The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Putting Things in Even Better Order: The Advantages of Canonical Correspondence Analysis
Open accessAbstract
Canonical Correspondence Analysis (CCA) is quickly becoming the most widely used gradient analysis technique in ecology. The CCA algorithm is based upon Correspondence Analysis (CA), an indirect gradient analysis (ordination) technique. CA and a related ordination technique, Detrended Correspondence Analysis, have been criticized for a number of reasons. To test whether CCA suffers from the same defects, I simulated data sets with properties that usually cause problems for DCA. Results indicate that CCA performs quite well with skewed species distributions, with quantitative noise in species abundance data, with samples taken from unusual sampling designs, with highly intercorrelated environmental variables, and with situations where not all of the factors determining species composition are known. CCA is immune to most of the problems of DCA.
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Cites
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Cited by
Greenacre, M., Groenen, P. J. F., Hastie, T., D’Enza, A. I., Markos, A., & Tuzhilina, E. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00184-w · Cited by 1,773
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Habitat associations of small mammals at two spatial scales in the Northern Sierra Nevada
Coppeto, S. A., Kelt, D. A., Van Vuren, D. H., Wilson, J. A., & Bigelow, S. (2006) · Journal of Mammalogy · doi:10.1644/05-mamm-a-086r1.1 · Cited by 89
Livezey, B. C. (2003) · Ornithological Monographs · doi:10.2307/40168337 · Cited by 81
Improving habitat models by incorporating pelagic measurements from coastal ocean observatories
Palamara, L., Manderson, J., Kohut, J., Oliver, M., Gray, S., & Goff, J. (2012) · Marine Ecology Progress Series · doi:10.3354/meps09496 · Cited by 12
Metadata
- Authors
- Palmer, M. W.
- Venue
- Ecology
- Publisher
- Wiley
- Published
- 1993-12
- Volume
- 74
- Issue
- 8
- Pages
- 2215-2230
- ISSN
- 0012-9658 (ISSN-L)
- 1939-9170
- OpenAlex
- W1969139249
- Cited by
- 1,161
- References
- 32
- FWCI
- 39.88
- Type
- journal article
- Language
- en
- Open access
- green
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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.
