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The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Non-invasive genetic sampling and individual identification

Open access
TABERLET, P·1999·Biological Journal of the Linnean Society

Abstract

Individual identification via non-invasive sampling is of prime importance in conservation genetics and in behavioural ecology. This approach allows for genetics studies of wild animals without having to catch them, or even to observe them. The material used as a source of DNA is usually faeces, shed hairs, or shed feathers. It has been recendy shown that this material may lead to genotyping errors, mainly due to allelic dropout. In addition to these technical errors, there are problems with accurately estimating the probability of identity (PI, or the probability of two individuals having identical genotypes) because of the presence of close relatives in natural populations. As a consequence, before initiating an extensive study involving non-invasive sampling, we strongly suggest conducting a pilot study to assess both the technical difficulties and the PI for the genetic markers to be used. This pilot study could be carried out in three steps: (i) estimation of the PI using preliminary genetic data; (ii) simulations taking into account the PI and choosing the technical error rate mat is sufficiently low for assessing the scientific question; (iii) polymerase chain reaction (PCR) experiments to check if it is technically possible to achieve this error rate.

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Metadata

Authors
TABERLET, P.
Venue
Biological Journal of the Linnean Society
Published
1999-09
Volume
68
Issue
1-2
Pages
41-55
ISSN
0024-4066 (ISSN-L)
OpenAlex
W2010722055
Cited by
774
References
3
FWCI
5.57
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Non-invasive genetic sampling and individual identification. https://app.cochat.ai/papers/10.1006/bijl.1999.0329
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TABERLET, P. (1999). Non-invasive genetic sampling and individual identification. Biological Journal of the Linnean Society. https://doi.org/10.1006/bijl.1999.0329

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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