Soil quality increases with long-term chabazite-zeolite tuff amendments in arable and perennial cropping systems.

The application of natural zeolites to improve soil quality and functioning has become highly popular, but we still miss information about the long-term effects on the soil due to its application. This study assesses the soil quality index (SQI) of three distinct agricultural soil systems 6-10 years after a single application of natural chabazite zeolite as a soil amendment. These soils exhibit different management practices: intensive arable (cereals), intensive perennial (pear) and organic perennial (olive). In the arable system, a zeolite application dosage of 5, 10 and 15 kg m-2 was tested and compared to unamended soil. In the two perennial systems, an application of 5 kg m-2 was tested against untreated reference sols. A set of 25 soil physical, chemical and biological parameters linked to soil health and quality were analysed at each experimental site. The dataset was investigated through Principal Component Analysis (PCA) to calculate the soil quality index (SQI) using linear scoring. In the arable-cereal field, the SQI doubled (0.3 to ca. 0.6 for all amendments) in chabazite-amended plots; a dose effect was not recognizable. In both perennial fields, the SQI was significantly higher in the chabazite-amended plots (5 kg m-2) with similar increases as compared to the arable-cereal field. At each site, the indicators selected by the PCA were different, indicating that chabazite addition impacted soil quality differently in each cropping system. Overall, the results highlighted a significant increase in soil quality with chabazite amendment, which confirms its potential for increasing soil health in the long-term.

Fungicide application increased copper-bioavailability and impaired nitrogen fixation through reduced root nodule formation on alfalfa.

Copper-based fungicides have been used for a long time in viticulture and have accumulated in many vineyard soils. In this study, incrementing Cu(OH)2-based fungicide application from 0.05 to 5 g Cu kg-1 on two agricultural soils (an acidic sandy loam (L, pH 4.95) and an alkaline silt loam (D, pH 7.45)) resulted in 5 times more mobile Cu in the acidic soil. The most sensitive parameters of alfalfa (Medicago sativa) growing in these soils were the root nodule number, decreasing to 34% and 15% of the control at 0.1 g Cu kg-1 in soil L and at 1.5 g Cu kg-1 in soil D, respectively, as well as the nodule biomass, decreasing to 25% and 27% at 0.5 g Cu kg-1 in soil L and at 1.5 g Cu kg-1 in soil D, respectively. However, the enzymatic N2-fixation was not directly affected by Cu in spite of the presence of Cu in the meristem and the zone of effective N2-fixation, as illustrated by chemical imaging. The strongly different responses observed in the two tested soils reflect the higher buffering capacity of the alkaline silt loam and showed that Cu mitigation and remediation strategies should especially target vineyards with acidic, sandy soils.

Assessment of Cu applications in two contrasting soils-effects on soil microbial activity and the fungal community structure.

Copper (Cu)-based fungicides have been used in viticulture to prevent downy mildew since the end of the 19th century, and are still used today to reduce fungal diseases. Consequently, Cu has built up in many vineyard soils, and it is still unclear how this affects soil functioning. The present study aimed to assess the short and medium-term effects of Cu contamination on the soil fungal community. Two contrasting agricultural soils, an acidic sandy loam and an alkaline silt loam, were used for an eco-toxicological greenhouse pot experiment. The soils were spiked with a Cu-based fungicide in seven concentrations (0-5000 mg Cu kg-1 soil) and alfalfa was grown in the pots for 3 months. Sampling was conducted at the beginning and at the end of the study period to test Cu toxicity effects on total microbial biomass, basal respiration and enzyme activities. Fungal abundance was analysed by ergosterol at both samplings, and for the second sampling, fungal community structure was evaluated via ITS amplicon sequences. Soil microbial biomass C as well as microbial respiration rate decreased with increasing Cu concentrations, with EC50 ranging from 76 to 187 mg EDTA-extractable Cu kg-1 soil. Oxidative enzymes showed a trend of increasing activity at the first sampling, but a decline in peroxidase activity was observed for the second sampling. We found remarkable Cu-induced changes in fungal community abundance (EC50 ranging from 9.2 to 94 mg EDTA-extractable Cu kg-1 soil) and composition, but not in diversity. A large number of diverse fungi were able to thrive under elevated Cu concentrations, though within the order of Hypocreales several species declined. A remarkable Cu-induced change in the community composition was found, which depended on the soil properties and, hence, on Cu availability.

