ОСОБЕННОСТИ ЛЕТНЕГО ПРОСТРАНСТВЕННОГО РАСПРЕДЕЛЕНИЯ ФОСФОРА, АЗОТА И ХЛОРОФИЛЛА-а В КРУПНОМ ЭВТРОФИРУЕМОМ АРКТИЧЕСКОМ ОЗЕРЕ ИМАНДРА (МУРМАНСКАЯ ОБЛАСТЬ) В СВЯЗИ С МАССОВЫМ РАЗВИТИЕМ ФОТОСИНТЕЗИРУЮЩИХ МИКРООРГАНИЗМОВ

The lake Imandra is a major Arctic water basin where harmful algal blooms (HABs) are observed regularly starting from the turn of the 20th and 21st centuries. HABs occur in the lake at significantly lower temperatures and phosphorus (P) and nitrogen (N) levels than in lakes located at lower latitudes. With regard to the above, the interrelationships between and the patterns of the spatial distributions of P, N and chlorophyll-a (Chl-a) in the upper layers of the lake have been considered. The complex outline of and strong gravity currents in the lake combined with potent focal anthropogenic sources of P and N determine the gradients of biogenic elements levels in the lake. Their examination suggest that HABs development is limited mutually by the levels of N and P and by their stoichiometric proportions. At the levels of total P and N (Ptot and Ntot) below 17 µg/L and 150 µg/L respectively, HABs probability is low. At Ptot>17 µg/L, HABs are limited by N rather than P. At Ntot>180 µg/L, HABs probability becomes increased. In the major part of the lake, N is mostly organic and NO3– levels are low, NH4+ being predominant among the inorganic forms of N. This makes conditions for the development of green algae and for the predominance of cyanobacteria. At [NO3-]:[NH4+] within 0.1 to 1.0, the probability of cyanoHABs is high. HABs development is promoted by [NO3-] > 2.5 µg/L upon [РО43-] > 3.1 µg/l, the N:P ratio being above 9.7. The ascertaining of the critical levels of N- and P-containing compounds will be useful in HABs forecasting and in understanding of HABs development in Arctic water basins.

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Growth performance of Alexandrium catenella from the Chilean fjords under different environmental drivers: plasticity as a response to a highly variable environment

Journal of Plankton Research ◽

10.1093/plankt/fbaa011 ◽

2020 ◽

Vol 42 (2) ◽

pp. 119-134 ◽

Cited By ~ 1

Author(s):

Javier Paredes-Mella ◽

Daniel Varela ◽

Pamela Fernández ◽

Oscar Espinoza-González

Keyword(s):

Light Intensity ◽

Growth Performance ◽

Harmful Algal Blooms ◽

Algal Blooms ◽

Optimal Growth ◽

N:P Ratio ◽

Environmental Drivers ◽

Growth Responses ◽

Variable Environment ◽

Alexandrium Catenella

Abstract Alexandrium catenella, the main species associated with harmful algal blooms, has progressively increased its distribution through one of the most extensive and highly variable fjord systems in the world. In order to understand this successful expansion, we evaluated the effects of different salinities, light intensity, temperatures, nitrogen (N) forms and nitrogen/phosphate (N:P) ratio levels on the growth performance, using clones isolated from different locations across its wide geographic distribution. Results showed that the growth responses were plastic and, in some cases, different reaction norms among clones were observed. Despite plasticity, the optimal growth of A. catenella (i.e. highest growth rate and highest maximal cells density) was reached within a narrow thermal range (12–15°C), while salinity (20–30 PSU) and light intensity (20–120 μmol m−2 s−1) ranges were wider. These results are partially consistent with the highest cell densities recorded in the field. Furthermore, optimal growth was reached using reduced forms of nitrogen (i.e. urea and NH4+) and in unbalanced N:P ratios (18:1 and 30:1). These characteristics likely allow A. catenella to grow in highly variable environmental conditions and might partly explain the recent expansion of this species.

