Journal articles: 'RothC model'

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Paul, K. I., and P. J. Polglase. "Calibration of the RothC model to turnover of soil carbon under eucalypts and pines." Soil Research 42, no. 8 (2004): 883. http://dx.doi.org/10.1071/sr04025.

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Abstract The FullCAM model was developed for full carbon accounting in agriculture and forests at project and national scales. For forest systems, FullCAM links the empirical CAMFor model to models of tree growth (3PG), litter decomposition (GENDEC), and soil carbon turnover (RothC). Our objective was to calibrate RothC within the FullCAM framework using 2 long-term forestry experiments where productivity had been manipulated and archived and new soil samples were available for analysis of carbon within the various pools described by RothC. Inputs of carbon to soil at these trials were estimated by calibrating FullCAM to temporal data on above-ground growth, litterfall, and accumulation of litter. Two alternative submodels are available in FullCAM (CAMFor and GENDEC) for predicting decomposition of litter, and thus the input of carbon into the soil. Calibration of RothC was most sensitive to the partitioning of carbon during decomposition of debris between that lost as CO2 and that transferred to soil. Turnover of soil carbon was best simulated when the proportion of carbon lost to CO2 from relatively labile pools of debris was 77% (when simulated by CAMFor) and 95% (when simulated by GENDEC), whereas resistant pools of debris lost about 40% to CO2 during decomposition. Although rates of decomposition of pools of soil carbon were originally developed in RothC for agricultural soils, these constants were found to be also suitable for soils under plantation systems.

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Diele, Fasma, Carmela Marangi, and Angela Martiradonna. "Non-Standard Discrete RothC Models for Soil Carbon Dynamics." Axioms 10, no. 2 (April 8, 2021): 56. http://dx.doi.org/10.3390/axioms10020056.

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Soil Organic Carbon (SOC) is one of the key indicators of land degradation. SOC positively affects soil functions with regard to habitats, biological diversity and soil fertility; therefore, a reduction in the SOC stock of soil results in degradation, and it may also have potential negative effects on soil-derived ecosystem services. Dynamical models, such as the Rothamsted Carbon (RothC) model, may predict the long-term behaviour of soil carbon content and may suggest optimal land use patterns suitable for the achievement of land degradation neutrality as measured in terms of the SOC indicator. In this paper, we compared continuous and discrete versions of the RothC model, especially to achieve long-term solutions. The original discrete formulation of the RothC model was then compared with a novel non-standard integrator that represents an alternative to the exponential Rosenbrock–Euler approach in the literature.

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GONZÁLEZ-MOLINA, L., J. D. ETCHEVERS-BARRA, F. PAZ-PELLAT, H. DÍAZ-SOLIS, M. H. FUENTES-PONCE, S. COVALEDA-OCÓN, and M. PANDO-MORENO. "Performance of the RothC-26.3 model in short-term experiments in Mexican sites and systems." Journal of Agricultural Science 149, no. 4 (March 10, 2011): 415–25. http://dx.doi.org/10.1017/s0021859611000232.

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SUMMARYInformation on the performance of the Rothamsted organic carbon turnover model (RothC model) in predicting changes in soil organic carbon (SOC) in short-term experiments is scarce. In Mexico, it was found that these experiments covered not more than 20 years. The purpose of the present study was to evaluate short-term SOC prediction performance of the RothC model in the following systems: (1) farming with residues added (A+R), (2) farming with no added residues (A−R), (3) pure forest stands (F), (4) grasslands (GR) and (5) rangeland (RL). Work was done in five experimental sites: Atécuaro, Michoacán; Santiago Tlalpan, Tlaxcala; El Batán, State of Mexico; Sierra Norte, Oaxaca; and Linares, Nuevo León. Carbon (C) inputs to the soil were plant residues and organic fertilizers, which need to be known to operate the RothC model. The adjustment coefficients for site modelling had R2 values of 0·77–0·95 and model efficiency (EF) was −0·60 to 0·93. When RothC performance was evaluated by a system, R2 values were 0·06–0·92 and EF was −0·24 to 0·90. The low R2 and EF values in rangelands were attributed to the fact that these systems are complex because of heterogeneous vegetation, soil and climate. In general, the evaluation of the RothC model indicates that it can be useful in simulating SOC changes in temperate and warm climate sites and in farming, forest and grassland systems in Mexico.

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D’Avino, Lorenzo, Claudia Di Bene, Roberta Farina, and Francesco Razza. "Introduction of Cardoon (Cynara cardunculus L.) in a Rainfed Rotation to Improve Soil Organic Carbon Stock in Marginal Lands." Agronomy 10, no. 7 (July 1, 2020): 946. http://dx.doi.org/10.3390/agronomy10070946.

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The production of a biomass as a feedstock for biorefinery is gaining attention in many agricultural areas. The adoption of biorefinery crops (i.e., perennial cardoon) can represent an interesting option for farmers and can contribute to increase soil organic carbon stock (SOCS). The study aimed to assess the potential effect on long-term SOCS change by the introduction of cardoon in a Mediterranean marginal area (Sassari, Italy). To this end, three process-oriented models, namely the Intergovernmental Panel on Climate Change (IPCC) guidelines for national greenhouse gas inventories (Tier 2), a humus-balance model (SOMBIT) and Rothamsted carbon model (RothC), were used to compare two scenarios over 20 years. The traditional cropping system’s faba bean–durum wheat biennial rotation was compared with the same scenario alternating seven years of cardoon cultivation. The model’s calibration was performed using climate, soil and crop data measured in three cardoon trials between 2011 and 2019. SOMBIT and Roth C models showed the best values of model performance metrics. By the insertion of cardoon, IPCC tool, SOMBIT and RothC models predicted an average annual SOCS increase, whereas, in the baseline scenario, the models predicted a steady state or a slight SOCS decrease. This increase can be attributed to a higher input of above- and belowground plant residues and a lower number of bare soil days (41 vs. 146 days year−1).

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Jebari, Asma, Jorge Álvaro-Fuentes, Guillermo Pardo, María Almagro, and Agustin del Prado. "Estimating soil organic carbon changes in managed temperate moist grasslands with RothC." PLOS ONE 16, no. 8 (August 20, 2021): e0256219. http://dx.doi.org/10.1371/journal.pone.0256219.

