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Soil microorganisms rely on coupled fluxes of carbon and energy from the decomposition of organic substrates to fuel their maintenance and growth requirements. This complex coupling depends on environmental conditions as well as the specific metabolic reactions carried out by the microbial community, but our understanding of the principles governing these dynamics is still limited. The joint analysis of both matter and energy fluxes and in particular the linkage of the microbial carbon and energy use efficiencies (CUE and EUE) during substrate turnover have the potential to elucidate the underlying metabolic pathways. However, such evaluations remain rare.In this study, we present measurements of heat and CO2 release from soil after batch input of glucose along with estimates of microbial biomass and community composition. The results reveal a temporal variation in the ratio of heat to CO2 release (Calorespirometric Ratio, CR) that is inconsistent with simple aerobic decomposition of the substrate. In addition, we find that the dynamics are dominated by the growth of Firmicutes, whose relative abundance increases from 2 percent of initial biomass to almost 50 percent over the course of the incubation.To interpret these findings, we developed a dynamic model of carbon and energy fluxes during growth on glucose. The model simulates aerobic respiration as well as anaerobic fermentation to lactate and acetate depending on the time-varying availability of O2 and accounts for activation of the microbial population after initial dormancy. Model simulations capture the complex experimental CR pattern and suggest a gradual depletion of available O2 and a concurrent shift to anaerobic pathways as the main driver of the dynamics. Given the widespread adaptation to anaerobic conditions found in prevalent members of the Firmicutes, this interpretation is consistent with the observed dominance of the phylum. Notably, model variants of lower complexity that do not include fermentation or increasing microbial activity fail to appropriately reproduce the measured CR and biomass.These results highlight the potential of the joint analysis of matter and energy fluxes in a combined experimental and modeling approach. The evolution of CR over time revealed the presence of complex dynamics even in the simple case of glucose-amended soil samples and provided constraints on the metabolic processes behind those dynamics that align with the available biomass and community composition estimates. By considering the balance of multiple metabolic pathways as well as the concept of microbial activity, our findings offer a more detailed description of temporal microbial carbon and energy use that goes beyond the assumption of constant CUE and EUE. Such an approach will be essential for the investigation of more complicated transformations of organic matter in soil.

Mountains occupy almost a quarter of the land area and store significant pools of soil organic matter (SOM), which is a potential source of atmospheric CO2 under warming climate. However, carbon fluxes in mountain areas with high environmental heterogeneity remain poorly understood, in particular regarding the spatial variability of soil respiration (RS). The study was conducted on the northeastern slope of the Northwest Caucasus Mountains (1260-2480 m a.s.l.; Russia) that crossed five vegetation belts (i.e., mixed, fir and deciduous forests, subalpine and alpine meadows). RS was measured simultaneously (at 10 a.m. on 11 August 2018) across five vegetation belts (at 12 randomly distributed points per belt; totally n = 60) using the closed static chamber technique. As potential drivers of RS spatial variability, soil physico-chemical (temperature, moisture, total and dissolved C and N contents, C:N ratio, pH), soil microbial (microbial biomass C content, basal respiration, enzymatic activities: β-glucosidase, chitinase and leucine aminopeptidase) and vegetation properties (grasses projective cover, its species richness, Shannon-Wiener diversity index, abundance of graminoids and forbs) were assessed. The RS rate ranged from 1.3-12.7 µmol CO2 m-1 s-1, with average values of 3.7 and 7.3 µmol CO2 m-1 s-1 for forests and grasslands respectively. Stepwise regression and subsequent path analysis showed that key driver of RS spatial variability in forests was temperature-sensitive soil chitinase activity (explained variance 50%), while in grasslands it was graminoid abundance (explained variance 27%). The forest soils are mostly limited in N, therefore RS variability depends largely on SOM-derived CO2 sources, i.e. activity of the N-acquiring enzyme. In the grasslands, extensive network of fine roots and the associated considerable contribution of root-derived respiration to Rs, makes the flux more sensitive to vegetation composition and associated phenology and C allocation patterns. Thus, soil N availability and differences in plant cover play a crucial role in regulation of RS spatial patterns in mountains ecosystems.This study was financially supported by Russian Science Foundation, No 22-74-10124.

In mountain areas, one of the noticeable results of modern climate change is rapid shift of treelines to subalpine and alpine meadows. Such vegetation shifts is associated with a change in quality of the plant residues entering the soils, which in turn can affect the mineralization activity (basal respiration) and functional diversity of the soil microbial community. Therefore, the study was aimed at assessing the soil microbial (basal respiration and functional diversity) and chemical (C, N, C/N, pH) properties (0-10 cm) along the reserved and grazed forest-meadow transects of the Northwestern Caucasus (Karachay-Cherkess Republic), as well as evaluating an effect of vegetation type and land use on variation of these soil properties. It was found that the C and N contents (for both land usees), pH and basal respiration (reserved slope) significantly increase from forest to meadow soils. In contrary, the microbial functional diversity decreased from forest to meadow soils, which might be due to less diverse organic compounds entering the soil only with grass residues than their combination with forest litter. Two-way ANOVA showed that soil microbial functional diversity, pH, C and N along the studied forest-meadow transects was mostly associated with vegetation type (1439 % of the explained variation), and C/N and basal respiration - with land use (3336 % of the explained variation). Thus, a land use change will have a more significant effect on the mineralization activity of soil microbial community than a treeline shifts.

Soil organic matter (SOM) turnover models predict changes in SOM due to management and environmental factors. Their initialization remains challenging as partitioning of SOM into different hypothetical pools is intrinsically linked to model assumptions. Diffuse reflectance mid-infrared Fourier transform spectroscopy (DRIFTS) provides information on SOM quality and could yield a measurable pool-partitioning proxy for SOM. This study tested DRIFTS-derived SOM pool partitioning using the Daisy model. The DRIFTS stability index (DSI) of bulk soil samples was defined as the ratio of the area below the aliphatic absorption band (2930 cm−1) to the area below the aromatic–carboxylate absorption band (1620 cm−1). For pool partitioning, the DSI (2930 cm−1 ∕ 1620 cm−1) was set equal to the ratio of fast-cycling ∕ slow-cycling SOM. Performance was tested by simulating long-term bare fallow plots from the Bad Lauchstädt extreme farmyard manure experiment in Germany (Chernozem, 25 years), the Ultuna continuous soil organic matter field experiment in Sweden (Cambisol, 50 years), and 7 year duration bare fallow plots from the Kraichgau and Swabian Jura regions in southwest Germany (Luvisols). All experiments were at sites that were agricultural fields for centuries before fallow establishment, so classical theory would suggest that a steady state can be assumed for initializing SOM pools. Hence, steady-state and DSI initializations were compared, using two published parameter sets that differed in turnover rates and humification efficiency. Initialization using the DSI significantly reduced Daisy model error for total soil organic carbon and microbial carbon in cases where assuming a steady state had poor model performance. This was irrespective of the parameter set, but faster turnover performed better for all sites except for Bad Lauchstädt. These results suggest that soils, although under long-term agricultural use, were not necessarily at a steady state. In a next step, Bayesian-calibration-inferred best-fitting turnover rates for Daisy using the DSI were evaluated for each individual site or for all sites combined. Two approaches significantly reduced parameter uncertainty and equifinality in Bayesian calibrations: (1) adding physicochemical meaning with the DSI (for humification efficiency and slow SOM turnover) and (2) combining all sites (for all parameters). Individual-site-derived turnover rates were strongly site specific. The Bayesian calibration combining all sites suggested a potential for rapid SOM loss with 95 % credibility intervals for the slow SOM pools' half-life being 278 to 1095 years (highest probability density at 426 years). The credibility intervals of this study were consistent with several recently published Bayesian calibrations of similar two-pool SOM models, i.e., with turnover rates being faster than earlier model calibrations suggested; hence they likely underestimated potential SOM losses.

