Satellite discrimination of Karenia mikimotoi and Phaeocystis harmful algal blooms in European coastal waters: Merged classification of ocean colour data

The detection of dense harmful algal blooms (HABs) by satellite remote sensing is usually based on analysis of chlorophyll-a as a proxy. However, this approach does not provide information about the potential harm of bloom, nor can it identify the dominant species. The developed HAB risk classification method employs a fully automatic data-driven approach to identify key characteristics of water leaving radiances and derived quantities, and to classify pixels into “harmful”, “non-harmful” and “no bloom” categories using Linear Discriminant Analysis (LDA). Discrimination accuracy is increased through the use of spectral ratios of water leaving radiances, absorption and backscattering. To reduce the false alarm rate the data that cannot be reliably classified are automatically labelled as “unknown”. This method can be trained on different HAB species or extended to new sensors and then applied to generate independent HAB risk maps; these can be fused with other sensors to fill gaps or improve spatial or temporal resolution. The HAB discrimination technique has obtained accurate results on MODIS and MERIS data, correctly identifying 89% of Phaeocystis globosa HABs in the southern North Sea and 88% of Karenia mikimotoi blooms in the Western English Channel. A linear transformation of the ocean colour discriminants is used to estimate harmful cell counts, demonstrating greater accuracy than if based on chlorophyll-a; this will facilitate its integration into a HAB early warning system operating in the southern North Sea.

Drivers and effects of Karenia mikimotoi blooms in the western English Channel

Naturally occurring red tides and harmful algal blooms (HABs) are of increasing importance in the coastal environment and can have dramatic effects on coastal benthic and epipelagic communities worldwide. Such blooms are often unpredictable, irregular or of short duration, and thus determining the underlying driving factors is problematic. The dinoflagellate Karenia mikimotoi is an HAB, commonly found in the western English Channel and thought to be responsible for occasional mass finfish and benthic mortalities. We analysed a 19-year coastal time series of phytoplankton biomass to examine the seasonality and interannual variability of K. mikimotoi in the western English Channel and determine both the primary environmental drivers of these blooms as well as the effects on phytoplankton productivity and oxygen conditions. We observed high variability in timing and magnitude of K. mikimotoi blooms, with abundances reaching >1000 cells mL�1 at 10 m depth, inducing up to a 12-fold increase in the phytoplankton carbon content of the water column. No long-term trends in the timing or magnitude of K. mikimotoi abundance were evident from the data. Key driving factors were identified as persistent summertime rainfall and the resultant input of low-salinity high-nutrient river water. The largest bloom in 2009 was associated with highest annual primary production and led to considerable oxygen depletion at depth, most likely as a result of enhanced biological breakdown of bloom material; however, this oxygen depletion may not affect zooplankton. Our data suggests that K. mikimotoi blooms are not only a key and consistent feature of western English Channel productivity, but importantly can potentially be predicted from knowledge of rainfall or river discharge.

Individual-based modelling of the development and transport of a Karenia mikimotoi bloom on the North-West European continental shelf

In 2006, a large and prolonged bloom of the dinoflagellate Karenia mikimotoi occurred in Scottish coastal waters, causing extensive mortalities of benthic organisms including annelids and molluscs and some species of fish ( Davidson et al., 2009). A coupled hydrodynamic-algal transport model was developed to track the progression of the bloom around the Scottish coast during June–September 2006 and hence investigate the processes controlling the bloom dynamics. Within this individual-based model, cells were capable of growth, mortality and phototaxis and were transported by physical processes of advection and turbulent diffusion, using current velocities extracted from operational simulations of the MRCS ocean circulation model of the North-west European continental shelf. Vertical and horizontal turbulent diffusion of cells are treated using a random walk approach. Comparison of model output with remotely sensed chlorophyll concentrations and cell counts from coastal monitoring stations indicated that it was necessary to include multiple spatially distinct seed populations of K. mikimotoi at separate locations on the shelf edge to capture the qualitative pattern of bloom transport and development. We interpret this as indicating that the source population was being transported northwards by the Hebridean slope current from where colonies of K. mikimotoi were injected onto the continental shelf by eddies or other transient exchange processes. The model was used to investigate the effects on simulated K. mikimotoi transport and dispersal of: (1) the distribution of the initial seed population; (2) algal growth and mortality; (3) water temperature; (4) the vertical movement of particles by diurnal migration and eddy diffusion; (5) the relative role of the shelf edge and coastal currents; (6) the role of wind forcing. The numerical experiments emphasized the requirement for a physiologically based biological model and indicated that improved modelling of future blooms will potentially benefit from better parameterisation of temperature dependence of both growth and mortality and finer spatial and temporal hydrodynamic resolution.

