Density estimation in tiger populations: combining information for strong inference

Ecology
By: , and 

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Abstract

A productive way forward in studies of animal populations is to efficiently make use of all the information available, either as raw data or as published sources, on critical parameters of interest. In this study, we demonstrate two approaches to the use of multiple sources of information on a parameter of fundamental interest to ecologists: animal density. The first approach produces estimates simultaneously from two different sources of data. The second approach was developed for situations in which initial data collection and analysis are followed up by subsequent data collection and prior knowledge is updated with new data using a stepwise process. Both approaches are used to estimate density of a rare and elusive predator, the tiger, by combining photographic and fecal DNA spatial capture–recapture data. The model, which combined information, provided the most precise estimate of density (8.5 ± 1.95 tigers/100 km2 [posterior mean ± SD]) relative to a model that utilized only one data source (photographic, 12.02 ± 3.02 tigers/100 km2 and fecal DNA, 6.65 ± 2.37 tigers/100 km2). Our study demonstrates that, by accounting for multiple sources of available information, estimates of animal density can be significantly improved.
Publication type Article
Publication Subtype Journal Article
Title Density estimation in tiger populations: combining information for strong inference
Series title Ecology
DOI 10.1890/11-2110.1
Volume 93
Issue 7
Year Published 2012
Language English
Publisher ESA
Publisher location Ithaca, NY
Contributing office(s) Patuxent Wildlife Research Center
Description 11 p.
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Ecology
First page 1741
Last page 1751
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