Christian Beer

Oxygen (O ₂ ) in marsh rhizospheres varies strongly at millimetre scales due to radial oxygen loss (ROL), re-oxidation of reduced compounds, hydrology, and sediment structure. Yet many models estimate heterotrophic (microbial) respiration at a single mean O ₂ , which can bias CO ₂ fluxes because the O ₂ response of respiration is curved (nonlinear). We calibrated an enzyme kinetic respiration function to marsh-soil incubations, then compared (I) respiration evaluated at a single mean O ₂ value with (II) the mean of different respiration fluxes over a prescribed rhizosphere O ₂ distribution. To isolate oxygen effects, temperature and the relation between substrate and soil moisture were held fixed; incubations were used only to calibrate carbon kinetics. For a gas-phase, air-equivalent O ₂ proxy, the single mean approach overestimates respiration by ∼ 12 % on average. This bias increases with increasing variation of O ₂ and with the ratio of mean O ₂ to the O ₂ half-saturation constant KM,O2. In the dissolved phase, mean O ₂ ≪ KM,O2 and variation in O ₂ is small, so the bias is negligible due to linear behaviour of the relation in these conditions; when physiology is unit-matched to a similar relative saturation, however, the dissolved case shows a negative bias comparable to the gas-phase one. Our findings suggest reporting the mean and variation of O ₂ together with a calibrated KM,O2 allows modellers to anticipate or correct the bias associated with replacing heterogeneous rhizosphere conditions with a single mean.

The vast majority of land-surface models uses a tiling-approach to capture the effects of subgrid-scale spatial heterogeneity in the land-surface properties. In most cases, however, the tiles, which represent patches with homogeneous characteristics at and below the surface, are treated independently of each other and the lateral exchange between them is not being taken into consideration. The present manuscript describes an approach for a tile-based representation of lateral exchange processes in heterogeneous landscapes that was recently implemented into ICON-Land, the land surface component of the ICON framework. The scheme captures the horizontal fluxes on a broad range of spatial scales and represents 5 lateral exchange processes, namely gravity-driven moisture fluxes and the corresponding advective heat transport, diffusive- and conductive fluxes of water and heat as well as the redistribution of snow between small-scale topographic features. In the approach, the relationships between any two tiles are determined by a set of characteristic connectivities which are treated as inherent properties of the pair of tiles – invariant in time and independent of the location – and derive from the internal logic underlying the definition of the tiles. The characteristic connectivities are used to calculate the spatio-geometric relationships between two tiles, such as the (geometrical) contact length or the characteristic center-to-center distance between two adjacent surface clusters. These, in turn, define gradients as well as the time-lag factors that govern the lateral transport in the model. In addition to a description of the model development, we present two example applications of the new scheme, which address the effect of sub-grid scale fluxes on the model's ability to capture the spatial variability in the state of the surface and sub-surface and the overall terrestrial water storage. Here, our results suggest that lateral exchange processes, especially on small horizontal scales, are highly relevant for the spatial variability in the soil temperatures and for the simulated extent of surface water bodies, while the effects on the grid-cell mean state and the turbulent exchange with the atmosphere appear to be largely negligible.

Greenhouse gas release due to microbial decomposition of thawing permafrost organic matter receives ample attention but the other side of the permafrost soil carbon budget, the stabilization of organic matter due to rising plant litter input in a greening Arctic has hardly been addressed. Here we explore whether thawing permafrost material may act as a long-term sink of fresh plant litter carbon. To identify the magnitude and drivers of litter carbon stabilization in thawing permafrost material, we incubated samples from the permafrost layer under oxic and anoxic conditions with ¹³C-labelled plant litter. Subsequently, we used the microbial CO₂ and CH₄ production from the added litter carbon (litter-C) and from the carbon in the thawed permafrost material (permafrost-C) to calibrate a carbon decomposition model with a fast and a slow carbon pool. Beside the size of the different pools, their mean residence times (MRT) were calculated as an indicator for carbon stabilization in these soils. Finally, we fractionated the remaining organic matter into a dissolved, a mineral-associated and a particulate fraction. At the end of the experiment, after nine years, on average 40 % to 60 % of the added litter-C persisted in the thawed permafrost material. The MRT of the slow litter-C pool of 18 years (oxic) and 52 years (anoxic) indicate a substantial stabilization of fresh litter-C over the course of the experiment. More than 80 % of the remaining litter-C was part of the mineral-associated fraction, but in contrast to current understanding, litter decomposability was positively correlated with the size of the mineral bound litter-C pool. Although the fraction of mineral-bound permafrost-C (64 % to 68 %) was significantly smaller than of litter-C, the MRT of the slow permafrost-C pools was more than 10-fold higher. Hence, the size of the mineral bound carbon pool alone may not be a suitable measure of carbon stabilization. We furthermore identified interactions between new litter carbon and pre-existing mineral-bound carbon from the thawed permafrost material as an important driver of litter-C stabilization. Such interactions could reduce net carbon emissions from thawing permafrost and add complexity to the permafrost carbon climate feedback.

