Samuel Bodé

Development and evaluation of a high-performance liquid chromatography/isotope ratio mass spectrometry methodology for δ13C analyses of amino sugars in soil†

Amino sugars have been used as biomarkers to assess the relative contribution of dead microbial biomass of different functional groups of microorganisms to soil carbon pools. However, little is known about the dynamics of these compounds in soil. The isotopic composition of individual amino sugars can be used as a tool to determine the turnover of these compounds. Methods to determine the delta(13)C of amino sugars using gas chromatography/combustion/isotope ratio mass spectrometry (GC/C/IRMS) have been proposed in literature. However, due to derivatization, the uncertainty on the obtained delta(13)C is too high to be used for natural abundance studies. Therefore, a new high-performance liquid chromatography/isotope ratio mass spectrometry (HPLC/IRMS) methodology, with increased accuracy and precision, has been developed. The repeatability on the obtained delta(13)C values when pure amino sugars were analyzed were not significantly concentration-dependent as long as the injected amount was higher than 1.5 nmol. The delta(13)C value of the same amino sugar spiked to a soil deviated by only 0.3 per thousand from the theoretical value.

Stable isotope probing of amino sugars – a promising tool to assess microbial interactions in soils†

RATIONALE Bacteria and fungi are key protagonists of litter degradation in soils. Often they have to share common substrates, which has led to special interactions between both microbial groups. Due to the historical classification of bacteriology and mycology as two separate fields of microbial research, the understanding of their interactions in soils is scares, while it is crucial for a better understanding of nutrient recycling and carbon sequestration in soils. Therefore, a new approach to investigate fungal-bacterial interactions is proposed using stable isotope probing of their amino sugar biomarkers. METHODS An agricultural soil, under different microbial inhibition treatments, was incubated for 21 days with (13)C-labeled plant residues. Residue respiration was determined by measuring the isotopic composition and concentration of the produced CO2, using an isotope ratio mass spectrometer coupled to a trace gas preparation unit. At several time points, amino sugars were extracted, after hydrolysis, from the incubated microcosms. Subsequently, (13)C-isotopic composition and concentration of the individual amino sugars was determined using liquid chromatography/isotope ratio mass spectrometry. RESULTS When the bacterial community was inhibited, fungi showed an increased capacity to metabolize added plant residues indicating an antagonistic effect of bacteria towards fungi. Furthermore, the fungal community was able to take benefit of a larger portion of the residue, which indicates that this antagonism was at least partially due to interference competition. On the other hand, the inhibition of the fungal community appeared to have a very negative effect on the capacity of bacteria to metabolize added plant residues. Therefore, the bacterial community could be considered as playing a parasitic type role towards fungi during litter degradation. CONCLUSIONS This newly developed methodology proved to be very useful for elucidating microbial interactions during plant residue degradation.

Phosphorus resource partitioning shapes phosphorus acquisition and plant species abundance in grasslands

Species diversity is commonly hypothesized to result from trade-offs for different limiting resources, providing separate niches for coexisting species1–4. As soil nutrients occur in multiple chemical forms, plant differences in acquisition of the same element derived from different compounds may represent unique niche dimensions5,6. Because plant productivity of ecosystems is often limited by phosphorus7, and because plants have evolved diverse adaptations to acquire soil phosphorus6,8, a promising yet untested hypothesis is phosphorus resource partitioning6,9,10. Here, we provided two different chemical forms of phosphorus to sown grassland mesocosms to investigate phosphorus acquisition of eight plant species that are common in European grasslands, and to identify subsequent patterns of plant abundance. For the first time, we show that the relative abundance of grassland plant species can be influenced by soil phosphorus forms, as higher abundance was linked to higher acquisition of a specific form of phosphorus. These results were supported by a subsequent isotope dilution experiment using intact grassland sods that were treated with different inorganic or organic phosphorus forms. Here, 5 out of 14 species showed greater phosphorus acquisition in the inorganic phosphorus treatment, and 4 in the organic phosphorus treatments. Furthermore, for the species used in both experiments we found similar acquisition patterns. Our results support the hypothesis of phosphorus resource partitioning and may provide a new mechanistic framework to explain high plant diversity in phosphorus-poor ecosystems6,11–13. As world biodiversity hotspots are almost invariably related to phosphorus limitation8,11,12, our results may thus also be key to understanding biodiversity loss in an era of ever-increasing nutrient enrichment14.

