Global Soil Organic Carbon Stocks Research Articles

Soil carbon in the world’s tidal marshes

Tidal marshes are threatened coastal ecosystems known for their capacity to store large amounts of carbon in their water-logged soils. Accurate quantification and mapping of global tidal marshes soil organic carbon (SOC) stocks is of considerable value to conservation efforts. Here, we used training data from 3710 unique locations, landscape-level environmental drivers and a global tidal marsh extent map to produce a global, spatially explicit map of SOC storage in tidal marshes at 30 m resolution. Here we show the total global SOC stock to 1 m to be 1.44 Pg C, with a third of this value stored in the United States of America. On average, SOC in tidal marshes’ 0–30 and 30–100 cm soil layers are estimated at 83.1 Mg C ha−1 (average predicted error 44.8 Mg C ha−1) and 185.3 Mg C ha−1 (average predicted error 105.7 Mg C ha−1), respectively.

Observational benchmarks inform representation of soil organic carbon dynamics in land surface models

Abstract. Representing soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon–climate feedbacks. Machine learning models can help identify dominant environmental controllers and establish their functional relationships with SOC stocks. The resulting knowledge can be integrated into ESMs to reduce uncertainty and improve predictions of SOC dynamics over space and time. In this study, we used a large number of SOC field observations (n=54 000), geospatial datasets of environmental factors (n=46), and two machine learning approaches (namely random forest, RF, and generalized additive modeling, GAM) to (1) identify dominant environmental controllers of global and biome-specific SOC stocks, (2) derive functional relationships between environmental controllers and SOC stocks, and (3) compare the identified environmental controllers and predictive relationships with those in models used in Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Our results showed that the diurnal temperature, drought index, cation exchange capacity, and precipitation were important observed environmental predictors of global SOC stocks. While the RF model identified 14 environmental factors that describe climatic, vegetation, and edaphic conditions as important predictors of global SOC stocks (R2=0.61, RMSE = 0.46 kg m−2), current ESMs oversimplify the relationships between environmental factors and SOC, with precipitation, temperature, and net primary productivity explaining > 96 % of the variability in ESM-modeled SOC stocks. Further, our study revealed notable disparities among the functional relationships between environmental factors and SOC stocks simulated by ESMs compared with observed relationships. To improve SOC representations in ESMs, it is imperative to incorporate additional environmental controls, such as the cation exchange capacity, and refine the functional relationships to align more closely with observations.

Land use drives the distribution of free, physically protected, and chemically protected soil organic carbon storage at a global scale.

Soil organic carbon (SOC) sequestration is increasingly emphasized as a climate mitigation solution, as scientists, policy makers, and land managers prioritize enhancing belowground C storage. To identify key underlying drivers of total SOC distributions, we compiled a global dataset of soil C stocks held in three chemical forms, reflecting different mechanisms of organic C protection: free particulate organic C (fPOC), physically protected particulate organic C (oPOC), and mineral-protected soil organic C (mSOC). In our dataset, these three SOC pools were differentially sensitive to the effects of climate, soil mineralogy, and ecosystem type, emphasizing the importance of distinguishing between physical and chemical C protection mechanisms. C stocks in all three pools varied among ecosystems: cropland soils stored the least amount in each pool, with forest and grassland soils both containing significantly more fPOC (40%-60% greater in each ecosystem) than croplands. oPOC stocks did not significantly differ from zero in croplands but were substantial in forest and grassland soils. Meanwhile, mSOC stocks were the greatest in grasslands and shrublands (90%-100% greater than croplands). In cropland soils, there were no major effects of tillage on C storage in any of the three pools, while manure addition enhanced mSOC stocks, especially when added with inorganic N. Thus, the human land use intensity in croplands appears to reduce SOC storage in all major pools, depending upon management; retaining native vegetation should be emphasized to maintain current global SOC stocks.