Nitrogen (N) lost from the agricultural field as leachate and nitrous oxide (N2O) gas causes water pollution, accelerates global warming and decreases agricultural N use efficiency. Soil amendments with straw and nitrification inhibitors are used to combat these problems by increasing microbial N immobilization and suppressing nitrification, respectively. The potential N competition between soil microorganisms and subsequent crops under the incorporation of pre-crop straw can be moderated by seasonal temperature variation, but this interfering factor is insufficiently studied. A 99-days mesocosm experiment that simulated the seasonal temperature variation was conducted, to investigate the effects of wheat straw amendment (WSA) and nitrification inhibitor (NI) on the competition for soil N between soil microbes and winter barley under three N fertilization levels (N0 as control, N1 as low N fertilizer, N2 as high N fertilizer), and N lost from soil as N2O and leachate. Strong mineralization was detected after the cooling-warming cycle, which happens in early spring frequently in Germany. Soil NH4+ of all treatments were increased by 34-138 % and soil NO3− of N2 levels were increased by 42-133 % during this process, providing mineral N for barley growth but also imposing the risk of N losses. Straw incorporation stimulated immobilization of N by soil microorganisms, increased soil microbial biomass C and N by 45-123 % till the end of experiment, thus decreased the total N lost by 41 % on average by decreasing N leaching (43-91 %), NI mitigated N2O emission by 40 % in N2 levels, the combination of WSA and NI could mitigate N losses and global warming. However, the immobilized N under WSA was not remineralized timely during barley growth, therefore, barley shoot biomass (by 23-34 %) and N (by 28-46 %) decreased in N0 and N1 fertilizer levels, the shoot nitrogen use efficiency (NUE) decreased in N1 (by 53 %) and N2 (by 30 %) fertilizer levels. Considering the strong (long term) N immobilization induced by straw, we suggest applying straw and N fertilizer separately to avoid N competition between soil microorganisms and crops.

Large‐scale conversion of natural forest to rubber plantations has taken place for decades in Southeast Asia, help to make it a deforestation hot spot. Besides negative changes in biodiversity, ecosystem water, and carbon budgets, converting forests to plantations often reduced CH₄ uptake by soils. The latter process, which might be partly responsible for resumed increase in the growth rate of CH₄ atmospheric concentrations since 2006, has not been adequately investigated. We measured soil surface CH₄ fluxes during 2014 and 2015 in natural forests and rubber plantations of different age and soil textures in Xishuangbanna, Southwest China—a representative area for this type of land‐use change. Natural forest soils were stronger CH₄ sinks than rubber soils, with annual CH₄ fluxes of −2.41 ± 0.28 and −1.01 ± 0.23 kg C ha⁻¹ yr⁻¹, respectively. Water‐filled pore space was the main factor explaining the differences between natural forests and rubber plantations, even reverting rubber soils temporarily from CH₄ sink into a methane source during the rainy season in older plantations. Soil nitrate content was often lower under rubber plantations. Added as a model covariate, this factor improved explanation power of the CH₄ flux—water‐filled pore space regression. Although soils under rubber plantation were more clayey than soils under natural forest, this was not the decisive factor driving higher soil moisture and lower CH₄ uptake in rubber soils. Thus, the conversion of forests into rubber plantations exerts a negative impact on the CH₄ balance in the tropics and likely contributes to global climate.

Para rubber (Hevea brasiliensis Mull. Arg) plantations have expanded into regions with sub-optimal growth conditions: distinct dry seasons and temperatures cooler than in humid tropics. The impact of these new marginal environments and future climate change on rubber tree development and latex yield is largely unknown. This hampers reliable prediction of farmers’ revenues and extent of carbon sequestration at landscape level. To improve our understanding of rubber trees response to planting at high altitudes and associated increase in planting densities, we applied the process-based Land Use Change Impact Assessment tool (LUCIA). It was calibrated with detailed ground survey data from Xishuangbanna, southwest China to model tree biomass development and latex yield in rubber plantations at the tree, plot and landscape level. Plantations were analyzed at 600 trees ha−1) were tested. Four greenhouse gas emission scenarios, with Representative Concentration Pathways (RCP) ranging from the lowest RCP 2.6 to the highest emission scenario RCP 8.5, were used to test rubber tree response to climate change. During a 40-year rotation under current climate, lowland rubber plantations grew faster and had larger latex yields than highland rubber. The average biomass of lowland rubber was 9% and 18% higher than those of highland rubber for aboveground and belowground biomass, respectively. High planting density rubber plantations showed 5% and 4% higher above ground biomass than those at low- and medium-planting density, but simulations suggest that the cumulative latex production decreased strongly by 26% and 14% respectively. The results of the RCP 8.5 climate change scenario suggested that during 40 years simulation mean total biomass and cumulative latex yield of highland rubber (per tree) increased by 28% and 48%, while lowland rubber increased by 8% and 10% respectively when compared to the baseline. Other rubber cultivation regions could also benefit from this modelling approach that helps in optimization of carbon stock and latex production in rubber-based system. The results could help in development of future climate change adaption and mitigation strategies.

The role of weeds in soil conservation in agroforestry systems has been largely ignored. We used the Land Use Change Impact Assessment (LUCIA) model to simulate the effects of weed management on erosion in rubber plantations (Hevea brasiliensis Muell. Arg). In order to quantify the impact of a dynamic, spatially explicit multi-layer plantation structure on erosion processes in agroforestry systems, we updated LUCIA's erosion module. Its new version simulates soil detachment due to rainfall and runoff, considering the separate effects of the tree canopy and surface cover on soil erosion. The updated LUCIA model was calibrated and validated based on an established rubber plantation experiment in Xishuangbanna, Southwest China, to evaluate the impact of different weeding strategies on soil loss. The model successfully represented the impact of the dynamic multi-layer structure on erosion and was able to predict well the effects of weed management on soil loss and runoff at the test site over 1 year, with a modelling efficiency (EF) of 0.5–0.96 and R2 of 0.64–0.92. Subsequently, we validated the ability of the model to simulate surface cover changes under rubber plantations of different age (up to 40 years). Simulation outputs for 4-, 12- and 18-year-old rubber plantations revealed satisfying to good results. However, the predicted change in surface cover for old rubber plantations (25- and 36-year) failed to meet the field trends. The model predicted the greatest erosion in the year when the rubber canopy started to close. During this period, weed growth was limited by light, while litter input from rubber was insufficient to provide good soil cover. Four weeding strategies (“clean-weeding”, “twice-weeding”, “once-weeding” and “no-weeding”) were designed for scenario simulations. Based on the results of 20-year runs, we concluded that “once-weeding” and “no-weeding” both efficiently minimized soil loss during one rotation length. A high degree of surface and weed cover (over 95% and 60%) under “no-weeding” makes this management strategy with dense undergrowth hardly acceptable by local farmers due to reduced tree accessibility for tapping and increased potential danger through poisonous caterpillars. “Once-weeding”, on the other hand, controlled overgrowth of understory vegetation by keeping weed cover below 50%. We therefore suggest “once-weeding” as an improved herbicide management strategy in rubber plantations, to meet ecological system service maintenance and to facilitate adoption in practice.

Petroleum pollution of soils is a major environmental problem. Soil microorganisms can decompose a significant fraction of petroleum hydrocarbons in soil at low concentrations (1–5%). This characteristic can be used for soil remediation after oil pollution. Microbial community dynamics and functions are well studied in cases of moderate petroleum pollution, while cases with heavy soil pollution have received much less attention. We studied bacterial and fungal successions in three different soils with high petroleum contents (6 and 25%) in a laboratory experiment. The proportion of aliphatic and aromatic compounds decreased by 4–7% in samples with 6% pollution after 120 days of incubation but remained unchanged in samples with 25% hydrocarbons. The composition of the microbial community changed significantly in all cases. Oil pollution led to an increase in the relative abundance of bacteria such as Actinobacteria and the candidate TM7 phylum (Saccaribacteria) and to a decrease in that of Bacteroidetes. The gene abundance (number of OTUs) of oil-degrading bacteria (Rhodococcus sp., candidate class TM7-3 representative) became dominant in all soil samples, irrespective of the petroleum pollution level and soil type. The fungal communities in unpolluted soil samples differed more significantly than the bacterial communities. Nonmetric multidimensional scaling revealed that in the polluted soil, successions of fungal communities differed between soils, in contrast to bacterial communities. However, these successions showed similar trends: fungi capable of lignin and cellulose decomposition, e.g., from the genera Fusarium and Mortierella, were dominant during the incubation period.

