Rhizosphere-associated bacteria play a key role in enhancing plant performance under saline and nutrient-limited soil conditions, where plant establishment is strongly constrained. In this study, we evaluated the plant growth-promoting potential of rhizobacteria isolated from the rhizosphere of wild-growing Lotus creticusPseudomonas protegens, Pseudomonas sesami, Pseudomonas versuta, Pseudomonas helleri, and Pseudomonas trivialis. Phenotypic characteristics, including IAA production, phosphate solubilization capacity, cellulase and protease activities, and tolerance to salinity and temperature, were evaluated. Additionally, a pot experiment was conducted to assess the impact of inoculation on L. creticusPseudomonas protegens−1), and notable cellulase and protease activities. It also demonstrated high tolerance to salinity (up to 13 % NaCl) and temperature (up to 45 °C). Comparatively, Pseudomonas sesamiAspergillus ochraceus. The pot experiment revealed that inoculation with Pseudomonas helleriPseudomonas trivialisP < 0.05) enhanced the aerial dry biomass of L. creticusPseudomonas protegensPseudomonas
The assessment of soil health relies on sensitive indicators to detect management-induced changes, yet the analytical reliability of these indicators following long-term storage is rarely assessed. We investigated how multi-year storage of air-dried samples influenced the concentrations of several common soil health indicators, including water-extractable organic carbon and nitrogen (WEOC, WEN), mineralizable carbon (Cmin), and permanganate-oxidizable carbon (POX-C), using archived samples from a cover crop experiment. Concentrations of WEOC nearly doubled after three years of storage, while WEN decreased by 19 %. A small but significant 6 % increase in Cmin concentration was also observed. In contrast, POX-C concentrations remained stable, indicating robustness to storage effects. These storage effects were consistent among three treatments with different cover crop species. In addition, WEOC concentrations consistently declined over time in this experiment along with four long-term agricultural sites in the USA, but their bulk soil organic carbon (SOC) or soil organic matter (SOM) did not. These results suggest that multi-year storage of air-dried samples inflates the WEOC pool. Therefore, we caution the use of WEOC as a soil health indicator in archived samples, as the observed variations might reflect storage artifacts rather than genuine management impacts.
Soil respiration is a key component of the global carbon cycle, yet its dynamics in urban Mediterranean environments remain poorly understood. This study investigated the effects of soil temperature, soil moisture, and plant community on soil CO2Diplotaxis virgata, Hordeum leporinum, MalvaDactylis glomerata) were monitored across three urban green spaces. Soil CO2Q102Malva22
Forest soils underpin ecosystem resilience and productivity but are increasingly threatened by natural and anthropogenic disturbances. Monitoring post-disturbance soil degradation at operational scales remains challenging in forests, where ground-signal obstruction and reliance on proxy indicators constrain remote sensing (RS) applications. To identify where RS can benefit soil monitoring and inform emerging reporting needs, we developed a structured evidence map of studies assessing post-disturbance forest soil degradation using RS methods. From 4338 records, 72 primary studies were synthesized across disturbance types, biomes, platforms, scales, and indicators. The evidence base is dominated by wildfire and harvesting, reflecting disturbance pathways that produce observable surface impacts. Multispectral satellite data remain the primary tool for mapping post-fire severity and erosion-related indicators, while LiDAR and stereo-photogrammetry are most often used to quantify surface deformation after harvest operations. Indicators tied to subsurface physical, chemical, or biological change remain sparsely represented due to observability limits. Overall, RS is most effective for mapping disturbance footprints, detecting surface-expressed indicators, and stratifying landscapes for targeted field assessment, rather than directly measuring soil properties. This evidence map clarifies the benefits and limits of RS, identifies persistent gaps, and highlights priorities for developing disturbance-aware soil-monitoring frameworks. It also clarifies which soil indicators are most consistently observable with RS and which require complementary approaches. By linking disturbance processes to observable indicators, this synthesis helps identify realistic RS-supported objectives that may inform future reporting frameworks within national forest monitoring and assessment programs.
