The effect of animal movement on line transect estimates of abundance
MetadataShow full item record
Line transect sampling is a distance sampling method for estimating the abundance of wild animal populations. One key assumption of this method is that all animals are detected at their initial location. Animal movement independent of the transect and observer can thus cause substantial bias. We present an analytic expression for this bias when detection within the transect is certain (strip transect sampling) and use simulation to quantify bias when detection falls off with distance from the line (line transect sampling). We also explore the non-linear relationship between bias, detection, and animal movement by varying detectability and movement type. We consider animals that move in randomly orientated straight lines, which provides an upper bound on bias, and animals that are constrained to a home range of random radius. We find that bias is reduced when animal movement is constrained, and bias is considerably smaller in line transect sampling than strip transect sampling provided that mean animal speed is less than observer speed. By contrast, when mean animal speed exceeds observer speed the bias in line transect sampling becomes comparable with, and may exceed, that of strip transect sampling. Bias from independent animal movement is reduced by the observer searching further perpendicular to the transect, searching a shorter distance ahead and by ignoring animals that may overtake the observer from behind. However, when animals move in response to the observer, the standard practice of searching further ahead should continue as the bias from responsive movement is often greater than that from independent movement.
Glennie , R , Buckland , S T & Thomas , L 2015 , ' The effect of animal movement on line transect estimates of abundance ' PLoS One , vol. 10 , no. 3 , e0121333 . https://doi.org/10.1371/journal.pone.0121333
© 2015 Glennie et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
DescriptionThis work was supported by the University of St Andrews (http://www.st-andrews.ac.uk/; RG, STB, LT) and by a summer scholarship and PhD grant from The Carnegie Trust for the Universities of Scotland (http://www.carnegie-trust.org/) to RG.
Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.