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 POC-MAOC framework, which frames SOC dynamics using only two time scales, may not always be sufficient to fully characterize SOC processes. Rather than advocating for a specific model configuration, we argue that the conceptual simplification of soil C into POC and MAOC might fail to capture the multiple timescale responses frequently observed in experimental studies. Furthermore, as transfer rates play a key role in determining SOC persistence, it is important to better understand and quantify how C is transferred toward MAOC and how these processes can be represented in models.
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.
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 based on field measurements and from 2.98 to 5.34 Mg C ha−1 yr−1 according to model simulations. However, treatment-dependent discrepancies were observed between modelled and field-based SOC stocks. While Compost and Mixture showed close agreement, Biochar exhibited the largest mismatch, likely due to its intrinsic properties that complicate field quantification and are not fully represented in current SOC models, posing challenges for monitoring and verification within carbon accounting frameworks.
Recent meta-analyses suggest risks of increased nitrate (NO3-) leaching with the implementation of reduced tillage practices. This study aimed to quantify effects of a subsidized and commonly implemented form of non-inversion tillage in Switzerland (NIT, i.e. chisel ploughing) in comparison to conventional tillage (CT, i.e. mouldboard ploughing) on NO3- leaching and its driving processes (i.e. water fluxes, soil temperature, plant uptake). A lysimeter experiment was conducted at the lysimeter facility Reckenholz/Zurich in Switzerland, mimicking tillage differences. Results after three years of treatment implementation show that during the following three years, tillage treatment had a significant effect on NO3- leaching in one of three seepage periods for two of three soil types considered. NIT reduced NO3- leaching in the seepage period 2014/2015 by 42 % on a Cambisol from Reckenholz and 32 % on a Luvisol from Schafisheim, respectively. The observed effect was driven by differences in NO3- concentrations in seepage water rather than seepage water amounts. Differences in NO3- concentrations could be attributable to structural differences in the topsoil, leaving larger amounts of soil N exposed to matrix water flow in the disturbed topsoil under CT than in the largely undisturbed topsoil under NIT. Also, differences in crop residue amount between treatments could have contributed to NO3- concentration differences. The treatment impact on NO3- leaching was most pronounced during and shortly after a bare soil period following sugar beet cultivation, which coincided with above-average spring precipitation. Considering that winter and spring precipitation is expected to increase with progressing climate change in Switzerland, reduced soil management may hold potentials to mitigate NO3- leaching in the face of progressing climate change. However, more research is needed to prove the relevance of this mechanism and its sensitivity to soil, climate and management drivers.
Abstract. Glacial retreat has uncovered vast landmasses in the European Alps over the last 150 years. Soil formation in these areas is likely slow due to low temperatures, lack of moisture, and short growing seasons. Previous studies have however focused solely on dry soils, omitting any water saturated locations. Our research shows that these water saturated locations are key locations of daytime CO2 uptake and have a significant role in carbon storage in the proglacial valley, despite their small surface area (<5 %). Loss-on-ignition analyses showed certain wetland soils contained up to 85 % carbon, suggesting these wetlands can become peatlands over time, storing large amounts of carbon. CO2 flux measurements showed atmospheric CO2 uptake in wetlands of all measured ages, even as young as 5 years after deglaciation. As little moss or plant cover was generally observed at locations < 50 years, the autotrophic microbial community likely plays an important role in these young systems. Non-saturated locations showed a much larger variation in daytime CO2 fluxes, with both emission and uptake of CO2 being observed across ages. Overall, our research shows that wetlands are hotspots of biological activity and pedogenic processes in proglacial areas and should therefore receive more attention in proglacial research.
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.
