ABSTRACT. The presentation:

• Recalls why a EU law is needed on soil
• Outlines the main elements of the Commission proposal and the main changes proposed by the Parliament and the Council
• Indicates the remaining main legislative steps
• Stresses the need to reinforce a science policy interface and build together the capacity for an effective implementation of the law towards healthy soils

ABSTRACT. New frontiers in soil health knowledge

ABSTRACT. Healthy soils are essential for sustainable food production, achieving climate neutrality and halting the loss of biodiversity. The European Commission turned the spotlights on these vital aspects of soils with the launch of the EU Soil Observatory (EUSO) in 2021 to support the European Green Deal. Also, the EU Soil Strategy for 2030 and the proposed Soil Monitoring Law marked a major milestone for soil protection.  Through its activities, the EUSO supports an EU-wide soil monitoring system and provides policy support to a wide range of policy areas (including Soil Monitoring Law, Carbon farming certification, HORIZON Europe and Soil Mission, the Common Agricultural Policy and the Nature Restoration Law). Moreover, the EUSO monitors the state of soil health in the EU through the EUSO Soil Health Dashboard. This comprehensive and easy understandable tool shows, for the first time, where current scientific evidence converges to indicate areas in the EU likely to be affected by soil degradation. Furthermore, the EUSO supports soil research and innovation, enhances the capacity and functionality of the European Soil Data Centre and supports citizen engagements regarding soil matters. Overall, since 2021, the EUSO has successfully taken up its role to be the principal knowledge hub for soil information and data to underpin EU policy development and implementation. Also in the next years, EUSO will continue to provide data and knowledge to monitor, safeguard and restore soils in the EU.

ABSTRACT. No abstract

ABSTRACT. After three years of implementation, the Mission Soil is reaching cruising speed with a diversified portfolio of 50 projects and the first 25 living labs starting operations. This presentation will offer an overview of the Mission developments, results, opportunities, challenges and next steps.

ABSTRACT. Copernicus is the European Union’s Earth observation programme. Its major components comprise the fleet of Sentinel satellites, a dedicated ground segment and six thematic core services. The European Environment Agency and the Joint Research Centre of the European Commission are entrusted with the joint implementation of the Copernicus Land Monitoring Service (CLMS). Since 2012, CLMS offers an ever-growing portfolio of free and open, operational Earth observation-based datasets and mapping products – from ground motion, near-real time vegetation and water monitoring, to land cover and land use mapping at different levels of detail and even ready-to-use imagery and reference data – thereby facilitating versatile applications and usage in and beyond the land domain. More recently, soils have been increasingly recognized as a limited resource and for its invaluable services to society (e.g. agricultural productivity, carbon storage, water retention and filtration). For instance, an EU soil strategy has been proposed in 2022 and followed by a legislative policy proposal in 2023 aiming to improve the condition of soils in Europe. These initiatives include land-related indicators which cover measurements of the condition of the Earth’s surface (e.g. visibly destroyed and re-located soil, soil sealing), but also stress the need for future monitoring solutions supported by Earth observation. Timely and trustworthy geospatial datasets, harmonized over large areas, are critical inputs to monitoring and modelling applications. In this context, CLMS is a key provider of such datasets and an overview of portfolio implementation priorities and roadmap relevant to soil applications will be explored here. For instance, all existing flagship land cover and land use products are being continued (e.g. Corine Land Cover for the reference year 2024) and – depending on the product – updated more frequently (e.g. Urban Atlas every three instead of six years). Land cover datasets for operational monitoring at 10m-resolution have been introduced (CLC+ Backbone) and will be launched with global coverage. Daily near-surface water content measurements and moisture condition estimates at various depth levels are offered on pan-European (1km) and global basis (12.5km). Regular updates of established datasets for soil sealing in Europe (HRL Imperviousness) and new datasets offering annual crop types, cropping patterns (HRL Crops), indications of most recent ploughing, and grassland mowing occurrence and timing (HRL Grasslands) will be released by the end of 2024. With CLMS being a user-driven service, fostering of user uptake and increased policy orientation are prioritized. The CLMS recently launched different stakeholder engagement and involvement initiatives, such as the National Collaboration Programmes with countries and the support in the development and promotion of use cases. These initiatives shall support the roadmap to ultimately develop CLMS datasets that can serve upcoming European cross-cutting environmental and soil legislation.

