proportional.overlap function

Proportional similarity overlap index

This index is a measurement of the overlap of proportional similarity (PS) indices between pairs of taxa across samples. As the PS is a niche breadth index that measures the similarity between a taxon's distribution and an environmental parameter, the PS overlap also considers environmental information. A value of 1 indicates perfect overlap, and 0 indicates no overlap.

proportional.overlap(df, sampleInfo, envInfo, q = 1.65)

Arguments

• df: A matrix of taxa (rows) by samples (columns) as discrete counts per sample. Col 1 must be a taxon identifier.
• sampleInfo: A categorical variable identifying which samples correspond to which environment.
• envInfo: A quantitative variable of some environmental parameter measured per sample.
• q: A coefficient for the LOQ, set to 1.65. Decreasing or increasing q will affect which taxa are flagged as being below the LOQ.

Details

Taxon inputs must be as discrete counts across samples, with a taxon identifier in column 1. The output is a matrix of paired taxon overlap indices. Specifically, Proportional Overlap (PO) indices of PO[1,2] are rows and PO[2,1] are columns, for taxa 1 and 2, however these values are identical. Feinsinger's PS is calculated as per feinsingers.PS.

Proportional overlap is calculated as follows: PO[i,j] = 1 - (|PS[i] - PS[j]|)/(PS[i] + PS[j]) whereby PS[i] is the PS of taxon i and PS[j] is the PS of taxon j.

Taxa below the LOQ are flagged with an asterisk.

This function depends on reshape2 to produce a matrix of overlap comparisons.

Returns

An object of class "data.frame" that gives PO[1,2] as rows and PO[2,1] as columns.

References

Feinsinger et al. 1981. A simple measure of niche breadth. Ecology 62(1):27-32

Author(s)

Damien Finn

Note

NA

See Also

feinsingers.PS

Examples

data(df)
overlapdf <- df[48:53,]
sampleInfo <- c(rep("R1",10), rep("R2",10), rep("R3",10), rep("R4",10))
pH.grad <- c(2.1, 2.2, 2, 1.9, 2.1, 1.8, 1.9, 2, 2.1, 1.9, 3.5, 3.6, 3.5, 
             3.4, 3.6, 3.5, 3.5, 3.4, 3.7, 3.4, 6.6, 6.5, 6.4, 6.8, 7, 6.6, 
             6.8, 6.9, 7, 7.1, 8, 8.2, 7.9, 8.1, 7.8, 7.9, 8.3, 8.2, 8.1, 7.9) 
res <- proportional.overlap(overlapdf, sampleInfo, pH.grad)