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Temperate grassland soils store significant amounts of carbon (C). Estimating how much livestock grazing and manuring can influence grassland soil organic carbon (SOC) is key to improve greenhouse gas grassland budgets. The Rothamsted Carbon (RothC) model, although originally developed and parameterized to model the turnover of organic C in arable topsoil, has been widely used, with varied success, to estimate SOC changes in grassland under different climates, soils, and management conditions. In this paper, we hypothesise that RothC-based SOC predictions in managed grasslands under temperate moist climatic conditions can be improved by incorporating small modifications to the model based on existing field data from diverse experimental locations in Europe. For this, we described and evaluated changes at the level of: (1) the soil water function of RothC, (2) entry pools accounting for the degradability of the exogenous organic matter (EOM) applied (e.g., ruminant excreta), (3) the month-on-month change in the quality of C inputs coming from plant residues (i.e above-, below-ground plant residue and rhizodeposits), and (4) the livestock trampling effect (i.e., poaching damage) as a common problem in areas with higher annual precipitation. In order to evaluate the potential utility of these changes, we performed a simple sensitivity analysis and tested the model predictions against averaged data from four grassland experiments in Europe. Our evaluation showed that the default model’s performance was 78% and whereas some of the modifications seemed to improve RothC SOC predictions (model performance of 95% and 86% for soil water function and plant residues, respectively), others did not lead to any/or almost any improvement (model performance of 80 and 46% for the change in the C input quality and livestock trampling, respectively). We concluded that, whereas adding more complexity to the RothC model by adding the livestock trampling would actually not improve the model, adding the modified soil water function and plant residue components, and at a lesser extent residues quality, could improve predictability of the RothC in managed grasslands under temperate moist climatic conditions.

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Mondini, Claudio, Maria Luz Cayuela, Tania Sinicco, Flavio Fornasier, Antonia Galvez, and Miguel Angel Sánchez-Monedero. "Modification of the RothC model to simulate soil C mineralization of exogenous organic matter." Biogeosciences 14, no. 13 (July 10, 2017): 3253–74. http://dx.doi.org/10.5194/bg-14-3253-2017.

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Abstract. The development of soil organic C (SOC) models capable of producing accurate predictions for the long-term decomposition of exogenous organic matter (EOM) in soils is important for the effective management of organic amendments. However, reliable C modeling in amended soils requires specific optimization of current C models to take into account the high variability in EOM origin and properties. The aim of this work was to improve the prediction of C mineralization rates in amended soils by modifying the RothC model to encompass a better description of EOM quality. The standard RothC model, involving C input to the soil only as decomposable (DPM) or resistant (RPM) organic material, was modified by introducing additional pools of decomposable (DEOM), resistant (REOM) and humified (HEOM) EOM. The partitioning factors and decomposition rates of the additional EOM pools were estimated by model fitting to the respiratory curves of amended soils. For this task, 30 EOMs from 8 contrasting groups (compost, anaerobic digestates, sewage sludge, agro-industrial waste, crop residues, bioenergy by-products, animal residues and meat and bone meals) were added to 10 soils and incubated under different conditions. The modified RothC model was fitted to C mineralization curves in amended soils with great accuracy (mean correlation coefficient 0.995). In contrast to the standard model, the EOM-optimized RothC was able to better accommodate the large variability in EOM source and composition, as indicated by the decrease in the root mean square error of the simulations for different EOMs (from 29.9 to 3.7 % and 20.0 to 2.5 % for soils amended with bioethanol residue and household waste compost, respectively). The average decomposition rates for DEOM and REOM pools were 89 and 0.4 yr−1, higher than the standard model coefficients for DPM (10 yr−1) and RPM (0.3 yr−1). The results indicate that the explicit treatment of EOM heterogeneity enhances the model ability to describe amendment decomposition under laboratory conditions and provides useful information to improve C modeling on the effects of different EOM on C dynamics in agricultural soils. Future research will involve the validation of the modified model with field data and its application in the long-term simulation of SOC patterns in amended soil at regional scales under climate change.

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Barančíková, G., J. Halás, M. Gutteková, J. Makovníková, M. Nováková, R. Skalský, and Z. Tarasovičová. "Application of RothC model to predict soil organic carbon stock on agricultural soils of Slovakia." Soil and Water Research 5, No. 1 (February 26, 2010): 1–9. http://dx.doi.org/10.17221/23/2009-swr.

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Soil organic matter (SOM) takes part in many environmental functions and, depending on the conditions, it can be a source or a sink of the greenhouse gases. Presently, the changes in soil organic carbon (SOC) stock can arise because of the climatic changes or changes in the land use and land management. A promising method in the estimation of SOC changes is modelling, one of the most used models for the prediction of changes in soil organic carbon stock on agricultural land being the RothC model. Because of its simplicity and availability of the input data, RothC was used for testing the efficiency to predict the development of SOC stock during 35-year period on agricultural land of Slovakia. The received data show an increase of SOC stock during the first (20 years) phase and no significant changes in the course of the second part of modelling. The increase of SOC stock in the first phase can be explained by a high carbon input of plant residues and manure and a lower temperature in comparison with the second modelling part.

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Pulcher, Roberta, Enrico Balugani, Maurizio Ventura, Nicolas Greggio, and Diego Marazza. "Inclusion of biochar in a C dynamics model based on observations from an 8-year field experiment." SOIL 8, no. 1 (March 17, 2022): 199–211. http://dx.doi.org/10.5194/soil-8-199-2022.

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Abstract. Biochar production and application as soil amendment is a promising carbon (C)-negative technology to increase soil C sequestration and mitigate climate change. However, there is a lack of knowledge about biochar degradation rate in soil and its effects on native soil organic carbon (SOC), mainly due to the absence of long-term experiments performed in field conditions. The aim of this work was to investigate the long-term degradation rate of biochar in an 8-year field experiment in a poplar short-rotation coppice plantation in Piedmont (Italy), and to modify the RothC model to assess and predict how biochar influences soil C dynamics. The RothC model was modified by including two biochar pools, labile (4 % of the total biochar mass) and recalcitrant (96 %), and the priming effect of biochar on SOC. The model was calibrated and validated using data from the field experiment. The results confirm that biochar degradation can be faster in field conditions in comparison to laboratory experiments; nevertheless, it can contribute to a substantial increase in the soil C stock in the long term. Moreover, this study shows that the modified RothC model was able to simulate the dynamics of biochar and SOC degradation in soils in field conditions in the long term, at least in the specific conditions examined.

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Fantin, Valentina, Alessandro Buscaroli, Patrizia Buttol, Elisa Novelli, Cristian Soldati, Denis Zannoni, Giovanni Zucchi, and Serena Righi. "The RothC Model to Complement Life Cycle Analyses: A Case Study of an Italian Olive Grove." Sustainability 14, no. 1 (January 5, 2022): 569. http://dx.doi.org/10.3390/su14010569.

