SSS9.3

The young moraine landscape of North-East Germany is highly prone to tillage-dominated soil erosion processes due to highly mechanised farming in a rolling topography. The corresponding soil redistribution pattern highly influences crop biomass production and soil organic carbon (SOC) dynamics. The aims of the study are to understand the effect of soil redistribution processes on SOC dynamics like dynamic replacement and efficient SOC burial. Therefore, an updated version of the spatially explicit soil redistribution and carbon turnover model SPEROS-C was applied for a large-scale (200 km²) simulation of lateral soil and SOC redistribution and vertical SOC turnover (spatial and vertical resolution 5 m x 5 m and 1 m soil depth, respectively). A sensitivity analysis was applied to identify the dominant modulators of SOC in the modelling approach (carbon input by roots, manure, and residues, decomposition of SOC, etc.). Uncertainties in model structure, process parameterisation, and input data are analysed with the GLUE approach (Generalized Likelihood Uncertainty Estimation). This approach is also used to estimate regional model parameters (e.g. SOC turnover rates, crop-specific root length density distribution, C input by aboveground biomass, manure, residues, etc.) to allow landscape-scale estimations of soil redistribution and accompanied C balance and hence, if this leads to a sink or source of CO₂.

How to cite: Öttl, L. K., Wilken, F., Sommer, M., and Fiener, P.: Modulators of soil organic carbon (SOC) stocks and dynamics in an intensively used hummocky landscape in North-East Germany, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2803, https://doi.org/10.5194/egusphere-egu21-2803, 2021.

To meet the growing challenges of food security, sufficient biomass for biorefineries and mitigation of climate change, perennial grass is recommended as an alternative for annual grain crop to increase biomass production while protecting soil C stock. However, the long-term biomass yield production, soil C stock, and ecosystem CO₂ flux are rarely simultaneously evaluated in the same study site, limiting the understanding of C flows in different cropping systems. We compared the annual grain crop triticale (Triticosecale) grown every year since 2012 with the productive perennial grass festulolium (Festulolium braunii) both established in 2012 and festulolium renewed in 2018. Annual yield production, five-year changes in soil C stock, and ecosystem CO₂ fluxes in 2020 are documented. The first five-year field observations showed that festulolium produced 76% more biomass as compared to triticale (grain and straw). Meanwhile, there was an increasing trend of soil C stock in festulolium but a declining trend of soil C stock in triticale across the first five years, despite both changes were statistically non-significant. By having measurements of the complete carbon balance for 2020, we can investigate the carbon cycling of a cereal and a perennial grass crop. The results improve our knowledge in how we can optimize the biomass, yield and carbon stocks.

Keywords: continuous monoculture; perennial grass; biomass production; soil carbon content; ecosystem CO₂ flux

How to cite: Pullens, J. W. M., Chen, J., and Lærke, P. E.: Carbon balance of annual versus perennial cropping systems, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3967, https://doi.org/10.5194/egusphere-egu21-3967, 2021.

