Impacts of atmospheric stilling and climate warming on cyanobacterial blooms: An individual-based modelling approach

Harmful algal blooms of the freshwater cyanobacteria genus Microcystis are a global problem and are expected to intensify with climate change. In studies of climate change impacts on Microcystis blooms, atmospheric stilling has not been considered. Stilling is expected to occur in some regions of the world with climate warming, and it will affect lake stratification regimes. We tested if stilling could affect water column Microcystis distributions using a novel individual-based model (IBM). Using the IBM coupled to a three-dimensional hydrodynamic model, we assessed responses of colonial Microcystis biomass to wind speed decrease and air temperature increase projected under a future climate. The IBM altered Microcystis colony size using relationships with turbulence from the literature, and included light, temperature, and nutrient effects on Microcystis growth using input data from a shallow urban lake. The model results show that dynamic variations in colony size are critical for accurate prediction of cyanobacterial bloom development and decay. Colony size (mean and variability) increased more than six-fold for a 20% decrease in wind speed compared with a 2 °C increase in air temperature. Our results suggest that atmospheric stilling needs to be included in projections of changes in the frequency, distribution and magnitude of blooms of buoyant, colony-forming cyanobacteria under climate change

An Overview of Cyanobacteria Harmful Algal Bloom (CyanoHAB) Issues in Freshwater Ecosystems

This chapter will present an overview of cyanobacterial harmful algal blooms (cyanoHABs) and biotic and abiotic factors, as well as various aspects associated with these worldwide ecological bursts. The exact causes of the cyanoHABs are still not well defined, but eutrophication and climate change (temperature increase, light intensity variation, etc.) are the two assumed main factors that may promote the proliferation and expansion of cyanobacterial blooms. However, these premises need to be profoundly investigated as the optimal combination of all factors such as increased nutrient loading, physiological characteristics of cyanobacterial species, and climate effects which could lead to the blooming pattern will require robust modeling approaches to predict the phenomena. Negative issues associated with cyanoHABs are diverse including the toxic products (cyanotoxins) released by certain taxa which can damage the health of humans and animal habitats around the related watershed as well as generate a huge water quality problem for aquatic industries

Simulating Behavioral Microcystin Impairment in Fish

Fish experiencing blooms of the cyanobacteria genera Microcystis and Anabaena acquire microcystin and saxitoxin through ingestion of contaminated food and absorption of dissolved toxin. Even low chronic doses induce sensory and motor impairment—the impact of which is unquantified in wild populations. Here, I introduce Lagrangian particle models for cyanobacteria and fish which test the hypotheses that impairment symptoms suppress movement and growth. This is implemented within the Finite-Volume Coastal Ocean Model (FVCOM). Cyanobacteria particles move vertically according to mixing and buoyancy (a function of cellular reservoirs). Fish navigate the horizontal domain, foraging in high growth areas, and fleeing when toxin increases. The framework is demonstrated here for the case of juvenile fish encountering Microcystis aeruginosa in an idealized Louisiana estuary. Self-shading reduces bloom growth, and causes algae to collect at the surface. Turbulent diffusivity is insufficient to break up this layer, so dissolved toxin becomes surface-intensified. Fish seek high growth areas in this environment, and dietary uptake increases. This triggers flight and swimming impairment. As cyanobacteria excrete microcystin, absorption forces fish to become intoxicated even in areas of lower toxic risk. Repeated flight means fish spend more time in suboptimal areas, with final growth reduced up to 6.6%. In vivo, this would be exacerbated by physiological stress and the metabolic cost of toxin removal. Collective movement (group diffusivity) is suppressed nearly 50% during wide-spread intoxication. Simulations show that within a certain parameter space, both movement and growth are suppressed relative to the control case as expected. However, additional experiments resulted in higher growth, indicating the methods are sensitive to model parameterization. Ultimately, these are sandbox cases, which will require carefully-designed lab and field experiments before predictive capability can be assumed

CyanoNews (Vol. 10, No. 1, February 1994)

CyanoNews was a newsletter that served the cyanobacteriological community from 1985 to 2003, with content provided by readers (sort of a blog before there were blogs). The newsletter reported new findings from the lab, summaries of recent meetings (often provided by graduate students and post-docs entering the field), positions sought or available, life transitions, a compendium of recent cyanobacteria-related articles, and other items of interest to those who study cyanobacteria

Teadusuuringutest rakendusteni–optiliselt keerukate vete seire satelliitsensori MERIS/ENVISAT abil

