rarefaction | R Documentation |
Computes Hurlbert's unbiased estimate of Sander's rarefaction.
rarefaction(object, ...) index_hurlbert(x, ...) ## S4 method for signature 'matrix' rarefaction(object, sample = NULL, method = c("hurlbert"), step = 1) ## S4 method for signature 'data.frame' rarefaction(object, sample = NULL, method = c("hurlbert"), step = 1) ## S4 method for signature 'numeric' index_hurlbert(x, sample, ...)
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Currently not used. |
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rarefaction()
returns a RarefactionIndex object.
index_*()
return a numeric
vector.
The number of different taxa, provides an instantly comprehensible expression of diversity. While the number of taxa within a sample is easy to ascertain, as a term, it makes little sense: some taxa may not have been seen, or there may not be a fixed number of taxa (e.g. in an open system; Peet 1974). As an alternative, richness (S) can be used for the concept of taxa number (McIntosh 1967).
It is not always possible to ensure that all sample sizes are equal and the number of different taxa increases with sample size and sampling effort (Magurran 1988). Then, rarefaction (E(S)) is the number of taxa expected if all samples were of a standard size (i.e. taxa per fixed number of individuals). Rarefaction assumes that imbalances between taxa are due to sampling and not to differences in actual abundances.
N. Frerebeau
Hurlbert, S. H. (1971). The Nonconcept of Species Diversity: A Critique and Alternative Parameters. Ecology, 52(4), 577-586. doi: 10.2307/1934145.
Sander, H. L. (1968). Marine Benthic Diversity: A Comparative Study. The American Naturalist, 102(925), 243-282.
Other diversity measures:
heterogeneity()
,
occurrence()
,
plot_diversity
,
richness()
,
similarity()
,
simulate()
,
turnover()
## Richness ## Margalef and Menhinick index ## Data from Magurran 1988, p. 128-129 trap <- matrix(data = c(9, 3, 0, 4, 2, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 2, 0, 5, 3, 0), nrow = 2, byrow = TRUE, dimnames = list(c("A", "B"), NULL)) richness(trap, method = "margalef") # 2.55 1.88 richness(trap, method = "menhinick") # 1.95 1.66 ## Asymptotic species richness ## Chao1-type estimators ## Data from Chao & Chiu 2016 brazil <- matrix( data = rep(x = c(1:21, 23, 25, 27, 28, 30, 32, 34:37, 41, 45, 46, 49, 52, 89, 110, 123, 140), times = c(113, 50, 39, 29, 15, 11, 13, 5, 6, 6, 3, 4, 3, 5, 2, 5, 2, 2, 2, 2, 1, 2, 1, 1, 1, 1, 1, 0, 0, 2, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0)), nrow = 1, byrow = TRUE ) composition(brazil, method = c("chao1"), unbiased = FALSE) # 461.625 composition(brazil, method = c("ace"), k = 10) # 445.822 ## Rarefaction rarefaction(trap, sample = 13) # 6.56 6.00
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