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Unsteady Multi-Element Time Series Analysis and Prediction Based on Spatial-Temporal Attention and Error Forecast Fusion

Future Internet ◽

10.3390/fi12020034 ◽

2020 ◽

Vol 12 (2) ◽

pp. 34

Author(s):

Xiaofan Wang ◽

Lingyu Xu

Keyword(s):

Harmful Algal Blooms ◽

Algal Blooms ◽

Short Term Memory ◽

Sudden Change ◽

Back Propagation ◽

Red Tides ◽

Model Errors ◽

Chl A ◽

Error Forecast ◽

Concentration Prediction

Harmful algal blooms (HABs) often cause great harm to fishery production and the safety of human lives. Therefore, the detection and prediction of HABs has become an important issue. Machine learning has been increasingly used to predict HABs at home and abroad. However, few of them can capture the sudden change of Chl-a in advance and handle the long-term dependencies appropriately. In order to address these challenges, the Long Short-Term Memory (LSTM) based spatial-temporal attentions model for Chlorophyll-a (Chl-a) concentration prediction is proposed, a model which can capture the correlation between various factors and Chl-a adaptively and catch dynamic temporal information from previous time intervals for making predictions. The model can also capture the stage of Chl-a when values soar as red tide breaks out in advance. Due to the instability of the current Chl-a concentration prediction model, the model is also applied to make a prediction about the forecast reliability, to have a basic understanding of the range and fluctuation of model errors and provide a reference to describe the range of marine disasters. The data used in the experiment is retrieved from Fujian Marine Forecasts Station from 2009 to 2011 and is combined into 8-dimension data. Results show that the proposed approach performs better than other Chl-a prediction algorithms (such as Attention LSTM and Seq2seq and back propagation). The result of error prediction also reveals that the error forecast method possesses established advantages for red tides prevention and control.

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Nutrient Control to Prevent the Occurrence of Cyanobacterial Blooms in a Eutrophic Lake in Southern Sweden, Used for Drinking Water Supply

10.20944/preprints201804.0316.v1 ◽

2018 ◽

Author(s):

Jing Li ◽

Lars-Anders Hansson ◽

Kenneth M. Persson

Keyword(s):

Total Phosphorus ◽

Harmful Algal Blooms ◽

Algal Blooms ◽

Cyanobacterial Bloom ◽

Eutrophic Lake ◽

N:P Ratio ◽

Cyanobacterial Blooms ◽

Southern Sweden ◽

Dissolved Phosphorus ◽

Future Work

Control of nutrients, mainly nitrogen (N) and phosphorus (P), plays a significant role in preventing cyanobacterial blooms (harmful algal blooms (HABs)). This study aimed at evaluating changes in the risk of the occurrence of cyanobacterial blooms and advancing the understanding of how N and P affect the growth of cyanobacteria in a eutrophic lake, Lake Vombsjön, in southern Sweden. Statistical analysis was used to demonstrate the pattern of cyanobacterial blooms, that the highest content present in September and the later that algal blooms occur, the more likely it is a cyanobacterial bloom as cyanobacteria became dominating in October and November (90%). Two hypothesises tested in Lake Vombsjön confirmed namely that a high total phosphorus (TP) level correlates with an abundance of cyanobacteria and that low N:P ratio (total nitrogen/total phosphorus < 20) favours the growth of cyanobacteria. To control the growth of cyanobacteria in Lake Vombsjön, the TP level should be kept below 20 µg/L and the N:P ratio be maintained at a level of over 20. The two species Planktothrix agardhii, and Pseudanabaena spp. should be carefully monitored especially in late autumn. Future work should consider any high degree of leakage from the sediment of the dissolved phosphorus available there.

