1995Journal of Vegetation ScienceRequires access

Spatial pattern analysis in ecology based on Ripley's K‐function: Introduction and methods of edge correction

Peter Haase

Open publisher page 640 citations

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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What this paper is about

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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Available 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.

Key concepts: Point pattern analysis, Spatial ecology, Randomness, Null hypothesis, Common spatial pattern, Statistics, Ecology, Spatial analysis

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