OPTICAL MONITORING AND FORECASTING SYSTEMS FOR HARMFUL ALGAL BLOOMS: POSSIBILITY OR PIPE DREAM?

Monitoring programs for harmful algal blooms (HABs) are currently reactive and provide little or no means for advance warning. Given this, the development of algal forecasting systems would be of great use because they could guide traditional monitoring programs and provide a proactive means for responding to HABs. Forecasting systems will require near real-time observational capabilities and hydrodynamic/biological models designed to run in the forecast mode. These observational networks must detect and forecast over ecologically relevant spatial/ temporal scales. One solution is to incorporate a multiplatform optical approach utilizing remote sensing and in situ moored technologies. Recent advances in instrumentation and data-assimilative modeling may provide the components necessary for building an algal forecasting system. This review will outline the utility and hurdles of optical approaches in HAB detection and monitoring. In all the approaches, the desired HAB information must be isolated and extracted from the measured bulk optical signals. Examples of strengths and weaknesses of the current approaches to deconvolve the bulk optical properties are illustrated. After the phytoplankton signal has been isolated, species-recognition algorithms will be required, and we demonstrate one approach developed for Gymnodinium breve Davis. Pattern-recognition algorithms will be species-specific, reflecting the acclimation state of the HAB species of interest.Field data will provide inputs to optically based ecosystem models, which are fused to the observational networks through data-assimilation methods. Potential model structure and data-assimilation methods are reviewed.     

Molecular approaches to diagnosing nutritional physiology in harmful algae: Implications for studying the effects of eutrophication

Every year harmful algal blooms (HABs) cause serious impacts to local economies, coastal ecosystems, and human health on a global scale. It is well known that nutrient availability can influence important aspects of harmful algae biology and ecology, such as growth, toxin production, and life cycle stage, as well as bloom initiation, persistence and decline. Increases in the rate of supply of organic matter to ecosystems (eutrophication) carries many possible ramifications to coastal systems, including the potential for nutrient enrichment and the potential for stimulation of harmful algal blooms. Traditional studies on algal nutrition typically use either cultured isolates or community level assays, to examine nutrient uptake, nutrient preference, elemental composition, and other metrics of a species’ response to nutrients. In the last decade, technological advances have led to a great increase in the number of sequences available for critical harmful species. This, in turn, has led to new insights with regards to algal nutrition, and these advances highlight the promise of molecular technologies, and genomic approaches, to improving our understanding of algal nutrient acquisition and nutritional physiological ecology, in both cultures and field populations. With these developments increased monitoring of nutritional physiology in field populations of harmful algae will allow us to better discriminate how eutrophication impacts these groups.     

Reducing harmful algae in raw water by light-shading

The occurrence of harmful algal bloom in water source poses a serious water safety problem to local water supply systems. In order to ensure the raw water quality, the feasibility of an in situ light-shading measure was investigated through enclosure experiment and pilot-scale experiment. The results showed that harmful algal bloom could be controlled by light-shading lasting for 6–9 days, with water quality being partially improved. When aeration was added, the reduction of algal biomass could be enhanced, and water quality was further improved compared to that without aeration. These experimental results offered an attractive in situ algal control measure for lakes or reservoirs suffered from harmful algal bloom.     

Epilimnetic nutrient loading by metalimnetic erosion and resultant algal responses in Lake Waramaug,Connecticut

