Relationship Between Infestation By Mytilicola-Intestinalis Steuer (Copepoda Cyclopoidea) And Condition Index Of Mytilus-Edulis In Southwest England

Seasonal cycles in the condition index of Mytilus edulis from three sites in southwest England are described. These are analysed in relation to host length, stage of gonad development and parasite burden by linear regression analysis. An effect on the condition index due to the presence of Mytilicola intestinalis can be detected only in the sublittoral mussels in those few winter months when the mean intensity of infestation is over about 25 parasites per host. In all cases studied, the magnitude of the effect due to variation in host length, stage of gonad development, seasonal cycles and environmental factors is greater than that due to parasitism.

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.