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Phosphorus (P) availability affects the response of terrestrial ecosystems to environmental and climate change (e.g., elevated CO2), yet the magnitude of this effect remains uncertain. This uncertainty arises mainly from a lack of quantitative understanding of the soil biological and geochemical P cycling processes, particularly the P exchange with soil mineral surfaces, which is often described by a Langmuir sorption isotherm. We first conducted a literature review on P sorption experiments and terrestrial biosphere models (TBMs) using a Langmuir isotherm. We then developed a new algorithm to describe the inorganic P exchange between soil solution and soil matrix based on the double-surface Langmuir isotherm and extracted empirical equations to calculate the sorption capacity and Langmuir coefficient. We finally tested the conventional and new models of P sorption at five beech forest sites in Germany along a soil P stock gradient using the QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system) TBM. We found that the conventional (single-surface) Langmuir isotherm approach in most TBMs largely differed from P sorption experiments regarding the sorption capacities and Langmuir coefficients, and it simulated an overly low soil P-buffering capacity. Conversely, the double-surface Langmuir isotherm approach adequately reproduced the observed patterns of soil inorganic P pools. The better representation of inorganic P cycling using the double-surface Langmuir approach also improved simulated foliar N and P concentrations as well as the patterns of gross primary production and vegetation carbon across the soil P gradient. The novel model generally reduces the estimates of P limitation compared with the conventional model, particularly at the low-P site, as the model constraint of slow inorganic P exchange on plant productivity is reduced.

Laboratory quantification and computer modeling of soil organic carbon (SOC) and radiocarbon (14C) rarely align well. Diverse lab methods exist to separate SOC into “fractions” with operationally defined boundaries which include physical, chemical, and biological thresholds. Compartmental soil models, on the other hand, use homogeneous “pools” to group SOC by its rate of decay. However, the stochastic nature of organic matter decomposition makes it virtually impossible to isolate model pools through fractionation or to model fractions as pools. Radiocarbon is a powerful metric that integrates C fluxes in and out of a system, but fraction and pool 14C valuesrepresent an average which may be composed of widely different C ages. In order to advance and constrain our understanding of SOC dynamics, we need to go beyond mean 14C values of operationally defined pools and instead use radiocarbon distributions. Thermal (oxidative) fractionation of SOC produces continuous C data as a function of temperature (20˚C to 900˚C), and discrete 14C measurements by collecting evolved gas. By fitting splines to 14C data and weighing by C release over temperature, a continuous mass-weighted distribution of 14C can be estimated. Recent modeling advances can similarly estimate system 14C distributions, and models may thus be constrained for the first time by continuous lab data. This convergence is a first step beyond pools and fractions that may significantly increase constraining power. We will present lab and mathematical methods, limitations, and outlooks for advancing soil SOC modeling.

Forest ecosystems in central Europe are currently experiencing various environmental changes like ongoing nitrogen deposition, rising CO2 levels and more frequent summer droughts, with potential impacts on biogeochemical processes in soils. Monitoring of soil properties, especially sensitive indicators like the activities of extracellular enzymes, enables studying the net effect of different simultaneously ongoing global changes on soil processes. Therefore, we measured the potential activities of four extracellular enzymes related to the C, N, P and S cycle (beta-glucosidase, N-actetyl-glucosaminidase, acid phosphatase and sulfatase) of topsoils (0-10 cm of the mineral soil) from 150 forest plots under different management in three German regions as part of the Biodiversity Exploratories (https://www.biodiversity-exploratories.de/en/) project (Swabian Alb in the South, Hainich-Dün in the center and Schorfheide Chorin in the North of Germany) in May of 2011, 2014, 2017 and 2021. Analyzed soil samples were mixed samples composed of 14 soil cores (5 cm diameter) per plot, taken along two 40 m transects, sieved to < 2mm, and stored frozen before analyses. Additional information on soil C, N and pH was obtained for the same samples. Results revealed that the interannual variation of enzyme activities was about twice as high as that of soil organic carbon contents. Organic carbon, total nitrogen contents or soil pH showed no consistent trend over time across the regions. The same was true for the enzymes beta-glucosidase, N-acetyl-glucosaminidase and sulfates while acid phosphatase activity increased in all regions from 2011 to 2021 with the smallest absolute increase from on average 1290 to 2753 nmol MUF g−1 dw h−1 in the sandy and most acidic region Schorfheide Chorin, and the largest one in the loess-dominated silt-clay soils of the Hainich-Dün region (from 3474 to 5570 nmol MUF g−1 dw h−1). Accordingly, the ratio of carbon-to-phosphorus acquiring enzymes declined with time. Plots following Moorhead et al. (2016, http://dx.doi.org/10.1016/j.soilbio.2015.10.01) indicated a consistent shift from N- to P-limitation across regions, independent of their total P contents and for both, coniferous and deciduous forests. Forest ecosystems seem to need to acquire more P from organic sources but given that both, plants and microorganisms can produce acid phosphatase, we are currently not able to say, if the increased phosphatase activity was a direct plant response or one (potentially mediated) by microorganisms. However, elevated CO2 and N-deposition can both potentially lead to nutrient imbalances and thus increasing forest P requirements, and also summer droughts might reduce plant nutrient uptake, so that the observed trend might be an additive effect of all, rather than being attributable to one alone. As next steps we will test if changes in enzyme activities go along with changes in soil microbial communities and with leaf litter P contents.