ABSTRACT. Monitoring soil health is crucial for reversing soil degradation and promoting sustainable farming practices. Integrating cover crops into crop rotations is a sustainable soil management practice that enhances soil health through nutrient retention and carbon accumulation. Remote sensing techniques, particularly the use of Unmanned Aerial Vehicles (UAVs), offer a solution for high-frequency monitoring of vegetation over time and space. This technology enables the observation of above-ground changes, which can be linked to soil functions through process-based modelling and data assimilation. In our research, we have combined the study of nutrient cycling and the impact of cover crops on soil health using the WOFOST-SWAP model. This model simulates the influence of cover crop monocultures and mixtures on Soil Organic Carbon (SOC) and Nitrogen cycling in a 7-year crop rotation on sandy soil. By incorporating UAV data and in-situ measurements of crop characteristics such as biomass and Nitrogen uptake, we enhance the calibration and validation of our models. This integrated approach allows us to effectively monitor soil health indicators, such as the Carbon cycle and Nitrogen use efficiency, which are crucial for selecting appropriate field management practices. Our findings suggest that the combination of UAV-based remote sensing, field sensors, and process-based modelling can significantly improve soil health monitoring. This research contributes to the promotion of sustainable farming practices by providing a comprehensive understanding of the interactions between cover crops, nutrient cycling, and soil health.

ABSTRACT. Soil spectroscopy has emerged as a non-destructive, and cost-effective method for analyzing various soil characteristics. Despite its advantages, combining data from different Soil Spectral Libraries (SSLs) presents significant challenges due to differences in measurement protocols, sample preparation, and environmental conditions. This study investigates the impact of merging different SSLs on modeling performance, focusing on the LUCAS 2015 soil spectral library and legacy Greek spectral data. Using Partial Least Squares Regression (PLSR), models were developed to predict Soil Organic Carbon (SOC) of two merged SSLs before and after harmonization. Results indicated that merging datasets without harmonization decreased model accuracy, whereas applying Internal Soil Standards (ISS) correction significantly improved performance. The harmonized dataset outperformed both the initial LUCAS 2015 dataset and the non-harmonized merged dataset, highlighting the necessity of harmonization for accurate soil property predictions. This study underscores the importance of developing robust, standardized protocols for integrating and analyzing diverse SSLs to advance soil spectroscopy and global soil monitoring efforts.

ABSTRACT. (Introduction) The increase of the world population up to 9.5 billion by 2050 will require an increase on food demand of the order of 30% (Lal, 2015). Agroecological practices aim to produce significant amounts of food and can improve sustainability of agroecosystems while being based on various ecological processes and ecosystem services such as nutrient cycling, N fixation, natural regulation of pests, soil, water and biodiversity conservation and, carbon sequestration (Wezel et al., 2014). Carbon credits is a financing mechanism for farmers who implement such practices in order to increase soil organic carbon (SOC) and thus produce higher quantities of food. Carbon credits are economically viable for farmers as they receive an additional income for every ton of CO2 sequestered. A smallholder farmer can earn an average of $2.80 per day (Liu, 2022). The objective of this study was to assess the impact of agroecological practices on avocado plantations (2019-2024) and forecast the carbon accumulation until 2028 using the Carbon, Aggregation and Structure Turnover (CAST) model (Stamati et al., 2013). (Methods) The study area is located in the valley of Koiliaris River Basin (Latitude: 35.43717, Longitude: 24.1427, Elevation: 15 m). The avocado plantation consists of 25 six-year-old trees (Avocado 1) and 45 four-year-old ones (Avocado 2) irrigated through drip irrigation with a piping system of 25 and 15 drips, respectively. The agroecological practices that have been applied to the field are manure addition, mulching and grass incorporation in the soil and sustainable irrigation practices. The CAST model, which was used in this study, uses the RothC carbon pools and simulates the macro-aggregate formation (around POM) and disruption to form micro-aggregates and silt-clay sized micro-aggregates (Stamati et al., 2013). The CAST model was initialized and calibrated using chronosequence data (2019, 2023 and 2024). The model simulated the Water Stable Aggregates (WSA), the soil organic carbon (SOC) and the organic carbon contained in macro-aggregates (AC3), micro-aggregates (AC2) and silt-clay sized micro-aggregates (AC1) during a 10-year period (2019-2028). (Results) It was observed that the WSA mass in macro-aggregates (AC3) decreased by approximately 10% from 2019 to 2024 (Figure 1). It was assumed that drought (due to the limited precipitation during January to March of 2024) resulted in a decline of macro-aggregate mass (>250μm) and an increase of micro-aggregate mass (53-250μm). These findings are consistent with several studies conducted in forests and agricultural lands (Zhang et al., 2019). However, to confirm these findings, soil samples will be collected from the field in October (or November) 2024 (when precipitation occurs) and will be analyzed to determine the WSA and organic carbon distribution.

