Purpose This study offers transformation pathways through the intersections of enterprise governance and farming in response to climate and ecological crises (COP21, COP28 et al.). The analysis further proposes Virtuoso as a novel integration capability for the Viable System Model (“VSM”), Stafford Beer's systemic methodology for enterprise management (Beer, 1985; Jenkinson, 2022). It thereby contrasts farming models and their ways of seeing. Design/methodology/approach The interdisciplinary methodology synthesizes insights from five domains: epistemology, ecological paradigms, farming practices, the VSM theory and Virtuoso, an identity governance framework. Comparative case studies contrast two paradigmatic systems of intensive English farming: conventional “industrial-chemical” (“IC”) and “biodynamic regeneration” (“BD”). Interdisciplinary research, fieldwork, and participatory engagement explored the interrelation of system elements and regenerative potential (Shweder, 1999). Findings Farming has radically altered the planetary biosphere (Ellis et al., 2010). The IC model is a major contributor to global climate and biodiversity challenges through its degenerative cycle of soil degradation, input dependency, and declining resilience (Montgomery, 2017, 39–40, 80–81). BD demonstrates that economically sound, mitigation and regeneration is possible, exceeding UN COP21 soil organic carbon (“SOC”) targets, a key indicator of climate change (Gantlett, 2021, 2022, 2024, 2025). Virtuoso articulates their contrasting identities and operational logics, revealing latent potential for agriculture and the VSM. Research limitations/implications The interdisciplinary synthesis suggests fresh lines of academic research and practice in farming, the VSM, and Virtuoso. Given some novelty and interplay between multiple complex fields, each aspect could inevitably be expanded both theoretically and practically. Practical implications Advances the VSM and System 5 (“S5”) practice and capability. Outlines implications for government agricultural policy, positioning farming as a key agent of biodiversity regeneration and climate change requiring support for integrated transition pathways. Notes the rich capability of biodynamic farming. Social implications Global futures are dependent on farming and food systems; this comparative study explores the global significance of agritechnique over agritech. It offers scope for improved enterprise management and performance. Originality/value This study contributes to the novel synthesis of regenerative agriculture, cybernetic governance, and ecological epistemology as it introduces novel VSM system capabilities and biologically intensive farming, each of significant ecosystem potential.

Ecosystem restoration is increasingly recognized as a sustainable climate change mitigation strategy, yet global estimates of its carbon sequestration potential widely vary. Modeling-based studies differ in assumptions over key restoration aspects, including restorable areas and restoration outcomes. Many assume recovery of carbon stocks to pristine levels, an expectation not supported by empirical evidence. They also focus primarily on forests and biomass, with limited attention to soil organic carbon (SOC). Here, we estimate the global SOC sequestration potential of forest and grassland restoration by combining current SOC levels on degraded land areas available for restoration with empirically derived SOC increase factors at the ecosystem scale. We provide spatially explicit estimates of SOC sequestration potential, absolute and per hectare. We also assess the carbon sequestration potential achievable under national forest restoration pledges across four major resolutions. With 1223 million hectares (Mha) of degraded land globally, the SOC sequestration potential is 38.5 GtC, of which 35.1 GtC (IQR 30.4–39.3 GtC) in forests and 3.4 GtC (IQR 2.6–4.2) in grasslands. National pledges cover 133 Mha, whose restoration could sequester 4–5.5 Gt of SOC. We show that there is a large unexplored theoretical climate mitigation potential of restoration globally. Environmental policies targeting Southeast Asia and South America, where potential is high and pledges are low, are particularly promising.

