Potential adaptation zones for temperate pasture species as constrained by climate: a knowledge-based logical modelling approach

Abstract

Potential adaptation zones were modelled for major temperate pasture species using climate data and knowledge-based logical rules. A GIs database was constructed using a 0.025 degree digital elevation model and the Australian Climate Surfaces to create layers of monthly mean climate data for Australia. Soil pH maps for New South Wales, Victoria, and south-eastern South Australia were digitised and added to the database. Simple models using logical operators were constructed using estimates of temperature and aridity thresholds for the main temperate pasture species. The logical models were executed using primary and derived climate layers to create raster maps of potential adaptation zones for pasture species in eastern and south-western Australia. Areas of adaptation on freehold/leasehold land were expressed relative to a potential temperate pasture adaptation zone described by the lower (arid) limit of annual legume adaptation in temperate Australia and the northern limit of lucerne adaptation. Potential adaptation within this area ranged from 66% for lucerne down to <20% for perennial ryegrass in eastern Australia, and 93% for subterranean clover down to zero for perennial ryegrass in south-western Australia. Utility of the species adaptation zones could be enhanced using soil pH maps: a zone for serradella in NSW was refined by restricting adaptation to areas of climatic suitability with low soil pH. Maps for lucerne and Mount Barker subterranean clover showed good agreement with validation data for NSW. The zones may be readily adjusted by simple changes to parameter values in the algorithms. This knowledge-based approach has potential as an aid to targeting resources for plant improvement or to provide advice for more efficient utilisation of existing commercial pasture plants.