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

Heat 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.

Bomb radiocarbon evidence for strong global carbon uptake and turnover in terrestrial vegetation

Vegetation and soils are taking up approximately 30% of anthropogenic carbon dioxide emissions because of small imbalances in large gross carbon exchanges from productivity and turnover that are poorly constrained. We combined a new budget of radiocarbon produced by nuclear bomb testing in the 1960s with model simulations to evaluate carbon cycling in terrestrial vegetation. We found that most state-of-the-art vegetation models used in the Coupled Model Intercomparison Project underestimated the radiocarbon accumulation in vegetation biomass. Our findings, combined with constraints on vegetation carbon stocks and productivity trends, imply that net primary productivity is likely at least 80 petagrams of carbon per year presently, compared with the 43 to 76 petagrams per year predicted by current models. Storage of anthropogenic carbon in terrestrial vegetation is likely more short-lived and vulnerable than previously predicted.

Convergence in simulating global soil organic carbon by structurally different models after data assimilation

Current biogeochemical models produce carbon-climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first-order or Michaelis-Menten kinetics at the global scale. Nevertheless, a wider range of data with high-quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics-function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions.

Projected soil carbon loss with warming in constrained Earth system models

The soil carbon-climate feedback is currently the least constrained component of global warming projections, and the major source of uncertainties stems from a poor understanding of soil carbon turnover processes. Here, we assemble data from long-term temperature-controlled soil incubation studies to show that the arctic and boreal region has the shortest intrinsic soil carbon turnover time while tropical forests have the longest one, and current Earth system models overestimate intrinsic turnover time by 30 percent across active, slow and passive carbon pools. Our constraint suggests that the global soils will switch from carbon sink to source, with a loss of 0.22-0.53 petagrams of carbon per year until the end of this century from strong mitigation to worst emission scenarios, suggesting that global soils will provide a strong positive carbon feedback on warming. Such a reversal of global soil carbon balance would lead to a reduction of 66% and 15% in the current estimated remaining carbon budget for limiting global warming well below 1.5 °C and 2 °C, respectively, rendering climate mitigation much more difficult.

Carbon sequestration in the subsoil and the time required to stabilize carbon for climate change mitigation

Soils store large quantities of carbon in the subsoil (below 0.2 m depth) that is generally old and believed to be stabilized over centuries to millennia, which suggests that subsoil carbon sequestration (CS) can be used as a strategy for climate change mitigation. In this article, we review the main biophysical processes that contribute to carbon storage in subsoil and the main mathematical models used to represent these processes. Our guiding objective is to review whether a process understanding of soil carbon movement in the vertical profile can help us to assess carbon storage and persistence at timescales relevant for climate change mitigation. Bioturbation, liquid phase transport, belowground carbon inputs, mineral association, and microbial activity are the main processes contributing to the formation of soil carbon profiles, and these processes are represented in models using the diffusion-advection-reaction paradigm. Based on simulation examples and measurements from carbon and radiocarbon profiles across biomes, we found that advective and diffusive transport may only play a secondary role in the formation of soil carbon profiles. The difference between vertical root inputs and decomposition seems to play a primary role in determining the shape of carbon change with depth. Using the transit time of carbon to assess the timescales of carbon storage of new inputs, we show that only small quantities of new carbon inputs travel through the profile and can be stabilized for time horizons longer than 50 years, implying that activities that promote CS in the subsoil must take into consideration the very small quantities that can be stabilized in the long term.

36Cl, a new tool to assess soil carbon dynamics

Soil organic carbon is one of the largest surface pools of carbon that humans can manage in order to partially mitigate annual anthropogenic CO2 emissions. A significant element to assess soil sequestration potential is the carbon age, which is evaluated by modelling or experimentally using carbon isotopes. Results, however, are not consistent. The 14C derived approach seems to overestimate by a factor of 6-10 the average carbon age in soils estimated by modeling and 13C approaches and thus the sequestration potential. A fully independent method is needed. The cosmogenic chlorine nuclide, 36Cl, is a potential alternative. 36Cl is a naturally occurring cosmogenic radionuclide with a production that increased by three orders of magnitude during nuclear bomb tests. Part of this production is retained by soil organic matter in organochloride form and hence acts as a tracer of the fate of soil organic carbon. We here quantify the fraction and the duration of 36Cl retained in the soil and we show that retention time increases with depth from 20 to 322 years, in agreement with both modelling and 13C-derived estimates. This work demonstrates that 36Cl retention duration can be a proxy for the age of soil organic carbon.

Younger carbon dominates global soil carbon efflux

Soil carbon (C) is comprised of a continuum of organic compounds with distinct ages (i.e., the time a C atom has experienced in soil since the C atom entered soil). The contribution of different age groups to soil C efflux is critical for understanding soil C stability and persistence, but is poorly understood due to the complexity of soil C pool age structure and potential distinct turnover behaviors of age groups. Here, we build upon the quantification of soil C transit times to infer the age of C atoms in soil C efflux (a_efflux ) from seven sequential soil layer depths down to 2 m at a global scale, and compare this age with radiocarbon-inferred ages of C retained in corresponding soil layers (a_soil ). In the whole 0-2 m soil profile, the mean a_efflux is 194 21 1021 (mean with 5%-95% quantiles) year and is just about one-eighth of a_soil ( 1476 717 2547 year), demonstrating that younger C dominates soil C efflux. With increasing soil depth, both a_efflux and a_soil are increased, but their disparities are markedly narrowed. That is, the proportional contribution of relatively younger soil C to efflux is decreased in deeper layers, demonstrating that C inputs (new and young) stay longer in deeper layers. Across the globe, we find large spatial variability of the contribution of soil C age groups to C efflux. Especially, in deep soil layers of cold regions (e.g., boreal forests and tundra), a_efflux may be older than a_soil , suggesting that older C dominates C efflux only under a limited range of conditions. These results imply that most C inputs may not contribute to long-term soil C storage, particularly in upper layers that hold the majority of new C inputs.

