The integration of GPS, vegetation mapping and GIS in ecological and behavioural studies

Abstract

Global Positioning System {(GPS)} satellite navigation receiversare increasingly being used in ecological and behavioural studiesto track the movements of animals in relation to the environmentsin which they live and forage. Concurrent recording of the animal'sforaging behaviour (e.g. from jaw movement recording) allows foraginglocations to be determined. By combining the animal {GPS} movementand foraging data with habitat and vegetation maps using a GeographicalInformation System {(GIS)} it is possible to relate animal movementand foraging location to landscape and habitat features and vegetationtypes. This powerful approach is opening up new opportunities tostudy the spatial aspects of animal behaviour, especially foragingbehaviour, with far greater precision and objectivity than before.Advances in {GPS} technology now mean that sub-metre precisionsystems can be used to track animals, extending the range of applicationof this technology from landscape and habitat scale to paddock andpatch scale studies. As well as allowing ecological hypotheses tobe empirically tested at the patch scale, the improvements in precisionare also leading to the approach being increasing extended from largescale ecological studies to smaller (paddock) scale agriculturalstudies. The use of sub-metre systems brings both new scientificopportunities and new technological challenges. For example, fittingall of the animals in a group with sub-metre precision {GPS} receiversallows their relative inter-individual distances to be preciselycalculated, and their relative orientations can be derived from datafrom a digital compass fitted to each receiver. These data, analyzedusing {GIS,} could give new insights into the social behaviourof animals. However, the improvements in precision with which theanimals are being tracked also needs equivalent improvements in theprecision with which habitat and vegetation are mapped. This needssome degree of automation, as vegetation mapping at a fine spatialscale using the traditional manual approach is far too time consuming.This paper explores these issues, discussing new applications aswell as approaches to overcoming some of the associated problems.