Evaluation of effects of heat released from SOC decomposition on soil carbon stock and temperature

AbstractHeat released from soil organic carbon (SOC) decomposition (referred to as microbial heat hereafter) could alter the soil's thermal and hydrological conditions, subsequently modulate SOC decomposition and its feedback with climate. While understanding this feedback is crucial for shaping policy to achieve specific climate goal, it has not been comprehensively assessed. This study employs the ORCHIDEE‐MICT model to investigate the effects of microbial heat, referred to as heating effect, focusing on their impacts on SOC accumulation, soil temperature and net primary productivity (NPP), as well as implication on land‐climate feedback under two CO2 emissions scenarios (RCP2.6 and RCP8.5). The findings reveal that the microbial heat decreases soil carbon stock, predominantly in upper layers, and elevates soil temperatures, especially in deeper layers. This results in a marginal reduction in global SOC stocks due to accelerated SOC decomposition. Altered seasonal cycles of SOC decomposition and soil temperature are simulated, with the most significant temperature increase per unit of microbial heat (0.31 K J−1) occurring at around 273.15 K (median value of all grid cells where air temperature is around 273.15 K). The heating effect leads to the earlier loss of permafrost area under RCP8.5 and hinders its restoration under RCP2.6 after peak warming. Although elevated soil temperature under climate warming aligns with expectation, the anticipated accelerated SOC decomposition and large amplifying feedback on climate warming were not observed, mainly because of reduced modeled initial SOC stock and limited NPP with heating effect. These underscores the multifaceted impacts of microbial heat. Comprehensive understanding of these effects would be vital for devising effective climate change mitigation strategies in a warming world.

Global mangrove soil organic carbon stocks dataset at 30 m resolution for the year 2020 based on spatiotemporal predictive machine learning.

This dataset presents global soil organic carbon stocks in mangrove forests at 30 m resolution, predicted for 2020. We used spatiotemporal ensemble machine learning to produce predictions of soil organic carbon content and bulk density (BD) to 1 m soil depth, which were then aggregated to calculate soil organic carbon stocks. This was done by using training data points of both SOC (%) and BD in mangroves from a global dataset and from recently published studies, and globally consistent predictive covariate layers. A total of 10,331 soil samples were validated to have SOC (%) measurements and were used for predictive soil mapping. We used time-series remote sensing data specific to time periods when the training data were sampled, as well as long-term (static) layers to train an ensemble of machine learning model. Ensemble models were used to improve performance, robustness and unbiasedness as opposed to just using one learner. In addition, we performed spatial cross-validation by using spatial blocking of training data points to assess model performance. We predicted SOC stocks for the 2020 time period and applied them to a 2020 mangrove extent map, presenting both mean predictions and prediction intervals to represent the uncertainty around our predictions. Predictions are available for download under CC-BY license from 10.5281/zenodo.7729491 and also as Cloud-Optimized GeoTIFFs (global mosaics).

A Study of Dominant Vegetation Phenology in a Sphagnum Mountain Peatland Using In Situ and Sentinel‐2 Observations

AbstractPeatlands store more than a third of the global soil organic carbon stock. Bryophytes, more specifically Sphagnum mosses, play a major role in the carbon and water cycles of these ecosystems. There is a need to include Sphagnum mosses into Earth system models to better simulate the dynamics of peatlands in a changing environment. Leaf area index (LAI) is a key plant trait that characterizes the plant photosynthesizing capacity. Moreover, LAI is a variable calculated by land surface models used in climate models, allowing control of the exchange of matter and energy between vegetation and the environment. There is extremely little data on Sphagnum LAI and none on its seasonal change. We monitored Sphagnum mosses LAI phenology in a mountainous peatland site (altitude of 1,343 m) from June to December 2021 using two methods: 2D scans of monthly Sphagnum moss samples and analysis of Sentinel‐2 images. LAI derived from field campaigns and the remote sensing approach show a strong seasonality, with high peak values reaching 10 and 7 m2·m−2, respectively. The Sentinel‐2 images were also used to derive common vegetation indices. The moisture soil index effectively discriminates Sphagnum‐dominated areas in the peatland. Satellite‐derived LAI of Sphagnum mosses is directly correlated to gross primary production monitored by gas exchange measurements (R2 = 0.83) but also to physical drivers of the environment such as air temperature (R2 = 0.74) or water table depth (R2 = 0.61) over the 2017–2021 period. It is therefore highly suitable to investigate ecosystemic functions.