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Soil organic carbon (SOC) plays a fundamental role in soil health, and its storage in soil is an important element to mitigate climate change. How to include this factor in Life Cycle Assessment studies has been the object of several papers and is still under discussion. SOC storage has been proposed as an additional environmental information in some applications of the Product Environmental Footprint (PEF). In the framework of wider activity aimed at producing the PEF of olive oil, the RothC model was applied to an olive cultivation located in Lazio region (Italy) to calculate the SOC storage and assess four scenarios representing different agricultural practices. RothC applicability, possible use of its results for improving product environmental performance, and relevance of SOC storage in terms of CO2eq compared to greenhouse gas emissions of the life-cycle of olive oil are discussed in this paper. According to the results, in all scenarios, the contribution in terms of CO2eq associated with SOC storage is remarkable compared to the total greenhouse gas emissions of the olive oil life-cycle. It is the opinion of the authors that the calculation of the SOC balance allows a more proper evaluation of the agricultural products contribution to climate change, and that the indications of the scenarios analysis are useful to enhance the environmental performance of these products. The downside is that the application of RothC requires additional data collection and expertise if compared to the execution of PEF studies.

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Scharnagl, B., J. A. Vrugt, H. Vereecken, and M. Herbst. "Information content of incubation experiments for inverse estimation of pools in the Rothamsted carbon model: a Bayesian perspective." Biogeosciences 7, no. 2 (February 25, 2010): 763–76. http://dx.doi.org/10.5194/bg-7-763-2010.

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Abstract. A major drawback of current soil organic carbon (SOC) models is that their conceptually defined pools do not necessarily correspond to measurable SOC fractions in real practice. This not only impairs our ability to rigorously evaluate SOC models but also makes it difficult to derive accurate initial states of the individual carbon pools. In this study, we tested the feasibility of inverse modelling for estimating pools in the Rothamsted carbon model (ROTHC) using mineralization rates observed during incubation experiments. This inverse approach may provide an alternative to existing SOC fractionation methods. To illustrate our approach, we used a time series of synthetically generated mineralization rates using the ROTHC model. We adopted a Bayesian approach using the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm to infer probability density functions of the various carbon pools at the start of incubation. The Kullback-Leibler divergence was used to quantify the information content of the mineralization rate data. Our results indicate that measured mineralization rates generally provided sufficient information to reliably estimate all carbon pools in the ROTHC model. The incubation time necessary to appropriately constrain all pools was about 900 days. The use of prior information on microbial biomass carbon significantly reduced the uncertainty of the initial carbon pools, decreasing the required incubation time to about 600 days. Simultaneous estimation of initial carbon pools and decomposition rate constants significantly increased the uncertainty of the carbon pools. This effect was most pronounced for the intermediate and slow pools. Altogether, our results demonstrate that it is particularly difficult to derive reasonable estimates of the humified organic matter pool and the inert organic matter pool from inverse modelling of mineralization rates observed during incubation experiments.

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Karunaratne, S. B., T. F. A. Bishop, J. S. Lessels, J. A. Baldock, and I. O. A. Odeh. "A space–time observation system for soil organic carbon." Soil Research 53, no. 6 (2015): 647. http://dx.doi.org/10.1071/sr14178.

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In this paper, we present a framework for a space–time observation system for soil organic carbon (STOS-SOC). We propose that the RothC model be embedded within the STOS-SOC, which is driven by satellite-derived inputs and readily available geospatial inputs, such as digital soil maps. In particular, advances in remote sensing have enabled the development of satellite products that represent key inputs into soil carbon models, examples being evapotranspiration and biomass inputs to soil, which characterise space–time variations in management and land use. Starting from an initial calibrated base for prediction, as new observations are acquired, data assimilation techniques could be used to optimise calibration algorithms and predicted model outputs. We present initial results obtained from the implementation of the proposed STOS-SOC approach to the 1445-km2 Cox’s Creek catchment in northern New South Wales, Australia. Our results showed that use of satellite-derived biomass inputs with a MODIS satellite product (MOD17A3) improved the accuracy of simulations by 16% compared with carbon inputs derived through other methods normally adopted in the spatialisation of the RothC model. We further discuss the possibility of improving the capabilities of the STOS-SOC for future applications.

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Ferrarini, Andrea, Enrico Martani, Claudio Mondini, Flavio Fornasier, and Stefano Amaducci. "Short-Term Mineralization of Belowground Biomass of Perennial Biomass Crops after Reversion to Arable Land." Agronomy 12, no. 2 (February 15, 2022): 485. http://dx.doi.org/10.3390/agronomy12020485.

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Little is known about the effect of perennial biomass crops (PBCs) removal on soil C dynamics. The belowground biomass (BGB) that is composed by plant belowground organs (PBO) such as rhizomes in the herbaceous PBCs and stumps in woody PBCs should be considered, together with fine roots (FR), as a huge input of exogenous organic matter (EOM) that is incorporated into the soil at the reversion. In this study, we mimic the incorporation of BGB of PBCs through a soil-residues incubation under controlled conditions to investigate the effects of adding FR and PBO (at real field rates) on soil C and N mineralization dynamics, and to understand decomposition controlling factors. A modified RothC model version, encompassing a better description of decomposable (DEOM) and resistant (REOM) pools, was fitted to C mineralization curves of respiration measured by CO2 evolution in incubated soil to quantify partitioning factors and decomposition rates of PBCs BGB components. After 1 month, PBO showed higher mineralization rates (498 µg CO2-C gsoil−1) than FR (196 µg CO2-C gsoil−1), with black locust having the highest amount of C respired (38% of added C). The emission peak occurred within 3 days from the beginning of the experiment for PBO and after 1 day for FR. Generally, according to the modified version of RothC model, PBO had higher proportion of REOM than FR, except for black locust. The decomposition constant rates from the optimized RothC model were higher for PBO (kDEOM: 20.9 y−1, kREOM: 12.1 y−1) than FR (kDEOM: 0.4 y−1, kREOM: 0.1 y−1), indicating that FR are less decomposable than PBO. The C/N ratio is not the main controlling factor of decomposition when residue N is not a limiting factor, while the availability of easily decomposable substrates (DEOM/REOM ratio) and cell-wall composition decomposition is a strong predictor of C and N mineralization of these EOM types. The explicit inclusion of crop-specific DEOM/REOM ratios within RothC or a similar soil C model will help to improve the predictions of long-term C sequestration trajectories (half-life > 30 years) associated with PBCs cultivation, especially when dismission of such perennial cropping systems is addressed.

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Rethemeyer, Janet, Pieter M. Grootes, Sonja Brodowski, and Bernard Ludwig. "Evaluation of Soil 14C Data for Estimating Inert Organic Matter in the Rothc Model." Radiocarbon 49, no. 2 (2007): 1079–91. http://dx.doi.org/10.1017/s0033822200042934.