Phosphorus regeneration from lake sediments, and subsequent migration to trophogenic surface water, significantly contributes to the lake nutrient budgets and algal bloom conditions in some lake types. Decomposition of organic matter in deep water and sediments results in the accumulation of regenerated nutrients, alternate electron acceptors (reduced products of anaerobic respiration = COD), carbon dioxide, and depletion of dissolved oxygen (electron acceptor in aerobic respiration). Thermal stratification creates spatial segregation of trophogenic and tropholytic environments in the lake, resulting in gradients between sediments, hypolimnion, and the epilimnion. Exchange of oxygen, nutrients, and reduced alternate electron acceptors between the hypolimnion and epilimnion affects the productivity of a lake. Secchi depth, temperature, and dissolved oxygen profiles were determined twice each week from May 1980 to October 1980 at each of five lake stations. Nutrient concentration profiles, including total soluble and total phosphorus, ammonium-N, nitrate, soluble Kjeldahl, and total Kjeldahl nitrogen were determined twice each month. Epilimnetic algal samples were collected twice each week using Kemmerer and water column ‘straw’ amplers. Cell counts of total, green, bluegreen, and diatom algae groups were made. Three methods were used to describe hypolimnetic-epilimnetic exchange, including coefficients of eddy diffusion (based on lake heat budget), a graphical method of defining thermocline location, and relative thermal resistance to mixing (RTRM, based on density differences). All three methods yeilded comparable estimates of net seasonal transport. The graphical and RTRM methods described events occurring at shorter intervals (greater resolution). We find general agreement between the three methods of describing hypolimnetic-epilimnetic transport. The frequency of sampling resulted in increased resolution of thermal profiles (in time), allowing accurate estimation of short-term nutrient flux into epilimnetic waters. An algal bloom event occurred 5 to 12 days following erosion of the top of the metalimnion to below the aerobic-anaerobic interface. The lag time to peak algal concentration, following such events, decreased through the summer (June = 12 days, September = 5 days)     

2002-2018年滇池外海蓝藻水华暴发时空变化特征及其驱动因子

为弄清滇池外海蓝藻水华暴发时空变化规律及其影响因素,将滇池外海分为北、中、南3个区域,基于2002—2018年期间中分辨率成像光谱仪(MODIS)反演的水华面积,分析了上述3个区域蓝藻水华的时空变化特征。基于2007—2018年水文、气象和出入流数据,构建了外海三维水动力生态模型(AEM3D),并计算了各区域的水力滞留时间。通过冗余分析(RDA)、随机森林(RF)和斯皮尔曼相关分析方法,分析了影响以上区域蓝藻水华暴发的主要驱动因子。结果表明：2002—2018年期间,整个滇池外海区域年平均水华面积比(水华面积占该区域总面积比例)呈缓慢下降趋势,空间上由北向南依次递减,整个外海水华暴发面积最大主要发生在秋季。在外海北部区域,其东部水华较西部更为严重,而在中部和南部区域,呈现西部水华较东部更为严重的空间分布模式。通过对各影响因子的统计分析发现,风速、水温和日照时长是上述各区域中蓝藻水华暴发的主要决定性因素。水华暴发期间以西南风为主导风向,且上述区域的水华面积比随风速增加呈下降趋势。在外海各区域,水力滞留时间与水华暴发面积均呈显著正相关,空间上水力滞留时间由北向南逐渐增大,风速和风向是影响蓝...     

Use of a real-time remote monitoring network (RTRM) and shipborne sampling to characterize a dinoflagellate bloom in the Neuse Estuary, North Carolina, USA

The spatial-temporal distribution of a dinoflagellate bloom dominated or co-dominated by Prorocentrum minimum was examined during autumn through early spring in a warm temperate, eutrophic estuary. The developing bloom was first detected from a web-based alert provided by a network of real-time remote monitoring (RTRM) platforms indicating elevated dissolved oxygen and pH levels in upper reaches of the estuary. RTRM data were used to augment shipboard sampling, allowing for an in-depth characterization of bloom initiation, development, movement, and dissipation. Prolonged drought conditions leading to elevated salinities, and relatively high nutrient concentrations from upstream inputs and other sources, likely pre-disposed the upper estuary for bloom development. Over a 7-month period (October 2001–April 2002), the bloom moved toward the northern shore of the mesohaline estuary, intensified under favorable conditions, and finally dissipated after a major storm. Bloom location and transport were influenced by prevailing wind structure and periods of elevated rainfall. Chlorophyll a within bloom areas averaged 106 ± 13 μg L⁻¹ (mean ± 1 S.E.; maximum, 803 μg L⁻¹), in comparison to 20 ± 1 μg L⁻¹ outside the bloom. There were significant positive relationships between dinoflagellate abundance and TN and TP. Ammonium, NO₃⁻, and SRP concentrations did not decrease within the main bloom, suggesting that upstream inputs and other sources provided nutrient-replete conditions. In addition, PAM fluorometric measurements (09:00–13:00 h) of maximal PSII quantum yield (F_v/F_m) were consistently 0.6–0.8 within the bloom until late March, providing little evidence of photo-physiological stress as would have been expected under nutrient-limiting conditions. Nitrogen uptake kinetics were estimated for P. minimum during the period when that species was dominant (October–December 2001), based on literature values for N uptake by an earlier P. minimum bloom (winter 1999) in the Neuse Estuary. The analysis suggests that NH₄⁺ was the major N species that supported the bloom. Considering the chlorophyll a concentrations during October and December and the estimated N uptake rates, phytoplankton biomass was estimated to have doubled once per day. Bloom displacement (January–February) coincided with higher diversity of heterotrophic dinoflagellate species as P. minimum abundance decreased. This research shows the value of RTRM in bloom detection and tracking, and advances understanding of dinoflagellate bloom dynamics in eutrophic estuaries.     