Learning vs. understanding: When does artificial intelligence outperform process-based modeling in soil organic carbon prediction?

In recent years, machine learning (ML) algorithms have gained substantial recognition for ecological modeling across various temporal and spatial scales. However, little evaluation has been conducted for the prediction of soil organic carbon (SOC) on small data sets commonly inherent to long-term soil ecological research. In this context, the performance of ML algorithms for SOC prediction has never been tested against traditional process-based modeling approaches. Here, we compare ML algorithms, calibrated and uncalibrated process-based models as well as multiple ensembles on their performance in predicting SOC using data from five long-term experimental sites (comprising 256 independent data points) in Austria. Using all available data, the ML-based approaches using Random forest and Support vector machines with a polynomial kernel were superior to all process-based models. However, the ML algorithms performed similar or worse when the number of training samples was reduced or when a leave-one-site-out cross validation was applied. This emphasizes that the performance of ML algorithms is strongly dependent on the data-size related quality of learning information following the well-known curse of dimensionality phenomenon, while the accuracy of process-based models significantly relies on proper calibration and combination of different modeling approaches. Our study thus suggests a superiority of ML-based SOC prediction at scales where larger datasets are available, while process-based models are superior tools when targeting the exploration of underlying biophysical and biochemical mechanisms of SOC dynamics in soils. Therefore, we recommend applying ensembles of ML algorithms with process-based models to combine advantages inherent to both approaches.

Stoichiometric controls of nitrogen and phosphorus cycling in decomposing beech leaf litter.

Resource stoichiometry (C:N:P) is an important determinant of litter decomposition. However, the effect of elemental stoichiometry on the gross rates of microbial N and P cycling processes during litter decomposition is unknown. In a mesocosm experiment, beech (Fagus sylvatica L.) litter with natural differences in elemental stoichiometry (C:N:P) was incubated under constant environmental conditions. After three and six months, we measured various aspects of nitrogen and phosphorus cycling. We found that gross protein depolymerization, N mineralization (ammonification), and nitrification rates were negatively related to litter C:N. Rates of P mineralization were negatively correlated with litter C:P. The negative correlations with litter C:N were stronger for inorganic N cycling processes than for gross protein depolymerization, indicating that the effect of resource stoichiometry on intracellular processes was stronger than on processes catalyzed by extracellular enzymes. Consistent with this, extracellular protein depolymerization was mainly limited by substrate availability and less so by the amount of protease. Strong positive correlations between the interconnected N and P pools and the respective production and consumption processes pointed to feed-forward control of microbial litter N and P cycling. A negative relationship between litter C:N and phosphatase activity (and between litter C:P and protease activity) demonstrated that microbes tended to allocate carbon and nutrients in ample supply into the production of extracellular enzymes to mine for the nutrient that is more limiting. Overall, the study demonstrated a strong effect of litter stoichiometry (C:N:P) on gross processes of microbial N and P cycling in decomposing litter; mineralization of N and P were tightly coupled to assist in maintaining cellular homeostasis of litter microbial communities.

Soil metaproteomics - Comparative evaluation of protein extraction protocols.

