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.

Dimethylsulfide gas transfer coefficients from algal blooms in the Southern Ocean

Air–sea dimethylsulfide (DMS) fluxes and bulk air–sea gradients were measured over the Southern Ocean in February–March 2012 during the Surface Ocean Aerosol Production (SOAP) study. The cruise encountered three distinct phytoplankton bloom regions, consisting of two blooms with moderate DMS levels, and a high biomass, dinoflagellate-dominated bloom with high seawater DMS levels (> 15 nM). Gas transfer coefficients were considerably scattered at wind speeds above 5 m/s. Bin averaging the data resulted in a linear relationship between wind speed and mean gas transfer velocity consistent with that previously observed. However, the wind-speed-binned gas transfer data distribution at all wind speeds is positively skewed. The flux and seawater DMS distributions were also positively skewed, which suggests that eddy covariance-derived gas transfer velocities are consistently influenced by additional, log-normal noise. A flux footprint analysis was conducted during a transect into the prevailing wind and through elevated DMS levels in the dinoflagellate bloom. Accounting for the temporal/spatial separation between flux and seawater concentration significantly reduces the scatter in computed transfer velocity. The SOAP gas transfer velocity data show no obvious modification of the gas transfer–wind speed relationship by biological activity or waves. This study highlights the challenges associated with eddy covariance gas transfer measurements in biologically active and heterogeneous bloom environments.

Satellite monitoring of harmful algal blooms (HABs) to protect the aquaculture industry

Harmful algal blooms (HABs) can cause sudden and considerable losses to fish farms, for example 500,000 salmon during one bloom in Shetland, and also present a threat to human health. Early warning allows the industry to take protective measures. PML's satellite monitoring of HABs is now funded by the Scottish aquaculture industry. The service involves processing EO ocean colour data from NASA and ESA in near-real time, and applying novel techniques for discriminating certain harmful blooms from harmless algae. Within the AQUA-USERS project we are extending this capability to further HAB species within several European countries.

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.

Electrochemical RNA genosensors for toxic algal species: enhancing selectivity and sensitivity

Harmful algal blooms (HABs) are becoming more frequent as climate changes, with tropical species moving northward. Monitoring programs detecting the presence of toxic algae before they bloom are of paramount importance to protect aquatic ecosystems, aquaculture, human health and local economies. Rapid and reliable species identification methods using molecular barcodes coupled to biosensor detection tools have received increasing attention over the past decade as an alternative to the impractical standard microscopic counting-based techniques. This work reports on a PCR amplification-free electrochemical genosensor for the enhanced selective and sensitive detection of RNA from multiple Mediterranean toxic algal species. For a sandwich hybridization (SHA), we designed longer capture and signal probes for more specific target discrimination against a single base-pair mismatch from closely related species and for reproducible signals. We optimized experimental conditions, viz., minimal probe concentration in the SHA on a screen-printed gold electrode and selected the best electrochemical mediator. Probes from 13 Mediterranean dinoflagellate species were tested under optimized conditions and the format further tested for quantification of RNA from environmental samples. We not only enhanced the selectivity and sensitivity of the state-of-the-art toxic algal genosensors but also increased the repertoire of toxic algal biosensors in the Mediterranean, towards an integral and automatic monitoring system.

Electrochemical RNA genosensors for toxic algal species: enhancing selectivity and sensitivity

Harmful algal blooms (HABs) are becoming more frequent as climate changes, with tropical species moving northward. Monitoring programs detecting the presence of toxic algae before they bloom are of paramount importance to protect aquatic ecosystems, aquaculture, human health and local economies. Rapid and reliable species identification methods using molecular barcodes coupled to biosensor detection tools have received increasing attention over the past decade as an alternative to the impractical standard microscopic counting-based techniques. This work reports on a PCR amplification-free electrochemical genosensor for the enhanced selective and sensitive detection of RNA from multiple Mediterranean toxic algal species. For a sandwich hybridization (SHA), we designed longer capture and signal probes for more specific target discrimination against a single base-pair mismatch from closely related species and for reproducible signals. We optimized experimental conditions, viz., minimal probe concentration in the SHA on a screen-printed gold electrode and selected the best electrochemical mediator. Probes from 13 Mediterranean dinoflagellate species were tested under optimized conditions and the format further tested for quantification of RNA from environmental samples. We not only enhanced the selectivity and sensitivity of the state-of-the-art toxic algal genosensors but also increased the repertoire of toxic algal biosensors in the Mediterranean, towards an integral and automatic monitoring system.