水中病原微生物分子检测技术研究进展

基于PCR方法的多种分子检测技术已广泛的应用于水体病原微生物的检测中。而以DNA芯片为代表的微型化、快速化手段将是未来检测技术的发展方向,可实现对病原微生物实时和快速的检测。新检测技术的发展有利于建立水体污染早期预警机制,同时,可靠的病原微生物检测方法可降低有害微生物对人类健康的影响。对水体病原微生物分子检测方法及其在水污染相关疾病风险控制中所扮演的重要角色进行阐述。     

On-site rapid detection of toxic <Emphasis Type="Italic">Alexandrium tamiyavanichii</Emphasis>: integrating the species-specific hydrolysis probe in insulated isothermal polymerase chain reaction (iiPCR)

On-site investigation of phytoplankton samples is important for rapid detection of harmful algal species and for early warning of harmful algal bloom. Molecular detection method by DNA amplification in a portable insulated isothermal PCR (iiPCR) device provides a simple and rapid detection based on fluorescent probe within an hour of reaction time. The assay was developed for a paralytic shellfish toxin-producing dinoflagellate Alexandrium tamiyavanichii. The assay presents the data as positive or negative on the presence or absence of A. tamiyavanichii cells, with a limit of detection (LOD) at five target cells per reaction. While the assay is incapable to accurately quantify cell density, it exhibits high detection accuracy and strongly correlated with quantitative PCR (qPCR) data. The user repeatability of iiPCR assay was evaluated; the results showed that no significant differences in the assay run by different operators. Field applicability of the assay was further validated by environmental samples. Despite the shortcoming of the assay, the overall performance of the assay to detect cells, its low-cost effectiveness, and portability for on-site detection, iiPCR has proven its potential as an early screening tool for harmful algae monitoring.     

Progress and opportunities in advancing near-term forecasting of freshwater quality

Near-term freshwater forecasts, defined as sub-daily to decadal future predictions of a freshwater variable with quantified uncertainty, are urgently needed to improve water quality management as freshwater ecosystems exhibit greater variability due to global change. Shifting baselines in freshwater ecosystems due to land use and climate change prevent managers from relying on historical averages for predicting future conditions, necessitating near-term forecasts to mitigate freshwater risks to human health and safety (e.g., flash floods, harmful algal blooms) and ecosystem services (e.g., water-related recreation and tourism). To assess the current state of freshwater forecasting and identify opportunities for future progress, we synthesized freshwater forecasting papers published in the past 5 years. We found that freshwater forecasting is currently dominated by near-term forecasts of water quantity and that near-term water quality forecasts are fewer in number and in the early stages of development (i.e., non-operational) despite their potential as important preemptive decision support tools. We contend that more freshwater quality forecasts are critically needed and that near-term water quality forecasting is poised to make substantial advances based on examples of recent progress in forecasting methodology, workflows, and end-user engagement. For example, current water quality forecasting systems can predict water temperature, dissolved oxygen, and algal bloom/toxin events 5 days ahead with reasonable accuracy. Continued progress in freshwater quality forecasting will be greatly accelerated by adapting tools and approaches from freshwater quantity forecasting (e.g., machine learning modeling methods). In addition, future development of effective operational freshwater quality forecasts will require substantive engagement of end users throughout the forecast process, funding, and training opportunities. Looking ahead, near-term forecasting provides a hopeful future for freshwater management in the face of increased variability and risk due to global change, and we encourage the freshwater scientific community to incorporate forecasting approaches in water quality research and management.     

