Returns the degree of turnover in taxa composition along a gradient or transect.
Usage
turnover(object, ...)
# S4 method for class 'matrix'
turnover(
object,
...,
method = c("whittaker", "cody", "routledge1", "routledge2", "routledge3", "wilson")
)
# S4 method for class 'data.frame'
turnover(
object,
...,
method = c("whittaker", "cody", "routledge1", "routledge2", "routledge3", "wilson")
)Arguments
- object
A \(m \times p\)
numericmatrixordata.frameof count data or incidence data. Adata.framewill be coerced to anumericmatrixviadata.matrix().- ...
Further arguments to be passed to internal methods.
- method
A
characterstring specifying the method to be used (see details). Any unambiguous substring can be given.
Value
A numeric vector.
Details
The following methods can be used to ascertain the degree of turnover in taxa composition along a gradient (\(\beta\)-diversity) on qualitative (presence/absence) data:
codyroutledge1routledge2routledge3Routledge third measure (exponential form of the second measure).
whittakerwilson
This assumes that the order of the matrix rows (from \(1\) to \(n\)) follows the progression along the gradient/transect.
Data are standardized on a presence/absence scale (\(0\)/\(1\)) beforehand.
See also
index_cody(), index_routledge1(), index_routledge2(),
index_routledge3(), index_whittaker(), index_wilson()
Other diversity measures:
diversity(),
evenness(),
heterogeneity(),
occurrence(),
plot.DiversityIndex(),
plot.RarefactionIndex(),
profiles(),
rarefaction(),
richness(),
she(),
similarity(),
simulate()
Examples
## Data from Magurran 1988, p. 162
data("woodland")
## Whittaker's measure
turnover(woodland, "whittaker") # 1
#> [1] 1
## Cody's measure
turnover(woodland, "cody") # 3
#> [1] 1
## Routledge's measures
turnover(woodland, "routledge1") # 0.29
#> [1] 1
turnover(woodland, "routledge2") # 0.56
#> [1] 1
turnover(woodland, "routledge3") # 1.75
#> [1] 1
## Wilson and Shmida's measure
turnover(woodland, "wilson") # 1
#> [1] 1
