Towards a representation of priming on soil carbon decomposition in the global land biosphere model ORCHIDEE (version 1.9.5.2)

Priming of soil carbon decomposition encompasses different processes through which the decomposition of native (already present) soil organic matter is amplified through the addition of new organic matter, with new inputs typically being more labile than the native soil organic matter. Evidence for priming comes from laboratory and field experiments, but to date there is no estimate of its impact at global scale and under the current anthropogenic perturbation of the carbon cycle. Current soil carbon decomposition models do not include priming mechanisms, thereby introducing uncertainty when extrapolating short-term local observations to ecosystem and regional to global scale. In this study we present a simple conceptual model of decomposition priming, called PRIM, able to reproduce laboratory (incubation) and field (litter manipulation) priming experiments. Parameters for this model were first optimized against data from 20 soil incubation experiments using a Bayesian framework. The optimized parameter values were evaluated against another set of soil incubation data independent from the ones used for calibration and the PRIM model reproduced the soil incubations data better than the original, CENTURY-type soil decomposition model, whose decomposition equations are based only on first-order kinetics. We then compared the PRIM model and the standard first-order decay model incorporated into the global land biosphere model ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems). A test of both models was performed at ecosystem scale using litter manipulation experiments from five sites. Although both versions were equally able to reproduce observed decay rates of litter, only ORCHIDEE-PRIM could simulate the observed priming (R² = 0.54)in cases where litter was added or removed. This result suggests that a conceptually simple and numerically tractable representation of priming adapted to global models is able to capture the sign and magnitude of the priming of litter and soil organic matter

Defining Quantitative Targets for Topsoil Organic Carbon Stock Increase in European Croplands: Case Studies With Exogenous Organic Matter Inputs

The EU Mission Board for Soil Health and Food proposed a series of quantitative targets for European soils to become healthier. Among them, current soil organic carbon (SOC) concentration losses in croplands (0.5% yr(-1) on average at 20 cm depth) should be reversed to an increase of 0.1-0.4% yr(-1) by 2030. Quantitative targets are used by policy makers to incentivize the implementation of agricultural practices that increase SOC stocks. However, there are different approaches to calculate them. In this paper, we analyzed the effect of exogenous organic matter (EOM) inputs on the evolution of SOC stocks, with a particular focus on the new European targets and the different approaches to calculate them. First, we illustrated through two case-study experiments the different targets set when the SOC stock increase is calculated considering as reference: 1) the SOC stock level at the onset of the experiment and 2) the SOC stock trend in a baseline, i.e., a control treatment without EOM addition. Then, we used 11 long-term experiments (LTEs) with EOM addition in European croplands to estimate the amount of carbon (C) input needed to reach the 0.1 and 0.4% SOC stock increase targets proposed by the Mission Board for Soil Health and Food, calculated with two different approaches. We found that, to reach a 0.1 and 0.4% increase target relative to the onset of the experiment, 2.51 and 2.61 Mg C ha(-1) yr(-1) of additional C input were necessary, respectively. Reaching a 0.1 and 0.4% increase target relative to the baseline required 1.38 and 1.77 Mg C ha(-1) yr(-1) of additional input, respectively. Depending on the calculation method used, the estimated amounts of additional C input required to reach each quantitative target were significantly different from each other. Furthermore, the quality of C input as represented by the C retention rate of the additional organic material (EOM and crop residue), had a significant effect on the variation of SOC stocks. Our work highlights the necessity to take into consideration the additional C input required to increase SOC stocks, especially for soils with decreasing SOC stocks, when targets are set independently of the baseline

Projected soil carbon loss with warming in constrained Earth system models

This study was supported by the National Natural Science Foundation of China (42230411), the NSFC project Basic Science Centre for Tibetan Plateau Earth System (41988101), the Second Tibetan Plateau Scientific Expedition and Research Program (2019QZKK0606), the Science and Technology Plan Project of Tibet Autonomous Region (XZ202201ZY0015G), and Innovation Program for Young Scholars of TPESER (TPESER-QNCX2022ZD-02). We also acknowledge the support of Kathmandu Center for Research and Education, Chinese Academy of Sciences—Tribhuvan University.Peer reviewedPublisher PD

