Landscape metrics can also be classified according to whether or not they measure landscape patterns with explicit reference to a particular ecological process.

  • Structural metrics -- Structure metrics can be defined as those that measure the physical composition or configuration of the patch mosaic without explicit reference to an ecological process. The functional relevance of the computed value is left for interpretation during a subsequent step. Most landscape metrics are of this type.

  • Functional metrics -- Functional metrics, on the other hand, can be defined as those that explicitly measure landscape pattern in a manner that is functionally relevant to the organism or process under consideration. Functional metrics require additional parameterization prior to their calculation, such that the same metric can return multiple values depending on the user specifications.

The difference between structural and functional metrics is best illustrated with an example. As conventionally computed, mean nearest neighbor distance is based on the distances between neighboring patches of the same class. The mosaic is in essence treated as a binary landscape (i.e., patches of the focal class versus everything else). The composition and configuration of the intervening matrix is ignored. Consequently, the same landscape can only return a single value for this metric. Clearly, this is a structural metric because the functional meaning of any particular computed value is left to subsequent interpretation. Conversely, connectivity metrics that consider the permeability of various patch types to movement of the organism or process of interest are functional metrics. Here, every patch in the mosaic contributes to the calculation of the metric. Moreover, there are an infinite number of values that can be returned from the same landscape, depending on the permeability coefficients assigned to each patch type. Given a particular parameterization, the computed metric is in terms that are already deemed functionally relevant.