Acknowledgements The authors acknowledge the funding support of the CARBON FARMING MED project (Innovative Sustainable Economy Mission, Interreg Euro-MED governance projects. 2024).

References Lal, R., 2015. Restoring soil quality to mitigate soil degradation. Sustain. 7, 5875-5895. https://doi.org/10.3390/su7055875 Liu, S., 2022. Restoring Carbon Sinks in Agriculture through Carbon Credits. Sustainable Finance Initiative. Precourt Institute for Energy, Stanford. 1-18. Stamati, F. E., Nikolaidis, Ν. P., Banwart, S., and Blum, W. E. H. (2013). A coupled carbon, aggregation, and structure turnover (CAST) model for topsoils. Geoderma. 51-64. doi: 10.1016/j.geoderma.2013.06.014 Wezel, A., Casagrande, M., Celette, F., Vian, J-F., Ferrer, A., Peigné, J., 2014. Agroecological practices for sustainable agriculture. A review. Agron. Sustain. Dev. 34, 1-20. https://doi.org/10.1007/s13593-013-0180-7 Zhang, Q., Shao, M., Jia, Χ., Wei, X., 2019. Changes in soil physical and chemical properties after short drought stress in semi-humid forests. Geoderma. 338, 170-177. https://doi.org/10.1016/j.geoderma.2018.11.051

ABSTRACT. Introduction Agriculture plays a vital role in global food security but also contributes significantly to environmental and ecosystem challenges. To achieve ambitious climate, biodiversity and soil health goals, leading to achieving carbon-neutral farms by 2050, agricultural production requires a sustainable transformation that focuses on greenhouse gas (GHG) mitigation, increased carbon sequestration, and improved soil health while reducing ecosystem degradation. Achieving this transformation requires a deep understanding of the complex biogeochemical and ecological processes within agricultural systems. This understanding is often hampered by limitations in measuring and monitoring these processes across different land uses and management practices. Modelling approaches offer a powerful tool to overcome these limitations and facilitate informed decision-making. Among various modelling approaches, the whole-farm model provides a more comprehensive perspective of the entire farm ecosystem. This holistic view aligns with our primary objective of developing a digital platform that addresses the agricultural system. While the comprehensive model's ability to consider interactions between various farm components is valuable, its data-intensive approach and complexity can present challenges in implementation.

Methodologies To overcome the challenges, we have been developing an agricultural system-based digital platform HOLOS-IE (www.ucd.ie/holos-ie, Khalil et al. 2024), leading to HOLOS-EU, using large datasets and algorithms (e.g. experimental, literature review and gap filling using Machine Learning), GIS and programming languages such as C#.NET (Fig. 1) and the prototype is ready. This ongoing work includes refining the model components (crops, grasses, livestock, trees as agroforestry, and infrastructure) and their sub-components (types/species) to be driven by key soil and climate variables (automated or user inputs) to assess for example sectoral GHGs, SOC density changes, production and economic modules. The key focus is also to capture the complex interactions between agricultural practices and ecosystem services. Data from field trials and literature are being used to enhance the model's accuracy. Iterative feedback guides the integration process to ensure the development of a comprehensive tool that also supports soil health (e.g. Feeney et al. 2024), and agrobiodiversity, leading to improved ecosystem services (e.g. Carlier et al. 2024) and sustainable farm management at land parcel to regional levels.

Results and Discussion HOLOS-IE simplifies complex modelling processes, empowering farmers and stakeholders to understand their agri-environmental footprint and explore strategies for reducing it through informed decision-making. The platform simplifies data input by automating the integration of relevant soil and climate parameters. Furthermore, it incorporates process-based algorithms and sub-modules, leading to a more accurate simulation of C and N cycling and GHG emissions under different management scenarios across sectors. This integration enables the active monitoring and management of farm-level carbon footprints, leading to provide net farm-C balance (Fig. 2). Based on the various model components and sub-components, there is a huge potential for advancing the framework and integration aligned with soil health and agroecosystem well-being.

