Organic fertilization reduces nitrous oxide emission by altering nitrogen cycling microbial guilds favouring complete denitrification at soil aggregate scale.

Agricultural management practices can induce changes in soil aggregation structure that alter the microbial nitrous oxide (N2O) production and reduction processes occurring at the microscale, leading to large-scale consequences for N2O emissions. However, the mechanistic understanding of how organic fertilization affects these context-dependent small-scale N2O emissions and associated key nitrogen (N) cycling microbial communities is lacking. Here, denitrification gas (N2O, N2) and potential denitrification capacity N2O/(N2O + N2) were assessed by automated gas chromatography in different soil aggregates (>2 mm, 2-0.25 and <0.25 mm), while associated microbial communities were assessed by sequencing and qPCR of N2O-producing (nirK and nirS) and reducing (nosZ clade I and II) genes. The results indicated that organic fertilization reduced N2O emissions by enhancing the conversion of N2O to N2 in all aggregate sizes. Moreover, potential N2O production and reduction hotspots occurred in smaller soil aggregates, with the degree depending on organic fertilizer type and application rate. Further, significantly higher abundance and diversity of nosZ clades relative to nirK and nirS revealed complete denitrification promoted through selection of denitrifying communities at microscales favouring N2O reduction. Communities associated with high and low emission treatments form modules with specific sequence types which may be diagnostic of emission levels. Taken together, these findings suggest that organic fertilizers reduced N2O emissions through influencing soil factors and patterns of niche partitioning between N2O-producing and reducing communities within soil aggregates, and selection for communities that overall are more likely to consume than emit N2O. These findings are helpful in strengthening the ability to predict N2O emissions from agricultural soils under organic fertilization as well as contributing to the development of net-zero carbon strategies for sustainable agriculture.

Untangling the Complexities of Processing and Analysis for Untargeted LC-MS Data Using Open-Source Tools.

Untargeted metabolomics is a powerful tool for measuring and understanding complex biological chemistries. However, employment, bioinformatics and downstream analysis of mass spectrometry (MS) data can be daunting for inexperienced users. Numerous open-source and free-to-use data processing and analysis tools exist for various untargeted MS approaches, including liquid chromatography (LC), but choosing the 'correct' pipeline isn't straight-forward. This tutorial, in conjunction with a user-friendly online guide presents a workflow for connecting these tools to process, analyse and annotate various untargeted MS datasets. The workflow is intended to guide exploratory analysis in order to inform decision-making regarding costly and time-consuming downstream targeted MS approaches. We provide practical advice concerning experimental design, organisation of data and downstream analysis, and offer details on sharing and storing valuable MS data for posterity. The workflow is editable and modular, allowing flexibility for updated/changing methodologies and increased clarity and detail as user participation becomes more common. Hence, the authors welcome contributions and improvements to the workflow via the online repository. We believe that this workflow will streamline and condense complex mass-spectrometry approaches into easier, more manageable, analyses thereby generating opportunities for researchers previously discouraged by inaccessible and overly complicated software.

How does partial substitution of chemical fertiliser with organic forms increase sustainability of agricultural production?

To ensure global food security, agriculture must increase productivity while reducing environmental impacts associated with chemical nitrogen (N) fertilisation. This necessitates towards more sustainable practices such as recycling organic waste to substitute chemical fertiliser N inputs. However, hitherto how such strategy controls the succession of microbial communities and their relationship with crop yields and environmental impacts have not been comprehensively investigated. We conducted a field experiment with vegetable production in China examining partial substitution (25-50%) of chemical fertiliser with organic forms (pig manure or municipal sludge compost) considering key sustainability metrics: productivity, soil health, environmental impacts and microbial communities. We demonstrate that partial organic substitution improved crop yields, prevented soil acidification and improved soil fertility. Treatments also reduced detrimental environmental impacts with lower N2O emission, N leaching and runoff, likely due to reduced inorganic nitrogen surplus. Microbial communities, including key genes involved in the N cycle, were dynamic and time-dependent in response to partial organic substitution, and were also important in regulating crop yields and environmental impacts. Partial organic substitution increased bacterial diversity and the relative abundance of several specific microbial groups (e.g. Sphingomonadales, Myxococcales, Planctomycetes, and Rhizobiales) involved in N cycling. Additionally, partial organic substitution reduced the number of bacterial ammonia oxidizers and increased the number of denitrifiers, with the proportion of N2O-reducers being more pronounced, suggesting a mechanism for reducing N2O emissions. Comprehensive economic cost-benefit evaluation showed that partial organic substitution increased economic benefit per unit area by 37-46%, and reduced agricultural inputs and environmental impacts per unit product by 22-44%. Among them, 50% substitution of pig manure was the most profitable strategy. The study is crucial to policy-making as it highlights the potential advantages of shifting towards systems balancing chemical and organic fertilisers with economic benefits for farmers, reduced environmental damage and an efficient way for organic waste disposal.

