Isolation and characterization of a double stranded DNA mgavirus infecting the toxin-producing haptophyte Prymnesium parvum

Prymnesium parvum is a toxin-producing haptophyte that causes harmful algal blooms globally, leading to large-scale fish kills that have severe ecological and economic implications. For the model haptophyte, Emiliania huxleyi, it has been shown that large dsDNA viruses play an important role in regulating blooms and therefore biogeochemical cycling, but much less work has been done looking at viruses that infect P. parvum, or the role that these viruses may play in regulating harmful algal blooms. In this study, we report the isolation and characterization of a lytic nucleo-cytoplasmic large DNA virus (NCLDV) collected from the site of a harmful P. parvum bloom. In subsequent experiments, this virus was shown to infect cultures of Prymnesium sp. and showed phylogenetic similarity to the extended Megaviridae family of algal viruse

Climate Change and Eutrophication: A Short Review

Water resources are vital not only for human beings but essentially all ecosystems. Human health is at risk if clean drinking water becomes contaminated. Water is also essential for agriculture, manufacturing, energy production and other diverse uses. Therefore, a changing climate and its potential effects put more pressure on water resources. Climate change may cause increased water demand as a result of rising temperatures and evaporation while decreasing water availability. On the other hand, extreme events as a result of climate change can increase surface runoff and flooding, deteriorating water quality as well. One effect is water eutrophication, which occurs when high concentrations of nutrients, such as nitrogen and phosphorus, are present in the water. Nutrients come from different sources including agriculture, wastewater, stormwater, and fossil fuel combustion. Algal blooms can cause many problems, such as deoxygenation and water toxicity, ultimately disrupting normal ecosystem functioning. In this paper, we investigate the potential impacts of climatic factors affecting water eutrophication, how these factors are projected to change in the future, and what their projected potential impacts will be

Monitoring Coastal Chlorophyll-a Concentrations in Coastal Areas Using Machine Learning Models

Harmful algal blooms have negatively affected the aquaculture industry and aquatic ecosystems globally. Remote sensing using satellite sensor systems has been applied on large spatial scales with high temporal resolutions for effective monitoring of harmful algal blooms in coastal waters. However, oceanic color satellites have limitations, such as low spatial resolution of sensor systems and the optical complexity of coastal waters. In this study, bands 1 to 4, obtained from Landsat-8 Operational Land Imager satellite images, were used to evaluate the performance of empirical ocean chlorophyll algorithms using machine learning techniques. Artificial neural network and support vector machine techniques were used to develop an optimal chlorophyll-a model. Four-band, four-band-ratio, and mixed reflectance datasets were tested to select the appropriate input dataset for estimating chlorophyll-a concentration using the two machine learning models. While the ocean chlorophyll algorithm application on Landsat-8 Operational Land Imager showed relatively low performance, the machine learning methods showed improved performance during both the training and validation steps. The artificial neural network and support vector machine demonstrated a similar level of prediction accuracy. Overall, the support vector machine showed slightly superior performance to that of the artificial neural network during the validation step. This study provides practical information about effective monitoring systems for coastal algal blooms

Toward predicting Dinophysis blooms off NW Iberia: a decade of events

Dinophysis acuminata and Dinophysis acuta are recurrent species off NW Iberia but their outbreaks occur under different conditions. A decade (2004-2013) of weekly data for each species at two sentinel stations located at the entrance of Rias de Aveiro-AV (NW Portugal, 40 degrees 38.6' N) and Pontevedra-PO (Galicia, Spain, 42 degrees 21.5' N), were used to investigate the regional synchronism and mesoscale differences related to species detection, bloom (>200 cells L-1) initiation and development. Results highlight the high interannual variability of bloom events and summarize the associated meteorological/oceanographic conditions. D. acuta blooms were observed in 2004-2008 and 2013, and the species highest maxima at AV occurred after the highest maxima of its prey Mesodinium, with a time-lag of 2-3 weeks. D. acuminate blooms were observed every year at both stations. The cell concentration time series shows that the blooms generally present a sequence starting in March with D. acuminata in PO and three weeks later in AV, followed by D. acuta that starts at AV and three months later in PO. Exceptionally, D. acuminate blooms occurred earlier at AV than PO, namely in high spring upwelling (2007) or river runoff (2010) years. A four-year gap (2009-2012) of D. acuta blooms occurred after an anomalous 2008 autumn with intense upwelling which is interpreted as the result of an equatorward displacement of the population core. Numerical model solutions are used to analyze monthly alongshore current anomalies and test transport hypotheses for selected events. The results show a strong interannual variability in the poleward/equatorward currents associated with changes in upwelling forcing winds, the advection of D. acute blooms from AV to PO and the possibility that D. acuminata blooms at AV might result from inocula advected southward from PO. However, the sensitivity of the results to vertical position of the lagrangian tracers call for more studies on species distribution at the various bloom stages. (C) 2015 Elsevier B.V. All rights reserved

Comparison of the Functional and Numerical Responses of Resistant versus Non-resistant Populations of the Copepod Acartia Hudsonica Fed the Toxic Dinoflagellate Alexandrium Tamarense