Climate change is causing rapid warming at northern high latitudes and disproportionately affecting ecosystem services that northern communities rely upon. In Canada’s Northwest Territories (NWT), climate change is impacting the access and availability of traditional foods that are critical for community health and well-being. With climate change potentially expanding the envelope of suitable agricultural land northward, many communities in the NWT are evaluating including agriculture in their food systems. However, the conversion of boreal forest to agriculture may degrade the carbon rich soils that characterize the region, resulting in large carbon losses to the atmosphere and the depletion of existing ecosystem services associated with the accumulation of soil organic matter. Here, we first summarize the results of 35 publications that address land use change from boreal forest to agriculture, with the goal of understanding the magnitude and drivers of carbon stock changes with time-since-land use change. Results from the literature synthesis show that conversion of boreal forest to agriculture can result in up to ~57% of existing soil carbon stocks being lost 30 years after land use change occurs. In addition, a three-way interaction with soil carbon, pH and time-since-land use change is observed where soils become more basic with increasing time-since-land use change, coinciding with declines in soil carbon stocks. This relationship is important when looking at the types of crops communities are interested in growing and the type of agriculture associated with cultivating these crops. Partnered communities have identified crops such as berry bushes, root vegetables, potatoes and corn as crops they are interested in growing. As berry bushes grow in acidic conditions and the other mentioned crops grow in more neutral conditions, site selection and management practices associated with growing these crops in appropriate pH environments will be important for managing soil carbon in new agricultural systems in the NWT. Secondly, we also present community scale soil data assessing variation in soil carbon stocks in relation to potential soil fertility metrics targeted to community identified crops of interest for two communities in the NWT.  We collected 192 soil cores from two communities to determine carbon stocks along gradients of potential agriculture suitability. Our field soil carbon measurements in collaboration with the partnered NWT communities show that land use conversions associated with agricultural development could translate to carbon losses ranging from 2.7-11.4 kg C/m² depending on the type of soil, agricultural suitability class, and type of land use change associated with cultivation. These results highlight the importance of managing soil carbon in northern agricultural systems and can be used to emphasize the need for new community scale data relating to agricultural land use change in boreal soils. Through the collection of this data, we hope to provide northern communities with a more robust, community scale product that will allow them to make informed land use decisions relating to the cultivation of crops and the minimization of soil carbon losses while maintaining the culturally important traditional food system.

How to cite: Bysouth, D., Turetsky, M., and Spring, A.: Agriculture in the Boreal Forest: Understanding the Impact of Land Use Change on Soil Carbon for Developing Sustainable Community Food Systems, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6071, https://doi.org/10.5194/egusphere-egu21-6071, 2021.

Soil organic carbon (SOC) is essential for soil fertility and further represents a global carbon stock with potential to control atmospheric CO₂ concentrations. Due to intense agricultural management, SOC is decreasing in many parts of the world, meaning that the soils act as CO₂ sources rather than CO₂ sinks, which they could have the capacity to be. Therefore, it is important to identify pertinent agricultural management practices that allow for high productivity, but at the same time allow for carbon sequestration and increase in SOC.

In order to document changes in SOC, it is necessary to monitor SOC over decadal time scales, since changes occur slowly and are small as compared with existing stocks. The SOC content in Danish agricultural soils has been monitored at approx. 10-yr intervals (1986, 1997, 2009) since the first systematic national observations in 1986, where soils were sampled from a national 7 km x 7 km grid.

In 2018, a new sampling campaign was conducted from the national 7 km x 7 km grid and soils were analysed for SOC to 1 m depth. The procedures applied in 2018 allowed for more precise relocation of the sampling points from 2009 as compared to precision obtained during the period from 1986-2009. Further, measurements in 2018 included assessment of soil bulk density and stone content in the upper 0-50 cm, which was not measured previously. Thus, one of the aims of the study was to evaluate how more precise point-specific information on bulk density and stone fractions affected the calculated SOC stocks across different soil types and management practices.

The point-specific bulk density measured in 2018 were on average lower than the bulk densities used previously, which were retrieved from a database of texture-based soil classes. The volumetric stone fraction in the upper 0-50 cm was found to be <5% for roughly 90% of the soils, whereas <3% of the soils had stone fractions of >10%. On average, the inclusion of point-specific bulk density and stone fractions lead to approx. 5% lower SOC estimation, with equal approximmately contribution from the two variables.

How to cite: Harbo, L. S., Olesen, J. E., Liang, Z., and Elsgaard, L.: Stocks and changes in organic carbon in Danish agricultural soils – role of bulk density and stone fractions, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16073, https://doi.org/10.5194/egusphere-egu21-16073, 2021.

Soil carbon sequestration (SCS) has been identified by the IPCC as one of the most promising and cheap methodology to reduce atmospheric CO₂. Moreover, an increase in soil organic carbon (SOC) levels improves soil quality by increasing soil structure (and, hence, resistance to erosion) and promoting soil ecosystems services like water retention, productivity, and biodiversity. Various agricultural techniques are available to increase SOC; among them, crop rotation can improve SOC through soil coverage, changes in water regimes, increase in both carbon inputs, and increase in soil aggregates formation.

