Predicting badger sett numbers: evaluating methods in East Sussex

Abstract

Abstract. One way in which a species' numbers may be estimated without direct counting is to predict their dispersion and density from more readily available habitat measures, such as landscape variables measured from maps or vegetation variables measured in the field. We compare the power of ordination and regression techniques for predicting badger (Meles meles L.) numbers at a local scale, using a land class system, map‐read landscape variables and field‐derived vegetation variables. Sett density was used as a surrogate of badger density. Multiple linear regression using vegetation and landscape variables together gave the most accurate prediction of sett density, while ordination techniques were of lesser value. The addition of vegetation variables to landscape variables did not substantially improve the power of ordination. Outlier Sett Density was predicted more accurately, and by different variables, to Main Sett Density. The relationship between badger ecology and habitat variables that were useful in predicting sett density is discussed.