Describing the coupling of nitrogen (N), phosphorus (P), and carbon (C) cycles of land ecosystems requires understanding microbial element use efficiencies of soil organic matter (SOM) decomposition. These efficiencies are studied by the soil enzyme steady allocation model (SESAM) at decadal scale. The model assumes that the soil microbial community and their element use efficiencies develop in a way that maximizes the growth of the entire community. Specifically, SESAM approximated this growth optimization by allocating resources to several SOM degrading enzymes proportional to the revenue of these enzymes, called the Relative approach. However, a rigorous mathematical treatment of this approximation has been lacking so far. Therefore, this study derives explicit formulas of enzyme allocation that maximize total return from enzyme reactions, called the Optimal approach. When comparing predictions across these approaches, we find that the Relative approach is a special case of the Optimal approach valid at sufficiently high microbial biomass. However, at low microbial biomass, it overestimates allocation to the enzymes having lower revenues.The model finding that a smaller set of enzyme types is expressed at low microbial biomass provides another hypothesis for why some substrates in soil are preserved over decades although being decomposed within a few years in incubation experiments. This study is another step in integrating a simple representation of an adaptive microbial community into coupled stoichiometric CNP SOM dynamic models.

Roots are difficult to measure at high temporal resolution but are important as belowground sinks and sources of CO2. Even in an age of automated and remote estimation of many ecosystem properties, belowground plant biomass is opaque at all but the coarsest timescales. Further, root dynamics are not fully predictable from aerial biomass change. Many uncertainties in predicting whole ecosystem function derive from this lack of data belowground.Using automated minirhizotrons, we captured images of root dynamics four times a day from February to October in a permanent temperate grassland in Germany. We processed all images collected using a trained neural network model and image analysis scripts to extract morphological traits from segmented images. We found root growth occurring continuously, even at sub-zero aboveground air temperatures. As a whole population, most of the root growth was in spring, although turnover and replacement happened at all times. Root length density and extractable root surface area increased through spring but decreased through a dry summer into autumn. Mean rooting depth increased until summer but did not decrease during the study period. Mean root diameter only increased once the dry period began.We also examined the patterns of growth between day and night. Early in the year roots grew in both day and night time periods, but after initial rapid biomass growth, root growth was at night. We examine the reasons for this switch relating to source and sink control of plant growth. We also consider implications for an accurate partitioning of carbon budgets in terrestrial ecosystems.

Elevated atmospheric carbon dioxide (CO2) concentrations can have a positive effect on plant growth, and are also expected to alter the plant belowground allocation of photosynthetically fixed carbon (C). The release of root-derived exudates can potentially stimulate soil microbial activity and the turnover of existing soil C. However, soil organic matter decomposition response to elevated CO2 may vary depending on the level of available nutrients, particularly nitrogen (N), which is the most limiting nutrient. To investigate the combined effect of CO2­ and available N on rhizodeposition and soil C turnover, a greenhouse mesocosm experiment was conducted. A total of 64 hornbeam (Carpinus betulus L.) trees were exposed to ambient (400 ppm, aCO2) or elevated (580 ppm, eCO2) concentrations of CO2 at 13C-enrichment of 100 permil, in order to trace C in the system. Two levels of N were applied to the soils in the form of 15N-labelled ammonium nitrate (NH4NO3). Above and belowground C fluxes were continuously monitored for partitioning of soil heterotrophic and autotrophic respirations. After one growing season, the trees and soils were destructively harvested. The trees were separated into buds, leaves, branches, stem and roots, which were analysed for CN and their respective isotopic compositions. Soils were separated into rhizosphere and bulk soils, and were analysed for CN, isotopic compositions, microbial biomass and enzyme activities. We observed an increase in the belowground C allocation under eCO2 and trees showed a higher active fine root growth response to eCO2. Consequently, the overall microbial biomass in the rhizosphere as well as the fraction of microbial biomass C derived from roots increased under eCO2. Enzyme activities, especially those of β-Glucosidase and N-acetyl-β-d-glucosaminidase, increased, while phosphatase and peroxidase activities decreased under eCO2. Despite the stimulated microbial activities, changes in soil C were not observed. Furthermore, we did not find any interactive effect of available N with eCO2, which suggested that N availability did not strongly influence belowground C allocation by trees.

Formation of mineral-associated organic matter (MAOM) supports accumulation and stabilization of carbon in soil, and thus, is a key factor in the global carbon cycle. Little is known about the interplay of mineral type, land use, and management intensity on the extent of MAOM formation. We addressed this research question by exposing mineral containers with pristine minerals (goethite, as a representative of oxide-type mineral phases, and illite, representing layered aluminosilicate minerals) for five years to ambient soil conditions at 5 cm depth in 150 grassland and 150 forest plots in three regions across Germany. After recovery, the content of organic carbon (OC) of the minerals was determined by dry combustion. Results show that irrespective of land use and management intensity, more OC accumulated on goethite than illite (on average 0.23 and 0.06 mg m-2 mineral surface, respectively), demonstrating that mineral type was the most crucial factor for MAOM formation. Carbon accumulation was consistently greater in coniferous forests than in deciduous forests and grasslands. Structural equation models revealed that in grasslands, fertilization had contradictory effects on carbon accumulation, with the positive effect being mediated by enhanced plant productivity and the negative effect by reduced plant species richness. Overall, our results suggest that OC stabilization in soil is primarily driven by mineral type, in particular iron and other metal oxides. The mineral-driven MAOM formation is further modified by land use and management intensity.

