NEWS

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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.

douconca 1.2.1 (2024-09-25)

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

douconca 1.2.0 (2024-09-13)

• 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 For users of the previous version, the function dc_CA_vegan has been replaced by the more general function dc_CA.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).