SSS9.7

Conservation tillage has been widely applied to improve soil health, sustain crop production, and promote carbon (C) sequestration in soil. Positive effects often depend on the degree of tillage intensity and time of adoption. This study was thus aimed to determine temporal changes of selected soil health indicators under different tillage intensities in a long-term tillage trial.

Accordingly, bulk and rhizosphere soil samples were taken after 8 and 13 years of adoption from topsoil under four different tillage systems ranging from conventional (high intensity), reduced, minimum, to no-tillage (low intensity).  Aggregate stability and soil fungal indicators (ergosterol and glomalin-related soil protein) were analysed. Soil organic carbon stocks were assessed at 10 and 13 years of adoption. To determine long-term effect of tillage on soil microbial necromass accumulation, amino sugars were measured after 13 years of adoption.

Aggregate stability and soil fungal indicators increased with lower tillage intensity for both sampling time points. Conservation tillage practices promoted the accumulation of soil organic carbon and microbial necromass. Interestingly, among conservation tillage practices, the soil fungal indicators showed highest values for reduced and minimum tillage compared to no-tillage at 13 years of adoption. This suggests that fungal growth could potentially benefit from slight soil disturbance in the long-term. Therefore, reduction of tillage intensity evidently improved soil health by promoting soil carbon sequestration and aggregate stability via fungal growth as well as soil microbial necromass accumulation.

Conventional tillage is most detrimental to soil health indicators, while reduced tillage seem to promote soil biological processes via gentle mixing of soil substrate. Instead, no-tillage is most beneficial to aggregate stability but not for fungal indicators.  

How to cite: Sae-Tun, O., Bodner, G., Rosinger, C., Weninger, T., Zechmeister-Boltenstern, S., Mentler, A., and Keiblinger, K.: Conservation tillage practices facilitate soil organic carbon sequestration and aggregate stability via fungal abundance and necromass, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2206, https://doi.org/10.5194/egusphere-egu22-2206, 2022.

In this study we used the biogeochemical model ECOSSE-6.2b _[1] in site-specific mode to evaluate/test model accuracy to estimate soil organic carbon (SOC) in Irish grassland systems under mineral soils. The selection of sites and management practices, as well as model inputs and model initialization followed procedures explained in Premrov et al. (2021) and (2020) _[2],[3]. Results indicated a possible overestimation of modelled SOC for some grassland management categories, highlighted the sensitivity of the model to the initial SOC inputs and demonstrated the need for replicated measurements of SOC over time _[4]. One of the challenges faced in this study was the lack of availability of site-specific data for the selected Irish sites, such as data on livestock stocking rates (SR) for grazed grasslands, which can differ greatly from year to year. SR could be only estimated as a single numeric value for each site, which demonstrated the need for greater availability and more detailed site-specific data for Irish grasslands. The availability of repeated measurements of SOC over time for the whole country represented another major challenge in modelling SOC for Irish grassland systems _[4]. It is thought that the modelling undertaken here could be further enhanced using additional time-dependent SOC soil-point data, such as LUCAS data _[5], as this would provide datasets that have repeated measurements of SOC needed for further model evaluation and parameterization. This work also showed a significant potential for further model improvement; grazing-induced vegetation changes, and associated impacts on SOC, could be accounted by introducing new types of grazed grassland vegetation parameters into the ECOSSE model _[4]. These modelling opportunities could also have significant potential for further assessment of SOC dynamics and for spatial and temporal upscaling.

Acknowledgements

SOLUM project is funded under the Irish EPA Research programme 2014-2020.

Literature

[1] Smith, J., et al. (2010). ECOSSE. User Manual.

[2] Premrov, A., et al. (2021). Insights into ECOSSE modelling of soil organic carbon at site scale

from Irish grassland sites and a French grazed experimental plot. EGU21-1879. https://doi.org/10.5194/egusphere-egu21-1879; (CC BY 4).

[3] Premrov, A., et al. (2020). Insights into modelling of soil organic carbon from Irish grassland sites using ECOSSE model. EGU2020-8090. doi.org/10.5194/egusphere-egu2020-18940; (CC BY 4).

[4] Saunders, M. et al. (2021) Soil Organic Carbon and Land Use Mapping (SOLUM) (2016-CCRP-MS.40). EPA Research Report.

[5] JRC (2020). LUCAS 2015, ESDAC. JRC. EC.

