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.

Assessing non-market benefits of seagrass restoration in the Gulf of Gdańsk

Seagrass meadows (Zostera marina) are an important ecosystem in the coastal environment of the Baltic Sea. This study employs a discrete choice experiment to value a set of non-market benefits provided by seagrass meadows in the Gulf of Gdańsk, Poland. The benefits valued in this study are a reduction of filamentous algae in the water and on the beach; access to seagrass meadows for boaters and divers; and improved water clarity. Results show significant willingness to pay for each attribute and differences of value estimates across different groups of survey respondents. It is discussed how to link choice attributes and estimated values with established ecosystem benefit categories in order to facilitate value transfer.