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Changes in soil organic carbon stocks were simulated with the Rothamsted carbon (RothC) model. We evaluated the calculation of a major input variable, the amount of inert organic matter (IOM), using measurable data. Three different approaches for quantifying IOM were applied to soils with mainly recent organic matter and with carbon contribution from fossil fuels: 1) IOM estimation via total soil organic carbon (SOC); 2) through bulk soil radiocarbon and a mass balance; and 3) by quantifying the portion of black carbon via a specific marker. The results were highly variable in the soil containing lignite-derived carbon and ranged from 8% to 52% inert carbon of total SOC, while nearly similar amounts of 5% to 8% were determined in the soil with mainly recent organic matter. We simulated carbon dynamics in both soils using the 3 approaches for quantifying IOM in combination with carbon inputs derived from measured crop yields. In the soil with recent organic matter, all approaches gave a nearly similar good agreement between measured and modeled data, while in the soil with a fossil carbon admixture, only the 14C approach was successful in matching the measured data. Although 14C was useful for initializing RothC, care should be taken when interpreting SOC dynamics in soils containing carbon from fossil fuels, since these reflect the contribution from both natural and anthropogenic carbon sources.

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Weihermüller, L., A. Graf, M. Herbst, and H. Vereecken. "Simple pedotransfer functions to initialize reactive carbon pools of the RothC model." European Journal of Soil Science 64, no. 5 (March 22, 2013): 567–75. http://dx.doi.org/10.1111/ejss.12036.

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Takata, Yusuke, Toyoaki Ito, Toshiaki Ohkura, Hiroshi Obara, Kazunori Kohyama, and Yasuhito Shirato. "Phosphate adsorption coefficient can improve the validity of RothC model for Andosols." Soil Science and Plant Nutrition 57, no. 3 (June 2011): 421–28. http://dx.doi.org/10.1080/00380768.2011.584510.

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Barão, Lúcia, Abdallah Alaoui, and Rudi Hessel. "Identifying and Comparing Easily Accessible Frameworks for Assessing Soil Organic Matter Functioning." Agronomy 13, no. 1 (December 29, 2022): 109. http://dx.doi.org/10.3390/agronomy13010109.

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Soil organic matter (SOM) stocks are crucial for soil fertility and food provision and also contribute to climate change adaptation and mitigation. However, assessing SOM changes in cropping systems is difficult due to the varying quantity and quality of input data. SOM processes have been described by several models, but these are complex and require high amounts of input data. In this work, we identified and selected frameworks that simulate SOM pools and stocks as well as the effects of different management practices. We also required that the frameworks be easily accessible for farm-related end users and require limited and accessible amounts of input data. In all, six frameworks met our inclusion criteria: SOCRATES (Soil Organic Carbon Reserves and Transformations in EcoSystems), CCB (CANDY and-Carbon Balance), AMG, CENTURY, CQESTR, and RothC (Rothamsted Carbon Model). We collected information on these frameworks and compared them in terms of their accessibility, the model time steps used, the nutrient cycles included in the simulation, the number of SOM pools, and the agricultural management options included. Our results showed that CCB was the most robust of the frameworks considered, while AMG, CQESTR, and RothC performed the least well. However, all frameworks have strengths which may match the specific requirements and abilities of individual users.

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Scharnagl, B., J. A. Vrugt, H. Vereecken, and M. Herbst. "Information content of incubation experiments for inverse estimation of pools sizes in the Rothamsted carbon model: a Bayesian approach." Biogeosciences Discussions 6, no. 5 (September 30, 2009): 9331–57. http://dx.doi.org/10.5194/bgd-6-9331-2009.

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Abstract. Turnover of soil organic matter (SOM) is usually described with multi-compartment models. A model compartment (or pool) contains all carbon compounds with similar functional properties, such as decomposition rate and partitioning of decomposition products. These functionally defined carbon pools do not necessarily correspond to measurable (SOC) fractions in real practice. This not only impairs our ability to rigorously evaluate SOC models, but also makes it difficult to derive accurate initial states. In this study, we test the usefulness and applicability of inverse modeling to derive the various carbon pool sizes in the Rothamsted carbon model (ROTHC) using observed mineralization rate data during incubation of soil samples in the laboratory. In the last decade, inverse modeling has found widespread application and use for environmental model calibration, but this methodology has not yet been tested for assessing carbon pools in multi-compartment SOC models. To appropriately consider data and model uncertainty we consider a Bayesian approach using the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm. This Markov Chain Monte Carlo (MCMC) scheme derives the posterior probability density distribution of the initial pool sizes at the start of incubation from measured mineralization rates. Our results show that measured mineralization rates generally provide sufficient information to reliably estimate the sizes of all active carbon pools in the ROTHC model. However, for soils with slow and intermediate carbon turnover an excessively long incubation time is required to appropriately constrain all carbon pools. The explicit use of prior information on microbial biomass provides a way forward to significantly reduce uncertainty and required duration of incubation. Our illustrative case studies show how Bayesian inverse modeling can be used to provide important insights into the information content of incubation experiments for assessing SOC turnover and dynamics.

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Mishra, Gaurav, Abhishek Jangir, and Rosa Francaviglia. "Modeling soil organic carbon dynamics under shifting cultivation and forests using Rothc model." Ecological Modelling 396 (March 2019): 33–41. http://dx.doi.org/10.1016/j.ecolmodel.2019.01.016.

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Nemo, K. Klumpp, K. Coleman, M. Dondini, K. Goulding, A. Hastings, Michael B. Jones, et al. "Soil Organic Carbon (SOC) Equilibrium and Model Initialisation Methods: an Application to the Rothamsted Carbon (RothC) Model." Environmental Modeling & Assessment 22, no. 3 (November 4, 2016): 215–29. http://dx.doi.org/10.1007/s10666-016-9536-0.

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Zimmermann, M., J. Leifeld, M. W. I. Schmidt, P. Smith, and J. Fuhrer. "Measured soil organic matter fractions can be related to pools in the RothC model." European Journal of Soil Science 58, no. 3 (June 2007): 658–67. http://dx.doi.org/10.1111/j.1365-2389.2006.00855.x.

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Bhattacharyya, T., D. K. Pal, A. S. Deshmukh, R. R. Deshmukh, S. K. Ray, P. Chandran, C. Mandal, B. Telpande, A. M. Nimje, and P. Tiwary. "Evaluation of RothC model using four Long Term Fertilizer Experiments in black soils, India." Agriculture, Ecosystems & Environment 144, no. 1 (November 2011): 222–34. http://dx.doi.org/10.1016/j.agee.2011.07.021.

