The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
How to fail at species delimitation
Open accessAbstract
Species delimitation is the act of identifying species‐level biological diversity. In recent years, the field has witnessed a dramatic increase in the number of methods available for delimiting species. However, most recent investigations only utilize a handful (i.e. 2–3) of the available methods, often for unstated reasons. Because the parameter space that is potentially relevant to species delimitation far exceeds the parameterization of any existing method, a given method necessarily makes a number of simplifying assumptions, any one of which could be violated in a particular system. We suggest that researchers should apply a wide range of species delimitation analyses to their data and place their trust in delimitations that are congruent across methods. Incongruence across the results from different methods is evidence of either a difference in the power to detect cryptic lineages across one or more of the approaches used to delimit species and could indicate that assumptions of one or more of the methods have been violated. In either case, the inferences drawn from species delimitation studies should be conservative, for in most contexts it is better to fail to delimit species than it is to falsely delimit entities that do not represent actual evolutionary lineages.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Model selection and multimodel inference: a practical information-theoretic approach.
Guthery, F. S., Burnham, K. P., & Anderson, D. R. (2003) · The Journal of Wildlife Management · doi:10.2307/3802723 · Cited by 41,495
Bayesian inference of species trees from multilocus data
Heled, J., & Drummond, A. J. (2010) · Molecular Biology and Evolution · doi:10.1093/molbev/msp274 · Cited by 2,453
Gutenkunst, R. N., Hernandez, R. D., Williamson, S. H., & Bustamante, C. D. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000695 · Cited by 1,906 · cited 3×
“1998), population divergence (Hey & Nielsen 2007) or combinations of these processes (Gutenkunst et al. 2009) are widely applied to phylogeographical data.”
BackgroundBayesian species delimitation using multilocus sequence data
Yang, Z., & Rannala, B. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0913022107 · Cited by 1,405
Approximate Bayesian Computation (ABC) in practice
Csilléry, K., Blum, M. G. B., Gaggiotti, O. E., & François, O. (2010) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2010.04.001 · Cited by 1,302
Flot, J.-F., Couloux, A., & Tillier, S. (2010) · BMC Evolutionary Biology · doi:10.1186/1471-2148-10-372 · Cited by 139
Cited by
The BPP program for species tree estimation and species delimitation
Yang, Z. (2015) · Current Zoology · doi:10.1093/czoolo/61.5.854 · Cited by 772
Cryptic species as a window into the paradigm shift of the species concept
Fišer, C., Robinson, C. T., & Malard, F. (2018) · Molecular Ecology · doi:10.1111/mec.14486 · Cited by 574
Coates, D. J., Byrne, M., & Moritz, C. (2018) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2018.00165 · Cited by 460
Gómez Daglio, L., & Dawson, M. N. (2017) · Invertebrate Systematics · doi:10.1071/is16055 · Cited by 98
A paradigm shift in our view of species drives current trends in biological classification
Padial, J. M., & De la Riva, I. (2021) · Biological Reviews · doi:10.1111/brv.12676 · Cited by 85
Metadata
- Authors
- Carstens, B. C., Pelletier, T. A., Reid, N. M., & Satler, J. D.
- Venue
- Molecular Ecology
- Publisher
- Wiley
- Published
- 2013-07-16
- Volume
- 22
- Issue
- 17
- Pages
- 4369-4383
- ISSN
- 0962-1083 (ISSN-L)
- 1365-294X
- OpenAlex
- W2141283603
- Cited by
- 1,248
- References
- 6
- FWCI
- 44.31
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: How to fail at species delimitation. https://app.cochat.ai/papers/10.1111/mec.12413
- The paper
- Carstens, B. C., Pelletier, T. A., Reid, N. M., & Satler, J. D. (2013). How to fail at species delimitation. Molecular Ecology. https://doi.org/10.1111/mec.12413
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.