SOC dynamic models, such as RothC, have been suggested by the IPCC as a way to evaluate the SCS potentials of different soils. Such models could also be used to evaluate the sequestration potential of different agricultural practices. Moreover RothC allows to estimate the time within which the SOC variation, due to a certain agronomic management, can be considered significant as measurable above a threshold value.

In this study, we evaluated the SOC changes for different crop rotations through direct measurements and RothC modelling, with the objective of: (a) estimating their SCS potential, and (b) propose a robust monitoring methodology for SCS practices. We performed the study in an agricultural field close to Ravenna (Italy) characterized by Cambisols and humid subtropical climate. Soil carbon content was assessed before the setup of the crop rotation, and after 3 years of rotation. A RothC model was calibrated with field data, and used to estimate SOC dynamics to 50 years, in order to assess long-term SCS. The model results were also used to assess the best methodology to estimate the SOC variation significance.

The measured SOC was similar to the equilibrium SOC predicted by the RothC model, on average, for the crop rotations. The measurements showed that the SOC, already low at the beginning of the experiment, further decreased due to the crop rotation practice. Of those tested, the best for SCS involves the following crops: corn, soybeans, wheat on tilled soil, and soybeans; while the worst is with corn, wheat on tilled soil, and wheat on untilled soil. However, the SOC variations predicted by RothC for the various rotations were too small to be observable in the field during experimentation. This could be due both to the uncertainty associated with SOC sampling and analysis, and to the short duration of the experiment. The moving average computations on the simulation values allowed us to assess the time required to measure the long-term trend of SOC variation as significant with respect to the environmental background, instrumental error, and SOC periodic fluctuations. That time was estimated to range from 8 to 50 years, changing depending on the rotation type. Periodic fluctuations in SOC should be carefully considered in a monitoring protocol to assess SCS.

How to cite: Balugani, E., Maines, M., Zannoni, D., Buscaroli, A., and Marazza, D.: Soil carbon sequestration through crops rotation in a Mediterranean Cambisols: measurement and modelling, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6372, https://doi.org/10.5194/egusphere-egu21-6372, 2021.

Increasing soil organic carbon (SOC) in agro-ecosystems enables to address simultaneously food security as well as climate change adaptation and mitigation. Croplands represent a great potential to sequester atmospheric C because they are depleted in SOC. Hence, reliable estimations of SOC deficits in agro-ecosystems are crucial to evaluate the C sequestration potential of agricultural soils and support management practices. Using a 30-year old soil monitoring networks with 250 sites established in western Switzerland, we identified factors driving the long-term SOC dynamics in croplands (CR) and permanent grasslands (PG) and quantified SOC deficit. A new relationship between the silt + clay (SC) soil particles and the C stored in the mineral-associated fraction (MAOMC) was established. We also tested the assumption about whether or not PG can be used as carbon-saturated reference sites. The C-deficit in CR constituted about a third of their potential SOC content and was mainly affected by the proportion of temporary grassland in the crop rotation. SOC accrual or loss were the highest in sites that experienced land-use change. The MAOMC level in PG depended on the C accrual history, indicating that C-saturation level was not coincidental. Accordingly, the relationship between MAOMC and SC to determine soil C-saturation should be estimated by boundary line analysis instead of least squares regressions. In conclusion, PG do provide an additional SOC storage capacity under optimal management, though the storage capacity is greater for CR.

How to cite: Guillaume, T., Makowski, D., Libohova, Z., Bragazza, L., and Sinaj, S.: Soil organic carbon dynamics and sequestration potential in cropland-grassland agro-ecosystems, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12465, https://doi.org/10.5194/egusphere-egu21-12465, 2021.