Soil respiration is rarely studied at the landscape scale where forest and soil properties can be important drivers. We performed forest and soil inventories in 150 temperate forest sites in three German landscapes and measured in situ soil CO2 efflux with the soda-lime method in early summer 2018 and 2019. Both years were affected by naturally occurring summer droughts. Our aim was to investigate the impact of forest structural and compositional properties, soil properties and climate on soil CO2 efflux at the landscape. Forest properties explained a large portion of soil CO2 efflux variance (i.e., 14% in 2018 and 20% in 2019), which was comparable or larger than the portion explained by soil properties (i.e., 15% in 2018 and 6% in 2019), and much larger than that of climate. Using Structural Equation Modeling, we found that forest structural properties, i.e., tree density and basal area, were negatively linked to soil CO2 efflux, while forest composition, i.e., conifer share and tree species richness, was not important. Forest structure effects on soil CO2 efflux were either direct or mediated by fine root biomass under dry summer conditions. Summer soil CO2 efflux was positively linked to fine root biomass but not related to total soil organic carbon stocks or climate. Forest structural properties influence soil CO2 efflux under drought events and should be considered when predicting soil respiration at the landscape scale.

Understanding the coupling of nitrogen (N) and carbon (C) cycles of land ecosystems requires understanding microbial element use efficiencies of soil organic matter (SOM) decomposition. Whereas important controls of those efficiencies by microbial community adaptations have been shown at the scale of a soil pore, a simplified representation of those controls is needed at the ecosystem scale. However, without abstracting from the many details, models are not identifiable; i.e. they cannot be fitted without ambiguities to observations. There is a need to find, implement, and validate abstract simplified formulations of theses processes. Therefore, we developed the Soil Enzyme Allocation Model (SEAM). The model explicitly represents community adaptation strategies of resource allocation to extracellular enzymes and enzyme limitations on SOM decomposition. They thus provide an abstraction from several microbial functional groups to a single holistic microbial community. Here we further simplify SEAM using a quasi-steady-state assumption for extracellular enzyme pools to derive the Soil Enzyme Steady Allocation Model (SESAM) and test whether SESAM can provide the same decadal-term predictions as SEAM. SESAM reproduced the priming effect, the SOM banking mechanism, and the damping of fluctuations in carbon use efficiency with microbial competition as predicted by SEAM and other more detailed models. This development is an important step towards a more parsimonious representation of soil microbial effects in global land surface models.

Climate and parent material both affect soil C persistence, yet the relative importance of climatic versus mineralogical controls on soil C dynamics remains unclear. To test this, we collected soil samples in 2001, 2009, and 2019 along a combined gradient of parent material (andesite, basalt, granite) and climate (mean annual temperature (MAT): 6.5 °C “cold”, 8.6 °C “cool”, 12.0 °C “warm”). We measured the radiocarbon of heterotrophically respired CO2 (∆14Crespired) and bulk soil C (∆14Cbulk) as proxies for transient and persistent soil C, and characterized mineral assemblages using selective dissolution. Using linear regression, we observed that MAT was not a significant predictor of either ∆14Cbulk or ∆14Crespired, yet climate was highly significant as a categorical variable. Climate explained more variance in ∆14Cbulk and ∆14Crespired over 0–0.1 m, but parent material explained more from 0.1–0.3 m. Cool site soil C was more persistent (lower ∆14Cbulk) than cold or warm climate sites, and also more persistent on andesitic soils, followed by basaltic and then granitic soils. Poorly crystalline metal oxides (PCMs) (but not crystalline metal oxides) were significantly (p < 0.1) correlated with ∆14Cbulk, ∆14Crespired, and ∆14Crespired - ∆14Cbulk, indicating their importance for soil C cycling on both short and long timescales. The change in ∆14Crespired observed over the study period was linearly related to MAT for the granite soils with the lowest PCM content, but not in the andesitic and basaltic soils with higher PCM content. This link between PCM abundance and the decoupling of MAT and soil C cycling rates suggests PCMs may attenuate the temperature sensitivity of decomposition.

Members of the verrucomicrobial clade 'Candidatus Udaeobacter' rank among the most dominant bacterial phylotypes in soil. Nevertheless, despite this global prevalence, in-depth analyses with respect to pH preferences of 'Ca. Udaeobacter' representatives are still lacking. Here, we utilized a recently designed primer pair, specifically targeting 'Ca. Udaeobacter', to investigate links between soil pH and the abundance as well as phylotype composition of this largely unexplored verrucomicrobial clade. Based on 150 forest and 150 grassland soils, comprising a broad pH range, we determined the highest total abundance of 'Ca. Udaeobacter' in strongly acidic soil (pH, ~5.1) and, noteworthy, in ultra-acidic soil (pH

Carbon (C) in soils persists on a range of timescales that depend on physical, chemical and biological processes that interact with soil organic matter (SOM) and affect its rate of decomposition. Together these processes determine the age distribution of C. Most attempts to measure this age distribution have relied on operationally defined fractions using properties like density, aggregate stability, solubility, or chemical reactivity. Recently, thermal fractionation, which relies on the activation energy needed to combust SOM, shows promise in separating young from old C by applying increasing heat to decompose SOM and equate this with biochemical stability in soil. Here, we investigated radiocarbon (14C) released during thermal fractionation to reconstruct thermal stabilities and age distributions of C released from bulk soil as well as its component density and chemical fractions. We found that bulk soil and all density and chemical fractions released progressively older C as temperatures increased. In addition, all fractions released some C across the entire temperature range, indicating that bulk soil thermal fractionations integrate young and old C at all temperatures. In the bulk soil, age distribution could be identifed by isolating particulate C prior to thermal fractionation of mineral-associated SOM. For the Podzol analyzed here, thermal fractions confirmed that ~95 % of the mineral-associated organic matter (MOM) had a relatively narrow 14C distribution, while 5 % was very low in 14C and likely reflected C from the < 2mm parent shale material in the soil matrix. By first removing particulate C using density or size separation, thermal fractionation can provide a rapid technique to study the age structure of MOM and how it is influenced by different OM-mineral interactions.