The potential role of anthropogenically derived nitrogen in the growth of harmful algae in California,USA

Cultural eutrophication is frequently invoked as one factor in the global increase in harmful algal blooms, but is difficult to definitively prove due to the myriad of factors influencing coastal phytoplankton bloom development. To assess whether eutrophication could be a factor in the development of harmful algal blooms in California (USA), we review the ecophysiological potential for urea uptake by Pseudo-nitzschia australis (Bacillariophyceae), Heterosigma akashiwo (Raphidophyceae), and Lingulodinium polyedrum (Dinophyceae), all of which have been found at bloom concentrations and/or exhibited noxious effects in recent years in California coastal waters. We include new measurements from a large (Chlorophyll a > 500 mg m⁻³) red tide event dominated by Akashiwo sanguinea (Dinophyceae) in Monterey Bay, CA during September 2006. All of these phytoplankton are capable of using nitrate, ammonium, and urea, although their preference for these nitrogenous substrates varies. Using published data and recent coastal time series measurements conducted in Monterey Bay and San Francisco Bay, CA, we show that urea, presumably from coastal eutrophication, was present in California waters at measurable concentrations during past harmful algal bloom events. Based on these observations, we suggest that urea uptake could potentially sustain these harmful algae, and that urea, which is seldom measured as part of coastal monitoring programs, may be associated with these harmful algal events in California.     

How well can we forecast high biomass algal bloom events in a eutrophic coastal sea?

High biomass algal bloom events are a characteristic of eutrophic coastal waters; these may result both in ecosystem degradation and economic loss. We present a skill evaluation of a coupled hydrodynamic ecosystem model of the NW European shelf for predicting bloom events based on a comparison with satellite chlorophyll estimates. By setting thresholds to define bloom events we use a binary classification system to generate maps showing the probability a model bloom prediction is correct. Model and satellite data limitations are discussed along with the application of this method to forecasting specific harmful algal species.     

Retrospective eDNA assessment of potentially harmful algae in historical ship ballast tank and marine port sediments

Microalgal bloom events can cause major ecosystem disturbances, devastate local marine economies, and endanger public health. Therefore, detecting and monitoring harmful microalgal taxa is essential to ensure effective risk management in waterways used for fisheries, aquaculture, recreational activity, and shipping. To fully understand the current status and future direction of algal bloom distributions, we need to know how populations and ecosystems have changed over time. This baseline knowledge is critical for predicting ecosystem responses to future anthropogenic change and will assist in the future management of coastal ecosystems. We explore a NGS metabarcoding approach to rapidly identify potentially harmful microalgal taxa in 63 historic and modern Australian marine port and ballast tank sediment samples. The results provide a record of past microalgal distribution and important baseline data that can be used to assess the efficacy of shipping guidelines, nutrient pollution mitigation, and predict the impact of climate change. Critically, eDNA surveys of archived sediments were able to detect harmful algal taxa that do not produce microscopic fossils, such as Chattonella, Heterosigma, Karlodinium, and Noctiluca. Our data suggest a potential increase in Australian harmful microalgal taxa over the past 30 years, and confirm ship ballast tanks as key dispersal vectors. These molecular mapping tools will assist in the creation of policies aimed at reducing the global increase and spread of harmful algal taxa and help prevent economic and public‐health problems caused by harmful algal blooms.     

