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Advisor(s)
Abstract(s)
Distance sampling is extensively used for estimating animal density or
abundance. Conventional methods assume that location of line or point transects is
random with respect to the animal population, yet transects are often placed along
linear features such as roads, rivers or shorelines that do not randomly sample the
study region, resulting in biased estimates of abundance. If it is possible to collect
additional data that allow an animal density gradient with respect to the transects to
be modelled, we show how to extend the conventional distance sampling likelihood to
give asymptotically unbiased estimates of density for the covered area. We illustrate
the proposed methods using data for a kangaroo population surveyed by line transects
laid along tracks, for which the true density is known from an independent source,
and the density gradient with respect to the tracks is estimated from a sample of GPS collared animals. For this example, density of animals increases with distance from
the tracks, so that detection probability is overestimated and density underestimated
if the non-random location of transects is ignored. When we account for the density
gradient, there is no evidence of bias in the abundance estimate. We end with a list
of practical recommendations to investigators conducting distance sampling surveys where density gradients could be an issue.
Description
Keywords
Density gradients Distance sampling Kangaroo Road surveys Line and point transects Wildlife abundance
Citation
Statistical Methods & Applications, 22, 67-80
Publisher
Springer-Verlag