A proposal for an integrated modelling framework to characterise habitat pattern

The methodology is demonstrated for the focal forest habitat, by using sixty-five in-situ based habitat maps from the EBONE project (“European Biodiversity Observation NEtwork”). Twelve indices are applied. A statistical analysis is then conducted using classical linear correlation and nonlinear Brownian Distance Correlation (Mastrave free software modelling library) as alternative to traditional dimensionality-reduction techniques and with an effort towards reusability in other contexts and reproducible research, by means of concise semantic array programming codelets. The results highlight the less correlated and fundamental pattern components, corroborating the hypothesized hierarchical organization of the indices into four families, and also the feasibility of reducing further the number of indices within each category.