Analysis of underwater visual data to identify the impact of physical disturbance on horse mussel (Modiolus modiolus) beds

Underwater visual data from video or still photography can provide immediate qualitative descriptions of in situ epibenthic communities. However, few studies have attempted statistical analysis of such data in order to quantitatively assess the sensitivity of epifauna to anthropogenic influences. This paper discusses the use of species-time techniques, which substitute time for area and produce estimates of relative abundance of species based on time. This paper adapts such a technique, the ‘Visual Fast Count’, to quantitatively assess the impact of trawling on horse mussel, Modiolus modiolus, communities. Direct counts of individuals at various taxonomic levels were made from the still photographic images. The potential role of such techniques in the management of epifaunal communities in wider marine pollution studies is discussed.