How does tillage intensity affect soil organic carbon? A systematic review protocol

Background Soils contain the greatest terrestrial carbon (C) pool on the planet. Since approximately 12% of soil C is held in cultivated soils, management of these agricultural areas has a huge potential to affect global carbon cycling; acting sometimes as a sink but also as a source. Tillage is one of the most important agricultural practices for soil management and has been traditionally undertaken to mechanically prepare soils for seeding and minimize effects of weeds. It has been associated with many negative impacts on soil quality, most notably a reduction in soil organic carbon (SOC), although still a matter of considerable debate, depending on factors such as depth of measurement, soil type, and tillage method. No tillage or reduced intensity tillage are frequently proposed mitigation measures for preservation of SOC and improvement of soil quality, for example for reducing erosion. Whilst several reviews have demonstrated benefits to C conservation of no till agriculture over intensive tillage, the general picture for reduced tillage intensity is unclear. This systematic review proposes to synthesise an extensive body of evidence, previously identified through a systematic map. Methods This systematic review is based on studies concerning tillage collated in a recently completed systematic map on the impact of agricultural management on SOC restricted to the warm temperate climate zone (i.e. boreo-temperate). These 311 studies were identified and selected systematically according to CEE guidelines. An update of the original search will be undertaken to identify newly published academic and grey literature in the time since the original search was performed in September 2013. Studies will be critically appraised for their internal and external validity, followed by full data extraction (meta-data describing study settings and quantitative study results). Where possible, studies will be included in meta-analyses examining the effect of tillage reduction (‘moderate' (i.e. shallow) and no tillage relative to ‘intensive' tillage methods such as mouldboard ploughing, where soil is turned over throughout the soil profile). The implications of the findings will be discussed in terms of policy, practice and research along with a discussion of the nature of the evidence base

Land use and climate change impacts on global soil erosion by water (2015-2070)

Soil erosion is a major global soil degradation threat to land, freshwater, and oceans. Wind and water are the major drivers, with water erosion over land being the focus of this work; excluding gullying and river bank erosion. Improving knowledge of the probable future rates of soil erosion, accelerated by human activity, is important both for policy makers engaged in land use decision-making and for earth-system modelers seeking to reduce uncertainty on global predictions. Here we predict future rates of erosion by modeling change in potential global soil erosion by water using three alternative (2.6, 4.5, and 8.5) Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios. Global predictions rely on a high spatial resolution Revised Universal Soil Loss Equation (RUSLE)-based semiempirical modeling approach (GloSEM). The baseline model (2015) predicts global potential soil erosion rates of 43+9.2−7 Pg yr−1, with current conservation agriculture (CA) practices estimated to reduce this by ∼5%. Our future scenarios suggest that socioeconomic developments impacting land use will either decrease (SSP1-RCP2.6–10%) or increase (SSP2-RCP4.5 +2%, SSP5-RCP8.5 +10%) water erosion by 2070. Climate projections, for all global dynamics scenarios, indicate a trend, moving toward a more vigorous hydrological cycle, which could increase global water erosion (+30 to +66%). Accepting some degrees of uncertainty, our findings provide insights into how possible future socioeconomic development will affect soil erosion by water using a globally consistent approach. This preliminary evidence seeks to inform efforts such as those of the United Nations to assess global soil erosion and inform decision makers developing national strategies for soil conservation

Which agricultural management interventions are most influential on soil organic carbon (using time series data)?

Background Loss of soil organic carbon (SOC) from agricultural land is identified as one of the major threats to soils, as it influences both fertility and the production of ecosystem services from agriculture. Losses of SOC across regions are often determined by monitoring in different land use systems. Results from agricultural field experiments can reveal increasing SOC stocks after implementation of specific management practices compared to a control, though in time series experiments the relative rate of change is often negative and implying an overall loss. Long-term agricultural field experiments are indispensable for quantifying absolute changes in SOC stocks under different management regimes. Since SOC responses are seldom linear over time, time series data from these experiments are particularly valuable. Methods This systematic review is based on studies reporting time series data collated in a recently completed systematic map on the topic restricted to the warm temperate climate zone and the snow climate zone. These 53 studies were identified and selected systematically according to CEE guidelines. An update of the original search for studies will be repeated using Web of Science and Google Scholar to include newly published academic and grey literature in the time since the original search was performed in September 2013. Studies will be subject to critical appraisal of the internal and external validity, followed by full data extraction (meta-data describing study settings and quantitative study results). Where possible, studies will be included in a quantitative synthesis using time series meta-analytical approaches. The implications of the meta-analytical findings will be discussed in terms of policy, practice and research along with a discussion of the nature of the evidence base

