Long-term Soil Organic Carbon Dynamics Research Articles

Soil carbon dynamics in perennial biomass crops on marginally productive cropland in southern Canada

Predicting changes in soil organic carbon (SOC) in perennial biomass crops using process-based models provides a greater understanding of land management impacts on climate mitigation through long-term soil carbon sequestration. The objective of this study was to predict long-term SOC dynamics in different perennial biomass crops [miscanthus (Miscanthus giganteus L.), switchgrass (Panicum virgatum L.), willow (Salix miyabeana L.)] as compared to secondary regrowth vegetation (successional site) and a row crop system. The Century model accurately predicted SOC when simulated values were compared to measured field data. Average SOC stocks over the 162-year simulation period to 20 cm, were highest in miscanthus (8521 g C m−2), followed by the successional site (6877 g C m−2), switchgrass (6480 g C m−2), willow (5448 g C m−2) and lowest in the row crop system (3995 g C m−2). Higher SOC stocks in the miscanthus than the successional site indicates that, despite frequent biomass harvest, perennial biomass crops can accumulate higher carbon in soil than when a marginally productive cropland is left to undergo secondary regrowth. However, this depends on the crop species, since the miscanthus was the only biomass crop that reached pre-cultivation (1911) SOC stock of 8288 g C m−2. Moreover, the perennial biomass crops enhanced SOC in the slow fraction, whereas row crops depleted SOC in this fraction. This indicates the vital contribution of perennial biomass crops in long-term SOC sequestration and their role in climate change mitigation, especially when grown on marginally productive croplands.

Long-term soil organic carbon dynamics in temperate cropland-grassland systems

Increasing soil organic carbon (SOC) in agroecosystems enables to address simultaneously multiple goals such as climate change adaptation and mitigation as well as food security. As croplands are depleted in SOC, they offer a great potential to sequester atmospheric carbon (C). Nonetheless, croplands are still losing SOC under most of the current agricultural systems. Although many factors driving SOC dynamics have already been identified, their relative importance has not been quantified yet. Using one of the densest European soil monitoring networks with 250 sites established in western Switzerland, in the present study we (i) assessed long-term (over 30 years) SOC dynamics in croplands (CR), permanent grasslands (PG) and mountain pastures (MP), and (ii) prioritized the importance of land use, soil characteristics and sites conditions in driving SOC dynamics. The SOC levels in PG and MP were similar when clay content was accounted for, whereas CR were depleted in SOC by 3.9 mg C mg−1 clay as compared to PG. The majority (61 %) of CR had SOC:clay ratio below 1:10, but only 16 % of PG and MP sites reached this threshold. By contrast, soil organic matter stoichiometry (C:N:Porg ratios) was similar in CR and PG for comparable SOC content. The increase of C:Porg ratio with SOC content (dilution effect) and the high total P in CR and PG (legacy effect) indicate the possibility to sequester atmospheric C at reduced nutrient sequestration costs. SOC changes ranged from -0.61 to 1.32 mg g-1 soil yr−1 and were the highest in sites that experienced land-use changes. No PG were losing SOC, while CR sites exhibited both SOC gains and losses. Because of the predominance of the initial SOC content on SOC dynamics, land-use history must be accounted for when assessing the effect of management practices. The main manageable factors driving SOC dynamics were the time under temporary or permanent grasslands along with the soil total P. As PG already are rich in SOC and total P, organic amendments should be partly redirected to CR.

Modelling long-term soil organic carbon dynamics under the impact of land cover change and soil redistribution

During the last millennia, anthropogenic land cover change has caused a significant release of carbon from soils while also accelerating rates of soil erosion by one to two orders of magnitude. However, mechanistic frameworks that explicitly link land cover change, erosion and soil organic carbon (SOC) cycling and, in addition, can be applied to longer timescales are currently lacking. This study presents a 4D soil-landscape model coupling sediment fluxes and carbon dynamics in response to continuous land cover change over a period of 1000years. We applied the model to a well-studied catchment of 591km2 in Central Belgium. The model evaluation showed that the simulated magnitude and spatial patterns of soil redistribution and SOC stocks are in good agreement with field observations. At the catchment scale, land cover change over the last 1000years decreased the SOC stock of the top 1m of soil by 33.1tC·ha−1 (32% loss compared to the initial SOC stock) while in contrast, erosion resulted in an uptake of 31.9tC·ha−1 from the atmosphere (29% gain compared to the initial SOC stock). As a result, the combined effect is a small source of c. 1.2tC·ha−1 over the last 1000years. While the SOC released from the soil to the atmosphere quickly responded to land conversion, the erosion induced sink operated at a much lower intensity but with a longer duration. These transient simulations show that the soil carbon budget is highly variable in both space and time.