Soil respiration is an important pathway of soil organic carbon losses in temperate grasslands; however, it is rarely studied across broad management intensity gradients in a landscape. Using the soda-lime method, we measured in-situ soil CO2 efflux with single measurements of long exposure time (i.e. 3 day long) in 150 grasslands in three German regions in early summer 2018 and 2019. The grasslands ranged from unfertilized and grazed grasslands to intensively fertilized and frequently harvested ones. To assess effects of grazing and fertilization intensities and plant diversity on soil CO2 efflux, we used Structural Equation Modeling to account for direct effects and indirect effects through soil and plant organic matter quantity and quality. Soil CO2 efflux was suppressed by limited water availability caused by naturally occurring droughts in both study years. Under the prevailing environmental conditions, grazing intensity, plant biomass and plant C:N ratio were not related to soil CO2 efflux. In contrast, fertilization intensity was positively associated with soil CO2 efflux (standardized coefficient of net effect: + 0.04 in 2018 and + 0.03 in 2019). This was because fertilization led to lower plant species richness and, thus, to lower C:N ratios in soils, which were associated with higher soil CO2 efflux (plant species richness net effect: −0.09 in 2018 and −0.18 in 2019; soil C:N ratio direct effect: −0.23 in 2018 and −0.33 in 2019). Intensively managed grasslands have higher soil respiration than extensively managed, plant species-rich grasslands even under the extreme conditions of natural droughts., Nutrient Cycling in Agroecosystems, 124, ISSN:1385-1314, ISSN:1573-0867

Understanding the coupling of nitrogen (N) and carbon (C) cycles of land ecosystems requires understanding microbial element use efficiencies of soil organic matter (SOM) decomposition. Whereas important controls of those efficiencies by microbial community adaptations have been shown at the scale of a soil pore, a simplified representation of those controls is needed at the ecosystem scale. However, without abstracting from the many details, models are not identifiable; i.e. they cannot be fitted without ambiguities to observations. There is a need to find, implement, and validate abstract simplified formulations of theses processes. Therefore, we developed the Soil Enzyme Allocation Model (SEAM). The model explicitly represents community adaptation strategies of resource allocation to extracellular enzymes and enzyme limitations on SOM decomposition. They thus provide an abstraction from several microbial functional groups to a single holistic microbial community. Here we further simplify SEAM using a quasi-steady-state assumption for extracellular enzyme pools to derive the Soil Enzyme Steady Allocation Model (SESAM) and test whether SESAM can provide the same decadal-term predictions as SEAM. SESAM reproduced the priming effect, the SOM banking mechanism, and the damping of fluctuations in carbon use efficiency with microbial competition as predicted by SEAM and other more detailed models. This development is an important step towards a more parsimonious representation of soil microbial effects in global land surface models.

Phosphorus (P) availability affects the response of terrestrial ecosystems to environmental and climate change (e.g. elevated CO2), yet the magnitude of this effect remains uncertain. This uncertainty arises mainly from a lack of quantitative understanding of the soil biological and geochemical P cycling processes, particularly the P exchange with soil mineral surfaces, which is often described by a Langmuir sorption isotherm. We first conducted a literature review on P sorption experiments and terrestrial biosphere models (TBMs) using Langmuir isotherm. We then developed a new algorithm to describe the inorganic P exchange between soil solution and soil matrix based on the double-surface Langmuir isotherm and extracted empirical equations to calculate the sorption capacity and Langmuir coefficient. We finally tested the conventional and new models of P sorption at five beech forest sites in Germany along a soil P stock gradient using the QUINCY (QUantifying Interactions between terrestrial Nutrient CYcles and the climate system) TBM. We found that the conventional (single-surface) Langmuir isotherm approach in most TBMs largely differed from P sorption experiments regarding the sorption capacities and Langmuir coefficients, and simulated a too low soil P buffering capacity. Conversely, the double-surface Langmuir isotherm approach adequately reproduced the observed patterns of soil inorganic P pools. The better representation of inorganic P cycling using the double Langmuir approach also improved simulated foliar N and P concentrations, and the patterns of gross primary production and vegetation carbon across the soil P gradient. The novel model generally reduces the estimates of P limitation compared to the conventional model, particularly at the low-P site, as the model constraint of slow inorganic P exchange on plant productivity is reduced.

