Design and analysis of line transect surveys for primates

An erratum to this article can be found at http://dx.doi.org/10.1007/s10764-010-9470-yLine 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.PostprintPeer reviewe

Line transect sampling of primates : can animal-to-observer distance methods work?

An erratum to this article can be found at http://dx.doi.org/10.1007/s10764-010-9469-4Line transect sampling is widely used for estimating abundance of primate populations. Animal-to-observer distances (AODs) are commonly used in analysis, in preference to perpendicular distances from the line. This is in marked contrast with standard practice for other applications of line transect sampling. We formalize the mathematical shortcomings of approaches based on AODs, and show that they are likely to give strongly biased estimates of density. We review papers that claim good performance for the method, and explore this performance through simulations. These confirm strong bias in estimates of density using AODs. We conclude that AOD methods are conceptually flawed, and that they cannot in general provide valid estimates of density.PostprintPeer reviewe