Tree functional traits, forest biomass, and tree species diversity interact with site properties to drive forest soil carbon

Forests constitute important ecosystems in the global carbon cycle. However, how trees and environmental conditions interact to determine the amount of organic carbon stored in forest soils is a hotly debated subject. In particular, how tree species influence soil organic carbon (SOC) remains unclear. Based on a global compilation of data, we show that functional traits of trees and forest standing biomass explain half of the local variability in forest SOC. The effects of functional traits on SOC depended on the climatic and soil conditions with the strongest effect observed under boreal climate and on acidic, poor, coarse-textured soils. Mixing tree species in forests also favours the storage of SOC, provided that a biomass over-yielding occurs in mixed forests. We propose that the forest carbon sink can be optimised by (i) increasing standing biomass, (ii) increasing forest species richness, and (iii) choosing forest composition based on tree functional traits according to the local conditions.

Forests constitute important ecosystems in the global carbon cycle. This study investigates how tree species influence soil organic carbon using a global dataset, showing the importance of tree functional traits and forest standing biomass to optimise forest carbon sink.

Beyond bulk: Density fractions explain heterogeneity in global soil carbon abundance and persistence

Understanding the controls on the amount and persistence of soil organic carbon (C) is essential for predicting its sensitivity to global change. The response may depend on whether C is unprotected, isolated within aggregates, or protected from decomposition by mineral associations. Here, we present a global synthesis of the relative influence of environmental factors on soil organic C partitioning among pools, abundance in each pool (mg C g^-1  soil), and persistence (as approximated by radiocarbon abundance) in relatively unprotected particulate and protected mineral-bound pools. We show that C within particulate and mineral-associated pools consistently differed from one another in degree of persistence and relationship to environmental factors. Soil depth was the best predictor of C abundance and persistence, though it accounted for more variance in persistence. Persistence of all C pools decreased with increasing mean annual temperature (MAT) throughout the soil profile, whereas persistence increased with increasing wetness index (MAP/PET) in subsurface soils (30-176 cm). The relationship of C abundance (mg C g^-1  soil) to climate varied among pools and with depth. Mineral-associated C in surface soils (<30 cm) increased more strongly with increasing wetness index than the free particulate C, but both pools showed attenuated responses to the wetness index at depth. Overall, these relationships suggest a strong influence of climate on soil C properties, and a potential loss of soil C from protected pools in areas with decreasing wetness. Relative persistence and abundance of C pools varied significantly among land cover types and soil parent material lithologies. This variability in each pool's relationship to environmental factors suggests that not all soil organic C is equally vulnerable to global change. Therefore, projections of future soil organic C based on patterns and responses of bulk soil organic C may be misleading.

Carbon turnover times shape topsoil carbon difference between Tibetan Plateau and Arctic tundra

The Tibetan Plateau (TP) and Arctic permafrost constitute two large reservoirs of organic carbon, but processes which control carbon accumulation within the surface soil layer of these areas would differ due to the interplay of climate, soil and vegetation type. Here, we synthesized currently available soil carbon data to show that mean organic carbon density in the topsoil (0-10 cm) in TP grassland (3.12 ± 0.52 kg C m^-2) is less than half of that in Arctic tundra (6.70 ± 1.94 kg C m^-2). Such difference is primarily attributed to their difference in radiocarbon-inferred soil carbon turnover times (547 years for TP grassland versus 1609 years for Arctic tundra) rather than to their marginal difference in topsoil carbon inputs. Our findings highlight the importance of improving regional-specific soil carbon turnover and its controlling mechanisms across permafrost affected zones in ecosystem models to fully represent carbon-climate feedback.

Anthropogenic Transformation Disconnects a Lowland River From Contemporary Carbon Stores in Its Catchment

Rivers transport carbon from continents to oceans. Surprisingly, this carbon has often been found to be centuries old, not originating from contemporary plant biomass. This can be explained by anthropogenic disturbance of soils or discharge of radiocarbon–depleted wastewater. However, land enclosure and channel bypassing transformed many rivers from anabranching networks to single–channel systems with overbank sediment accumulation and lowered floodplain groundwater tables. We hypothesized that human development changed the fluvial carbon towards older sources by changing the morphology of watercourses. We studied radiocarbon in the Elbe, a European, anthropogenically–transformed lowland river at discharges between low flow and record peak flow. We found that the inorganic carbon, dissolved organic carbon (DOC) and particulate organic carbon was aged and up to 1850 years old. The ∆14C values remained low and invariant up to median discharges, indicating that the sources of modern carbon (fixed after 1950) were disconnected from the river during half of the time. The total share of modern carbon in DOC export was marginal (0.04%), 72% of exported DOC was older than 400 years. This was in contrast to undisturbed forested subcatchments, 72% of whose exported DOC was modern. Although population density is high, mass balances showed that wastewater did not significantly affect the ∆14C-DOC in the Elbe river. We conclude that wetlands and other sources of contemporary carbon were decoupled from the anthropogenically transformed Elbe stream network with incised stream bed relative to overbank sediments, shifting the sources of fluvial carbon in favor of aged stores.