Metaproteomics and its potential applications are very promising to study microbial activity in environmental samples and to obtain a deeper understanding of microbial interactions. However, due to the complexity of soil samples the exhaustive extraction of proteins is a major challenge. We compared soil protein extraction protocols in terms of their protein extraction efficiency for two different soil types. Four different protein extraction procedures were applied based on (a) SDS extraction without phenol, (b) NaOH and subsequent phenol extraction, (c) SDS-phenol extraction and (d) SDS-phenol extraction with prior washing steps. To assess the suitability of these methods for the functional analysis of the soil metaproteome, they were applied to a potting soil high in organic matter and a forest soil. Proteins were analyzed by two-dimensional liquid chromatography/tandem mass spectrometry (2D-LC-MS/MS) and the number of unique spectra as well as the number of assigned proteins for each of the respective protocols was compared. In both soil types, extraction with SDS-phenol (c) resulted in "high" numbers of proteins. Moreover, a spiking experiment was conducted to evaluate protein recovery. To this end sterilized forest soil was amended with proteins from pure cultures of Pectobacterium carotovorum and Aspergillus nidulans. The protein recovery in the spiking experiment was almost 50%. Our study demonstrates that a critical evaluation of the extraction protocol is crucial for the quality of the metaproteomics data, especially in highly complex samples like natural soils.

Influence of litter chemistry and stoichiometry on glucan depolymerization during decomposition of beech (Fagus sylvatica L.) litter.

Glucans like cellulose and starch are a major source of carbon for decomposer food webs, especially during early- and intermediate-stages of decomposition. Litter quality has previously been suggested to notably influence decomposition processes as it determines the decomposability of organic material and the nutrient availability to the decomposer community. To study the impact of chemical and elemental composition of resources on glucan decomposition, a laboratory experiment was carried out using beech (Fagus sylvatica, L.) litter from four different locations in Austria, differing in composition (concentration of starch, cellulose and acid unhydrolyzable residue or AUR fraction) and elemental stoichiometry (C:N:P ratio). Leaf litter was incubated in mesocosms for six months in the laboratory under controlled conditions. To investigate the process of glucan decomposition and its controls, we developed an isotope pool dilution (IPD) assay using (13)C-glucose to label the pool of free glucose in the litter, and subsequently measured the dilution of label over time. This enabled us to calculate gross rates of glucose production through glucan depolymerization, and glucose consumption by the microbial community. In addition, potential activities of extracellular cellulases and ligninases (peroxidases and phenoloxidases) were measured to identify effects of resource chemistry and stoichiometry on microbial enzyme production. Gross rates of glucan depolymerization and glucose consumption were highly correlated, indicating that both processes are co-regulated and intrinsically linked by the microbial demand for C and energy and thereby to resource allocation to enzymes that depolymerize glucans. At early stages of decomposition, glucan depolymerization rates were correlated with starch content, indicating that starch was the primary source for glucose. With progressing litter decomposition, the correlation with starch diminished and glucan depolymerization rates were highly correlated to cellulase activities, suggesting that cellulose was the primary substrate for glucan depolymerization at this stage of decomposition. Litter stoichiometry did not affect glucan depolymerization or glucose consumption rates early in decomposition. At later stages, however, we found significant negative relationships between glucan depolymerization and litter C:N and AUR:N ratio and a positive relationship between glucan depolymerization and litter N concentration. Litter C:N and C:P ratios were negatively related to cellulase, peroxidase and phenoloxidase activities three and six months after incubation, further corroborating the importance of resource stoichiometry for glucan depolymerization after the initial pulse of starch degradation.

Cadmium retention and microbial response in volcanic soils along gradients of soil age and climate on the Galápagos Islands.

The behavior of trace metals may vary strongly in the course of volcanic soil development. Cadmium retention in soils is specifically important for some Galápagos islands where agriculture is leading to anthropogenic Cd contamination. To assess the influence of soil development factors on soil Cd retention and toxicity, we performed Cd sorption-desorption experiments with volcanic topsoils from the Galápagos Islands sampled along gradients of (a) substrate age (chronosequence, 1.5-1,070 ka) and (b) climate (elevation sequence, 47-866 m asl) ranging from arid lowland areas to humid highland areas. Additionally, the effects of Cd toxicity on the soil microbial community composition were evaluated for two soils of the chronosequence. In young volcanic soils, the sorption capacity was very high but decreased rapidly with soil age and increasing elevation. These trends were coupled with decreases in soil weathering indicators (e.g., electrical conductivity, pH, and effective cation exchange capacity) as well as changes in soil mineralogy. Cadmium addition did not influence total phospholipid fatty acids and basal respiration in most soils. However, with increasing Cd concentration, a pronounced reduction in the Gram-negative/Gram-positive bacteria ratio (from 0.32 to 0.12) occurred in an old, highly weathered soil with low Cd retention capacity. Our results show that up to 60% of added Cd was only weakly sorbed in old volcanic soils. As a consequence, the old volcanic soils of Galápagos bear the potential risk that the mobile Cd fraction is taken up by soil microorganisms, transferring this element into the food chain.

