{"id":648,"date":"2012-04-09T17:39:15","date_gmt":"2012-04-09T17:39:15","guid":{"rendered":"http:\/\/www.agron.iastate.edu\/glsi\/?p=648"},"modified":"2025-09-29T04:35:35","modified_gmt":"2025-09-29T09:35:35","slug":"a-taxonomically-based-ordinal-estimate-of-soil-productivity-for-landscape-scale-analyses","status":"publish","type":"post","link":"https:\/\/www.agron.iastate.edu\/glsi\/manuscripts\/a-taxonomically-based-ordinal-estimate-of-soil-productivity-for-landscape-scale-analyses\/","title":{"rendered":"A Taxonomically Based, Ordinal Estimate of Soil Productivity for Landscape-Scale Analyses"},"content":{"rendered":"
\n

In this article, we introduce, evaluate, and apply a new ordinally based soil Productivity Index (PI). The PI uses family-level Soil Taxonomy information, that is, interpretations of features or properties, recognized in Soil Taxonomy, that tend to be associated with low or high soil productivity, to rank soils from 0 (least productive) to 19 (most productive). The index has a wide application generally at landscape scales. Unlike competing indexes, it does not require copious amounts of soil data, for example, pH, organic matter, or cation exchange capacity, in its derivation. Geographic information system applications of the PI, in particular, have great potential. Results confirmed that for 1,000 sites in southern Michigan, the mean PI of cultivated sites is significantly higher (10.94) than that of forested sites (7.77). We also compared the PI with published productivity values for Illinois soils. The positive statistical correlations that resulted confirmed that the PI is an effective measure of productivity for areas that do not have robust productivity data or a wealth of local soil knowledge, as does Illinois. Last, 2009 crop yield data for 11 Midwestern states were used to further evaluate the PI. In a geographic information system, we determined the soils and crops in particular fields and thus were able to ascertain the mean PI value per soil, per crop, per county. Statewide summaries of these data produced statistical correlations among yields of specific crops and PI values that were all positive; many exceeded 0.60. For regionally extensive applications, the PI may be as useful and robust as other indexes that have much more exacting data requirements.<\/p>\n<\/div><\/div>\n\n

\n

Schaetzl, R.J., F.J. Krist Jr., and B.A. Miller. 2012. A taxonomically based, ordinal estimate of soil productivity for landscape-scale analyses. Soil Science 177(4):288-299. doi:10.1097\/SS.0b013e3182446c88.<\/a><\/p>\n<\/div><\/div>\n\n

\n

<\/p>\n<\/div><\/div>","protected":false},"excerpt":{"rendered":"

We introduce, evaluate, and apply a new ordinally based soil Productivity Index (PI). The index has a wide application generally at landscape scales. Unlike competing indexes, it does not require copious amounts of soil data, for example, pH, organic matter, or cation exchange capacity, in its derivation. Geographic information system applications of the PI, in particular, have great potential. For regionally extensive applications, the PI may be as useful and robust as other indexes that have much more exacting data requirements.<\/p>\n","protected":false},"author":3216,"featured_media":10947,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"ngg_post_thumbnail":0,"footnotes":""},"categories":[5,7],"tags":[27,49,57,100,105,118,121,125,142],"class_list":["post-648","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-manuscripts","category-miller","tag-crop-yield","tag-gis","tag-index","tag-productivity-index","tag-regional","tag-soil-fertility","tag-soil-maps","tag-soil-taxonomy","tag-usa"],"acf":[],"featured_image_urls_v2":{"full":["https:\/\/www.agron.iastate.edu\/glsi\/files\/2012\/04\/A-taxonomically-based-ordinal-estimate-of-soil-productivity.png",991,905,false],"thumbnail":["https:\/\/www.agron.iastate.edu\/glsi\/files\/2012\/04\/A-taxonomically-based-ordinal-estimate-of-soil-productivity-150x150.png",150,150,true],"medium":["https:\/\/www.agron.iastate.edu\/glsi\/files\/2012\/04\/A-taxonomically-based-ordinal-estimate-of-soil-productivity-300x274.png",300,274,true],"medium_large":["https:\/\/www.agron.iastate.edu\/glsi\/files\/2012\/04\/A-taxonomically-based-ordinal-estimate-of-soil-productivity-768x701.png",768,701,true],"large":["https:\/\/www.agron.iastate.edu\/glsi\/files\/2012\/04\/A-taxonomically-based-ordinal-estimate-of-soil-productivity.png",991,905,false],"1536x1536":["https:\/\/www.agron.iastate.edu\/glsi\/files\/2012\/04\/A-taxonomically-based-ordinal-estimate-of-soil-productivity.png",991,905,false],"2048x2048":["https:\/\/www.agron.iastate.edu\/glsi\/files\/2012\/04\/A-taxonomically-based-ordinal-estimate-of-soil-productivity.png",991,905,false]},"post_excerpt_stackable_v2":"

We introduce, evaluate, and apply a new ordinally based soil Productivity Index (PI). The index has a wide application generally at landscape scales. Unlike competing indexes, it does not require copious amounts of soil data, for example, pH, organic matter, or cation exchange capacity, in its derivation. Geographic information system applications of the PI, in particular, have great potential. For regionally extensive applications, the PI may be as useful and robust as other indexes that have much more exacting data requirements.<\/p>\n","category_list_v2":"Manuscripts<\/a>, Miller<\/a>","author_info_v2":{"name":"Bradley Miller","url":"https:\/\/www.agron.iastate.edu\/glsi\/author\/millerba\/"},"comments_num_v2":"0 comments","yoast_head":"\nA Taxonomically Based, Ordinal Estimate of Soil Productivity for Landscape-Scale Analyses - Geospatial Laboratory for Soil Informatics<\/title>\n<meta name=\"description\" content=\"We introduce a new soil Productivity Index (PI) that requires less data than competing indexes, showing promise for landscape-scale applications in GIS.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.agron.iastate.edu\/glsi\/manuscripts\/a-taxonomically-based-ordinal-estimate-of-soil-productivity-for-landscape-scale-analyses\/\" \/>\n<meta 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