Priming of soil organic matter decomposition scales linearly with microbial biomass response to litter input in steppe vegetation

Research Funding: 'Strategic Priority Research Program - Climate Change: Carbon Budget and Related Issues' of the Chinese Academy of Sciences. Grant Number: XDA05050407. The National Natural Science Foundation of China. Grant Number: 31370462. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, the Chinese Academy of Sciences. The Flemish National Science Foundation. The European Community's Seventh Framework Programme (FP7/2007-2013). Grant Number: 226701 (CARBO-Extreme). The European Research Council Synergy. Grant Number: 610028. The Cost Action Terrabites. Grant Number: ES-0805.Fresh plant litter inputs accelerate soil organic matter (SOM) decomposition through a ubiquitous mechanism called priming. Insufficient priming has been suggested as a stabilization mechanism of SOM at depth, as well as the long-term persistence of some highly degradable organic compounds in soils. Priming therefore plays a crucial, albeit unquantified and commonly neglected, role in the global carbon cycle. Because priming intensity is likely to be altered by global changeinduced changes in net primary productivity, it casts substantial uncertainty to future projections of the climate-carbon cycle feedback. Using results from a large field litter manipulation experiment in Mongolian steppe, we here show that priming intensifies with increasing litter inputs, but at a decreasing efficiency: the stimulation per unit litter added declines with increasing litter inputs. This non-linear behavior originates from two antagonistic responses to fresh litter inputs: a stimulation of microbial activity versus a shift in microbial community composition (more fungi) associated to substrate shift from SOM to litter. Despite all complexity, however, the priming effect on SOM decomposition scaled linearly with the response of microbial biomass across the entire range of plant litter addition (60-480 g C m⁻²), suggesting that priming could be modeled effectively as a function of the response of microbial biomass to litter inputs. Incorporating the priming mechanism in Earth System models will improve their estimates of the SOM-climate feedback and appears to be best addressed by explicitly representing microbial biomass in the models

Organic carbon decomposition rates with depth under an agroforestry system in a calcareous soil

The aims of this study were: (i) assess soil organic carbon (SOC) mineralisation potential as a function of soil depth in an agroforestry (AF) plot compared to an agricultural plot (ii) estimate the contribution of soil inorganic carbon (SIC) to CO2 emissions at different depths. Soils were collected in an 18-year-old AF (tree rows and alleys) and in an adjacent agricultural plot. The incubation comprised four soil replicates per location (control, tree row, alley) and per depth (0-10, 10-30, 70-100 and 160-180 cm). Soil samples were moistened to reach field capacity, at pF 2.5, and were then incubated at 20°C in the dark. The CO2 concentration and the δ13C of the CO2 were measured after 1, 3, 7, 14, 21, 28, 35 and 44 days. The microbial biomass was measured at the end of the incubation. Decomposition rates were calculated, as well as the metabolic quotient. The cumulated total CO2, SIC-derived CO2 and SOC-derived CO2 emissions were only significantly higher in tree row than in the alley or in the control plot at 0-10 cm. SOC decomposition rates decreased with increasing depth. Contributions of SIC to total CO2 emissions according were comprised between 0.15 and 0.30 in topsoil layers and between 0.50 and 0.70 in subsoil layers. The higher emission in the tree row at 0-10 cm was related to a large amount of labile particulate organic matter. SOC did not seem to be more stabilized in AF compared to the control. SIC-derived CO2 must be taken into account on calcareous soils

Matrix representation of lateral soil movements: scaling and calibrating CE-DYNAM (v2) at a continental level