Soil organic carbon (SOC) losses under a changing climate are driven by the temperature sensitivity of SOC mineralization (usually expressed as Q10, the multiplier of activity with 10 °C temperature increase). The activation energy theory (AET) suggests that, due to higher activation energies, the more complex the carbon, the higher is mineralization Q10. However, studies on Q10 have been inconsistent with regard to AET. Measurements of potential soil enzymes activity Q10 even contradicted AET: Phenoloxidase (representing complex carbon) had consistently lower Q10 than the more labile xylanase and glucosidase. This study used two approaches of examining Q10 in SOC modeling: 1) Bayesian calibration (BC) and 2) using different measured enzyme Q10 as proxies for mineralization Q10 of different SOC pools. The SOC model was DAISY (S. Hansen et al., 2012). BC informed Q10 by field measured data, while the second approach tested if directly using enzyme Q10 (of phenoloxidase, glucosidase and xylanase) for DAISY pools improved simulation results. Both approaches used the temperature sensitive measurements of CO2 evolution and soil microbial biomass. The measured enzyme Q10 were from field manipulation experiments with bare fallow and vegetated plots in the two regions of Kraichgau and Swabian Jura in Southwest Germany. The enzyme-derived Q10 were used for modelling those fields and furthermore for in‑situ litterbag decomposition experiments at 20 sites in the same region. Two further laboratory experiments with temperature manipulation were included: an incubation of the field residues into soil and an incubation of bare soil from the start and year 50 of a long duration bare fallow (from Ultuna). The BC made use of CO2 and microbial data to inform about the range of Q10 of different carbon pools for the individual experiments and combined data.The BC of the residue incubation experiment constrained Q10 for metabolic (~3) and structural litter (~2). Estimated 95% credibility intervals did not overlap. The BC for Ultuna could constrain the slow and fast SOC pool with Q10 ~2.8 and ~3, respectively, but credibility intervals of both pools overlapped. The Q10 of field experiments, which had most abundant data, could not be constrained by BC, probably because their annual temparature variability was too low. However, the model errors of the field experiment could be reduced by the second approach, when the Q10 of phenoloxidase was used for to the structural litter pool as well as for the fast and slow SOC pools. Thus regional enzyme Q10 improved the model fit but only for regional simulations. Therefore, they could be useful proxies when natural temperature range is too small to inform temperature sensitivity by BC. Any trends found in this study contradicted AET, both from measured enzymes and BC of the incubation experiments. This calls for alternative Q10 hypotheses and the need for individual Q10 values for different SOC pool rather than a general one. BC approaches would benefit from a wider temperature range of field experiments and understanding what causes variable enzyme Q10 could help to improve future SOC models.

Unregulated surface gold mining contributes to deforestation and land degradation in Ghana and Burkina Faso (West Africa). In addition, small-scale gold mining uses a technology for gold amalgamation that pollutes the environment with mercury (Hg) and adversely affects human health. In the framework of the recently started Mercury-AMF-project we aim to reduce the environmental damage caused by mercury used in gold mining in Ghana and Burkina Faso. This will be achieved by developing and implementing novel arbuscular mycorrhizal fungi (AMF) - plant systems as a strategy to reclaim mercury-contaminated sites. The cultivation of pioneer plants on contaminated soils can reduce the mercury pollution. Symbiotic mycorrhizal associations of those plants may strengthen the potential to remediate Hg-contaminated soils.The implementation of the project is based on the following specific activities:Characterization of the arbuscular mycorrhizal fungus (AMF) candidates in the soils of Ghana and Burkina Faso; Development of prototype AMF plant systems as an innovative strategy for the remediation of Hg-contaminated sites; Testing of mycophytoextraction methods to reduce the Hg soil concentration below threshold values; Examination of the return of Hg-contaminated sites to agricultural use and the promotion of sustainable land management in gold mining regions; Set-up of modelling approaches for the efficiency of mycophytoextraction methods and Hg plant uptake; Exploration and communication of institutional and socio-economic framework conditions for the introduction of AMF plant systems. During the first year of the project soil and plant sampling campaigns in Ghana and Burkina Faso were organised for screening the AMF-candidates capable for symbiosis with local plant species and tolerant to the mercury pollution. Clarification of possible mechanisms of phytoremediation is the next essential component of the research: several pathways of decontamination are possible including phytostabilization, phytovolatilization and phytoextraction. Based on the first results, field experimental trials with new AMF-plant systems will be established.

Due to the spatial variability of soil resources in rapidly changing landscapes, such as rubber expansion areas in mountainous South East Asia, landscape based soil organic carbon (SOC) stock assessments need new approaches to obtain cost effective high-resolution soil maps. 3D modelling presents the opportunity to model changes of soil properties with soil depth and in space in one single model. While most 3D models make use of spatial autocorrelation to create soil maps, it might be feasible for upscaling to neglect the spatial autocorrelation and only model autocorrelation within the soil profiles. We propose a “mixed model over continuous depth” (MMCD), which uses a linear and quadratic term to model changes of soil properties with depth and predicts the spatial distribution of soil properties at the landscape level. As the study area of 43 km2 in South West China was subject to multiple constraints such as sparse road networks, steep terrain, and poor infrastructure, we applied the cost-constrained conditioned Latin hypercube sampling (CCLHS) scheme for soil sampling at 120 locations to a depth of 1 m. The MMCD provides information on the most important drivers of selected soil properties, and their relative importance. In this study, SOC was strongly linked to an interaction of elevation with mean horizon depth (p

Input of labile carbon may accelerate the decomposition of existing soil organic matter (priming effect), with the priming intensity depending on changes in soil nitrogen availability after permafrost thaw. However, experimental evidence for the linkage between the priming effect and post-thaw nitrogen availability is unavailable. Here we test the hypothesis that elevated nitrogen availability after permafrost collapse inhibits the priming effect by increasing microbial metabolic efficiency based on a combination of thermokarst-induced natural nitrogen gradient and nitrogen addition experiment. We find a negative correlation between the priming intensity and soil total dissolved nitrogen concentration along the thaw sequence. The negative effect is confirmed by the reduced priming effect after nitrogen addition. In contrast to the prevailing view, this nitrogen-regulated priming intensity is independent of extracellular enzyme activities but associated with microbial metabolic efficiency. These findings demonstrate that post-thaw nitrogen availability regulates topsoil carbon dynamics through its modification of microbial metabolic efficiency., Soil nitrogen availability may alter carbon dynamics after permafrost thaw, but experimental evidence for this carbon-nitrogen interaction is still lacking. Here the authors show that elevated post-thaw nitrogen availability inhibits soil carbon release through its enhancement in microbial metabolic efficiency.

Rubber (Hevea brasiliensis) plantations have a lifespan in the range of 25–40 years. We aimed at assessing soil losses in rubber plantations of different ages (4, 12, 18, 25 and 36 years old) and r...

An altitudinal gradient in the mountains constitutes a unique ‘open-lab’ to examine environmental hypotheses and analyse the expected effects of global warming. The distribution of carbon (C)-, nitrogen (N)-, and phosphorus (P)-acquiring enzyme activity, microbial catabolic activity as represented by a community-level physiological profile (CLPP), and microbial functional diversity (HCLPP) within mountainous ecosystems consisting of mixed, fir and deciduous forests, as well as subalpine and alpine meadows (1260–2480 m a.s.l., Mt. Tkachiha, the Northwest Caucasus, Russia) has been studied. Concerning potential drivers, vegetation (plant projective cover, plant functional group composition, plant richness and diversity) and edaphic (soil nutrients: total and available C and N, total P, pH, texture, temperature, microbial biomass C) and topographic (elevation, slope, mean annual temperature calculated using biannual monitoring data) properties have been considered. The distribution patterns of the studied hydrolytic enzymes along an altitudinal gradient cannot be explained solely by elevation change and soil nutrient content. The activity of soil leucine aminopeptidase depends on vegetation type and graminoid abundance. β-D-glucosidase activity was mainly driven by the quality of soil organic matter (SOM), demonstrating a significant relation with the soil C:N ratio. The chitinase and phosphatase turned out soil temperature-sensitive enzymes. The CLPP depends on the available N content in the soil. The HCLPP distribution with altitude was driven by available N and forbs abundance represented by the widest spectrum of plant families and species. An altitudinal gradient determines the spread of the vegetation zone. In turn, vegetation properties, such as plant functional group composition, species richness and diversity, play a significant role in the distribution of soil microbial activity along an altitudinal gradient that controls the decomposition of SOM and nutrient cycling. Thus, the significant role of vegetation in the distribution of soil microbial activity across a wide range of natural ecosystems and in consideration of topographic and edaphic factors has been demonstrated.

