The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Spatial pattern analysis in ecology based on Ripley's K‐function: Introduction and methods of edge correction
Abstract
Abstract. Spatial pattern analysis based on Ripley's K‐function is a second‐order analysis of point patterns in a twodimensional space. The method is increasingly used in studies of spatial distribution patterns of plant communities, but the statistical methods involved are sometimes poorly understood or have been modified without evaluating the effects on results. The procedures of field data acquisition, statistical analysis, and the test for the null hypothesis of complete spatial randomness are described and the presentation of results is discussed. Different methods of edge correction were tested on a computer‐generated random pattern and a mapped distribution of a Mediterranean shrubland. The inclusion of buffer zones around mapped plots describes the spatial pattern most accurately, but may not warrant the additional labour involved. Three variations of the weighted edge correction yielded comparable results for the distribution patterns tested. The toroidal edge correction may give biased results for non‐random patterns. Recommendations for standardisation of the statistical procedures and data presentation are given.
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Cites
Distance to Nearest Neighbor as a Measure of Spatial Relationships in Populations
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Ripley, B. D. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01615.x · Cited by 2,511
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Ripley, B. D. (1981) · Wiley Series in Probability and Statistics · doi:10.1002/0471725218 · Cited by 2,052
The second-order analysis of stationary point processes
Ripley, B. D. (1976) · Journal of Applied Probability · doi:10.2307/3212829 · Cited by 1,539
Randomization and Monte Carlo Methods in Biology
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Spatial Data Analysis by Example
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Cited by
Spatial Patterns in the Distribution of Tropical Tree Species
Condit, R., Ashton, P. S., Baker, P., Bunyavejchewin, S., Gunatilleke, S., Gunatilleke, N., Hubbell, S. P., Foster, R. B., Itoh, A., LaFrankie, J. V., et al. (2000) · Science · doi:10.1126/science.288.5470.1414 · Cited by 1,251
Rings, circles and null models for point pattern analysis in ecology.
Wiegand, T., & A. Moloney, K. (2004) · Oikos · doi:10.1111/j.0030-1299.2004.12497.x · Cited by 1,157
Spatial Analysis: A Guide for Ecologists
Fortin, M.-J., & Dale, M. R. T. (2005) · doi:10.1017/cbo9780511542039 · Cited by 991
Spatial Pattern Analysis in Plant Ecology
Dale, M. R. T. (1999) · Cambridge University Press eBooks · doi:10.1017/cbo9780511612589 · Cited by 746
A comparison of methods for the statistical analysis of spatial point patterns in plant ecology
Perry, G. L. W., Miller, B. P., & Enright, N. J. (2006) · Plant Ecology · doi:10.1007/s11258-006-9133-4 · Cited by 386
Metadata
- Authors
- Haase, P.
- Venue
- Journal of Vegetation Science
- Publisher
- Wiley
- Published
- 1995-08
- Volume
- 6
- Issue
- 4
- Pages
- 575-582
- ISSN
- 1100-9233 (ISSN-L)
- 1654-1103
- OpenAlex
- W2146402105
- Cited by
- 621
- References
- 32
- FWCI
- 12.13
- 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.