Methodological perspectives on the application of compound-specific stable isotope fingerprinting for sediment source apportionment

PurposeCompound-specific stable isotope (CSSI) fingerprinting of sediment sources is a recently introduced tool to overcome some limitations of conventional approaches for sediment source apportionment. The technique uses the 13C CSSI signature of plant-derived fatty acids (δ13C-fatty acids) associated with soil minerals as a tracer. This paper provides methodological perspectives to advance the use of CSSI fingerprinting in combination with stable isotope mixing models (SIMMs) to apportion the relative contributions of different sediment sources (i.e. land uses) to sediments.Results and discussionCSSI fingerprinting allows quantitative estimation of the relative contribution of sediment sources within a catchment at a spatio-temporal resolution, taking into account the following approaches. First, application of CSSI fingerprinting techniques to complex catchments presents particular challenges and calls for well-designed sampling strategies and data handling. Hereby, it is essential to balance the effort required for representative sample collection and analyses against the need to accurately quantify the variability within the system. Second, robustness of the CSSI approach depends on the specificity and conservativeness of the δ13C-FA fingerprint. Therefore, saturated long-chain (>20 carbon atoms) FAs, which are biosynthesised exclusively by higher plants and are more stable than the more commonly used short-chain FAs, should be used. Third, given that FA concentrations can vary largely between sources, concentration-dependent SIMMs that are also able to incorporate δ13C-FA variability should be standard operation procedures to correctly assess the contribution of sediment sources via SIMMs.ConclusionsThis paper reflects on the use of δ13C-FAs in erosion studies and provides recommendations for its application. We strongly advise the use of saturated long-chain (>20 carbon atoms) FAs as tracers and concentration-dependent Bayesian SIMMs. We anticipate progress in CSSI sediment fingerprinting from two current developments: (i) development of hierarchical Bayesian SIMMs to better address catchment complexity and (ii) incorporation of dual isotope approaches (δ13C- and δ2H-FA) to improve estimates of sediment sources.

A robust nitrifying community in a bioreactor at 50 °C opens up the path for thermophilic nitrogen removal.

The increasing production of nitrogen-containing fertilizers is crucial to meet the global food demand, yet high losses of reactive nitrogen associated with the food production/consumption chain progressively deteriorate the natural environment. Currently, mesophilic nitrogen-removing microbes eliminate nitrogen from wastewaters. Although thermophilic nitrifiers have been separately enriched from natural environments, no bioreactors are described that couple these processes for the treatment of nitrogen in hot wastewaters. Samples from composting facilities were used as inoculum for the batch-wise enrichment of thermophilic nitrifiers (350 days). Subsequently, the enrichments were transferred to a bioreactor to obtain a stable, high-rate nitrifying process (560 days). The community contained up to 17% ammonia-oxidizing archaea (AOAs) closely related to ‘Candidatus Nitrososphaera gargensis’, and 25% nitrite-oxidizing bacteria (NOBs) related to Nitrospira calida. Incorporation of 13C-derived bicarbonate into the respective characteristic membrane lipids during nitrification supported their activity as autotrophs. Specific activities up to 198±10 and 894±81 mg N g−1 VSS per day for AOAs and NOBs were measured, where NOBs were 33% more sensitive to free ammonia. The NOBs were extremely sensitive to free nitrous acid, whereas the AOAs could only be inhibited by high nitrite concentrations, independent of the free nitrous acid concentration. The observed difference in product/substrate inhibition could facilitate the development of NOB inhibition strategies to achieve more cost-effective processes such as deammonification. This study describes the enrichment of autotrophic thermophilic nitrifiers from a nutrient-rich environment and the successful operation of a thermophilic nitrifying bioreactor for the first time, facilitating opportunities for thermophilic nitrogen removal biotechnology.

