ecospat.cons_Cscore

0th

Percentile

Constrained Co-Occurrence Analysis.

Co-occurrence Analysis & Environmentally Constrained Null Models. The function tests for non-random patterns of species co-occurrence in a presence-absence matrix. It calculates the C-score index for the whole community and for each species pair. An environmental constraint is applied during the generation of the null communities.

Usage
ecospat.cons_Cscore(presence,pred,nperm,outpath)
Arguments
presence

A presence-absence dataframe for each species (columns) in each location or grid cell (rows) Column names (species names) and row names (sampling plots).

pred

A dataframe object with SDM predictions. Column names (species names SDM) and row names (sampling plots).

nperm

The number of permutation in the null model.

outpath

Path to specify where to save the results.

Details

An environmentally constrained approach to null models will provide a more robust evaluation of species associations by facilitating the distinction between mutually exclusive processes that may shape species distributions and community assembly. The format required for input databases: a plots (rows) x species (columns) matrix. Input matrices should have column names (species names) and row names (sampling plots). NOTE: a SES that is greater than 2 or less than -2 is statistically significant with a tail probability of less than 0.05 (Gotelli & McCabe 2002 - Ecology)

Value

Returns the C-score index for the observed community (ObsCscoreTot), the mean of C-score for the simulated communities (SimCscoreTot), p.value (PValTot) and standardized effect size (SES.Tot). It also saves a table in the specified path where the same metrics are calculated for each species pair (only the table with species pairs with significant p.values is saved in this version).

References

Gotelli, N.J. and D.J. McCabe. 2002. Species co-occurrence: a meta-analysis of JM Diamond`s assembly rules model. Ecology, 83, 2091-2096.

Peres-Neto, P.R., J.D. Olden and D.A. Jackson. 2001. Environmentally constrained null models: site suitability as occupancy criterion. Oikos, 93, 110-120.

Aliases
  • ecospat.cons_Cscore
Examples
# NOT RUN {
presence <- ecospat.testData[c(53,62,58,70,61,66,65,71,69,43,63,56,68,57,55,60,54,67,59,64)]
pred <- ecospat.testData[c(73:92)]
nperm <- 10000
outpath <- getwd()
ecospat.cons_Cscore(presence, pred, nperm, outpath)
# }
Documentation reproduced from package ecospat, version 3.0, License: GPL

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