{"id":505,"date":"2015-10-09T16:43:36","date_gmt":"2015-10-09T16:43:36","guid":{"rendered":"http:\/\/www.agron.iastate.edu\/glsi\/?p=505"},"modified":"2025-09-27T07:30:54","modified_gmt":"2025-09-27T12:30:54","slug":"spatial-modeling-of-organic-carbon-in-degraded-peatland-soils-of-northeast-germany","status":"publish","type":"post","link":"https:\/\/www.agron.iastate.edu\/glsi\/manuscripts\/spatial-modeling-of-organic-carbon-in-degraded-peatland-soils-of-northeast-germany\/","title":{"rendered":"Spatial Modeling of Organic Carbon in Degraded Peatland Soils of Northeast Germany"},"content":{"rendered":"<div class=\"paragraph-widget paragraph-widget--text-html\"><div class=\"text-content\">\n<p>Spatial variation of carbon stocks within peatlands is an overall challenge for monitoring global carbon cycle processes, which is critical for responding to climate change induced by greenhouse gases. The objective of this study was to evaluate the ability of high-resolution, minimally invasive sensor data to predict spatial variation of soil organic carbon stocks within highly degraded peatland soils in northeast Germany. Within the Rhin-Havelluch, a paludification mire that has been cultivated and drained for about 300 years, seven fields were sampled by soil cores up to 2 m in depth, nine points for each field. Soil horizons were examined for dry bulk density, soil organic carbon content, and thickness to calculate soil organic carbon stocks and to test for relationships with overall peat thickness, elevation, and electrical conductivity (ECa). Elevation was determined by LiDAR and electrical conductivity by an EM38DD, both producing maps of high resolution (1 m).<\/p>\n<\/div><\/div>\n\n<div class=\"paragraph-widget paragraph-widget--text-html\"><div class=\"text-content\">\n<p>Soil organic carbon density (SOC<sub>d<\/sub>) was related to elevation, electrical conductivity, and peat thickness. Based on these relationships, maps of SOC<sub>d<\/sub> were produced. Within field variation of SOC<sub>d<\/sub> was high, which could be modeled by the use of the covariate maps. If available, ECa maps can improve the prediction of SOC<sub>d<\/sub> based on elevation. Modeling peat thickness based on sensor data needs additional research, but seems to be a valuable covariate in digital soil mapping.<\/p>\n<\/div><\/div>\n\n<div class=\"paragraph-widget paragraph-widget--text-html\"><div class=\"text-content\">\n<p><\/p>\n<\/div><\/div>\n\n<div class=\"paragraph-widget paragraph-widget--text-html\"><div class=\"text-content\">\n<p>Koszinski, S., B.A. Miller, W. Hierold, H. Haelbich, and M. Sommer. 2015. Organic carbon stocks in degraded peatland soils of northeast Germany in relation to elevation, electrical conductivity, and peat thickness. <a title=\"Soil Science Society of America Journal\" href=\"https:\/\/dl.sciencesocieties.org\/publications\/sssaj\/abstracts\/79\/5\/1496\" target=\"_blank\" rel=\"noopener noreferrer\">Soil Science Society of America Journal 79(5):1496-1508. doi: 10.2136\/sssaj2015.01.0019.<\/a><\/p>\n<\/div><\/div>\n\n<div class=\"paragraph-widget paragraph-widget--text-html\"><div class=\"text-content\">\n<p><\/p>\n<\/div><\/div>","protected":false},"excerpt":{"rendered":"<p>The objective of this study was to evaluate the ability of high-resolution, minimally invasive sensor data to predict spatial variation of soil organic carbon stocks within highly degraded peatland soils in northeast Germany. Soil organic carbon density was related to elevation, electrical conductivity, and peat thickness. Modeling peat thickness based on sensor data needs additional research, but seems to be a valuable set of covariates in digital soil mapping.