Effect of the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) on N-turnover, the N2O reductase-gene nosZ and N2O:N2 partitioning from agricultural soils.

Nitrification inhibitors (NIs) have been shown to reduce emissions of the greenhouse gas nitrous oxide (N2O) from agricultural soils. However, their N2O reduction efficacy varies widely across different agro-ecosystems, and underlying mechanisms remain poorly understood. To investigate effects of the NI 3,4-dimethylpyrazole-phosphate (DMPP) on N-turnover from a pasture and a horticultural soil, we combined the quantification of N2 and N2O emissions with 15N tracing analysis and the quantification of the N2O-reductase gene (nosZ) in a soil microcosm study. Nitrogen fertilization suppressed nosZ abundance in both soils, showing that high nitrate availability and the preferential reduction of nitrate over N2O is responsible for large pulses of N2O after the fertilization of agricultural soils. DMPP attenuated this effect only in the horticultural soil, reducing nitrification while increasing nosZ abundance. DMPP reduced N2O emissions from the horticultural soil by >50% but did not affect overall N2 + N2O losses, demonstrating the shift in the N2O:N2 ratio towards N2 as a key mechanism of N2O mitigation by NIs. Under non-limiting NO3- availability, the efficacy of NIs to mitigate N2O emissions therefore depends on their ability to reduce the suppression of the N2O reductase by high NO3- concentrations in the soil, enabling complete denitrification to N2.

Does Soil Contribute to the Human Gut Microbiome?

Soil and the human gut contain approximately the same number of active microorganisms, while human gut microbiome diversity is only 10% that of soil biodiversity and has decreased dramatically with the modern lifestyle. We tracked relationships between the soil microbiome and the human intestinal microbiome. We propose a novel environmental microbiome hypothesis, which implies that a close linkage between the soil microbiome and the human intestinal microbiome has evolved during evolution and is still developing. From hunter-gatherers to an urbanized society, the human gut has lost alpha diversity. Interestingly, beta diversity has increased, meaning that people in urban areas have more differentiated individual microbiomes. On top of little contact with soil and feces, hygienic measures, antibiotics and a low fiber diet of processed food have led to a loss of beneficial microbes. At the same time, loss of soil biodiversity is observed in many rural areas. The increasing use of agrochemicals, low plant biodiversity and rigorous soil management practices have a negative effect on the biodiversity of crop epiphytes and endophytes. These developments concur with an increase in lifestyle diseases related to the human intestinal microbiome. We point out the interference with the microbial cycle of urban human environments versus pre-industrial rural environments. In order to correct these interferences, it may be useful to adopt a different perspective and to consider the human intestinal microbiome as well as the soil/root microbiome as 'superorganisms' which, by close contact, replenish each other with inoculants, genes and growth-sustaining molecules.

Response of Microbial Communities and Their Metabolic Functions to Drying⁻Rewetting Stress in a Temperate Forest Soil.

