Globally, soil organic matter (SOM) contains more than three times as much carbon as either the atmosphere or terrestrial vegetation. Yet it remains largely unknown why some SOM persists for millennia whereas other SOM decomposes readily-and this limits our ability to predict how soils will respond to climate change. Recent analytical and experimental advances have demonstrated that molecular structure alone does not control SOM stability: in fact, environmental and biological controls predominate. Here we propose ways to include this understanding in a new generation of experiments and soil carbon models, thereby improving predictions of the SOM response to global warming.Understanding soil biogeochemistry is essential to the stewardship of ecosystem services provided by soils, such as soil fertility (for food, fibre and fuel production), water quality, resistance to erosion and climate mitigation through reduced feedbacks to climate change. Soils store at least three times as much carbon (in SOM) as is found in either the atmosphere or in living plants 1 . This major pool of organic carbon is sensitive to changes in climate or local environment, but how and on what timescale will it respond to such changes? The feedbacks between soil organic carbon and climate are not fully understood, so we are not fully able to answer these questions 2-7 , but we can explore them using numerical models of soil-organic-carbon cycling. We can not only simulate feedbacks between climate change and ecosystems, but also evaluate management options and analyse carbon sequestration and biofuel strategies. These models, however, rest on some assumptions that have been challenged and even disproved by recent research arising from new isotopic, spectroscopic and molecularmarker techniques and long-term field experiments.Here we describe how recent evidence has led to a framework for understanding SOM cycling, and we highlight new approaches that could lead us to a new generation of soil carbon models, which could better reflect observations and inform predictions and policies.

A large source of uncertainty in present understanding of the global carbon cycle is the distribution and dynamics of the soil organic carbon reservoir, Most of the organic carbon in soils is ; degraded to inorganic forms slowly, on timescales from centuries to millennia(1). Soil minerals are known to play a stabilizing role, but how spatial and temporal variation in soil mineralogy controls the quantity and turnover of long-residence-time organic carbon is not well known(2). Here we use radiocarbon analyses to explore interactions between soil mineralogy and soil organic carbon along two natural gradients-of soil-age and of climate-in volcanic soil environments, During the first similar to 150,000 years of soil development, the volcanic parent material weathered to metastable, non-crystalline minerals, Thereafter, the amount of non-crystalline minerals declined, and more stable crystalline minerals accumulated. Soil organic carbon content followed a similar trend, accumulating to a maximum after 150,000 years, and then decreasing by 50% over the next four million years. A positive relationship between non-crystalline minerals and organic carbon was also observed in soils through the climate gradient, indicating that the accumulation and subsequent loss of organic matter were largely driven by changes in the millennial scale cycling of mineral-stabilized carbon, rather than by changes in the amount of fast-cycling organic matter or in net primary productivity. Soil mineralogy is therefore important in determining the quantity of organic carbon stored in soil, its turnover time, and atmosphere-ecosystem carbon fluxes during long-term soil development; this conclusion should be generalizable at least to other humid environments

Abstract. Terrestrial net CH 4 surface fluxes often represent the difference between much larger gross production and consumption fluxes and depend on multiple physical, biological, and chemical mechanisms that are poorly understood and represented in regional-and global-scale biogeochemical models. To characterize uncertainties, study feedbacks between CH 4 fluxes and climate, and to guide future model development and experimentation, we developed and tested a new CH 4 biogeochemistry model (CLM4Me) integrated in the land component (Community Land Model; CLM4) of the Community Earth System Model (CESM1). CLM4Me includes representations of CH 4 production, oxidation, aerenchyma transport, ebullition, aqueous and gaseous diffusion, and fractional inundation. As with most global models, CLM4 lacks important features for predicting current and future CH 4 fluxes, including: vertical representation of soil organic matter, accurate subgrid scale hydrology, realistic representation of inundated system vegetation, anaerobic decomposition, thermokarst dynamics, and aqueous chemistry. We compared the seasonality and magnitude of predicted CH 4 emissions to observations from 18 sites and three global atmospheric inversions. Simulated net CH 4 emissions using our baseline parameter set were 270, 160, 50, and 70 Tg CH 4 yr −1 globally, in the tropics, in the temperate zone, and north of 45 • N, respectively; these values are within the range of previous estimates. We then used the model to characterize the sensitivity of regional and global CH 4 emission estimates to uncertainties in model paCorrespondence to: W. J. Riley (wjriley@lbl.gov) rameterizations. Of the parameters we tested, the temperature sensitivity of CH 4 production, oxidation parameters, and aerenchyma properties had the largest impacts on net CH 4 emissions, up to a factor of 4 and 10 at the regional and gridcell scales, respectively. In spite of these uncertainties, we were able to demonstrate that emissions from dissolved CH 4 in the transpiration stream are small (<1 Tg CH 4 yr −1 ) and that uncertainty in CH 4 emissions from anoxic microsite production is significant. In a 21st century scenario, we found that predicted declines in high-latitude inundation may limit increases in high-latitude CH 4 emissions. Due to the high level of remaining uncertainty, we outline observations and experiments that would facilitate improvement of regional and global CH 4 biogeochemical models.