Intelligent infrastructure for sustainable potable water: a roundtable for emerging transnational research and technology development needs

PROBLEM STATEMENT: Recent commercial and residential development have substantially impacted the fluxes and quality of water that recharge the aquifers and discharges to streams, lakes and wetlands and, ultimately, is recycled for potable use. Whereas the contaminant sources may be varied in scope and composition, these issues of urban water sustainability are of public health concern at all levels of economic development worldwide, and require cheap and innovative environmental sensing capabilities and interactive monitoring networks, as well as tailored distributed water treatment technologies. To address this need, a roundtable was organized to explore the potential role of advances in biotechnology and bioengineering to aid in developing causative relationships between spatial and temporal changes in urbanization patterns and groundwater and surface water quality parameters, and to address aspects of socioeconomic constraints in implementing sustainable exploitation of water resources. WORKSHOP OUTCOMES: An interactive framework for quantitative analysis of the coupling between human and natural systems requires integrating information derived from online and offline point measurements with Geographic Information Systems (GIS)-based remote sensing imagery analysis, groundwater-surface water hydrologic fluxes and water quality data to assess the vulnerability of potable water supplies. Spatially referenced data to inform uncertainty-based dynamic models can be used to rank watershed-specific stressors and receptors to guide researchers and policymakers in the development of targeted sensing and monitoring technologies, as well as tailored control measures for risk mitigation of potable water from microbial and chemical environmental contamination. The enabling technologies encompass: (i) distributed sensing approaches for microbial and chemical contamination (e.g. pathogens, endocrine disruptors); (ii) distributed application-specific, and infrastructure-adaptive water treatment systems; (iii) geostatistical integration of monitoring data and GIS layers; and (iv) systems analysis of microbial and chemical proliferation in distribution systems. IMPACT: This operational framework is aimed at technology implementation while maximizing economic and public health benefits. The outcomes of the roundtable will further research agendas in information technology-based monitoring infrastructure development, integration of processes and spatial analysis, as well as in new educational and training platforms for students, practitioners and regulators. The potential for technology diffusion to emerging economies with limited financial resources is substantial.     

Harmful algal blooms: causes,impacts and detection

Blooms of autotrophic algae and some heterotrophic protists are increasingly frequent in coastal waters around the world and are collectively grouped as harmful algal blooms (HABs). Blooms of these organisms are attributed to two primary factors: natural processes such as circulation, upwelling relaxation, and river flow; and, anthropogenic loadings leading to eutrophication. Unfortunately, the latter is commonly assumed to be the primary cause of all blooms, which is not the case in many instances. Moreover, although it is generally acknowledged that occurrences of these phenomena are increasing throughout the world's oceans, the reasons for this apparent increase remain debated and include not only eutrophication but increased observation efforts in coastal zones of the world. There is a rapidly advancing monitoring effort resulting from the perception of increased impacts from these HABs, manifested as expanding routine coastal monitoring programs, rapid development and deployment of new detection methods for individual species, toxins, and toxicities, and expansion of coastal modeling activities towards observational forecasts of bloom landfall and eventually bloom prediction. Together, these many efforts will provide resource managers with the tools needed to develop effective strategies for the management and mitigation of HABs and their frequently devastating impacts on the coastal environment.     

Remote, subsurface detection of the algal toxin domoic acid onboard the Environmental Sample Processor: Assay development and field trials

The ability to detect harmful algal bloom (HAB) species and their toxins in real- or near real-time is a critical need for researchers studying HAB/toxin dynamics, as well as for coastal resource managers charged with monitoring bloom populations in order to mitigate their wide ranging impacts. The Environmental Sample Processor (ESP), a robotic electromechanical/fluidic system, was developed for the autonomous, subsurface application of molecular diagnostic tests and has successfully detected several HAB species using DNA probe arrays during field deployments. Since toxin production and thus the potential for public health and ecosystem effects varies considerably in natural phytoplankton populations, the concurrent detection of HAB species and their toxins onboard the ESP is essential. We describe herein the development of methods for extracting the algal toxin domoic acid (DA) from Pseudo-nitzschia cells (extraction efficiency >90%) and testing of samples using a competitive ELISA onboard the ESP. The assay detection limit is in the low ng/mL range (in extract), which corresponds to low ng/L levels of DA in seawater for a 0.5 L sample volume acquired by the ESP. We also report the first in situ detection of both a HAB organism (i.e., Pseudo-nitzschia) and its toxin, domoic acid, via the sequential (within 2–3 h) conduct of species- and toxin-specific assays during ESP deployments in Monterey Bay, CA, USA. Efforts are now underway to further refine the assay and conduct additional calibration exercises with the aim of obtaining more reliable, accurate estimates of bloom toxicity and thus their potential impacts.     

