Correcting wildlife counts using detection probabilities. White, G. *Wildlife Research*, 32(3):211–216, Department of Fishery and Wildlife Biology, Colorado State University, Fort Collins, CO 80523, United States, 2005. abstract bibtex One of the most pervasive uses of indices of wildlife populations is unconnected counts of animals. Two examples are the minimum number known alive from capture and release studies, and aerial surveys where the detection probability is not estimated from a sightability model, marked animals, or distance sampling. Both the mark-recapture and distance-sampling estimators are techniques to estimate the probability of detection of an individual animal (or cluster of animals), which is then used to correct a count of animals. However, often the number of animals in a survey is inadequate to compute an estimate of the detection probability and hence correct the count. Modern methods allow sophisticated modelling to estimate the detection probability, including incorporating covariates to provide additional information about the detection probability. Examples from both distance and mark-recapture sampling are presented to demonstrate the approach. © CSIRO 2005.

@ARTICLE{White2005,
author = {White, G.C.},
title = {Correcting wildlife counts using detection probabilities},
journal = {Wildlife Research},
year = {2005},
volume = {32},
pages = {211--216},
number = {3},
abstract = {One of the most pervasive uses of indices of wildlife populations
is unconnected counts of animals. Two examples are the minimum number
known alive from capture and release studies, and aerial surveys
where the detection probability is not estimated from a sightability
model, marked animals, or distance sampling. Both the mark-recapture
and distance-sampling estimators are techniques to estimate the probability
of detection of an individual animal (or cluster of animals), which
is then used to correct a count of animals. However, often the number
of animals in a survey is inadequate to compute an estimate of the
detection probability and hence correct the count. Modern methods
allow sophisticated modelling to estimate the detection probability,
including incorporating covariates to provide additional information
about the detection probability. Examples from both distance and
mark-recapture sampling are presented to demonstrate the approach.
© CSIRO 2005.},
address = {Department of Fishery and Wildlife Biology, Colorado State University,
Fort Collins, CO 80523, United States},
owner = {eric},
subdatabase = {distance},
timestamp = {2006.11.05}
}

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