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Molina, Lucila González, Esaú del C. Moreno Pérez, and Aurelio Baéz Pérez. "Simulation of soil organic carbon changes in Vertisols under conservation tillage using the RothC model." Scientia Agricola 74, no. 3 (June 2017): 235–41. http://dx.doi.org/10.1590/1678-992x-2015-0487.

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Poeplau, Christopher. "Estimating root: shoot ratio and soil carbon inputs in temperate grasslands with the RothC model." Plant and Soil 407, no. 1-2 (August 24, 2016): 293–305. http://dx.doi.org/10.1007/s11104-016-3017-8.

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Liu, De Li, K. Yin Chan, Mark K. Conyers, Guangdi Li, and Graeme J. Poile. "Simulation of soil organic carbon dynamics under different pasture managements using the RothC carbon model." Geoderma 165, no. 1 (October 2011): 69–77. http://dx.doi.org/10.1016/j.geoderma.2011.07.005.

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Farina, Roberta, Kevin Coleman, and Andrew P. Whitmore. "Modification of the RothC model for simulations of soil organic C dynamics in dryland regions." Geoderma 200-201 (June 2013): 18–30. http://dx.doi.org/10.1016/j.geoderma.2013.01.021.

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Hasukawa, Hiroyuki, Yumi Inoda, Satoshi Toritsuka, Shigeto Sudo, Noriko Oura, Tomohito Sano, Yasuhito Shirato, and Junta Yanai. "Effect of Paddy-Upland Rotation System on the Net Greenhouse Gas Balance as the Sum of Methane and Nitrous Oxide Emissions and Soil Carbon Storage: A Case in Western Japan." Agriculture 11, no. 1 (January 10, 2021): 52. http://dx.doi.org/10.3390/agriculture11010052.

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To investigate the effect of paddy-upland (PU) rotation system on greenhouse gas emissions, methane (CH4) and nitrous oxide (N2O) emissions were monitored for three years for a PU rotation field (four cultivations (wheat-soybean-rice-rice) over three years) and continuous paddy (CP) field on alluvial soil in western Japan. Soil carbon storage was also calculated using an improved Rothamsted Carbon (RothC) model. The net greenhouse gas balance was finally evaluated as the sum of CO2eq of the CH4, N2O and changes in soil carbon storage. The average CH4 emissions were significantly lower and the average N2O emissions were significantly higher in the PU field than those in the CP field (p < 0.01). On CO2 equivalent basis, CH4 emissions were much higher than N2O emission. In total, the average CO2eq emissions of CH4 plus N2O in the PU field (1.81 Mg CO2 ha−1 year−1) were significantly lower than those in the CP field (7.42 Mg CO2 ha−1 year−1) (p < 0.01). The RothC model revealed that the changes in soil carbon storage corresponded to CO2eq emissions of 0.57 and 0.09 Mg CO2 ha−1 year−1 in the both fields, respectively. Consequently, the net greenhouse gas balance in the PU and CP fields were estimated to be 2.38 and 7.51 Mg CO2 ha−1 year−1, respectively, suggesting a 68% reduction in the PU system. In conclusion, PU rotation system can be regarded as one type of the climate-smart soil management.

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Hasukawa, Hiroyuki, Yumi Inoda, Satoshi Toritsuka, Shigeto Sudo, Noriko Oura, Tomohito Sano, Yasuhito Shirato, and Junta Yanai. "Effect of Paddy-Upland Rotation System on the Net Greenhouse Gas Balance as the Sum of Methane and Nitrous Oxide Emissions and Soil Carbon Storage: A Case in Western Japan." Agriculture 11, no. 1 (January 10, 2021): 52. http://dx.doi.org/10.3390/agriculture11010052.

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To investigate the effect of paddy-upland (PU) rotation system on greenhouse gas emissions, methane (CH4) and nitrous oxide (N2O) emissions were monitored for three years for a PU rotation field (four cultivations (wheat-soybean-rice-rice) over three years) and continuous paddy (CP) field on alluvial soil in western Japan. Soil carbon storage was also calculated using an improved Rothamsted Carbon (RothC) model. The net greenhouse gas balance was finally evaluated as the sum of CO2eq of the CH4, N2O and changes in soil carbon storage. The average CH4 emissions were significantly lower and the average N2O emissions were significantly higher in the PU field than those in the CP field (p < 0.01). On CO2 equivalent basis, CH4 emissions were much higher than N2O emission. In total, the average CO2eq emissions of CH4 plus N2O in the PU field (1.81 Mg CO2 ha−1 year−1) were significantly lower than those in the CP field (7.42 Mg CO2 ha−1 year−1) (p < 0.01). The RothC model revealed that the changes in soil carbon storage corresponded to CO2eq emissions of 0.57 and 0.09 Mg CO2 ha−1 year−1 in the both fields, respectively. Consequently, the net greenhouse gas balance in the PU and CP fields were estimated to be 2.38 and 7.51 Mg CO2 ha−1 year−1, respectively, suggesting a 68% reduction in the PU system. In conclusion, PU rotation system can be regarded as one type of the climate-smart soil management.

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Kaonga, M. L., and K. Coleman. "Modelling soil organic carbon turnover in improved fallows in eastern Zambia using the RothC-26.3 model." Forest Ecology and Management 256, no. 5 (August 2008): 1160–66. http://dx.doi.org/10.1016/j.foreco.2008.06.017.

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Rampazzo Todorovic, Gorana, Michael Stemmer, Michael Tatzber, Christian Katzlberger, Heide Spiegel, Franz Zehetner, and Martin H. Gerzabek. "Soil-carbon turnover under different crop management: Evaluation of RothC-model predictions under Pannonian climate conditions." Journal of Plant Nutrition and Soil Science 173, no. 5 (May 20, 2010): 662–70. http://dx.doi.org/10.1002/jpln.200800311.

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Skjemstad, J. O., R. C. Dalal, L. J. Janik, and J. A. McGowan. "Changes in chemical nature of soil organic carbon in Vertisols under wheat in south-eastern Queensland." Soil Research 39, no. 2 (2001): 343. http://dx.doi.org/10.1071/sr99138.