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The Use of Sentinel-3 Imagery to Monitor Cyanobacterial Blooms

Environments ◽

10.3390/environments6060060 ◽

2019 ◽

Vol 6 (6) ◽

pp. 60 ◽

Cited By ~ 2

Author(s):

Igor Ogashawara

Keyword(s):

Remote Sensing ◽

Harmful Algal Blooms ◽

Algal Blooms ◽

Lake Erie ◽

Water Governance ◽

Spectral Band ◽

Cyanobacterial Blooms ◽

Chl A ◽

Cyanobacterial Harmful Algal Blooms ◽

New Algorithms

Cyanobacterial harmful algal blooms (CHABs) have been a concern for aquatic systems, especially those used for water supply and recreation. Thus, the monitoring of CHABs is essential for the establishment of water governance policies. Recently, remote sensing has been used as a tool to monitor CHABs worldwide. Remote monitoring of CHABs relies on the optical properties of pigments, especially the phycocyanin (PC) and chlorophyll-a (chl-a). The goal of this study is to evaluate the potential of recent launch the Ocean and Land Color Instrument (OLCI) on-board the Sentinel-3 satellite to identify PC and chl-a. To do this, OLCI images were collected over the Western part of Lake Erie (U.S.A.) during the summer of 2016, 2017, and 2018. When comparing the use of traditional remote sensing algorithms to estimate PC and chl-a, none was able to accurately estimate both pigments. However, when single and band ratios were used to estimate these pigments, stronger correlations were found. These results indicate that spectral band selection should be re-evaluated for the development of new algorithms for OLCI images. Overall, Sentinel 3/OLCI has the potential to be used to identify PC and chl-a. However, algorithm development is needed.

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LSTM Networks to Improve the Prediction of Harmful Algal Blooms in the West Coast of Sabah

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18147650 ◽

2021 ◽

Vol 18 (14) ◽

pp. 7650

Author(s):

Fatin Nadiah Yussof ◽

Normah Maan ◽

Mohd Nadzri Md Reba

Keyword(s):

West Coast ◽

Harmful Algal Blooms ◽

Algal Blooms ◽

Time Series Data ◽

Short Term Memory ◽

Harmful Algal Bloom ◽

Series Data ◽

Severe Illness ◽

The West ◽

Chl A

Harmful algal bloom (HAB) events have alarmed authorities of human health that have caused severe illness and fatalities, death of marine organisms, and massive fish killings. This work aimed to perform the long short-term memory (LSTM) method and convolution neural network (CNN) method to predict the HAB events in the West Coast of Sabah. The results showed that this method could be used to predict satellite time series data in which previous studies only used vector data. This paper also could identify and predict whether there is HAB occurrence in the region. A chlorophyll a concentration (Chl-a; mg/L) variable was used as an HAB indicator, where the data were obtained from MODIS and GEBCO bathymetry. The eight-day dataset interval was from January 2003 to December 2018. The results obtained showed that the LSTM model outperformed the CNN model in terms of accuracy using RMSE and the correlation coefficient r as the statistical criteria.

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Long-Term Eutrophication and Dynamics of Bloom-Forming Microbial Communities during Summer HAB in Large Arctic Lake

Environments ◽

10.3390/environments8080082 ◽

2021 ◽

Vol 8 (8) ◽

pp. 82

Author(s):

Nikolay Kashulin ◽

Tatiana Kashulina ◽

Alexander Bekkelund

Keyword(s):

Microbial Communities ◽

Harmful Algal Blooms ◽

Algal Blooms ◽

Temporal Dynamics ◽

Arctic Lakes ◽

Genetic Traits ◽

Genetic Mechanisms ◽

Redfield Ratios ◽

Lake Imandra

Harmful algal blooms (HABs) in arctic lakes are recent phenomena. In our study, we performed a long-term analysis (1990–2017) of the eutrophication of Lake Imandra, a large subarctic lake, and explored the biodiversity of bloom-forming microorganisms of a 2017 summer HAB. We performed a 16Sr rRNA metabarcoding study of microbial communities, analysed the associations between N, P, C, and chlorophyll concentrations in the lake water, and developed models for the prediction of HABs based on total P concentration. We have demonstrated that blooms in Lake Imandra occur outside of optimal Redfield ratios and have a nonlinear association with P concentrations. We found that recent summer HABs in a lake occur as simultaneous blooms of a diatom Aulacoseira sp. and cyanobacteria Dolichospermum sp. We have studied the temporal dynamics of microbial communities during the bloom and performed an analysis of the publicly available Dolichospermum genomes to outline potential genetic mechanisms beneath simultaneous blooming. We found genetic traits requisite for diatom-diazotroph associations, which may lay beneath the simultaneous blooming of Aulacoseira sp. and Dolichospermum sp. in Lake Imandra. Both groups of organisms have the ability to store nutrients and form a dormant stage. All of these factors will ensure the further development of the HABs in Lake Imandra and the dispersal of these bloom-forming species to neighboring lakes.

