calcBetaDiv {chemodiv}

Calculate beta diversity

Description

Function to calculate beta diversity in the Hill diversity framework. This can be calculated as Hill beta diversity or Functional Hill beta diversity.

Usage

calcBetaDiv(sampleData, compDisMat = NULL, type = "HillDiv", q = 1)

Arguments

sampleData

Data frame with the relative concentration of each compound (column) in every sample (row).

compDisMat

Compound dissimilarity matrix, as calculated by compDis. Has to be supplied for calculations of Functional Hill beta diversity.

type

Type(s) of Hill beta diversity to calculate. "HillDiv" and/or "FuncHillDiv".

q

Diversity order to use for the calculation of beta diversity. See calcDiv for further details on q.

Details

The function calculates a single beta diversity value for the supplied sampleData. This is calculated as beta = gamma / alpha. Gamma diversity represents the diversity of the pooled data set, alpha diversity represents the mean diversity across individual samples, and beta diversity represents turnover or variability among samples. With type = "HillDiv" and q = 0 the calculated beta diversity is equal to the well-known and most simple measure of beta diversity introduced by Whittaker 1960, where beta = gamma / alpha, based only on the number of species (here compounds).

Value

Data frame with type of Hill beta diversity calculated, q, and values for gamma diversity, mean alpha diversity and beta diversity.

References

Chao A, Chiu C-H, Jost L. 2014. Unifying Species Diversity, Phylogenetic Diversity, Functional Diversity, and Related Similarity and Differentiation Measures Through Hill Numbers. Annual Review of Ecology, Evolution, and Systematics 45: 297-324.

Jost L. 2007. Partitioning diversity into independent alpha and beta components. Ecology 88: 2427-2439.

Whittaker RH. 1960. Vegetation of the Siskiyou Mountains, Oregon and California. Ecological Monographs 30: 279-338.

Examples

data(minimalSampData)
data(minimalCompDis)
calcBetaDiv(sampleData = minimalSampData)
calcBetaDiv(sampleData = minimalSampData, compDisMat = minimalCompDis,
type = c("HillDiv", "FuncHillDiv"), q = 2)

data(alpinaSampData)
data(alpinaCompDis)
calcBetaDiv(sampleData = alpinaSampData, compDisMat = alpinaCompDis,
type = "FuncHillDiv")