Ensemble modelling, uncertainty and robust predictions of organic carbon in long-term bare-fallow soils.

Simulation models represent soil organic carbon (SOC) dynamics in global carbon (C) cycle scenarios to support climate-change studies. It is imperative to increase confidence in long-term predictions of SOC dynamics by reducing the uncertainty in model estimates. We evaluated SOC simulated from an ensemble of 26 process-based C models by comparing simulations to experimental data from seven long-term bare-fallow (vegetation-free) plots at six sites: Denmark (two sites), France, Russia, Sweden and the United Kingdom. The decay of SOC in these plots has been monitored for decades since the last inputs of plant material, providing the opportunity to test decomposition without the continuous input of new organic material. The models were run independently over multi-year simulation periods (from 28 to 80 years) in a blind test with no calibration (Bln) and with the following three calibration scenarios, each providing different levels of information and/or allowing different levels of model fitting: (a) calibrating decomposition parameters separately at each experimental site (Spe); (b) using a generic, knowledge-based, parameterization applicable in the Central European region (Gen); and (c) using a combination of both (a) and (b) strategies (Mix). We addressed uncertainties from different modelling approaches with or without spin-up initialization of SOC. Changes in the multi-model median (MMM) of SOC were used as descriptors of the ensemble performance. On average across sites, Gen proved adequate in describing changes in SOC, with MMM equal to average SOC (and standard deviation) of 39.2 (±15.5) Mg C/ha compared to the observed mean of 36.0 (±19.7) Mg C/ha (last observed year), indicating sufficiently reliable SOC estimates. Moving to Mix (37.5 ± 16.7 Mg C/ha) and Spe (36.8 ± 19.8 Mg C/ha) provided only marginal gains in accuracy, but modellers would need to apply more knowledge and a greater calibration effort than in Gen, thereby limiting the wider applicability of models.

How to measure, report and verify soil carbon change to realize the potential of soil carbon sequestration for atmospheric greenhouse gas removal.

There is growing international interest in better managing soils to increase soil organic carbon (SOC) content to contribute to climate change mitigation, to enhance resilience to climate change and to underpin food security, through initiatives such as international '4p1000' initiative and the FAO's Global assessment of SOC sequestration potential (GSOCseq) programme. Since SOC content of soils cannot be easily measured, a key barrier to implementing programmes to increase SOC at large scale, is the need for credible and reliable measurement/monitoring, reporting and verification (MRV) platforms, both for national reporting and for emissions trading. Without such platforms, investments could be considered risky. In this paper, we review methods and challenges of measuring SOC change directly in soils, before examining some recent novel developments that show promise for quantifying SOC. We describe how repeat soil surveys are used to estimate changes in SOC over time, and how long-term experiments and space-for-time substitution sites can serve as sources of knowledge and can be used to test models, and as potential benchmark sites in global frameworks to estimate SOC change. We briefly consider models that can be used to simulate and project change in SOC and examine the MRV platforms for SOC change already in use in various countries/regions. In the final section, we bring together the various components described in this review, to describe a new vision for a global framework for MRV of SOC change, to support national and international initiatives seeking to effect change in the way we manage our soils.

Modeling Regional Effects of Climate Change on Soil Organic Carbon in Spain.

Soil organic C (SOC) stock assessments at the regional scale under climate change scenarios are of paramount importance in implementing soil management practices to mitigate climate change. In this study, we estimated the changes in SOC sequestration under climate change conditions in agricultural land in Spain using the RothC model at the regional level. Four Intergovernmental Panel on Climate Change (IPCC) climate change scenarios (CGCM2-A2, CGCM2-B2, ECHAM4-A2, and ECHAM4-B2) were used to simulate SOC changes during the 2010 to 2100 period across a total surface area of 2.33 × 10 km. Although RothC predicted a general increase in SOC stocks by 2100 under all climate change scenarios, these SOC sequestration rates were smaller than those under baseline conditions. Moreover, this SOC response differed among climate change scenarios, and in some situations, some losses of SOC occurred. The greatest losses of C stocks were found mainly in the ECHAM4 (highest temperature rise and precipitation drop) scenarios and for rainfed and certain woody crops (lower C inputs). Under climate change conditions, management practices including no-tillage for rainfed crops and vegetation cover for woody crops were predicted to double and quadruple C sequestration rates, reaching values of 0.47 and 0.35 Mg C ha yr, respectively.