Fig. 1. Schematic diagram of HOLOS-IE, a comprehensive digital platform under development, framework, functionalities, services and deliveries.

Fig. 2. HOLOS-IE prototype simulated Net C Balance of a dairy farm with 10% and 20% of farmland area occupied by agroforestry and hedgerows/

Conclusions This paper introduces HOLOS-IE, paving the way for a more expansive digital platform, leading to HOLOS-EU, with wider application across Europe. It could assess farm sustainability and provide a net balance for carbon neutrality through alternative land use and management planning. By combining farm-level data with process-based algorithms, we can improve accuracy and develop targeted interventions, as future challenges. This will help farmers and stakeholders address climate change, enhance soil health, and promote sustainable agroecosystem services.

This ongoing research is funded by Science Foundation Ireland via GOV.IE, and ECRRF (HOLOS-IE). Collaboration of ERA-NET (ReLive) through DAFM, Ireland, projects is greatly appreciated.

References Carlier J. et al. 2024. Modelling enhancement of Ecosystem Services provision through integrated agri-environment and forestry measures. Sci Total Environ. 948:174509. Feeney, C.J., et al. 2024. Benchmarking soil organic carbon (SOC) concentration provides more robust soil health assessment than the SOC/clay ratio at European scale, Sci Total Environ. 951: 175642. Khalil, M.I., et al. 2024. HOLOS-IE: Bridging Gaps for Sustainable Agriculture and Carbon Neutrality. In: Book of Abstracts. In: ISCRAES Book of Abstracts Series III (M.I. Khalil, Ed.). p43 (Click here)

ABSTRACT. (Introduction) The world today faces many environmental challenges related to climate change, biodiversity loss, water and soil pollution. These multiple stressors act simultaneously over a range of temporal and spatial scales, resulting in significant losses of ecosystem services that eventually affect societal well-being and humanity (Mirtl et al., 2018). The assessment of the impacts of climate change and the sustainability of land management can be achieved through modeling of soil functions in the earth’s critical zone (Banwart et al., 2019). The main objective of this work was to use data from two distinct and well-instrumented forested long-term ecosystem research (LTER) sites to model the soil functions of two forested watersheds, Zöbelboden in Austria and Hyytiälä in Finland, using the one-dimensional critical zone (1D-ICZ) model. The sites belong to the temperate and boreal forests of Europe with long term monitoring data (>25 years) that can be used to fully assess ecosystem services as well as better understand the limitations to plant growth and below ground carbon accumulation, processes that are highly relevant to climate mitigation. (Methods) The 1D-ICZ model links soil aggregate formation and soil structure development to nutrient dynamics, plant nutrition, water flow and mass transport. It simulates and quantifies four of the main ecosystem functions by accounting for interactions between water flow, solute transport, soil structure, carbon and nutrient dynamics and plant biomass production (Giannakis et al., 2017; Kotronakis et al., 2017). The model was initialized and calibrated during a 25-year period (1996−2020) using long term observations derived from the eLTER Repositories (https://deims.org/8eda49e9-1f4e-4f3e-b58e-e0bb25dc32a6, https://deims.org/663dac80-211d-4c19-a356-04ee0da0f0eb) and from FLUXNET (only for Hyytiälä). In addition, soil samples were collected from 3 different locations in each site in order to simulate the soil dynamics. (Results) The 1D-ICZ model simulated two mature forested ecosystems, Zöbelboden (temperate mountain forest in Central Europe) and Hyytiälä (boreal forest in Northern Europe) capturing the biomass production, soil structure and geochemistry. Temperature and light were found to be the primary limiting factors of plant growth in both sites, and precipitation a limiting factor only at Hyytiälä. The soils of the two sites are quite different with Zöbelboden having higher silt-clay content (74%) while Hyytiala’s soils are very sandy (69%). The difference in silt-clay content is reflected in the Water Stable Aggregate (WSA) distribution which in combination with below ground C content (which is mostly in the cPOM fraction) show very strong aggregation processes which relate to soil fertility. Lastly, in Zöbelboden the annual average gross primary production (GPP) is estimated at 15.6 tC/ha/yr, C sequestration at 82.6 tC/ha and N sequestration at 3.8 tN/ha while for Hyytiala, the GPP is 11.6 tC/ha/yr, C and N sequestration 38.6 tC/ha and 1.3 tN/ha respectively (Table 1).

