[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-657488-105":59,"doc-detail-657488-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","unconstrained-ordination-ordination-diagrams-theory-r-functions-examples-exercise","Unconstrained ordination - Ordination diagrams - Theory R functions examples exercise","","Unconstrained ordination focuses on creating ordination diagrams using R for DCA (detrended correspondence analysis) results from Vltava data. It provides R code and explanations for reading vegetation and environmental tables, computing DCA, and visualizing ordination via ordiplot. The document details how to draw sites, species, and labels, add labeled “stickers,” customize points by group classifications, and enhance plots with ordihull envelopes, ordispider spiders, and transparent polygons. It also introduces ordicenter for labeling group centroids with optional scaling by sample counts and colored labels.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":30,"@type":76,"position":81},"https://docshare.wps.com/document/technology/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/unconstrained-ordination-ordination-diagrams-theory-r-functions-examples-exercise/657488/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/unconstrained-ordination-ordination-diagrams-theory-r-functions-examples-exercise/657488.png","ImageObject",300,407,{"name":92,"@type":93},"miraaa_2004","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-28","2026-10-26",true,{"@type":102,"interactionType":103,"userInteractionCount":14},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"How is DCA computed from the Vltava vegetation data in this document?","Question",{"text":112,"@type":113},"The document reads the vegetation data, applies log1p to it, and then runs DCA using deco rana with the prepared veg matrix.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How can labels be added to an ordination diagram without overlap?",{"text":117,"@type":113},"It first draws an empty diagram with ordiplot using type = 'n' and then adds readable labels using orditorp (or ordilabel for sticker-like labels).",{"name":119,"@type":110,"acceptedAnswer":120},"What are ordihull and ordispider used for in the diagrams?",{"text":121,"@type":113},"ordihull draws envelopes around groups of samples, while ordispider connects each sample to the centroid of its group. The document also shows how to add centroid labels (label = T) within these visualizations.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},657488,1793051279,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":29,"category_name":30,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":81,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},962094249165,"https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0","Unconstrained ordination  \nOrdination diagrams  \nTheory R functions Examples Exercise   \nThe following plotting functions are using results of DCA (detrended correspondence analysis) of Vltava data:  \n[veg.](veg.data)[data](veg.data) \u003C- read.delim  \n('[http://www.davidzeleny.net/anadat-r/data-download/vltava-spe.txt](http://www.davidzeleny.net/anadat-r/data-download/vltava-spe.txt) ', row.names = 1) [env.](env.data)[data](env.data) \u003C- read .delim  \n('[http://www.davidzeleny.net/anadat-r/data-download/vltava-env.txt](http://www.davidzeleny.net/anadat-r/data-download/vltava-env.txt) ')  \nlibrary (vegan )  \nDCA \u003C- deco rana (veg = log1p ([veg.](veg.data)[data](veg.data)))  \nordiplot (library vegan)  \nDraws ordination diagrams.  \nordiplot (DCA, display = 'sites' , type = 'p' )  \nordiplot (DCA, display = 'species' , type = 't' )  \norditorp (library vegan)  \nAdds the labels onto an ordination diagram, so as they can be read (and don't overlap) . First, draw empty diagram using function ordiplot and argument type = 'n' . Then add the labels using function ordito rp.  \nordiplot (DCA, display = 'sp' , type = 'n' ) orditorp (DCA, display = 'sp' )  \nordilabel (library vegan)  \nAdds the labels which looks like stickers:  \nordiplot (DCA, display = 'sp' , type = 'n' ) ordilabel (DCA, display = 'sp' )  \nOther options: identify .ordiplot (adding the labels onto diagram by clicking the mouse), orditklabel (interactive diagrams in tcltk interface, but still not too elegant) .  \npoints (library vegan)  \nAdds points to ordination diagram-you can control their color, symbol, size etc. The following examples use the classification of samples (done by cluster analysis) into four groups, which is stored in variable GROUP in[env.data](env.data) data frame. First, draw empty ordination diagram (argument type = 'n' in function ordiplot) and add colourful points according to [env.data$GROUP](env.data$GROUP variable)[ variable](env.data$GROUP variable) using function points:  \nordiplot (DCA, display = 'si' , type = 'n' )  \npoints (DCA, [col](col = env.data$GROUP)[ =](col = env.data$GROUP)[ env.](col = env.data$GROUP)[data](col = env.data$GROUP)[$GROUP](col = env.data$GROUP) , [pch](pch = env.data$GROUP)[ =](pch = env.data$GROUP)[ env.](pch = env.data$GROUP)[data](pch = env.data$GROUP)[$GROUP](pch = env.data$GROUP) )  \nordispider and ordihull (library vegan)  \nFunction ordihull adds envelopes around groups of samples, while function ordispider adds so called spiders, connecting each sample with the centroid of particular group. Argument label = T draws the labels into the centroid of each spider:  \nordiplot (DCA, display = 'si' , type = 'n' )  \nfor (i in seq (1, 4)) ordispider (DCA, [groups](groups = env.data$GROUP)[ =](groups = env.data$GROUP)[ env.](groups = env.data$GROUP)[data](groups = env.data$GROUP)[$GROUP](groups = env.data$GROUP), show.groups = i, col = i, label = T )  \nfor (i in seq (1, 4)) ordihull (DCA, [groups](groups = env.data$GROUP)[ =](groups = env.data$GROUP)[ env.](groups = env.data$GROUP)[data](groups = env.data$GROUP)[$GROUP](groups = env.data$GROUP), show.groups = i, col = i, lty = 'dotted' )  \nFunction ordihull can draw not only envelopes, but also transparent polygons, by modifying the argument draw = “polygon” and optionally also transparency by argument alpha (default alpha = 127 means that polygons will be semitransparent):  \nordiplot (DCA, display = 'si' , type = 'n' )  \npoints (DCA, [col](col = env.data$GROUP)[ =](col = env.data$GROUP)[ env.](col = env.data$GROUP)[data](col = env.data$GROUP)[$GROUP](col = env.data$GROUP) , [pch](pch = env.data$GROUP)[ =](pch = env.data$GROUP)[ env.](pch = env.data$GROUP)[data](pch = env.data$GROUP)[$GROUP](pch = env.data$GROUP))  \nfor (i in unique ([env.](env.data$GROUP)[data](env.data$GROUP)[$GROUP](env.data$GROUP))) ordihull (DCA, [groups](groups = env.data$GROUP)[ =](groups = env.data$GROUP)[ env.](groups = env.data$GROUP)[data](groups = env.data$GROUP)[$GROUP](groups = env.data$GROUP) , [sho","cbCaiiZJtuwBlzUg","https://ap.wps.com/l/cbCaiiZJtuwBlzUg","pdf",367696,15,"English","# Unconstrained ordination\n## Ordination diagrams overview\n## Loading Vltava data and computing DCA\n## ordiplot: sites, species, and unlabeled diagrams\n## Adding labels: orditorp and ordilabel\n## Adding grouped points and styling\n## ordihull and ordispider: envelopes and spiders\n## Transparent polygons with ordihull\n## ordicenter: labeling group centroids","[{\"question\":\"How is DCA computed from the Vltava vegetation data in this document?\",\"answer\":\"The document reads the vegetation data, applies log1p to it, and then runs DCA using deco rana with the prepared veg matrix.\"},{\"question\":\"How can labels be added to an ordination diagram without overlap?\",\"answer\":\"It first draws an empty diagram with ordiplot using type = 'n' and then adds readable labels using orditorp (or ordilabel for sticker-like labels).\"},{\"question\":\"What are ordihull and ordispider used for in the diagrams?\",\"answer\":\"ordihull draws envelopes around groups of samples, while ordispider connects each sample to the centroid of its group. The document also shows how to add centroid labels (label = T) within these visualizations.\"}]","Unconstrained ordination - Ordination diagrams - Theory R functions examples exercise | PDF",1792980992,38]