Biochemistry and genetics of taste- and odor-producing cyanobacteria

Cyanobacteria are one of the principal sources of volatile organic compounds (VOCs) which cause offensive taste and odor (T&O) in drinking and recreational water, fish, shellfish and other seafood. Although non-toxic to humans, these T&O compounds severely undermine public trust in these commodities, resulting in substantial costs in treatment, and lost revenue to drinking water, aquaculture, food and beverage and tourist/hospitality industries. Mitigation and control have been hindered by the complexity of the communities and processes which produce and modify T&O events, making it difficult to source-track the major producer(s) and the factors governing VOC production and fate. Over the past decade, however, advances in bioinformatics, enzymology, and applied detection technologies have greatly enhanced our understanding of the pathways, the enzymes and the genetic coding for some of the most problematic VOCs produced by cyanobacteria. This has led to the development of tools for rapid and sensitive detection and monitoring for the VOC production at source, and provided the basis for further diagnostics of endogenous and exogenous controls. This review provides an overview of current knowledge of the major cyanobacterial VOCs, the producers, the biochemistry and the genetics and highlight the current applications and further research needs in this area.     

Improved monitoring of HABs using autonomous underwater vehicles (AUV)

Blooms of toxic algae are increasing in magnitude and frequency around the globe, causing extensive economic and environmental impacts. On the west coast of Florida, blooms of the toxic dinoflagellate Karenia brevis (Davis) have been documented annually for the last 30 years causing respiratory irritation in humans, fish kills, and toxin bioaccumulation in shellfish beds. As a result, methods need to be established to monitor and predict bloom formation and transport to mitigate their harmful effects on the surrounding ecosystems and local communities. In the past, monitoring and mitigation efforts have relied on visual confirmation of water discoloration, fish kills, and laborious cell counts, but recently satellite remote sensing has been used to track harmful algal blooms (HABs) along the Florida coast. Unfortunately satellite ocean color is limited by cloud cover, lack of detection below one optical depth, and revisit frequency, all of which can lead to extended periods without data. To address these shortcomings, an optical phytoplankton discriminator (OPD) was developed to detect K. brevis cells in mixed phytoplankton assemblages. The OPD was integrated into autonomous underwater vehicle (AUV) platforms to gather spatially and temporally relevant data that can be used in collaboration with satellite imagery to provide a 3D picture of bloom dynamics over time. In January 2005, a Remote Environmental Monitoring UnitS (REMUS) AUV with an OPD payload was deployed on the west coast of Florida to retrieve a similarity index (SI), which indicates when K. brevis dominates the phytoplankton community. SI was used to monitor a K. brevis bloom in relation to temperature, salinity, chlorophyll, and ocean currents. Current speed, SI, temperature, salinity, and chlorophyll a from the AUV were used to quantify a 1 km displacement of the K. brevis bloom front that was observed over the deployment period. The ability to monitor short term bloom movement will improve monitoring and predictive efforts that are used to provide warnings for local tourism and fishing industries. In addition, understanding the fine scale environmental conditions associated with bloom formation will increase our ability to predict the location and timing of K. brevis bloom formation. This study demonstrates the use of one autonomous platform and provides evidence that a nested array of AUVs and moorings equipped with new sensors, combined with remote sensing, can provide an early warning and monitoring system to reduce the impact of HABs.     