Climate indices as predictors of global soil organic carbon stocks

ABSTRACT Global soils store more carbon than the atmosphere and terrestrial vegetation combined, with a significant proportion located in colder regions. Earth system models incorporating climate-carbon feedback suggest that a warming climate can potentially destabilize soil carbon storage, leading to carbon release into the atmosphere. However, existing models are based on limited measurements of soil organic carbon (SOC) loss and a comprehensive global-scale climate indices that effectively characterizes climate-SOC relationships is currently lacking. In this study, we present a synthetic analysis that evaluates the effectiveness of different climate indices in estimating SOC stocks using a global compilation of SOC data and the Boltzmann Sigmoidal Model (BSM). Our findings reveal that a climate index, defined as TD - Index = exp ( − 0.002 T − 0.8 D ) , where T and D are mean century temperature (MCT) and dryness respectively, serves as the most reliable predictor for SOC stocks. Furthermore, we observed temperature tipping points for SOC, ranging from −4.5 to −3°C for different soil layers. As the temperature transitions from being below to above the tipping point, the SOC shifts from a stable, high state to a rapid decline. An analysis of the projected temperatures for SOC under various future greenhouse gas emissions scenarios showed a northward shift in the northern hemisphere, potentially opening up vast areas of arctic territory to increased SOC loss from the soils, with corresponding emissions of the stored carbon into the atmosphere. Our findings open up new avenues for research on and management strategies for climate-related SOC dynamics.

Uncertainty in land use obscures global soil organic carbon stock estimates

Uncertainty in land use obscures global soil organic carbon stock estimates

Monitoring changes in global soil organic carbon stocks from space

Soils are under threat globally, with declining soil productivity and soil health in many places. As a key indicator of soil functioning, soil organic carbon (SOC) is crucial for ensuring food, soil, water and energy security, together with biodiversity protection. While there is a global effort to map SOC stock and status, SOC is a dynamic soil property and can change rapidly as a function of land management and land use. Here, we introduce a semi-mechanistic model to monitor SOC stocks at a global scale, underpinned by one of the largest worldwide soil database to date. Our model generates a SOC stock baseline for the year 2001, which is then propagated through time by keeping track of annual landcover changes obtained from remote sensing products with loss and gain dynamics dependent on temperature and precipitation, which finally define the magnitude, rate and direction of the SOC changes. We estimated a global SOC stock in the top 30 cm of around 793 Pg with annual losses due to landcover change of 1.9 Pg SOC yr−1 from 2001 to 2020, 20% larger than the annual production-based emissions of the United States in 2018. The biggest losses were found in the tropic and sub-tropical regions, accounting for almost 50% of the total global loss. This is a considerable contribution to greenhouse gas emissions but it also has a direct impact on agricultural production with more than 16 million hectares yr−1 falling below critical SOC limits. The proposed modelling framework is flexible, allowing it to be updated as more remote sensing and soil data becomes available, offering a first-of-its-kind global spatio-temporal SOC stock assessment and monitoring system.

