ECOLOGICAL-NICHE FACTOR ANALYSIS: HOW TO COMPUTE HABITAT-SUITABILITY MAPS WITHOUT ABSENCE DATA?

TLDR

The study builds on Hutchinson’s ecological niche concept, comparing observed species localities to a reference set across multidimensional ecological variables. The authors propose a multivariate approach to geographic species distribution that does not require absence data. Using factor analysis, the method extracts a marginality factor and specialization factors, interprets eigenvectors and eigenvalues, and constructs habitat‑suitability maps, as illustrated and validated with the alpine ibex. The approach is recommended when absence data are unavailable, unreliable, or meaningless, and it was validated with the reintroduced alpine ibex in Switzerland.

Abstract

We propose a multivariate approach to the study of geographic species distribution which does not require absence data. Building on Hutchinson's concept of the ecological niche, this factor analysis compares, in the multidimensional space of ecological variables, the distribution of the localities where the focal species was observed to a reference set describing the whole study area. The first factor extracted maximizes the marginality of the focal species, defined as the ecological distance between the species optimum and the mean habitat within the reference area. The other factors maximize the specialization of this focal species, defined as the ratio of the ecological variance in mean habitat to that observed for the focal species. Eigenvectors and eigenvalues are readily interpreted and can be used to build habitat-suitability maps. This approach is recommended in situations where absence data are not available (many data banks), unreliable (most cryptic or rare species), or meaningless (invaders). We provide an illustration and validation of the method for the alpine ibex, a species reintroduced in Switzerland which presumably has not yet recolonized its entire range.