Marine Data

The Marine Environment Classification (MEC), a GIS-based environmental classification of the marine environment of the New Zealand region, is an ecosystem-based spatial framework designed for marine management purposes.

Several spatially-explicit data layers describing the physical environment define the MEC. A physically-based classification was chosen because data on these physical variables were available or could be modelled, and because the pattern of the physical environment is a reasonable surrogate for biological pattern, particularly at larger spatial scales. Classes within the classification were defined using multivariate clustering methods. These produce hierarchical classifications that enable the user to delineate environmental variation at different levels of detail and associated spatial scales.

The Marine Environment Classification (MEC), a GIS-based environmental classification of the marine environment of the New Zealand region, is an ecosystem-based spatial framework designed for marine management purposes.

Several spatially-explicit data layers describing the physical environment define the MEC. A physically-based classification was chosen because data on these physical variables were available or could be modelled, and because the pattern of the physical environment is a reasonable surrogate for biological pattern, particularly at larger spatial scales. Classes within the classification were defined using multivariate clustering methods. These produce hierarchical classifications that enable the user to delineate environmental variation at different levels of detail and associated spatial scales.

The Marine Environment Classification (MEC), a GIS-based environmental classification of the marine environment of the New Zealand region, is an ecosystem-based spatial framework designed for marine management purposes.

Several spatially-explicit data layers describing the physical environment define the MEC. A physically-based classification was chosen because data on these physical variables were available or could be modelled, and because the pattern of the physical environment is a reasonable surrogate for biological pattern, particularly at larger spatial scales. Classes within the classification were defined using multivariate clustering methods. These produce hierarchical classifications that enable the user to delineate environmental variation at different levels of detail and associated spatial scales.