Mediterranean and humid subtropical climate is characterized by hot summer and cold to mild winter with a medium-low soil organic carbon (SOC) content and high risk of land desertification. Recent EU policies pointed out the need to preserve the SOC stock and to enhance its accumulation by promoting the adoption of conservation agriculture (CA) as an efficient action for climate change adaptation and mitigation. The meta-analysis is a powerful data analysis tool, which can be useful to evaluate the effectiveness of CA in increase SOC in comparison with conventional agriculture. In fact, this topic has been addressed by several published articles even though the methodology shortcomings make sometimes difficult to draw reliable conclusions about the contribution of CA. In our work, we applied a robust methodology to comply with the meta-analytic assumptions, such as an independence of effect sizes and weighting, as well as the requirement to use no predictive functions like pedotransfer. Therefore, the present meta-analysis defines a conservative and replicable approach to deal with soil carbon data, explaining the differences between conventional (control) and CA management (treatment) in terms of SOC stock accumulation in the first 0-0.3 m layer. A defined methodology was developed to summarize carbon data within a unique soil layer taking into account the real variance and correlation between different initial soil carbon layers. A final database of 49 studies has been used to summarize the effect and to explain the heterogeneity across studies, including also several pedoclimatic moderators in the analysis. An overall positive effect of about 13 % change in SOC accumulation was found due to CA practices compared to control. To better explain the data variability, we created two different groups of studies ("low carbon in control, LC" and "high carbon in control", HC) base on the amount of SOC in control (with 40 Mg ha^-1 as a threshold). This method leads to more reliable conclusions that it is more likely to find a response to CA management in soil with low carbon content rather than in soil that have more than 40 t C stock ha^-1 . A positive correlation was also found between clay soils with high carbon content in control and carbon sequestration event though the texture classification did not explain data variability. Agronomic management plays an essential role in inducing C accumulation under CA in both LC and HC groups, especially with high residue retention during long-term experiments (0.21 Mg C ha^-1 yr^-1 for the whole database). We also found that climatic and geographical moderators can explain the variability among the effect sizes, like the absolute value of latitude or the precipitation during the year, even though the different continent or climate Köppen classification did not give significant results.

How to cite: Tadiello, T., Acutis, M., Perego, A., Schillaci, C., and Valkama, E.: Can Conservation Agriculture Enhance Soil Organic Carbon Sequestration In Mediterranean And Humid Subtropical Climates? A Meta-Analysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12243, https://doi.org/10.5194/egusphere-egu21-12243, 2021.

Legacy data are frequently unique sources of data for the estimation of past soil properties. With the rising concerns about greenhouse gases (GHG) emission and soil degradation due to intensive agriculture and climate change effects, soil organic carbon (SOC) concentration might change heavily over time.

When SOC changes is estimated with legacy data, the use of soil samples collected in different plots (i.e., non-aligned data) may lead to biased results. The sampling schemes adopted to capture SOC variation usually involve the resampling of the original sample using a so called paired-site approach.

In the present work, a regional (Sicily, south of Italy) soil database, consisting of N=302 georeferenced soil samples from arable land collected in 1993 [1], was used to select coinciding sites to test a former temporal variation (1993-2008) obtained by a comparison of models built with data sampled in non-coinciding locations [2]. A specific sampling strategy was developed to spot SOC concentration changes from 1994 to 2017 in the same plots at the 0-30 cm soil depth and tested.

To spot SOC changes the minimum number of samples needed to have a reliable estimate of SOC variation after 23 years has been estimated. By applying an effect size based methodology, 30 out of 302 sites were resampled in 2017 to achieve a power of 80%, and an a=0.05.

After the collection of the 30 samples, SOC concentration in the newly collected samples was determined in lab using the same method

A Wilcoxon test applied to the variation of SOC from 1994 to 2017 suggested that there was not a statistical difference in SOC concentration after 23 years (Z = -0.556; 2-tailed asymptotic significance = 0.578). In particular, only 40% of resampled sites showed a higher (not always significant) SOC concentration than in 2017.

This finding contrasts with a previous SOC concentration increase that was found in 2008 (75.8% increase when estimated as differences of 2 models built with non-aligned data) [2], when compared to 1994 observed data (Z = -9.119; 2-tailed asymptotic significance < 0.001).

