Abstract for presentation at Spatial Sciences Institute International Biennial Conference

Spatial (landscape ecology) metrics are being utilised as key research tools in a major investigation of biodiversity on grazing and cropping properties across Australia for the Biodiversity in Grain and Graze (BiGG) consortium. The spatial analysis tools are required to provide multiple analyses as the methods and metrics vary substantially depending upon the focus of the analysis. For example, the objectives of the BiGG project include the study of the relationships between measures of biodiversity and the landscape extent, composition or configuration of a mosaic of land use types, such as crops, grazed and remnant vegetation. The objectives also include a study of the degree of fragmentation of a single land use, i.e. remnant vegetation, which requires a different approach. Further, the field of spatial metrics is rapidly evolving and new metrics are regularly proposed. Therefore, a desirable goal is the automation of the spatial metric production process that would enable researchers to easily vary the parameters of the analyses. The development environment chosen was Python and ArcGIS and the spatial metrics engine is FRAGSTATS. The quality of the data sets in this case is variable, which is typical of national projects, and the application of data management standards is a critical prerequisite, including coordinate systems, data models and data formats. The resulting spatial metrics production tool has enabled a large number of fully documented repeatable analyses to be conducted, which in turn, have supported multiscale analyses of the contribution of landscape pattern to biodiversity on Australian agricultural land including at the farm, regional and national levels.