Globally, soil temperature to 1 m depth is predicted to be up to 4 °C warmer by the end of this century, with pronounced effects expected in temperate forest regions. Increased soil temperatures will potentially increase the release of CO2 from temperate forest soils, resulting in important positive feedback on climate change. Dark CO2 fixation by microbes can recycle some of the released soil CO2, and CO2 fixation rates are reported to increase under higher temperatures. However, research on the influence of temperature on dark CO2 fixation rates, particularly in comparison to the temperature sensitivity of respiration in soils of temperate forest regions is missing. To determine the temperature sensitivity (Q10) of dark CO2 fixation and respiration rates, we investigated soil profiles to 1 m depth from beech (deciduous) and spruce (coniferous) forest plots of the Hummelshain forest, Germany. We used 13C-CO2 labelling and incubations of soils at 4 and 14 °C to determine CO2 fixation and net soil respiration rates and derived the Q10 values for both processes with depth. The average Q10 for dark CO2 fixation rates normalized to soil dry weight was 2.07 for beech and spruce profiles, and this was lower than the measured average Q10 of net soil respiration rates with ~2.98. Assuming these Q10 values, we extrapolated that net soil respiration might increase 1.16 times more than CO2 fixation under a projected 4 °C warming. In the beech soil, a proportionally larger fraction of the label CO2 was fixed into soil organic carbon than into microbial biomass compared to the spruce soil. This suggests primarily higher turnover (i.e. growth and death) of microbial cells, and we speculate that this is related to lower clay content in the beech soil. Despite a similar abundance of the total bacterial community in the beech and spruce soils, the beech soil also had a lower abundance of autotrophs, implying a higher proportion of heterotrophs when compared to the spruce soil, hence might partly explain the higher biomass turnover. Furthermore, higher temperatures in general lead to higher microbial biomass turnover in both soils. Our findings suggest that in temperate forest soils, CO2 fixation might be less responsive to future warming than net soil respiration and that variations in site-specific parameters might affect microbial biomass turnover and resultantly, dark CO2 fixation rates and its temperature sensitivity in temperate forest soils.

Soil organic carbon (SOC) is the largest terrestrial carbon pool. However, it is still uncertain how it will respond to climate change in the 21st century. Especially SOC losses due to soil warming are a source of uncertainty. It is generally accepted that microbially driven SOC decomposition will increase with warming, provided that sufficient assimilable substrate is available. Sorption to mineral surfaces or the soil moisture-dependent diffusion of substrates to microbial cells can limit substrate availability. Substrate supply is therefore a potentially rate limiting step for the temperature response of SOC decomposition.In SOC decomposition models, the combined effects of temperature and soil moisture on the decomposition rate can be represented by the Dual Arrhenius Michaelis-Menten (DAMM) model (Davidson et al. 2012). For any substrate (S), it describes the reaction velocity V = Vmax [S]/(kMS+ [S]), where [S] is the substrate concentration and kMS is the half-saturation constant. The maximum reaction velocity, Vmax, is temperature dependent and follows an Arrhenius function. Also, a positive correlation between temperature and kM-values of different enzymes has been empirically shown, with Q10 values ranging from 0.71-2.8 (Allison et al., 2018). As kMS appears in the denominator of the Michaelis-Menten equation, an increase in kMS leads to a lower reaction velocity (V) and V would become less temperature sensitive at low substrate concentrations.Besides temperature, substrate concentration [S] depends on soil moisture content. In a dry soil, substrate diffusion to the microbial surface is limited, whereas in a very wet soil, reduced oxygen availability can lower the reaction velocity (V). Changes in substrate supply in drying/(re)wetting soils coincide with changes in temperature which directly interact with the temperature sensitivities of Vmax and kMS. These interactions can have consequences for decomposition rates in the topsoil versus the deeper soil, since substrate concentrations and temperature are generally higher in the topsoil, but moisture could be more important for substrate limitation. In contrast, in the deep soil, soil moisture might be more available but substrate concentrations (and potentially soil temperatures) might be lower.This study focuses on this interaction between climate change and substrate availability by comparing two model experiments: 1) a modelling experiment where only Vmax is temperature sensitive and 2) one where both Vmax and kMS are temperature sensitive. We also investigate the consequences of the counteracting temperature sensitivities of Vmax and kMS among a substrate gradient, and at different soil temperatures and soil moisture ranges. Finally, we look at dynamic changes in substrate supply, temperature sensitivities and changes in soil moisture and their effects on SOC decomposition in a microbially explicit dynamic SOC decomposition model which also includes organo-mineral interactions.

Over the past years, many mechanistic soil organic carbon models have been developed. While these models offer a clear improvement in process representation compared to classic SOC models (e.g. of microbial mineralization and mineral protection of OC), the increase in model complexity, and thus the number of uncertain model parameters, is generally not supported by sufficient available data. Thus, model parameters can generally not be sufficiently constrained through a calibration with typically used data, like soil carbon contents, because multiple, similarly good solutions are possible (referred to as the equifinality problem).A common approach to reduce equifinality in SOC models is to use 14C isotopes of SOC as an additional constraint during model calibration. While this approach has shown to improve parameter identifiability (i.e., the identification of unique parameters that lead to optimal results), data on the Δ14C of SOC is often not available due to high measurement costs. Therefore, we explored the potential of constraining a SOC model with the more widely available ratio of stable carbon isotopes of SOC (δ13C). While simulations of Δ14C generally better constrain the turnover time of slowly cycling SOC pools, simulations of δ13C allow to constrain additional processes, such as mixing of OC from aboveground and belowground sources and recycling of SOC through microbes. To do so, we developed a novel mechanistic, microbially driven model that simulates depth profiles of SOC (SOILcarb). In addition to total OC, the model simulates the δ13C and Δ14C value of SOC, by incorporating multiple processes affecting these isotopic ratios in soils.Our results show that SOILcarb was able to accurately simulate depth profiles of total SOC, δ13C and Δ14C of a forest soil. To optimally explore the parameter space, we used a differential evolution calibration algorithm and extracted all parameter sets that led to a reliable simulation of depth profiles given a fixed error margin. The results showed that simulations calibrated only on total OC data did not results in a good fit of simulated depth profiles of either δ13C or Δ14C. In contrast, simulations using either δ13C or Δ14C as an additional model constraint led to accurate simulations of depth profiles of total OC, δ13C and Δ14C by reducing the range in, and absolute value of, parameter values related to mainly vertical transport and protection rates of OC. Notably, parameters related to microbial OC uptake rates and microbial turnover were not better constrained by either isotopic ratio. Our results show that additional constraints on parameter values, in addition to total SOC, are necessary to increase confidence in model parameters of mechanistic SOC models, while more work is needed to better constrain microbial processes in these models.

