[Vegan-commits] r981 - pkg/vegan/man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Tue Sep 1 21:36:32 CEST 2009
Author: psolymos
Date: 2009-09-01 21:36:32 +0200 (Tue, 01 Sep 2009)
New Revision: 981
Modified:
pkg/vegan/man/adipart.Rd
Log:
separating adipart and multipart docs
Modified: pkg/vegan/man/adipart.Rd
===================================================================
--- pkg/vegan/man/adipart.Rd 2009-09-01 18:53:43 UTC (rev 980)
+++ pkg/vegan/man/adipart.Rd 2009-09-01 19:36:32 UTC (rev 981)
@@ -1,28 +1,22 @@
\encoding{UTF-8}
\name{adipart}
\alias{adipart}
-\alias{multipart}
\alias{print.adipart}
-\alias{print.multipart}
\alias{hiersimu}
\alias{print.hiersimu}
-\title{Diversity Partitioning and Hierarchical Null Model Testing}
+\title{Additive Diversity Partitioning and Hierarchical Null Model Testing}
\description{
-In diversity partitioning, mean values of alpha diversity at lower levels of a sampling
+In additive diversity partitioning, mean values of alpha diversity at lower levels of a sampling
hierarchy are compared to the total diversity in the entire data set (gamma diversity).
-The partitioning can be additive (\code{adipart}) or multiplicative (\code{multipart}).
In hierarchical null model testing, a statistic returned by a function is evaluated
according to a nested hierarchical sampling design (\code{hiersimu}).
}
\usage{
adipart(formula, data, index=c("richness", "shannon", "simpson"),
weights=c("unif", "prop"), relative = FALSE, nsimul=99, ...)
-multipart(formula, data, index=c("renyi", "tsallis"), scales = 1,
- global = FALSE, relative = FALSE, nsimul=99, ...)
hiersimu(formula, data, FUN, location = c("mean", "median"),
relative = FALSE, drop.highest = FALSE, nsimul=99, ...)
\method{print}{adipart}(x, ...)
-\method{print}{multipart}(x, ...)
\method{print}{hiersimu}(x, ...)
}
\arguments{
@@ -39,17 +33,13 @@
weighting proportional to sample abundances to use in weighted averaging of individual
alpha values within strata of a given level of the sampling hierarchy.}
\item{relative}{Logical, if \code{TRUE} then alpha and beta diversity values are given
- relative to the value of gamma for function \code{adipart}. For function \code{multipart},
- it sets the standardization of the beta diversity value with its maximum (see Details).}
- \item{scales}{Numeroc, of length 1, the order of the generalized diversity index
- to be used.}
- \item{global}{Logical, indicates the calculation of beta values, see Details.}
+ relative to the value of gamma for function \code{adipart}.}
\item{nsimul}{Number of permutation to use if \code{matr} is not of class 'permat'.
If \code{nsimul = 0}, only the \code{FUN} argument is evaluated. It is thus possible
to reuse the statistic values without using a null model.}
\item{FUN}{A function to be used by \code{hiersimu}. This must be fully specified,
because currently other arguments cannot be passed to this function via \code{\dots}.}
- \item{location}{Character, identifies which function (mean or median) is used to
+ \item{location}{Character, identifies which function (mean or median) is to be used to
calculate location of the samples.}
\item{drop.highest}{Logical, to drop the highest level or not. When \code{FUN}
evaluates only arrays with at least 2 dimensions, highest level should be dropped,
@@ -84,35 +74,8 @@
The implementation of additive diversity partitioning in \code{adipart} follows Crist et
al. 2003. It is based on species richness (\eqn{S}, not \eqn{S-1}), Shannon's and
-Simpson's diversity indices states as argument \code{index}.
+Simpson's diversity indices stated as the \code{index} argument.
-Multiplicative diversity partitioning is based on Whittaker's (1972) ideas, that has
-recently been generalised to one parametric diversity families (i.e. \enc{R\'enyi}{Renyi}
-and Tsallis) by Jost (2006, 2007). Jost recommends to use the numbers equivalents
-(Hill numbers), instead of pure diversities, and proofs, that this satisfies the
-multiplicative partitioning requirements.
-
-The current implementation of \code{multipart} calculates Hill numbers based on the
-functions \code{\link{renyi}} and \code{\link{tsallis}} (provided as \code{index} argument).