Storage, patterns, and environmental controls of soil organic carbon stocks in the permafrost regions of the Northern Hemisphere

Large stocks of soil organic carbon (SOC) accumulated in the Northern Hemisphere permafrost regions may be vulnerable to climatic warming, but global estimates of SOC distribution and magnitude in permafrost regions still have large uncertainties. Based on multiple high-resolution environmental variables and a compiled soil sample dataset (>3000 soil profiles), we used machine-learning methods to estimate the size and spatial distribution of SOC for the top 3 m soils in the Northern Hemisphere permafrost regions. We also identified key environmental predictors of SOC. The results showed that the SOC storage for the top 3 m soil was 1079 ± 174 Pg C across the Northern Hemisphere permafrost regions (20.8 × 106 km2), including 1057 ± 167 Pg C in the northern permafrost regions and 22 ± 7 Pg C in the Third Pole permafrost regions. The mean annual air temperature and NDVI are the main controlling factors for the spatial distribution of SOC stocks in the northern and the Third Pole permafrost regions. Our estimations were more accurate than the existing global SOC stock maps. The results improve our understanding of the regional and global permafrost carbon cycle and their feedback to the climate system.

Is it possible to attain the same soil organic matter content in arable agricultural soils as under natural vegetation?

Clearing natural vegetation to establish arable agriculture (cropland) almost invariably causes a loss of soil organic carbon (SOC). Is it possible to restore soil that continues in arable agriculture to the pre-clearance SOC level through modified management practices? To address this question we reviewed evidence from long-term experiments at Rothamsted Research, UK, Bad Lauchstädt, Germany, Sanborn Field, USA and Brazil and both experiments and surveys of farmers’ fields in Ethiopia, Australia, Zimbabwe, UK and Chile. In most cases SOC content in soil under arable cropping was in the range 38–67% of pre-clearance values. Returning crop residues, adding manures or including periods of pasture within arable rotations increased this, often to 60–70% of initial values. Under tropical climatic conditions SOC loss after clearance was particularly rapid, e.g. a loss of >50% in less than 10 years in smallholder farmers’ fields in Zimbabwe. If larger yielding crops were grown, using fertilizers, and maize stover returned instead of being grazed by cattle, the loss was reduced. An important exception to the general trend of SOC loss after clearance was clearing Cerrado vegetation on highly weathered acidic soils in Brazil and conversion to cropping with maize and soybean. Other exceptions were unrealistically large annual applications of manure and including long periods of pasture in a highly SOC-retentive volcanic soil. Also, introducing irrigated agriculture in a low rainfall region can increase SOC beyond the natural value due to increased plant biomass production. For reasons of sustainability and soil health it is important to maintain SOC as high as practically possible in arable soils, but we conclude that in the vast majority of situations it is unrealistic to expect to maintain pre-clearance values. To maintain global SOC stocks at we consider it is more important to reduce current rates of land clearance and sustainably produce necessary food on existing agricultural land.

Soil carbon-food synergy: sizable contributions of small-scale farmers

BackgroundBenefits to agricultural yield improvement, soil degradation prevention, and climate mitigation are central to the synergies of soil organic carbon (SOC) build-up. However, the contributions of small-scale farmers, the main target of recent agricultural and rural development policies, to SOC enhancement are understudied. Here, we present a global analysis of small-scale farmers’ contributions to the potential of additional SOC stocks and the associated increase in crop production.MethodsWe applied random forest machine learning models to global gridded datasets on crop yield (wheat, maize, rice, soybean, sorghum and millet), soil, climate and agronomic management practices from the 2000s (n = 1808 to 8123). Using the established crop-specific SOC-yield relationships, the potentials of additional SOC build-up and crop production increase were simulated. The estimated SOC increase was converted into global decadal mean temperature change using the temperature sensitivity to cumulative total anthropogenic CO2 emissions from preindustrial levels. The amount of inorganic nitrogen (N) input that would result in the same yield outcome as the SOC build-up was derived from the crop-specific N-yield relationships.ResultsSOC contributes to yields in addition to management and climatic factors. Additional SOC sums up to 12.78 GtC (11.55–14.05 GtC) of global SOC stock, which earns 38.24 Mt (22.88–57.48 Mt) of additional crop production and prevents warming by 0.030 °C (0.019–0.041 °C). This production increase equates to what would be achieved by an inorganic N input of 5.82 Mt N (3.89–7.14 Mt N). Small-scale farmers account for 28% (26–30%) of the additional SOC build-up and 17% (15–20%) of the production increase. Key crops and regions in terms of small-scale farmers’ contributions include Sub-Saharan African maize and rice, Latin American and Caribbean soybean and maize, and South Asian rice and wheat.ConclusionsThe contribution of small-scale farmers to the potential increase in SOC stock and crop production is sizable, which in theory further leads to saving inorganic N input. These findings emphasize the importance of linking soil management to sustainable land and climate mitigation with institutions and policy for small-scale farmers. Such a joint policy would assist multiple development goals.

