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

Abstract

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