Arctic landscapes could add 55-230 Pg of carbon (in CO2 equivalent) to the atmosphere, through CO2 and CH(4 )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 & micro;m), 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 (C-def) 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 C-def. Here, we aim to (i) develop spectroscopic models to estimate the MAOC and C-def of 482 Australian topsoil samples, (ii) model MAOC and C-def using mid-IR spectra and an interpretable machine learning algorithm, and (iii) further interpret the MAOC and C-def models using SHapley Additive exPlanations (SHAP). Using frontier line analysis, we fitted a function to the upper envelope of the MAOC vs. clay + silt relationship to derive C-def. We recorded mid-IR spectra of the samples and used the regression trees method CUBIST to model MAOC content and C-def. We interpreted these models by examining the regression trees and using SHAP. The models were unbiased and estimated MAOC content with R-2 of 0.86 and RMSE of 2.77 (g kg soil(-1)), and C-def with R-2 of 0.89 and RMSE of 3.72 (g kg soil(-1)). Model interpretation showed that C-def estimates relied on negative interactions with absorptions from organic matter functional groups and positive interactions with absorptions from clay minerals. Our results demonstrate that mid-IR spectra can effectively estimate MAOC and soil C-def, providing a rapid, cost-effective method for assessing and monitoring this critical soil function.
Paleosols formed by the burial of topsoil during landscape evolution can sequester substantial amounts of soil organic carbon (SOC) over millennia due to protection from surface disturbances. We investigated the moisture sensitivity of buried SOC storage in the Brady paleosol, a loess-derived soil in Nebraska, USA, where historical aeolian deposition during the Pleistocene-Holocene transition buried soils up to 6 m deep. Topsoils from erosional (up to 1.8 m depth) and burial (up to 5.8 m depth) transects were incubated under two moisture regimes - continuous wetting (60 % water-holding capacity) and repeated drying-rewetting - to assess soil organic matter (SOM) vulnerability to changing hydrologic conditions. SOC decomposition rates modeled from CO2 fluxes were consistently higher in erosional than burial settings, with surface re-exposure of Brady soils enhancing microbial accessibility and destabilization. A two-pool model showed that >96 % of SOC was stored in a slow-cycling pool, particularly in deeply buried soils where stabilization was linked to mineral association, fine particles, and Ca-mediated flocculation. However, this pool decomposed more rapidly in shallower Brady soils (higher turnover rate relative to buried soil), reflecting increased microbial responsiveness to surface-driven processes. Drying-rewetting cycles caused greater C losses from Brady soils than continuous wetting, despite the dominance of the slow pool and depletion of labile C. These cycles also accelerated fast pool decay in modern soils and erosional transects, whereas burial dampened variability in Brady soils. Although continuous wetting increased overall decay in burial transects during the incubation period, wet-dry cycles destabilized the slow pool, which may result in greater long-term C loss. Together, these results underscore the importance of burial depth, geomorphic context, and moisture regime in shaping the long-term vulnerability of ancient SOC under climate change.
Although soil C is a critical component of soil health, studies robustly exploring the agronomic and pedoclimatic effects on soil C are limited, especially at the landscape scale. Therefore, a dataset of 1490 topsoil samples from agricultural fields across Ontario was used to evaluate the impacts of agronomic and pedoclimatic factors on eight soil C indicators including chemistry and thermal stability of soil C using the programmed pyrolysis approach. Soil C quality and stability were largely controlled by the inherent soil characteristics such as soil texture. Significant interactive effects of cropping system and tillage intensity on soil C indicators were observed; however, the number of significant effects varied among the three soil textural classes. All soil C indicators were significantly different among the cropping systems for the coarse textured soils, but the cropping system differences decreased under medium and fine textured soils. From the pyrolysis analysis, the hydrogen index (HI) and oxygen index (OI) also confirmed that the soil C chemistry was influenced by the cropping system. For instance, orchard systems had stable pools of soil C whereas vegetable systems were associated with less advanced degree of soil C decomposition. Remaining soil management variables (cover crop use, tillage intensity, and organic amendments) had a weaker influence than cropping systems and soil textural classes on soil C indicators. Principal component analysis revealed a close association of soil C indicators with the mean annual precipitation (MAP) and cropping system; suggesting that the quantity and quality of soil C inputs associated with different cropping systems and increase in precipitation had a large influence on soil C. Our results confirm the significant effects of agronomic and pedoclimatic variables on chemistry, thermal stability, and composition of soil C pools, which have long-term implications on soil C storage, mitigating global climate change, and improving soil health.