Väitekirja elektrooniline versioon ei sisalda publikatsioone.Järved ja rannikuveed pakuvad olulisi ökosüsteemi teenuseid. Tagamaks veekeskkondade seire ja ökoloogilise seisundi hindamise on Euroopa Liidus loodud mitmeid direktiive ja regionaalseid konventsioone. Kuna vee kvaliteet võib olla muutlik nii sesoonselt kui ruumiliselt võimaldab kaugseire efektiivset seire meetodit, mille abil saab hinnata vee kvaliteedi hetkeolukorda, muutusi võrreldes varasema seisundiga ning seda ka veekogudes, mis ei ole kaetud tavaseireprogrammide raames. Käesolevas töös uuriti esimese spetsiaalselt optilistelt keerukate vete seireks loodud satelliitsensori MERIS/ENVISAT andmete kasutamisvõimalusi viie Põhja Euroopa järve ja kahe Läänemere rannikuala bio-optiliste andmete alusel. Olemasolevate MERIS standardalgoritmide õigsuse hinnang näitas, et need ei anna täpseid tulemusi veekogudes, kus on kõrge lahustunud orgaanilise aine ja klorofüll a hulk. Fütoplanktoni parameetrite (klorofüll a, sinivetikate biomass, fütoplanktoni biomass) hindamiseks kasutati punases ja lähisinfrapunases spektriosas töötavat spektraalset indeksit, mis kalibreeriti kohalikesse oludesse. Kuna indeks on rakendatav MERIS L1b andmetele, lubab see kvantitatiivselt hinnata vee kvaliteedi parameetreid sinivetika õitsengute korral, mille puhul MERIS standardalgoritmid ei tööta. Hindamaks kaugseire andmetest veealust valgusvälja, millest sõltub veealuste organismide elutegevus, loodi kaalufunktsioonidel põhinev kombineeritud kanalisuhte algoritm, mis selgemate vete puhul kasutab kanalite 490/709 suhet ning sogasemate puhul 560/70 ning hindab edukalt valguse difuusset nõrgenemiskoefitsienti, Kd(490), satelliidiandmetest. Secchi sügavuse hindamiseks andis parimaid tulemusi algoritm, mis võttis pikselhaaval sisendiks satellidiandmetest arvutatud diffusse ja summaarse nõrgenemiskoefitsiendi ning peegeldusteguri väärtused üle nähtava laineala. Töös arendatud algoritmid rakendati MERIS arhiivi 2002–2011 andmetele hindamaks erinevate järvede ökoloogilist seisundit nii nagu on nõutud EL veepoliitika raamdirektiivi poolt. Tulemused näitasid, et kaugseire andmeid saab kasutada täiendava infoallikana ökoloogilise seisundi hindamisel. Väljatöötatud algoritmid ja rakendused on kohandatavad 2016. aasta veebruaris tööd alustanud Sentinel-3/OLCI andmetele, mille abil on optiliselt keerukate vete seire kosmosest võimalik vähemalt aastani 2029.Lakes and coastal areas provide a wide range of essential ecosystem services. Various directives and regional conventions have been established to ensure the monitoring and assessment of the ecological status of the aquatic ecosystems. Since water quality can have rapid changes in temporal and spatial scale, remote sensing can provide a cost-effective approach to assess the current and derive historic water quality information also for waterbodies that have not been part of conventional monitoring programmes. This thesis presents research about applications for MERIS/ENVISAT data in order to monitor optically-complex aquatic environment such as inland and coastal waters on the basis of bio-optical data from five North European lakes and two Baltic Sea coastal sites. The validation of MERIS standard water quality products indicated their unsuitability for waters with high amounts of chlorophyll a and humic substances. To map the phytoplankton parameters (CHL, cyanobacterial biomass, phytoplankton biomass) a spectral index which operates on red and near-infrared bands was used and calibrated to local conditions. So, this index allows derivation of the water quality parameters quantitatively in case of highly scattering cyanobacterial blooms, which is not possible with standard algorithms. To estimate underwater light field via transparency, an empirical combined band ratio algorithm was developed which switches from various band ratios based on the water transparency and determines the diffuse attenuation coefficient Kd(490) with high accuracy. Additionally, Secchi depth can be also estimated reliably via satellite derived inputs of diffuse and total beam attenuation coefficients and reflectance over visible wavelengths. The developed algorithms were applied on the MERIS archive from 2002 to 2011 to estimate the ecological status in lakes as required by the EU Water Framework Directive which showed that remote sensing products could be used as an additional source of information for assessment and reporting purposes. Despite the study in this thesis is based on the MERIS/ENVISAT data, the developed algorithms and methods can be applied on new Sentinel3/OLCI data that will provide EO data over optically complex waters at least until 2029

Improving the Lake Erie HAB Tracker: A Forecasting & Decision Support Tool for Harmful Algal Blooms