The utility of rice straw as an organic fertilizer has been widely recognized as a promising approach to enhancing soil fertility. However, straw return is currently in a dilemma, as it may also provoke greenhouse gas (GHG) emissions, leading to serious environmental consequences. It is urgent to reveal the feasibility of straw incorporation regarding soil fertility improvement without notable increases in GHG emissions. Here, a soil microcosm experiment was conducted using paddy soils collected from a long-term rice straw incorporation field experiment. The treatments of the field experiment, namely CK, ST1, ST2, and ST3 corresponding to the straw application rates of 0 %, 50 %, 100 %, and 150 % of the local rice straw yield, respectively, were continued in the microcosm experiment. The dynamics of GHG fluxes and concentrations in soils, and the variations in the abundances of soil microbial communities were systematically determined. The results indicated that ST1 treatment obviously improved soil fertility but did not induce significant elevation of global warming potential (GWP) with only 3 % increase compared to CK. Although ST2 and ST3 treatments showed greater improvements in soil fertility, they significantly increased GWP by up to 151 %. The minimal GWP increase under ST1 was mainly attributed to the significant reduction in N2O emission and the slight rise in CH4nosZII abundance and the lowest nirS/nosZII ratio, indicating its highest N2O consumption ability. Meanwhile, its CH44−1), and most of the produced CH4
Manure is widely applied in greenhouses to enhance soil organic carbon (SOC) and improve fertility. However, how SOC fractions and their chemical stability change under different soil textures and long-term manure inputs remains unclear. We investigated greenhouse soils with 2–50 years of manure application in loam and sandy loam. SOC, easily oxidizable carbon (EOC), microbial biomass carbon (MBC), dissolved organic carbon (DOC), particulate organic carbon (POC), and mineral-associated organic carbon (MAOC) were quantified. The molecular structures of SOC were analyzed via 13C NMR spectroscopy. Results showed that SOC in loam stabilized after about 20 years of manure application, whereas sandy loam reached equilibrium within 2 years. In loam, aromatic C and carbonyl C in SOC increased, raising the aromaticity index (AI); in sandy loam, alkyl C increased, elevating alkyl C to O-alkyl C (
Intensive agricultural practices have degraded soil fertility and polluted natural resources in Spanish citrus orchards, highlighting the need for more sustainable management strategies. Composting rice straw (RS) and sewage sludge (SS), two residues that are difficult to manage in Mediterranean regions, offers an environmentally sound alternative for residue valorisation and soil fertility restoration. This study assessed the agronomic performance of two industrial-scale composts produced from pruning residues (PR)/SS and RS/SS in a commercial Mediterranean citrus orchard. The effects of compost application at two rates were evaluated through analyses of soil physical, chemical, and biological properties, as well as foliar nutrient concentrations, yield, and fruit quality. RS/SS compost contained higher nutrient levels, particularly P, suggesting its potential as a P-rich organic fertiliser. Compost application reduced soil pH and slightly increased electrical conductivity without exceeding critical thresholds. Soil organic matter, organic N, available P and K, and Zn contents generally increased following compost application, while improvements in soil biological indicators were mainly observed during the first growing season. Effects on foliar nutrient status, yield, and fruit quality were limited. These results indicate that industrial-scale RS/SS compost application represents a sustainable strategy for residue valorisation and soil fertility improvement in Mediterranean citrus systems. Moreover, successive compost applications improved several soil fertility indicators and support the partial replacement of mineral P fertilisation under similar conditions.
Soil health is foundational to ecological sustainability, economic productivity, and societal wellbeing. However, fragmented perspectives on what constitutes “healthy soil” hinder coherent policies and business models. This article addresses that gap by offering a value-based framework to guide soil-health initiatives. Building on the Total Economic Value framework, six complementary perspectives are identified: (1) productivist, (2) ecosystem services, (3) resilience, (4) non-use value, (5) intrinsic value, and (6) social innovation. These represent different motivations and beneficiaries – from private returns through public goods, to moral duties and collective empowerment. Each perspective implies specific opportunities and challenges for policy design. For instance, direct subsidies may be justified in cases where economic returns are delayed or insufficient, while ecosystem service payments require credible measurement and market mechanisms. Resilience investments often suffer from coordination failures, and intrinsic or social values lack clear economic incentives, requiring legal, educational, or institutional support instead. The article argues that no single policy instrument can serve all these perspectives effectively; rather, a differentiated, multi-perspective strategy is needed to align incentives, avoid over-subsidization, and ensure equitable access and accountability. This framework provides a foundation for designing inclusive and adaptive policies that foster sustainable soil stewardship across diverse stakeholders.