Mineral-associated organic matter, the dominant form of relatively stable carbon (C) in soil, often co-occurs with reactive iron (Fe) and aluminum (Al) phases across soils. Yet, how organo-metallic associations at the molecular scale give rise to emergent soil properties such as aggregate formation and the persistence of organic matter (OM) in soil remains unclear. The organo-metallic glue hypothesis proposes that dissolved metal released from weathering and microbially processed OM form cohesive organo-metallic phases that bind other particles into stable assemblages. We tested this concept using an artificial soil system comprising crushed rocks (fine basalt: 20-38 & micro;m, coarse basalt and granite: 38-75 & micro;m, and river sand), mixed with leaf compost and microbial inoculum, subjected to eight wet-dry cycles using artificial rainwater (pH 4.7) over 55 d. Sequential density fractionation after the incubation revealed the formation of meso-density, organo-mineral assemblages (1.8-2.4 g cm-3: MF) in the following order: fine basalt > coarse basalt > granite > sand. The accretion of C and oxalate-extractable Fe, Al, and Si in MF generally followed the same pattern. Fine basalt showed the strongest increase in extractable metals, especially Fe, in MF and the highest leaching of Fe and base cations (esp. Na and Ca). Enrichment of extractable Fe, Al, and Si in MF and their slight depletion in the high-density fraction (> 2.4 g cm-3) suggest that weathering-derived metals first associated with OM, forming organo-metal-rich phases that subsequently bound other particles to form organo-mineral assemblages. MF formed in fine basalt treatment had the C : (Fe+Al) molar ratio of 0.6, consistent with organo-metal coprecipitates. Preferential incorporation of microbially-processed, N-rich OM into MF in the two basalt treatments was indicated by lower C:N ratios by 23-25 units and enrichment of delta 13C and delta 15N by 0.9 parts per thousand-1.2 parts per thousand and 0.6 parts per thousand, respectively, relative to low-density fraction (< 1.8 g cm-3). SEM and STXM/NEXAFS analyses of limited MF materials confirmed the presence of shaking-resistant microaggregates and the co-localization of microbially altered C with Fe and Al. Collectively, these results provide experimental evidence supporting the organo-metallic glue hypothesis and demonstrate that basaltic rock weathering can promote organo-mineral assemblage formation. This mechanism links microbial processing, mineral weathering, and reactive metal dynamics, offering insights into early pedogenesis and soil OM formation under rock amendment conditions.
Soil health assessment depends on the appropriate selection of indicators and robust, sensitive methods for its determination. In this study, four integrative approaches were evaluated to assess the impacts of no-till systems with and without agricultural terraces on soil health in Southern Brazil. The different methods used were: (1) Principal Component Analysis (PCA); (2) expert opinion (EO); (3) Soil Fertility and Biology approach (FERTBIO), based on the Soil Bioanalysis framework; and (4) Soil Management Assessment Framework (SMAF). All approaches followed four steps: (i) selection of indicators; (ii) interpretation of indicators; (iii) integration of indicators; and (iv) calculation of soil health indices. The methods varied in the steps of indicator selection, interpretation, and the approach to indicator integration. The indicators used included physical (bulk density, total porosity, soil penetration resistance, and water retention capacity), chemical (pH, calcium, phosphorus, potassium, organic matter, CEC, and base saturation), and biological indicators (microbial biomass carbon, beta-glucosidase, and arylsulfatase). Crop yield was evaluated for maize (2019/2020 and 2021/2022 harvests), wheat (2021 harvest), and soybean (2020/2021 harvest). Descriptive statistics, median comparisons, principal component analysis, and Spearman correlation analysis were applied to analyze the results. The results showed that only the EO and FERTBIO approaches were sensitive enough to detect differences in soil health between management systems, indicating that no-till with terraces resulted in better soil health. Biological indicators were more sensitive in differentiating treatments, showing a rapid response in the short term. Maize (2019/2020 harvest) and wheat (2021 harvest) yields were higher under the no-till with terraces treatment. Over time, crop yield showed a stronger relationship with soil health. The results highlight the importance of selecting appropriate indicators for soil health assessment and reinforce the benefits of agricultural terracing for the sustainability of production systems.