Climate and parent material interact to form mineral assemblages that contribute to soil organic matter persistence across a range of time scales. Mineral associated soil organic matter (MAOM, the heavy soil component separated by density fractionation) generally contains more C and persists in soils longer than free or occluded light material. Yet while some MAOM persists for centuries, other forms of MAOM turnover on annual to decadal timescales. In order to predict the response of soil C pools to changes in inputs and decomposition rates under climate change we must be able to distinguish the relatively labile component of this mineral-associated soil C pool from the relatively passive component.We collected samples in 2001, 2009, and 2019 from 9 sites along a combined gradient of parent material (granite, andesite, basalt) and mean annual temperature (MAT) (6.7°C, 9.1°C, 13.6°C). Mean annual precipitation was similar across all sites (80-130 mm yr-1). We measured the radiocarbon (14C) values of bulk soils, respired CO2, density fractions, and thermal fractions. We used selective dissolution and quantitative x-ray diffraction to determine mineral assemblages. We modeled turnover rates for bulk soil and MAOM using SoilR with C stocks and 14C data as constraints.Using the difference between respired 14C and bulk 14C as a proxy for soil C protection, we observed a strong negative correlation with poorly crystalline mineral content at all time points, suggesting these secondary minerals play a key role in protecting soil C from decomposition. Poorly crystalline mineral content was greatest in the andesite soils, followed by basalt, then granite soils. Temperature also affected poorly crystalline mineral content, with greater abundances in sites with MAT of 9.1°C than in warmer or colder sites across lithologies.Mineral assemblages were also related to the change in bulk 14C over time. Between 2001 and 2019, bulk 14C declined 4-5‰ yr-1 faster (p < 0.05) in granite and basalt versus andesite soils at the 9.1°C MAT sites. Within the andesite soils, bulk 14C declined 6‰ yr-1 faster at 13.6°C than 9.1°C (p < 0.05). Overall, slower rates of bulk 14C change were correlated with older mean C ages in the models. When compared within each MAT regime, our models revealed andesite soils to have older mean soil C ages than the basalt or granite soils. Respiration fluxes from these soils were more enriched in 14C than the fluxes from the basaltic or granitic soils, and were also enriched relative to the atmosphere. This indicates active decomposition of older decadally cycling soil C derived from mid-20th century nuclear weapons testing in the andesitic soils but not in the basalt or granite soils.Measurements of 14C in MAOM and associated thermal fractions (currently underway) will enable us to quantify the relative amounts of MAOM cycling at time scales relevant for improving near-term C budgets not only at our sites, but with implications for improving future models of soil C cycling at broader scales as well.

In order to understand the coupling of land ecosystem carbon (C), nitrogen (N), and phosphorous (P) cycles, it is necessary to understand microbial element use efficiencies (C, N and P) of soil organic matter (SOM) decomposition. While important controls of those efficiencies by microbial community adaptations have been shown at the scale of a soil pore, an abstract simplified representation of community adaptations is needed at the ecosystem scale. The conceptual soil enzyme allocation model (SEAM) explicitly models community adaptation strategies of resource allocation to extracellular enzymes and enzyme limitations on SOM decomposition. It thus provides a scaling from representing several microbial functional groups to a single holistic microbial community. The model has been further abstracted using quasi-steady-state assumption for extracellular enzyme pools to the SESAM model. While initially, P optimality considerations have been treated analogue to N, we found with simulating a sequence of sites with a P availability gradient that model extensions were required for P. Here we discuss effects of explicitly considering two assumptions on SOM dynamics: (1) oxidative enzymes can acquire P from SOM without necessary stoichiometric decomposition of C and N, and (2) for the case where P is limiting, in addition to P cost, also the C and N cost of enzyme production are important for optimality. We found that neglecting these two assumptions did not significantly change system behavior and predictions in the case where P was not limiting soil microbes. However, it changed model predictions of ecosystem-scale SOM dynamics for the case where P started to become limiting.This modeling study links knowledge of constraints at soil microbial scale to SOM dynamics at ecosystem scale. It highlights the important role of adaptability of soil microbial communities to resource supply and stoichiometry for the development of SOM stocks and nutrient availability.

