Analysing space use patterns by Thiessen polygon and triangulated irregular network interpolation: a non-parametric method for processing telemetric animal fixes

This paper describes a new non-parametric model to estimate space use. We t est the similarity in space use patterns between an artificially generated utilization distribution (Seaman - UD) and the model estimates for five dif ferent sample sizes. Three different test statistics (Kappa, gamma, T-c,) r eveal a high similarity between the estimates and the Seaman - UD. The test s also show that, beyond a certain threshold value, larger sample sizes do not return significantly better results. We further demonstrate that the Th iessen model delineated areas of intensive use more effectively in a home r ange than Kernel estimators. UD estimation uses AML (ArcInfo Macro Language ), thus facilitating overlay operations with habitat information stored in the same ArcInfo GIS environment.