Such a result implies that the use of legacy data to estimate SOC concentration changes need soil resampling in the same locations to overcome the stochastic model errors. Further experiment is needed to identify the percentage of the sites to resample in order to align two legacy datasets in the same area.

Bibliography

[1]Schillaci C, et al.,2019. A simple pipeline for the assessment of legacy soil datasets: An example and test with soil organic carbon from a highly variable area. CATENA.

[2]Schillaci C, et al., 2017. Spatio-temporal topsoil organic carbon mapping of a semi-arid Mediterranean region: The role of land use, soil texture, topographic indices and the influence of remote sensing data to modelling. Sci Total Environ. 

How to cite: Schillaci, C., Saia, S., Lipani, A., Perego, A., Zaccone, C., and Acutis, M.: Matching legacy estimation of soil organic carbon changes from non-paired data with measured values in paired soil samples after two decades: a case study, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10639, https://doi.org/10.5194/egusphere-egu21-10639, 2021.

In calcareous Mediterranean soils, pedogenic and lithogenic carbonates can be important constituents of the soil matrix. However, their relative proportion and their relation to soil functioning has been scarcely studied. The interest in determining the proportion of pedogenic carbonates relies on the fact that they can be related to the physical, chemical and biological properties of the soil and, therefore, affect plant growth and soil productivity. Carbonates dynamics can be affected by some farming management practices and land-use changes, such as the adoption of irrigation, due to changes in the soil water regime, the composition of the soil solution, the concentration of CO₂ in the soil atmosphere, and the changes related to fertilization.

To gain knowledge on the importance of the effect of the introduction of irrigation on carbonates dynamics in the tilled layer of agricultural soils, we studied the evolution of the proportion of pedogenic carbonates in a Mediterranean calcareous soil after seven years of irrigation. We used the isotopic signature of C in soil carbonates for these estimations. The study was conducted in two plots under contrasting agricultural management on the same soil unit: dryland wheat cropping, and irrigated corn for 7 consecutive years, in Enériz (Navarre, Spain).

Our results showed that the transformation of dryland wheat to irrigated corn, produced a preferential accumulation of pedogenic carbonates (31-56%) in the tilled layer (0-30 cm) of the irrigated soil only over 7 years after the land-use change. Therefore, the processes related to this land use change can alter the soil carbonates dynamics in a very short period of time, and they may have consequences in terms of plant nutrient dynamics and the soil structure. Future research on the origin of the soil carbonates (pedogenic or geogenic) in agricultural soils will help to understand the actual significance of carbonates dynamics in terms of the global C balance in these soils.

How to cite: De Soto, I. S., Virto, I., Enrique, A., Antón, R., Barré, P., and Zamanian, K.: Pedogenic carbonates accumulation in a calcareous Mediterranean soil following introduction of irrigation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8479, https://doi.org/10.5194/egusphere-egu21-8479, 2021.

CO₂ emissions triggered by anthropogenic and natural activities contribute to climate change, one of the current environmental threats of public and scientific concern. At present, microbially-induced biomineralization of CO₂ by calcium carbonate (CaCO₃) is one of the highly topical study subjects as carbon stabilization process. In the present study we focused our attention on the calcifying bacteria of “living rocks”. The origin of these concretions, composed by a silicate skeleton of quartz and feldspars, merged by massive carbonate concrete, has so far been recognized as abiotic. Within this study we investigated the role of calcifying bacteria in their formation of these concretions and we isolated and characterized the species with CaCO₃ precipitation abilities. Concretions were sampled in Romania (Trovant) and Italy (Sibari and Rome). Samples were first analyzed for their culturable microflora (i.e. isolation, CaCO₃ precipitation capability and molecular characterization). Then, in vitro regeneration tests were carried out to confirm the contribution of bacteria in the formation of these erratic masses. Moreover, natural samples and bioliths regenerated in vitro were (i) observed and analyzed by scanning electron microscopy (SEM-EDS) and (ii) characterized at molecular level by DNA extraction and 16S rRNA analysis (V3-V4 regions). By isolating and characterizing the culturable microflora, we obtained 19 calcifying isolates, with different morphological, bacteriological and mineral precipitation properties. These evidences have given a first relevant contribution for the definition of the biotic role to the formation of these concretions. These evidences were confirmed by the efficient in vitro regeneration and SEM-EDS analysis. The molecular identification of the isolates and the comparison of the data obtained from the Illumina sequencing with those present in the literature, allowed us to hypothesize the genera that most likely contributed to the formation of these concretions. The results obtained provide a good scientific basis for further studies, which should be directed towards the use of isolates in studies of environmental and socio-economic relevance. Several studies demonstrate that microbially mediated biomineralization has the potential to capture and sequester carbon. Calcium carbonate, is a stable pool of carbon and is an effective sealant to prevent CO₂ release back into the atmosphere.