Expansion of rubber plantations into sub-optimal environments has been a dominating land conversion in continental South-East Asia in the last decade. Regional evaluation of the carbon sequestration potential of rubber trees depends largely on the selection of suitable allometric equations and the biomass-to-carbon conversion factor. Most equations are age-, elevation-, or clone-specific, and their application therefore gives uncertain results at the landscape level with varying age groups, elevation ranges, and clone types. Currently, for rubber-based systems, none of the allometric equations takes environmental factors (e.g. climate, topographic condition, soil properties, and management scheme) into consideration to allow pan-tropical usage. Against this background, 30 rubber trees with a root profile of up to 2 m were destructively harvested and 882 rubber trees were measured non-destructively in 27 plots, covering rotation lengths of 4–35 years, elevation gradients of 621–1127 m, and locally used clone types (GT1, PRIM600, Yunyan77-4) in mountainous South Western China. Allometric equations for aboveground biomass ( AGB ) estimations considering diameter at breast height ( DBH ), tree height ( H ), and wood density were superior to other equations. A simpler model with similar performance ( AGB = 0.0419 DBH 2.316 H 0.478 ) can be used if tree-specific wood density is not available. For belowground biomass ( BGB ) a model using only DBH can provide a robust prediction ( BGB = 0.207 DBH 1.668 ). We also tested goodness of fit for the recently proposed pan-tropical forest model, which includes a bioclimatic factor E , combining indices of temperature and precipitation variability and drought intensity. Prediction of AGB by the model calibrated with the harvested rubber tree biomass and wood density was more accurate than the results produced by the pan-tropical forest model adjusted to local conditions. The relationships between DBH and height and between DBH and biomass were influenced by tapping, therefore biomass and C stock calculations for rubber have to be done using species-specific allometric equations. Based on the analysis of environmental factors acting at the landscape level, we found that above- and belowground carbon stocks were mostly affected by stand age, soil clay content, aspect, and planting density. Increasing planting density to >570 trees per ha according to the regional plantation management strategy had a negative impact on aboveground carbon stock of old rubber plantations. The integration of bioclimatic and regional management factors is a further approach to build widely applicable biomass models for pan-tropical rubber-based systems. The results of this study provide reference for reliable carbon accounting in other rubber-cultivated regions.

Rubber plantations expanded remarkably in South-East Asia, while the impact of this land use change on soil carbon dynamics and greenhouse gases emissions has not been sufficiently understood. We measured monthly soil CO2 fluxes during one year as well as CH4 fluxes during the rainy season in secondary rainforest, 9 and 22 year-old rubber monoculture and 22-year-old rubber-tea intercropping in Xishuangbanna, Southwest China. Our aim was to assess the impact of the land use change on soil carbon fluxes and quantify the factors determining the difference in the carbon fluxes. A linear mixed effect model was used in studying the soil temperature and moisture variation and temperature sensitivity (Q10) of soil respiration. The temporal pattern of soil respiration distinctly differed between sites during the rainy season: rainforest maintained a high soil respiration rate, while soil respiration became suppressed (by up to 69%) during the most moist period in rubber plantations. Rainforest soils thus emitted the highest amount of CO2 with an annual cumulative flux of 8.48 ± 0.71 Mg C ha−1 yr−1, compared to 6.75 ± 0.79, 5.98 ± 0.42 and 5.09 ± 0.47 Mg C ha−1 yr−1 for mature rubber, rubber-tea intercropping, and young rubber, respectively. Additionally, the soil CH4 uptake was stronger in rainforest than in rubber plantations during the wet period. Soil temperature was the main factor explaining the overall seasonal variation of soil respiration. Adding a quadratic soil moisture term into the model accounted for moisture effects, identified moisture tipping points, and improved temperature sensitivity assessment when high soil moisture suppressed soil respiration under rubber. Temperature sensitivity of soil respiration was higher for rainforest soil compared to rubber plantations, Q10 values were 3.1 for rainforest and 1.7, 2.2 and 2.4 for mature rubber, rubber-tea intercropping and young rubber respectively. Converting rainforest to rubber plantations tended to reduce soil CO2 emissions and weakened CH4 uptake especially during the very wet period. The altered condition of soil aeration under converted land appears to have a pronounced impact on processes of carbon fluxes from the soil and thus mitigates the positive feedback of climate change given the large area of cultivated rubber.

The initialization of soil organic matter (SOM) turnover models has been a challenge for decades. Instead of using laborious and error prone size-density fractionation SOM pool partitioning, we propose the inexpensive, rapid, and non destructive Diffuse reflectance mid infrared Fourier transform spectroscopy (DRIFTS) technique on bulk soil samples to gain information on SOM pool partitioning from the spectra. Specifically, the DRIFTS stability index, defined as the ratio of aliphatic C-H (2930 cm−1) to aromatic C=C (1620 cm−1) stretching vibrations, was used to divide SOM into fast and slow cycling pools in the soil organic module of the DAISY model. Long-term bare fallow plots from Bad Lauchstädt (Chernozem, 25 years) and the Ultuna frame trial in Sweden (Cambisol, 50 years) were combined with bare fallow plots of 7 years duration in the Kraichgau and Swabian Jura region in Southwest Germany (Luvisols). All fields had been in agricultural use for centuries before fallow establishment, so classical theory would suggest an initial steady state of SOM, which was hence used to compare the performance of DAISY initializations against the newly established DRIFTS stability index. The test was done using two different published parameter sets (2.7 × 10−6 d−1, 1.4 × 10−4 d−1, 0.1 compared to 4.3 × 10−5 d−1, 1.4 × 10−4 d−1, 0.3 for the turnover rates of slow pool, fast pool and humification efficiency, respectively). The DRIFTS initialization of SOM pools significantly reduced model errors of poor performing model runs assuming steady state, irrespective of the turnover rates used, but the faster turnover parameter set fit better to all sites except Bad Lauchstädt. This suggests that soils under long-term agricultural use were not necessarily at steady state. A Bayesian calibration was applied in a next step to identify the best-fitting turnover rates for the DRIFTS stability index in DAISY, both for each site individually and for a combination of all sites. The two approaches which significantly reduced parameter uncertainty and equifinality were: (1) the addition of the physico-chemically based DRIFTS stability index, and (2) combining several sites into one Bayesian calibration, as derived turnover rates can be strongly site specific. The combination of all four sites showed that SOM is likely lost at relatively fast turnover rates with the 95 % credibility intervals of the slow SOM pools half life ranging from 278 to 1095 years, with 426 years as a value of highest probability density. The credibility intervals of this study were consistent with several recently published Bayesian calibrations of similar SOM models, all turnover rates were considerably faster than earlier models suggested. It is therefore likely that published turnover rates understimate the potential loss of SOM.

Reforestation and agricultural conservation have long been recognized as important in reducing on-site soil loss and off-site sediment export. Quantitative assessment of their effectiveness is critical, and assists cost-benefit analysis and decision-making in land management and landscape planning. We applied a paired watershed approach to monitor 1-year sediment export in two watersheds with forest-dominated (reference) and mosaic (target) land use in the Naban River Watershed National Natural Reserve (NRWNNR) in Xishuangbanna, south-western China. Analysis of land-use change in the target watersheds showed decreasing total forest cover (FC) (from 57% to 47%), but increasing FC in steep areas (from 54% to 59%) from 2007 to 2012. A distributed hydrological model (Land-Use Change Impact Assessment, LUCIA) was well calibrated and validated through field data from the two watersheds. Scenarios were created representing different FCs (from 31% to 83%) and agricultural management (as-usual and conservation). Simulation results quantified the relation between FC and sediment export as a logarithmic or logit model, indicating at least one turning point of FC, beyond which further forest reduction should significantly increase sediment export. This point was identified in the range between 57% and 61% of the target watershed under as-usual management; it was shifted to 47%-53% by conservation agriculture. Compared with the reference (with 83% FC), conservation agriculture was able to almost fully compensate for increased sediment export by forest reduction to 57% in 2007. However, when forest was reduced further to 47% in 2012, sediment export increased significantly. We concluded that total FC was as important as FC in montane watershed management in steep areas; and crop type conversion, such as rubber to maize in this study, and on-site agriculture management affect more to sediment export than agricultural expansion. We recommend conservation agriculture as an efficient tool for reducing sediment export on a watershed scale.

