Rings, circles, and null-models for point pattern analysis in ecology

By T. Wiegand, Kirk Moloney. 2004

1,137 citations recorded by the source corpus.

Subfields: Environmental Engineering, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/59d9094758d513a97a58a96419ecd0995dff025b

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In Environmental Engineering

In Nature and Landscape Conservation

Citations in the corpus

Land use impact on Vitellaria paradoxa C.F. Gaerten. stand structure and distribution patterns: a comparison of Biosphere Reserve of Pendjari in Atacora district in Benin (2008, methodology): “The paircorrelation function is a non-accumulative version of Ripley’s K-function (Ripley 1981) satisfying g(r) = (1/2 pr) dK(r)/dr.”
Spatial interactions between storm damage and subsequent infestations by the European spruce bark beetle (2014, positive): “of the spatial pattern of locally distinct bark beetle infestations, including the underlying processes and neighborhood effects between bark beetle infestations, often relies on point pattern analysis (for reviews cf. Perry et al., 2002; Wiegand and Moloney, 2004; Illian et al., 2008).”
Spacing patterns of an Acacia tree in the Kalahari over a 61-year period: How clumped becomes regular and vice versa (2008, methodology): “For the abovementioned point pattern analysis of tree spatial distributions, Programita software was used (Wiegand and Moloney, 2004).”
Ecological information from spatial patterns of plants: insights from point process theory (2009, methodology): “Some authors advocate the use of more complex models such as Neyman–Scott processes (e.g. Thomas processes or Matern cluster processes) or other cluster processes as a null model (Wiegand & Moloney 2004; Wiegand et al. 2007b).”
A comparison of methods for the statistical analysis of spatial point patterns in plant ecology (2006, methodology): “Nevertheless, because it is effectively a differenced version of the K-function, we might also expect the NDF to be more noisy, and sensitive to small sample sizes (Wiegand and Moloney 2004).”
Spatial distributions of tree species in a subtropical forest of China (2009, background): “Wiegand and Moloney (2004) demonstrate that large-scale heterogeneity of a point-pattern biases Ripley’s K-function at smaller scales.”
Spatial variation in below‐ground seed germination and divergent mycorrhizal associations correlate with spatial segregation of three co‐occurring orchid species (2012, methodology): “The bivariate pair correlation function gij(r) (Stoyan & Stoyan 1994; Wiegand & Moloney 2004; Illian et al. 2008) is related to the bivariate neighbourhood density function [i.e.Oij(r) = kjgij(r)].”
Tree spatial patterns and stand attributes in temperate forests: The importance of plot size, sampling design, and null model (2018, background): “This differs from CSR in that the intensity λ (x, y) of the process depends on location (x, y), but the occurrence of any point remains independent of that of any other (Wiegand and Moloney, 2004).”
Drought induces lagged tree mortality in a subalpine forest in the Rocky Mountains (2007, methodology): “Point pattern analysis using Ripley’s K function is a common method to analyse spatial data in ecology (Wiegand and Moloney 2004).”