Development of real-time PCR assays for rapid detection of Pfiesteria piscicida and related dinoflagellates

Pfiesteria complex species are heterotrophic and mixotrophic dinoflagellates that have been recognized as harmful algal bloom species associated with adverse fish and human health effects along the East Coast of North America, particularly in its largest (Chesapeake Bay in Maryland) and second largest (Albermarle-Pamlico Sound in North Carolina) estuaries. In response to impacts on human health and the economy, monitoring programs to detect the organism have been implemented in affected areas. However, until recently, specific identification of the two toxic species known thus far, Pfiesteria piscicida and P. shumwayae (sp. nov.), required scanning electron microscopy (SEM). SEM is a labor-intensive process in which a small number of cells can be analyzed, posing limitations when the method is applied to environmental estuarine water samples. To overcome these problems, we developed a real-time PCR-based assay that permits rapid and specific identification of these organisms in culture and heterogeneous environmental water samples. Various factors likely to be encountered when assessing environmental samples were addressed, and assay specificity was validated through screening of a comprehensive panel of cultures, including the two recognized Pfiesteria species, morphologically similar species, and a wide range of other estuarine dinoflagellates. Assay sensitivity and sample stability were established for both unpreserved and fixative (acidic Lugol's solution)-preserved samples. The effects of background DNA on organism detection and enumeration were also explored, and based on these results, we conclude that the assay may be utilized to derive quantitative data. This real-time PCR-based method will be useful for many other applications, including adaptation for field-based technology.     

太湖水华程度及其生态环境因子的时空分布特征

湖泊水华是全世界面临的严重生态环境问题之一,对人类和生态系统健康都有重大影响。由于湖泊水华受流域面源、点源污染、气候、水文因子以及湖泊生态系统自身特征等众多因素影响,水华是否爆发、其严重程度及时空分布特征呈现明显的复杂性。以我国太湖为研究区域,基于近年的水华及水环境的监测数据,用自组织特征映射神经网络对太湖不同监测点的水华程度进行了自动聚类分析。结果表明,太湖水华程度呈现为明显的无水华、轻度、中度和重度水华4类。不同程度水华的叶绿素a、水温、COD_(Mn)、营养盐、浮游植物生物量以及藻种(蓝藻、绿藻、硅藻)结构的时空差异显著,不同变量间的关系复杂,有助于深入认识太湖近年水华发生的时空变异特性。     

Assessing and managing nutrient-enhanced eutrophication in estuarine and coastal waters: Interactive effects of human and climatic perturbations

Estuaries are among the most productive, resourceful, and dynamic aquatic ecosystems on Earth. Their productive nature is linked to the fact that they process much of the world's riverine and coastal watershed discharge. These watersheds support more than 75% of the human population and are sites of large increases in nutrient loading associated with urban and agricultural expansion. Increased nutrient loading has led to accelerated primary production, or eutrophication; symptoms include increased algal bloom activity (including harmful taxa), accumulation of organic matter, and excessive oxygen consumption (hypoxia and anoxia). While nutrient-enhanced eutrophication is a “driver” of hypoxia and anoxia, physical–chemical alterations due to climatic events, such as stormwater discharge, flooding, droughts, stagnancy, and elevated temperatures are also involved. The complex interactions of anthropogenic and climatic factors determine the magnitude, duration, and aerial extent of productivity, algal booms, hypoxia, and anoxia. Using the eutrophic Neuse River Estuary (NRE), North Carolina, USA, as a case study, the physical–chemical mechanisms controlling algal bloom and hypoxia dynamics were examined. Because primary production in the NRE and many other estuaries is largely nitrogen (N) limited, emphasis has been placed on reducing N inputs. Both the amounts and chemical forms of N play roles in determining the composition and extent of phytoplankton blooms that supply the bulk of the organic carbon fueling hypoxia. Biomass from bloom organisms that are readily grazed will be readily transferred up the planktonic and benthic food chain, while toxic or inedible blooms frequently promote sedimentary C flux, microbial mineralization, and hence may exacerbate hypoxia potential. From a watershed perspective, nutrient input reductions are the main options for reducing eutrophication. Being able to distinguish the individual and cumulative effects of physical, chemical and biotic controls of phytoplankton productivity and composition is key to understanding, predicting, and ultimately managing eutrophication. Long-term collaborative (University, State, Federal) monitoring, experimental assessments, and modeling of eutrophication dynamics over appropriate spatial and temporal scales is essential for developing realistic, ecologically sound, and cost-effective nutrient management strategies for estuarine and coastal ecosystems impacted by both anthropogenic and climatic perturbations.