How to cite: Premrov, A., Zimmermann, J., Dondini, M., Green, S., Fealy, R., Fealy, R., Decau, M.-L., Klumpp, K., Afrasinei, G. M., and Saunders, M.: ECOSSE biogeochemical modelling of soil organic carbon from Irish grassland systems - challenges and opportunities, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2944, https://doi.org/10.5194/egusphere-egu22-2944, 2022.

Forest soils contain a large amount of carbon and play an important role in its global cycle. As forest soil organic carbon (SOC) mineralization is one of the major sources of atmospheric carbon, small changes of SOC can have effects on climate. Therefore, the Rural Development Programme (RDP) of Emilia-Romagna Region (Northeastern Italy) financed our SuoBo project, which aims to assess and preserve the quantity and quality of soil organic matter (SOM) in mountainous forest ecosystems located on the Apennine chain of the Emilia-Romagna Region. Our specific goal was to explore the response of SOC pools to forest thinning under two vegetation types. For this purpose, a chestnut forest of Beghelli farm (BEG), located at about 550 m a.s.l., and a mixed forest of Branchicciolo farm (BRA), located at about 225 m a.s.l, were selected. Soil samples were collected from each forest stand at 0-15 cm and 15-30 cm depths, in October 2020 in both farms and then in July 2021 in BRA farm and September 2021 in BEG farm. The soil samples were analyzed for the elemental contents and isotopic ratios (δ¹³C) of the soil total (TC), organic (SOC) and inorganic (SIC) carbon using an elemental analyzer coupled with an isotope ratio mass spectrometer. In October 2020, forest soil in BRA had higher TC, SOC, and SIC content in 0-30 cm (average: 7.1, 4.8 and 2.3 wt%, respectively) than in BEG (3.0, 2.8 and 0.1 wt%, respectively). The δ¹³C_TC of the BRA soil is less negative than that of the BEG farm (–17.3‰ and –25.9‰, respectively) due to the higher SIC content, inherited by the parent rock mainly composed by limestones. In 2021, after one year since the thinning intervention, the TC and SOC contents in BEG soil were like those recorded in 2020, whereas those in BRA soils showed lower values. In particular in the superficial layer of BRA soils (0-15 cm), the SOC decreased from 6.9% to 4.1% in 2020 and 2021, respectively, while SIC content was unchanged (2.0 vs 2.1 wt%). Even in the deepest layer (15-30 cm) SIC remained the same over time (2.5 vs 2.4 wt%), while SOC decreased (2.5 vs 1.2 wt%). Also, the changes of δ¹³C_SOC underlined a loss of organic matter from 2020 to 2021 (0-15 cm: –27.0 vs –26.2‰; 15-30 cm: –26.2 vs –25.9‰). Different concomitants may be contributing to this significant decrease in SOC: a) the different period of soil sampling (autumn vs summer), considering that the year 2021 is one of the seven warmest years on record globally and BRA has a lower altitude than BEG; b) the high slope (>45°) and the triggering of erosion process after the thinning intervention, which took away the surface soil, mainly characterized by organic hemitransformed horizons (e.g., Oe horizons). The future planned analyses of the quality of the SOM through i) chemical extraction and separation of the different humic fractions and ii) stability of the C fractions at different temperatures with a SoliTOC analyzer will shed a light on the prevailing phenomenon.

How to cite: Brombin, V., Salani, G. M., Mistri, E., De Feudis, M., Falsone, G., Vittori Antisari, L., and Bianchini, G.: Organic and inorganic carbon in managed forest soils of the Emilia-Romagna Region (Northeastern Italy), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3667, https://doi.org/10.5194/egusphere-egu22-3667, 2022.