Soil properties vary within centimeters, which is not captured by state-of-the-art land-surface models due to their kilometer-scale grid. This mismatch can lead to systematic errors when simulating the exchange of energy, water, and greenhouse gases between the land and atmosphere – collectively referred to as “aggregation error”. To quantify the potential aggregation error of soil temperature, we developed the two-dimensional pedon-scale geophysical soil model DynSoM-2D, which has a spatial resolution of 10 cm. We applied DynSoM-2D at a permafrost-affected, non-sorted circle site using three different setups: (i) a homogeneous soil profile representing a typical land surface model, compiled by averaging the heterogeneous soil inputs; (ii) the actual heterogeneous soil profile of a typical non-sorted circle; and (iii) the heterogeneous soil profile including lateral heat fluxes. Our results show that DynSoM simulates warmer soil temperatures when heterogeneous soil properties are considered, with this warming becoming even more pronounced and consistent across the domain when lateral heat fluxes are included. By aggregating grid cells, we traced the aggregation error back to the spatial distribution of organic matter, which nonlinearly alters soil thermal and hydrological properties, leading to the observed differences between simulations. In our case, the heterogeneity-induced warming led to a deepening of the active layer and an extension of the snow-free period, both of which can strongly alter ecosystem dynamics, while having only a minor effect on soil-atmosphere heat exchange on an annual basis.

Pyrogenic carbon capture and storage, enhanced weathering (EW), soil organic carbon (SOC) enhancement and biomass carbon capture are terrestrial carbon dioxide removal (CDR) methods that could be implemented on a short timescale. To maximize the CDR potential per area, these methods could be co-deployed and provide complementary co-benefits. This requires a substantial understanding of the ongoing reactions and interactions in the system at different scales, backed up by field data and dynamic models to estimate applicability and scalability of the method combination. Biochar and weathering of silicate rock powder have the potential to provide besides CDR also nutrients, change soil properties and affect plant growth, directly impacting soil organic carbon storage and biomass carbon capture. Nevertheless, the interactions between the amendments and their combined effects in the soil system are sparsely researched.PyMiCCS as part of CDRterra addresses these knowledge gaps and estimates the potential of the proposed combination of the different methods. The co-application of various biochars with rock powder as well as the co-pyrolysis of both amendments was realized and products characterized. The co-pyrolysis of biochar and rock powder can modify biochar properties, such as weight, porosity, nutrient content and stability. Furthermore, the application of materials to different soil types with and without crops was tested at various spatio-temporal scales. Biochar additions improved water circulation in clayey soils, while rock powders released nutrients. Furthermore, amendments increased SOC contents, with differences between combinations and single applications. While soil nutrient levels were elevated, no significant plant growth increases were observed in comparison to single applications. In the long-term, simulations for temperate climate and sandy soil suggest that the solo-biochar applications can increase non-biochar SOC by up to 300 kg ha-1 yr-1 per ton biochar and result in net ecosystem carbon uptake over 1000 years. Complementing experimental results and process-based modeling, an integrated economic assessment was conducted using a global land-use modelling framework. The analysis shows that the environmental and mitigation outcomes of biochar-based CDR depend on interactions between costs, agronomic yield responses, biochar persistence, application rates, and assumptions about carbon pricing or crediting. Overall, the results demonstrate that co-application of biochar and enhanced weathering can enhance soil carbon storage and nutrient dynamics, but side-specific assessments are needed, and amendments do not necessarily translate into increased crop yields. Our results highlight the substantial CDR potential and the importance of tailored evaluations, management strategies, and policy frameworks for their scalable and effective implementation.

Greenhouse gas release due to microbial decomposition of thawing permafrost organic matter receives ample attention but the other side of the permafrost soil carbon budget, the stabilization of organic matter due to rising plant litter input in a greening Arctic has hardly been addressed. Here we explore whether thawing permafrost may act as a long-term sink of fresh plant litter carbon. To identify the magnitude and drivers of litter carbon stabilization in thawing permafrost, we incubated permafrost samples under oxic and anoxic conditions with ¹³C-labelled plant litter for nine years, used the microbial CO₂ and CH₄ production to calibrate a carbon decomposition model, and finally fractionated the remaining organic matter into a dissolved, a mineral-associated and a particulate fraction. At the end of the experiment, on average 38.9 ± 21.1 (mean ± SD, oxic) and 59.1 ± 12.2 % (anoxic) of the added litter-C was still present in the thawed permafrost. The mean residence times of the stable litter carbon pool of 17.6 (22.3) yr (median (IQR), oxic) and 52.4 (54.2) yr (anoxic) indicate a substantial stabilization of fresh litter carbon in thawing permafrost. Most of the remaining litter carbon (82.5 (35.3) % oxic and 83.8 (21.4) % anoxic) was part of the mineral-associated fraction, but in contrast to current understanding, litter decomposability is positively correlated with the size of the mineral bound litter pool. Although the fraction of mineral-bound permafrost carbon (64.4 (20.0) % oxic and 68.0 (17.0) % anoxic) was significantly smaller than of litter carbon, the mean residence times of the stable permafrost carbon pools were more than 10-fold higher. We identified interactions between new litter carbon and pre-existing mineral-bound permafrost carbon as an important driver of litter carbon stabilization. Such interactions may reduce net carbon emissions from thawing permafrost and add complexity to the permafrost carbon climate feedback.