Data-driven estimates of global litter production imply slower vegetation carbon turnover

Accurate quantification of vegetation carbon turnover time (τ_veg ) is critical for reducing uncertainties in terrestrial vegetation response to future climate change. However, in the absence of global information of litter production, τ_veg could only be estimated based on net primary productivity under the steady-state assumption. Here, we applied a machine-learning approach to derive a global dataset of litter production by linking 2401 field observations and global environmental drivers. Results suggested that the observation-based estimate of global natural ecosystem litter production was 44.3 ± 0.4 Pg C year^-1 . By contrast, land-surface models (LSMs) overestimated the global litter production by about 27%. With this new global litter production dataset, we estimated global τ_veg (mean value 10.3 ± 1.4 years) and its spatial distribution. Compared to our observation-based τ_veg , modelled τ_veg tended to underestimate τ_veg at high latitudes. Our empirically derived gridded datasets of litter production and τ_veg will help constrain global vegetation models and improve the prediction of global carbon cycle.

Soil carbon persistence governed by plant input and mineral protection at regional and global scales

Elucidating the processes underlying the persistence of soil organic matter (SOM) is a prerequisite for projecting soil carbon feedback to climate change. However, the potential role of plant carbon input in regulating the multi-layer SOM preservation over broad geographic scales remains unclear. Based on large-scale soil radiocarbon (∆¹⁴ C) measurements on the Tibetan Plateau, we found that plant carbon input was the major contributor to topsoil carbon destabilisation despite the significant associations of topsoil ∆¹⁴ C with climatic and mineral variables as well as SOM chemical composition. By contrast, mineral protection by iron-aluminium oxides and cations became more important in preserving SOM in deep soils. These regional observations were confirmed by a global synthesis derived from the International Soil Radiocarbon Database (ISRaD). Our findings illustrate different effects of plant carbon input on SOM persistence across soil layers, providing new insights for models to better predict multi-layer soil carbon dynamics under changing environments.

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 2 m) will decline by 4% (~80 Pg) 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.

Accelerated terrestrial ecosystem carbon turnover and its drivers

The terrestrial carbon cycle has been strongly influenced by human-induced CO₂ increase, climate change, and land use change since the industrial revolution. These changes alter the carbon balance of ecosystems through changes in vegetation productivity and ecosystem carbon turnover time (τ_eco ). Even though numerous studies have drawn an increasingly clear picture of global vegetation productivity changes, global changes in τ_eco are still unknown. In this study, we analyzed the changes of τ_eco between the 1860s and the 2000s and their drivers, based on theory of dynamic carbon cycle in non-steady state and process-based ecosystem model. Results indicate that τ_eco has been reduced (i.e., carbon turnover has accelerated) by 13.5% from the 1860s (74 years) to the 2000s (64 years), with reductions of 1 year of carbon residence times in vegetation (r_veg ) and of 9 years in soil (r_soil ). Additionally, the acceleration of τ_eco was examined at biome scale and grid scale. Among different driving processes, land use change and climate change were found to be the major drivers of turnover acceleration. These findings imply that carbon fixed by plant photosynthesis is being lost from ecosystems to the atmosphere more quickly over time, with important implications for the climate-carbon cycle feedbacks.

Organic Carbon Storage and 14C Apparent Age of Upland and Riparian Soils in a Montane Subtropical Moist Forest of Southwestern China

Upland and riparian soils usually differ in soil texture and moisture conditions, thus, likely varying in carbon storage and turnover time. However, few studies have differentiated their functions on the storage of soil organic carbon (SOC) in sub-tropical broad-leaved evergreen forests. In this study, we aim to uncover the SOC storage and 14C apparent age, in the upland and riparian soils of a primary evergreen broad-leaved montane subtropical moist forest in the Ailao Mountains of southwestern China. We sampled the upland and riparian soils along four soil profiles down to the parent material at regular intervals from two local representative watersheds, and determined SOC concentrations, δ13C values and 14C apparent ages. We found that SOC concentration decreased exponentially and 14C apparent age increased linearly with soil depth in the four soil profiles. Although, soil depth was deeper in the upland soil profiles than the riparian soil profiles, the weighted mean SOC concentration was significantly greater in the riparian soil (25.7 ± 3.9 g/kg) than the upland soil (19.7 ± 2.3 g/kg), but has an equal total SOC content per unit of ground area around 21 kg/m2 in the two different type soils. SOC δ13C values varied between −23.7 (±0.8)‰ and −33.2 (±0.2)‰ in the two upland soil profiles and between −25.5 (±0.4)‰ and −36.8 (±0.4)‰ along the two riparian soil profiles, with greater variation in the riparian soil profiles than the upland soil profiles. The slope of increase in SOC 14C apparent age along soil depth in the riparian soil profiles was greater than in the upland soil profiles. The oldest apparent age of SOC 14C was 23,260 (±230) years BP (before present, i.e., 1950) in the riparian soil profiles and 19,045 (±150) years BP in the upland soil profiles. Our data suggest that the decomposition of SOC is slower in the riparian soil than in the upland soil, and the increased SOC loss in the upland soil from deforestation may partially be compensated by the deposition of the eroded upland SOC in the riparian area, as an under-appreciated carbon sink.

Generic parameters of first-order kinetics accurately describe soil organic matter decay in bare fallow soils over a wide edaphic and climatic range

The conventional soil organic matter (SOM) decay paradigm considers the intrinsic quality of SOM as the dominant decay limitation with the result that it is modelled using simple first-order decay kinetics. This view and modelling approach is often criticized for being too simplistic and unreliable for predictive purposes. It is still under debate if first-order models can correctly capture the variability in temporal SOM decay observed between different agroecosystems and climates. To address this question, we calibrated a first-order model (Q) on six long-term bare fallow field experiments across Europe. Following conventional SOM decay theory, we assumed that parameters directly describing SOC decay (rate of SOM quality change and decomposer metabolism) are thermodynamically constrained and therefore valid for all sites. Initial litter input quality and edaphic interactions (both local by definition) and microbial efficiency (possibly affected by nutrient stoichiometry) were instead considered site-specific. Initial litter input quality explained most observed kinetics variability, and the model predicted a convergence toward a common kinetics over time. Site-specific variables played no detectable role. The decay of decades-old SOM seemed mostly influenced by OM chemistry and was well described by first order kinetics and a single set of general kinetics parameters.