Accurate estimation of microbial carbon use efficiency (CUE) in soil is challenged by a high degree of genetic and environmental variability. Different methods vary in their estimates of soil microbial CUE giving the room to select the optimal method for a specific research task, while integrating different methods could improve our understanding of processes controlling CUE variability. Aiming to estimate CUE during plant residue decomposition in different soils, we applied the conventional C-balance method, single C-cycling enzymatic stoichiometry (SCE-STM) and newly proposed “multi”-C-cycling enzymatic stoichiometry (MCE-STM) methods. The STM approach derives CUE from elemental ratios of microbial biomass, substrate, and activities of C and nutrient (e.g. N) acquiring exoenzymes. The extended MCE-STM is a modification of the SCE-STM method, where we used the sum of three C-cycling enzymatic activities (β-glucosidase (BGL), β-D-cellobiohydrolase (BCL), β-xylosidase (BXL)) as proxy for CUE calculation, instead of using a single C-acquiring enzyme (BGL). We hypothesized that MCE-STM provides a more reliable estimation of microbial CUE in soils amended with complex plant residues than the SCE-STM or the C balance approach. The comparison of methods was done in a laboratory incubation experiment, using two soils differing mainly in acidity level mixed with two specimen of plant residues differing in lignin (L) and polyphenol (PP) content. We anticipated a higher microbial CUE in less acidic (pH 5.1) soil amended with higher quality (lower (L + PP)/N) ratio)) plant residues than in more acidic (pH 4.3) soils amended with medium quality (higher (L + PP)/N ratio) plant residues, due to less energy investment in microbial metabolism in the former case. Microbial CUE estimations were completed at 7, 15, 30, 45 and 60 days. Lower CUE values (0.09–0.18) were recorded by MCE-STM as compare to those (0.24–0.47) obtained by C-balance and SCE-STM methods. Irrespective of applied CUE estimation methods, higher CUE was recorded in less acidic (pH 5.1) soil amended with residues of higher quality than the other three combinations. Microorganisms invested more energy to support growth in low pH soil in order to tolerate soil acidity, which, in turn, suppressed N-acquiring enzymatic activity and further decreased CUE. The modification of the MCE-STM method for CUE determination proposed in this work was capable to quantify the combined effect of soil pH and plant residue quality on efficiency of microbial metabolism. It, therefore, can be considered as viable alternative to the original stoichiometric modeling approach (SCE-STM).

The direction and magnitude of change of soil organic carbon (SOC) stocks due to global warming depend strongly on the temperature sensitivity (e.g., Q10) of carbon mineralization. To date, most multi-pool SOC models assume a general Q10 of 2 despite experimental evidence suggesting different Q10 for different carbon fractions. The aim of this study was to test if the use of experimentally derived pool specific Q10 values improves the performance of SOC models. Five contrasting data sets from three field experiments and two laboratory incubations were used to study the link between carbon pool recalcitrance and Q10 using two different approaches: a) Bayesian calibration of the Daisy SOC model parameters to infer Q10 of SOC and crop-litter pools, and b) using measured Q10 values of carbon degrading enzymes as proxies for Q10 of different Daisy pools. Namely β-glucosidase (median Q10 of 1.82) was assigned to metabolic litter and phenol/peroxidase (1.35) to structural litter and both SOC pools. To partition litter-carbon and SOC into model pools, the lignin-to-nitrogen ratio and the ratio of aliphatic/aromatic-carboxylate carbon were used, respectively. Measurements included soil microbial biomass, soil carbon dioxide (CO2) evolution and remaining carbon in soils and crop-litter. In the Bayesian calibration, strong differences in inferred Q10 values of the same pools between experiments suggested that intrinsic substrate recalcitrance was not the main driver of temperature sensitivity. For field experiment simulations, both the Q10 values derived by Bayesian calibration and measured enzyme Q10 were centered around values below 2, contrasting with high Q10 values for mineralization under laboratory incubations (close to 3). Furthermore, assigning measured phenol/peroxidase Q10 values to the slow crop-litter as well as both SOC pools and β-glucosidase to the fast crop-litter pool (approach b), could significantly improve model performance compared to using the default Q10 value of 2 for all pools. Root-mean-squared-deviation reductions were between 3 and 10% for field experiments, with no change in the laboratory experiments. Thus, site specific Q10 values of soil enzymes show potential as proxies for pool specific Q10. We present a new conceptual framework to explain the observed differences in temperature sensitivities between experiments as a result of two fundamental driving factors classified in a) state variables, that fluctuate in time, and b) soil properties, that are constant over decades. Measured enzyme Q10 values were interpreted as a proxy incorporating both factors. More than intrinsic substrate recalcitrance, the state variables such as physical protection, substrate abundance and unfavorable conditions for microorganisms control temperature sensitivity of mineralization. To reduce the uncertainty in global SOC simulations under a changing climate, their relative contributions should be disentangled and then implemented into SOC models.

Rubber plantations are strongly increasing in Xishuangbanna, Southwest China. Herbicide applications controlling the undergrowth may increase erosion potential and carbon export by decreasing plant and litter cover. Quantitative evaluation of the erodibility of rubber systems and the impact of herbicides has not been studied. This study aimed at assessing the impact of herbicide application on soil loss and the induced carbon export in a rubber plantation. Runoff, sediment yield, and total organic carbon (TOC) content in sediments were measured under natural rainfall for one year in a 12-year old rubber plantation subjected to three different herbicide treatments: i) standard application twice per year practiced by the majority of farmers (Hs); (ii) no application to maintain a high understory plant cover (H −); and (iii) bimonthly application (adopted by some farmers) in order to largely avoid understory plant cover (H +). The infiltration rate under different treatments was measured with a rainfall simulator. Monthly measurements of fine root density using soil coring, surface cover, and understory plant cover making photography were carried out. The highest soil and TOC in sediment losses (425 g m − 2 , 15 g C m − 2 respectively) were observed under H + treatment, while under H − treatment they were strongly reduced (50 g m − 2 and 2 g C m − 2 respectively). Compared to Hs, H + increased soil and sediment TOC loss by 34 and 52%, while H − reduced soil and TOC loss, both by 82%. Notably, H − presented high conservation efficiency, reducing sediment yields by 86% for highly erosive rainfall events. The cover and management ( C ) factor and support practice factor ( P ) are essential components of the common Universal Soil Loss Equation (USLE) model. We combined the C and P factors into a single value ( CP ) and, for the first time, derived estimations of annual CP values for a rubber plantation (0.005–0.04) using our data. The dynamic change of the CP factor of plantations during the rainy season was quantified by relating relative soil loss to changes in understory plant cover (PC), which can be expressed as CP = 0.04e − 0.028PC ( R 2 = 0.88, P

The expansion of rubber plantations (Hevea brasiliensis Mull. Arg) is a major driving force for deforestation and forest degradation in mountainous South-East Asia. In China, the unclear distinction between natural forest and commercial plantations has permitted the expansion of rubber into protected forest areas of nature reserves. However, the impact of such land-use changes on landscape carbon balances within nature reserves has rarely been investigated. We selected the Naban River Watershed National Nature Reserve (NRWNNR) in Xishuangbanna, China as a case study area and evaluated carbon stocks using the Rapid Carbon Stock Appraisal (RaCSA) method based on tree, plot, land use and landscape assessments, integrating field sampling with remote sensing and GIS technology. Six dominant land use systems were surveyed: lowland forest ( 800 m a.s.l.), lowland rubber, highland rubber, bush and grassland and agricultural crops. Land use type-specific time-averaged carbon stocks (Cta) were calculated based on total above ground biomass (AGB). Soil organic carbon (surface 30 cm) and below ground biomass were measured, but not included in Cta calculations due to large uncertainties unrelated to land use change. The Cta of lowland and highland rubber plantations were 58 Mg C ha−1 and 28 Mg C ha−1 respectively, showing larger carbon sequestration potential than nonforest land use types (agricultural crops, bush and grassland) but much lower than Cta of natural forest (156–185 Mg C ha−1). Sensitivity analysis of Cta variability showed that forest C stocks have the largest influence on landscape carbon balance. Time series analysis of land-use and land-cover maps (1989, 2007, 2012) demonstrated that during 23 years, the whole landscape of the nature reserve (26,574 ha) gained 0.644 Tg C. Despite rubber expansion, biosphere zoning strategy (i.e. experimental, buffer, core zones), and reforestation activities conducted in NRWNNR were able to enhance the carbon stocks.