Table 1. Parameters for Zöbelboden and Hyytiälä derived from the model. Zöbelboden Hyytiälä WSA_AC3 (%) 99.2 87.6 WSA_AC2 (%) 0.7 9.0 WSA_AC1 (%) 0.1 3.3 Sand (%) 26.2 69.1 Silt-clay (%) 73.8 30.9 Above ground C (tC/ha) 15.6 11.6 Below ground C (tC/ha) 82.6 38.6 cPOM (tC/ha) 71.8 25.5 Below ground N (tN/ha) 3.8 1.3 cPOM (tN/ha) 3.3 0.8 C to N (below ground) 21.7 29.7

Acknowledgements The authors acknowledge the funding support of the eLTER PLUS project (Grant agreement No. 871128, EU Horizon 2020 Research and Innovation action).

References Banwart, S. A., Nikolaidis, N. P., Zhu, Y-G., Peacock, C. L., Sparks, D. L., 2019. Soil Functions: Connecting Earth’s Critical Zone, Annu. Rev. Earth Planet. Sci., 47, 333-359. https://doi.org/10.1146/annurev-earth-063016-020544 Giannakis, G.V., Nikolaidis, N. P., Valstar, J., Rowe, E.C., Moirogiorgou, K., Kotronakis, E., Paranychianakis, N. V., Rousseva, S., Stamati, F. E., Banwart, S. A., 2017. Integrated Critical Zone Model (1D-ICZ): A Tool for Dynamic Simulation of Soil Functions and Soil Structure, In: Quantifying and Managing Soil Functions in Earth’s Critical Zone: Combining Experimentation and Mathematical Modelling, Advances in Agronomy, 142, 277-314. http://dx.doi.org/10.1016/bs.agron.2016.10.009 Kotronakis, E., Giannakis, G.V., Nikolaidis, N. P., Rowe, E. C., Valstar, J., Paranychianakis, N. V., Banwart, S. A., 2017. Modeling the Impact of Carbon Amendments on Soil Ecosystem Functions Using the 1D-ICZ Model, In: Quantifying and Managing Soil Functions in Earth’s Critical Zone: Combining Experimentation and Mathematical Modelling, Advances in Agronomy, 142, 315-352. http://dx.doi.org/10.1016/bs.agron.2016.10.010 Mirtl. M., Borer, E.T., Djukic. I., Forsius, M., Haubold, H., Hugo, W., Jourdan, J., Lindenmayer, D., McDowell, W.H., Muraoka, H, Orenstein. D.E., Pauw, J.C., Peterseil, J., Shibata, H., Wohner, C., Yu, X., Haase, P., 2018. Genesis, goals and achievements of Long-Term Ecological Research at the global scale: A critical review of ILTER and future directions, Science of the Total Environment, 626, 1439-1462. https://doi.org/10.1016/j.scitotenv.2017.12.001

