Title
The flexibility of distance sampling data for monitoring rare species—an evaluation of density surface models versus conventional distance sampling
Author(s)
Nuttall, M.;O'Kelly, H.;Nut, M.;Ung, V.
Published
2015
Publisher
Cambodian Journal of Natural History
Abstract
Distance sampling is a suite of methods that have become some of the most widely used techniques for estimating the abundance of biological populations. One of the fundamental requirements, however, is an appropriate number of observations of the objects, or groups of objects, of interest with which to conduct the analysis. This often deters researchers from using these methods for rare or elusive species. Advanced distance sampling techniques have been developed that may prove useful to researchers faced with challenging environments or species that do not conform to standard distance sampling assumptions. We present the results of a long-term wildlife monitoring programme from Seima Protection Forest in eastern Cambodia, conducted by the Wildlife Conservation Society in collaboration with the Forestry Administration, Royal Government of Cambodia, over the last 10 years. We will evaluate the use of both conventional distance sampling and density surface modelling for estimating the abundance of rare species. We demonstrate that in some instances conventional distance sampling can be effective for monitoring elusive species, but we will highlight the difficulties associated with this approach. We will then evaluate the use of Density Surface Models as an alternative, and present the benefits and challenges of estimating abundance using environmental covariates within a model-based framework. The fundamental differences between design-based and model-based inference in the context of rare wildlife species, challenging environments, and low technical capacity will be discussed.
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PUB15643