Terrestrial ecosystems play a significant role in global warming by regulating CO₂ concentration in the atmosphere. A comprehensive understanding of carbon (C) sources and stocks in soils, as well as the driving mechanisms, are critical to reducing CO₂ emission from soil and thus mitigating climate change. To date, most studies have solely focused on processes involving soil organic C (SOC), but few studies have addressed the potential contribution of soil inorganic C (SIC) mostly CaCO₃ pool to ecosystem C fluxes. SIC can potentially be a regulator of atmospheric CO₂. However, so far the effects of plant species (i.e. variations in nitrogen (N) demand and N use efficiency (NUE)) as well as soil temperature on SIC-derived CO₂ are unclear. We hypothesized that 1) relatively less SIC-derived CO₂ is expected from soils covered under plant species with lower N demand and higher NUE. We conducted a 4-month field experiment from June to October 2021 at the research station of the University of Göttingen in Deppoldshausen (51.58^oN, 9.97^oE) with ca. 6% CaCO₃ equivalent in the topsoil. We analyzed the effects of two plant species 1) wheat (high N demand and low NUE), 2) legume (low N demand and high NUE) and two N fertilization (urea) levels, 1) low (50 kg N ha^-1), 2) high (200 kg N ha^-1) on CO₂ emission out of SIC. Each treatment had four replicate plots (1×1 m²), and at least a 0.5 m gap was established between plots. We measured CO₂ fluxes weekly by using the static chamber method. The δ¹³C natural abundance was used to determine the contribution of SIC and SOC in the emitted CO₂. The total CO₂ emission and its δ¹³C signature increased with soil temperature, indicating that the portion (%) of SIC-derived CO₂ was stimulated by temperature (^oC) (slope = 0.33). The portion of SIC-derived CO₂ stimulated by temperature increased faster under wheat than under legume (slope = 0.36 vs. 0.26), especially under high N treatment (slope = 0.65 vs. 0.54). The portion of SIC-derived CO₂ under wheat (13.0%) was higher than that under legume (11.3%). Moreover, the portion of SIC-derived CO₂ was 1.2% higher under wheat than under legume at high N fertilization level, whereas it was increased to 2.2% under low N fertilization. This indicates a significant role of plant species with different N demand and NUE on dynamics of SIC pool and its contribution in CO₂ emission from soil. The rate of SIC-derived CO₂ was comparable between wheat and legume under high N fertilization, but it was 1.6 times higher under wheat than that under legume at low N fertilization. The contribution of SIC-derived C to the atmosphere was ~63.7 g C m^-2 yr^-1 under legume with low N demand vs. ~82.1 g C m^-2 yr^-1 under wheat with high N demand. In this regard, the impacts of plant species and their N demand and NUE are important controlling factors determining the dynamics of the SIC pool in agroecosystems.

How to cite: Fan, L., Tao, J., Shao, G., Ai, J., and Zamanian, K.: Nitrogen use efficiency of plant species matters: CO2 emission from soil inorganic carbon and its temperature dependence in a calcareous soil, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5018, https://doi.org/10.5194/egusphere-egu22-5018, 2022.

Soil organic carbon (SOC) accumulation in agroecosystems is a promising solution to simultaneously improve food security and mitigate climate change. Indeed, because of their large carbon deficit, cropland soils can potentially sequester a substantial amount of atmospheric carbon (C). To estimate the soil C-sequestration potential, it is critical to derive reliable estimations of the current soil C-saturation level. This step is essential to obtain an accurate quantification of C-deficits in cultivated soils. In addition, it is important to identify agricultural practices that favor SOC accumulation in order to reduce the soil C-deficit. Based on a 30-year old soil monitoring network of multiple cropland (CR) and permanent grassland (PG) sites established in western Switzerland, we (i) quantified the C-deficit in croplands, (ii) identified the factors driving the C-deficit and (iii) evaluated the assumption that grasslands can be used as C-saturated reference sites. We demonstrated that SOC in CR were depleted by a third compared to PG. The main factor affecting C-deficit in CR was the proportion of temporary grasslands (TG) within the crop rotation. We also showed that PG have not reached their C-saturation level in the study area and that additional C could be stored in PG soil under optimal management. When accounting for pedo-climatic differences, the C-deficit of CR that do not include TG in the rotation was equivalent to 3 kg C m^-2 down to 50 cm depth. The relationship between the proportion of TG in the rotation and SOC stocks in the topsoil (0-20 cm) and subsoil (20-50 cm) was linear and similar at both depths, revealing the strong potential of the subsoil to sequester C.

How to cite: Guillaume, T., Makowski, D., Elfouki, S., Bragazza, L., Libohova, Z., and Sinaj, S.: Increasing topsoil and subsoil organic carbon storage with improved rotation in cropland-grassland agroecosystems, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5184, https://doi.org/10.5194/egusphere-egu22-5184, 2022.