This Master’s Project sought to improve the performance, data display and utility of the Lake Erie HAB Tracker model for predicting the location and movement of harmful algal blooms (HABs) in western Lake Erie. These improvements will benefit stakeholders by allowing public water systems to prepare for HAB events and by allowing anglers and boaters to avoid affected locations. Specifically, this research addressed three topics: 1) Microcystis colony rising/sinking (buoyant) velocity, a parameter in the HAB Tracker model, was measured using an improved method. Statistical relationships were obtained between buoyant velocity and environmental variables, showing lower buoyancy associated with greater light exposure, smaller colony size and deficient nutrient levels. 2) Model skill was assessed in comparison to satellite-derived HAB distributions using a neighborhood-based spatial smoothing method. We found that model skill was improved after spatial smoothing using a 3-km neighborhood. 3) We conducted a series of focus group interviews with Lake Erie fishing charter captains and recreational anglers to evaluate perceptions of HABs and the HAB Tracker. Our results indicated that the majority of anglers seek to avoid fishing in HABs, but that beliefs vary regarding the impact of HABs on fish and human health. We determined that anglers may find the HAB Tracker to be useful, but we recommend specific changes to improve the presentation of information on the HAB Tracker web site to make it more accessible. We also recommend improved content and methods of communication to better reflect angler concerns and interests.Master of ScienceNatural Resources and EnvironmentUniversity of Michiganhttps://deepblue.lib.umich.edu/bitstream/2027.42/136562/1/305_Improving Lake Erie HAB Tracker.pd

\u3ci\u3eTrichodesmium\u3c/i\u3e spp.: Numerical Studies of Resource Competition, Carbohydrate Ballasting, and Remote-Sensing Reflectance

In recent years, a new appreciation for the role of diazotrophy in the oceans has emerged. This dissertation reports on three modeling studies designed to investigate ecological processes associated with Trichodesmium spp., the most conspicuous marine diazotroph: (1) characterization of a generalized model Trichodesmium and issues of macronutrient resource competition; (2) carbohydrate ballasting by Trchodesmium and implications for the formation of surface accumulations; and (3) the vertical distribution of Trichodesmium and implications for detection from space. The first study focuses on issues of nitrogen and phosphorus competition and ecosystem structure. It utilizes a simple ecosystem model that includes dissolved nitrogen and phosphorus plus two classes each of primary producers, grazers, and particulate detritus. In a monoculture submodel, the Trichodesmium biomass is most sensitive to the nitrogen: phosphorus compositional ratio and the senescence and gross growth rates. In the competitive model, Trichodesmium is adversely affected by competitors for model phosphorus, while the contribution of diazotrophy to fueling non-diazotrophy new production is limited by the concomitant lack of other nutrients. This model\u27s outcome is most sensitive to the Trichodesmium gross growth and senescence rates. Experimental studies that would be particularly useful in this context include determination of the Trichodesmium half-saturation coefficient for phosphate, as well as quantitative co-occurrence data for Trichodesmium and Macrosetella gracilis. In the second study, an individual-based Lagrangian model is used to explore carbohydrate ballasting and its implications for Trichodesmium vertical distribution in quiescent waters. The model results indicate that mean population depth is controlled primarily by environmental conditions (incident irradiance and its vertical attenuation) and physiological rate parameters for ballast processes. Morphologic parameters have a greater effect on the amplitude of ballast-driven oscillations. Post-mixing quiescence, high incident irradiance, and high water clarity all encourage the formation of surface accumulations. Post-mixing quiescence produces a depth-segregated population, with the proportion ascending to the surface increasing as a function of water-column turbidity. This study provides insight into environmental and biological conditions that encourage Trichodesmium accumulation at the marine boundary layer and identifies key processes for further study. In the third study, a radiative transfer model is used to quantify the effects of Trichodesmium vertical distribution on remote-sensing reflectance, Rrs(λ). For the detection thresholds employed here, the model results indicate that surface accumulations of Trichodesmium can be detected when chlorophyll ≥1.5 mg m−3. For near-surface populations, R rs is most sensitive to chlorophyll concentration. For populations at 10–20 m depth, Rrs is most sensitive to population depth. Populations deeper than 20 m are not detected. These results, in conjunction with recent field surveys, indicate a detection rate of approximately 25%. These results have implications for ocean-color sensor and algorithm development and may have direct application to satellite estimations of N2-fixation. In summary, these three modeling studies confirm the importance of Trichodesmium in marine ecosystems. Moreover, these studies identify critical areas in which future research is required for illumination of the role of Trichodesmium in elemental cycling and marine ecosystems