The use of double-cropping in combination with no-tillage and optimized nitrogen fertilization reduces soil N2O emissions under irrigation.

The irrigation systems of the Ebro valley can lead to high N2O emissions. The effects that crop diversification, such as double-cropping in combination with conservation tillage and different N fertilizer ratios, has on soil N2O emissions have not been extensively studied in this region. The goal of this research was to measure N2O soil emissions and determine the tillage practices and N fertilization rates that provide the lowest emissions when combined with double-cropping systems. The work compared monocropping maize (MC) versus legume-maize double-cropping (DC) with two tillage systems (conventional tillage, CT; and no-tillage, NT), and three mineral N fertilization rates (zero, medium and high). Pea for grain (2019), vetch for green manure (2020), and vetch for forage (2021) were the legumes employed. The N2O emissions ranged from 0 to 15.5 mg N2O-N m-2 d-1 and were concentrated in the fertilization periods. Soil temperature and water filled pore space (WFPS) content significantly influenced soil N2O emissions. For both cropping systems, the conditions with the highest N2O emissions were soil temperatures above 20 °C and a WFPS of 50-60 %. The use of legumes facilitated reduced N fertilization in DC without affecting crop yield and led to reduced N2O emissions in this cropping system. DC reduced the emission factor (EF), which in all cases was lower than the default IPCC EF (1 %). With DC, a medium N fertilization rate produced similar yields to the high rate commonly applied by farmers, and also entailed lower N2O emissions. The no-tillage system, although producing higher levels of N2O, achieved lower yield-scaled N2O emissions due to greater crop yields. This work underlines the advantages of using double-cropping no-tillage systems combined with medium rates of N fertilization to reduce soil N2O emissions.

Vertical organization of microbial communities in Salineta hypersaline wetland, Spain.

Microbial communities inhabiting hypersaline wetlands, well adapted to the environmental fluctuations due to flooding and desiccation events, play a key role in the biogeochemical cycles, ensuring ecosystem service. To better understand the ecosystem functioning, we studied soil microbial communities of Salineta wetland (NE Spain) in dry and wet seasons in three different landscape stations representing situations characteristic of ephemeral saline lakes: S1 soil usually submerged, S2 soil intermittently flooded, and S3 soil with halophytes. Microbial community composition was determined according to different redox layers by 16S rRNA gene barcoding. We observed reversed redox gradient, negative at the surface and positive in depth, which was identified by PERMANOVA as the main factor explaining microbial distribution. The Pseudomonadota, Gemmatimonadota, Bacteroidota, Desulfobacterota, and Halobacteriota phyla were dominant in all stations. Linear discriminant analysis effect size (LEfSe) revealed that the upper soil surface layer was characterized by the predominance of operational taxonomic units (OTUs) affiliated to strictly or facultative anaerobic halophilic bacteria and archaea while the subsurface soil layer was dominated by an OTU affiliated to Roseibaca, an aerobic alkali-tolerant bacterium. In addition, the potential functional capabilities, inferred by PICRUSt2 analysis, involved in carbon, nitrogen, and sulfur cycles were similar in all samples, irrespective of the redox stratification, suggesting functional redundancy. Our findings show microbial community changes according to water flooding conditions, which represent useful information for biomonitoring and management of these wetlands whose extreme aridity and salinity conditions are exposed to irreversible changes due to human activities.

