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Please use this identifier to cite or link to this item: http://hdl.handle.net/10023/1927
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Title: Design and analysis of line transect surveys for primates
Authors: Buckland, Stephen Terrence
Plumptre, A J
Thomas, Len
Rexstad, Eric A
Keywords: Distance sampling
Estimating primate density
Line transect sampling
Primate survey
QA Mathematics
Issue Date: Oct-2010
Citation: Buckland , S T , Plumptre , A J , Thomas , L & Rexstad , E A 2010 , ' Design and analysis of line transect surveys for primates ' International Journal of Primatology , vol 31 , no. 5 , pp. 833-847 .
Abstract: Line transect surveys are widely used for estimating abundance of primate populations. The method relies on a small number of key assumptions, and if these are not met, substantial bias may occur. For a variety of reasons, primate surveys often do not follow what is generally considered to be best practice, either in survey design or in analysis. The design often comprises too few lines (sometimes just one), subjectively placed or placed along trails, so lacks both randomization and adequate replication. Analysis often involves flawed or inefficient models, and often uses biased estimates of the locations of primate groups relative to the line. We outline the standard method, emphasizing the assumptions underlying the approach. We then consider options for when it is difficult or impossible to meet key assumptions. We explore the performance of these options by simulation, focusing particularly on the analysis of primate group sizes, where many of the variations in survey methods have been developed. We also discuss design issues, field methods, analysis, and potential alternative methodologies for when standard line transect sampling cannot deliver reliable abundance estimates.
Version: Postprint
Description: An erratum to this article can be found at http://dx.doi.org/10.1007/s10764-010-9470-y
Status: Peer reviewed
URI: http://hdl.handle.net/10023/1927
http://www.creem.st-and.ac.uk/len/papers/BucklandIJP2009b.pdf
DOI: http://dx.doi.org/10.1007/s10764-010-9431-5
ISSN: 0164-0291
Type: Journal article
Rights: © Springer Science+Business Media, LLC 2010. This is an author version of this article. The original publication is available at www.springerlink.com
Appears in Collections:University of St Andrews Research
Mathematics & Statistics Research



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