Graduation Year

2018

Date of Submission

4-2018

Document Type

Open Access Senior Thesis

Degree Name

Bachelor of Arts

Department

Mathematics

Reader 1

Mark Huber

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Terms of Use for work posted in Scholarship@Claremont.

Rights Information

© 2018 Maia Adar

Abstract

Understanding what factors influence wildlife movement allows landscape planners to make informed decisions that benefit both animals and humans. New quantitative methods, such as step-selection functions, provide valuable objective analyses of wildlife connectivity. This paper provides a framework for creating a step-selection function and demonstrates its use in a case study. The first section provides a general introduction about wildlife connectivity research. The second section explains the math behind the step-selection function using a simple example. The last section gives the results of a step-selection model for African buffalo in the Kavango Zambezi Transfrontier Conservation Area. Buffalo were found to avoid fences, rivers, and anthropogenic land use; however, there was great variation in individual buffalo's preferences.

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