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Generalized site occupancy models allowing for false positive and false negative errors

Ecology

6548_Royle.pdf
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Abstract

Site occupancy models have been developed that allow for imperfect species detection or ?false negative? observations. Such models have become widely adopted in surveys of many taxa. The most fundamental assumption underlying these models is that ?false positive? errors are not possible. That is, one cannot detect a species where it does not occur. However, such errors are possible in many sampling situations for a number of reasons, and even low false positive error rates can induce extreme bias in estimates of site occupancy when they are not accounted for. In this paper, we develop a model for site occupancy that allows for both false negative and false positive error rates. This model can be represented as a two-component finite mixture model and can be easily fitted using freely available software. We provide an analysis of avian survey data using the proposed model and present results of a brief simulation study evaluating the performance of the maximum-likelihood estimator and the naive estimator in the presence of false positive errors.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Generalized site occupancy models allowing for false positive and false negative errors
Series title:
Ecology
Volume
87
Issue:
4
Year Published:
2006
Language:
English
Contributing office(s):
Patuxent Wildlife Research Center
Description:
835-841
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
First page:
835
Last page:
841
Number of Pages:
7