{ "_id": "6a12a92facfb0bcc41d15b19", "Package": "douconca", "Type": "Package", "Title": "Double Constrained Correspondence Analysis for Trait-Environment\nAnalysis in Ecology", "Version": "1.2.5", "Date": "2026-02-23", "Authors@R": "c(person(given = \"Cajo J.F\", \nfamily = \"ter Braak\",\nemail = \"cajo.terbraak@wur.nl\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0002-0414-8745\")),\nperson(given = \"Bart-Jan\",\nfamily = \"van Rossum\",\nemail = \"bart-jan.vanrossum@wur.nl\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-8673-2514\")))", "Description": "Double constrained correspondence analysis (dc-CA)\nanalyzes (multi-)trait (multi-)environment ecological data by\nusing the 'vegan' package and native R code. Throughout the two\nstep algorithm of ter Braak et al. (2018) is used. This\nalgorithm combines and extends community- (sample-) and\nspecies-level analyses, i.e. the usual community weighted means\n(CWM)-based regression analysis and the species-level analysis\nof species-niche centroids (SNC)-based regression analysis. The\ntwo steps use canonical correspondence analysis to regress the\nabundance data on to the traits and (weighted) redundancy\nanalysis to regress the CWM of the orthonormalized traits on to\nthe environmental predictors. The function dc_CA() has an\noption to divide the abundance data of a site by the site\ntotal, giving equal site weights. This division has the\nadvantage that the multivariate analysis corresponds with an\nunweighted (multi-trait) community-level analysis, instead of\nbeing weighted. The first step of the algorithm uses\nvegan::cca(). The second step uses wrda() but vegan::rda() if\nthe site weights are equal. This version has a predict()\nfunction. For details see ter Braak et al. 2018\n. and ter Braak & van Rossum\n2025 .", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.3.3", "NeedsCompilation": "no", "VignetteBuilder": "knitr", "URL": "https://zenodo.org/records/13970152,\nhttps://github.com/Biometris/douconca", "BugReports": "https://github.com/Biometris/douconca/issues", "Repository": "https://biometris.r-universe.dev", "Date/Publication": "2026-02-23 12:48:12 UTC", "RemoteUrl": "https://github.com/biometris/douconca", "RemoteRef": "HEAD", "RemoteSha": "b56e98d23c3c52d872a7a03fb150dd97196015b6", "Packaged": { "Date": "2026-05-24 07:25:01 UTC", "User": "root" }, "Author": "Cajo J.F ter Braak [aut] (ORCID:\n),\nBart-Jan van Rossum [aut, cre] (ORCID:\n)", "Maintainer": "Bart-Jan van Rossum ", "MD5sum": "6ca68af1597461e1181d24356d65884f", "_user": "biometris", "_type": "src", "_file": "douconca_1.2.5.tar.gz", "_fileid": "f9d024e403144529bda3859690dcbe0a7a45c5de91a559eb94bdfcc8487257db", 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"ggplot2", "version": ">= 3.5.1", "role": "Imports" }, { "package": "ggrepel", "role": "Imports" }, { "package": "gridExtra", "role": "Imports" }, { "package": "permute", "role": "Imports" }, { "package": "rlang", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "vegan", "version": ">= 2.6-8", "role": "Imports" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "tinytest", "role": "Suggests" } ], "_owner": "biometris", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2025-42", "n": 3 }, { "week": "2026-09", "n": 4 } ], "_tags": [ { "name": "v.1.2.4", "date": "2025-10-14" }, { "name": "v.1.2.5", "date": "2026-02-23" } ], "_topics": [ "correspondence-analysis", "ecology", "ecology-modeling", "multi-environment", "multi-trait" ], "_stars": 0, "_contributors": [ { "user": "bartjanvanrossum", "count": 99, "uuid": 28725410 }, { "user": "cajoterbraak", "count": 89, "uuid": 12693502 } ], "_userbio": 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double-constrained correspondence analysis (dc-CA)", "topics": [ "fitted.dcca" ] }, { "page": "fN2", "title": "Hill number of order 2: N2", "topics": [ "fN2" ] }, { "page": "FS", "title": "Default forward selection function.", "topics": [ "FS" ] }, { "page": "FS.dcca", "title": "Forward selection of traits or environmental variables using dc-CA.", "topics": [ "FS.dcca" ] }, { "page": "FS.wrda", "title": "Forward selection of predictor variables using wrda or cca0", "topics": [ "FS.wrda" ] }, { "page": "getPlotdata", "title": "Utility function: extracting data from a 'dc_CA' object for plotting a single axis by your own code or 'plot.dcca'.", "topics": [ "getPlotdata" ] }, { "page": "ipf2N2", "title": "Iterative proportional fitting of an abundance table to Hill-N2 marginals", "topics": [ "ipf2N2" ] }, { "page": "plot_dcCA_CWM_SNC", "title": "Plot the CWMs and SNCs of a single dc-CA axis.", "topics": [ "plot_dcCA_CWM_SNC" ] }, { "page": "plot_species_scores_bk", "title": "Vertical 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