Unifying soil organic matter formation and persistence frameworks: the MEMS model

Soil organic matter (SOM) dynamics in ecosystem-scale biogeochemical models have traditionally been simulated as immeasurable fluxes between conceptually defined pools. This greatly limits how empirical data can be used to improve model performance and reduce the uncertainty associated with their predictions of carbon (C) cycling. Recent advances in our understanding of the biogeochemical processes that govern SOM formation and persistence demand a new mathematical model with a structure built around key mechanisms and biogeochemically relevant pools. Here, we present one approach that aims to address this need. Our new model (MEMS v1.0) is developed from the Microbial Efficiency-Matrix Stabilization framework, which emphasizes the importance of linking the chemistry of organic matter inputs with efficiency of microbial processing and ultimately with the soil mineral matrix, when studying SOM formation and stabilization. Building on this framework, MEMS v1.0 is also capable of simulating the concept of C saturation and represents decomposition processes and mechanisms of physico-chemical stabilization to define SOM formation into four primary fractions. After describing the model in detail, we optimize four key parameters identified through a variance-based sensitivity analysis. Optimization employed soil fractionation data from 154 sites with diverse environmental conditions, directly equating mineral-associated organic matter and particulate organic matter fractions with corresponding model pools. Finally, model performance was evaluated using total topsoil (0–20&thinsp;cm) C data from 8192 forest and grassland sites across Europe. Despite the relative simplicity of the model, it was able to accurately capture general trends in soil C stocks across extensive gradients of temperature, precipitation, annual C inputs and soil texture. The novel approach that MEMS v1.0 takes to simulate SOM dynamics has the potential to improve our forecasts of how soils respond to management and environmental perturbation. Ensuring these forecasts are accurate is key to effectively informing policy that can address the sustainability of ecosystem services and help mitigate climate change.</p

Can animal manure be used to increase soil organic carbon stocks in the Mediterranean as a mitigation climate change strategy?

Soil organic carbon (SOC) plays an important role on improving soil conditions and soil functions. Increasing land use changes have induced an important decline of SOC content at global scale. Increasing SOC in agricultural soils has been proposed as a strategy to mitigate climate change. Animal manure has the characteristic of enriching SOC, when applied to crop fields, while, in parallel, it could constitute a natural fertilizer for the crops. In this paper, a simulation is performed using the area of Catalonia, Spain as a case study for the characteristic low SOC in the Mediterranean, to examine whether animal manure can improve substantially the SOC of agricultural fields, when applied as organic fertilizers. Our results show that the policy goals of the 4x1000 strategy can be achieved only partially by using manure transported to the fields. This implies that the proposed approach needs to be combined with other strategies.Comment: Proc. of EnviroInfo 2020, Nicosia, Cyprus, September 2020. arXiv admin note: text overlap with arXiv:2006.0912

The consolidated European synthesis of CH₄ and N₂O emissions for the European Union and United Kingdom: 1990–2019

Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CH₄ and N₂O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990–2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH₄ emissions, over the updated 2015–2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 Tg CH₄ yrc (EDGARv6.0, last year 2018) and 18.4 Tg CH₄ yr⁻¹ (GAINS, last year 2015), close to the NGHGI estimates of 17.5±2.1 Tg CH₄ yr⁻¹. TD inversion estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high-resolution regional TD inversions report a mean emission of 34 Tg CH₄ yr⁻¹. Coarser-resolution global-scale TD inversions result in emission estimates of 23 and 24 Tg CH₄ yr⁻¹ inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soil emissions from the JSBACH–HIMMELI model, natural rivers, lake and reservoir emissions, geological sources, and biomass burning together could account for the gap between NGHGI and inversions and account for 8 Tg CH₄ yr⁻¹. For N₂O emissions, over the 2015–2019 period, both BU products (EDGARv6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 Tg N₂O yr⁻¹, close to the NGHGI data (0.8±55 % Tg N₂O yr⁻¹). Over the same period, the mean of TD global and regional inversions was 1.4 Tg N₂O yr⁻¹ (excluding TOMCAT, which reported no data). The TD and BU comparison method defined in this study can be operationalized for future annual updates for the calculation of CH₄ and N₂O budgets at the national and EU27 + UK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, which is of great importance for CH₄ and N₂O, and may help identify sector contributions to divergence between prior and posterior estimates at the annual and/or inter-annual scale. Even if currently comparison between CH₄ and N₂O inversion estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emission inventories for CH₄, N₂O and other GHGs. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.7553800 (Petrescu et al., 2023)

The effcts of biochar application on water relation and soil quality in Vitis vinifera

Soil water status plays an important role on the growth-yield response on Vitis vinifera and on the quality of productions. Moderate water stress periods are in some cases needed to ensure high quality productions, but especially in dry Mediterranean environment, water stress may lead to an unbalance of the sugar/acidity ratio due to berry dehydration. Biochar is a co-product of thermochemical conversion of lignocellulosic biomass and it is well recognized to exert, if incorporated to the soil, an amendant action and an increase of water retention. The scientific literature on soil biochar application show a small overall, but statistically significant, positive effect of the biochar on plant productivity. In this work we investigated the effect of biochar amendments on Vitis vinifera (cv. Merlot) in a acid soil (pH 5.5) in Central Italy for two consecutive seasons. The biochar was applied at two rates 22 and 44 t ha-1 in a strip plot design with 5 replicates During summer 2011 the seasonal course of leaf water potentials, chlorophyll content, and chlorophyll fluorescence were measured as potential indicators of water stress. Detailed soil samples were also made during the entire season to detect the effects of the biochar application on soil parameters and on their dynamic. Preliminary results that will be reported in this presentation are showing that the soil pH increased by about one unit after biochar application and that a substantial reduction of water stress effect of plant treated with biochar has occurre

Olsen phosphorus, exchangeable cations and salinity in two long-term experiments of north-eastern Italy and assessment of soil quality evolution

Due to its food production and environmental buffering functions, soil is considered a strategic target by the European Union and its quality evaluation could be used as an effective index of sustainability. The evolution of some soil chemical parameters has been studied in two long-term trials established in the early 1960s in north-eastern Italy: one (SF) comparing nutrient management treatments (i.e. organic, mineral and mixed fertilizers) in lysimeters containing widely contrasting soil types (i.e. sand, clay and peat) and the other (CR) involving a field study with crop rotation, nutrient (organic vs. mineral fertilizers), and management intensity variables. Soil was analysed for Olsen phosphorus (Pav), exchangeable cations (Kex, Naex, Mgex and Caex) and salinity, evaluated by measuring the electrical conductivity (EC). A bi-factorial quality index based on fuzzy logic was then tested and applied to assess the overall soil quality and its evolution in the cropping systems. A minimum dataset of chemical (pH, organic carbon, cation exchange capacity, Pav and Kex) and physical parameters (available water content and water-filled porosity) was used to elaborate the index. In general, the use of organic fertilizer resulted in higher Pav, Kex and Mgex concentrations than the mineral treatments at the same levels, whereas no differences for Naex and Caex were observed. Salinity level was not influenced by the organic treatments probably because the consistent water drainage in the area prevented salt accumulation. The soil quality index represented the soil productivity function, explaining up to 74% of yield variability. Index comparison highlighted the positive role of organic and mixed fertilizations in increasing and maintaining the soil quality. The bi-factorial index of soil quality based on a minimum dataset is a good tool for the policy maker to evaluate the effects of management practices. However, standardization and accuracy of the soil analyses are important to reduce sources of variability that could have a strong influence on the soil quality evaluation