| Summary: | Describing a population in space and time may provide essential information to govern regimes for the effective and sustainable management of that population. Some fish species exhibit naturally complex and changeable patterns of distribution relating to their life history characteristics, biological requirements (which may vary between ages and seasons), the environment, climate change and human factors. Where this is the case, investigating a populations distribution in varying spatial (and temporal) scales has the advantage of being able to extract a more ecosystem focused and detailed pattern of possible causes for and therefore implications of a particular distribution. The northeast Atlantic supports some of the world's most highly productive fish stocks and as a result is impacted heavily by human activity. Northeast Atlantic waters are highly dynamic with complex oceanographic and hydrographic features which are responding significantly and variably to a changing climate. In this thesis, results show that northeast Atlantic mackerel (NEAM) western spawning component (WSC) are moving north associated with a change in survey effort and warming waters, and that their distribution is related to local topographic features. Important fishing areas for Atlantic mackerel are the continental shelf edge, northern North Sea and southern Norwegian Sea. Shifts in NEAM catch have occurred 1977 - 2010 and show a northern and off-shelf preference in distribution. Cod in the North Sea and Celtic Sea and western Channel are examined to show a northwest shift in North Sea cod made up of spatially heterogenous local scale site specific changes. The Celtic sea and western Channel stock were not shown to display any density dependent habitat selection. An across species comparison of mackerel, blue whiting and horse mackerel suggested species specific responses to environmental variables as well as some biological species interactions. This thesis analyses important data sets whilst considering the limitations of the data ...
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