-If values for more than one \code{scales} values are desired, it should be done in separate
-runs, because it adds extra dimensionality to the implementation, which has not been resolved
-efficiently.
-
-Alpha diversities are then the averages of these Hill numbers for each hierarchy levels,
-the global gamma diversity is the alpha value calculated for the highest hierarchy level.
-When \code{global = TRUE}, beta is calculated relative to the global gamma value:
-\deqn{\beta_i = \gamma / \alpha_{i}}{beta_i = gamma / alpha_i}
-when \code{global = FALSE}, beta is calculated relative to local gamma values (local gamma
-means the diversity the calculated for a particular cluster based on the pooled abundance vector):
-\deqn{\beta_ij = \alpha_{(i+1)j} / mean(\alpha_{ij})}{beta_ij = alpha_(i+1)j / mean(alpha_i)}
-where \eqn{j} is a particular cluster at hierarchy level \eqn{i}. Then beta diversity value for
-level \eqn{i} is the mean of the beta values of the clusters at that level,
-\eqn{\beta_{i} = mean(\beta_{ij})}.
-
-If \code{relative = TRUE} for \code{multipart}, the respective beta diversity values are
-standardized by their maximum expected values (\eqn{mean(\beta_{ij}) / \beta_{max,ij}})
-given as \eqn{\beta_{max,ij} = n_{j}} (the number of lower level units in a given cluster \eqn{j}).
-
The expected diversity components are calculated \code{nsimul} times by individual based
randomisation of the community data matrix. This is done by the \code{"r2dtable"} method
in \code{\link{oecosimu}} by default.
@@ -125,7 +88,6 @@
\value{
An object of class 'adipart' or 'hiersimu' with same structure as 'oecosimu' objects.
}
-
\references{
Crist, T.O., Veech, J.A., Gering, J.C. and Summerville,
K.S. (2003). Partitioning species diversity across landscapes and regions:
@@ -133,23 +95,13 @@
\eqn{\gamma}-diversity.
\emph{Am. Nat.}, \bold{162}, 734--743.
-Jost, L. (2006). Entropy and diversity.
-\emph{Oikos}, \bold{113}, 363--375.
-
-Jost, L. (2007). Partitioning diversity into independent alpha and beta components.
-\emph{Ecology}, \bold{88}, 2427--2439.
-
Lande, R. (1996). Statistics and partitioning of species
diversity, and similarity among multiple communities.
\emph{Oikos}, \bold{76}, 5--13.
-
-Whittaker, R. (1972). Evolution and measurement of species diversity.
-\emph{Taxon}, \bold{21}, 213--251.
}
\author{\enc{P\'eter S\'olymos}{Peter Solymos}, \email{solymos at ualberta.ca}}
-\seealso{See \code{\link{permatfull}}, \code{\link{permatswap}} and \code{\link{permat.control}}
- for permutation settings, and \code{\link{oecosimu}} for calculating confidence levels.}
+\seealso{See \code{\link{oecosimu}} for permutation settings and calculating \eqn{p}-values.}
\examples{
data(mite)
data(mite.xy)
@@ -173,20 +125,7 @@
plot(mite.xy, main="l3", col=as.numeric(levsm$l3)+1)
par(mfrow=c(1,1))
## Additive diversity partitioning
-adpMite <- adipart(mite ~., levsm, index="richness", nsimul=20)
-adpMite
-## Simple artificial example
-set.seed(4321)
-matr <- r2dtable(1, c(3,4,3,7,4,8,7,6), 3:9)[[1]]
-strata <- data.frame(letters[1:8], rep(letters[1:4],each=2), rep("a",8))
-## Restricted permutation within habitat classes
-contr <- permat.control(strata = c("a","a","a","b","a","b","b","b"))
-## Additive diversity partitioning
-x1 <- adipart(matr ~ ., strata, index="shannon", nsimul=25, control=contr)
-x1
-## Multiplicative diversity partitioning
-x2 <- multipart(matr ~ ., strata, index="renyi", scales=1, nsimul=25)
-x2
+adipart(mite ~., levsm, index="richness", nsimul=20)
## Hierarchical null model testing
## diversity analysis (similar to adipart)
hiersimu(mite ~., levsm, diversity, relative=TRUE, nsimul=25)
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