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Step-Selection Functions for Modeling Animal Movement -- Case Study: African Buffalo

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.

Identiferoai:union.ndltd.org:CLAREMONT/oai:scholarship.claremont.edu:cmc_theses-2949
Date01 January 2018
CreatorsAdar, Maia
PublisherScholarship @ Claremont
Source SetsClaremont Colleges
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceCMC Senior Theses
Rights© 2018 Maia Adar, default

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