Intensive cropping and long-term ammoniacal nitrogen (N) fertilization have degraded soil health in eastern Oregon dryland wheat systems, leading to soil acidification and declining soil organic carbon (SOC) stocks, which poses a critical threat to sustainability. This study assessed the impacts of a one-time biochar application on soil acidity, SOC sequestration, and nutrient dynamics over 10 years in a winter wheat–spring pea rotation. Biochar, derived from forest waste and applied only once in 2013 at rates of 11.2, 22.4, and 44.8 t ha −1 , was evaluated against both non-amended control plots and plots receiving nitrogen fertilizer alone. Key soil properties, including pH, SOC, labile carbon (POXC), cation exchange capacity (CEC), electrical conductivity (EC), nutrient concentrations, and mineralization rates, were measured. Results showed biochar significantly increased soil pH by up to 0.9 units, with improvements persisting for a decade, particularly at higher rates. Elevated pH positively correlated with improved CEC, indicating enhanced nutrient retention and better macro/micronutrient availability (Zn, Ca, Mg, K), reducing Fe solubility. Biochar instantly increased SOC stocks by 95–207% and maintained the stocks for more than 10 years, demonstrating long-term persistence, particularly at higher application rates. Biochar effectively maintained a higher labile carbon content (POXC), although a declining POXC/SOC ratio suggested a shift to more stabilized carbon pools. Mineralization changes were moderate, with non-significant increases in CO 2 efflux at higher biochar rates and no consistent net N mineralization trends, suggesting limited direct stimulation of microbial N cycling. Overall, a single alkaline biochar application provided sustained, long-term benefits, playing a dual role in mitigating acidity and enhancing carbon sequestration, thereby supporting a sustainable strategy for restoring soil fertility and ecosystem function and strengthening dryland agroecosystem resilience.

The growing frequency and extent of wildfires constitute a significant environmental challenge, posing serious threats to ecosystems, biodiversity, and human livelihoods. This study presents a comprehensive wildfire susceptibility assessment for El Tarf Province, one of the most fire-prone yet understudied regions in Algeria. Long-term Landsat imagery (1995-2024) combined with four machine learning algorithms was used to produce high-resolution susceptibility maps and identify the key environmental and bioclimatic drivers of wildfire occurrence. Ten conditioning factors representing topographic, vegetative, edaphic, and climatic conditions were integrated, with elevation, Enhanced Vegetation Index (EVI), wind speed, and precipitation emerging as dominant predictors. Among the tested models, Random Forest achieved the highest predictive performance (ROC-AUC = 0.897), closely followed by XGBoost (0.896), while LightGBM provided an optimal balance between accuracy (0.875) and computational efficiency. Logistic Regression, though simpler, performed reasonably well (0.794). The Landsat-derived wildfire inventory comprised approximately 622,221 burned pixels and was subsequently split into a pre-2017 training set (72.8%) and a post-2017 testing set (27.2%) to evaluate model generalization over time. Spatial block cross-validation was applied to reduce spatial autocorrelation and enhance model generalization. This methodological framework, combining spatial and temporal validation, temporal hold-out, and spatial blocking, strengthens the robustness and reliability of wildfire susceptibility modeling. Interpretability analyses based on SHAP values, Gini importance, and permutation importance identified the contributions of underexplored variables, including vegetation type, soil type, and soil organic carbon (SOC). The resulting susceptibility maps provide valuable insights for spatial planning and ecosystem management, supporting evidence-based strategies to enhance environmental resilience and biodiversity conservation in Mediterranean landscapes.

Nitrous oxide (N2O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N2O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high-emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N2O fluxes from US cropland. Trained and validated on ~12,000 N2O chamber measurements at 17 US Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N2O at both training (R2 = 0.84, RMSE = 16.4 g N ha-1 d-1) and held-out testing sites (R2 = 0.84, RMSE = 6.2 g N ha-1 d-1). Analyses identified six dominant N2O drivers: soil organic carbon (SOC), NH4+, NO3-, water-filled pore space, temperature, and aboveground biomass production. Wet, warm soils produced large N2O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N2O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

The role of soil organic carbon (SOC) dynamics in forest carbon (C) balance has been widely recognized. The processes that mediate the relationships between forest tree species composition and the formation, turnover, and stabilization of SOC are not sufficiently understood. This paper aimed to compile the state of knowledge on the involvement of tree species composition in the regulation of SOC dynamics through litter quality, root properties, root exudates, microbial-mediated processes, and soil mineral interactions. A greater emphasis is given to the role of the SOC pool subdivision into active (labile) and passive (non-labile) fractions. These fractions turn over at a significantly different rate and have also been proven to be considerably different in terms of long-term stability. The properties of the trees and soil in the rhizosphere influence the rate of short-term and chemical conversion of plant material into the persistent or passive fraction of soil C through the mediating process of microorganisms. Evidence confirmed that the functional interactions between the mix of tree species increase the rate of SOC stabilization through an increase in the rate of active to passive fraction transition. This synthesis presents a trait-based approach for considering and addressing the dynamics of SOC in the environment.