Soil organic carbon dynamics from agricultural management practices under climate change

Abstract. Sequestration of soil organic carbon (SOC) on cropland has been proposed as a climate change mitigation strategy to reduce global greenhouse gas (GHG) concentrations in the atmosphere, which in particular is needed to achieve the targets proposed in the Paris Agreement to limit the increase in atmospheric temperature to well below 2 ∘C. We analyze the historical evolution and future development of cropland SOC using the global process-based biophysical model LPJmL, which was recently extended by a detailed representation of tillage practices and residue management (version 5.0-tillage2). We find that model results for historical global estimates for SOC stocks are at the upper end of available literature, with ∼2650 Pg C of SOC stored globally in the year 2018, ∼170 Pg C of which is stored in cropland soils. In future projections, assuming no further changes in current cropland patterns and under four different management assumptions with two different climate forcings, RCP2.6 and RCP8.5, results suggest that agricultural SOC stocks decline in all scenarios, as the decomposition of SOC outweighs the increase in carbon inputs into the soil from altered management practices. Different climate change scenarios, as well as assumptions on tillage management, play a minor role in explaining differences in SOC stocks. The choice of tillage practice explains between 0.2 % and 1.3 % of total cropland SOC stock change in the year 2100. Future dynamics in cropland SOC are most strongly controlled by residue management: whether residues are left on the field or harvested. We find that on current cropland, global cropland SOC stocks decline until the end of the century by only 1.0 % to 1.4 % if residue retention management systems are generally applied and by 26.7 % to 27.3 % in the case of residue harvest. For different climatic regions, increases in cropland SOC can only be found for tropical dry, warm temperate moist, and warm temperate dry regions in management systems that retain residues.

Natural versus urban global soil organic carbon stocks: A meta-analysis

Increasingly, the human existence in urban environments is growing. In addition, anthropogenic activity has altered the global carbon (C) cycle and triggered climate change. Soil is the largest pool of organic C in terrestrial ecosystems, but its ability to retain and store C varies. As humans move forward to mitigate climate change, there is a growing need to understand the C storing capacity of soils and their interactions with factors like climate, vegetation or a footprint of human activity. Here, we constructed a meta-analysis which focused on 30cm soil depth by collecting data from over 191 studies measuring soil organic carbon (SOC) stocks across natural, urban green space, and urban intensive habitats. We then compared the SOC data between different climatic zones, vegetation types, and anthropogenic influences with the human footprint index. The results indicate that SOC stocks in natural habitats (98.22±49.10Mgha-1) are significantly higher than those of urban green spaces (54.61±22.02Mgha-1) and urban intensive habitats (65.88±35.27Mgha-1). We find a significant and negative relationship between the human footprint and SOC stocks of natural habitats but not between the human footprint and either of the urban habitats. Urban intensive and urban green space habitat soils store less C than natural ones. However, when compared across climatic zones or vegetation types, the capacity of natural soils to store C is variable and vulnerable to human activity. Carbon storage in urban soils is likely limited by persistent and stable anthropogenic influences keeping variability low. This is most pronounced in urban green spaces where human management is high (i.e. a golf course) and SOC is low. A comprehensive understanding of C storage in soils is essential to land management and climate mitigation measures.

Current and future carbon stocks in coastal wetlands within the Great Barrier Reef catchments.