Rapid expansion of natural rubber plantations in South-East Asia and other regions has greatly altered ecosystem based carbon (C) stocks with potential impacts on climate change mitigation and future C trading opportunities. Therefore, reliable estimations of carbon sequestration and emission at the landscape level after land cover transition from forest, swidden agriculture and other land use types are needed. We reviewed studies on C stocks and dynamics in rubber plantations considering the contribution of aboveground and belowground biomass, soil organic matter, collected latex and other minor components. C sequestration occurred after conversion of arable land to rubber plantations while C losses usually prevailed if forest was converted to rubber. These general trends strongly depended on local climate conditions and soil properties as well as on topography. Non-traditional planting of rubber under subtropical conditions with a dryer climate and at high elevations (300–1000 m above sea level) decreased the C sequestration potential of rubber. We show how rotation length, rubber clone, and management strategies like tapping frequency or planting density affect C stocks, discuss the uncertainties in C stock estimation and highlight improved approaches. An important conclusion is that upscaling of C stocks and dynamics under different climate scenarios and rotation lengths to a regional level requires the use of time averaged C stocks. Enhanced remote sensing techniques can greatly improve C stock estimates at the regional level, allowing for an accounting of the variability caused by terrain and plantation properties. A partial life cycle assessment of rubber production revealed greenhouse gas emissions as a minor contribution when compared to land use change effects on plant and soil C stocks and C accumulation in latex, wood products and seed oil. The review highlights scantily explored topics and proposes directions for future studies, which should decrease uncertainties in C estimates in rubber dominated landscapes.

Land-use change modulates the balance between methane (CH4) oxidation by soil methanotrophs, and production by methanogens through changes in soil physical, chemical and biological properties. The large-scale expansion of rubber plantations in Southeast Asia has decreased CH4 uptake by soil, but a mechanistic understanding of the associated processes within the soil profile is missing. To assess such land-use change impacts, we quantified the relative controls of CH4 diffusion and oxidation processes on soil profile methane fluxes using two datasets from Xishuangbanna, Southwest China. CH4 concentration, bulk density, soil temperature and moisture were measured at 5, 10, 30 and 70 cm depths during the dry and rainy season to determine the effective CH4 diffusion coefficient, diffusive flux, turnover rate and methanotrophic activity. Isotopic fractionation of carbon during CH4 oxidation was estimated using δ13CH4 profiles from in situ soil probes sampled in the dry season. This fractionation factor was used to model the seasonality of CH4 fluxes under the two land uses. CH4 consumption at 0–5 cm soil depth was significantly greater in natural forest than in rubber plantations, with a mean CH4 flux of −23.8 ± 1.0 and −14.4 ± 1.0 μg C m−2 h−1, respectively. Atmospheric CH4 oxidized in the top 10 cm accounted for 93% and 99% of total consumption in forest and rubber profiles, respectively. CH4 diffusivity at the four sampled depths was significantly lower in rubber plantations than in forest. Higher soil water content predominately explained the weakened CH4 sink in converted rubber plantations. During the transition from dry season to rainy season, methanotrophic activity at 5–10 cm depth decreased by 99.6% and 83.3% in forest and rubber plantations, respectively. The estimated isotope fractionation factor for carbon due to CH4 oxidation was 1.0292 ± 0.0015 (n = 12). A diffusion-oxidation model of the 13CH4 profile explained the oxidative behavior in the dry season, but suggested CH4 production in the subsoil during the rainy season. This production needs to be considered in future studies to explain changes in CH4 processes caused by land use transformations. The weakened CH4 sink function in soils under rubber monoculture exerts a negative effect on the global CH4 budget and climate change, given the large extent of rubber plantations worldwide. More sustainable cultivation approaches, such as rubber agroforestry that also improve soil structure and aeration are needed to mitigate this negative impact.

The concept of ecosystem services (ESS) has been increasingly recognized for its potential in decision making processes concerning environmental policy. Multidisciplinary projects on rubber (Hevea brasiliensis) cultivation, integrating research on a variety of ESS, have been few and far between. More than three years of iterative workshops with regional stakeholders resulted in the development of future land use scenarios for our study area in Xishuangbanna, PR China. We used the InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) modeling framework to analyze their impact on sediment retention, water yield, habitat quality, and carbon sequestration and developed a model for assessing rubber yields. We investigated the percentage deviations of integrated ESS indices in each scenario, as compared to the initial state of 2015 and as a novelty used different statistical weighting methods to include rankings for the preference of ESS from three contrasting stakeholder groups. The business-as-usual scenario (BAU, continuous rubber expansions) revealed an increase in rubber yields trading off against all other ESS analyzed. Compared to BAU, the measures introduced in the balanced-trade-offs scenario (reforestation, reduced herbicide application, riverine buffer zones, etc.) reduced the total amount of rubber yield but enhanced habitat quality and regulating ESS. The results show that the integrated indices for the provisioning of ESS would be overestimated without the inclusion of the stakeholder groups. We conclude that policy regulations, if properly assessed with spatial models and integrated stakeholder feedback, have the potential to buffer the typical trade-off between agricultural intensification and environmental protection.

The recently developed 3-source-partitioning approach: addition of 14 C labeled organics to soil after C3–C4 vegetation changes, was used to distinguish C sources in three compartments, namely CO 2 , microbial biomass and dissolved organic C (DOC) during decomposition of labeled cellulose. Microbial community structure (based on PLFA composition) and functions (based on enzyme activities and on microbial growth parameters) revealed mechanisms and drivers of priming effects (PE) induced by cellulose addition. 14 C-cellulose input caused negative PE within the first week and was accompanied by fast consumption of unlabelled DOC and its incorporation into microbial biomass. Microbial activation however, was not confirmed by substrate-induced respiration, nor by hydrolytic enzymes activity or by PLFA changes. A remarkable exception was a 2-fold increase in protozoan PLFA. Such an increase indicates that microorganisms feeding on cellulose and on DOC were quickly grazed by protozoans acting as a driver of microbial succession. This experimentally demonstrates the functioning of the microbial interactions: protozoan grazers provided for rapid recycling of nutrients and facilitated the succession of cellulose-degrading microorganisms during the second week of cellulose decomposition. An increase in the activity of cellulolytic enzymes caused short-term real PE accompanied by increase in abundance of slow-growing fungi and G(−) bacteria. Long-term real PE observed between 14 and 60 days after cellulose input was due to decomposition of SOM-originated hemicelluloses by fungi and G(+) bacteria. The CO 2 released by primed soil organic matter (SOM) decomposition was originated mainly from C younger than 12 years (63%) and only 37% were older than 12 years despite the recent and old C contributed almost equally (51 and 49%, respectively) to SOM under Miscanthus giganteus . This indicates that the SOM pools are involved in PE according to their availability. Despite 71% of the applied cellulose-C was sequestered in the soil, the net soil C-gain amounted only for 28% of the applied cellulose-C after factoring in the C losses by the PE. Our study emphasizes the role of food webs in the PE dynamics: cellulose input served as a driver activating the food chain through the microbial loop.

Under conditions of the global climate warming, the changes in the reserves of soil humus depend on the temperature sensitivities of polyphenol peroxidases (PPPOs) and polyphenol oxidases (PPOs). They play an important role in lignin decomposition, mineralization, and humus formation. The temperature dependence of the potential enzyme activity in modern and buried soils has been studied during incubation at 10 or 20°C. The experimental results indicate that it depends on the availability of the substrate and the presence of oxygen. The activity of PPOs during incubation in the absence of oxygen for two months decreases by 2–2.5 times, which is balanced by an increase in the activity of PPPOs by 2–3 times. The increase in the incubation temperature to 20°C and the addition of glucose accelerates this transition due to the more abrupt decrease in the activity of PPOs. The preincubation of the soil with glucose doubles the activity of PPPOs but has no significant effect on the activity of PPOs. The different effects of temperature on two groups of the studied oxidases and the possibility of substituting enzymes by those of another type under changing aeration conditions should be taken into consideration in predicting the effect of the climate warming on the mineralization of the soil organic matter. The absence of statistically significant differences in the enzymatic activity between the buried and modern soil horizons indicates the retention by the buried soil of some of its properties (soil memory) and the rapid restoration of high enzymatic activity during the preincubation.

Peak area (PA) integration of diffuse reflectance mid infrared Fourier transform spectroscopy (DRIFTS) spectra is useful to study soil organic matter (SOM) quality and as a potential modelling proxy. Residual water of soil samples after drying affects DRIFTS spectra, mainly in the region >2500 cm−1. Therefore, SOM quality related PA at different wavenumbers should be influenced to varying degrees. We studied how absolute, normalized and relative PA related to SOM functional groups (at 2930, 1620, 1530 and 1159 cm−1), as well as their ratios were influenced by oven drying of soil samples at increasing temperatures (from 32 °C to 105 °C). All organic and even mineral associated PA significantly increased with drying temperature. The PA of aliphatic C H stretching (2930 cm−1), located on the shoulder of the broad O H stretching PA, was influenced most strongly. Our results indicate that using 105 °C as drying temperature and storing samples in a desiccator is the best way to minimize water interference. These findings apply to relative PA and ratios of organic compounds, while no effect of drying temperatures on PA correlations to C or N were found.