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The impact of cropping and cultivation (up to 50 years) on the nature and pool structure of organic C in two different soil types was investigated using a combination of physical and chemical fractionations and solid-state 13 C NMR spectroscopy. NMR spectroscopy revealed that aryl C contributed significantly to the organic C in the Waco soil (Pellustert) but not in the Langlands-Logie soil (Chromustert). The aryl C content of both soils was largely preserved despite the significant decrease in total organic C, following cultivation, although other organic forms appeared to rapidly decline at similar rates to one another. High energy UV photo-oxidation along with solid-state 13 C NMR spectroscopy demonstrated that the aryl C was mainly charcoal (char) in the <53 mm fraction of the soils which appeared to be highly resistant to microbial decomposition. Char C content of the Waco soil remained near 6.0 g C/kg soil and near 2.0 g C/kg soil for the Langlands-Logie soil. This char was evident to a depth of at least 30 cm in both soils. Fractionation yielded 4 organic C fractions: particulate organic C, humic C, char C, and physically protected C. By equating these fractions to the resistant plant material (particulate organic C), humic pool (humic C), and inert pool (char C) of the RothC soil C turnover model and comparing a number of simulations with measured fractions, we showed that the inert pool equated well with the measured char C. The measured particulate organic C fraction was of an appropriate size to represent the resistant plant material pool of the model but appeared to have a much slower turnover rate. Similarly, the measured humic pool was of a similar size to that required by the model but was more labile (faster turnover rate) than that used in the RothC model. This may be due to a combination of the labile proteinaceous nature of this pool and its lower than expected protection by physical association with the smectitic clay matrix.

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Skjemstad, J. O., L. R. Spouncer, B. Cowie, and R. S. Swift. "Calibration of the Rothamsted organic carbon turnover model (RothC ver. 26.3), using measurable soil organic carbon pools." Soil Research 42, no. 1 (2004): 79. http://dx.doi.org/10.1071/sr03013.

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A fractionation scheme that provided the measurement of a labile pool (particulate organic carbon), a charcoal-carbon pool, and a humic pool by difference was tested as a means of initialising the Rothamsted organic carbon turnover model version 26.3. Equating these 3 fractions with the resistant plant material, inert organic matter, and humic pools of the model, respectively, gave good agreement between measured and modelled data for 2 long-term rotation trials in Australia using a soil depth of 30 cm. At one location, Brigalow Research Station in Queensland, there were 3 distinct soil types, two clays and a duplex soil, in a semi-arid, subtropical climate. At this site, continuous wheat with some sorghum was established after clearing land under brigalow (Acacia harpophylla) and continued for 18 years. The second location was near Tarlee, South Australia, and was established on existing agricultural land. One soil type (red brown earth) with 2 rotations (continuous wheat and wheat–fallow) were available over a period of 8 years.The modelled and measured data were in good agreement for both locations but the level of agreement was substantially improved when the resistant plant material decomposition rate was reduced from 0.3 to 0.15/year. No other modifications were required and the resulting values provided excellent agreement between the modelled and measured data not only for the total soil organic carbon but also for the individual pools. Using this fractionation scheme therefore provides an excellent means of initialising and testing the Rothamsted model, not only in Australia, but also in countries with similar soil types and climate.For the first time, the work reported here demonstrates a methodology linking measured soil carbon pools with a conceptual soil carbon turnover model. This approach has the advantage of allowing the model to be initialised at any point in the landscape without the necessity for historical data or for using the model itself to generate an initial equilibrium pool structure. The correct prediction of the changing total soil organic carbon levels, as well as the pool structure over time, acts as an internal verification and gives confidence that the model is performing as intended.

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Polevoy, Anatoliy N., and Ludmila E. Bozko. "Assessment of organic carbon dynamics in podzolized chernozem soil in field crop rotation under the climate change." Journal of the Belarusian State University. Geography and Geology, no. 2 (November 29, 2019): 65–78. http://dx.doi.org/10.33581/2521-6740-2019-2-65-78.

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The work presents assessment of organic carbon in the soil and СО2 – C emissions for the ten-field crop rotation in a changing climate conditions. The expected weather conditions for the 2021–2050 are estimated with RCP4.5 and RCP8.5 models. The research uses the updated model for the soil carbon cycle RothC-26.3, which describes the dynamics of four active and one inert compartments of the soil organic matter. The numerical studies consider three variants of the ten-fields crops rotation: 1) growing crops without fertilizing; 2) fertilization with mineral fertilizers in N45 P45 K45 and N90P90K 90 doses; 3) fertilization with organic fertilizers in the amounts of 9 and 18 t/ha. The research object is the balance of organic carbon in the soil and СО2 – C emissions from all crop rotation fields and the singular crop rotation field in the climate change conditions.

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Falloon, P., and P. Smith. "Simulating SOC changes in long-term experiments with RothC and CENTURY: model evaluation for a regional scale application." Soil Use and Management 18, no. 2 (January 19, 2006): 101–11. http://dx.doi.org/10.1111/j.1475-2743.2002.tb00227.x.

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Roxburgh, S. H., B. G. Mackey, C. Dean, L. Randall, A. Lee, and J. Austin. "Organic carbon partitioning in soil and litter in subtropical woodlands and open forests: a case study from the Brigalow Belt, Queensland." Rangeland Journal 28, no. 2 (2006): 115. http://dx.doi.org/10.1071/rj05015.

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A woodland–open forest landscape within the Brigalow Belt South bioregion of Queensland, Australia, was surveyed for soil organic carbon, soil bulk density and soil-surface fine-litter carbon. Soil carbon stocks to 30 cm depth across 14 sites, spanning a range of soil and vegetation complexes, ranged from 10.7 to 61.8 t C/ha, with an overall mean of 36.2 t C/ha. Soil carbon stocks to 100 cm depth ranged from 19.4 to 150.5 t C/ha, with an overall mean of 72.9 t C/ha. The standing stock of fine litter ranged from 1.0 to 7.0 t C/ha, with a mean of 2.6 t C/ha, and soil bulk density averaged 1.4 g/cm3 at the soil surface, and 1.6 g/cm3 at 1 m depth. These results contribute to the currently sparse database of soil organic carbon and bulk density measurements in uncultivated soils within Australian open forests and woodlands. The estimates of total soil organic carbon stock calculated to 30 cm depth were further partitioned into resistant plant material (RPM), humus (HUM), and inert organic matter (IOM) pools using diffuse mid-infrared (MIR) analysis. Prediction of the HUM and RPM pools using the RothC soil carbon model agreed well with the MIR measurements, confirming the suitability of RothC for modelling soil organic carbon in these soils. Methods for quantifying soil organic carbon at landscape scales were also explored, and a new regression-based technique for estimating soil carbon stocks from simple field-measured soil attributes has been proposed. The results of this study are discussed with particular reference to the difficulties encountered in the collection of the data, their limitations, and opportunities for the further development of methods for quantifying soil organic carbon at landscape scales.

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Guo, L., P. Falloon, K. Coleman, B. Zhou, Y. Li, E. Lin, and F. Zhang. "Application of the RothC model to the results of long-term experiments on typical upland soils in northern China." Soil Use and Management 23, no. 1 (March 2007): 63–70. http://dx.doi.org/10.1111/j.1475-2743.2006.00056.x.

