A spatial model with ordinal responses for grazing impact data

We propose a model for use with ordinal spatial data arising from field assessments of the grazing and trampling impact by animals on vegetation, and study the predictive performance of the model on partial surveys. We employ a mixed effects model, including a term for spatial correlation, which assumes a continuous underlying scale of grazing impact, and where the classification into discrete categories is made via cut-points. We analyse two classes of data: full census data and sample data drawn from the full census. In the latter case, we show that the estimation of nonsampled data improves as the spatial information included within the model increases.