Approaches for Testing Uniformity Hypothesis in Angular Data of Mega-Herbivores

Abstract

Circularstatistics is an area not used verymuch by ecologists to describe animal movement patterns.Nevertheless,the connection betweenthe evaluation of temporalrecurring events and theanalysis of directional data haveconverged in several papers, and showcircularstatistics to be an outstandingtoolforunderstanding animal movementbetter. Theaim of thischapter is to evaluate the applications of circularstatisticaltests to check uniformityhypothesis in animal movement and its potential interpretationwithin the general framework of movementecology. Four methods of circularstatistics: Rayleigh’s,Watson’s,Rao’s spacing and Kuiper’s test based on the mean resultantlengthare applied to examine theuniformityhypothesis of GPS derived telemetry data of elephant movementcollected fromKrugerNationalPark(KNP) South Africa.Overall,circularstatisticaluniformitytests methods represent a usefultoolfor evaluation of directionalityelephant movement with applications including(i) assessment of animal foragingstrategies; (ii)determination of orientation in response to landscape features and (iii)determination of therelativestrengths of landscape features present binacomplex environment.