Accelerated soil carbon turnover under tree plantations limits soil carbon storage.

The replacement of native forests by tree plantations is increasingly common globally, especially in tropical and subtropical areas. Improving our understanding of the long-term effects of this replacement on soil organic carbon (SOC) remains paramount for effectively managing ecosystems to mitigate anthropogenic carbon emissions. Meta-analyses imply that native forest replacement usually reduces SOC stocks and may switch the forest from a net sink to a net source of atmospheric carbon. Using a long-term chronosequence during which areas of subtropical native forest were replaced by Chinese fir, we show by direct measurement that plantations have significantly accelerated SOC turnover compared with native forest, an effect that has persisted for almost a century. The immediate stimulation of SOC decomposition was caused by warmer soil before the closure of the plantation’s canopy. Long-term reductions in SOC mean residence times were coupled to litter inputs. Faster SOC decomposition was associated with lower soil microbial carbon use efficiency, which was due to smaller litter inputs and reduced nutrient availabilities. Our results indicate a previously unelucidated control on long-term SOC dynamics in native forests and demonstrate a potential constraint on climate mitigation when such forests are replaced by plantations.

Significance of microbial asynchronous anabolism to soil carbon dynamics driven by litter inputs.

Soil organic carbon (SOC) plays an important role in the global carbon cycle. However, it remains largely unknown how plant litter inputs impact magnitude, composition and source configuration of the SOC stocks over long term through microbial catabolism and anabolism, mostly due to uncoupled research on litter decomposition and SOC formation. This limits our ability to predict soil system responses to changes in land-use and climate. Here, we examine how microbes act as a valve controlling carbon sequestrated from plant litters versus released to the atmosphere in natural ecosystems amended with plant litters varying in quantity and quality. We find that litter quality – not quantity – regulates long-term SOC dynamics under different plausible scenarios. Long-term changes in bulk SOC stock occur only when the quality of carbon inputs causes asynchronous change in a microbial physiological trait, defined as “microbial biosynthesis acceleration” (MBA). This is the first theoretical demonstration that the response of the SOC stocks to litter inputs is critically determined by the microbial physiology. Our work suggests that total SOC at an equilibrium state may be an intrinsic property of a given ecosystem, which ultimately is controlled by the asynchronous MBA between microbial functional groups.

Is priming effect a significant process for long-term SOC dynamics? Analysis of a 52-years old experiment

Short time scale (~days to year) soil incubation experiments have evidenced that mineralisation rate of soil organic carbon could be increased by higher fresh organic matter (FOM) inputs. This process could affect global soil C stocks but its importance has yet to be assessed at decennial or centennial time-scales. In this study, we analysed soil organic carbon (SOC) data from a 52-years old bare-fallow experiment in Grignon (France) where plots received no organic matter, or only fresh straw or composted straw. Treatments receiving fresh or composted straw showed no significant difference in SOC stocks dynamics over the 52 years, suggesting no long-term impact of priming effect. To go further, we evaluated whether soil organic matter (SOM) mineralisation rates differed between plots with no input and plots with FOM inputs, using simple models of SOC dynamics based on the Henin-Dupuis formalism. Using a model with three SOC pools, we showed that estimated mineralisation rates were 3–4 times slower for the plots with no input, suggesting an important role of priming effect. However, a 4-pools model with first order kinetics could satisfactorily fit all the data using a same set of parameters. Our results did not assess the absence of priming effect on SOC stocks dynamics at decennial timescale, but suggest that priming effect is not necessarily a relevant process to explain long-term SOC dynamics. It would be worthwhile to test our modelling approach on other long-term datasets, in particular from more nitrogen-limited experiments and using other data giving complementary information on mineralisation rates, such as 14C.