Including Stable Carbon Isotopes to Evaluate the Dynamics of Soil Carbon in the Land-Surface Model ORCHIDEE

Soil organic carbon (SOC) is a crucial component of the terrestrial carbon cycle and its turnover time in models is a key source of uncertainty. Studies have highlighted the utility of δ13C measurements for benchmarking SOC turnover in global models. We used 13C as a tracer within a vertically discretized soil module of a land-surface model, Organising Carbon and Hydrology In Dynamic Ecosystems- Soil Organic Matter (ORCHIDEE-SOM). Our new module represents some of the processes that have been hypothesized to lead to a 13C enrichment with soil depth as follows: 1) the Suess effect and CO2 fertilization, 2) the relative 13C enrichment of roots compared to leaves, and 3) 13C discrimination associated with microbial activity. We tested if the upgraded soil module was able to reproduce the vertical profile of δ13C within the soil column at two temperate sites and the short-term change in the isotopic signal of soil after a shift in C3/C4 vegetation. We ran the model over Europe to test its performance at larger scale. The model was able to simulate a shift in the isotopic signal due to short-term changes in vegetation cover from C3 to C4; however, it was not able to reproduce the overall vertical profile in soil δ13C, which arises as a combination of short and long-term processes. At the European scale, the model ably reproduced soil CO2 fluxes and total SOC stock. These findings stress the importance of the long-term history of land cover for simulating vertical profiles of δ13C. This new soil module is an emerging tool for the diagnosis and improvement of global SOC models.

Evidence for a non-linear carbon accumulation pattern along an Alpine glacier retreat chronosequence in Northern Italy

Background

The glaciers in the Alps, as in other high mountain ranges and boreal zones, are generally retreating and leaving a wide surface of bare ground free from ice cover. This early stage soil is then colonized by microbes and vegetation in a process of primary succession. It is rarely experimentally examined whether this colonization process is linear or not at the ecosystem scale. Thus, to improve our understanding of the variables involved in the carbon accumulation in the different stages of primary succession, we conducted this research in three transects on the Matsch glacier forefield (Alps, N Italy) at an altitude between 2,350 and 2,800 m a.s.l.

Methods

In three field campaigns (July, August and September 2014) a closed transparent chamber was used to quantify the net ecosystem exchange (NEE) between the natural vegetation and the atmosphere. On the five plots established in each of the three transects, shading nets were used to determine ecosystem response function to variable light conditions. Ecosystem respiration (Reco) and gross ecosystem exchange (GEE) was partitioned from NEE. Following the final flux measurements, biometric sampling was conducted to establish soil carbon (C) and nitrogen (N) content and the biomass components for each transect.

Results

A clear difference was found between the earlier and the later successional stage. The older successional stages in the lower altitudes acted as a stronger C sink, where NEE, GEE and Reco were significantly higher than in the earlier successional stage. Of the two lower transects, the sink capacity of intermediate-succession plots exceeded that of the plots of older formation, in spite of the more developed soil. Total biomass (above- and belowground) approached its maximum value in the intermediate ecosystem, whilst the later stage of succession predominated in the corresponding belowground organic mass (biomass, N and C).

Outlook

We found that the process of carbon accumulation along a glacier retreat chronosequence is not linear, and after a quite rapid increase in carbon accumulation capacity in the first 150 years, in average 9 g C m⁻² year⁻¹, it slows down, taking place mainly in the belowground biomass components. Concurrently, the photosynthetic capacity peaks in the intermediate stage of ecosystem development. If confirmed by further studies on a larger scale, this study would provide evidence for a predominant effect of plant physiology over soil physical characteristics in the green-up phase after glacier retreat, which has to be taken into account in the creation of scenarios related to climate change and future land use.

Global subsoil organic carbon turnover times dominantly controlled by soil properties rather than climate

Soil organic carbon (SOC) in the subsoil below 0.3 m accounts for the majority of total SOC and may be as sensitive to climate change as topsoil SOC. Here we map global SOC turnover times (τ) in the subsoil layer at 1 km resolution using observational databases. Global mean τ is estimated to be \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1015_{729}^{1414}$$\end{document}10157291414 yr (mean with 95% confidence interval), and deserts and tundra show the shortest (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$146_{114}^{188}$$\end{document}146114188 yr) and longest (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$3854_{2651}^{5622}$$\end{document}385426515622 yr) τ respectively. Across the globe, mean τ ranges from 9 (the 5% quantile) to 6332 years (the 95% quantile). Temperature is the most important factor negatively affecting τ, but the overall effect of climate (including temperature and precipitation) is secondary compared with the overall effect of assessed soil properties (e.g., soil texture and pH). The high-resolution mapping of τ and the quantification of its controls provide a benchmark for diagnosing subsoil SOC dynamics under climate change.

The sensitivity of soil organic carbon (SOC) in subsoil (below 0.3 m) to climate change is poorly constrained. Here, the authors map global subsoil (0.3–1 m soil layer) SOC turnover times and find that temperature and in general climate effects are secondary to effects due to soil properties at both local and global scales—this now needs to be regarded for diagnosing subsoil SOC dynamics.

