marine landscape mapping; Commonwealth Marine Economies Programme; Commonwealth of Dominica; confusion index maps; principal component analysis; eigenvalue; K-means analysis; publicly available data
A lack of data hinders effective marine management strategies for developing island states. This is a particularly acute problem for the Commonwealth of Dominica. Here we use publicly available remote sensing and model data to map their relatively unstudied waters. Two study areas were selected; a smaller area focussing on the nearshore marine environment, and a larger area to capture broader spatial patterns and context. Three broadscale landscape maps were created, using geophysical and oceanographic data to classify the marine environment based on its abiotic characteristics. Principal component analysis (PCA) was performed on each area, followed by K-means clustering. The larger area PCA revealed three eigenvalues > 1, and one eigenvalue of 0.980. Therefore, two maps were created for this area, to assess the significance of including the fourth principal component (PC). We demonstrate that including too many PCs could lead to an increase in the confusion index of final output maps. Overall, the marine landscape maps were used to assess the spatial characteristics of the benthic environment and to identify priority areas for future high-resolution study. Through defining and analysing existing conditions and highlighting important natural areas in the Dominican waters, these study results can be incorporated into the Marine Spatial Planning process.
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