R: Analysis of the Elements of Metacommunity Structure
Metacommunity
R Documentation
Analysis of the Elements of Metacommunity Structure
Description
'Metacommunity' is a wrapper for the analysis of the three elements of
metacommunity structure (coherence, boundary clumping, & turnover) following
the framework of Leibold & Mikkelson 2002. It is important to note here that
the results of boundary clumping and turnover are only relevant if the
matrix is significantly positively coherent (i.e. empirical matrix has fewer
embedded absences than null matrices).
community data in the form of a presence absence matrix
scores
Axis scores to ordinate matrix. 1: primary axis scores
(default) 2: secondary axis scores. See Details.
method
null model randomization method used by 'nullmaker'. See
details.
sims
number of simulated null matrices to use in analysis
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
'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 can be attained using many of swap
algorithms described in the vegan package (sequential methods like 'tswap',
'swap', and non-sequential 'quasiswap' and 'backtracking'). See the help
file for 'commsim' 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.
Value
A list of length 4, containing;
Comm – ordinated matrix used to calculate coherence, boundary
clumping & turnover
Coherence –output of the Coherence() function, giving information on
the number of embedded absences and the significance relative to simulated
null matrices
Turnover – output of the Turnover() function, testing the number of
species replacements relative to simulated null matrices
Boundary – output of the BoundaryClump() function, which calculates the
Morisita's index, assessing significance using a chi-squared test
Note
This function may take awhile to finish as a result of the creation of
null matrices. If you are running multiple interaction matrices, the code
can be parallelized using the 'snow' package.
Author(s)
Tad Dallas
References
Dallas,T. 2014. metacom: an R package for the analysis of
metacommunity structure. Ecography. DOI:10.1111/j.1600-0587.2013.00695.x
Leibold, M.A. and G.M. Mikkelson. 2002. Coherence, species turnover, and
boundary clumping: elements of meta-community structure. Oikos 97: 237 -
250.
Presley, S. J., C. L. Higgins, and M. R. Willig. 2010. A comprehensive
framework for the evaluation of metacommunity structure. Oikos 119:908-917
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[[7]]
#determines the elements of metacommunity structure
ems.test <- Metacommunity(intmat, method='r1', sims=100, scores=1)