The functional and numerical responses of grazers are key pieces of information in predicting and modeling predator–prey interactions. It has been demonstrated that exposure to toxic algae can lead to evolved resistance in grazer populations. However, the influence of resistance on the functional and numerical response of grazers has not been studied to date. Here, we compared the functional and numerical responses of populations of the copepod Acartia hudsonica that vary in their degree of resistance to the toxic dinoflagellate Alexandrium tamarense. In common environment experiments carried out after populations had been grown under identical conditions for several generations, female copepods were offered solutions containing different concentrations of either toxic A. tamarense or the non-toxic green flagellate Tetraselmis sp. ranging from ∼25 to 500 μgC L−1, and ingestion and egg production rates were measured. Throughout most of the range of concentrations of the toxic diet, copepod populations that had been historically exposed to toxic blooms of Alexandrium exhibited significantly higher ingestion and egg production rates than populations that had little or no exposure to these blooms. In contrast, there were no significant differences between populations in ingestion or egg production for the non-toxic diet. Hence, the between population differences in functional and numerical response to A. tamarense were indeed related to resistance. We suggest that the effect of grazer toxin resistance should be incorporated in models of predator and toxic prey interactions. The potential effects of grazer toxin resistance in the development and control of Alexandrium blooms are illustrated here with a simple simulation exercise

Drivers and food web effects of Gonyostomum semen blooms

The flagellate Gonyostomum semen forms dense late-summer blooms in humic lakes and is a nuisance to swimmers because it forms a slimy coat on the skin, causing irritation in sensitive individuals. Increasing occurrence and bloom incidence of G. semen has been reported during recent decades, but it is not clear which factors affect the distribution and bloom formation of this alga. Large cell size, ejection of long, slimy threads (trichocysts), and nighttime migration to the hypolimnion may limit grazing on G. semen by herbivorous zooplankton, resulting in a decreased coupling between phytoplankton and higher trophic levels during blooms. The studies included in this thesis investigate which factors affect G. semen occurrence and bloom formation and how G. semen blooms affect the community composition and trophic interactions in boreal, humic lakes. The occurrence of G. semen has increased between 1995 and 2010, especially in southern Sweden. Bloom incidence and total biomass did not increase continually, but fluctuated among years and peaked in the middle of the study period. Temperature and length of the growing season affected the occurrence and, to a lesser extent, bloom formation of G. semen, but local factors such as pH and water colour were more important for bloom formation. More lakes may become suitable habitats with the ongoing increase in water colour and increasing temperatures may result in a more frequent occurrence and bloom formation of G. semen. Blooms resulted in a shift in zooplankton assemblages toward predominance by small cladocerans, which were not able to feed on G. semen but instead fed more on heterotrophic food resources, supporting the hypothesis of a reduced coupling between phytoplankton and zooplankton. Zooplankton assemblages predominated by small animals feeding on low-quality resources may reduce the food quality for planktivorous fish. Instead, the invertebrate predator C. flavicans appeared to benefit from G. semen blooms, as indicated by its high abundance in bloom-lakes. Calanoid copepods and a large cladoceran fed efficiently on G. semen in the laboratory, indicating that there is, however, some trophic coupling between G. semen and higher trophic levels. This supports the use of biomanipulation of fish communities for controlling G. semen blooms

Do Cyanobacteria Blooms Enhance Parasite Loads in Lake Erie Yellow Perch?

Harmful Algal Blooms composed of cyanobacteria (HABs) are a major concern globally, especially in ecosystems that support commercial and recreational fisheries. Although HABs have been shown to negatively affect the services provided by ecosystems (e.g., safe water for drinking and recreation), their influence on fish populations, and fish health in particular, remains largely unknown. Given that Lake Erie has been experiencing large HABs during the past 15 years and supports important commercial and recreational fisheries, I sought to help Lake Erie agencies understand if HABs are posing a health risk to their valued fish populations. To this end, I explored the relationship between parasite loads in yellow perch (Perca flavescens), which supports Lake Erie’s largest commercial fishery and second largest recreational fishery, and cyanobacteria concentration. Specifically, I tested the hypothesis that parasite loads in the liver of young-of-year yellow perch would increase with increasing cyanobacteria concentration, as cyanotoxins associated with HABs (e.g., microcystin) have been shown to cause liver damage and physiological stress in other fish species. To answer this question, I measured parasite loads in 519 individuals captured from 54 sites across the western basin of Lake Erie during 2011-2019. My results were opposite of my expectations with mean liver parasite loads being negatively correlated with HAB severity. This finding, which was supported by other non-fish studies, suggests that HABs may actually benefit yellow perch by reducing parasite infections. Ultimately, my research points to the need for more research, if fisheries management agencies are truly to understand the net effect of HABs on their valued fishery resources.No embargoAcademic Major: Neuroscienc

Image processing for smart browsing of ocean colour data products and subsequent incorporation into a multi-modal sensing framework

Ocean colour is defined as the water hue due to the presence of tiny plants containing the pigment chlorophyll, sediments and coloured dissolved organic material and so water colour can provide valuable information on coastal ecosystems. The ‘Ocean Colour project’ collects data from various satellites (e.g. MERIS, MODIS) and makes this data available online. One method of searching the Ocean Colour project data is to visually browse level 1 and level 2 data. Users can search via location (regions), time and data type. They are presented with images which cover chlorophyll, quasi-true colour and sea surface temperature (11 μ) and links to the source data. However it is often preferable for users to search such a complex and large dataset by event and analyse the distribution of colour in an image before examination of the source data. This will allow users to browse and search ocean colour data more efficiently and to include this information more seamlessly into a framework that incorporates sensor information from a variety of modalities. This paper presents a system for more efficient management and analysis of ocean colour data and suggests how this information can be incorporated into a multi-modal sensing framework for a smarter, more adaptive environmental sensor network