Accurately estimating crop yields and soil organic carbon (SOC) dynamics is essential for agricultural planning, carbon accounting, and sustainable land management. However, process-based agroecosystem models often produce divergent estimates due to variations in model structure, parameterization, and underlying assumptions. In this study, we developed a multi-model ensemble framework that integrates three widely used process-based models-Daily Century (DAYCENT), DeNitrification DeComposition (DNDC), and Ecosystem model (ECOSYS)-to simulate crop yields and SOC stock changes (0–30 cm) across cultivated lands of the continental United States (CONUS) at 4 km2 spatial resolution. Each model was parameterized using harmonized environmental, soil, and management datasets and evaluated using observed crop yields from the National Agricultural Statistics Service and measured SOC data from the Rapid Carbon Assessment. For the baseline period (2014–2023) under conventional corn–soybean rotation, the ensemble mean showed strong agreement with observations (corn: 7.7 vs. 8.5 Mg ha−1, RMSE = 3.0 Mg ha−1; soybean: 2.5 vs. 3.0 Mg ha−1, RMSE = 1.0 Mg ha−1), while simulated SOC stocks (5.5 vs. 4.8 kg C m−2, RMSE = 2.5 kg C m−2) closely matched measured data. Spatially, the ensemble model projected SOC gains in the Midwest and Southeastern regions and losses in the Great Plains and Western United States, underscoring the importance of region-specific management practices. Overall, the ensemble framework characterizes structural uncertainty by capturing the range of plausible model responses, while the ensemble mean provides a more reliable estimate of system behavior than any individual model. By integrating diverse model perspectives, this approach enhances predictive robustness and reduces dependence on model-specific assumptions. Consequently, it offers a scalable and data-driven framework for assessing soil carbon dynamics and crop productivity across US agroecosystems, while explicitly characterizing and communicating uncertainties associated with model variability.
In the last decade, the conceptual framework that characterizes soil organic carbon (SOC) into particulate organic carbon (POC) and mineral-associated organic carbon (MAOC) fractions has gained traction in studies of C dynamics. This SOC characterization is useful for developing empirical studies and for parsimonious model parameterizations. However, rigorous testing of model structures incorporating the POC-MAOC framework is still lacking, particularly tests evaluating whether this framework can adequately reproduce simultaneous measurements of changes in C pool contents and respiration fluxes. We conducted an incubation experiment using control and litter-addition treatments, measuring changes in SOC fraction contents and respiration fluxes throughout the incubation. Then, we applied an inverse modelling approach to compare the performance of 2-pool (POC-MAOC) and 3-pool models (which also included a faster-cycling litter C pool) to reproduce the observed data. We then calculated the C ages and transit times to explore the predicted C persistence. Finally, we performed simulations to evaluate the effects of different model structures and parameterizations on SOC persistence. For both treatments, we observed that 2-pool models were unable to simultaneously reproduce the changes in C pool contents and respiration, while the 3-pool models adequately predicted both variables and yielded lower C ages and transit times. 2-pool models collapsed POC dynamics operating across different timescales into a single one, failing to capture the distinct respiration phases and gradual C pool changes. Instead, 3-pool models distributed these processes among compartments: the Litter C pool captured fast-cycling dynamics, allowing POC and MAOC to better represent intermediate- and long-term dynamics, respectively. The fact that 3-pool models outperformed 2-pool models -even in control soils- indicates that, in our soils, POC is a heterogeneous pool that cannot be adequately represented as a single compartment. We also found that both model structure and changes in key parameters affected C persistence estimations: models that included shorter pathways to MAOC, or allowed faster transfers into more persistent pools, predicted higher C age and transit time, showing how model structure shapes SOC contents and persistence estimates. This study highlights that the
Confronting the global need for climate-smart agriculture, this study investigated the major factors controlling CO22> sludge compost (SLS) > goat manure-leaf compost (GLCS) > food waste compost (FWCS). Multiple regression analyses identified soil available phosphorus (AP) and pH as the key interactive drivers of CO2In this experiment, four composts (FWC, GLC, CDC, SL) were applied at 2.5 % and 10 % rates to typical Malaysian tropical soils and incubated for 90 d. The CO22
