The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Applying Metric and Nonmetric Multidimensional Scaling to Ecological Studies: Some New Results
Abstract
Metric (eigenanalysis) and nonmetric multidimensional scaling strategies for ecological ordination were compared. The result, based on simulated coenoplane data showing varying degrees of species turnover on two independent environmental axes, suggested some strong differences between metric and nonmetric scaling methods in their ability to recover underlying nonlinear data structures. Prior data standardization had important effects on the results of both metric and nonmetric scaling, though the effect varied with the ordination method used. Nonmetric multidimensional scaling based on Euclidean distance following stand norm standardization proved to be the best strategy for recovering simulated coenoplane data. Of the metric strategies compared, correspondence analysis and the detrended form were the most successful. While detrending improved ordination configurations in some cases, in others it led to a distortion of results. It is suggested that none of the currently available ordination strategies is appropriate under all circumstances, and that future research in ordination methodology should emphasize a statistical rather than empirical approach.
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Cites
Analysis of a complex of statistical variables into principal components.
Hotelling, H. (1933) · Journal of Educational Psychology · doi:10.1037/h0071325 · Cited by 9,633
Cluster Analysis for Applications
(1973) · Elsevier eBooks · doi:10.1016/c2013-0-06161-0 · Cited by 5,080
Some distance properties of latent root and vector methods used in multivariate analysis
GOWER, J. C. (1966) · Biometrika · doi:10.1093/biomet/53.3-4.325 · Cited by 4,293
Multivariate Analysis in Community Ecology
Gauch, H. G. (1982) · Cambridge University Press eBooks · doi:10.1017/cbo9780511623332 · Cited by 3,426
Detrended Correspondence Analysis: An Improved Ordination Technique
Hill, M. O., & Gauch, H. G. (1980) · Classification and Ordination · doi:10.1007/978-94-009-9197-2_7 · Cited by 3,337
The Analysis of Proximities: Multidimensional Scaling with an Unknown Distance Function. I.
Shepard, R. N. (1962) · Psychometrika · doi:10.1007/bf02289630 · Cited by 2,550
Multidimensional Scaling: I. Theory and Method
Torgerson, W. S. (1952) · Psychometrika · doi:10.1007/bf02288916 · Cited by 2,126
Sampling Design and Statistical Methods for Environmental Biologists
Green, R. H. (1979) · Andalas University Repository (Andalas University) · Cited by 1,550
Reciprocal Averaging: An Eigenvector Method of Ordination
Hill, M. O. (1973) · The Journal of Ecology · doi:10.2307/2258931 · Cited by 1,027
(1981) · Cited by 813
Cited by
Ter Braak, C. J. F., & Prentice, I. C. (1988) · Advances in Ecological Research · doi:10.1016/s0065-2504(08)60183-x · Cited by 1,963
Putting Things in Even Better Order: The Advantages of Canonical Correspondence Analysis
Palmer, M. W. (1993) · Ecology · doi:10.2307/1939575 · Cited by 1,161
Use of Amazonian Forest Fragments by Understory Insectivorous Birds
Stouffer, P. C., & Bierregaard, R. O. (1995) · Ecology · doi:10.2307/2265818 · Cited by 609
The effect of 16S rRNA region choice on bacterial community metabarcoding results
Bukin, Y. S., Galachyants, Y. P., Morozov, I. V., Bukin, S. V., Zakharenko, A. S., & Zemskaya, T. I. (2019) · Scientific Data · doi:10.1038/sdata.2019.7 · Cited by 394
Gut microbiota-derived hexa-acylated lipopolysaccharides enhance cancer immunotherapy responses
Sardar, P., Beresford-Jones, B. S., Xia, W., Shabana, O., Suyama, S., Ramos, R. J. F., Soderholm, A. T., Tourlomousis, P., Kuo, P., Evans, A. C., et al. (2025) · Nature Microbiology · doi:10.1038/s41564-025-01930-y · Cited by 49
Metadata
- Authors
- Kenkel, N. C., & Orloci, L.
- Venue
- Ecology
- Publisher
- Wiley
- Published
- 1986-08
- Volume
- 67
- Issue
- 4
- Pages
- 919-928
- ISSN
- 0012-9658 (ISSN-L)
- OpenAlex
- W2123128218
- Cited by
- 668
- References
- 33
- FWCI
- 25.91
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
