This study presents results of a new approach for sea floor habitat mapping based on an integrated analysis of multibeam bathymetric data, associated geoscientific information, and benthos data from Browns Bank on the southwestern Scotian Shelf, off the Canadian Atlantic coast. Based on sea floor sediment maps and statistical analysis of megabenthos determined from photographs, 6 habitats and corresponding associations of benthos were derived and mapped. The habitats are distinguished primarily on the basis of sediment type and water depth. Additional factors are sea floor geomorphology, habitat complexity, and relative current strength. A Browns Bank benthic habitat map is developed as a conceptual model summarizing the understanding of the bank ecology. This study highlights the utility of multibeam bathymetric sonar for interpretation of sea floor sediments and for extrapolating benthic habitat characteristics across large areas of sea floor.

Cogan, C. B., Todd, B. J., Lawton, P., and Noji, T. T. 2009. The role of marine habitat mapping in ecosystem-based management. – ICES Journal of Marine Science, 66: 2033–2042. Ecosystem-based management (EBM) and the related concept of large marine ecosystems (LMEs) are sometimes criticized as being too broad for many management and research applications. At the same time, there is a great need to develop more effectively some substantive scientific methods to empower EBM. Marine habitat mapping (MHM) is an example of an applied set of field methods that support EBM directly and contribute essential elements for conducting integrated ecosystem assessments. This manuscript places MHM practices in context with biodiversity models and EBM. We build the case for MHM being incorporated as an explicit and early process following initial goal-setting within larger EBM programmes. Advances in MHM and EBM are dependent on evolving technological and modelling capabilities, conservation targets, and policy priorities within a spatial planning framework. In both cases, the evolving and adaptive nature of these sciences requires explicit spatial parameters, clear objectives, combinations of social and scientific considerations, and multiple parameters to assess overlapping viewpoints and ecosystem functions. To examine the commonalities between MHM and EBM, we also address issues of implicit and explicit linkages between classification, mapping, and elements of biodiversity with management goals. Policy objectives such as sustainability, ecosystem health, or the design of marine protected areas are also placed in the combined MHM–EBM context.

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