ABSTRACT. Arable soils are often depleted in soil organic carbon partially due to disturbances caused by inversion tillage. Reduced tillage, defined as the non-inversion harrowing of the uppermost topsoil, is assumed to maintain a higher soil organic carbon storage in the topsoil due to minimized soil disturbances compared to Conventional tillage under specific soil and environmental conditions. Hence, the accrued or maintained soil organic carbon via reduced tillage does not rely on inputs of exogenous carbon and might lead to an actual carbon dioxide (CO2) mitigation potential. However, reduced tillage might also lead to changes in crop yield and nitrous oxide (N2O) emissions from soils, thereby compromising its climate change mitigation potential. It is even less understood, how crop yield, soil organic carbon and greenhouse gases might develop under the two tillage systems (Conventional and Reduced tillage) in anticipation of a drier future. In this study, we measured crop yields, soil carbon stocks and soil CO2 effluxes and N2O fluxes in a Conventional vs. Reduced tillage field trial in Göttingen in central Germany named Garte-Sued. The long-term experiment runs since 1970 in a field with Luvisol soil, characterized by 73% silt, 15% clay, and a pH of 6.6. The mean annual precipitation is 611±120 mm and the mean annual temperature is 9.6±0.7°C. The field trial follows a randomized block design and consists of 16 plots: eight under Conventional tillage with inversion ploughing to a depth of 27-30 cm, and eight under Reduced tillage with non-inversion harrowing to a depth of 7-10 cm. In February 2023, rain-out shelters (area =2 m × 2 m) designed to intercept 50% of the precipitation were installed in half of the plots leading to a two-factor experimental design. We collected information on crop yields from 35 harvest events between 1970 and 2022. In 2022-23 and in 2023-24 we cultivated winter wheat and winter barley respectively, and we monitored the biomass development and the crop yields. In May 2023, we determined soil bulk density using Kopecky rings at 0-60 cm at 10 cm depth intervals. In August 2023, we conducted a soil sampling at 0-90 cm at 10 cm depth intervals, and we measured soil carbon at bulk soil samples and at particulate and mineral-associated organic matter samples isolated with the by-size fractionation method. Since mid-February 2023, we monitored soil CO2 effluxes and N2O fluxes with static chambers and portable gas analysers. Soil water content and temperature were monitored by portable sensors at 0-10 cm. Flux measurements were also accompanied by frequent soil samplings at 0-30 cm depth for mineral nitrogen. Under the rain-out shelters, soil sampling was sparse due to space restrictions. Based on 35 harvest events between 1970 and 2022, crop yield was on average 6.5% lower in the reduced-till plots than the conventional-till plots. Winter wheat grain yield in the period 2022-23 was 0.87±0.02 kg m-2 in the reduced-till plots compared to 1.06±0.14 kg m-2 in conventional-till plots. Under 50% rain exclusion, the grain yield was 0.61±0.05 kg m-2 and 0.58±0.06 kg m-2 for the reduced and conventional-till plots, respectively. Stubble biomass followed the same patterns as grain yield. Regarding soil organic carbon, we found that reduced-till plots had higher stocks than conventional-till plots in the 0-10 cm depth, but the opposite occurred in the 20-30 cm depth. Comparing the stocks at 0-60 cm, there was no difference between the two tillage systems. In the period Feb. to Sep. 2023, average water-filled pores space (WFPS) from 53 measurement dates was lower in conventional-till plots (45.1±2.2% under ambient rain and 40.1±2.3% under rain exclusion) than in reduced-till plots (49.1±2.5% under ambient rain and 43.3±2.5% under rain exclusion). Based on the same measurement dates, cumulative soil CO2 efflux was 24% higher in conventional-till (0.584±0.044 kg CO2-C m-2) than in reduced-till plots (0.471±0.036 kg CO2-C m-2). This difference might be explained by greater organic matter inputs under conventional than reduced tillage through the incorporation of stubble biomass in the soils. In contrast, soil N2O emissions were 41% lower in conventional-till (43.0±15.5 mg N2O-N m-2) than reduced-till plots (73.1±16.2 mg N2O-N m-2) and this difference was also observed under 50% rain exclusion (29.2±4.7 mg N2O-N m-2 compared to 69.7±17.9 mg N2O-N m-2). Using mixed effect models with blocks and dates as random factors, we found that both tillage system and rain exclusion affected soil CO2 and N2O emissions which were also strongly associated with WFPS. We detected an interaction effect between WFPS and rain exclusion on CO2 and N2O emissions and an additional interaction effect between WFPS and tillage practice on CO2 emissions only. Carbon farming initiatives will incentivize the implementation of agroecological practices aiming at increasing or maintaining carbon storage in agricultural soils as climate change mitigation measure. Reduced tillage is assumed to be such an agroecological practice. However, the implementation of reduced tillage might lead to crop yields losses compared to conventional tillage even decades after the initiation of the agroecological practice. Given the ever-increasing needs for food, a yield loss might result in agricultural land leakage. In addition, when the whole ploughing layer and the subsoil are considered, there seems to be no difference in soil carbon stocks between Conventional and Reduced tillage systems even in the long-term, which questions the CO2 mitigation potential of Reduced tillage. Finally, reduced-till plots were linked to greater N2O emissions compared to conventional-till plots both under ambient rain and under controlled drought conditions. Combining the above, Reduced tillage seems to have no climate change mitigation potential in the productive fine textured soils of temperate central Europe.

ABSTRACT. In conventional crop fertilization systems, fertilizers are applied uniformly across the field with the application rate usually determined based on the least fertile part of the field. Consequently, the more fertile sections often receive more fertilizer than necessary leading to economic losses and environmental contamination. In recent years, an advanced management approach has been developed by applying inputs according to the actual needs of the plants that vary spatially within a field. A key factor of this variation is the spatial variability of soil properties that determines optimal nitrogen (N) fertilization. This paper presents the evolution of the in-season N fertilizer management based on an algorithm that utilizes canopy reflectance which varies spatially within a field depending on the distribution of soil properties. Initially, N fertilization was performed in different management zones (MZs) using multispectral sensors for the MZ delineation. This system evolved into an innovative automated variable-rate N application system (VRA) that applies the optimum amount of granular N fertilizer according to plant needs under high spatial resolution and real-time conditions. Nowadays, the same canopy detection system has been adapted to apply “on the go” variable-rate nitrogen fertilizer of a liquid form.