To explore the relationship between carbon storage and environmental factors in Populus plantations of different stand ages, and to reveal the carbon sequestration mechanisms of Populus plantations across different age classes, this study employed field surveys and laboratory analysis to investigate the distribution patterns and influencing factors of carbon storage in trunk-branch-leaf-root-soil systems of Populus plantations with different stand ages (10 y, 30 y, 40 y, 50 y) in the Luxi Yellow River floodplain. The results showed that the carbon storage in trunks, branches, and roots increased gradually with increasing stand age, while the carbon storage in leaves reached a maximum of 7.52 t·hm 2 at 40 y, followed by a gradual decrease. Soil carbon storage increased consistently with stand age. Overall, the total carbon storage of Populus plantations across different age classes exhibited a linear increasing trend with advancing standage. Correlation analysis, principal component analysis, and structural equation modeling indicated that diameter at breast height (DBH), tree height (H), tree age (AGE), and stand density (SD) were the key factors affecting carbon storage in Populus plantations. The findings of this study can provide theoretical basis and technical support for enhancing carbon sequestration and sink capacity, as well as ecological restoration of Populus plantations in the Luxi Yellow River floodplain.

Grass root litter and soil carbon quality contrarily control Q10 of labile and recalcitrant carbon pools in a semi-arid inceptisol

Abstract Soils hold vast amounts of organic carbon and play a pivotal role in the global carbon cycle. The turnover time ( τ ) and temperature sensitivity of the soil carbon cycle—commonly expressed as Q 10 —are critical parameters for projecting climate–carbon feedbacks under climate change. However, the temperature dependency of soil Q 10 remains controversial, with reported values varying widely across studies. Here, we synthesize global datasets of soil organic carbon stocks and heterotrophic respiration to evaluate turnover time and Q 10 . Our analysis of harmonized global maps shows that the soil carbon turnover time decreases with increasing temperature and the soil carbon-weighted mean τ for the 0–100 cm layer is 83.3 years. Analysis of the temperature dependence of turnover time indicates that the emergent temperature dependency of Q 10 is weak, with limited divergence across climate zones. These findings suggest that, despite large carbon stocks, the temperature-driven vulnerability of soil carbon in cold regions may be lower than previously assumed. The emergent turnover time and temperature sensitivity derived in this study provide new constraints for Earth system models.

Land use and land cover (LULC) change strongly influences national carbon dynamics and the effectiveness of forest-based climate mitigation strategies, particularly in mountainous developing countries. This study integrates scenario-based LULC modeling, spatially explicit carbon accounting, and economic valuation to assess how alternative development pathways affect carbon storage and its economic value in Nepal over the 2020–2050 period. LULC projections for four scenarios: Business-as-Usual (BAU), Rapid Urban Development (RUD), Forest Degradation and Terai Contraction (FDTC), and Agricultural Land Abandonment and Ecological Recovery (ALER), were generated using the TerrSet Land Change Modeler, with 2020 as the baseline. These projections were then used as inputs to the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Carbon Storage and Sequestration model to estimate changes in ecosystem carbon stocks, integrating aboveground biomass, belowground biomass, soil organic carbon, and dead organic matter pools. Carbon stock changes were monetized using a constant carbon price of USD 5/tCO2e and a 3% discount rate to estimate net present values (NPV). Results reveal strong divergence across scenarios. National carbon storage remains near-neutral under BAU (−0.46% by 2050), declines under RUD (−2.42%) and FDTC (−5.32%), and increases substantially under ALER (+11.74%). These biophysical outcomes translate into contrasting economic values: BAU yields a small negative NPV, RUD and FDTC generate large discounted losses, and ALER produces a strongly positive NPV exceeding USD 800 million by 2050. Spatially, forest and other wooded land dominate national carbon dynamics, while urban expansion and forest degradation drive disproportionate losses. Overall, the study results demonstrate that recovery-oriented land-use pathways offer substantially greater long-term carbon and economic benefits than development trajectories dominated by urban expansion or forest degradation, providing a policy-relevant framework to support Reducing Emissions from Deforestation and Forest Degradation, together with conservation, sustainable forest management, and enhancement of forest carbon stocks (REDD+) planning and long-term mitigation assessment in Nepal.