<\/p>\n","protected":false},"author":3216,"featured_media":4257,"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":[19,34,39,48,66,89,116],"class_list":["post-505","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-manuscripts","category-miller","tag-carbon","tag-digital-soil-mapping","tag-eca","tag-germany","tag-lidar","tag-peatland","tag-soc"],"acf":[],"featured_image_urls_v2":{"full":["https:\/\/www.agron.iastate.edu\/glsi\/files\/2015\/10\/Paulinenau-thumb-1.jpg",220,200,false],"thumbnail":["https:\/\/www.agron.iastate.edu\/glsi\/files\/2015\/10\/Paulinenau-thumb-1-150x150.jpg",150,150,true],"medium":["https:\/\/www.agron.iastate.edu\/glsi\/files\/2015\/10\/Paulinenau-thumb-1.jpg",220,200,false],"medium_large":["https:\/\/www.agron.iastate.edu\/glsi\/files\/2015\/10\/Paulinenau-thumb-1.jpg",220,200,false],"large":["https:\/\/www.agron.iastate.edu\/glsi\/files\/2015\/10\/Paulinenau-thumb-1.jpg",220,200,false],"1536x1536":["https:\/\/www.agron.iastate.edu\/glsi\/files\/2015\/10\/Paulinenau-thumb-1.jpg",220,200,false],"2048x2048":["https:\/\/www.agron.iastate.edu\/glsi\/files\/2015\/10\/Paulinenau-thumb-1.jpg",220,200,false]},"post_excerpt_stackable_v2":"<p>The objective of this study was to evaluate the ability of high-resolution, minimally invasive sensor data to predict spatial variation of soil organic carbon stocks within highly degraded peatland soils in northeast Germany. Soil organic carbon density was related to elevation, electrical conductivity, and peat thickness. Modeling peat thickness based on sensor data needs additional research, but seems to be a valuable set of covariates in digital soil mapping.<\/p>\n","category_list_v2":"<a href=\"https:\/\/www.agron.iastate.edu\/glsi\/category\/manuscripts\/\" rel=\"category tag\">Manuscripts<\/a>, <a href=\"https:\/\/www.agron.iastate.edu\/glsi\/category\/miller\/\" rel=\"category tag\">Miller<\/a>","author_info_v2":{"name":"Bradley Miller","url":"https:\/\/www.agron.iastate.edu\/glsi\/author\/millerba\/"},"comments_num_v2":"0 comments","yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Spatial Modeling of Organic Carbon in Degraded Peatland Soils of Northeast Germany - Geospatial Laboratory for Soil Informatics<\/title>\n<meta name=\"description\" content=\"Soil organic carbon density (SOCd) was related to elevation, electrical conductivity, and peat thickness. Based on these relationships, maps of SOCd were produced. Within field variation of SOCd was high, which could be modeled by the use of the covariate maps. If available, ECa maps can improve the prediction of SOCd based on elevation. Modeling peat thickness based on sensor data needs additional research, but seems to be a valuable covariate in digital soil mapping.\" \/>\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\/spatial-modeling-of-organic-carbon-in-degraded-peatland-soils-of-northeast-germany\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Spatial Modeling of Organic Carbon in Degraded Peatland Soils of Northeast Germany - Geospatial Laboratory for Soil Informatics\" \/>\n<meta property=\"og:description\" content=\"Soil organic carbon density (SOCd) was related to elevation, electrical conductivity, and peat thickness. Based on these relationships, maps of SOCd were produced. Within field variation of SOCd was high, which could be modeled by the use of the covariate maps. If available, ECa maps can improve the prediction of SOCd based on elevation. Modeling peat thickness based on sensor data needs additional research, but seems to be a valuable covariate in digital soil mapping.