Multivariate clustering based on fine spatial resolution maps of elevation, temperature, precipitation, soil characteristics,
and solar inputs has been used at several specified levels of division to produce a spectrum of quantitative ecoregion maps
for the conterminous United States. The coarse ecoregion divisions accurately capture intuitively-understood regional environmental
differences, whereas the finer divisions highlight local condition gradients, ecotones, and clines. Such statistically generated
ecoregions can be produced based on user-selected continuous variables, allowing customized regions to be delineated for any
specific problem. By creating an objective ecoregion classification, the ecoregion concept is removed from the limitations
of human subjectivity, making possible a new array of ecologically useful derivative products. A red–green–blue visualization
based on principal components analysis of ecoregion centroids indicates with color the relative combination of environmental
conditions found within each ecoregion. Multiple geographic areas can be classified into a single common set of quantitative
ecoregions to provide a basis for comparison, or maps of a single area through time can be classified to portray climatic
or environmental changes geographically in terms of current conditions. Quantified representativeness can characterize borders
between ecoregions as gradual, sharp, or of changing character along their length. Similarity of any ecoregion to all other
ecoregions can be quantified and displayed as a “representativeness” map. The representativeness of an existing spatial array
of sample locations or study sites can be mapped relative to a set of quantitative ecoregions, suggesting locations for additional
samples or sites. In addition, the shape of Hutchinsonian niches in environment space can be defined if a multivariate range
map of species occurrence is available.
Keywords Clustering - Climate change - Ecotone - Environmental envelope - Fences - Gradient - Network - Niche - Preserve design - Range - Representativeness - Similarity - Time series