Report of the ICES - FAO Working Group on Fishing Technology & Fish Behaviour (WGFTFB) [18–22 May 2009 Ancona, Italy]

Contributors: Arill Engås, Bjørnar Isaksen, Svein Løkkeborg and Terje Jørgense

Beyond the reef: the influence of seascape structure on the composition and function of tropical fish communities

Katie Sambrook investigated how seascape structure affects the composition and function of tropical fish communities. She found that many fishes use multiple habitats and that the spatial arrangement of habitats shape ecological patterns and processes. Her findings highlight the need to incorporate seascape ecology into future management and conservation strategies

Book of abstracts – 53^rd European Marine Biology Symposium. Oostende, Belgium, 17-21 September 2018

The primary cause of this accident is listed as “Inadequate survey” because there seems to have been confusion about the area that required search. The secondary cause is listed as a “Management Control Inadequacy” because the failure to search the areas that were very obviously hazardous appears to have been the result of poor communication, a lack of adequate task documentation, a failure to keep MDD working records, poor understanding of Technical Survey, and other “shortcuts” that commercial demining groups may be expected to make when inadequately tasked

Automatic Classification of Seafloor Image Data by Geospatial Texture Descriptors

A novel approach for automatic context-sensitive classification of spatially distributed image data is introduced. The proposed method targets applications of seafloor habitat mapping but is generally not limited to this domain or use case. Spatial context information is incorporated in a two-stage classification process, where in the second step a new descriptor for patterns of feature class occurrence according to a generically defined classification scheme is applied. The method is based on supervised machine learning, where numerous state-of-the-art approaches are applicable. The descriptor computation originates from texture analysis in digital image processing. Patterns of feature class occurrence are perceived as a texture-like phenomenon and the descriptors are therefore denoted by Geospatial Texture Descriptors. The proposed method was extensively validated based on a set of more than 4000 georeferenced video mosaics acquired at the Haakon Mosby Mud Volcano north-west of Norway recorded during cruise ARK XIX3b of the German research vessel Polarstern. The underlying classification scheme was derived from a scheme developed for manual annotation of the same dataset applied in the course of Jerosch [2006]. Features of interest are related to methane discharge at mud volcanoes, which are considered a significant source of methane emission. In the experimental evaluation, based on the prepared training and test data, a major improvement of the classification precision compared to local classification as well as classification based on the raw data from the local spatial context was achieved by the application of the proposed method. The classification precision was particularly improved for rarely occurring classes. In a further comparison with annotated data available from Jerosch [2006] the regional setting of the investigation area obtained by the application of the proposed method was found almost equivalent to the results of an experienced scientist