Soil Carbon Sequestration Potential as Affected by Management Practices in Northern China: A Simulation Study

Soil has been identified as a possible carbon (C) sink for sequestering atmospheric carbon dioxide (CO2). However, soil organic carbon (SOC) dynamics in agro-ecosystems is affected by complex interactions of various factors including climate, soil and agricultural management practices, which hinders our understanding of the underlying mechanisms. The objectives of this study were to use the Agricultural Production Systems sIMulator (APSIM) model to simulate the long-term SOC dynamics under different management practices at four long-term experimental sites, Zhengzhou and Xuzhou with double cropping systems and Gongzhuling and Ürümqi with single cropping systems, located in northern China. Firstly, the model was calibrated using information from the sites and literature, and its performance to predict crop growth and SOC dynamics was examined. The calibrated model was then used to assess the impacts of different management practices, including fertilizer application, irrigation, and residue retention, on C dynamics in the top 30 cm of the soil by scenario modelling. Results indicate a significant SOC sequestration potential through improved management practices of nitrogen (N) fertilizer application, stubble retention, and irrigation. Optimal N fertilization (Nopt) and 100% stubble retention (R100) increased SOC by about 11.2%, 208.29%, and 283.67% under irrigation at Gongzhuling, Zhengzhou, and Xuzhou, respectively. Soil organic carbon decreased rapidly at Ürümqi under irrigation, which was due to the enhanced decomposition by increased soil moisture. Under rainfed condition, SOC remained at a higher level. The combination of Nopt and R100 increased SOC by about 0.46% under rainfed condition at Ürümqi. Generally, agricultural soils with double cropping systems (Zhengzhou and Xuzhou) showed a greater potential to sequester C than those with single cropping systems (Gongzhuling and Ürümqi).

Validation of soil organic carbon dynamics model in the semi-arid tropics in Niger, West Africa

The fertility of sandy soils in the Sahelian zone (SZ) is extremely low. This poor soil fertility is one of the limiting factors of crop production in the SZ. Therefore, it is imperative to improve or to maintain soil fertility through various agricultural management methods. Further, it is well known that soil organic matter plays an important role in improving the physico-chemical properties of these sandy infertile soils. Therefore, it is essential to develop a suitable tool for the appropriate evaluation of soil organic carbon (SOC) dynamics in the SZ. Therefore, the Rothamsted carbon model (Roth-C) was verified in 32 treatments of two long-term field experiments with and without crop residue application. These experiments were performed by ICRISAT. The performance of the model was evaluated by statistical methods using four indices (RMSE: root mean square error, LOFIT: lack of fit, r: correlation coefficient, and M: mean difference). As a result, the predicted SOC values in the case without crop residue management decreased with time in approximately 10 cultivated years. In contrast, in the case with crop residue application, the predicted SOC remained roughly equal to the initial SOC value during the term observed. Mostly, the Roth-C-modelled values agreed well with the actual value. RMSE and LOFIT, the statistical indicators of agreement between predicted and observed values, showed a significant conformity between the predicted and observed SOC values in all the 32 treatments. This fact means that Roth-C can estimate long-term SOC dynamics of several technical options that developed with short-term trials. Moreover the annual carbon requirement for SOC maintaining can be calculate if enough number of cases was estimated. And also analysis of regional carbon dynamics was made possible with using Roth-C model. It will contribute to show the sustainable development in SZ against global warming and other climatic changes.

Parameter and input data uncertainty estimation for the assessment of long-term soil organic carbon dynamics

The use of integrated soil organic matter (SOM) models to assess SOM dynamics under climate change, land use change and different land management practices require a quantification of uncertainties and key sensitive factors related to the respective modelling framework. Most uncertainty studies hereby focus on model parameter uncertainty, neglecting other sources like input data derived uncertainties, and spatial and temporal properties of uncertainty. Sources of uncertainties assessed in this study stem from uncertainties in model parameterisation and from uncertainties in model input data (climate, soil data, and land management assumptions). Thereby, Monte Carlo based global sensitivity and uncertainty analysis using a latin hypercube stratified sampling technique was applied to derive plot scale (focusing on temporal propagation) and river basin scale propagation of uncertainty for long-term soil organic carbon (SOC) dynamics. The model used is the eco-hydrological river basin model SWIM (Soil and Water Integrated Model), which has been extended by a process-based multi-compartment model for SOM turnover. Results obtained by this study can be transferred and used in other simulation models of this kind. Uncertainties resulting from all input factors used (model parameters + model input data) show a coefficient of variation between 5.1 and 6.7% and accounted for ± 0.065 to ± 0.3% soil carbon content (0.06–0.15 t C ha −1 yr −1). Parameter derived uncertainty contributed most to overall uncertainty. Concerning input data contributions, uncertainties stemming from soil and climate input data variations are striking. At the river basin scale, cropland and forest ecosystems, loess and gleyic soils possess the highest degree of uncertainty. Quantified magnitudes of uncertainty stemming from the examined sources vary temporally and spatially due to specific natural settings (e.g. climate, land use and soil properties) and deliver useful information for interpreting simulation results on long-term soil organic carbon dynamics under environmental change. Derived from this analysis, key sensitive model parameters and interactions between them were identified: the mineralization rate coefficient, the carbon use efficiency parameter (synthesis coefficient) along with parameters determining the soil temperature influence on SOM turnover (mainly Q10 value) and the soil input related data ( soil bulk density and initial soil C content) introduced the highest degree of model uncertainty. The here gained information can be transferred to other process-based SOM turnover models to consider stronger most crucial parameters introducing highest uncertainty contribution to soil C storage assessment under changing environmental conditions.