Global climate change is predicted to alter drought-precipitation patterns, which will likely affect soil microbial communities and their functions, ultimately shifting microbially-mediated biogeochemical cycles. The present study aims to investigate the simultaneous variation of microbial community compositions and functions in response to drought and following rewetting events, using a soil metaproteomics approach. For this, an established field experiment located in an Austrian forest with two levels (moderate and severe stress) of precipitation manipulation was evaluated. The results showed that fungi were more strongly influenced by drying and rewetting (DRW) than bacteria, and that there was a drastic shift in the fungal community towards a more Ascomycota-dominated community. In terms of functional responses, a larger number of proteins and a higher functional diversity were observed in both moderate and severe DRW treatments compared to the control. Furthermore, in both DRW treatments a rise in proteins assigned to "translation, ribosomal structure, and biogenesis" and "protein synthesis" suggests a boost in microbial cell growth after rewetting. We also found that the changes within intracellular functions were associated to specific phyla, indicating that responses of microbial communities to DRW primarily shifted microbial functions. Microbial communities seem to respond to different levels of DRW stress by changing their functional potential, which may feed back to biogeochemical cycles.

Sample Preparation for Metaproteome Analyses of Soil and Leaf Litter.

Soil and litter metaproteomics, assigning soil and litter proteins to specific phylogenetic and functional groups, has a great potential to shed light on the impact of microbial diversity on soil ecosystem functioning. However, metaproteomic analysis of soil and litter is often hampered by the enormous heterogeneity of the soil matrix and high concentrations of humic acids. To circumvent these challenges, sophisticated protocols for sample preparation have to be applied. This chapter provides the reader with detailed information on well-established protocols for protein extraction from soil and litter samples together with protocols for further sample preparation for subsequent MS analyses.

Biochar application increases sorption of nitrification inhibitor 3,4-dimethylpyrazole phosphate in soil.

Biochar (BC) application to soils is of growing interest as a strategy to improve soil fertility and mitigate climate change. However, BC-induced alterations in the soil N cycle are currently under debate. BC has recently been shown to accelerate the emissions of N2O via the biotic ammonium oxidation pathway, which results in lower nitrogen use efficiency and environmentally harmful losses of NO3 and/ or N2O. To avoid these potential losses, the use of nitrification inhibitor (NI) could provide a useful mitigation strategy for BC-amended agricultural fields. Here, we tested the sorption behavior of a model NI, the synthetic 3,4-dimethylpyrazole phosphate (DMPP) on 15-month-aged soil-BC mixtures. We saw that BC additions increased DMPP sorption to varying extents depending on BC feedstock type and pyrolysis temperature. The highest sorption was found for BC pyrolyzed at a lower temperature. BC effects on soil physico-chemical characteristics (i.e., hydrophobicity) seem to be important factors.

Decoupling of microbial carbon, nitrogen, and phosphorus cycling in response to extreme temperature events.

Predicted changes in the intensity and frequency of climate extremes urge a better mechanistic understanding of the stress response of microbially mediated carbon (C) and nutrient cycling processes. We analyzed the resistance and resilience of microbial C, nitrogen (N), and phosphorus (P) cycling processes and microbial community composition in decomposing plant litter to transient, but severe, temperature disturbances, namely, freeze-thaw and heat. Disturbances led temporarily to a more rapid cycling of C and N but caused a down-regulation of P cycling. In contrast to the fast recovery of the initially stimulated C and N processes, we found a slow recovery of P mineralization rates, which was not accompanied by significant changes in community composition. The functional and structural responses to the two distinct temperature disturbances were markedly similar, suggesting that direct negative physical effects and costs associated with the stress response were comparable. Moreover, the stress response of extracellular enzyme activities, but not that of intracellular microbial processes (for example, respiration or N mineralization), was dependent on the nutrient content of the resource through its effect on microbial physiology and community composition. Our laboratory study provides novel insights into the mechanisms of microbial functional stress responses that can serve as a basis for field studies and, in particular, illustrates the need for a closer integration of microbial C-N-P interactions into climate extremes research.

Soil and leaf litter metaproteomics-a brief guideline from sampling to understanding.

