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The most popular method used to obtain information on population size is distance sampling, and the most commonly used form of distance sampling is line transect sampling (Buckland et al. [3]; Spaan et al. [5]). This paper propagates poor practices that are too prevalent in primate surveys: use of methods that have long been superceded by improved methods; very small numbers of transects; no randomization of the design. We reiterate the need for sufficient replicates, placed in the desired area of inference independently of the animal distribution, to obtain robust estimates of population size using distance sampling. [Extracted from the article]

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 1), 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. [ABSTRACT FROM AUTHOR]

Line transect sampling is widely used for estimating abundance of primate populations. Researchers commonly use animal-to-observer distances (AODs) in analysis, in preference to perpendicular distances from the line, which 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. [ABSTRACT FROM AUTHOR]

The article reports a two-stage method for analyzing distance sampling data from designed experiments. It illustrates the approach using data from a before-after control-impact experiment designed to assess the effects of large-scale prescribed fire treatments on bird density in the U.S. forests. This approach aims to estimate the abundance or density of wild animal populations.

A correction to the article "Line Transect Sampling of Primates: Can Animal-to-Observer Distance Methods Work?" that was published in the 2010 issue is presented.

A correction to the article "Design and Analysis of Line Transect Surveys of Primates" that was published in the 2010 issue is presented.