spatialMingling: von Gadow's spatial mingling index

In johngodlee/compInd: Forest tree-tree competition indices

von Gadow's spatial mingling index

Description

von Gadow's spatial mingling index

Usage

spatialMingling(x, sp, k = 4, adj = FALSE)

Arguments

x	two column matrix of individual x and y coordinates
sp	vector of individual species names
k	number of neighbours to consider
adj	logical, if TRUE the basic spatial mingling index is multiplied by \frac{S_{i}}{n_{max}}, where S_{i} is the number of species in the neighbourhood of the focal individual, and n_{max} is the maximum number of species possible in the neighbourhood, including the focal individual, i.e. k + 1.

Details

Describes the degree of variety in species in the vicinity of a given focal individual. The proportion of the k nearest neighbours not belonging to the same species as the focal individual, given by the equation:

\frac{1}{k} \sum_{j=1}^{k} v_{j}

where v_{j} is the status of the competitor individual j, either 0 if j belongs to the same species as the focal individual, or 1 if j belongs to a different species. Values of spatial mingling for a given individual therefore vary between 0 and 1.

As per von Gadow and Hui (2001) this function could be adapted to calculate spatial mingling as a point attribute rather than an individual attribute.

Normally expressed as the mean of values per structural unit to scale up.

Value

value of the spatial mingling index for each individual in the structural unit.

References

von Gadow, K., Hui, G. Y. (2001). Characterising forest spatial structure and diversity. Sustainable Forestry in Temperate Regions. Proc. of an international workshop organized at the University of Lund, Sweden. Pages 20-30.

Examples

data(bicuar)
spatialMingling(bicuar[, c("x", "y")], bicuar$species,
  k = 4, adj = FALSE
)
spatialMingling(bicuar[, c("x", "y")], bicuar$species,
  k = 4, adj = TRUE
)

johngodlee/compInd documentation built on Aug. 5, 2024, 8:44 a.m.