Greenhouse Gas Concentration and Volcanic Eruptions Controlled the Variability of Terrestrial Carbon Uptake Over the Last Millennium

The terrestrial net biome production (NBP) is considered as one of the major drivers of interannual variation in atmospheric CO2 levels. However, the determinants of variability in NBP under the background climate (i.e., preindustrial conditions) remain poorly understood, especially on decadal-to-centennial timescales. We analyzed 1,000-year simulations spanning 850-1,849 from the Community Earth System Model (CESM) and found that the variability in NBP and heterotrophic respiration (RH) were largely driven by fluctuations in the net primary production (NPP) and carbon turnover rates in response to climate variability. On interannual to multidecadal timescales, variability in NBP was dominated by variation in NPP, while variability in RH was driven by variation in turnover rates. However, on centennial timescales (100-1,000 years), the RH variability became more tightly coupled to that of NPP. The NBP variability on centennial timescales was low, due to the near cancellation of NPP and NPP-driven RH changes arising from climate internal variability and external forcings: preindustrial greenhouse gases, volcanic eruptions, land use changes, orbital change, and solar activity. Factorial experiments showed that globally on centennial timescales, the forcing of changes in greenhouse gas concentrations were the largest contributor (51%) to variations in both NPP and RH, followed by volcanic eruptions impacting NPP (25%) and RH (31%). Our analysis of the carbon-cycle suggests that geoengineering solutions by injection of stratospheric aerosols might be ineffective on longer timescales.

Approaching the potential of model-data comparisons of global land carbon storage

Carbon storage dynamics in vegetation and soil are determined by the balance of carbon influx and turnover. Estimates of these opposing fluxes differ markedly among different empirical datasets and models leading to uncertainty and divergent trends. To trace the origin of such discrepancies through time and across major biomes and climatic regions, we used a model-data fusion framework. The framework emulates carbon cycling and its component processes in a global dynamic ecosystem model, LPJ-GUESS, and preserves the model-simulated pools and fluxes in space and time. Thus, it allows us to replace simulated carbon influx and turnover with estimates derived from empirical data, bringing together the strength of the model in representing processes, with the richness of observational data informing the estimations. The resulting vegetation and soil carbon storage and global land carbon fluxes were compared to independent empirical datasets. Results show model-data agreement comparable to, or even better than, the agreement between independent empirical datasets. This suggests that only marginal improvement in land carbon cycle simulations can be gained from comparisons of models with current-generation datasets on vegetation and soil carbon. Consequently, we recommend that model skill should be assessed relative to reference data uncertainty in future model evaluation studies.

Underestimated ecosystem carbon turnover time and sequestration under the steady state assumption: A perspective from long-term data assimilation

It is critical to accurately estimate carbon (C) turnover time as it dominates the uncertainty in ecosystem C sinks and their response to future climate change. In the absence of direct observations of ecosystem C losses, C turnover times are commonly estimated under the steady state assumption (SSA), which has been applied across a large range of temporal and spatial scales including many at which the validity of the assumption is likely to be violated. However, the errors associated with improperly applying SSA to estimate C turnover time and its covariance with climate as well as ecosystem C sequestrations have yet to be fully quantified. Here, we developed a novel model-data fusion framework and systematically analyzed the SSA-induced biases using time-series data collected from 10 permanent forest plots in the eastern China monsoon region. The results showed that (a) the SSA significantly underestimated mean turnover times (MTTs) by 29%, thereby leading to a 4.83-fold underestimation of the net ecosystem productivity (NEP) in these forest ecosystems, a major C sink globally; (b) the SSA-induced bias in MTT and NEP correlates negatively with forest age, which provides a significant caveat for applying the SSA to young-aged ecosystems; and (c) the sensitivity of MTT to temperature and precipitation was 22% and 42% lower, respectively, under the SSA. Thus, under the expected climate change, spatiotemporal changes in MTT are likely to be underestimated, thereby resulting in large errors in the variability of predicted global NEP. With the development of observation technology and the accumulation of spatiotemporal data, we suggest estimating MTTs at the disequilibrium state via long-term data assimilation, thereby effectively reducing the uncertainty in ecosystem C sequestration estimations and providing a better understanding of regional or global C cycle dynamics and C-climate feedback.

Effects of soil process formalisms and forcing factors on simulated organic carbon depth-distributions in soils

Soil organic carbon (OC) sequestration (i.e. the capture and long-term storage of atmospheric CO₂) is being considered as a possible solution to mitigate climate change, notably through land use change (conversion of cropped land into pasture) and conservation agricultural practices (reduced tillage). Subsoil horizons (from 30 cm to 1 m) contribute to ca. half the total amount of soil OC, and the slow dynamics of deep OC as well as the relationships between the OC depth distribution and changes in land use and tillage practices still need to be modelled. We developed a fully modular, mechanistic OC depth distribution model, named OC-VGEN. This model includes OC dynamics, plant development, transfer of water, gas and heat, mixing by bioturbation and tillage as processes and climate and land use as boundary conditions. OC-VGEN allowed us to test the impact of 1) different numerical representations of root depth distribution, decomposition coefficients and bioturbation; 2) evolution of forcing factors such as land use, agricultural practices and climate on OC depth distribution at the century scale. We used the model to simulate decadal to century time scale experiments in Luvisols with different land uses (pasture and crop) and tillage practices (conventional and reduced) as well as projection scenarios of climate and land use at the horizon of 2100. We showed that, among the different tested formalisms/parametrizations: 1) the sensitivity of the simulated OC depth distribution to the tested numerical representations depended on the considered land use; 2) different numerical representations may accurately fit past soil OC evolution while leading to different OC stock predictions when tested for future forcing conditions (change of land use, tillage practice or climate).