How to cite: del Gallo, M., Mignini, A., Moretti, G., Pellegrini, M., and Cacchio, P.: Isolation and characterization of calcifying bacteria from “living rocks”: a possible carbon sink, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8538, https://doi.org/10.5194/egusphere-egu21-8538, 2021.

Mid-Infrared reflectance spectroscopy (MIRS, 4000 – 400 cm^-1) is being considered to provide accurate estimations of soil inorganic carbon (SIC) contents. Usually, the prediction performances by MIRS are analyzed using figures of merit based on entire test datasets characterized by large SIC ranges, without paying attention to performances at sub-range scales. This work aims to 1) evaluate the performances of MIR regression models for SIC prediction, for a large range of SIC test data (0-100 g/kg) and for several regular sub-ranges of SIC values (0-5, 5-10, 10-15 g/kg, etc.) and 2) adapt the prediction model depending on sub-ranges of test samples, using the absorbance peak at 2510 cm^-1 for separating SIC-poor and SIC-rich test samples. This study used a Tunisian MIRS topsoil dataset including 96 soil samples, mostly rich in SIC, to calibrate and validate SIC prediction models; and a French MIRS topsoil dataset including 2178 soil samples, mostly poor in SIC, to test them. Two following regression models were used: a partial least squares regression (PLSR) using the entire spectra and a simple linear regression (SLR) using the height of the carbonate absorbance peak at 2150 cm^-1.

First, our results showed that PLSR provided 1) better performances than SLR on the Validation Tunisian dataset (R²_test of 0.99 vs. 0.86, respectively), but 2) lower performances than SLR on the Test French dataset (R²_test of 0.70 vs. 0.91, respectively). Secondly, our results showed that on the Test French dataset, predicted SIC values were more accurate for SIC-poor samples (< 15 g/kg) with SLR (RMSE_test from 1.5 to 7.1 g/kg, depending on the sub-range) than with PLSR prediction model (RMSE_test from 7.3 to 14.8 g/kg, depending on the sub-range). Conversely, predicted SIC values were more accurate for carbonated samples (> 15 g/kg) with PLSR (RMSE_test from 4.4 to 10.1 g/kg, depending on the sub-range) than with SLR prediction model (RMSE_test from 6.8 to 14 g/kg, depending on the sub-range). Finally, our results showed that the absorbance peak at 2150 cm^-1 could be used before prediction to separate SIC-poor and SIC-rich test samples (452 and 1726 samples, respectevely). The SLR and PLSR regression methods applied to these SIC-poor and SIC-rich test samples, respectively, provided better prediction performances (R²_test of 0.95 and RMSE_test of 3.7 g/kg).

Finally, this study demonstrated that the use of the spectral absorbance peak at 2150 cm^-1 provided useful information on Test samples and helped the selection of the optimal prediction model depending on SIC level, when using calibration and test sample sets with very different SIC distributions.

How to cite: Gomez, C., Chevallier, T., Moulin, P., and Barthès, B. G.: Using absorbance peak of carbonate to select suitable regression model before predicting soil inorganic carbon concentration by mid-infrared reflectance spectroscopy, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15601, https://doi.org/10.5194/egusphere-egu21-15601, 2021.