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Yokozawa, Masayuki, Yasuhito Shirato, Toshihiro Sakamoto, Seiichirou Yonemura, Makoto Nakai, and Toshiaki Ohkura. "Use of the RothC model to estimate the carbon sequestration potential of organic matter application in Japanese arable soils." Soil Science and Plant Nutrition 56, no. 1 (February 2010): 168–76. http://dx.doi.org/10.1111/j.1747-0765.2009.00422.x.

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37

Francaviglia, Rosa, Kevin Coleman, Andrew P. Whitmore, Luca Doro, Giulia Urracci, Mariateresa Rubino, and Luigi Ledda. "Changes in soil organic carbon and climate change – Application of the RothC model in agro-silvo-pastoral Mediterranean systems." Agricultural Systems 112 (October 2012): 48–54. http://dx.doi.org/10.1016/j.agsy.2012.07.001.

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Ren, J., L. C. Wang, X. M. Yang, X. P. Zhang, H. J. Fang, and P. Zhu. "Long-Term Effects of Fertilization on Soil Organic Carbon Changes in Continuous Corn of Northeast China: RothC Model Simulations." Environmental Management 32, no. 4 (October 1, 2003): 459–65. http://dx.doi.org/10.1007/s00267-003-0082-6.

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Afzali, Sayed Fakhreddin, Bijan Azad, Mohammad H. Golabi, and Rosa Francaviglia. "Using RothC Model to Simulate Soil Organic Carbon Stocks under Different Climate Change Scenarios for the Rangelands of the Arid Regions of Southern Iran." Water 11, no. 10 (October 10, 2019): 2107. http://dx.doi.org/10.3390/w11102107.

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Soil organic carbon (SOC) is strongly influenced by climate change, and it is believed that increased temperatures might enhance the release of CO2 with higher emission into the atmosphere. Appropriate models may be used to predict the changes of SOC stock under projected future scenarios of climate change. In this investigation, the RothC model was run for a period of 36 years under climate scenarios namely: P (no climate change) as well as CCH1 and CCH2 (climate change scenarios) in the arid rangelands of Ghir–O-Karzin’s BandBast in southern Iran. Model results have shown that after 11 years (2014–25), SOC stock decreased by 3.05% under the CCH1 scenario (with a projected annual precipitation decrease by 6.69% and mean annual temperature increase by 9.96%) and by 0.23% under the P scenario. In CCH2, with further decreases in rainfall (10.93%) and increase in temperature (12.53%) compared to CCH1, the model predicted that the SOC stock during the 25 years (2025–50) was reduced by 2.36% and 3.53% under the CCH1 and CCH2 scenario respectively. According to model predictions, with future climatic conditions (higher temperatures and lower rainfall) the decomposition rate may increase resulting in higher losses of soil organic carbon from the soil matrix. The result from this investigation may also be used for developing management techniques to be practiced in the other arid rangelands of Iran with similar conditions.

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Nieto, O. M., J. Castro, E. Fernández, and P. Smith. "Simulation of soil organic carbon stocks in a Mediterranean olive grove under different soil-management systems using the RothC model." Soil Use and Management 26, no. 2 (March 15, 2010): 118–25. http://dx.doi.org/10.1111/j.1475-2743.2010.00265.x.

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Morais, Tiago, Ricardo Teixeira, Nuno Rodrigues, and Tiago Domingos. "Characterizing Livestock Production in Portuguese Sown Rainfed Grasslands: Applying the Inverse Approach to a Process-Based Model." Sustainability 10, no. 12 (November 27, 2018): 4437. http://dx.doi.org/10.3390/su10124437.

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Grasslands are a crucial resource that supports animal grazing and provides other ecosystem services. We estimated the main properties of Portuguese sown biodiverse permanent pastures rich in legumes (SBP) starting from measured data for soil organic carbon (SOC) and using the Rothamsted Carbon Model. Starting from a dataset of SOC, aboveground production (AGP) and stocking rates (SR) in SBP, we used an inverse approach to estimate root to shoot (RS) ratios, livestock dung (LD), livestock intake (LI) and the ratio between easily decomposable and resistant plant material. Results for the best fit show that AGP and belowground productivity is approximately the same (RS is equal to 0.96). Animals consume 61% of the AGP, which is within the acceptable range of protein and energy intake. Carbon inputs from dung are also within the range found in the literature (1.53 t C/livestock unit). Inputs from litter are equally distributed between decomposable and resistant material. We applied these parameters in RothC for a dataset from different sites that only comprises SOC to calculate AGP and SR. AGP and SR were consistently lower in this case, because these pastures did not receive adequate technical support. These results highlight the mechanisms for carbon sequestration in SBP.

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Yao, Zhiyuan, Dabin Zhang, Pengwei Yao, Na Zhao, Na Liu, Bingnian Zhai, Suiqi Zhang, et al. "Coupling life-cycle assessment and the RothC model to estimate the carbon footprint of green manure-based wheat production in China." Science of The Total Environment 607-608 (December 2017): 433–42. http://dx.doi.org/10.1016/j.scitotenv.2017.07.028.

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43

Paramesh, Venkatesh, Parveen Kumar, Arun Jyoti Nath, Rosa Francaviglia, Gaurav Mishra, Vadivel Arunachalam, and Sulekha Toraskar. "Simulating soil organic carbon stock under different climate change scenarios: A RothC model application to typical land-use systems of Goa, India." CATENA 213 (June 2022): 106129. http://dx.doi.org/10.1016/j.catena.2022.106129.

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Hashimoto, Shoji, Martin Wattenbach, and Pete Smith. "Litter carbon inputs to the mineral soil of Japanese Brown forest soils: comparing estimates from the RothC model with estimates from MODIS." Journal of Forest Research 16, no. 1 (February 2011): 16–25. http://dx.doi.org/10.1007/s10310-010-0209-6.

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Gottschalk, P., J. U. Smith, M. Wattenbach, J. Bellarby, E. Stehfest, N. Arnell, T. J. Osborn, and P. Smith. "How will organic carbon stocks in mineral soils evolve under future climate? Global projections using RothC for a range of climate change scenarios." Biogeosciences Discussions 9, no. 1 (January 13, 2012): 411–51. http://dx.doi.org/10.5194/bgd-9-411-2012.