A better understanding of peatland dynamics requires more data on more peat properties than provided by existing databases. These data needs may be addressed with resource-efficient measurement tools, such as models that predict peat properties from mid-infrared spectra (MIRS). High-quality spectral prediction models are already used for mineral soils, but similar developments for peatland-focused research lag behind. Here, we present transmission-MIRS prediction models for peat that are openly available, easy to use, include quality checks to assess prediction quality, and propagate prediction errors. The models target element contents (C, N, H, O, P, S, K, Ca, Si, Ti), element ratios (C/N, H/C, O/C), isotope values (delta 13C, delta 15N), physical properties (bulk density, loss on ignition (LOI), macroporosity, non-macroporosity, volume fraction of solids, hydraulic conductivity, specific heat capacity, dry thermal conductivity), thermodynamic properties (Gibbs free energy of formation (Delta Gf0)), and nominal oxidation state of carbon (NOSC). They are representative for a more diverse set of peat samples than currently existing peat-only models while having a competitive predictive accuracy. Relatively accurate predictions can be made, for example, for many element contents (C, N, O, S, Si, Ca, Delta Gf0, O/C, H/C, bulk density, and LOI). Many of these properties are not predicted by existing high-quality prediction models focusing on mineral soils. For some of the target variables, high-quality prediction models focused on mineral soils exist. These models may be more accurate, but reported predictive accuracies are not directly comparable because the training data is imbalanced in the number of organic versus mineral soil samples. We suggest that some soil properties are easier to predict for peat, whereas others are easier to predict for mineral soils, emphasizing that we need new approaches to meaningfully compare prediction errors of spectral models computed on datasets with variable amounts of organic soil samples. Our tests also indicate that replacing delta 13C and delta 15N measurements with MIRS models probably is unlikely to be feasible due to large prediction errors. Future studies should address the lack of open training and validation data for some peat properties (O, H, NOSC, Delta Gf0, LOI, H/C, O/C), the lack of mineral-rich peat samples, and improve and standardize model validation and comparison for models trained on data with very different proportions of peat soils. This study is a step to catch up with high quality standards set by models for mineral soils and provides models for several peat properties for which we could not find descriptions of previous models in the literature. By filling data gaps in the Peatland Mid-Infrared Database, we make a step towards providing the data required to better understand peatland dynamics.
Agroforestry systems - combining trees with crops and/or livestock - are increasingly promoted as sustainable and climate-resilient land-use strategies. Despite their widespread presence in the Sahel, experimental data on their potential as carbon sinks are scarce. This study presents a full-year, high-frequency dataset of CO2 fluxes in a Sahelian agro-silvo-pastoral parkland dominated by Faidherbia albida, located in Senegal's groundnut basin. CO2 fluxes were continuously measured using automated dynamic chambers, allowing the quantification of soil and crop respiration (Rch), gross primary production (GPPch), and net carbon exchange (FCO2ch) under both full sun and shaded (under tree canopies) environments. Seasonal patterns of CO2 fluxes were similar in both environments, with peaks during the rainy season. Rch and GPPch were significantly higher under tree canopies, indicating a "fertile island" effect. CO2 flux variability was primarily driven by soil moisture and leaf area index. Chamber-based GPP estimates closely matched those from Eddy Covariance measurements. On an annual scale, F. albida trees contributed approximately 23 % of total ecosystem GPP, with a carbon use efficiency of 0.48. Net annual vertical CO2 exchange was estimated at -1.4 +/- 0.46 and -1.8 +/- 0.17 Mg C-CO2 ha-1 using chamber and Eddy Covariance methods, respectively. These findings underscore the role of F. albida-based agroforestry systems as effective carbon sinks in Sahelian landscapes, supporting their potential contribution to climate change mitigation.
