douconca 1.2.5

• Minor update with cleaner version of function ipf2N2 or other minor changes.

douconca 1.2.4

• Update of function ipf2N2 for informative pre-processing of abundance data. The row and column marginals are set equal to Hill N2 or, the column marginals to N2(1-N2/N), the effective number of informative species. For max_iter==0 only the species marginal is adapted to N2 or N2(1-N2/N) without further adjustment to the abundance table. This is the simplest N2-preprocessing method and is generally quite powerful. It might be particulary useful if the function did not converge or gives a warning indicating very unequal site totals. # douconca 1.2.3

• Forward selection of traits and of environmental variables added (function FS()).

• Function ipf2N2 for informative pre-processing of abundance data. The row and column marginals are set equal to Hill N2 or, the column marginals to 2N2(N-N2)/N, the effective number of informative species. informative species

• More efficiency for large data sets by addition of a new cca function (cca0).

• An anova method for cca0 to enable residual predictor permutation.

• Improved stability for ‘exceptional’ data sets.

• The response can now be supplied as left-hand side of the environmental formula, instead of by the response argument.

douconca 1.2.2

• New coef.dcca() and fitted.dcca() functions with predict.dcca() adapted. The function coef() can give fourth-corner correlations and regression coefficients.
• Patch release with extended test files and associated small corrections, for example, SDS (standard deviation of predictors) was in v1.2.1 a constant factor too large with the default of the argument divideBySiteTotals (the regression weights and t-values were correct).

douconca 1.2.1

• Patch release addressing check errors on several CRAN build machines.

douconca 1.2.0

• Intial CRAN release

douconca 1.1.6

• An issue with collinear predictors in v1.1.5 has been resolved.

douconca 1.1.5

• The package can now do general dc-CA, instead of the vegan-based version with equal site weights only. For users of the previous version, the function dc_CA_vegan has been replaced by the more general function dc_CA. The default gives the same analysis. By specifying the argument divideBySiteTotals = FALSE, obtain the original dc-CA analysis with unequal site weights.
• The plot_dcCA function is now a method: plot.
• General dc-CA required weighted redundancy analysis. For this, a new function wrda has been added, with methods for print, scores and anova.
• A predict function has been added.
• A dc-CA can be computed from community-weighted means (CWMs) with trait and environment data with species and site weights. See the new function fCWM_SNC. This is of interest, for example, to make a dc-CA analysis reproducible when the abundance data cannot be made public, and it may also allow to perform dcCA with intra-species trait variation. The user needs to be able to compute meaningful CWMs in this case and supply trait data that reflect the (species-weighted) inter-trait covariance.
• Several functions are updated. In particular, there are corrections to the anova function.

douconca 1.1.2

• The scores.dccav function is corrected concerning intra-set correlations for traits and environmental variables.
• The plotting functions are updated to avoid ggplot2 warnings on color and size.
• The fitted straight lines in the plots use the implicit weights (they did already, but the help said they did not).