Equilibrated soil organic carbon (SOC) states are a prerequisite for Earth system model simulations following CMIP and TRENDY protocols, which rely on long preindustrial spin-up phases prior to historical and future integrations. While conventional linear soil carbon models readily achieve equilibrium, microbial-explicit soil carbon models frequently exhibit slow convergence or persistent SOC drift even after millennial-scale spin-up, raising concerns about their applicability in Earth system simulations.Previous analytical work has derived steady-state solutions for microbial soil carbon models under the assumption of vertically integrated, well-mixed systems, but it remains unclear whether such analytical equilibria are sufficient when models include vertical soil structure and transport processes. Here, we systematically assess the role of soil profile discretization, transport, and model structure in controlling SOC equilibration, and evaluate whether analytically derived steady states can provide reliable initial conditions for depth-resolved microbial soil carbon models.Using the QUINCY land model framework, we conduct a hierarchy of simulations under standard CMIP-style protocols, consisting of a 1000-year spin-up followed by historical simulations (1850–2019). First, we apply QUINCY-derived litter inputs to the vertically integrated microbial soil carbon model Millennial, which includes explicit microbial dynamics and mineral-associated organic matter formation but no vertical transport. Second, we simulate soil carbon dynamics in QUINCY using a CENTURY-type linear soil model (SSM) with explicit vertical discretization (5 and 15 soil layers to 9.5 m depth), providing a reference case with well-defined analytical equilibria. Third, we perform fully depth-resolved simulations using the Jena Soil Model (JSM) within QUINCY, combining microbial-explicit carbon cycling, sorption dynamics, and vertical transport.We hypothesize that difficulties in equilibrating microbial soil carbon models arise primarily from structural interactions between nonlinear microbial kinetics, sorption capacity constraints, and vertical transport, rather than from numerical deficiencies or insufficient spin-up duration. We further expect that analytically constrained initial conditions substantially reduce equilibration times and SOC drift in bucket models and linear depth-resolved systems, while providing a useful—but not fully sufficient—approximation for initializing complex microbial soil carbon models with dynamic soil profiles.By explicitly comparing linear and microbial soil carbon models across vertically integrated and depth-resolved configurations, this study clarifies the conditions under which analytical steady-state solutions are adequate for CMIP- and TRENDY-style simulations, and identifies remaining structural challenges for deploying microbial soil carbon models in Earth system frameworks.

The Arctic is warming at an increased rate. This will lead to large-scale permafrost thaw, thereby potentially releasing significant amounts of greenhouse gases to the atmosphere through the decomposition of previously frozen organic material in the soils. To accurately gauge the impact of these emissions, it is crucial to know the emission ratio between the two most important greenhouse gases CO2 and CH4. While CO2 is projected to be the dominant gas, it is important to consider the amplified climatic forcing of CH4, which is a stronger greenhouse gas than CO2. Laboratory incubations and in situ studies have shown that the CO2:CH4 ratio is highly variable. Despite this, most land surface models use a pre-set ratio factor to simulate methanogenesis, thus making it impossible to capture the dynamics of the CO2:CH4 ratio from the start, and, in consequence, making prediction of the Arctic carbon budget more uncertain. Methanogenesis is a complicated framework of different microbial processes, most importantly the two main production pathways – acetoclastic and hydrogenotrophic methanogenesis – and fermentation, which produces the substrate for the two former processes. The inclusion of these processes into models has been studied on the small, i.e. lab to site-level, scale but this has rarely been explored on a pan-Arctic scale. Here, we augmented the JSBACH land surface model’s methane routine, which normally uses a predefined CH4 production ratio factor, by including the three aforementioned microbial processes to study the CO2:CH4 ratio on a pan-Arctic scale. We present the new model routine, show how it performs against the base model, and how the results compare to other estimates from the literature. We discuss the uncertainty of the new results and highlight the difficulties in upscaling many of the factors that influence the CO2:CH4 production ratio.