ABSTRACT. (Introduction) Cover crops undersown to cereals can sequester extra soil carbon (C) though input of fresh organic matter. As fresh organic matter holds both bioavailable C and nitrogen (N), cover crops could also result in additional nitrous oxide (N2O) emissions, particularly during hemiboreal winters when plant N uptake is absent. This could compromise or negate the climate benefit of additional C sequestration. A recent meta-analysis by Guenet et al. (2021) concluded that N2O emissions from cover crops do not fully offset the benefit of extra C sequestration. However, this study did not account for freeze-thaw emissions during winter. In this presentation, we present two years of N¬2¬O emission data from a Norwegian field experiment testing various cover crops. (Methods) A plot experiment was conducted in Ås, SE Norway, testing seven different cover crops undersown to barley. Three varieties (Perennial ryegrass, Italian ryegrass and a herb mixture) were sown in spring, while four varieties (Oilseed radish, Summer vetch, Winter vetch and Phacelia) were sown three weeks before barley harvest. All treatments received fertilisation in the spring (N1), with some treatments receiving additional fertilisation in autumn (N2). Two barley control treatments without cover crops (N1 and N2) were included as control. Each treatment was replicated three times, and the experiment was repeated in the second year on the same plots. Nitrous oxide fluxes were measured whole year round on a weekly basis for two consecutive years from spring 2021 to spring 2023. Manual chambers were used during the period of barley growth, while a field flux robot was used after harvesting the barley, resulting in a high-frequency data set of off-season N2O fluxes. Soil samples for nitrate and ammonium concentrations were collected weekly, as long as the soil was not frozen. The field experiment was designed as a repeated measure, factorial experiment with completely randomized plots. (Results) Highest N2O emissions were observed in plots with oilseed radish during freeze-thaw events in spring, whereas the herb mixture and perennial ryegrass demonstrated reduced emissions compared to other cover crops and control treatments (Fig. 1). Oilseed radish, a N-rich brassicum, decomposes throughout winter, creating optimal conditions for N2O production during spring thaw. In contrast, the perennial species retain excess N throughout winter, thereby reducing N2O emissions. Therefore, perennial cover crops with good winter survival can reduce N2O emissions in areas with soil freezing. Cover crop species, time of sowing, yield and N-level had no significant effect on N2O emissions during the barley growing season. However, N2O emissions differed significantly between cover crop species in winter, underscoring the importance of measuring off-season emissions when estimating yearly N2O budgets (Fig. 1). Solely measuring during the growing season would substantially underestimate annual emissions and cover crop effects.

We conclude that additional N2O emissions from annual cover crops in Southeast Norway are likely to cancel out GHG savings by soil C gains typical for Scandinavia (0.32 ± 0.28 Mg C ha-1 yr-1, Poeplau et al. 2015), while perennial, non-leguminous cover crops may result in a win-win situation with reduced N2O winter emissions and increased soil C sequestration over time.

ABSTRACT. Soil salinity can shape soil microbial communities and affect their activities impacting critical soil processes. In this study the effect of three different levels of Na-induced salinity (<1, 3, 8 dS/m) on soil microbial communities and on nitrification were examined. Six soils (three with pH<7 & three with pH>7) with different management history (crops and agronomic practices) were used. Microcosms were amended with inorganic nitrogen (ΝΗ4+-Ν 70 mg/kg) or not-amended, and incubated under controlled conditions (25 oC, in the dark) in the lab for 30 days. Nitrification was inhibited by salinity (stronger inhibition in high salinity). The effect depended on soil characteristics (soil pH) and management history. Soils with high soil pH and high fertilizer-N history were less sensitive to salinity, with the later showing gradual recovery of nitrification activity particularly at intermediate salinity levels (3 mS/cm). Nitrification activity was strongly inhibited in acidic soils regardless of the level of soil salinity. Abundances of soil ammonium oxidizers responded to changes in salinity levels and nitrogen supply, however these responses were poorly related to the respective functional changes in nitrification, indicating that the activities rather than abundances of ammonium oxidizers are the major drivers of short-term responses to salinity stress in soils.