Soils across sub-Saharan Africa are exposed to extensive degradation processes, which can reduce their ability to produce crops and support livestock. While there has been a significant research effort focussing on soil degradation in sub-Saharan croplands, less research effort had been directed towards grasslands. Here, we tested the effectiveness of remote sensing to classify the soil degradation status of smallholder grazing lands. Focussing on grasslands used by smallholders in the districts of Nyando and Kuresoi in Western Kenya, we first used remote sensing (RS) to classify grasslands as productive grazing lands, grazing lands that followed a variable trend in vegetation productivity (transition), and unstable and unproductive (degraded) grazing lands. We then tested how this classification related to measured soil parameters indicative of soil degradation. We then used this classification, which was based on a temporal analysis of Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Normalised Difference Water Index (NDWI) between 2013 and 2018, to identify 90 field sites across the two districts, which we then sampled and analysed for a range of physical, chemical and biological soil properties. Only soil microbial biomass carbon (C) showed consistent alignment with the RS classification, although there was some overlap with other soil parameters at one or other of the study areas. To group the sites using the soil variables, which we split by study area and into stable (those that are slow to change) and transient (those that change rapidly in response to a changing pedological environment), K-means clustering was undertaken. Two sets of clusters were produced for each district for the stable and transient variables. For the stable variables, at Kuresoi one of these clusters included sites with higher levels of C, nitrogen (N), phosphorus (P) and pH, that aligned well with the RS classification, with seven out of 10 productive sites being assigned to this cluster. At Nyando one of the stable variable clusters included sites with high soil C and N, but low pH and relatively low soil bulk density, and corresponded to 12 out of the 16 productive sites. For the transient variables, agreement between the clusters and the remote sensing classification was poor indicating a lack of utility for degradation assessment. Overall, our results suggest that while the use of RS methods for classifying degraded grasslands and the soils supporting them does have significant advantages in terms of time and costs over field survey, supplementing these methods with a limited set of soil parameters related to nutrient cycling, such as microbial biomass C, soil P, percent C and N, and soil pH, could enhance our ability to identify degraded soils and target restoration efforts.
Glacial retreat has uncovered vast landmasses in the European Alps over the last 150 years. Soil formation in these areas is likely slow due to low temperatures, lack of moisture, and short growing seasons. Previous studies have however focused solely on dry soils, omitting any water saturated locations. Our research shows that these water saturated locations are key locations of daytime CO2 uptake and have a significant role in carbon storage in the proglacial valley, despite their small surface area (<5 %). Loss-on-ignition analyses showed certain wetland soils contained up to 85 % carbon, suggesting these wetlands can become peatlands over time, storing large amounts of carbon. CO2 flux measurements showed atmospheric CO2 uptake in wetlands of all measured ages, even as young as 5 years after deglaciation. As little moss or plant cover was generally observed at locations < 50 years, the autotrophic microbial community likely plays an important role in these young systems. Non-saturated locations showed a much larger variation in daytime CO2 fluxes, with both emission and uptake of CO2 being observed across ages. Overall, our research shows that wetlands are hotspots of biological activity and pedogenic processes in proglacial areas and should therefore receive more attention in proglacial research.
Enhanced Weathering using basalt rock dust is a scalable carbon dioxide removal (CDR) technique, but quantifying rock weathering and CDR rates poses a critical challenge. Here, we investigated realized inorganic CO2 removal (defined as the sum of the change in dissolved inorganic C leaching and in neoformed solid inorganic C) and weathering rates by treating mesocosms planted with maize with basalt (0, 10, 30, 50, 75, 100, 150 and 200 t ha(-1)) and monitoring them for 101 d. We observed no significant realized inorganic CO2 removal, as leaching of dissolved inorganic carbon did not increase and soil carbonate content declined over time. To gain insights into the weathering processes, we traced the fate of base cations in the soil and plants. This analysis showed that most base cations were retained in the topsoil reducible pool, typically associated with iron (hydr)oxides, while increases in the exchangeable pool were about a factor 10 smaller. Soil base cation scavenging exceeded plant scavenging by approximately two orders of magnitude. From the base cations in all pools (soil, soil water and plants), we quantified log weathering rates of -11 mol total alkalinity per m(2) basalt per s. The potential inorganic CO2 removal, defined as the maximum inorganic CO2 removal achievable if all weathered base cations, adsorbed by soil pools in this experiment, would leach out of the soil and be fully balanced by carbonate anions, was estimated at 26 kg CO2 t(-1) basalt. In conclusion, despite clear weathering of basalt rock, we found no inorganic CO2 removal within the timescale of this experiment. The observed increase of aluminum in association with the reducible soil fraction indicate the formation of secondary minerals. These, along with enhanced base cation exchange, may contribute to long-term soil fertility and promote the stabilization of soil organic matter.