Although carbon (C) stored deep in soils of tree-dominated land use systems in the tropics represents a large reservoir of organic matter its vulnerability to land use change has been hardly assessed. To fill this gap, we sampled Acrisols down to 3 m under three different land use systems; namely, recent cacao agroforestry ( 50 years), and secondary forest (>50 years) all located in Kapuas Hulu regency, West Kalimantan, Indonesia. We then assessed soil organic carbon (SOC) stocks as well as C accumulated in above- and belowground biomass, litter and dead wood debris at the soil surface. The amount of C stored in soils to a depth of 1 m exceeded the amount stored in living biomass (Σ C stored in roots, understorey and overstorey) strongly in the cacao agroforestry systems (69 Mg SOC vs. 12 Mg biomass-C ha−1), slightly in young rubber gardens (85 Mg SOC vs. 69 Mg C ha−1), but not in old rubber gardens (87 Mg SOC vs. 200 Mg C ha−1) and secondary forests (65 Mg SOC vs. 138 Mg C ha−1). Additionally in the older systems, up to 140 Mg C ha−1 (old rubber gardens) and 116 Mg C ha−1 (secondary forest) were found in soils to a depth of 3 m, thus raising soil C stocks by 60 to 80% relative to C stored in upper soil (0 to 1 m). We conclude that (1) the form of land use and land use change can substantially affect C stocks in living biomass, with aboveground biomass in old rubber gardens comparable to that of secondary forests; and (2) that land use change can reduce SOC in topsoil, but that substantial C stocks found in deep (down to 3 m) subsoil remain stable.

Rubber plantation, as a new land cover type expanding in Xishuangbanna, Southwest China, has a lifespan ranging 25 years to 40 years. Plantation development and forming of multi-layer structure comprising of canopy cover, surface cover and root system control the runoff and sediment yields dynamics. We applied Revised Universal Soil Loss Equation (RUSLE), a widely used in agricultural science predictive model, for the description of factors controlling the erosion in our case. The temporal change of erosion under growing rubber plantation was poorly studied, and RUSLE has been rarely applied in this kind of plantations. However, we believe that this approach is promising in integrative assessment of soil conservation measures in rubber system. The quantitative contribution of every part of plantation cover and roots to the protection from erosion has to be estimated for successful model application. This study aimed at assessing impact of rubber plantation ages on soil loss and relating it to canopy development and surface cover by applying RUSLE. We measured in field experiment runoff and sediment yields produced by each rainfall event in 4, 12, 18, 25 and 36 year old rubber plantations for two years (2013–2014). Monthly measurement of surface cover and understory plant cover in 2014 were completed using photography respectively. It was found that soil loss in plantations of different age varied from 52 gm–2 to 277 gm–2 with highest value appeared in mid-age (12 and 18 years) and lowest in old (25 and 36 year) rubber. We derived using our field data the Cropping management (C) factor of RUSLE in rubber plantations of different age. Thus, for the first time we quantitatively evaluated erosive potential of the rubber plantation and contribution of different factors to soil conservation. Surface cover determined erosive potential of rubber plantation while tree canopy contributed little to soil protection due to high canopy height caused by pruning activity. Sparse undergrowth under closed canopy, less litter and high decomposition rate made the rubber in mid-age the most vulnerable to erosion. Reduced herbicide application was proved to efficiently decrease soil loss to 50 gm–2. Improved soil conservation of rubber plantation should be considered by integrated land management.

Short-term acceleration of soil organic matter decomposition by increasing temperature conflicts with the thermal adaptation observed in long-term studies. Here we used the altitudinal gradient on Mt. Kilimanjaro to demonstrate the mechanisms of thermal adaptation of extra- and intracellular enzymes that hydrolyze cellulose, chitin and phytate and oxidize monomers (14C-glucose) in warm- and coldclimate soils. We revealed that no response of decomposition rate to temperature occurs because of a cancelling effect consisting in an increase in half-saturation constants (Km), which counteracts the increase in maximal reaction rates (Vmax with temperature). We used the parameters of enzyme kinetics to predict thresholds of substrate concentration (Scrit) below which decomposition rates will be insensitive to global warming. Increasing values of Scrit, and hence stronger canceling effects with increasing altitude on Mt. Kilimanjaro, explained the thermal adaptation of polymer decomposition. The reduction of the temperature sensitivity of Vmax along the altitudinal gradient contributed to thermal adaptation of both polymer and monomer degradation. Extrapolating the altitudinal gradient to the large-scale latitudinal gradient, these results show that the soils of cold climates with stronger and more frequent temperature variation are less sensitive to global warming than soils adapted to high temperatures. Open-Access Publikationsfonds 2016 peerReviewed

The rapid development of biogas production will result in increased use of biogas residues as organic fertilizers. However, control of microbial activity by organic fertilizers remains a challenge for modern land use, especially with respect to mitigating greenhouse effects and increasing C sequestration in soil. To address this issue, we compared CO 2 emissions, microbial growth and extracellular enzyme activities in agricultural soil amended with biogas residues (BGR) versus maize straw (MST). Over a 21 day incubation period, 6.4% of organic C added was mineralised and evolved as CO 2 with BGR and 30% with MST. As shown by the substrate-induced growth respiration approach, BGR and MST significantly decreased the specific microbial growth rate ( μ ) and increased the microbial biomass C in the soil, indicating a clear shift in the microbial community to slower-growing microorganisms. Because of the reduced availability of C associated with the less labile C and more lignin in biogas residues, observed μ values and microbial biomass C were lower after BGR application than after MST application. After 21 days incubation, BGR had no effect on the activity of three extracellular enzymes: β-glucosidase and cellobiohydrolase, both of which are involved in cellulose decomposition; and xylanase, which is involved in hemicellulose decomposition. In contrast, MST significantly increased the activity of these three enzymes. The application of biogas residues in short-term experiment leads to a 34% increase in soil C content and slower C turnover as compared to common maize residues.

The use of kinetic respiration analysis to determine soil microbial biomass its active part and maximum specific growth rate has recently increased. With this method, the increase in soil respiration rate initiated by application of carbon growth substrate, e.g. glucose, and mineral nutrients is used to estimate parameters describing microbial growth in soil. This study refines the method by developing statistical guidelines for the data analysis and processing. The kinetic respiration analysis assumes that microbial growth is not limited by substrate and energy. That is why it is critically important to identify the time period corresponding to the unlimited growth. In this work, we studied how the unlimited growth phase can be identified in less subjective ways by examining 121 datasets of respiration time series of 44 different soil samples taken from field plots. Deflection of the respiratory curve from the exponential pattern indicates growth limitation. Subjective selection of the part of respiratory curve which fits to the exponential pattern resulted in a 30% bias in specific microbial growth rates. We propose rules that are based on inspecting the patterns in a series of plots of residuals of fitted respiration rate. By comparing those rules with a set of statistical criteria we find that the weighted-coefficient of determination (r2) can be used to objectively constrain the unlimited growth phase in those cases where double-limitation does not occur. Furthermore, we discuss how the uncertainty of estimated microbial parameters is influenced by a) measurement uncertainty, b) biased measurement at the beginning of the experiment, and c) the number and timing of respiration measurements. We recommend checking plots of fits and residuals as well as reporting uncertainty bounds together with the estimated microbial parameters. A free statistical package is provided to easily deal with those aspects.

One of the issues hampering progress in modelling greenhouse gas (GHG) emissions from soils is a lack of co-ordination between models originating from different disciplines: soil physics and soil biology. We have reviewed recent advances in modelling both gaseous transport and the biochemical processes in the soil that lead to the emission of the main biogeneic GHGs: CO2, N2O, and CH4. The precise coupling of gaseous transport and biochemistry is necessary because CH4 and N2O can be both produced and consumed in soil, and eventual flux to the atmosphere depends on the position of reaction sites and the escape pathways for these gases. The CO2 production rate depends in turn on the efficiency of oxygen transport in the soil. Principles leading to successful simulation are: keeping a balanced level of detail in coupled model systems describing biochemical reactions and transport; reduction of unnecessary complexity by means of using the most essential relationships elucidated by comprehensive statistical model testing; consideration of all transport mechanisms in relation to prevailing ecological conditions, i.e., diffusion and convection in the air and liquid phases, plant-mediated transport and ebullition. It is important to model all three major GHG in accord with the description of O2 and N2 transport and concentration in soil. This helps: i) to estimate the full global warming potential; ii) to apply the model algorithms considering partial gas pressure and gas species interactions; iii) to describe the O2 effect on the biochemical processes in soil. We discuss the approaches linking the simple and more complex process-oriented models, and propose a strategy for up-scaling model results from soil aggregate to profile and to the field/catchment.