Integrated eco-hydrological modelling of soil organic matter dynamics for the assessment of environmental change impacts in meso- to macro-scale river basins

A process-based extension of the eco-hydrological river basin model SWIM (Soil and Water Integrated Model) to simulate selected environmental change impacts on soil organic carbon (SOC) dynamics for environmental conditions in meso- to macro-scale river basins is proposed. The novel aspect and main advantage of the extended model is an integrated consideration of hydrological processes, vegetation dynamics and biogeochemical cycles (soil carbon, phosphorus, and nitrogen) in semi-closed systems (river basins) under environmental change. Thereby the extension was designed to integrate present-day understanding of soil organic matter dynamics under the constraints of data availability for parameterisation at the regional scale. A major advantage is less data and parameter necessary to run the model compared to state of the art SOC models and the availability of direct measurements of soil C carbon contents to test and validate the model. The model extension was tested regarding primary organic matter decomposition and long-term SOC dynamics using observed data sets. This test delivered similar quality as other SOC models. The new SOC model extension adequately represents these processes when compared to observed data on experimental field sites and literature studies. Application of the extended model to assess impacts of land management practices (different organic and inorganic fertilisation schemes, different crop rotations, inclusion of cover crops and harvest by-product returns) on long-term SOC dynamics is presented here at the experimental field and river basin scale. The simulated quantification at the field scale of different fertilisation regimes led to changes from −0.13 to +0.1 t C ha −1 year −1 in SOC, different types of crop rotations and cover crop impacts changed SOC between −0.13 and +0.07 t C ha −1 year −1 and incorporation of harvest by-products (grain straw residuals) led to changes between −0.1 and +0.027 t C ha −1 year −1 in SOC. It is shown on the river basin scale that harvest by-products quantity remaining on the field significantly impact regional SOC dynamics (loss of 0.26 t C ha −1 year −1 when exporting all harvest by-products). The modelled results are in general agreement with studies reported in literature. The extended model is hence able to quantify the impacts of selected land management practices on long-term SOC dynamics and allows land management practices and their impacts on water availability, water quality, carbon storage in soils, and vegetation growth to be assessed in an integrated way.

Modeling impacts of management alternatives on soil carbon storage of farmland in Northwest China

Abstract. Long-term losses of soil organic carbon (SOC) have been observed in many agriculture lands in Northwest China, one of the regions with the longest cultivation history in the world. The decline of SOC contents not only impaired the soil fertility but also increased the amount of carbon dioxide (CO2) emitted from terrestrial ecosystems into the atmosphere. However, quantifying the SOC losses at regional scale has long been remaining unsolved. A process-based model, Denitrification-Decomposition or DNDC, was adopted in the study to quantify impacts of farming management practices on SOC dynamics for a selected region, Shaanxi Province. The selected domain, with 3 million hectares of cropland across different climatic and farming management regimes, is representative for the major agricultural areas in Northwest China. The DNDC model was tested against long-term SOC dynamics observed at five agricultural sites in China. The agreement between the observed and modeled results indicate that DNDC was capable of capturing patterns and magnitudes of SOC changes across the climate zones, soil types, and management regimes in China. To quantify SOC dynamics for Shaanxi, we constructed a GIS database to hold all of the DNDC-required input information (e.g., weather, soil properties, crop acreage, and farming practices) for all the farmland in the studied domain. Sensitivity tests indicated the spatial heterogeneity of soil properties, especially initial SOC content, was the major source of uncertainty for the modeled SOC dynamics at regional scale. The Most Sensitive Factor (MSF) method was employed in the study to quantify the uncertainties produced from the upscaling process. The results from the regional simulations for Shaanxi indicated that (1) the overall 3 million hectares of farmland in the province was a source of atmospheric CO2 with 0.5 Tg C yr−1 lost in 2000 under the current farming management conditions, (2) an increase in the rate of crop residue incorporation from 15% to 50% or 90% converted the farmland from the C source to a C sink with 0.7 or 2.1 Tg C yr−1 sequestered, respectively, and (3) applying farmyard manure at a rate of 500 kg C ha−1 also converted the cropland into a weak C sink with 0.2 Tg C sequestered in the farmland in Shaanxi. In the studied domain, crop residue and farmyard manure used to be the major sources of soil nutrients during the centuries-long cultivation history but were gradually abandoned since 1950s when synthetic fertilizers became available. The results from this modeling study suggest that recovery of the traditional farming practices (i.e., residue incorporation and manure amendment) be a feasible approach to substantially improve the soil C status in the farmland of Shaanxi. The values of C gain or loss from this study for Shaanxi could vary if the modeled domain shifts to other provinces in Northwest China although the general conclusion may remain.

