Predicting long-term organic carbon dynamics in organically amended soils using the CQESTR model

Purpose: The CQESTR model is a process-based C model recently developed to simulate soil organic matter (SOM) dynamics and uses readily available or easily measurable input parameters. The current version of CQESTR (v. 2.0) has been validated successfully with a number of datasets from agricultural sites in North America but still needs to be tested in other geographic areas and soil types under diverse organic management systems. Materials and methods: We evaluated the predictive performance of CQESTR to simulate long-term (34 years) soil organic C (SOC) changes in a SOM-depleted European soil either unamended or amended with solid manure, liquid manure, or crop residue. Results and discussion: Measured SOC levels declined over the study period in the unamended soil, remained constant in the soil amended with crop residues, and tended to increase in the soils amended with manure, especially with solid manure. Linear regression analysis of measured SOC contents and CQESTR predictions resulted in a correlation coefficient of 0.626 (P < 0.001) and a slope and an intercept not significantly different from 1 and 0, respectively (95% confidence level). The mean squared deviation and root mean square error were relatively small. Simulated values fell within the 95% confidence interval of the measured SOC, and predicted errors were mainly associated with data scattering. Conclusions: The CQESTR model was shown to predict, with a reasonable degree of accuracy, the organic C dynamics in the soils examined. The CQESTR performance, however, could be improved by adding an additional parameter to differentiate between pre-decomposed organic amendments with varying degrees of stability. © 2012 Springer-Verlag (outside the USA).

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Main Authors: Plaza de Carlos, César, Gollany, Hero T., Baldoni, Guido, Polo, Alfredo, Ciavatta, Claudio
Format: artículo biblioteca
Published: 2012-04-01
Subjects:C sequestration | Crop residue | Manure | Modeling | Organic amendment | Soil organic matter,
Online Access:http://hdl.handle.net/10261/330296
https://digital.csic.es/handle/10261/236614
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spelling dig-ica-es-10261-3302962024-05-17T21:04:12Z Predicting long-term organic carbon dynamics in organically amended soils using the CQESTR model Plaza de Carlos, César Gollany, Hero T. Baldoni, Guido Polo, Alfredo Ciavatta, Claudio C sequestration | Crop residue | Manure | Modeling | Organic amendment | Soil organic matter Purpose: The CQESTR model is a process-based C model recently developed to simulate soil organic matter (SOM) dynamics and uses readily available or easily measurable input parameters. The current version of CQESTR (v. 2.0) has been validated successfully with a number of datasets from agricultural sites in North America but still needs to be tested in other geographic areas and soil types under diverse organic management systems. Materials and methods: We evaluated the predictive performance of CQESTR to simulate long-term (34 years) soil organic C (SOC) changes in a SOM-depleted European soil either unamended or amended with solid manure, liquid manure, or crop residue. Results and discussion: Measured SOC levels declined over the study period in the unamended soil, remained constant in the soil amended with crop residues, and tended to increase in the soils amended with manure, especially with solid manure. Linear regression analysis of measured SOC contents and CQESTR predictions resulted in a correlation coefficient of 0.626 (P < 0.001) and a slope and an intercept not significantly different from 1 and 0, respectively (95% confidence level). The mean squared deviation and root mean square error were relatively small. Simulated values fell within the 95% confidence interval of the measured SOC, and predicted errors were mainly associated with data scattering. Conclusions: The CQESTR model was shown to predict, with a reasonable degree of accuracy, the organic C dynamics in the soils examined. The CQESTR performance, however, could be improved by adding an additional parameter to differentiate between pre-decomposed organic amendments with varying degrees of stability. © 2012 Springer-Verlag (outside the USA). Peer reviewed 2023-07-04T05:24:11Z 2023-07-04T05:24:11Z 2012-04-01 artículo http://purl.org/coar/resource_type/c_6501 14390108 http://hdl.handle.net/10261/330296 10.1007/s11368-012-0477-1 2-s2.0-84859505710 https://digital.csic.es/handle/10261/236614 Journal of Soils and Sediments Sí open
institution ICA ES
collection DSpace
country España
countrycode ES
component Bibliográfico
access En linea
databasecode dig-ica-es
tag biblioteca
region Europa del Sur
libraryname Biblioteca del ICA España
topic C sequestration | Crop residue | Manure | Modeling | Organic amendment | Soil organic matter
C sequestration | Crop residue | Manure | Modeling | Organic amendment | Soil organic matter
spellingShingle C sequestration | Crop residue | Manure | Modeling | Organic amendment | Soil organic matter
C sequestration | Crop residue | Manure | Modeling | Organic amendment | Soil organic matter
Plaza de Carlos, César
Gollany, Hero T.
Baldoni, Guido
Polo, Alfredo
Ciavatta, Claudio
Predicting long-term organic carbon dynamics in organically amended soils using the CQESTR model
description Purpose: The CQESTR model is a process-based C model recently developed to simulate soil organic matter (SOM) dynamics and uses readily available or easily measurable input parameters. The current version of CQESTR (v. 2.0) has been validated successfully with a number of datasets from agricultural sites in North America but still needs to be tested in other geographic areas and soil types under diverse organic management systems. Materials and methods: We evaluated the predictive performance of CQESTR to simulate long-term (34 years) soil organic C (SOC) changes in a SOM-depleted European soil either unamended or amended with solid manure, liquid manure, or crop residue. Results and discussion: Measured SOC levels declined over the study period in the unamended soil, remained constant in the soil amended with crop residues, and tended to increase in the soils amended with manure, especially with solid manure. Linear regression analysis of measured SOC contents and CQESTR predictions resulted in a correlation coefficient of 0.626 (P < 0.001) and a slope and an intercept not significantly different from 1 and 0, respectively (95% confidence level). The mean squared deviation and root mean square error were relatively small. Simulated values fell within the 95% confidence interval of the measured SOC, and predicted errors were mainly associated with data scattering. Conclusions: The CQESTR model was shown to predict, with a reasonable degree of accuracy, the organic C dynamics in the soils examined. The CQESTR performance, however, could be improved by adding an additional parameter to differentiate between pre-decomposed organic amendments with varying degrees of stability. © 2012 Springer-Verlag (outside the USA).
format artículo
topic_facet C sequestration | Crop residue | Manure | Modeling | Organic amendment | Soil organic matter
author Plaza de Carlos, César
Gollany, Hero T.
Baldoni, Guido
Polo, Alfredo
Ciavatta, Claudio
author_facet Plaza de Carlos, César
Gollany, Hero T.
Baldoni, Guido
Polo, Alfredo
Ciavatta, Claudio
author_sort Plaza de Carlos, César
title Predicting long-term organic carbon dynamics in organically amended soils using the CQESTR model
title_short Predicting long-term organic carbon dynamics in organically amended soils using the CQESTR model
title_full Predicting long-term organic carbon dynamics in organically amended soils using the CQESTR model
title_fullStr Predicting long-term organic carbon dynamics in organically amended soils using the CQESTR model
title_full_unstemmed Predicting long-term organic carbon dynamics in organically amended soils using the CQESTR model
title_sort predicting long-term organic carbon dynamics in organically amended soils using the cqestr model
publishDate 2012-04-01
url http://hdl.handle.net/10261/330296
https://digital.csic.es/handle/10261/236614
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