scholarly journals An overview of harmful algal blooms and eutrophication in Jakarta Bay, Indonesia

2021 ◽  
Vol 869 (1) ◽  
pp. 012039
Author(s):  
T Sidabutar ◽  
E S Srimariana ◽  
H Cappenberg ◽  
S Wouthuyzen
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Algal Bloom ◽  
Fish Mortality ◽  
Anthropogenic Activity ◽  
Red Tides ◽  
Cultural Eutrophication ◽  
Dry Seasons ◽  
Surrounding Areas ◽  
The City

Abstract Algal blooms have been occurring in Jakarta Bay for twenty years. However, recently the occurrence of algal blooms, their harmful effects, and their duration have been intensified. Algal blooms have devastated the marine environment, caused fish mortality, and been detrimental to local tourism, local fishing, and other industries along the coast. It comes to speculation that the increase of anthropogenic activity from surrounding areas is taking a toll on the environment. So, this research aimed to study the recent rise of algal blooms in Jakarta Bay and the possible anthropogenic links, mainly through cultural eutrophication, to the increasing occurrence of red tides and their impact. Observation has been conducted to study the dynamic of algal blooms concerning eutrophication and the existing seasons. Collecting samples were performed using a canonical plankton net from 2008 until 2015. The results showed that the abundance of phytoplankton ranged from 40.90 x 106 up to 1699.10 x 106 cells.m−3. The highest quantity of cells was observed in May 2010 between rainy to dry seasons. There is evidence that the reported increase in frequency and magnitude of algal bloom events in Jakarta Bay is linked to cultural eutrophication. The recent exponential growth of the city may be a contributing factor in the increasing intensity of algal blooms. The cultural eutrophication of coastal waters increased, leading to the intensity and frequency of algal bloom.

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

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.

scholarly journals Tracing the sources of nutrients fueling dinoflagellate red tides occurring along the coast of Korea using radium isotopes

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Hyeong Kyu Kwon ◽  
Guebuem Kim ◽  
Yongjin Han ◽  
Junhyeong Seo ◽  
Weol Ae Lim ◽  
...  
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Red Tide ◽  
Subsurface Layer ◽  
Vertical Mixing ◽  
Eastern Coast ◽  
Nutrient Concentrations ◽  
Red Tides ◽  
Radium Isotopes ◽  
Nutrient Sources

Abstract It is a well held concept that the magnitude of red-tide occurrence is dependent on the amount of nutrient supply if the conditions are same for temperature, salinity, light, interspecific competition, etc. However, nutrient sources fueling dinoflagellate red-tides are difficult to identify since red tides usually occur under very low inorganic-nutrient conditions. In this study, we used short-lived Ra isotopes (223Ra and 224Ra) to trace the nutrient sources fueling initiation and spread of Cochlodinium polykrikoides blooms along the coast of Korea during the summers of 2014, 2016, and 2017. Horizontal and vertical distributions of nutrient concentrations correlated well with 224Ra activities in nutrient-source waters. The offshore red-tide areas showed high 224Ra activities and low-inorganic and high-organic nutrient concentrations, which are favorable for blooming C. polykrikoides in competition with diatoms. Based on Ra isotopes, the nutrients fueling red-tide initiation (southern coast of Korea) are found to be transported horizontally from inner-shore waters. However, the nutrients in the spread region (eastern coast of Korea), approximately 200 km from the initiation region, are supplied continuously from the subsurface layer by vertical mixing or upwelling. Our study highlights that short-lived Ra isotopes are excellent tracers of nutrients fueling harmful algal blooms in coastal waters.

scholarly journals Red Tides

EDIS ◽  
2008 ◽  
Vol 2008 (3) ◽  
Author(s):  
Jorge R. Rey
Keyword(s):  
Human Health ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Marine Ecosystems ◽  
Red Tides ◽  
And Control

ENY-851, a 5-page illustrated factsheet by Jorge R. Rey, explains what these “harmful algal blooms” are, what causes them, their impacts on marine ecosystems, human health, and coastal economies, and strategies for mitigation and control. Includes references. Published by UF Entomology and Nematology Department, February 2008.

scholarly journals Fish Kill Incidents and Harmful Algal Blooms in Omani Waters

2011 ◽  
Vol 16 ◽  
pp. 23 ◽  
Author(s):  
Hamed Mohammed Al Gheilani ◽  
Kazumi Matsuoka ◽  
Abdulaziz Yahya AlKindi ◽  
Shehla Amer ◽  
Colin Waring
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Red Tide ◽  
Ecological Impacts ◽  
Red Tides ◽  
Fish Kill ◽  
Noctiluca Scintillans ◽  
Trichodesmium Erythraeum ◽  
Toxic Species ◽  
Desalination Plants

Red tide, one of the harmful algal blooms (HABs) is a natural ecological phenomenon and often this event is accompanied by severe impacts on coastal resources, local economies, and public health. The occurrence of red tides has become more frequent in Omani waters in recent years. Some of them caused fish kill, damaged fishery resources and mariculture, threatened the marine environment and the osmosis membranes of desalination plants. However, a number of them have been harmless. The most common dinoflagellate Noctiluca scintillans is associated with the red tide events in Omani waters. Toxic species like Karenia selliformis, Prorocentrum arabianum, and Trichodesmium erythraeum have also been reported recently. Although red tides in Oman have been considered a consequence of upwelling in the summer season (May to September), recent phytoplankton outbreaks in Oman are not restricted to summer. Frequent algal blooms have been reported during winter (December to March). HABs may have contributed to hypoxia and/or other negative ecological impacts. 