Soil acidification has increasingly become a critical issue for sustainable production due to the excessive nitrogen (N) fertilization in agricultural systems. Application of N fertilizers and the consequent nitrification yield protons (H⁺), which strongly and irreversibly accelerate dissolution of soil inorganic carbon (SIC) e.g., CaCO₃, leading to CO₂ release in the atmosphere. Here, ¹⁴C-labeled CaCO₃ was added to calcareous soil (0.75% CaCO₃) to investigate the effects of chicken manure, urea, NH₄NO_3, KNO₃ and (NH₄)₂SO₄ on soil acidification and to estimate the SIC contribution to CO₂ emission. 250 mL gas-tight jars were filled with a cropland soil (pH = 7.2), homogenously mixed with 1.3% Ca¹⁴CO₃ powder (¹⁴C activity = 11.3 kBq pot^-1). Following fertilization in rates of 0.1, 0.15, 0.25 g N kg^-1 soil, NaOH was applied to trap the emitted CO₂ and to determine ¹⁴C activity. CaCO₃ addition increased soil pH values by 0.17-0.43 units. Addition of ammonium-based fertilizers ((NH₄)₂SO₄, NH₄NO₃) strongly decreased pH up to 0.3 units. All fertilizers increased CO₂ emission (5.1%-180%) compared to the unfertilized soil after 44 days of incubation except KNO₃. SIC-originated CO₂ due to fertilization was ranged from 2.9 to 160 mg C kg^-1 (1.1% to 48% of total emitted CO₂). Manure and urea had lowest impacts on SIC-driven CO₂ during the first 5 days (2.9-34 mg C kg^-1) irrespective of the application rate. Thereafter, the effects of fertilizers on SIC-originated CO₂ increased in the order: urea < manure < KNO₃ < NH₄NO₃ < (NH₄)₂SO₄. As nitrification of (NH₄)₂SO₄ yields in 4 mol H⁺, which neutralizes 2 mol carbonates, it initially caused the highest SIC-originated CO₂ until 9 days. Urea and NH₄NO₃ release by nitrification 2 mol H⁺ per mole of fertilizer, but urea initially hydrolyses to NH₄OH, which increases soil pH. So, urea addition had the minimum SIC loss as CO₂ in the first 5 days, but starting from 16^th day, CO₂ emission sharply increased and reached to highest values among the fertilizers. Manure increased SIC-originated CO₂ emission from 23^rd day of incubation. Gradual and incomplete mineralization of organic N of chicken manure duration 44 days explains the smallest released CO₂ from CaCO₃ and slowest acidification in the first 16 days. Furthermore, Ca²⁺ and Mg²⁺ in manure may be precipitated as carbonates, which decrease the SIC share in the emitted CO₂. Generally, the higher the applied fertilizer amounts, the larger was the proportion of CO₂ released from SIC. Both the fertilizer chemistry and the application rate played significant roles in dissolution of carbonates. Summarizing, the correct selection of the type and amount of fertilizers based on soil properties and plant demand is necessary to decrease SIC-originated CO₂ emission to mitigate global warming, and also save various ecosystem services such as organic matter stability and increase C sequestration.

How to cite: Tao, J., Fan, L., Zhou, J., Kuzyakov, Y., and Zamanian, K.: Nitrogen fertilizers control CO2 emission from calcareous soils: implications for land management and global warming, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5503, https://doi.org/10.5194/egusphere-egu22-5503, 2022.

The effects of environmental change on ecosystem dynamics is nowadays a major research question. Soil organic carbon (SOC) models are integrated into many ecosystem models for projecting the effects of these changes in the achievement of land degradation neutrality. The  Rothamsted Carbon (RothC) model, initially developed to simulate the effects of different practices for long-term agricultural experimental sites, can be successfully used to monitor and project the SOC indicator of land degradation. Here, continuous and discrete versions of the RothC model are firstly compared on classical long-term experiments carried out at the Rothamsted Experimental Station; then a non-standard monthly time stepping procedure is used to evaluate the response of the model to changes of temperature, Net Primary Production (NPP), and land use soil class (forest, grassland, arable)  in the protected areas of Alta Murgia National Park in the Italian Apulia region and Magura National Park in Polish Subcarpathian Voivodeship.  

How to cite: Marangi, C., Diele, F., Luiso, I., Martiradonna, A., and Wozniak, E.: SOC indicator of land-degradation: responses of continuous and non-standard discrete RothC  models to environmental changes , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5894, https://doi.org/10.5194/egusphere-egu22-5894, 2022.

In the LANDSUPPORT project (H2020-RUR-2017-2/No. 774234), we have developed a web-based “Best Practices tool” that runs on the fly (https://dev.landsupport.eu/template.html) to identify optimized solutions for enhancing soil fertility and reducing nitrate leaching. The tool works at a regional scale (average area of approximately 2500 km²) in three case studies (Marchfeld – Austria, Campania Region – Italy, Zala County – Hungary) with a what-if scenario approach. The tool is dynamically linked to the ARMOSA process-based model, which simulates at a daily time step many combinations of farming systems (conservation, organic, conventional), crops, nitrogen fertilization rates, tillage solutions, crop residues management (up to 2520 combinations). ARMOSA simulates crop growth, soil water dynamics, nitrogen and carbon cycling.