The increasing application of soil metaproteomics is providing unprecedented, in-depth characterization of the composition and functionality of in situ microbial communities. Despite recent advances in high-resolution mass spectrometry, soil metaproteomics still suffers from a lack of effective and reproducible protein extraction protocols and standardized data analyses. This review discusses the opportunities and limitations of selected techniques in soil-, and leaf litter metaproteomics, and presents a step-by-step guideline on their application, covering sampling, sample preparation, extraction and data evaluation strategies. In addition, we present recent applications of soil metaproteomics and discuss how such approaches, linking phylogenetics and functionality, can help gain deeper insights into terrestrial microbial ecology. Finally, we strongly recommend that to maximize the insights environmental metaproteomics may provide, such methods should be employed within a holistic experimental approach considering relevant aboveground and belowground ecosystem parameters.

Adjustment of microbial nitrogen use efficiency to carbon:nitrogen imbalances regulates soil nitrogen cycling.

Microbial nitrogen use efficiency (NUE) describes the partitioning of organic N taken up between growth and the release of inorganic N to the environment (that is, N mineralization), and is thus central to our understanding of N cycling. Here we report empirical evidence that microbial decomposer communities in soil and plant litter regulate their NUE. We find that microbes retain most immobilized organic N (high NUE), when they are N limited, resulting in low N mineralization. However, when the metabolic control of microbial decomposers switches from N to C limitation, they release an increasing fraction of organic N as ammonium (low NUE). We conclude that the regulation of NUE is an essential strategy of microbial communities to cope with resource imbalances, independent of the regulation of microbial carbon use efficiency, with significant effects on terrestrial N cycling.

Who is who in litter decomposition? Metaproteomics reveals major microbial players and their biogeochemical functions.

Leaf-litter decomposition is a central process in carbon cycling; however, our knowledge about the microbial regulation of this process is still scarce. Metaproteomics allows us to link the abundance and activity of enzymes during nutrient cycling to their phylogenetic origin based on proteins, the 'active building blocks' in the system. Moreover, we employed metaproteomics to investigate the influence of environmental factors and nutrients on the decomposer structure and function during beech litter decomposition. Litter was collected at forest sites in Austria with different litter nutrient content. Proteins were analyzed by 1-D-SDS-PAGE followed by liquid-chromatography and tandem mass-spectrometry. Mass spectra were assigned to phylogenetic and functional groups by a newly developed bioinformatics workflow, assignments being validated by complementary approaches. We provide evidence that the litter nutrient content and the stoichiometry of C:N:P affect the decomposer community structure and activity. Fungi were found to be the main producers of extracellular hydrolytic enzymes, with no bacterial hydrolases being detected by our metaproteomics approach. Detailed investigation of microbial succession suggests that it is influenced by litter nutrient content. Microbial activity was stimulated at higher litter nutrient contents via a higher abundance and activity of extracellular enzymes.

The effect of resource quantity and resource stoichiometry on microbial carbon-use-efficiency.

The carbon-use-efficiency (CUE) of microorganisms is an important parameter in determining ecosystem-level carbon (C) cycling; however, little is known about how variance in resources affects microbial CUE. To elucidate how resource quantity and resource stoichiometry affect microbial CUE, we cultured four microorganisms - two fungi (Aspergillus nidulans and Trichoderma harzianum) and two bacteria (Pectobacterium carotovorum and Verrucomicrobium spinosum) - under 12 unique C, nitrogen (N) and phosphorus (P) ratios. Whereas the CUE of A. nidulans was strongly affected by C, bacterial CUE was more strongly affected by mineral nutrients (N and P). Specifically, CUE in P. carotovorum was positively correlated with P, while CUE of V. spinosum primarily depended on N. This resulted in a positive relationship between fungal CUE and resource C : nutrient stoichiometry and a negative relationship between bacterial CUE and resource C : nutrient stoichiometry. The difference in the direction of the relationship between CUE and C : nutrient for fungi vs. bacteria was consistent with differences in biomass stoichiometry and suggested that fungi have a higher C demand than bacteria. These results suggest that the links between biomass stoichiometry, resource demand and CUE may provide a mechanism for commonly observed temporal and spatial patterns in microbial community structure and function in natural habitats.