scholarly journals Cyanopeptides Restriction and Degradation Co-mediate Microbiota Assembly During a Freshwater Cyanobacterial Harmful Algal Bloom (CyanoHAB)

2022 ◽  
Author(s):  
Han Gao ◽  
Ze Zhao ◽  
Lu Zhang ◽  
Feng Ju
Keyword(s):  
Community Assembly ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Algal Bloom ◽  
Lake Taihu ◽  
Harmful Algal Bloom ◽  
Size Fraction ◽  
Freshwater Ecosystems ◽  
Cyanobacterial Harmful Algal Blooms ◽  
Microbiota Diversity

Cyanobacterial harmful algal blooms (CyanoHABs) are globally intensifying and exacerbated by climate change and eutrophication. However, microbiota assembly mechanisms underlying CyanoHABs remain scenario specific and elusive. Especially, cyanopeptides, as a group of bioactive secondary metabolites of cyanobacteria, could affect microbiota assembly and ecosystem function. Here, the trajectory of cyanopeptides were followed and linked to microbiota during Microcystis-dominated CyanoHABs in lake Taihu, China. The most abundant cyanopeptide classes detected included microginin, spumigin, microcystin, nodularin and cyanopeptolin with total MC-LR-equivalent concentrations between 0.23 and 2051.54 ppb, of which cyanotoxins beyond microcystins (e.g., cyanostatin B and nodularin_R etc.) far exceeded reported organismal IC50 and negatively correlated with microbiota diversity, exerting potential collective eco-toxicities stronger than microcystins alone. The microbial communities were differentiated by size fraction and sampling date throughout CyanoHABs, and surprisingly, their variances were better explained by cyanopeptides (19-38%) than nutrients (0-16%). Cyanopeptides restriction (e.g., inhibition) and degradation are first quantitatively verified as the deterministic drivers governing community assembly, with stochastic processes being mediated by interplay between cyanopeptide dynamics and lake microbiota. This study presents an emerging paradigm in which cyanopeptides restriction and degradation co-mediate lake water microbiota assembly, unveiling new insights about the ecotoxicological significance of CyanoHABs to freshwater ecosystems.

Resource fluctuation patterns influence emergent properties of phytoplankton assemblages and their resistance to harmful algal blooms

2020 ◽  
Vol 71 (1) ◽  
pp. 56 ◽  
Author(s):  
Daniel L. Roelke ◽  
Sierra E. Cagle ◽  
Rika M.W. Muhl ◽  
Athanasia Sakavara ◽  
George Tsirtsis
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Life History Traits ◽  
Algal Bloom ◽  
Harmful Algal Bloom ◽  
Emergent Properties ◽  
Resource Exploitation ◽  
Stable States ◽  
Phytoplankton Assemblages ◽  
High Degree

Recent advances in phytoplankton modelling have used species-rich, self-organising assemblages. These models have shown that phytoplankton with complementary life-history traits related to resource exploitation assemble into stable states of lumpy coexistence when resources fluctuate where species’ niches occur in clusters along resource gradients. They have also shown that a high degree of competitive dissimilarity between clusters arises, and that this relates to the incidence of monospecific blooms of allelochemical-producing taxa, i.e. some harmful algal bloom (HAB) species. These findings further suggest that the mode (sudden v. gradual changes) under which limiting resources fluctuate plays an important role in determining the emergent properties of the assemblage. For example, productivity, biodiversity and the number of species clusters (and, therefore, resistance to HABs) are all enhanced when switches in resource supplies are gradual, compared with when they are sudden. These theoretical findings, as well as others discussed herein, are of particular interest in watersheds where human activities, such as dam construction, have the capacity to dramatically alter natural-resource fluctuation patterns.

scholarly journals A Forecasting Method for Harmful Algal Bloom(HAB)-Prone Regions Allowing Preemptive Countermeasures Based only on Acoustic Doppler Current Profiler Measurements in a Large River

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3488
Author(s):  
Geunsoo Son ◽  
Dongsu Kim ◽  
Young Do Kim ◽  
Siwan Lyu ◽  
Soojeong Kim
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Algal Bloom ◽  
Hot Spot ◽  
Harmful Algal Bloom ◽  
Spatial Association ◽  
Acoustic Doppler Current Profiler ◽  
Large River ◽  
Concentration Data ◽  
Local Index

Harmful algal blooms (HABs) have been recognized as a serious problem for aquatic ecosystems and a threat to drinking water systems. The proposed method aimed to develop a practical and rapid countermeasure, enabling preemptive responses to massive algal blooms, through which prior to the algal bloom season we can identify HAB-prone regions based on estimations of where harmful algae initiates and develops significantly. The HAB-prone regions were derived from temperature, depth, flow velocity, and sediment concentration data based only on acoustic Doppler current profilers (ADCPs) without relying further on supplementary data collection, such as the water quality. For HAB-prone regions, we employed hot-spot analysis using K-means clustering and the Getis-Ord G*, in conjunction with the spatial autocorrelation of Moran’s I and the local index of spatial association (LISA). The validation of the derived HAB-prone regions was conducted for ADCP measurements located at the downstream of Nam and Nakdong River confluence, South Korea, which preceded three months of algal bloom season monitored by unmanned aerial vehicles (UAVs). The visual inspection demonstrated that the comparison resulted in an acceptable range of agreement and consistency between the predicted HAB-prone regions and actual UAV-based observations of actual algal blooms.

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