The tool is meant to be applied by public authorities, such as regional environmental agencies, to find the best solutions out of feasible management practices according to the overall goal (e.g., increase in soil organic carbon stock, reduction of nitrate leaching) or by farmers who want to evaluate the crop production under current and optimized management.

The user defines the region of interest (ROI). To this ROI the tool automatically associates the soil profiles, having properties (texture, initial soil organic carbon, bulk density) described for each horizontal layer.

For a given region of interest within the case study being characterized by specific soil properties, the user sets the combination of agronomic practices with the interface: climate scenario (20 years), crops, system, fertilization rates, residues management, tillage, and the use of cover crops. The user-friendly interface hides the high complexity of the soil and crop processes which are simulated by ARMOSA, which has many crop and soil parameters. Parameters have been calibrated using the dataset available in the project and in previous studies.

For each of the simulated soils and scenarios, the tool returns the mean annual value of (1) the crop yield, (2) the nitrate leaching at the bottom of the soil profile, and (3) the change of the soil organic carbon stock in the upper soil layer (0-0.4 m). The tool also provides the value of the synthetic “best practices index” (I_BP) that is computed as a linear combination of the three variables and the weights that the user dynamically assigns to each of the variables according to the specific goal (e.g., increase in soil organic carbon). The user can then sort by descending order the I_BP values to identify the most suitable solutions (i.e., combinations of practices). The mean value of I_BP is plotted in charts for each of the simulated combinations.

Due to the link to the ARMOSA process-based model, the tool offers the great opportunity of a close representation of actual and optimized cropping systems with the possibility of further applications at a larger scale (e.g., European scale), in other regional case studies, and in tailored scenarios in which the user enters her/his own data of soil properties and climate. 

How to cite: Perego, A., Acutis, M., Botta, M., Tadiello, T., Langella, G., Terribile, F., Bancheri, M., and Basile, A.: The LANDSUPPORT best practices tool identifies optimized solutions for the health of agricultural soils, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10997, https://doi.org/10.5194/egusphere-egu22-10997, 2022.

Peatlands play a crucial role in the global carbon cycle and are a major ecosystem with potential to remove greenhouse gases from the atmosphere. Ombrotrophic peatlands constitute the largest soil organic carbon (SOC) stock in Republic of Ireland (ROI) and cover an estimated 20% of the land surface. Peatland nitrogen (N) stock remains unknown, despite its crucial role in peatland degradation with subsequent nitrous oxide (N₂O) emissions and eutrophication of downstream ecosystems. Land use impacts are major drivers of both peatland carbon and N stock degradation and disturbance of the peatland carbon sink function. Hence, in the context of this research it is assumed that past and present land use activity, including afforestation, grazing, and domestic and industrial peat extraction for energy and horticultural use, are likely to affect peat SOC and N stocks.

To date, estimation of the peat SOC-stock in ROI was based on non-directly measured values of SOC-concentration, dry bulk density and peat depth. In this study, these properties were measured for the first time along the entire peat soil profile at national scale across the major ombrotrophic peatland types and land uses. A predictive modeling approach, which compared linear and additive mixed-effects models, formed the basis for quantifying SOC and N stocks. The approach encompassed a model evaluation that used an iterative data-splitting algorithm, combined with an assessment of the bias-variance trade-off.

Our results depict a similar pattern for both SOC and N stocks, with mean stock estimates (t ha^-1) largest for near-natural bogs. The largest total amount (Mt) of SOC and N was stored in bogs (recently) used for domestic peat extraction. Stock calculations based on modelled SOC and N values resulted in initial estimates for the entire national peatland area and peatland type-land use strata of Irish peatlands. They revealed that national peatland SOC is nearly twice as large as previously calculated. Mixed-model analysis of main stock determinants revealed major influence of peat depth for quantification of stocks. It confirmed that land use exerts a strong influence on bulk density and SOC, whereas peat depth was found to be strongly associated with land use category.

The presented approach allowed quantification of SOC and N stocks for larger areas based on clustered soil data. It provided a methodology for identifying the best performing model to be implemented in stock assessments, thereby avoiding under- or over-parameterization. The study fills a gap in peat SOC quantification in ROI by updating existing uncertain estimates for peat SOC stock, and by providing the first estimates for national ombrotrophic peat N stock, based on measured covariates.

How to cite: Walz, K., Renou-Wilson, F., Wilson, D., and Byrne, K. A.: Estimation of soil organic carbon and nitrogen stocks in Irish peatlands using a predictive modeling approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12599, https://doi.org/10.5194/egusphere-egu22-12599, 2022.