Soil electrical conductivity (EC) and aggregate-size distribution are critical indicators of soil salinity risk, structural integrity, and overall soil health. We assessed the status of these properties in 188 wheat plots across nine European pedoclimatic zones to quantify the influence of climate and agricultural management. Most soils (~88%) were non-saline, 9% slightly saline, and 3% moderately saline, with the highest salinity in Mediterranean regions. EC was generally lower under organic management, reflecting higher soil organic carbon, improved porosity, and enhanced cation retention. Soils were dominated by small macroaggregates (250–2000 µm) and large microaggregates (53–250 µm), together accounting for an average of 73% of total aggregates. Climate was the primary determinant of both EC and aggregate distribution, with drier and warmer conditions promoting salinization and smaller aggregate sizes, whereas wetter conditions favored macroaggregate formation. Agricultural management had a secondary but context-dependent effect, particularly on soil aggregation, with organic farming, integrated organomineral fertilization, crop residue incorporation, and legume rotations enhancing macroaggregate formation, especially in low-SOC soils. These results indicate that pedoclimatic conditions largely shape soil salinity and structure, but adopting targeted, site-specific management practices can sustain soil health and mitigate risks related to salinity and structure, particularly under projected climate change.

Soil organic carbon (SOC) is crucial for maintaining soil health, as it supports microorganisms, improves soil structure, and regulates nutrient availability. Typically, SOC and salinity exhibit an inverse relationship, influenced by factors such as vegetation, topography, salt composition, and climate. In this study, we mapped soil salinity (ECe: 0.55–3.14 dS/m) and measured SOC (4.5–10.4 g/kg) at 50 field sites. The study employed statistical and spatial analyses, combined with remote sensing and geographic information systems, to quantify the interaction between them. The study found that SOC generally declines with increasing salinity, with a clear threshold at 1.43 dS/m. Beyond this threshold, further SOC loss slows, likely due to the mitigating effects of salinity-tolerant grasses and calcium-rich parent material on sodium stress. Vegetation cover (short grasses occupying 29.3 % of the area) helped sustain soil organic carbon even under higher salinity. These findings align with our research objectives by quantifying the relationship between SOC and salinity and identifying the primary factors that control it. The results suggest that promoting salinity-tolerant vegetation and applying calcium-based amendments are effective strategies for maintaining SOC levels in semiarid, calcareous soils. The study findings provide actionable spatial guidance for targeted soil management and ecological planning in similar regions.

Soil organic carbon sequestration efficiency with biochar addition across the croplands of China: A perspective from particulate and mineral-associated organic carbon.

Divergent responses of soil particulate and mineral-associated organic carbon to climate gradients in managed croplands of Northeast China.

Effects of tillage practices on aggregate-associated soil organic carbon fractions and maize yield.

Degraded coastal agricultural lands hold significant soil carbon stocks and are potential candidates for blue carbon restoration.

Microbial-derived carbon dominates shrub encroachment carbon loss in Inner Mongolia grasslands.

A coupled Hydro-Biogeochemical framework for evaluating lateral loss of soil organic carbon under land-use change at the basin scale.

Soil microbiome drives soil multifunctionality across slope positions in a mountain tea plantation ecosystem.

Abstract With the increase of organic agriculture throughout Europe, there is also an increase of stockless organic farms. On mixed farms, growth of perennial legume-grass mixtures as well as farmyard manure are important contributors to soil fertility and play a key role for nutrient management. On stockless farms, such crops have no direct economic use and their cultivation is therefore questionable, which poses challenges for maintaining nutrient balance and soil fertility. Disentangling physical, chemical, and biological long-term impacts on soil fertility and consequently on crop yield and quality requires long-term research. In 2017, a long-term field experiment was established in Hesse, Germany, in which three stockless organic farm types differing in crop rotation, each combined with three different fertilization treatments, are compared to a traditional mixed farm type with three livestock density levels. The results of the first crop rotation show that the Mixed Farm type achieved more synchronized nutrient input and output with increasing livestock density. Stockless farm types showed deficits, especially in P and K balances, unless compensated by organic fertilizers from external sources. The application of compost and grass-clover silage prepared from on site fertility-building leys resulted in significant increases in soil organic carbon. Significant correlations between soil organic carbon and crop yields in stockless farm types using compost emphasize the importance of soil organic carbon content for productivity in organic farming systems. In contrast, at least in this first rotation, treatments with lower organic matter inputs benefited from high site fertility and showed no yield declines.