Sequestering Atmospheric CO2 Inorganically: A Solution for Malaysia’s CO2 Emission

Malaysia is anticipating an increase of 68.86% in CO2 emission in 2020, compared with the 2000 baseline, reaching 285.73 million tonnes. A major contributor to Malaysia’s CO2 emissions is coal-fired electricity power plants, responsible for 43.4% of the overall emissions. Malaysia’s forest soil offers organic sequestration of 15 tonnes of CO2 ha−1·year−1. Unlike organic CO2 sequestration in soil, inorganic sequestration of CO2 through mineral carbonation, once formed, is considered as a permanent sink. Inorganic CO2 sequestration in Malaysia has not been extensively studied, and the country’s potential for using the technique for atmospheric CO2 removal is undefined. In addition, Malaysia produces a significant amount of solid waste annually and, of that, demolition concrete waste, basalt quarry fine, and fly and bottom ashes are calcium-rich materials suitable for inorganic CO2 sequestration. This project introduces a potential solution for sequestering atmospheric CO2 inorganically for Malaysia. If lands associated to future developments in Malaysia are designed for inorganic CO2 sequestration using demolition concrete waste, basalt quarry fine, and fly and bottom ashes, 597,465 tonnes of CO2 can be captured annually adding a potential annual economic benefit of €4,700,000.

Soil erosion is unlikely to drive a future carbon sink in Europe

Understanding of the processes governing soil organic carbon turnover is confounded by the fact that C feedbacks driven by soil erosion have not yet been fully explored at large scale. However, in a changing climate, variation in rainfall erosivity (and hence soil erosion) may change the amount of C displacement, hence inducing feedbacks onto the land C cycle. Using a consistent biogeochemistry-erosion model framework to quantify the impact of future climate on the C cycle, we show that C input increases were offset by higher heterotrophic respiration under climate change. Taking into account all the additional feedbacks and C fluxes due to displacement by erosion, we estimated a net source of 0.92 to 10.1 Tg C year^-1 from agricultural soils in the European Union to the atmosphere over the period 2016-2100. These ranges represented a weaker and stronger C source compared to a simulation without erosion (1.8 Tg C year^-1), respectively, and were dependent on the erosion-driven C loss parameterization, which is still very uncertain. However, when setting a baseline with current erosion rates, the accelerated erosion scenario resulted in 35% more eroded C, but its feedback on the C cycle was marginal. Our results challenge the idea that higher erosion driven by climate will lead to a C sink in the near future.

Soil Organic Matter Persistence as a Stochastic Process: Age and Transit Time Distributions of Carbon in Soils

The question of why some types of organic matter are more persistent while others decompose quickly in soils has motivated a large amount of research in recent years. Persistence is commonly characterized as turnover or mean residence time of soil organic matter (SOM). However, turnover and residence times are ambiguous measures of persistence, because they could represent the concept of either age or transit time. To disambiguate these concepts and propose a metric to assess SOM persistence, we calculated age and transit time distributions for a wide range of soil organic carbon models. Furthermore, we show how age and transit time distributions can be obtained from a stochastic approach that takes a deterministic model of mass transfers among different pools and creates an equivalent stochastic model at the level of atoms. Using this approach we show the following: (1) Age distributions have relatively old mean values and long tails in relation to transit time distributions, suggesting that carbon stored in soils is on average much older than carbon in the release flux. (2) The difference between mean ages and mean transit times is large, with estimates of soil organic carbon persistence on the order of centuries or millennia when assessed using ages and on the order of decades when using transit or turnover times. (3) The age distribution is an appropriate metric to characterize persistence of SOM. An important implication of our analysis is that random chance is a factor that helps to explain why some organic matter persists for millennia in soil.

Precipitation thresholds regulate net carbon exchange at the continental scale

Understanding the sensitivity of ecosystem production and respiration to climate change is critical for predicting terrestrial carbon dynamics. Here we show that the primary control on the inter-annual variability of net ecosystem carbon exchange switches from production to respiration at a precipitation threshold between 750 and 950 mm yr⁻¹ in the contiguous United States. This precipitation threshold is evident across multiple datasets and scales of observation indicating that it is a robust result and provides a new scaling relationship between climate and carbon dynamics. However, this empirical precipitation threshold is not captured by dynamic global vegetation models, which tend to overestimate the sensitivity of production and underestimate the sensitivity of respiration to water availability in more mesic regions. Our results suggest that the short-term carbon balance of ecosystems may be more sensitive to respiration losses than previously thought and that model simulations may underestimate the positive carbon–climate feedbacks associated with respiration.

The sensitivity of terrestrial net ecosystem carbon exchange (NEE) to climate remains a major source of uncertainty. Here, the authors identify a precipitation threshold of between 750-950 mm yr⁻¹ for the contiguous United States, beyond which NEE is regulated by respiration rather than production.

Matrix-Based Sensitivity Assessment of Soil Organic Carbon Storage: A Case Study from the ORCHIDEE-MICT Model

Modeling of global soil organic carbon (SOC) is accompanied by large uncertainties. The heavy computational requirement limits our flexibility in disentangling uncertainty sources especially in high latitudes. We build a structured sensitivity analyzing framework through reorganizing the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE)-aMeliorated Interactions between Carbon and Temperature (MICT) model with vertically discretized SOC into one matrix equation, which brings flexibility in comprehensive sensitivity assessment. Through Sobol's method enabled by the matrix, we systematically rank 34 relevant parameters according to variance explained by each parameter and find a strong control of carbon input and turnover time on long-term SOC storages. From further analyses for each soil layer and regional assessment, we find that the active layer depth plays a critical role in the vertical distribution of SOC and SOC equilibrium stocks in northern high latitudes (>50°N). However, the impact of active layer depth on SOC is highly interactive and nonlinear, varying across soil layers and grid cells. The stronger impact of active layer depth on SOC comes from regions with shallow active layer depth (e.g., the northernmost part of America, Asia, and some Greenland regions). The model is sensitive to the parameter that controls vertical mixing (cryoturbation rate) but only when the vertical carbon input from vegetation is limited since the effect of vertical mixing is relatively small. And the current model structure may still lack mechanisms that effectively bury nonrecalcitrant SOC. We envision a future with more comprehensive model intercomparisons and assessments with an ensemble of land carbon models adopting the matrix-based sensitivity framework.

