Use this URL to cite or link to this record in EThOS:
Title: Modelling the feeding distribution of wintering pink-footed geese (Anser brachyrhynchus) and Greylag geese (Anser anser) in central Scotland
Author: Urquhart, Christine D.
ISNI:       0000 0001 3541 3321
Awarding Body: University of Stirling
Current Institution: University of Stirling
Date of Award: 2002
Availability of Full Text:
Access from EThOS:
Access from Institution:
Pink-footed and Greylag geese winter in Britain and can cause damage to crops, resulting in a conflict with agriculture. An understanding of where geese are likely to feed would help to target suitable areas for goose management plans, aimed at relieving such conflict. The aim of this project was to create models to predict the feeding distribution of both Pink-footed and Greylag geese. Two separate approaches were taken to model goose feeding distribution from landscape characteristics. The first was a standard approach, logistic regression, which predicted the probability of a field being used by geese from the field's landscape characteristics. Models were based on goose distribution data from field surveys. The main factors affecting field choice by both species were distance from the nearest building and distance from the roost. The inclusion of autologistic terms did not improve the fit of the models. A second, more novel approach to predicting goose distribution was taken to see if more accurate predictions could be produced. This modelling technique involved simulating the movements of Greylag geese throughout the day. The rules constraining goose movement in the model were derived from analysis of radiotracked geese. Flight direction was constrained by altitude or distance from the river while the probability of landing was dependent on the distance from buildings. The accuracy of the models in predicting goose distribution was tested both within the study area, Strathearn and Strathallan, and in another area, Loch Leven. Models based on animal movements have the theoretical advantage of incorporating barriers to movement, but the simulation model did not out-perform the logistic regression model. The models can be applied to other goose feeding areas relatively easily and can be used to identify areas where management plans for both Pink-footed and Greylag geese should be targeted.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Greylag goose ; Pink-footed goose ; Birds--Feeding and feeds ; Birds--Wintering--Scotland