Testing the Suitability of the DNDC Model for Simulating Long-Term Soil Organic Carbon Dynamics in Japanese Paddy Soils

The suitability of the DeNitrification-DeComposition (DNDC) model for simulating long-term changes in the content of soil organic carbon (SOC) was validated using 5 sites for long-term experiments related to Japanese paddy soils. Since the model could not simulate crop growth adequately, several crop growth parameters provided by the model as default were changed to adjust crop growth to the observation. Overall, the changes in the content of SOC with time simulated by DNDC using adjusted crop parameters, agreed well with the observation in 9 plots from 5 experimental sites during the 16 to 22-year period of the experiment. The good performance of the decomposition sub-model in the DNDC was verified in the long-term SOC decomposition in paddy soils as well as in upland soils reported in previous studies. However, the simulated SOC did not agree well with the observation in some plots, especially in soils with a very low SOC content, suggesting that care should be exercised when applying the model to soils with a very low SOC content. Moreover, careful tuning of crop growth parameters should be promoted for better simulation, and detailed information about farm management required for input parameters is often difficult to obtain, especially in long-term experiments. In conclusion, the DNDC model is an effective tool for simulating long-term SOC dynamics in paddy soils. The unique kinetic scheme “anaerobic balloon” in the model may play an important role in successful simulation of SOC dynamics in paddy soils that are water-logged during the rice cropping period. This scheme may be helpful for modifying the other turnover models of soil organic matter for use for paddy soils, too.

Long-term soil organic carbon dynamics in a subhumid tropical climate: 13C data in mixed C3/C4 cropping and modeling with ROTHC

Scanty information on long-term soil organic carbon (SOC) dynamics hampers validation of SOC models in the tropics. We observed SOC content changes in a 16-year continuously cropped agroforestry experiment in Ibadan, south-western Nigeria. SOC levels declined in all treatments. The decline was most pronounced in the no-tree control treatments with continuous maize and cowpea cropping, where SOC levels dropped from the initial 15.4 to 7.3–8.0MgCha−1 in the 0–12 cm topsoil in 16 years. In the two continuously cropped alley cropping (AC) systems, one with Leucaena leucocephala and one with Senna siamea trees, SOC levels dropped to 10.7–13.2MgCha−1. Compared to the no-tree control treatments, an annual application of an additional 8.5Mgha−1 (dry matter) of plant residues, mainly tree prunings, led to an extra 3.5MgCha−1 (∼0.2% C) in the 0–12 cm top soil after 11 years, and 4.1MgCha−1 after 16 years. The addition of NPK fertilizer had little effect on the quantities of above-ground plant residues returned to the soil, and there was no evidence that the fertilizer affected the rate of SOC decomposition. The fact that both C3 and C4 plants returned organic matter to the soil in all cropping systems, but in contrasting proportions, led to clear contrasts in the 13C abundance in the SOC. This 13C information, together with the measured SOC contents, was used to test the ROTHC model. Decomposition was very fast, illustrated by the fact that we had to double all decomposition rate constants in the model in order to simulate the measured contrasts in SOC contents and δ13C between the AC treatments and the no-tree controls. We hypothesized (1) that the pruning materials from the legume trees and/or the extra rhizodeposition from the tree roots in the AC treatments accelerated the decomposition of the SOC present at the start of the experiment (true C-priming), and/or (2) that the physical protection of microbial biomass and metabolites by the clay fraction on this site, having a sandy top soil in which clay minerals are mainly of the 1:1 type, is lower than assumed by the model.