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Last data update: 2014.03.03

R: Determines species turnover

Turnover

R Documentation

Determines species turnover

Description

'Turnover' is a function that assesses species turnover from the range perspective (traditional method).

Usage

Turnover(comm, method = "r1", sims = 1000, scores = 1, order = TRUE,
  allowEmpty = FALSE, binary = TRUE, verbose = FALSE)

Arguments

`comm`	community data in the form of a presence absence matrix
`method`	null model randomization method used by 'nullmaker'. See details.
`sims`	number of simulated null matrices to use in analysis
`scores`	axis scores to ordinate matrix. 1: primary axis scores (default) 2: secondary axis scores
`order`	logical argument indicating whether to ordinate the interaction matrix or not. See details.
`allowEmpty`	logical argument indicating whether to allow null matrices to have empty rows or columns
`binary`	logical argument indicating whether to ordinate the community matrix based on abundance or binary (default) data.
`verbose`	Logical. Prints a graphical progress bar that tracks the creation of null matrices. Useful for conservative null models on large and/or sparse data.

Details

If the 'community' perspective is desired, simply transpose the matrix before analysis using the transpose function ('t()'), but make sure you understand the implications of this action, as the interpretation of the output changes dramatically.

'method' is an argument handed to functions in the 'vegan' package. Leibold & Mikkelson advocated the use of equiprobable rows and columns (provided that rows and columns had at least one entry). This method is called 'r00'. Methods maintaining row (site) frequencies include 'r0','r1' & 'r2'. The default method argument is 'r1', which maintains the species richness of a site (row totals) and fills species ranges (columns) based on their marginal probabilities. Arguably the most conservative null algorithm is the fixed row - fixed column total null, which is implemented as 'fixedfixed'. See the help file for 'commsimulator' or Wright et al. 1998 for more information.

If 'order' is FALSE, the interaction matrix is not ordinated, allowing the user to order the matrix based on site characteristics or other biologically relevant characteristics.

This function can either be used as a standalone, or can be used through the 'metacommunity()' function, which determines all 3 elements of metacommunity structure (coherence, boundary clumping, & turnover) (Leibold & Mikkelson 2002). The turnover metric used here is equivalent to the number of checkerboard units community with species ranges (range perspective) filled in

Value

A data.frame containing the test statistic (turnover), z-value (z), p-value (pval), mean (simulatedMean) and variance (simulatedVariance) of simulations, and randomization method (method)

Author(s)

Tad Dallas

References

Leibold, M.A. and G.M. Mikkelson. 2002. Coherence, species turnover, and boundary clumping: elements of meta-community structure. Oikos 97: 237 - 250.

Wright, D.H., Patterson, B.D., Mikkelson, G.M., Cutler, A. & Atmar, W. (1998). A comparative analysis of nested subset patterns of species composition. Oecologia 113, 1-20.

Examples


#define an interaction matrix
data(TestMatrices)
intmat <- TestMatrices[[3]]

#determine species turnover
turnover.intmat <- Turnover(intmat, method='r1', sims=100, scores=1, binary=TRUE)