turnover | R Documentation |
Returns the degree of turnover in taxa composition along a gradient or transect.
turnover(object, ...)
## S4 method for signature 'matrix'
turnover(
object,
...,
method = c("whittaker", "cody", "routledge1", "routledge2", "routledge3", "wilson")
)
## S4 method for signature 'data.frame'
turnover(
object,
...,
method = c("whittaker", "cody", "routledge1", "routledge2", "routledge3", "wilson")
)
object |
A |
... |
Further arguments to be passed to internal methods. |
method |
A |
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:
cody
Cody measure.
routledge1
Routledge first measure.
routledge2
Routledge second measure.
routledge3
Routledge third measure (exponential form of the second measure).
whittaker
Whittaker measure.
wilson
Wilson measure.
This assumes that the order of the matrix rows (from 1
to n
)
follows the progression along the gradient/transect.
A numeric
vector.
N. Frerebeau
index_cody()
, index_routledge1()
, index_routledge2()
,
index_routledge3()
, index_whittaker()
, index_wilson()
Other diversity measures:
heterogeneity()
,
occurrence()
,
plot_diversity
,
plot_rarefaction
,
profiles()
,
rarefaction()
,
richness()
,
she()
,
similarity()
,
simulate()
## Data from Magurran 1988, p. 162
data("woodland")
## Whittaker's measure
turnover(woodland, "whittaker") # 1
## Cody's measure
turnover(woodland, "cody") # 3
## Routledge's measures
turnover(woodland, "routledge1") # 0.29
turnover(woodland, "routledge2") # 0.56
turnover(woodland, "routledge3") # 1.75
## Wilson and Shmida's measure
turnover(woodland, "wilson") # 1
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