Root dynamics and allocation belowground are a major uncertainty in ecosystem studies because roots are hard to measure in comparison to leaves, which can be assessed at fine timescales using a variety of remote sensing approaches. We built an automated minirhizotron system capable of taking root images on a sub-daily scale and analyzed all high frequency images from this with a neural network approach. We pair this with a daily series of above-ground vegetation indexes of the same plants from standardized ‘phenocam’ digital camera methods. Here we will demonstrate, from a mesocosm experiment that 1) in a mixed species mesocosm, root and shoot production (i.e. rate of change of indexes) as not synchronized on short (multi-day) timescales and 2) root growth rate was more important than overall biomass and leaf growth rate in determining variability in soil CO2 efflux. Hence this efflux was likely driven by root growth respiration rather than maintenance respiration. We also show the first results from applying similar principles to ecosystem measurements.

The role of soil moisture for organic matter decomposition rates remains poorly understood and underrepresented in Earth System Models (ESMs). We apply the Dual Arrhenius Michaelis‐Menten (DAMM) model to a selection of ESM soil temperature and moisture outputs to investigate their effects on decomposition rates, at different soil depths, for a historical period and a future climate period. Our key finding is that the inclusion of soil moisture controls has diverging effects on both the speed and direction of projected decomposition rates (up to ±20%), compared to a temperature‐only approach. In the top soil, the majority of these changes is driven by substrate availability. In deeper soil layers, oxygen availability plays a relatively stronger role. Owing to these different moisture controls along the soil depth, our study highlights the need for depth‐resolved inclusion of soil moisture effects on decomposition rates within ESMs. This is particularly important for C‐rich soils in regions which may be subject to strong future warming and vertically opposing moisture changes, such as the peat soils at northern high latitudes., Plain Language Summary: Soils contain a lot of carbon (C). Earth System Models (ESMs) predict that the amount of C released from soils into the atmosphere as CO2 will increase in response to increased warming and microbial activity. Soil moisture also controls microbial C decomposition, but most ESMs do not yet describe this process very well. In this study we apply a simple equation to different ESMs, to see how both temperature and soil moisture change microbial decomposition under future climate. First, we show that the speed of C released into the atmosphere changes when we include soil moisture changes, compared to what is expected due to warming alone. Second, we found that the future speed at which carbon that can be decomposed in the topsoil mainly depends on how much carbon microbes have access to, but that in the deeper soil this process becomes much more affected by the absence/presence of oxygen. Including these soil moisture interactions in ESMs for different soil depths is important to predict whether soils will store more or less C in the future. Our findings are particularly relevant for high latitude soils which store large amounts of C, will warm fast, and experience frequent (re)wetting and drying., Key Points: Considering soil moisture effects can change modeled decomposition rates by up to ±20% compared to considering only temperature effects. The majority of these changes are driven by substrate availability, in particular in the top soil. In the subsoil, oxygen availability becomes an increasingly important factor., Norwegian Research Council, https://doi.org/10.5281/zenodo.5654554

Soil mineral characteristics have been shown to play a dominant role in stabilizing soil organic matter over medium to long term timescales. However, while great strides have been made (Kleber et al, 2021) toward understanding organic matter stabilization processes, there remain uncertainties about the chemistry, time scales, and age of carbon that is stored on soil minerals. We applied modern thermal analysis methods to investigate soil mineral effects on the thermal stability, chemical composition, and age distribution of soil organic matter. We selected subsoil mineral fractions that contained a single dominant stabilizing pathway (e.g. 2:1 clays, iron oxides, short-range order minerals, crystalline minerals) to isolate effects of individual minerals. We paired thermal fractionation with pyrolysis-GC/MS to describe the relationships of SOM age and chemical composition. Early results show that while certain minerals display heterogeneous thermal stabilities, single mineralogies contain generally narrow age ranges. In addition, organic matter chemistry associated with diverse minerals varies widely and indicates that certain minerals provide higher stability to complex, energy-rich molecules. Associated with this work, we also present novel continuous SOM radiocarbon distributions from thermal fractionation., EGUsphere

Grassland management intensity influences nutrient cycling both directly, by changing nutrient inputs and outputs from the ecosystem, and indirectly, by altering the nutrient content, and the diversity and functional composition of plant and microbial communities. However, the relative importance of these direct and indirect processes for the leaching of multiple nutrients is poorly studied. We measured the annual leaching of nitrate, ammonium, phosphate and sulphate at a depth of 10 cm in 150 temperate managed grasslands using a resin method. Using Structural Equation Modeling, we distinguished between various direct and indirect effects of management intensity (i.e. grazing and fertilization) on nutrient leaching. We found that management intensity was positively associated with nitrate, ammonium and phosphate leaching risk both directly (i.e. via increased nutrient inputs) and indirectly, by changing the stoichiometry of soils, plants and microbes. In contrast, sulphate leaching risk was negatively associated with management intensity, presumably due to increased outputs with mowing and grazing. In addition, management intensification shifted plant communities towards an exploitative functional composition (characterized by high tissue turnover rates) and, thus, further promoted the leaching risk of inorganic nitrogen. Plant species richness was associated with lower inorganic nitrogen leaching risk, but most of its effects were mediated by stoichiometry and plant community functional traits. Maintaining and restoring diverse plant communities may therefore mitigate the increased leaching risk that management intensity imposes upon grasslands., Nutrient Cycling in Agroecosystems, 123 (3), ISSN:1385-1314, ISSN:1573-0867