Modelling the persistence of soil organic carbon (SOC) is currently recognised as a key approach to enhance our understanding of its potential contribution to climate change mitigation. Despite its value, SOC modelling is challenged by soil heterogeneity and the limited availability of reliable data for model calibration and validation, often resulting in discrepancies between simulated and measured SOC dynamics. This study employs a modified version of the RothC model, adapted for amended soils, to simulate soil C dynamics under an 11-year experiment in an organic olive grove. The experiment evaluated four treatments of soil amendment: Compost, Biochar, a Mixture of both, and a Control soil without amendment. By comparing the SOC data simulated by the RothC model with experimental field-sampling data, we assessed the model's accuracy in estimating SOC accumulation and stability in the soil. Both field measurements and RothC simulations consistently identified Biochar as the most effective amendment for soil carbon accumulation over the 11-year period, followed by the Mixture and Compost treatments. Estimated soil carbon sequestration rates ranged from 1.67 to 2.66 Mg C ha−1 yr−1−1 yr−1
Global average temperatures are forecast to increase by 4 °C by 2100 under the Intergovernmental Panel on Climate Change SSP5-8.5 scenario. This warming could accelerate soil organic carbon (SOC) mineralization, net loss of soil carbon to the atmosphere, and consequently exacerbate global warming through a positive feedback loop. It is generally assumed that mineral-associated organic matter (MAOM) stocks are less sensitive to warming compared to particulate organic matter (POM), especially in the subsoil; yet more empirical data investigating the whole-soil responses to warming is still required to rigorously test this assumption.Our study was conducted in a whole-soil field warming experiment in a temperate mixed-conifer forest at Blodgett Forest Research Station, University of California, Berkeley, which had been subjected to 9.5 years of warming. Soils from three depths (10–20, 40–50, and 80–90 cm) were separated into three density fractions, free POM (fPOM), occluded POM (oPOM), and MAOM. We then investigated the SOC concentration and composition of bulk soil and fractions with elemental analysis and diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy. In subsoils below 50 cm, a decade of experimental warming caused bulk carbon loss and shifted its composition towards lignin and C–H aromatic bonds. Warmed plots had significantly lower mass of the POM fractions relative to control plots in the deep soil (80–90 cm) with no significant difference at or above 50 cm. fPOM composition showed a significant shift towards enrichment in lignin at 40–50 cm but not in topsoils. Meanwhile, MAOM mass and composition shifted along the depth gradient but were not significantly affected by warming. This study at Blodgett Forest thus supports the assumption that POM will be more responsive to warming in the subsoil than MAOM.
Reduced tillage lowered nitrate leaching by up to 42 percent in some soils during a very rainy period without crop cover. The results suggest that reduced soil management could help protect water quality under future climate conditions with wetter winter and spring conditions.
Recent meta-analyses suggest risks of increased nitrate (NO
Plastic films have been improving agricultural production and covering an increasing surface area of cropland in the last decades. Yet their use has been connected to the generation of plastic residues, potentially acting as a main secondary microplastic source in agricultural soils. Monitoring the generation of plastic film residues is crucial for identifying good management practices and assessing the risk of plastic use in agriculture. Remote sensing has been qualified as a valuable tool for monitoring macroplastic residues mainly on waters, while its use on agricultural soils is mostly unexplored. Our study combined proximal and remote sensing techniques to lay the foundations of UAV (Unmanned Aerial Vehicle) use for monitoring macroplastic film residues on cropland.Through proximal and UAV acquisitions of five-band multispectral data (i.e., blue, green, red, red edge, near infrared), we highlighted the potential of off-the-shelf miniaturised sensors and identified possible workflows for detecting macroplastic film residues. Our findings highlight a greater, or at least similar, efficacy of spatial resolution compared to spectral resolution, encouraging the use of high-resolution RGB cameras over multispectral cameras. Through proximal acquisitions of hyperspectral data on 8 different agricultural plastic films, we built spectral libraries and located absorption features at wavelengths that are not commonly available on off-the-shelf multispectral cameras. We highlighted that these absorption features unambiguously identify plastic films on cropland and offer the potential to distinguish plastic types, encouraging the development of sensors tailored for plastic detection.