Comparison of HPLC Methods for the Determination of Amino Sugars in Soil Hydrolysates

A study on the suitability of chromatographic techniques such as high performance anion exchange chromatography (HPAEC) with fluorescence detection (FL) and pulsed amperometric detection (PAD) and reversed phase (RP) chromatography for the determination of galactosamine, glucosamine, mannosamine, and muramic acid in soil hydrolysates was carried out. The reversed phase fluorescence method was rapid, provided good validation parameters, and employed relatively inexpensive instrumentation. The HPAEC methods had slightly higher limits of quantification, 0.6–5.0 µmol L−1 (HPAEC-FL) and 1.0–10.0 µmol L−1 (HPAEC-PAD), compared to the reversed phase fluorescence method (0.5–5.0 µmol L−1). Various sample pretreatment methods and chromatographic methods were investigated and the advantages and disadvantages of the HPLC methods are discussed.

Isotope mixing models require individual isotopic tracer content for correct quantification of sediment source contributions

The use of isotopic tracers for sediment source apportionment is gaining interest with recent introduction of compound-specific stable isotope tracers. The method relies on linear mixing of source isotopic tracers, and deconvolution of a sediment mixture initially quantifies the contribution of sources to the mixtures tracer signature. Therefore, a correction to obtain real sediment source proportions is subsequently required. As far as we are aware, all published studies to date have used total isotopic tracer content or a proxy (e.g., soil carbon content) for this post-unmixing correction. However, as the relationship between the isotopic tracer mixture and the source mixture is different for each isotopic tracer, post-unmixing corrections cannot be carried out with one single factor. This contribution presents an isotopic tracer model structurethe concentration-dependent isotope mixing model (CD-IMM)to overcome this limitation. Herein, we aim to clarify why the conventional approach to converting isotopic tracer proportions to source proportions using a single factor is wrong. In an initial mathematical assessment, error incurred by not using CD-IMM (NCD-IMM) in unmixing two sources with two isotopic tracers showed a complex relation as a function of relative tracer contents. Next, three artificial mixtures with different proportions of three soil sources were prepared and deconvoluted using C-13 of fatty acids using CD-IMM and NCD-IMM. Using NCD-IMM affected both accuracy (mean average error increased up to a threefold compared with the CD-IMM output) and precision (interquartile range was up to 2.5 times larger). Finally, as an illustrative example, the proportional source contribution reported in a published study was recalculated using CD-IMM. This resulted in changes in estimated source proportions and associated uncertainties. Content of isotopic tracers is seldom reported in published work concerning use of isotopic tracers for sediment source partitioning. The magnitude of errors made by miscalculation in former studies is therefore difficult to assess. With this contribution, we hope the community will acknowledge the limitations of prior approaches and use a CD-IMM in future studies.

Community managed forests dominate the catchment sediment cascade in the mid-hills of Nepal: A compound-specific stable isotope analysis

Soil erosion by water is critical for soil, lake and reservoir degradation in the mid-hills of Nepal. Identification of the nature and relative contribution of sediment sources in rivers is important to mitigate water erosion within catchments and siltation problems in lakes and reservoirs. We estimated the relative contribution of land uses (i.e. sources) to suspended and streambed sediments in the Chitlang catchment using stable carbon isotope signature (δ13C) of long-chain fatty acids as a tracer input for MixSIAR, a Bayesian mixing model used to apportion sediment sources. Our findings reveal that the relative contribution of land uses varied between suspended and streambed sediment, but did not change over the monsoon period. Significant over- or under-prediction of source contributions could occur due to overlapping source tracer values, if source groups are classified on a catchment-wide basis. Therefore, we applied a novel deconvolutional framework of MixSIAR (D-MixSIAR) to improve source apportionment of suspended sediment collected at tributary confluences (i.e. sub-catchment level) and at the outlet of the entire catchment. The results indicated that the mixed forest was the dominant (41 ± 13%) contributor of sediment followed by broadleaf forest (15 ± 8%) at the catchment outlet during the pre-wet season, suggesting that forest disturbance as well as high rainfall and steep slopes interact for high sediment generation within the study catchment. Unpaved rural road tracks located on flat and steep slopes (11 ± 8 and 9 ± 7% respectively) almost equally contributed to the sediment. Importantly, agricultural terraces (upland and lowland) had minimal contribution (each <7%) confirming that proper terrace management and traditional irrigation systems played an important role in mitigating sediment generation and delivery. Source contributions had a small temporal, but large spatial, variation in the sediment cascade of Chitlang stream. D-MixSIAR provided significant improvement regarding spatially explicit sediment source apportionment within the entire catchment system. This information is essential to prioritize implementation measures to control erosion in community managed forests to reduce sediment loadings to Kulekhani hydropower reservoir. In conclusion, using compound-specific stable isotope (CSSI) tracers for sediment fingerprinting in combination with a deconvolutional Bayesian mixing model offers a versatile approach to deal with the large tracer variability within catchment land uses and thus to successfully apportion multiple sediment sources.