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Kelimpahan Dinoflagellata Bentik Berbahaya di Habitat Lamun dan Makroalga di Pulau Pari, Kepulauan Seribu, Indonesia

Oseanologi dan Limnologi di Indonesia ◽

10.14203/oldi.2021.v6i3.382 ◽

2021 ◽

Vol 6 (3) ◽

pp. 191

Author(s):

Mochamad Ramdhan Firdaus ◽

Arief Rachman ◽

Oksto Ridho Sianturi ◽

Diah Anggraini Wulandari ◽

Hanny Meirinawati ◽

...

Keyword(s):

Harmful Algal Blooms ◽

Algal Blooms ◽

Principal Component ◽

N:P Ratio ◽

Artificial Substrates ◽

Marine Biota ◽

Nitrogen And Phosphorus ◽

Benthic Dinoflagellates ◽

Fish Poisoning ◽

Benthic Ecosystems

The Abundance of the Harmful Benthic Dinoflagellate in the Seagrass and Macroalgae Habitats on Pari Island, Thousand Islands, Indonesia. Benthic dinoflagellates are an important part of benthic ecosystems and part of their ecological functions. However, ciguatoxin (CTX) producer dinoflagellates, which could cause Ciguatera Fish Poisoning (CFP) disease, is a known threat to marine biota and the island’s coastal communities, such as in Pari Island. Thus, this research aimed is to study the population of five harmful and toxin producer benthic dinoflagellate genera, namely Amphidinium, Coolia, Gambierdiscus, Ostreopsis, and Prorocentrum, in macroalgae and seagrass habitats of Pari Island. Benthic dinoflagellate samples were collected in Juni 2019 using artificial substrates in the form of a 10×15 cm nylon screen. Environmental variables, such as nutrient concentration (nitrogen and phosphorus) and water temperature were also measured. The results showed that the average benthic dinoflagellate density in seagrass habitats was four times higher compared to the macroalgae habitats. Gambierdiscus were found as the most abundant benthic dinoflagellate in seagrass habitats, while Prorocentrum were more abundant in macroalgae habitats. Principal Component Analysis (PCA) showed that the N:P ratio was the most important regulating parameter for most benthic dinoflagellate genera in this study, except Ostreopsis, which was found to be more abundant in phosphorus-rich macroalga habitats. The data also shows an increase of benthic dinoflagellate cell density up to seven times compared to the previous research data in 2012 and 2013. That trend indicates an increase in the disturbance and pressure on the macroalgae and seagrass habitats of Pari Island, which require special attention to prevent the occurrence of toxic Benthic Harmful Algal Blooms (bHABs) and CFP cases in the island.

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A prolonged red tide of Heterocapsa triquetra (Ehrenberg) F. Stein (Dinophyceae) and phytoplankton succession in a eutrophic estuary in Turkey

Mediterranean Marine Science ◽

10.12681/mms.1049 ◽

2015 ◽

Vol 16 (3) ◽

pp. 621 ◽

Cited By ~ 6

Author(s):

S. TAS

Keyword(s):

Harmful Algal Blooms ◽

Algal Blooms ◽

Red Tide ◽

Prorocentrum Minimum ◽

Phytoplankton Succession ◽

Chl A ◽

Heterocapsa Triquetra ◽

Golden Horn ◽

Moderate Salinity ◽

Near Future

A prolonged red tide of Heterocapsa triquetra and phytoplankton succession were investigated in a eutrophic estuary (Golden Horn) for a year. Runoff following the rainfall in winter supplied high amounts of nutrients and also created a mesohaline frontal zone in the middle and upper estuary. Red tide of H. triquetra was first observed with an orange-brownish water discoloration at the upper estuary in January. Highest cell density of H. triquetra was 2.7×106 cells l-1 in January and reached to 19.2×106 cells l-1 in April. Successive blooms continued with dinoflagellate Prorocentrum minimum in May and phytoflagellates Eutreptiella marina and Fibrocapsa sp. in summer. High chl-a and dissolved oxygen were measured in the spring depending on algal biomass. Findings indicate that H. triquetra might be adapted to moderate salinity and low temperatures and red tide events should be considered as a response to increasing eutrophication due to high amounts of nutrients. Eutrophication can lead to harmful algal blooms for this area in the near future.

