulation areas were 17.95, 26.36, and 79.32 μmol·m–2·d–1, respectively, which were 2.0–7.5 times higher than the values in the non-algae accumulation areas. In addition, the decay and decomposition of algae released large amounts of nutrients and changed the physiochemical properties of the water column. Additionally, the increased algae biomass promoted N2O release and improved the proportion of N2O produced via denitrification process to being 9.8–20.4% microbial-derived N2O. This proportion became higher when the N2O consumption during denitrification was considered as evidenced by isotopic data. However, when the algae biomass was excessive in hypereutrophic state, the algae decomposition also consumed a large amount of oxygen, thus limiting the N2O production due to complete denitrification as well as due to the limited substrate supply of nitrate by nitrification in hypoxic or anoxic conditions. Further, the excessive algae accumulation on the water surface reduced N2O release fluxes via hindering the migration of the dissolved N2O into the atmosphere. These findings provide a new perspective and understanding for accurately evaluating N2O release fluxes driven by algae processes in eutrophic lakes.

Fluctuation of growth and photosynthetic characteristics in Prorocentrum shikokuense under phosphorus limitation: Evidence from field and laboratory

Exploring the complex interaction between algal growth and their photo-physiology is of significant interest as it can further the understanding of harmful algal blooms. To this end, we investigate variations in cell abundance and chlorophyll fluorescence parameters during the algal bloom formation of Prorocentrum shikokuense in the field and batch culture via the pulse amplitude modulated fluorometry. Furthermore, based on the interaction between algal growth and its photo-physiology status, we develop a novel algal growth model incorporating cell growth delay. The model parameters are estimated by fitting the experimental data of P. shikokuense and validated by the experimental data of Symbiodinium sp. The experimental results show that the growth status and photosynthetic parameters of algal cells fluctuate in both field and laboratory experiments and that the photosynthetic parameters have a faster response than growth parameters. According to the experimental and mathematical results, the time delay between the slow growth of algae and the rapid change of photosynthetic parameters may be a physiological mechanism leading to the fluctuations in algal growth. These results are significant for studying the relationship between phytoplankton growth dynamics and photosynthetic parameters and will help resource managers to predict and deepen the understanding of harmful algal blooms.

Interactions between chytrids cause variable infection strategies on harmful algal bloom forming species

Cyanobacteria have a great diversity of natural enemies, such as herbivores and pathogens, including fungal pathogens within the Chytridiomycota (chytrids). While these pathogens have been previously described on a select number of cyanobacterial hosts and are suspected to play a significant ecological role, little is understood about species interactions and how competition between parasites can affect epidemic development and bloom formation. Here, three Planktothrix agardhii isolates from Sandusky Bay, Lake Erie (OH, USA) were challenged in monoculture and polyculture against infection by three isolates (C1, C2, C10) of their obligate chytrid fungal pathogen, Rhizophydiales sp. The chytrid isolates were inoculated as single isolates or a mixture of up to three different isolates. In monoculture, host isolates were characterized as highly susceptible (P. agardhii 1030), moderately susceptible (P. agardhii 1808) or mostly resistant (P. agardhii 1801). Co-infection of chytrid isolates on the highly susceptible host isolate had an additive effect on chytrid prevalence, leading to a culture crash where 2 or 3 chytrid isolates were present. Co-infection of chytrid isolates on the moderately susceptible and mostly resistant isolates had no effect on chytrid infection outcome or prevalence compared to infection with a single isolate. In polyculture, the effect on host growth was most significant in the single chytrid isolate treatment, which was attenuated with the addition of mixed chytrid treatments. Genetic analysis of the resulting population after the experimental period showed a tendency for the chytrid isolate C1 and P. agardhii 1801 to dominate in mixed population samples. Two different interspecific interactions seem to be in play; varied parasite infection strategies allow for the amplification of infection prevalence due to mixed chytrids in a susceptible monoculture, or competition allows for the dominance of a single chytrid isolate in monoculture and the reduction of infection prevalence in a host polyculture. This work thus highlights how interactions between chytrid infections can change the course of epidemic development and harmful algal bloom formation.