ABSTRACT. Re-wetting of soils following a (long) period of drought stimulates a burst of microbial activity and peaks in CO2 and N2O emissions. This pulse of emissions also known as “Birch” effect after Birch (1964), represents a significant proportion of GHGs emitted throughout the whole season in arid and semi-arid climates (Barnard et al., 2020). This response has become particularly relevant in recent years considering the increase in the frequency of DRW cycles that is predicted by climate change. Most works on soil response to re-wetting have been performed under controlled conditions on small soil volumes that may not allow us to draw valid conclusions (Barrat et al 2020). To date information regarding the effect of conservation practices on soil response to rewetting remains scarce. Theoretically, opposing effects could be inferred by SOM increase and soil structure improvement. Pertinent knowledge is particularly important considering the spread of soil conservation practices to restore soil health and combat climate change (Norris et al., 2020). Herein, we investigate the effect of non-tillage on the emission rates of CO2 and N2O during re-wetting of soils under field conditions. We hypothesize that changes in structure and pore size distribution induced by soil conservation practices will compensate for the increases in SOM sequestration due to its physical protection decreasing thus GHGs emissions during soil re-wetting. Monitoring of GHGs was performed at three olive orchards located at the island of Crete, Greece, differing in pedo-climatic conditions and subjected two soil management practices, non-tillage and tillage since March 2021. Monitoring of GHGs was performed twice in each orchard between the end of October 2023 and the beginning of November 2023 following a long period without precipitation with a portable FTIR gas analyzer (GASMET 4015). The analyzer was integrated with a West Systems chamber with 100 mm height and 290 mm diameter and corresponding rings (two for each tillage in each site). Measurement of CO2 and N2O at each ring was performed for 6 minutes and recording of interval gasses was 1 min. Concentrations of GHGs were transformed to fluxes using the “gassfluxes” package in R. Soil physico-chemical properties, soil temperature and soil moisture were recorded in all experimental fields. In addition DNA was extracted from soil samples collected from 0-15 cm depth using the PowerSoil® Total DNA Kit (Qiagen GmbH) and the universal prokaryotic primer pair 515f/806r was used to amplify the V4 hypervariable region of the 16S rRNA gene. Amplicon sequencing was performed in a MiSeq Illumina platform at the NOVOGENE UK Facilities. Raw reads were processed with the DADA2 (v. 1.22) pipeline following the typical workflow. Different metrics were used to estimate the α-diversity of microbial communities (Shannon, Pielou’s J, Faith’s PD) and β-diversity (Bray–Curtis dissimilarity, UniFrac distances). All the bioinformatic and statistical analyses were performed in the R environment using the packages phyloseq, microbiome, microeco, vegan, ade and microeco. Rewetting of soils resulted in altered response patterns of CO2 and N2O emission rates between non-tilled and tilled soils. Specifically, non-tilled soils showed a faster response of respiration rates in all the fields and measurements (1st and 2nd) compared to tilled soils. This response was particularly evident in Field 1 (2nd measurement) and Field 2. In Field 3 the peak of soil respiration was smoother compared to the other fields but again higher than that recorded in the corresponding tilled plot. The peak of respiration lasted approximately 6 hrs before respiration rates return to the “regular” rates of the wetted soils. Regarding the emissions of N2O in response to re-wetting, non-tiled soils showed constantly higher emission rates that ranged from 6 times up to one order of magnitude. The emissions of N2O were short-lived (3 to 5 hrs) (Fig. 1B) and started earlier in the non-tilled soils compared to the tilled ones. They also showed a lag-phase compared to the response of respiration. These divergent response patterns of GHGs emissions could not be explained by differences in chemical or biological properties (a and b diversity, composition). The only parameter that was consistently linked to CO2 and N2O emissions was infiltration rate that was higher in non-tilled soils. These findings also indicate nitrification as the mechanism responsible for N2O emissions. Our findings provide documentation for a yet non-identified source of N2O from agroecosystems subjected to soil conservation practices and provide support for a more accurate prediction of N2O emissions based on first-principle parameters, like infiltration rate and SOM. However, it outlines the need for more studies in different climate zones to elucidate the underlying mechanisms that will allow us to develop simple and more accurate models for predicting soil response to rewetting.