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Predicting water quality variability in a Mediterranean hypereutrophic monomictic reservoir using Sentinel-2 MSI: the importance of model functional form

10.5194/egusphere-egu21-2039 ◽

2021 ◽

Author(s):

Ibrahim Alameddine ◽

Mohamad Abbas

Keyword(s):

Water Quality ◽

Harmful Algal Blooms ◽

Algal Blooms ◽

Multivariate Adaptive Regression Splines ◽

Support Vector ◽

Negative Consequences ◽

Significant Drop ◽

Chl A ◽

Spatio Temporal ◽

Sentinel 2

Anthropogenic eutrophication is a pressing global environmental problem that threatens the ecological functions of many inland freshwaters and diminishes their abilities to meet their designated uses. Water authorities worldwide are being pressed to manage the negative consequences of harmful algal blooms (HABs) based largely on data collected from conventional monitoring programs that lack the needed spatio-temporal resolution for effective lake/reservoir management. This study assesses the potential of using Sentinel 2 MSI to predict and assess the spatio-temporal variability in the water quality of the Qaraoun Reservoir, a poorly-monitored Mediterranean hypereutrophic monomictic reservoir that is subject to extensive HABs during the growing season. The performance and transferability of water quality models previously calibrated based on Landsat 7 and 8 surface reflectance to predict Chlorophyll-a (Chl-a), total suspended solids (TSS), Secchi Disk Depth (SDD), and Phycocyanin (PC) levels in the reservoir are first assessed. The results showed poor transferability between Landsat and Sentinel 2, with all models experiencing a significant drop in their predictive skill. Sentinel 2 specific models were then developed for the reservoir based on 153 water quality samples collected over two years. Different model functional forms were then tested, including multiple linear regressions (MR), multivariate adaptive regression splines (MARS), and support vector regressions (SVR). Our results showed that for Chl-a, the MARS model outperformed MR and SVR, with an R2 of 60%. Meanwhile, the SVR-based models outperformed their MR and MARS counterparts for TSS, SDD and PC (R2 = 59%, 94%, and 72% respectively).

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Nutrient content and stoichiometry of pelagic Sargassum reflects increasing nitrogen availability in the Atlantic Basin

Nature Communications ◽

10.1038/s41467-021-23135-7 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

B. E. Lapointe ◽

R. A. Brewton ◽

L. W. Herren ◽

M. Wang ◽

C. Hu ◽

...

Keyword(s):

Harmful Algal Blooms ◽

Algal Blooms ◽

Nitrogen Availability ◽

North Atlantic Ocean ◽

Nutrient Content ◽

N:P Ratio ◽

N Availability ◽

Brown Macroalgae ◽

The North ◽

P Limitation

AbstractThe pelagic brown macroalgae Sargassum spp. have grown for centuries in oligotrophic waters of the North Atlantic Ocean supported by natural nutrient sources, such as excretions from associated fishes and invertebrates, upwelling, and N2 fixation. Using a unique historical baseline, we show that since the 1980s the tissue %N of Sargassum spp. has increased by 35%, while %P has decreased by 44%, resulting in a 111% increase in the N:P ratio (13:1 to 28:1) and increased P limitation. The highest %N and δ15N values occurred in coastal waters influenced by N-rich terrestrial runoff, while lower C:N and C:P ratios occurred in winter and spring during peak river discharges. These findings suggest that increased N availability is supporting blooms of Sargassum and turning a critical nursery habitat into harmful algal blooms with catastrophic impacts on coastal ecosystems, economies, and human health.

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