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PROVIDING RELIABLE AND ACCURATE GENETIC CAPTURE‐MARK–RECAPTURE ESTIMATES IN A COST‐EFFECTIVE WAY
Author(s) -
McKELVEY KEVIN S.,
SCHWARTZ MICHAEL K.
Publication year - 2004
Publication title -
the journal of wildlife management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.94
H-Index - 111
eISSN - 1937-2817
pISSN - 0022-541X
DOI - 10.2193/0022-541x(2004)068[0453:praagc]2.0.co;2
Subject(s) - mark and recapture , computer science , identification (biology) , systematic error , variety (cybernetics) , econometrics , statistics , machine learning , artificial intelligence , biology , ecology , mathematics , population , demography , sociology
Capture‐mark–recapture (CMR) estimates assume no misidentification of individuals captured and are extremely sensitive to identification errors. A large body of published literature has demonstrated that non‐invasively derived genetic tags are error‐prone, and the potential biases associated with these errors are large. We provided methods to reduce and evaluate these errors. Paetkau (2004, this issue), in his comments concerning our paper, argues that no formal, statistical error testing is necessary and that good laboratory practices are sufficient to remove all error. However, he provides only anecdotal evidence that this is the case. Given the presence of a variety of errors in genetic tags and the potential for large biases associated with these errors, we argue that scientific norms require formal tests to demonstrate the absence of errors. The primary purpose of our study was to provide such tests in a manner that is not cost‐prohibitive.