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.agron.iastate.edu\/glsi\/manuscripts\/spatial-modeling-of-organic-carbon-in-degraded-peatland-soils-of-northeast-germany\/\" \/>\n<meta property=\"og:site_name\" content=\"Geospatial Laboratory for Soil Informatics\" \/>\n<meta property=\"article:published_time\" content=\"2015-10-09T16:43:36+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-09-27T12:30:54+00:00\" \/>\n<meta name=\"author\" content=\"Bradley Miller\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:image\" content=\"http:\/\/www.agron.iastate.edu\/glsi\/files\/2015\/10\/Paulinenau-thumb.jpg\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Bradley Miller\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.agron.iastate.edu\\\/glsi\\\/manuscripts\\\/spatial-modeling-of-organic-carbon-in-degraded-peatland-soils-of-northeast-germany\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.agron.iastate.edu\\\/glsi\\\/manuscripts\\\/spatial-modeling-of-organic-carbon-in-degraded-peatland-soils-of-northeast-germany\\\/\"},\"author\":{\"name\":\"Bradley Miller\",\"@id\":\"https:\\\/\\\/www.agron.iastate.edu\\\/glsi\\\/#\\\/schema\\\/person\\\/a96fa0c818314fce5f3928c232490277\"},\"headline\":\"Spatial Modeling of Organic Carbon in Degraded Peatland Soils of Northeast Germany\",\"datePublished\":\"2015-10-09T16:43:36+00:00\",\"dateModified\":\"2025-09-27T12:30:54+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.agron.iastate.edu\\\/glsi\\\/manuscripts\\\/spatial-modeling-of-organic-carbon-in-degraded-peatland-soils-of-northeast-germany\\\/\"},\"wordCount\":274,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\\\/\\\/www.agron.iastate.edu\\\/glsi\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/www.agron.iastate.edu\\\/glsi\\\/manuscripts\\\/spatial-modeling-of-organic-carbon-in-degraded-peatland-soils-of-northeast-germany\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.agron.iastate.edu\\\/glsi\\\/files\\\/2015\\\/10\\\/Paulinenau-thumb-1.jpg\",\"keywords\":[\"carbon\",\"Digital Soil Mapping\",\"ECa\",\"Germany\",\"LiDAR\",\"peatland\",\"SOC\"],\"articleSection\":[\"Manuscripts\",\"Miller\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\\\/\\\/www.agron.iastate.edu\\\/glsi\\\/manuscripts\\\/spatial-modeling-of-organic-carbon-in-degraded-peatland-soils-of-northeast-germany\\\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.agron.iastate.edu\\\/glsi\\\/manuscripts\\\/spatial-modeling-of-organic-carbon-in-degraded-peatland-soils-of-northeast-germany\\\/\",\"url\":\"https:\\\/\\\/www.agron.iastate.edu\\\/glsi\\\/manuscripts\\\/spatial-modeling-of-organic-carbon-in-degraded-peatland-soils-of-northeast-germany\\\/\",\"name\":\"Spatial Modeling of Organic Carbon in Degraded Peatland Soils of Northeast Germany - Geospatial Laboratory for Soil Informatics\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.agron.iastate.edu\\\/glsi\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/www.agron.iastate.edu\\\/glsi\\\/manuscripts\\\/spatial-modeling-of-organic-carbon-in-degraded-peatland-soils-of-northeast-germany\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/www.agron.iastate.edu\\\/glsi\\\/manuscripts\\\/spatial-modeling-of-organic-carbon-in-degraded-peatland-soils-of-northeast-germany\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.agron.iastate.edu\\\/glsi\\\/files\\\/2015\\\/10\\\/Paulinenau-thumb-1.jpg\",\"datePublished\":\"2015-10-09T16:43:36+00:00\",\"dateModified\":\"2025-09-27T12:30:54+00:00\",\"description\":\"Soil organic carbon density (SOCd) was related to elevation, electrical conductivity, and peat thickness. 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Based on these relationships, maps of SOCd were produced. Within field variation of SOCd was high, which could be modeled by the use of the covariate maps. If available, ECa maps can improve the prediction of SOCd based on elevation. 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