Estimating soil organic carbon changes in managed temperate moist grasslands with RothC.

Temperate grassland soils store significant amounts of carbon (C). Estimating how much livestock grazing and manuring can influence grassland soil organic carbon (SOC) is key to improve greenhouse gas grassland budgets. The Rothamsted Carbon (RothC) model, although originally developed and parameterized to model the turnover of organic C in arable topsoil, has been widely used, with varied success, to estimate SOC changes in grassland under different climates, soils, and management conditions. In this paper, we hypothesise that RothC-based SOC predictions in managed grasslands under temperate moist climatic conditions can be improved by incorporating small modifications to the model based on existing field data from diverse experimental locations in Europe. For this, we described and evaluated changes at the level of: (1) the soil water function of RothC, (2) entry pools accounting for the degradability of the exogenous organic matter (EOM) applied (e.g., ruminant excreta), (3) the month-on-month change in the quality of C inputs coming from plant residues (i.e above-, below-ground plant residue and rhizodeposits), and (4) the livestock trampling effect (i.e., poaching damage) as a common problem in areas with higher annual precipitation. In order to evaluate the potential utility of these changes, we performed a simple sensitivity analysis and tested the model predictions against averaged data from four grassland experiments in Europe. Our evaluation showed that the default model's performance was 78% and whereas some of the modifications seemed to improve RothC SOC predictions (model performance of 95% and 86% for soil water function and plant residues, respectively), others did not lead to any/or almost any improvement (model performance of 80 and 46% for the change in the C input quality and livestock trampling, respectively). We concluded that, whereas adding more complexity to the RothC model by adding the livestock trampling would actually not improve the model, adding the modified soil water function and plant residue components, and at a lesser extent residues quality, could improve predictability of the RothC in managed grasslands under temperate moist climatic conditions.

A historical perspective on soil organic carbon in Mediterranean cropland (Spain, 1900-2008).

Soil organic carbon (SOC) management is key for soil fertility and for mitigation and adaptation to climate change, particularly in desertification-prone areas such as Mediterranean croplands. Industrialization and global change processes affect SOC dynamics in multiple, often opposing, ways. Here we present a detailed SOC balance in Spanish cropland from 1900 to 2008, as a model of a Mediterranean, industrialized agriculture. Net Primary Productivity (NPP) and soil C inputs were estimated based on yield and management data. Changes in SOC stocks were modeled using HSOC, a simple model with one inert and two active C pools, which combines RothC model parameters with humification coefficients. Crop yields increased by 227% during the studied period, but total C exported from the agroecosystem only increased by 73%, total NPP by 30%, and soil C inputs by 20%. There was a continued decline in SOC during the 20th century, and cropland SOC levels in 2008 were 17% below their 1933 peak. SOC trends were driven by historical changes in land uses, management practices and climate. Cropland expansion was the main driver of SOC loss until mid-20th century, followed by the decline in soil C inputs during the fast agricultural industrialization starting in the 1950s, which reduced harvest indices and weed biomass production, particularly in woody cropping systems. C inputs started recovering in the 1980s, mainly through increasing crop residue return. The upward trend in SOC mineralization rates was an increasingly important driver of SOC losses, triggered by irrigation expansion, soil cover loss and climate change-driven temperature rise.

Soil management effects on aggregate dynamics in semiarid Aragon (NE Spain).

During decades, in semiarid rainfed Aragon, intensive soil tillage and low crop residue input have led to the loss of soil structure and soil degradation. Conservation tillage and cropping intensification can improve soil structure in these areas. The objective of this study was to determine the influence of three different tillage systems (traditional tillage, reduced tillage and no-tillage) under two cropping systems (fallow-barley rotation and barley monoculture) on soil aggregation dynamics during a cropping season. A decrease in tillage intensity resulted in a higher mean size of dry aggregates and a greater water aggregate stability in both cropping systems particularly under no-tillage.