The impact of local biodiversity loss on ecosystem functioning is well established, but the role of larger-scale biodiversity dynamics in the delivery of ecosystem services remains poorly understood. Here we address this gap using a comprehensive dataset describing the supply of 16 cultural, regulating and provisioning ecosystem services in 150 European agricultural grassland plots, and detailed multi-scale data on land use and plant diversity. After controlling for land-use and abiotic factors, we show that both plot-level and surrounding plant diversity play an important role in the supply of cultural and aboveground regulating ecosystem services. In contrast, provisioning and belowground regulating ecosystem services are more strongly driven by field-level management and abiotic factors. Structural equation models revealed that surrounding plant diversity promotes ecosystem services both directly, probably by fostering the spill-over of ecosystem service providers from surrounding areas, and indirectly, by maintaining plot-level diversity. By influencing the ecosystem services that local stakeholders prioritized, biodiversity at different scales was also shown to positively influence a wide range of stakeholder groups. These results provide a comprehensive picture of which ecosystem services rely most strongly on biodiversity, and the respective scales of biodiversity that drive these services. This key information is required for the upscaling of biodiversity–ecosystem service relationships, and the informed management of biodiversity within agricultural landscapes.

The active bacterial rhizobiomes and root exudate profiles of phytometers of six plant species growing in central European temperate grassland communities were investigated in three regions located up to 700 km apart, across diverse edaphic conditions and along a strong land use gradient. The recruitment process from bulk soil communities was identified as the major direct driver of the composition of active rhizosphere bacterial communities. Unexpectedly, the effect of soil properties, particularly soil texture, water content, and soil type, strongly dominated over plant properties and the composition of polar root exudates of the primary metabolism. While plant species-specific selection of bacteria was minor, the RNA-based composition of active rhizosphere bacteria substantially differed between rhizosphere and bulk soil. Although other variables could additionally be responsible for the consistent enrichment of particular bacteria in the rhizosphere, distinct bacterial OTUs were linked to the presence of specific polar root exudates independent of individual plant species. Our study also identified numerous previously unknown taxa that are correlated with rhizosphere dynamics and hence represent suitable targets for future manipulations of the plant rhizobiome.

Land‐use intensification drives changes in microbial communities and the soil functions they regulate, but the mechanisms underlying these changes are poorly understood as land use can affect soil communities both directly (e.g. via changes in soil fertility) and indirectly (e.g. via changes in plant inputs). The speed of microbial responses is also poorly understood. For instance, whether it is long‐term legacies or short‐term changes in land‐use intensity that drive changes in microbial communities. To address these topics, we measured multiple microbial functions, bacterial and fungal biomass and abiotic soil properties at two time intervals 3 years apart. This was performed in 150 grassland sites differing greatly in management intensity across three German regions. Observed changes in microbial soil properties were related to both long‐term means and short‐term changes in: abiotic soil properties, land‐use intensity, community abundance‐weighted means of plant functional traits and plant biomass properties in regression and structural equation models. Plant traits, particularly leaf phosphorus, and soil pH were the best predictors of change in soil microbial function, as well as fungal and bacterial biomass, while land‐use intensity showed weaker effects. Indirect legacy effects, in which microbial change was explained by the effects of long‐term land‐use intensity on plant traits, were important, thus indicating a time lag between plant community and microbial change. Whenever the effects of short‐term changes in land‐use intensity were present, they acted directly on soil microorganisms. Synthesis. The results provide new evidence that soil communities and their functioning respond to short‐term changes in land‐use intensity, but that both rapid and longer time‐scale responses to changes in plant functional traits are at least of equal importance. This suggests that management which shapes plant communities may be an effective means of managing soil communities and the functions and services they provide.

Functionally, ectomycorrhizal (ECM) and saprotrophic (SAP) fungi belong to different guilds, and they play contrasting roles in forest ecosystem C-cycling. SAP fungi acquire C by degrading the soil organic material, which precipitates massive CO2 release, whereas, as plant symbionts, ECM fungi receive C from plants representing a channel of recently assimilated C to the soil. In this study, we aim to measure the amounts and identify the drivers of ECM and SAP fungal biomass in temperate forest topsoil. To this end, we measured ECM and SAP fungal biomass in mineral topsoils (0–12 cm depth) of different forest types (pure European beech, pure conifers, and mixed European beech with other broadleaf trees or conifers) in a range of about 800 km across Germany; moreover, we conducted multi-model inference analyses using variables for forest and vegetation, nutritive resources from soil and roots, and soil conditions as potential drivers of fungal biomass. Total fungal biomass ranged from 2.4 ± 0.3 mg g−1 (soil dry weight) in pure European beech to 5.2 ± 0.8 mg g−1 in pure conifer forests. Forest type, particularly the conifer presence, had a strong effect on SAP biomass, which ranged from a mean value of 1.5 ± 0.1 mg g−1 in broadleaf to 3.3 ± 0.6 mg g−1 in conifer forests. The European beech forests had the lowest ECM fungal biomass (1.1 ± 0.3 mg g−1), but in mixtures with other broadleaf species, ECM biomass had the highest value (2.3 ± 0.2 mg g−1) among other forest types. Resources from soil and roots such as N and C concentrations or C:N ratios were the most influential variables for both SAP and ECM biomass. Furthermore, SAP biomass were driven by factors related to forest structure and vegetation, whereas ECM biomass was mainly influenced by factors related to soil conditions, such as soil temperature, moisture, and pH. Our results show that we need to consider a complex of factors differentially affecting biomass of soil fungal functional groups and highlight the potential of forest management to control forest C-storage and the consequences of changes in soil fungal biomass.