Soils play a dynamic role in the carbon cycle, functioning as both a source and a sink for atmospheric carbon. Despite their importance, uncertainties in soil-atmosphere interactions persist due to the complex processes governing soil carbon dynamics. Microbial access to substrate is a key mechanism regulating organic C decomposition. Evidence suggests this access is diffusion-limited, as reflected in the strong dependence of soil respiration on water availability. In recent years, non-destructive geophysical tools, including electrical conductivity measurements, have been used to determine the water content of soils and the connectedness of the water phase in the soil pore network. As both respiration and electrical conductivity may depend on water availability and connectivity, our study aimed to determine whether electrical conductivity measurements could serve as a proxy for soil respiration when microbial activity is potentially diffusion-limited. This was done by measuring electrical conductivity and respiration rates at different matric potentials, using sieved and undisturbed top- and subsoil samples taken from conventional tillage and conservation agriculture management plots of a Luvisol. Our results revealed an initial increase followed by a subsequent decrease in soil respiration with increasing matric suction (i.e., decreasing water saturation). Electrical conductivity decreased as the soil desaturated. The two variables exhibited a significant nonlinear relationship, indicating a shared sensitivity to changes in aqueous phase connectivity. Finally, a quantitative approach for estimating the tortuosity of the water phase in the samples, based on the electrical conductivity measurements, was used to show a clear relationship between water phase tortuosity and respiration measurements. These results thus suggest that both measured variables depend on the connectedness of the aqueous phase and highlight the potential of electrical conductivity measurements as a mechanistically informed proxy for diffusion-constrained soil respiration.
Soil organic matter (SOM) is a complex mixture of organic compounds derived from the decomposition of plant and animal residues. SOM that has undergone microbial transformation and formed stable associations with minerals represents the stabilized fraction of soil organic carbon, which differs from the simple physical accumulation of external organic materials. Current understanding suggests that particulate organic matter (POM) includes both undecomposed and partially decomposed residues. Conventional analytical methods cannot clearly distinguish undecomposed exogenous organic residues from indigenous SOM. Consequently, increases in operationally defined POM are often misinterpreted as evidence of SOM stabilization or microbially transformed organic carbon formation. In this study, straw and biochar were magnetized through chemical coprecipitation and applied to the soil. Magnetic separation was performed at successive incubation times to isolate undegraded magnetic residues, thereby enabling more accurate tracking of SOM dynamics. Five treatments were established: blank control (CK), untreated straw (CS), untreated biochar with carbon input equivalent to straw (Bc), magnetized straw (MCS), and magnetized biochar (MBc). The recovery of magnetized straw residues declined continuously and reached 54.55 % after 360 d, whereas biochar residues remained highly persistent at 92.48 %. In the CS and Bc treatments, the organic carbon content of POM fractions and their proportion in total SOM were consistently higher than in CK, particularly during early incubation. However, after removing undegraded residues by magnetic separation, values were close to those of CK. This result indicates that the observed POM increases mainly originated from undecomposed external residues rather than microbially stabilized SOM. On day 30, the apparent increase in particulate organic carbon (POC) was 63.48 % in CS and 58.99 % in Bc. Over time, the apparent POC increase in CS declined to 15.34 % by day 360, whereas that in Bc remained high (53.71 %). These findings suggest that interpreting total POM as stabilized or microbially transformed SOM may lead to misleading conclusions about SOM stability, particularly in short-term incubations or agroecosystems receiving fresh organic amendments. This study provides a basis for a more accurate evaluation of soil organic matter transformation dynamics and content.