Evaluating the effectiveness of conservation measures for European grassland-breeding waders.

Farmland birds are among the most threatened bird species in Europe, largely as a result of agricultural intensification which has driven widespread biodiversity losses. Breeding waders associated with grassland and arable habitats are particularly vulnerable and a frequent focus of agri-environment schemes (AES) designed to halt and reverse population declines. We review existing literature, providing a quantitative assessment of the effectiveness of policy and management interventions used throughout Europe to improve population and demographic metrics of grassland-breeding waders. Targeted AES and site protection measures were more likely to be effective than less targeted AES and were ten times more likely to be effective than would be expected by chance, particularly for population trend and productivity metrics. Positive effects of AES and site protection did not appear synergistic. Management interventions which had the greatest chance of increasing population growth or productivity included modification of mowing regimes, increasing wet conditions, and the use of nest protection. Success rates varied according to the species and metric being evaluated. None of the policy or management interventions we evaluated were associated with a significant risk of negative impacts on breeding waders. Our findings support the use of agri-environment schemes, site protection, and management measures for grassland-breeding wader conservation in Europe. Due to publication bias, our findings are most applicable to intensively managed agricultural landscapes. More studies are needed to identify measures that increase chick survival. Despite broadly effective conservation measures already in use, grassland-breeding waders in Europe continue to decline. More research is needed to improve the likelihood and magnitude of positive outcomes, coupled with wider implementation of effective measures to substantially increase favorable land management for these species.

Detecting macroecological patterns in bacterial communities across independent studies of global soils.

The emergence of high-throughput DNA sequencing methods provides unprecedented opportunities to further unravel bacterial biodiversity and its worldwide role from human health to ecosystem functioning. However, despite the abundance of sequencing studies, combining data from multiple individual studies to address macroecological questions of bacterial diversity remains methodically challenging and plagued with biases. Here, using a machine-learning approach that accounts for differences among studies and complex interactions among taxa, we merge 30 independent bacterial data sets comprising 1,998 soil samples from 21 countries. Whereas previous meta-analysis efforts have focused on bacterial diversity measures or abundances of major taxa, we show that disparate amplicon sequence data can be combined at the taxonomy-based level to assess bacterial community structure. We find that rarer taxa are more important for structuring soil communities than abundant taxa, and that these rarer taxa are better predictors of community structure than environmental factors, which are often confounded across studies. We conclude that combining data from independent studies can be used to explore bacterial community dynamics, identify potential 'indicator' taxa with an important role in structuring communities, and propose hypotheses on the factors that shape bacterial biogeography that have been overlooked in the past.

Metabolite profiling of non-sterile rhizosphere soil.

Rhizosphere chemistry is the sum of root exudation chemicals, their breakdown products and the microbial products of soil-derived chemicals. To date, most studies about root exudation chemistry are based on sterile cultivation systems, which limits the discovery of microbial breakdown products that act as semiochemicals and shape microbial rhizosphere communities. Here, we present a method for untargeted metabolic profiling of non-sterile rhizosphere soil. We have developed an experimental growth system that enables the collection and analysis of rhizosphere chemicals from different plant species. High-throughput sequencing of 16SrRNA genes demonstrated that plants in the growth system support a microbial rhizosphere effect. To collect a range of (a)polar chemicals from the system, we developed extraction methods that do not cause detectable damage to root cells or soil-inhabiting microbes, thus preventing contamination with cellular metabolites. Untargeted metabolite profiling by UPLC-Q-TOF mass spectrometry, followed by uni- and multivariate statistical analyses, identified a wide range of secondary metabolites that are enriched in plant-containing soil, compared with control soil without roots. We show that the method is suitable for profiling the rhizosphere chemistry of Zea mays (maize) in agricultural soil, thereby demonstrating the applicability to different plant-soil combinations. Our study provides a robust method for the comprehensive metabolite profiling of non-sterile rhizosphere soil, which represents a technical advance towards the establishment of causal relationships between the chemistry and microbial composition of the rhizosphere.