Closed MKLau closed 10 years ago
Function ‘commsimulator’ implements binary (presence/absence) null models for community composition. The implemented models are ‘r00’ which maintains the number of presences but fills these anywhere so that neither species (column) nor site (row) totals are preserved. Methods ‘r0’, ‘r1’ and ‘r2’ maintain the site (row) frequencies. Method ‘r0’ fills presences anywhere on the row with no respect to species (column) frequencies, ‘r1’ uses column marginal frequencies as probabilities, and ‘r2’ uses squared column sums. Methods ‘r1’ and ‘r2’ try to simulate original species frequencies, but they are not strictly constrained. All these methods are reviewed by Wright et al. (1998). Method ‘c0’ maintains species frequencies, but does not honour site (row) frequencies (Jonsson 2001).
The other methods maintain both row and column frequencies.
Methods ‘swap’ and ‘tswap’ implement sequential methods, where the
matrix is changed only little in one step, but the changed matrix
is used as an input if the next step. Methods ‘swap’ and ‘tswap’
inspect random 2x2 submatrices and if they are checkerboard units,
the order of columns is swapped. This changes the matrix
structure, but does not influence marginal sums (Gotelli &
Entsminger 2003). Method ‘swap’ inspects submatrices so long that
a swap can be done. Miklós & Podani (2004) suggest that this may
lead into biased sequences, since some columns or rows may be more
easily swapped, and they suggest trying a fixed number of times
and doing zero to many swaps at one step. This method is
implemented by method ‘tswap’ or trial swap. Function
‘commsimulator’ makes only one trial swap in time (which probably
does nothing), but ‘oecosimu’ estimates how many submatrices are
expected before finding a swappable checkerboard, and uses that
ratio to thin the results, so that on average one swap will be
found per step of ‘tswap’. However, the checkerboard frequency
analyze liv and sen in 4 ways