Accurate mapping of soil properties is vital for many applications, yet existing models for digital soil maps often underestimate their spatial variability or prediction uncertainties, which introduces risk for applications such as irrigation and drainage management. This study introduces an approach, iterative residual correction (IRC), to update existing probabilistic soil maps when new soil observations become available. We demonstrated its application for enhanced soil mapping performance using a Californian case study. To implement this, we first generate prior probabilistic soil property maps using a pruned hierarchical Random Forest (pHRF) method. These prior estimates are then refined by integrating additional soil profile data and iteratively adjusting residuals of distribution of soil properties (reducing differences between observations and prior predictions) pixel by pixel. For this purpose, we employed Random Forest regressors to gradually adjust the soil property distributions and incrementally correct prior bias. Updated soil maps were evaluated over California and at 1 km resolution to test the methodology, using additional soil observations from the World Soil Information Service, the Soil Characterization Database, the University of California Riverside, and the United States Department of Agriculture Agricultural Research Service. Posterior soil texture predictions achieved an RMSE below 10, a 7 % relative reduction in errors (mass fraction of the fine-earth fraction) over priors. RMSE and spatial representation for soil organic matter and bulk density also improved. Furthermore, the method reduced prediction uncertainties (narrower prediction intervals compared to the priors) and enforced physical constraints on soil property bounds. Looking forward, this IRC method offers a scalable pathway to improve existing probabilistic soil maps, providing a strategy for the evolution of digital soil products as new soil observations emerge.
Arctic landscapes could add 55–230 PgCO2CO2CH4 emissions, by the end of this century. These estimates could be quantified more accurately by constraining the contribution of rapid thawing processes such as thermokarst landscapes to permafrost carbon loss, and by investigating the exposed organic carbon (OC) interacting with mineral surfaces or metallic cations, i.e., the nature of these interactions and what controls their relative abundance. Here, we investigate two contrasted types of hillslope thermokarst landscapes: an Active Layer Detachment (ALD) which is a one-time event, and a Retrogressive Thaw Slump (RTS) which repeats annually during summer months in the Cape Bounty Arctic Watershed Observatory (Melville Island, Canada). We analyzed mineralogy, total and soluble element concentrations, total OC and mineral–OC interactions within the headwalls of both disturbances, and within corresponding undisturbed profiles. Our results show that small fragments of biopolymers stabilized by chemical bonds account for 13 ± 5 % of total OC in the form of organo–metallic complexes and up to 6 ± 2 % associated with poorly crystalline iron oxides. If we add the mechanisms of physical protection of particulate organic matter in aggregates and larger molecules stabilized by chemical bonds, we reach 64 ± 10 % of the total OC being stabilized. Importantly, we observe a decrease in the proportion of mineral-bound OC in the deeper layers exposed by the retrogressive thaw slump: the proportion of organo–metallic complexes drops from ∼ 18 % in surface samples (2–22 cm) to ∼ 1 % in the deepest samples (50–70 cm). These results therefore suggest that the OC exposed by thermokarst disturbances at Cape Bounty is protected by interactions with minerals to a certain extent, but that deep thaw features could expose OC more readily accessible to degradation.
Soil carbon sequestration refers to the process of capturing atmospheric carbon through plant photosynthesis and storing it in soil as organic carbon. The primary mechanism for carbon sequestration is the adsorption of organic carbon molecules onto the mineral surfaces of the soil's fine fraction (clay + silt ≤ 20 µm), forming mineral-associated organic carbon (MAOC). Soil has a finite capacity to stabilise and sequester organic carbon, known as carbon saturation capacity, which depends on the proportion of reactive minerals in the soil. The difference between the current MAOC content and the carbon saturation capacity is referred to as the organic carbon saturation deficit (Cdef) or sequestration potential. Fourier-transformed (FTIR) mid-infrared (mid-IR) spectroscopy can simultaneously measure soil properties relevant to carbon stabilisation: organic carbon functional groups, clay and iron-oxide mineralogy and particle size. Therefore, we hypothesise that mid-IR spectroscopy can effectively and accurately estimate Cdef. Here, we aim to (i) develop spectroscopic models to estimate the MAOC and CdefCdefCdef+ silt relationship to derive Cdef. We recorded mid-IR spectra of the samples and used the regression trees method CUBIST to model MAOC content and Cdef. We interpreted these models by examining the regression trees and using SHAP. The models were unbiased and estimated MAOC content with R2−1), and CdefR2−1). Model interpretation showed that CdefCdef, providing a rapid, cost-effective method for assessing and monitoring this critical soil function.