Australia's Great Barrier Reef (GBR) catchments include some of the world's most intact coastal wetlands comprising diverse mangrove, seagrass and tidal marsh ecosystems. Although these ecosystems are highly efficient at storing carbon in marine sediments, their soil organic carbon (SOC) stocks and the potential changes resulting from climate impacts, including sea level rise are not well understood. For the first time, we estimated SOC stocks and their drivers within the range of coastal wetlands of GBR catchments using boosted regression trees (i.e. a machine learning approach and ensemble method for modelling the relationship between response and explanatory variables) and identified the potential changes in future stocks due to sea level rise. We found levels of SOC stocks of mangrove and seagrass meadows have different drivers, with climatic variables such as temperature, rainfall and solar radiation, showing significant contributions in accounting for variation in SOC stocks in mangroves. In contrast, soil type accounted for most of the variability in seagrass meadows. Total SOC stock in the GBR catchments, including mangroves, seagrass meadows and tidal marshes, is approximately 137Tg C, which represents 9%-13% of Australia's total SOC stock while encompassing only 4%-6% of the total extent of Australian coastal wetlands. In a global context, this could represent 0.5%-1.4% of global SOC stock. Our study suggests that landward migration due to projected sea level rise has the potential to enhance carbon accumulation with total carbon gains between 0.16 and 0.46Tg C and provides an opportunity for future restoration to enhance blue carbon.

Global Simulation and Evaluation of Soil Organic Matter and Microbial Carbon and Nitrogen Stocks Using the Microbial Decomposition Model ORCHIMIC v2.0

AbstractSoils contain the largest amount of land carbon, even a small change of this pool can significantly affect atmospheric CO2 and climate change. A good representation of soil organic carbon (SOC) dynamics in Earth system models is therefore crucial to predict future climate change. The dynamics of SOC is largely driven by microbial activities and modulated by N cycles. Nevertheless, very few models have explicitly represented soil microorganisms and N cycles integrated at global scale. Here, we present an update of the microbial‐mediated ORCHIMIC model and its application to simulate global gridded SOC stocks, microbial biomass, soil C/N ratio, microbial C/N ratio, and heterotrophic respiration. This is a new attempt to model SOC dynamics with an explicit microbial representation with N dynamics applied at global scale. The model shows relatively good performance in reproducing global SOC and microbial biomass C. The spatial distributions of soil and microbial C/N ratios were not well reproduced because they are sensitive to mineral nitrogen availability controlled by plant uptake, which is not explicitly represented in the model. However, similar relationship between C/N ratios of microbes and soil as observation demonstrated the potential of the model to reproduce global C/N ratios for both microbe and soil pools. Dynamic carbon use efficiency modulated by substrate C/N ratio, consistent with observation, were well represented by mechanistic including microbial dynamics. Modeled suppressed microbial biomass growth under warming climate indicating a weaker positive feedback between soil C pool and climate compared to that predicted by traditional Earth system models.

New uses for old tools: Reviving Holdridge Life Zones in soil carbon persistence research

AbstractGrowing evidence suggests that climate classification facilitates the identification of zones that either agree or disagree with processes explaining soil organic carbon (SOC) persistence. Already forty years ago, Post et al. (1982) posited that the strict temperature and precipitation‐based classification defining the Holdridge Life Zones (HLZ) provides a descriptive tool to guide our understanding of the heterogeneous distribution of global SOC stocks. Here we argue that this classification has the potential for describing SOC persistence by linking top‐down and bottom‐up approaches from different scales, which allows selection of individual regional relevancies necessary to manage and track the fate of our largest terrestrial carbon (C) reservoir.

