Get reliable rangeland science

Two key challenges in rangeland management are determining the sustainability of management practices and the cumulative impact of those practices on the condition / health / productivity of the managed landscape. To this end remotely sensed cover products have been widely used in recent decades as there are no alternative products with a comparable spatiotemporal coverage and resolution. We trialled a new approach to remotely assess land condition and management sustainability using ground cover data. The method first benchmarks Spring ground cover per pixel against local ground cover values within the land type (regional comparison (RC)). RC is a useful ground cover benchmark because it accounts for impact of land type and rainfall history on ground cover at any site. We then model Spring RC values based on the RC value of the previous Spring and recency of fire (a driver of ground cover not well accounted for by RC). We interpret the predicted quantile of any model prediction (GCM) as an index of how well the RC value has been maintained over that year at the site. If annual GCM values do indicate how well ground cover has been maintained within the year, it is possible that long term consistency in GCM values (high or low) may highlight the broader sustainability of the management system (e.g. management that maintains ground cover probably also limits erosion and promotes desirable pasture species). Furthermore, more sustainable management systems might indicate places of high and/or improving land condition. This poster explains how the GCM layers were developed and tests the idea that they could be a useful tool to map both the historical sustainability of management systems as well as their impacts on land condition.