Links among warming, carbon and microbial dynamics mediated by soil mineral weathering

Quantifying soil carbon dynamics is of utmost relevance in the context of global change because soils play an important role in land–atmosphere gas exchange. Our current understanding of both present and future carbon dynamics is limited because we fail to accurately represent soil processes across temporal and spatial scales, partly because of the paucity of data on the relative importance and hierarchical relationships between microbial, geochemical and climatic controls. Here, using observations from a 3,000-kyr-old soil chronosequence preserved in alluvial terrace deposits of the Merced River, California, we show how soil carbon dynamics are driven by the relationship between short-term biotic responses and long-term mineral weathering. We link temperature sensitivity of heterotrophic respiration to biogeochemical soil properties through their relationship with microbial activity and community composition. We found that soil mineralogy, and in particular changes in mineral reactivity and resulting nutrient availability, impacts the response of heterotrophic soil respiration to warming by altering carbon inputs, carbon stabilization, microbial community composition and extracellular enzyme activity. We demonstrate that biogeochemical alteration of the soil matrix (and not short-term warming) controls the composition of microbial communities and strategies to metabolize nutrients. More specifically, weathering first increases and then reduces nutrient availability and retention, as well as the potential of soils to stabilize carbon.Soil weathering, rather than short-term warming, controls microbial community composition, nutrient availability and soil carbon content, according to observations from a 3-Myr-old soil chronosequence preserved in river terraces in California.

A deconvolutional Bayesian mixing model approach for river basin sediment source apportionment

Increasing complexity in human-environment interactions at multiple watershed scales presents major challenges to sediment source apportionment data acquisition and analysis. Herein, we present a step-change in the application of Bayesian mixing models: Deconvolutional-MixSIAR (D-MIXSIAR) to underpin sustainable management of soil and sediment. This new mixing model approach allows users to directly account for the ‘structural hierarchy’ of a river basin in terms of sub-watershed distribution. It works by deconvoluting apportionment data derived for multiple nodes along the stream-river network where sources are stratified by sub-watershed. Source and mixture samples were collected from two watersheds that represented (i) a longitudinal mixed agricultural watershed in the south west of England which had a distinct upper and lower zone related to topography and (ii) a distributed mixed agricultural and forested watershed in the mid-hills of Nepal with two distinct sub-watersheds. In the former, geochemical fingerprints were based upon weathering profiles and anthropogenic soil amendments. In the latter compound-specific stable isotope markers based on soil vegetation cover were applied. Mixing model posterior distributions of proportional sediment source contributions differed when sources were pooled across the watersheds (pooled-MixSIAR) compared to those where source terms were stratified by sub-watershed and the outputs deconvoluted (D-MixSIAR). In the first example, the stratified source data and the deconvolutional approach provided greater distinction between pasture and cultivated topsoil source signatures resulting in a different posterior distribution to non-deconvolutional model (conventional approaches over-estimated the contribution of cultivated land to downstream sediment by 2 to 5 times). In the second example, the deconvolutional model elucidated a large input of sediment delivered from a small tributary resulting in differences in the reported contribution of a discrete mixed forest source. Overall D-MixSIAR model posterior distributions had lower (by ca 25–50%) uncertainty and quicker model run times. In both cases, the structured, deconvoluted output cohered more closely with field observations and local knowledge underpinning the need for closer attention to hierarchy in source and mixture terms in river basin source apportionment. Soil erosion and siltation challenge the energy-food-water-environment nexus. This new tool for source apportionment offers wider application across complex environmental systems affected by natural and human-induced change and the lessons learned are relevant to source apportionment applications in other disciplines.