We propose and successfully applied a new approach for 3-source-partitioning based on a combination of 14 C labeling with 13 C natural abundance. By adding 14 C-labeled glucose to soil after C 3 – C 4 vegetation change, we partitioned three C sources in three compartments, namely CO 2 , microbial biomass and dissolved organic C (DOC). This enabled us to estimate mechanisms and sources of priming effects (PE). Glucose application at low and high rate (GL: 100 and GH: 1000 μg C g −1 , respectively) caused positive PE both short-term (during 1–3 days) and long-term (3–55 days). Despite a 10-fold difference in the amount of substrate added, the PE observed was larger by a factor of only 1.6 at the high versus low rate of glucose. The real and apparent priming effects were distinguished by partitioning of microbial C for glucose-C and SOM-derived C. As the amount of primed CO 2 respired during short-term PE was 40% lower than microbial C, and the contribution of soil C in microbial biomass did not increase, we concluded that such short-term PE was apparent and was mainly caused by accelerated microbial turnover (at GL) and by pool substitution (at GH). Both the amount of primed CO 2 –C, which was 1.3–2.1 times larger than microbial C, and the increased contribution of soil C in microbial biomass allowed us to consider the long-term PE as being real. The sole source of real PE (GL treatment) was the “recent” soil organic matter, which is younger than 12-year-old C. The real PE-induced by a glucose amount exceeding microbial biomass (GH) was due to the almost equal contribution of ‘recent’ ( 12 years) C. Thus, the decomposition of old recalcitrant SOM was induced only by an amount of primer exceeding microbial C. We conclude that combining 14 C labeling with 13 C natural abundance helped disentangle three C sources in CO 2 , microbial biomass and DOC and evaluate mechanisms and sources of PE.

Two processes contribute to changes of the δ13C signature in soil pools: 13C fractionation per se and preferential microbial utilization of various substrates with different δ13C signature. These two processes were disentangled by simultaneously tracking δ13C in three pools – soil organic matter (SOM), microbial biomass, dissolved organic carbon (DOC) – and in CO2 efflux during incubation of 1) soil after C3–C4 vegetation change, and 2) the reference C3 soil. The study was done on the Ap horizon of a loamy Gleyic Cambisol developed under C3 vegetation. Miscanthus giganteus – a perennial C4 plant – was grown for 12 years, and the δ13C signature was used to distinguish between ‘old’ SOM (>12 years) and ‘recent’ Miscanthus-derived C ( Based on the δ13C changes in SOM, we showed that the estimated turnover time of old SOM increased by two years per year in 9 years after the vegetation change. The relative increase in the turnover rate of recent microbial C was 3 times faster than that of old C indicating preferential utilization of available recent C versus the old C. Combining long-term field observations with soil incubation reveals that the turnover time of C in microbial biomass was 200 times faster than in total SOM. Our study clearly showed that estimating the residence time of easily degradable microbial compounds and biomarkers should be done at time scales reflecting microbial turnover times (days) and not those of bulk SOM turnover (years and decades). This is necessary because the absence of C reutilization is a prerequisite for correct estimation of SOM turnover. We conclude that comparing the δ13C signature of linked pools helps calculate the relative turnover of old and recent pools.

The most frequently used models simulating soil organic matter (SOM) dynamics are based on first-order kinetics. These models fail to describe and predict such interactions as priming effects (PEs), which are short-term changes in SOM decomposition induced by easily available C or N sources. We hypothesized that if decomposition rate depends not only on size of the SOM pool, but also on microbial biomass and its activity, then PE can be simulated. A simple model that included these interactions and that consisted of three C pools – SOM, microbial biomass, and easily available C – was developed. The model was parameterized and evaluated using results of 12C–CO2 and 14C–CO2 efflux after adding 14C-labeled glucose to a loamy Haplic Luvisol. Experimentally measured PE, i.e., changes in SOM decomposition induced by glucose, was compared with simulated PE. The best agreement between measured and simulated CO2 efflux was achieved by considering both the total amount of microbial biomass and its activity. Because it separately described microbial turnover and SOM decomposition, the model successfully simulated apparent and real PE. The proposed PE model was compared with three alternative approaches with similar complexity but lacking interactions between the pools and neglecting the activity of microbial biomass. The comparison showed that proposed new model best described typical PE dynamics in which the first peak of apparent PE lasted for 1 day and the subsequent real PE gradually increased during 60 days. This sequential decomposition scheme of the new model, with immediate microbial consumption only of soluble substrate, was superior to the parallel decomposition scheme with simultaneous microbial consumption of two substrates with different decomposability. Incorporating microbial activity function in the model improved the fit of simulation results with experimental data, by providing the flexibility necessary to properly describe PE dynamics. We conclude that microbial biomass should be considered in models of C and N dynamics in soil not only as a pool but also as an active driver of C and N turnover.

Increasing the belowground translocation of assimilated carbon by plants grown under elevated CO 2 can cause a shift in the structure and activity of the microbial community responsible for the turnover of organic matter in soil. We investigated the long-term effect of elevated CO 2 in the atmosphere on microbial biomass and specific growth rates in root-free and rhizosphere soil. The experiments were conducted under two free air carbon dioxide enrichment (FACE) systems: in Hohenheim and Braunschweig, as well as in the intensively managed forest mesocosm of the Biosphere 2 Laboratory (B2L) in Oracle, AZ. Specific microbial growth rates (μ) were determined using the substrate-induced respiration response after glucose and/or yeast extract addition to the soil. For B2L and both FACE systems, up to 58% higher μ were observed under elevated vs. ambient CO 2 , depending on site, plant species and N fertilization. The μ-values increased linearly with atmospheric CO 2 concentration at all three sites. The effect of elevated CO 2 on rhizosphere microorganisms was plant dependent and increased for: Brassica napus = Triticum aestivum < Beta vulgaris < Populus deltoides. N deficiency affected microbial growth rates directly (N limitation) and indirectly (changing the quantity of fine roots). So, 50% decrease in N fertilization caused the overall increase or decrease of microbial growth rates depending on plant species. The μ-value increase was lower for microorganisms growing on yeast extract then for those growing on glucose, i.e. the effect of elevated CO 2 was smoothed on rich vs. simple substrate. So, the r/K strategies ratio can be better revealed by studying growth on simple (glucose) than on rich substrate mixtures (yeast extract). Our results clearly showed that the functional characteristics of the soil microbial community (i.e. specific growth rates) rather than total microbial biomass amount are sensitive to increased atmospheric CO 2 . We conclude that the more abundant available organics released by roots at elevated CO 2 altered the ecological strategy of the soil microbial community specifically a shift to a higher contribution of fast-growing r-selected species was observed. These changes in functional structure of the soil microbial community may counterbalance higher C input into the soil under elevated atmospheric CO 2 concentration.

N 2 O emissions from soil contribute significantly to global warming. Pulse emissions of N 2 O from soils during freeze-thawing were recently recognized as important atmospheric sources. In this modelling study we explore three different hypotheses for explaining freeze–thaw related N 2 O emissions: (1) soil frost or snow cover may reduce gas diffusion and create anaerobic conditions that stimulate N 2 O production via denitrification, (2) microbes that die of frost deliver easy decomposable organic carbon and nitrogen to the soil, which stimulates microbial growth and vigorous N 2 O production during freeze–thaw, and (3) the enzyme nitrous oxide reductase, which is responsible for the reduction of N 2 O to N 2 during denitrification, is more sensitive to low temperatures than other enzymes, so that N 2 O becomes the dominating end-product of denitrification at low temperatures. These hypotheses were tested with a biogeochemical model that combines hydrology and physics calculations with a newly developed, parameter-poor biochemistry module. The model was first calibrated with field datasets on soil–atmosphere fluxes of N 2 O, NO and CO 2 and soil NO 3 and NH 4 concentrations that were measured in a spruce forest in Southeast Germany in the years 1994–1997. Subsequently, additional model mechanisms were implemented that allow the model to describe the outlined mechanisms potentially driving freeze–thaw N 2 O fluxes. After each implementation the model was recalibrated. We were able to mimic dimension and timing of high N 2 O emissions when either one of the first two hypotheses were assumed, but found no confirmation for the third. The best model fit was achieved by combining hypothesis one and two, indicating that freeze–thaw N 2 O emissions are not mono-causal.