Promoting sustainable soil management is a possible option for achieving net-zero greenhouse gas emissions in the future. Several efforts in this area exist, and the application of spatially explicit models to anticipate the effect of possible actions on soils at a regional scale is widespread. Currently, models can simulate the impacts of changes on land cover, land management, and the climate on the soil carbon stocks. However, existing modeling tools do not incorporate the lateral transport and deposition of soil material, carbon, and nutrients caused by soil erosion. The absence of these fluxes may lead to an oversimplified representation of the processes, which hinders, for example, a further understanding of how erosion has been affecting the soil carbon pools and nutrients through time. The sediment transport during deposition and the sediment loss to rivers create dependence among the simulation units, forming a cumulative effect through the territory. If, on the one hand, such a characteristic implies that calculations must be made for large geographic areas corresponding to hydrological units, on the other hand, it also can make models computationally expensive, given that erosion and redeposition processes must be modeled at high resolution and over long timescales. In this sense, the present work has a three-fold objective. First, we provide the development details to represent in matrix form a spatially explicit process-based model coupling sediment, carbon, and erosion, transport, and deposition (ETD) processes of soil material in hillslopes and valley bottoms (i.e., the CE-DYNAM model). Second, we illustrate how the model can be calibrated and validated for Europe, where high-resolution datasets of the factors affecting erosion are available. Third, we presented the results for a depositional site, which is highly affected by incoming lateral fluxes from upstream lands. Our results showed that the benefits brought by the matrix approach to CE-DYNAM enabled the before-precluded possibility of applying it on a continental scale. The calibration and validation procedures indicated (i) a close match between the erosion rates calculated and previous works in the literature at local and national scales, (ii) the physical consistency of the parameters obtained from the data, and (iii) the capacity of the model in predicting sediment discharge to rivers in locations observed and unobserved during its calibration (model efficiency (ME) =0.603, R2=0.666; and ME =0.152, R2=0.438, respectively). The prediction of the carbon dynamics on a depositional site illustrated the model's ability to simulate the nonlinear impact of ETD fluxes on the carbon cycle. We expect that our work advances ETD models' description and facilitates their reproduction and incorporation in land surface models such as ORCHIDEE. We also hope that the patterns obtained in this work can guide future ETD models at a European scale.</p

Corrigendum to “Seasonal variations of Quercus pubescens isoprene emissions from an in natura forest under drought stress and sensitivity to futureclimate change in the Mediterranean area”

International audienc

Lowering water table reduces carbon sink strength and carbon stocks in northern peatlands

Peatlands at high latitudes have accumulated \u3e400 Pg carbon (C) because saturated soil and cold temperatures suppress C decomposition. This substantial amount of C in Arctic and Boreal peatlands is potentially subject to increased decomposition if the water table (WT) decreases due to climate change, including permafrost thaw-related drying. Here, we optimize a version of the Organizing Carbon and Hydrology In Dynamic Ecosystems model (ORCHIDEE-PCH4) using site-specific observations to investigate changes in CO and CH fluxes as well as C stock responses to an experimentally manipulated decrease of WT at six northern peatlands. The unmanipulated control peatlands, with the WT (seasonal max up to 45 cm) below the surface, currently act as C sinks in most years (58 ± 34 g C m year ; including 6 ± 7 g C-CH m year emission). We found, however, that lowering the WT by 10 cm reduced the CO sink by 13 ± 15 g C m year and decreased CH emission by 4 ± 4 g CH m year , thus accumulating less C over 100 years (0.2 ± 0.2 kg C m ). Yet, the reduced emission of CH , which has a larger greenhouse warming potential, resulted in a net decrease in greenhouse gas balance by 310 ± 360 g CO m year . Peatlands with the initial WT close to the soil surface were more vulnerable to C loss: Non-permafrost peatlands lost \u3e2 kg C m over 100 years when WT is lowered by 50 cm, while permafrost peatlands temporally switched from C sinks to sources. These results highlight that reductions in C storage capacity in response to drying of northern peatlands are offset in part by reduced CH emissions, thus slightly reducing the positive carbon climate feedbacks of peatlands under a warmer and drier future climate scenario

Soil organic carbon models need independent time-series validation for reliable prediction

Numerical models are crucial to understand and/or predict past and future soil organic carbon dynamics. For those models aiming at prediction, validation is a critical step to gain confidence in projections. With a comprehensive review of ~250 models, we assess how models are validated depending on their objectives and features, discuss how validation of predictive models can be improved. We find a critical lack of independent validation using observed time series. Conducting such validations should be a priority to improve the model reliability. Approximately 60% of the models we analysed are not designed for predictions, but rather for conceptual understanding of soil processes. These models provide important insights by identifying key processes and alternative formalisms that can be relevant for predictive models. We argue that combining independent validation based on observed time series and improved information flow between predictive and conceptual models will increase reliability in predictions