Quantifying organic carbon stocks using a stereological profile imaging method to account for rock fragments in stony soils

Abstract Accounting for soil organic carbon (SOC) in stony soils is critical for estimating global SOC stocks. However, accurate and cost-effective assessments of SOC stocks in stony soil profiles remain challenging due to the difficulties in accurately determining the rock fragment volume. The objective of this study was to develop a stereological profile imaging method for rock fragment volume fraction estimation and SOC stock assessment in stony soil profiles. Three soil profiles with different rock fragment lithologies, concentrations, and distributions were imaged and quantitatively sampled. The stereological profile imaging method reproduced consistent estimation of the 3-dimensional rock fragment number density distribution and volume fraction compared to the direct measurement. The SOC stocks of the three stony profiles estimated by visual estimation, profile imaging, and stereological profile imaging methods were also assessed and compared to direct measurement. The average difference in total SOC stock between direct measurement and visual estimation, profile imaging, and stereological profile imaging methods was 0.32, 0.17, and 0.09 kg m−2, respectively. The total profile (0–100 cm) SOC stock for profile 2 differed among the visual estimation and profile imaging methods, but estimated SOC stock from the proposed method did not differ from direct measurement for the three profiles. Results also showed that the differences in SOC stock assessment between rock fragment estimation methods increased with rock fragment concentration. The proposed method was less affected by rock fragment concentration and was more stable compared to the visual and profile imaging methods. The stereological profile imaging method was demonstrated to be a reasonably accurate method for the quantification of rock fragment number density distribution, volume fraction, and SOC stock in stony soil profiles.

Warming-induced global soil carbon loss attenuated by downward carbon movement.

The fate of soil organic carbon (SOC) under warming is poorly understood, particularly across large extents and in the whole-soil profile. Using a data-model integration approach applied across the globe, we find that downward movement of SOC along the soil profile reduces SOC loss under warming. We predict that global SOC stocks (down to 2m) will decline by 4% (~80Pg) on average when SOC reaches the steady state under 2°C warming, assuming no changes in net primary productivity (NPP). To compensate such decline (i.e. maintain current SOC stocks), a 3% increase of NPP is required. Without the downward SOC movement, global SOC declines by 15%, while a 20% increase in NPP is needed to compensate that loss. This vital role of downward SOC movement in controlling whole-soil profile SOC dynamics in response to warming is due to the protection afforded to downward-moving SOC by depth, indicated by much longer residence times of SOC in deeper layers. Additionally, we find that this protection could not be counteracted by promoted decomposition due to the priming of downward-moving new SOC from upper layers on native old SOC in deeper layers. This study provides the first estimation of whole-soil SOC changes under warming and additional NPP required to compensate such changes across the globe, and reveals the vital role of downward movement of SOC in reducing SOC loss under global warming.

Drivers of seasonal- and event-scale DOC dynamics at the outlet of mountainous peatlands revealed by high-frequency monitoring

Abstract. Peatlands store ∼ 20 %–30 % of the global soil organic carbon stock and are an important source of dissolved organic carbon (DOC) for inland waters. Recent improvements for in situ optical monitoring revealed that the DOC concentration in streams draining peatlands is highly variable, showing seasonal variation and short and intense DOC concentration peaks. This study aimed to statistically determine the variables driving stream DOC concentration variations at seasonal and event scales. Two mountainous peatlands (one fen and one bog) were monitored in the French Pyrenees to capture their outlet DOC concentration variability at a high-frequency rate (30 min). Abiotic variables including precipitation, stream temperature and water level, water table depth, and peat water temperature were also monitored at high frequency and used as potential predictors to explain DOC concentration variability. Results show that at both sites DOC concentration time series can be decomposed into a seasonal baseline interrupted by many short and intense peaks of higher concentrations. The DOC concentration baseline is driven, at the seasonal scale, by peat water temperature. At the event scale, DOC concentration increases are mostly driven by a rise in the water table within the peat at both sites. Univariate linear models between DOC concentration and peat water temperature or water table increases show greater efficiency at the fen site. Water recession times were derived from water level time series using master recession curve coefficients. They vary greatly between the two sites but also within one peatland site. They partly explain the differences between DOC dynamics in the studied peatlands, including peat porewater DOC concentrations and the links between stream DOC concentration and water table rise within the peatlands. This highlights that peatland complexes are composed of a mosaic of heterogeneous peat units distinctively producing or transferring DOC to streams.