REMA: A neutral model to reveal patterns and processes of cover change in wooded rangelands

Remote sensing applications used for resource assessment often lack the capacity to test image data against predictions. This article describes remote environment and management assessment (REMA), a new method for the interpretation of rangeland plant cover change, which uses Landsat MSS data and neutral predictions. REMA has been designed to provide a generalized and testable method to assess herbivore impact on potential forage productiveness, even when a plant cover is heterogeneously distributed. In this article, models are constructed to interpret patterns and processes of cover change within paddocks exposed to alternating periods of plant cover increase and decline. Relative cover changes along distance from water point axes are derived to standardize and reveal gradients of cover change and cover resistance to drought. By testing cover changes against neutral predictions, insights are gained into the association between grazing processes, geomorphology, and climatic conditions. Four MSS images of two sheep-grazed paddocks from wooded rangelands in eastern Australia are used to demonstrate that increasing and decreasing linear cover change gradients, and contrasting forage resistances to drought, can be found and assessed. The patterns and levels of cover change due to grazing were found to be different and to have nominally high and low levels of drought resistance that were related to paddock management, geomorphology, and climate.