The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Soil organic matter (OM) can be stabilized against decomposition by association with minerals, by its inherent recalcitrance and by occlusion in aggregates. However, the relative contribution of these factors to OM stabilization is yet unknown. We analyzed pool size and isotopic composition ( 14 C, 13 C) of mineral-protected and recalcitrant OM in 12 subsurface horizons from 10 acidic forest soils. The results were related to properties of the mineral phase and to OM composition as revealed by CPMAS 13 C-NMR and CuO oxidation. Stable OM was defined as that material which survived treatment of soils with 6 wt% sodium hypochlorite (NaOCl). Mineral-protected OM was extracted by subsequent dissolution of minerals by 10% hydrofluoric acid (HF). Organic matter resistant against NaOCl and insoluble in HF was considered as recalcitrant OM. Hypochlorite removed primarily 14 C-modern OM. Of the stable organic carbon (OC), amounting to 2.4-20.6 g kg À1 soil, mineral dissolution released on average 73%. Poorly crystalline Fe and Al phases (Fe o , Al o ) and crystalline Fe oxides (Fe dÀo ) explained 86% of the variability of mineral-protected OC. Atomic C p /(Fe+Al) p ratios of 1.3-6.5 suggest that a portion of stable OM was associated with polymeric Fe and Al species. Recalcitrant OC (0.4-6.5 g kg À1 soil) contributed on average 27% to stable OC and the amount was not correlated with any mineralogical property. Recalcitrant OC had lower D 14 C and d 13 C values than mineral-protected OC and was mainly composed of aliphatic (56%) and O-alkyl (13%) C moieties. Lignin phenols were only present in small amounts in either mineral-protected or recalcitrant OM (mean 4.3 and 0.2 g kg À1 OC). The results confirm that stabilization of OM by interaction with poorly crystalline minerals and polymeric metal species is the most important mechanism for preservation of OM in these acid subsoil horizons.Abbreviations: CPMAS 13 C-NMR -cross-polarization magic-angle spinning 13 C nuclear magnetic resonance spectroscopy; FR -fluoride reactivity; OC -organic C; OM -organic matter; MOC and MN -mineral-protected organic C and N; ROC and RN -chemically resistant (recalcitrant) organic C and N; SSA -specific surface area; XRD -x-ray diffraction; TEM -transmission electron microscopy

Abstract. Soils are a crucial component of the Earth system; they comprise a large portion of terrestrial carbon stocks, mediate the supply and demand of nutrients, and influence the overall response of terrestrial ecosystems to perturbations. In this paper, we develop a new soil biogeochemistry model for the Community Land Model, version 4 (CLM4). The new model includes a vertical dimension to carbon (C) and nitrogen (N) pools and transformations, a more realistic treatment of mineral N pools, flexible treatment of the dynamics of decomposing carbon, and a radiocarbon ( 14 C) tracer. We describe the model structure, compare it with site-level and global observations, and discuss the overall effect of the revised soil model on Community Land Model (CLM) carbon dynamics. Site-level comparisons to radiocarbon and bulk soil C observations support the idea that soil C turnover is reduced at depth beyond what is expected from environmental controls for temperature, moisture, and oxygen that are considered in the model. In better agreement with observations, the revised soil model predicts substantially more and older soil C, particularly at high latitudes, where it resolves a permafrost soil C pool. In addition, the 20th century-C dynamics of the model are more realistic than those of the baseline model, with more terrestrial C uptake over the 20th century due to reduced N downregulation and longer turnover times for decomposing C.

Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool-and flux-based data sets through data assimilation is LUO ET AL.SOIL CARBON MODELING 40 PUBLICATIONS

[1] Accurately simulating gross primary productivity (GPP) in terrestrial ecosystem models is critical because errors in simulated GPP propagate through the model to introduce additional errors in simulated biomass and other fluxes. We evaluated simulated, daily average GPP from 26 models against estimated GPP at 39 eddy covariance flux tower sites across the United States and Canada. None of the models in this study match estimated GPP within observed uncertainty. On average, models overestimate GPP in winter, spring, and fall, and underestimate GPP in summer. Models overpredicted GPP under dry conditions and for temperatures below 0 C. Improvements in simulated soil moisture and ecosystem response to drought or humidity stress will improve simulated GPP under dry conditions. Adding a low-temperature response to shut down GPP for temperatures below 0 C will reduce the positive bias in winter, spring, and fall and improve simulated phenology. The negative bias in summer and poor overall performance resulted from mismatches between simulated and observed light use efficiency (LUE). Improving simulated GPP requires better leaf-to-canopy scaling and better values of model parameters that control the maximum potential GPP, such as ɛ max (LUE), V cmax (unstressed Rubisco catalytic capacity) or J max (the maximum electron transport rate).