Individual-based modelling of the development and transport of a Karenia mikimotoi bloom on the North-West European continental shelf

In 2006, a large and prolonged bloom of the dinoflagellate Karenia mikimotoi occurred in Scottish coastal waters, causing extensive mortalities of benthic organisms including annelids and molluscs and some species of fish ( Davidson et al., 2009). A coupled hydrodynamic-algal transport model was developed to track the progression of the bloom around the Scottish coast during June–September 2006 and hence investigate the processes controlling the bloom dynamics. Within this individual-based model, cells were capable of growth, mortality and phototaxis and were transported by physical processes of advection and turbulent diffusion, using current velocities extracted from operational simulations of the MRCS ocean circulation model of the North-west European continental shelf. Vertical and horizontal turbulent diffusion of cells are treated using a random walk approach. Comparison of model output with remotely sensed chlorophyll concentrations and cell counts from coastal monitoring stations indicated that it was necessary to include multiple spatially distinct seed populations of K. mikimotoi at separate locations on the shelf edge to capture the qualitative pattern of bloom transport and development. We interpret this as indicating that the source population was being transported northwards by the Hebridean slope current from where colonies of K. mikimotoi were injected onto the continental shelf by eddies or other transient exchange processes. The model was used to investigate the effects on simulated K. mikimotoi transport and dispersal of: (1) the distribution of the initial seed population; (2) algal growth and mortality; (3) water temperature; (4) the vertical movement of particles by diurnal migration and eddy diffusion; (5) the relative role of the shelf edge and coastal currents; (6) the role of wind forcing. The numerical experiments emphasized the requirement for a physiologically based biological model and indicated that improved modelling of future blooms will potentially benefit from better parameterisation of temperature dependence of both growth and mortality and finer spatial and temporal hydrodynamic resolution.

Relationships between nitrogen and phosphorus forms and ratios and the development of dinoflagellate blooms in the East China Sea

During late spring and early summer of 2005, large-scale (> 15 000 km(2)), mixed dinoflagellate blooms developed along the the coast of the East China Sea. Karenia mikimotoi was the dominant harmful algal bloom species in the first stage of the bloom (late May) and was succeeded by Prorocentrum donghaiense approximately 2 wk later. Samples were collected from different stations along both north-south and west-east transects, from the Changjiang River estuary to the south Zhejiang coast, during 3 cruises of the Chinese Ecology and Oceanography of Harmful Algal Blooms Program, before and during the bloom progression. Nitrogen isotope tracer techniques were used to measure rates of NO3-, NH4+, urea, and glycine uptake during the blooms. High inorganic nitrogen (N), but low phosphorus (P) loading from the Changjiang River led to high dissolved inorganic N:dissolved inorganic P ratios in the sampling area and indicate the development of P limitation. The rates of N-15-uptake experiments enriched with PO43- were enhanced compared to unamended samples, suggesting P limitation of the N-uptake rates. The bloom progression was related to the change in availability of both organic and inorganic N and P. Reduced N forms, especially NH4+, were preferentially taken up during the blooms, but different bloom species had different rates of uptake of organic N substrates. K mikimotoi had higher rates of urea uptake, while P. donghaiense had higher rates of glycine uptake. Changes in the availability of reduced N and the ratios of N:P in inorganic and organic forms were suggested to be important in the bloom succession. Nutrient ratios and specific uptake rates of urea were similar when compared to analogous blooms on the West Florida Shelf.

Temporal and spatial variability in nitrogen uptake kinetics during harmful dinoflagellate blooms in the East China Sea

Temporal and spatial variability in the kinetic parameters of uptake of nitrate (NO3-), ammonium (NH4+), urea, and glycine was measured during dinoflagellate blooms in Changjiang River estuary and East China Sea coast, 2005. Karenia mikimotoi was the dominant species in the early stage of the blooms and was succeeded by Prorocentrum donghaiense. The uptake of nitrogen (N) was determined using N-15 tracer techniques. The results of comparison kinetic parameters with ambient nutrients confirmed that different N forms were preferentially taken up during different stages of the bloom. NO3- (V-max 0.044 h(-1); K-s 60.8 mu M-N) was an important N source before it was depleted. NH4+ (V-max 0.049 h(-1); K-s 2.15 mu M-N) was generally the preferred N. Between the 2 organic N sources, urea was more preferred when K. mikimotoi dominated the bloom (V-max 0.020 h(-1); K-s 1.35 mu M-N) and glycine, considered as a dominant amino acid, was more preferred when P. donghaiense dominated the bloom (V-max 0.025 h(-1); K-s 1.76 mu M-N). The change of N uptake preference by the bloom-forming algae was also related to the variation in ambient N concentrations. Published by Elsevier B.V.

Operational monitoring and forecasting of bathing water quality through exploiting satellite Earth observation and models: The AlgaRisk demonstration service

Coastal zones and shelf-seas are important for tourism, commercial fishing and aquaculture. As a result the importance of good water quality within these regions to support life is recognised worldwide and a number of international directives for monitoring them now exist. This paper describes the AlgaRisk water quality monitoring demonstration service that was developed and operated for the UK Environment Agency in response to the microbiological monitoring needs within the revised European Union Bathing Waters Directive. The AlgaRisk approach used satellite Earth observation to provide a near-real time monitoring of microbiological water quality and a series of nested operational models (atmospheric and hydrodynamic-ecosystem) provided a forecast capability. For the period of the demonstration service (2008–2013) all monitoring and forecast datasets were processed in near-real time on a daily basis and disseminated through a dedicated web portal, with extracted data automatically emailed to agency staff. Near-real time data processing was achieved using a series of supercomputers and an Open Grid approach. The novel web portal and java-based viewer enabled users to visualise and interrogate current and historical data. The system description, the algorithms employed and example results focussing on a case study of an incidence of the harmful algal bloom Karenia mikimotoi are presented. Recommendations and the potential exploitation of web services for future water quality monitoring services are discussed.