A plant's development is strongly linked to the water and carbon (C) flows in the soil-plant-atmosphere continuum. Ongoing climate shifts will alter the water and C cycles and affect plant phenotypes. Comprehensive models that simulate mechanistically and dynamically the feedback loops between water and C fluxes in the soil-plant system are useful tools to evaluate the sustainability of genotype-environment-management combinations that do not yet exist. In this study, we present the equations and implementation of a rhizosphere-soil model within the CPlantBox framework, a functional-structural plant model that represents plant processes and plant-soil interactions. The multi-scale plant-rhizosphere-soil coupling scheme previously used for CPlantBox was likewise updated, among others to increase the accuracy and stability of the model outputs. The model was implemented to simulate the effect of dry spells occurring at different plant development stages, and for different soil kinetic parameterisations of microbial dynamics in soil. We could observe diverging results according to the date of occurrence of the dry spells and soil parameterisations. For instance, earlier dry spells (from 11th to the 18th day of growth) led to a lower cumulative plant C release, while later dry spells (from 18th to the 25th day of growth) led to higher C input to the soil. For more reactive microbial communities (higher maximum C uptake rate and (de)activation rates), this higher C input caused a strong increase in CO2 emissions. For the same weather scenario, we observed lower microbial CO2 emissions with less reactive communities. This model can be used to gain insight into C and water flows at the plant scale, and the influence of soil-plant interactions on C cycling in soils.
Soil health assessments increasingly rely on indicators to infer soil functions and ecosystem services; however, the extent to which these indicators accurately represent water-related soil processes remains uncertain. This study investigates the relationships between soil properties and provision of water regulation ecosystem services across three contrasting pedo-climatic regions in Austria, Italy, and Tunisia. Using 315 soil profiles, we applied a process-based soil-water model to quantify infiltration, runoff triggering, groundwater recharge, and crop water stress index under representative climatic conditions. We evaluated commonly used soil indicators, including saturated hydraulic conductivity, available water content, bulk density, organic matter content, clay content, saturated soil water content, soil depth, and macroporosity. Pairwise correlation and multiple linear regression analyses were employed to assess interactions between soil properties and soil water balance components. Results show that indicator-process relationships vary considerably across sites and are often non-linear, with specific correlations reflecting local combinations of soil texture, structure, profile development, and climate. For example, in the Marchfeld region (Austria), infiltration exhibited a strong positive correlation with bulk density (r=0.74, p<0.001), while the crop water stress index showed a significant negative correlation with soil depth (r= -0.35, p<0.001). In the Bologna area (Italy), the study also indicated that groundwater recharge was positively correlated with soil macro-porosity (r=0.45, p<0.001), whereas macro-porosity exhibited a strong negative correlation with flux-to-runoff (r= -0.66, p<0.001), underscoring the key role of soil structural characteristics in controlling infiltration-recharge-runoff dynamics. In addition, multiple linear regression models were developed to assess the relevance of the individual soil properties and their interactions in controlling soil water balance components. For instance, the infiltration model for Marchfeld (r=0.79, p<0.001) was highly predictive and incorporated clay content, organic matter, and soil depth. Several widely used indicators exhibited weaker or inconsistent relationships with water-related processes than commonly assumed. For instance, saturated hydraulic conductivity alone was not a robust predictor of infiltration and recharge across sites, whereas soil depth and clay content emerged as recurrent controls, especially when considered jointly. Overall, this study highlights the value of process-based modelling for disentangling soil-climate interactions and cautions against the generalized use of static soil indicators in hydrological and soil health assessments.