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Abstract. We use a soil carbon (C) model (RothC), driven by a range of climate models for a range of climate scenarios to examine the impacts of future climate on global soil organic carbon (SOC) stocks. The results suggest an overall global increase in global SOC stocks by 2100 under all scenarios, but with a different extent of increase among the climate model and emissions scenarios. Projected land use changes are also simulated, but have relatively small impacts at the global scale. Whether soils gain or lose SOC depends upon the balance between C inputs and decomposition. Changes in net primary production (NPP) change C inputs to the soil, whilst decomposition usually increases under warmer temperatures, but can also be slowed by decreased soil moisture. Underlying the global trend of increasing SOC under future climate is a complex pattern of regional SOC change. SOC losses are projected to occur in northern latitudes where higher SOC decomposition rates due to higher temperatures are not balanced by increased NPP, whereas in tropical regions, NPP increases override losses due to higher SOC decomposition. The spatial heterogeneity in the response of SOC to changing climate shows how delicately balanced the competing gain and loss processes are, with subtle changes in temperature, moisture, soil type and land use, interacting to determine whether SOC increases or decreases in the future. Our results suggest that we should stop asking the general question of whether SOC stocks will increase or decrease under future climate since there is no single answer. Instead, we should focus on improving our prediction of the factors that determine the size and direction of change, and the land management practices that can be implemented to protect and enhance SOC stocks.

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Gottschalk, P., J. U. Smith, M. Wattenbach, J. Bellarby, E. Stehfest, N. Arnell, T. J. Osborn, C. Jones, and P. Smith. "How will organic carbon stocks in mineral soils evolve under future climate? Global projections using RothC for a range of climate change scenarios." Biogeosciences 9, no. 8 (August 14, 2012): 3151–71. http://dx.doi.org/10.5194/bg-9-3151-2012.

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Abstract. We use a soil carbon (C) model (RothC), driven by a range of climate models for a range of climate scenarios to examine the impacts of future climate on global soil organic carbon (SOC) stocks. The results suggest an overall global increase in SOC stocks by 2100 under all scenarios, but with a different extent of increase among the climate model and emissions scenarios. The impacts of projected land use changes are also simulated, but have relatively minor impacts at the global scale. Whether soils gain or lose SOC depends upon the balance between C inputs and decomposition. Changes in net primary production (NPP) change C inputs to the soil, whilst decomposition usually increases under warmer temperatures, but can also be slowed by decreased soil moisture. Underlying the global trend of increasing SOC under future climate is a complex pattern of regional SOC change. SOC losses are projected to occur in northern latitudes where higher SOC decomposition rates due to higher temperatures are not balanced by increased NPP, whereas in tropical regions, NPP increases override losses due to higher SOC decomposition. The spatial heterogeneity in the response of SOC to changing climate shows how delicately balanced the competing gain and loss processes are, with subtle changes in temperature, moisture, soil type and land use, interacting to determine whether SOC increases or decreases in the future. Our results suggest that we should stop looking for a single answer regarding whether SOC stocks will increase or decrease under future climate, since there is no single answer. Instead, we should focus on improving our prediction of the factors that determine the size and direction of change, and the land management practices that can be implemented to protect and enhance SOC stocks.

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Qingsong, Shen, Liu Xiaobing, and Zhang Xingyi. "Evaluating soil organic carbon changes after 16 years of soil relocation in Chinese Mollisols by optimizing the input data of the RothC model." Soil and Tillage Research 225 (January 2023): 105561. http://dx.doi.org/10.1016/j.still.2022.105561.

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Dechow, Rene, Uwe Franko, Thomas Kätterer, and Hartmut Kolbe. "Evaluation of the RothC model as a prognostic tool for the prediction of SOC trends in response to management practices on arable land." Geoderma 337 (March 2019): 463–78. http://dx.doi.org/10.1016/j.geoderma.2018.10.001.

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Hábová, Magdalena, Lubica Pospíšilová, Petr Hlavinka, Miroslav Trnka, Gabriela Barančíková, Zuzana Tarasovičová, Jozef Takáč, Štefan Koco, Ladislav Menšík, and Pavel Nerušil. "Carbon pool in soil under organic and conventional farming systems." Soil and Water Research 14, No. 3 (May 27, 2019): 145–52. http://dx.doi.org/10.17221/71/2018-swr.

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Changes in the agricultural management and climatic changes within the past 25 years have had a serious impact on soil organic matter content and contribute to different carbon storage in the soil. Prediction of soil carbon pool, validation, and quantification of different models is important for sustainable agriculture in the future and for this purpose a long-term monitoring data set is required. RothC-26.3 model was applied for carbon stock simulation within two different climatic scenarios (hot-dry with rapid temperature increasing and warm-dry with less rapid temperature increasing). Ten years experimental data set have been received from conventional and organic farming of experimental plots of Mendel University School Enterprise (locality Vatín, Czech-Moravian Highland). Average annual temperature in this area is 6.9°C, average annual precipitation 621 mm, and altitude 530 m above sea level. Soil was classified as Eutric Cambisol, sandy loam textured, with middle organic carbon content. Its cumulative potential was assessed as high. Results showed linear correlation between carbon stock and climatic scenario, and mostly temperature and type of soil management has influenced carbon stock. In spite of lower organic carbon inputs under organic farming this was less depending on climatic changes. Conventional farming showed higher carbon stock during decades 2000–2100 because of higher carbon input. Besides conventional farming was more affected by temperature.

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Ilichev, Igor, Vladimir Romanenkov, Sergei Lukin, Vera Pavlova, Stanislav Siptits, and Pavel Krasilnikov. "Arable Podzols Are a Substantial Carbon Sink under Current and Future Climates: Evidence from a Long-Term Experiment in the Vladimir Region, Russia." Agronomy 11, no. 1 (January 6, 2021): 90. http://dx.doi.org/10.3390/agronomy11010090.

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Soil organic carbon (SOC) is an essential component of soil health and a potential sink for greenhouse gases. SOC dynamics in a long-term field experiment with mineral and organic fertilization on loamy sand podzol in the Vladimir Region, Russia, was traced with the dynamic carbon model RothC from 1968 until the present. During this period, C stock increased by 21%, compared to the initial level, with the application of manure, at an average annual rate of 10 t·ha−1. The model was also used to forecast SOC changes up to 2090 for two contrasting RCP4.5 and RCP8.5 climatic scenarios. Up to 2090, steady growth of SOC stocks is expected in all compared treatments for both climate scenarios. In the scenarios, this growth rate was the highest up to 2040, decreased in the period 2040–2070, and increased again in the period 2070–2090 for RCP4.5. The highest annual gain was 21–27‰ under the RCP4.5 scenario and 16–21‰ under the RCP8.5 scenario in 2020–2040 in a 0–20 cm soil layer. Under the expected climate conditions in the 21st century, the C input will increase 1.3–1.5 times under the RCP4.5 scenario and decrease by 13–20% for the same period under the RCP 8.5 scenario. Modelling demonstrated potentially more favourable conditions for SOC stability in arable podzols than in Retisols in central Russia in the 21st century.

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Journal articles on the topic 'RothC model'

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