Accelerating rates of Arctic carbon cycling revealed by long-term atmospheric CO2 measurements

The contemporary Arctic carbon balance is uncertain, and the potential for a permafrost carbon feedback of anywhere from 50 to 200 petagrams of carbon (Schuur et al., 2015) compromises accurate 21st-century global climate system projections. The 42-year record of atmospheric CO₂ measurements at Barrow, Alaska (71.29 N, 156.79 W), reveals significant trends in regional land-surface CO₂ anomalies (ΔCO₂), indicating long-term changes in seasonal carbon uptake and respiration. Using a carbon balance model constrained by ΔCO₂, we find a 13.4% decrease in mean carbon residence time (50% confidence range = 9.2 to 17.6%) in North Slope tundra ecosystems during the past four decades, suggesting a transition toward a boreal carbon cycling regime. Temperature dependencies of respiration and carbon uptake suggest that increases in cold season Arctic labile carbon release will likely continue to exceed increases in net growing season carbon uptake under continued warming trends.

Model structures amplify uncertainty in predicted soil carbon responses to climate change

Large model uncertainty in projected future soil carbon (C) dynamics has been well documented. However, our understanding of the sources of this uncertainty is limited. Here we quantify the uncertainties arising from model parameters, structures and their interactions, and how those uncertainties propagate through different models to projections of future soil carbon stocks. Both the vertically resolved model and the microbial explicit model project much greater uncertainties to climate change than the conventional soil C model, with both positive and negative C-climate feedbacks, whereas the conventional model consistently predicts positive soil C-climate feedback. Our findings suggest that diverse model structures are necessary to increase confidence in soil C projection. However, the larger uncertainty in the complex models also suggests that we need to strike a balance between model complexity and the need to include diverse model structures in order to forecast soil C dynamics with high confidence and low uncertainty.

A substantial portion of model uncertainty arises from model parameters and structures. Here, the authors show that alternative model structures with data-driven parameters project greater uncertainty in soil carbon responses to climate change than the conventional soil carbon model.

Long-term organic carbon sequestration in tidal marsh sediments is dominated by old-aged allochthonous inputs in a macrotidal estuary

Tidal marshes are vegetated coastal ecosystems that are often considered as hotspots of atmospheric CO₂ sequestration. Although large amounts of organic carbon (OC) are indeed being deposited on tidal marshes, there is no direct link between high OC deposition rates and high OC sequestration rates due to two main reasons. First, the deposited OC may become rapidly decomposed once it is buried and, second, a significant part of preserved OC may be allochthonous OC that has been sequestered elsewhere. In this study we aimed to identify the mechanisms controlling long-term OC sequestration in tidal marsh sediments along an estuarine salinity gradient (Scheldt estuary, Belgium and the Netherlands). Analyses of deposited sediments have shown that OC deposited during tidal inundations is up to millennia old. This allochthonous OC is the main component of OC that is effectively preserved in these sediments, as indicated by the low radiocarbon content of buried OC. Furthermore, OC fractionation showed that autochthonous OC is decomposed on a decadal timescale in saltmarsh sediments, while in freshwater marsh sediments locally produced biomass is more efficiently preserved after burial. Our results show that long-term OC sequestration is decoupled from local biomass production in the studied tidal marsh sediments. This implies that OC sequestration rates are greatly overestimated when they are calculated based on short-term OC deposition rates, which are controlled by labile autochthonous OC inputs. Moreover, as allochthonous OC is not sequestered in-situ, it does not contribute to active atmospheric CO₂ sequestration in these ecosystems. A correct assessment of the contribution of allochthonous OC to the total sedimentary OC stock in tidal marsh sediments as well as a correct understanding of the long-term fate of locally produced OC are both necessary to avoid overestimations of the rate of in-situ atmospheric CO₂ sequestration in tidal marsh sediments.

Soil carbon cycling proxies: Understanding their critical role in predicting climate change feedbacks

The complexity of processes and interactions that drive soil C dynamics necessitate the use of proxy variables to represent soil characteristics that cannot be directly measured (correlative proxies), or that aggregate information about multiple soil characteristics into one variable (integrative proxies). These proxies have proven useful for understanding the soil C cycle, which is highly variable in both space and time, and are now being used to make predictions of the fate and persistence of C under future climate scenarios. However, the C pools and processes that proxies represent must be thoughtfully considered in order to minimize uncertainties in empirical understanding. This is necessary to capture the full value of a proxy in model parameters and in model outcomes. Here, we provide specific examples of proxy variables that could improve decision-making, and modeling skill, while also encouraging continued work on their mechanistic underpinnings. We explore the use of three common soil proxies used to study soil C cycling: metabolic quotient, clay content, and physical fractionation. We also consider how emerging data types, such as genome-sequence data, can serve as proxies for microbial community activities. By examining some broad assumptions in soil C cycling with the proxies already in use, we can develop new hypotheses and specify criteria for new and needed proxies.

Comment on "Climate legacies drive global soil carbon stocks in terrestrial ecosystems"

Delgado-Baquerizo et al. (Science Advances, 12 April 2017, e1602008) use statistical correlations to infer that paleoclimate (6000 to 22,000 years ago) is a more important driver of current soil organic carbon stocks than the current-day climate. On the other hand, a wealth of radiocarbon measurements indicates that the organic carbon in most topsoils is only a few decades to perhaps a few centuries old. These seemingly incongruous results can perhaps be reconciled by considering that the long-term pedogenic development of a soil strongly influences the physiochemical properties, which lead to stabilization of new carbon entering that soil regardless of current climate.

