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Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe

Accuracy in assessing the distribution of soil organic carbon (SOC) is an important issue because of playing key roles in the functions of both natural ecosystems and agricultural systems. There are several studies in the literature with the aim of finding the best method to assess and map the distr...

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Autores principales: Aksoy, Ece, Yigini, Yusuf, Montanarella, Luca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4806992/
https://www.ncbi.nlm.nih.gov/pubmed/27011357
http://dx.doi.org/10.1371/journal.pone.0152098
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author Aksoy, Ece
Yigini, Yusuf
Montanarella, Luca
author_facet Aksoy, Ece
Yigini, Yusuf
Montanarella, Luca
author_sort Aksoy, Ece
collection PubMed
description Accuracy in assessing the distribution of soil organic carbon (SOC) is an important issue because of playing key roles in the functions of both natural ecosystems and agricultural systems. There are several studies in the literature with the aim of finding the best method to assess and map the distribution of SOC content for Europe. Therefore this study aims searching for another aspect of this issue by looking to the performances of using aggregated soil samples coming from different studies and land-uses. The total number of the soil samples in this study was 23,835 and they’re collected from the “Land Use/Cover Area frame Statistical Survey” (LUCAS) Project (samples from agricultural soil), BioSoil Project (samples from forest soil), and “Soil Transformations in European Catchments” (SoilTrEC) Project (samples from local soil data coming from six different critical zone observatories (CZOs) in Europe). Moreover, 15 spatial indicators (slope, aspect, elevation, compound topographic index (CTI), CORINE land-cover classification, parent material, texture, world reference base (WRB) soil classification, geological formations, annual average temperature, min-max temperature, total precipitation and average precipitation (for years 1960–1990 and 2000–2010)) were used as auxiliary variables in this prediction. One of the most popular geostatistical techniques, Regression-Kriging (RK), was applied to build the model and assess the distribution of SOC. This study showed that, even though RK method was appropriate for successful SOC mapping, using combined databases was not helpful to increase the statistical significance of the method results for assessing the SOC distribution. According to our results; SOC variation was mainly affected by elevation, slope, CTI, average temperature, average and total precipitation, texture, WRB and CORINE variables for Europe scale in our model. Moreover, the highest average SOC contents were found in the wetland areas; agricultural areas have much lower soil organic carbon content than forest and semi natural areas; Ireland, Sweden and Finland has the highest SOC, on the contrary, Portugal, Poland, Hungary, Spain, Italy have the lowest values with the average 3%.
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spelling pubmed-48069922016-03-25 Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe Aksoy, Ece Yigini, Yusuf Montanarella, Luca PLoS One Research Article Accuracy in assessing the distribution of soil organic carbon (SOC) is an important issue because of playing key roles in the functions of both natural ecosystems and agricultural systems. There are several studies in the literature with the aim of finding the best method to assess and map the distribution of SOC content for Europe. Therefore this study aims searching for another aspect of this issue by looking to the performances of using aggregated soil samples coming from different studies and land-uses. The total number of the soil samples in this study was 23,835 and they’re collected from the “Land Use/Cover Area frame Statistical Survey” (LUCAS) Project (samples from agricultural soil), BioSoil Project (samples from forest soil), and “Soil Transformations in European Catchments” (SoilTrEC) Project (samples from local soil data coming from six different critical zone observatories (CZOs) in Europe). Moreover, 15 spatial indicators (slope, aspect, elevation, compound topographic index (CTI), CORINE land-cover classification, parent material, texture, world reference base (WRB) soil classification, geological formations, annual average temperature, min-max temperature, total precipitation and average precipitation (for years 1960–1990 and 2000–2010)) were used as auxiliary variables in this prediction. One of the most popular geostatistical techniques, Regression-Kriging (RK), was applied to build the model and assess the distribution of SOC. This study showed that, even though RK method was appropriate for successful SOC mapping, using combined databases was not helpful to increase the statistical significance of the method results for assessing the SOC distribution. According to our results; SOC variation was mainly affected by elevation, slope, CTI, average temperature, average and total precipitation, texture, WRB and CORINE variables for Europe scale in our model. Moreover, the highest average SOC contents were found in the wetland areas; agricultural areas have much lower soil organic carbon content than forest and semi natural areas; Ireland, Sweden and Finland has the highest SOC, on the contrary, Portugal, Poland, Hungary, Spain, Italy have the lowest values with the average 3%. Public Library of Science 2016-03-24 /pmc/articles/PMC4806992/ /pubmed/27011357 http://dx.doi.org/10.1371/journal.pone.0152098 Text en © 2016 Aksoy et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Aksoy, Ece
Yigini, Yusuf
Montanarella, Luca
Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe
title Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe
title_full Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe
title_fullStr Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe
title_full_unstemmed Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe
title_short Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe
title_sort combining soil databases for topsoil organic carbon mapping in europe
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4806992/
https://www.ncbi.nlm.nih.gov/pubmed/27011357
http://dx.doi.org/10.1371/journal.pone.0152098
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