Empirical Niche Modelling of the Spontaneous Diversity of Forage and Turf Species to Improve Collection and Ex Situ Conservation

Abstract

Rational sampling of the spontaneous diversity of forage and turf species requires an a priori knowledge of the range of environmental conditions suitable for these species. We introduce some concepts and methods for investigating the environmental range of species by empirical modelling of species ecological niche, and we suggest how such investigations could help to plan collection campaigns and to improve the choice of core-collections. The empirical modelling of the ecological niche of a species consists of building a function of environmental parameters predicting the presence of the species from a calibration dataset including observed presence-absence or abundance records of the species and environmental data at observation sites. We emphasize that data from collection campaigns of plant breeders are valuable information for niche modelling. We introduce two methods for investigating the environmental distribution of species and for niche modelling based on presence-absence data: the canonical correlation analysis and the logistic regression. We give examples combining niche model and GIS software that may contribute to organize collection campaigns. We suggest that models predicting probability of presence of species may be useful for the selection of core-collections. Such models may help to delineate geographically isolated areas of presence of species that should be sampled separately for selecting a core-collection. In each isolated area of presence, we propose to stratify the accessions in clusters according to the predicted probability of presence of the species in collection sites, and to select accessions in each cluster.