Response to comment on "Climate legacies drive global soil carbon stocks in terrestrial ecosystem"

The technical comment from Sanderman provides a unique opportunity to deepen our understanding of the mechanisms explaining the role of paleoclimate in the contemporary distribution of global soil C content, as reported in our article. Sanderman argues that the role of paleoclimate in predicting soil C content might be accounted for by using slowly changing soil properties as predictors. This is a key point that we highlighted in the supplementary materials of our article, which demonstrated, to the degree possible given available data, that soil properties alone cannot account for the unique portion of the variation in soil C explained by paleoclimate. Sanderman also raised an interesting question about how paleoclimate might explain the contemporary amount of C in our soils if such a C is relatively new, particularly in the topsoil layer. There is one relatively simple, yet plausible, reason. A soil with a higher amount of C, a consequence of accumulation over millennia, might promote higher contemporary C fixation rates, leading to a higher amount of new C in our soils. Thus, paleoclimate can be a good predictor of the amount of soil C in soil, but not necessarily of its age. In summary, Sanderman did not question the validity of our results but rather provides an alternative potential mechanistic explanation for the conclusion of our original article, that is, that paleoclimate explains a unique portion of the global variation of soil C content that cannot be accounted for by current climate, vegetation attributes, or soil properties.

Networking our science to characterize the state, vulnerabilities, and management opportunities of soil organic matter

Soil organic matter (SOM) supports the Earth's ability to sustain terrestrial ecosystems, provide food and fiber, and retains the largest pool of actively cycling carbon. Over 75% of the soil organic carbon (SOC) in the top meter of soil is directly affected by human land use. Large land areas have lost SOC as a result of land use practices, yet there are compensatory opportunities to enhance productivity and SOC storage in degraded lands through improved management practices. Large areas with and without intentional management are also being subjected to rapid changes in climate, making many SOC stocks vulnerable to losses by decomposition or disturbance. In order to quantify potential SOC losses or sequestration at field, regional, and global scales, measurements for detecting changes in SOC are needed. Such measurements and soil-management best practices should be based on well established and emerging scientific understanding of processes of C stabilization and destabilization over various timescales, soil types, and spatial scales. As newly engaged members of the International Soil Carbon Network, we have identified gaps in data, modeling, and communication that underscore the need for an open, shared network to frame and guide the study of SOM and SOC and their management for sustained production and climate regulation.

Global Sequestration Potential of Increased Organic Carbon in Cropland Soils

The role of soil organic carbon in global carbon cycles is receiving increasing attention both as a potentially large and uncertain source of CO₂ emissions in response to predicted global temperature rises, and as a natural sink for carbon able to reduce atmospheric CO₂. There is general agreement that the technical potential for sequestration of carbon in soil is significant, and some consensus on the magnitude of that potential. Croplands worldwide could sequester between 0.90 and 1.85 Pg C/yr, i.e. 26–53% of the target of the “4p1000 Initiative: Soils for Food Security and Climate”. The importance of intensively cultivated regions such as North America, Europe, India and intensively cultivated areas in Africa, such as Ethiopia, is highlighted. Soil carbon sequestration and the conservation of existing soil carbon stocks, given its multiple benefits including improved food production, is an important mitigation pathway to achieve the less than 2 °C global target of the Paris Climate Agreement.

Faster turnover of new soil carbon inputs under increased atmospheric CO2

Rising levels of atmospheric CO₂ frequently stimulate plant inputs to soil, but the consequences of these changes for soil carbon (C) dynamics are poorly understood. Plant-derived inputs can accumulate in the soil and become part of the soil C pool ("new soil C"), or accelerate losses of pre-existing ("old") soil C. The dynamics of the new and old pools will likely differ and alter the long-term fate of soil C, but these separate pools, which can be distinguished through isotopic labeling, have not been considered in past syntheses. Using meta-analysis, we found that while elevated CO₂ (ranging from 550 to 800 parts per million by volume) stimulates the accumulation of new soil C in the short term (<1 year), these effects do not persist in the longer term (1-4 years). Elevated CO₂ does not affect the decomposition or the size of the old soil C pool over either temporal scale. Our results are inconsistent with predictions of conventional soil C models and suggest that elevated CO₂ might increase turnover rates of new soil C. Because increased turnover rates of new soil C limit the potential for additional soil C sequestration, the capacity of land ecosystems to slow the rise in atmospheric CO₂ concentrations may be smaller than previously assumed.

Increased precipitation accelerates soil organic matter turnover associated with microbial community composition in topsoil of alpine grassland on the eastern Tibetan Plateau

Large quantities of carbon are stored in alpine grassland of the Tibetan Plateau, which is extremely sensitive to climate change. However, it remains unclear whether soil organic matter (SOM) in different layers responds to climate change analogously, and whether microbial communities play vital roles in SOM turnover of topsoil. In this study we measured and collected SOM turnover by the ¹⁴C method in alpine grassland to test climatic effects on SOM turnover in soil profiles. Edaphic properties and microbial communities in the northwestern Qinghai Lake were investigated to explore microbial influence on SOM turnover. SOM turnover in surface soil (0-10 cm) was more sensitive to precipitation than that in subsurface layers (10-40 cm). Precipitation also imposed stronger effects on the composition of microbial communities in the surface layer than that in deeper soil. At the 5-10 cm depth, the SOM turnover rate was positively associated with the bacteria/fungi biomass ratio and the relative abundance of Acidobacteria, both of which are related to precipitation. Partial correlation analysis suggested that increased precipitation could accelerate the SOM turnover rate in topsoil by structuring soil microbial communities. Conversely, carbon stored in deep soil would be barely affected by climate change. Our results provide valuable insights into the dynamics and storage of SOM in alpine grasslands under future climate scenarios.