Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions

Towards climate-smart sustainable management of agricultural soils SUstainable Management of soil Organic Matter to MItigate Trade-offs between C sequestration and nitrous oxide, methane and nitrate losses Deliverable D#-WP2.4 Due date of deliverable: M36 Actual submission date: 31 January 2024 Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 2 GENERAL DATA Grant Agreement: 862695 Project acronym: EJP SOIL Project title: Towards climate-smart sustainable management of agricultural soils Project website: www.ejpsoil.eu Start date of the project: February 1st, 2020 Project duration: 60 months Name of lead contractor: INRAE Funding source: H2020-SFS-2018-2020 / H2020-SFS-2019-1 Type of action: European Joint Project COFUND DELIVERABLE NUMBER: D#-WP2.4 DELIVERABLE TITLE: Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions. DELIVERABLE TYPE: Report WORK PACKAGE N: WP2-T3-ST2 Biotic drivers WORK PACKAGE TITLE: Research synthesis and meta-analysis DELIVERABLE LEADER: ENEA (Italy) AUTHORS: ENEA (Italy): Arianna Latini, Luciana Di Gregorio, Manuela Costanzo, Annamaria Bevivino CREA (Italy): Stefano Mocali, Alessandra Lagomarsino, Francesco Vitali EV-ILVO (Belgium) Peter Maenhout LUKE (Finland): Elena Valkama ULBF (Slovenia): Marjetka Suhadolc DISSEMINATION LEVEL: Project Level Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 3 Abstract The current Report has been developed in the frame of WP2-T3, specifically in the Sub-Task ST2 related to biotic drivers. This Sub-Task aims to the realization of a literature survey focusing on the relationships between the soil microbiome and carbon sequestration as well as soil microbiome and non-CO2 GHG emissions in the main European agricultural soil types and pedoclimatic conditions. The efforts were addressed to provide a literature-based synthesis of soil biotic driving forces involved in removing atmospheric carbon dioxide and reducing anthropogenic GHG emissions from soil under different agricultural management practices and organic matter inputs, with respect to changes in soil microbiome composition and other common biodiversity indexes. After a specific interrogation of some of the most known scientific literature databases, a very stringent selection was applied returning 17 useful manuscripts dealing as much as possible with the target content (i.e. soil microbes, carbon sequestration and non-CO2 GHG emissions). The accurate reading and analysis of these manuscripts put in evidence the lack of robust results, also due to the lack of standardization among this kind of studies concerning both the experimental/field set up but also the final data measured under different conditions, to compare the diverse complex outputs. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 4 Table of Contents Abstract ...................................................................................................................................... 3 List of acronyms and abbreviations............................................................................................ 5 Introduction ................................................................................................................................ 6 Soil C sequestration ................................................................................................................ 7 Soil N2O emissions ................................................................................................................. 8 Soil CH4 emissions ................................................................................................................. 9 Soil N leaching ..................................................................................................................... 10 Methods .................................................................................................................................... 10 General methodological approach ........................................................................................ 10 1st approach: Research focus on soil microbial diversity and C sequestration .................... 12 Search on Scopus .............................................................................................................. 13 Search on JSTOR .............................................................................................................. 15 Search on PubMed ............................................................................................................ 15 Search on ScienceDirect ................................................................................................... 16 2nd approach: Research focus on soil microbial diversity and N2O emissions .................... 17 3rd approach: Research based on the trade-offs .................................................................... 18 Scientific manuscripts after the stringent selection .............................................................. 22 Manuscript Card 1: Badagliacca et al. 2022................................................................. 25 Manuscript Card 2: Rosinger et al. 2022 ...................................................................... 28 Manuscript Card 3: Rosinger et al. 2021 ...................................................................... 30 Manuscript Card 4: Badagliacca et al. 2021................................................................. 32 Manuscript Card 5: Rummel et al. 2020....................................................................... 36 Manuscript Card 6: Anastpoulos et al. 2019 ................................................................ 38 Manuscript Card 7: Bachmann et al. 2014 ................................................................... 41 Manuscript Card 8: Lori et al. 2019 .............................................................................. 42 Manuscript Card 9: Zistl-Schlingmann et al. 2020 ...................................................... 44 Manuscript Card 10: Drost et al. 2020 .......................................................................... 46 Manuscript Card 11: Lubbers et al. 2020 ..................................................................... 50 Manuscript Card 12: Niklaus et al. 2016 ...................................................................... 53 Manuscript Card 13: Pena et al. 2013 ........................................................................... 55 Manuscript Card 14: Dicke et al. 2015 ......................................................................... 57 Manuscript Card 15: Panico et al. 2020 ........................................................................ 60 Manuscript Card 16: Ribas et al. 2015 ......................................................................... 63 Manuscript Card 17: Johansen et al. 2013 ................................................................... 65 Discussion and Conclusions ..................................................................................................... 67 References ................................................................................................................................ 68 Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 5 List of acronyms and abbreviations amoA Ammonia Monooxygenase gene AOA Ammonia-Oxidizing Archea (AOA) AOB Ammonia-Oxidizing Bacteria (AOB) BI Biodiversity Index BNF Biological Nitrogen Fixation BR Basal Respiration C Carbon CT Conventional Tillage DHA Dehydrogenase Activity DM Dry Matter DW Dry Weight GHG Greenhouse Gas MBC Microbial Biomass Carbon MBN Microbial Biomass Nitrogen MRT Mean Residence Time nifH Nitrogenase iron protein gene (commonly used as a marker of microbial nitrogen fixation) nirK and nirS Nitrite reductase genes (commonly used as functional marker of denitrifying bacteria) nosZ I and nosZ II Nitrous Oxide Reductase coding genes of clade I and II, respectively NT No Tillage OM Organic Matter OTU Operational Taxonomic Unit PLFAs Phospholipid Fatty Acids SOC Soil Organic Carbon SR Systematic Review TOC Total Organic Carbon Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 6 Introduction Management of agricultural soils and land use change from forest and extensively managed vegetations to intensively managed vegetations and field crops represent a significant source of greenhouse gas (GHG) emissions (mainly carbon dioxide, methane and nitrous oxide). However, at the same time, they have an uncovered potential to mitigate them depending on the land use and management [Paustian et al. 2016]. To increase soil carbon (C) inputs numerous mitigation practices may be applied in agricultural ecosystems, such as reduced or no tillage (NT) instead of intensive conventional tillage (CT), or crop rotations instead of monoculture cropping. According to Tonitto et al. (2006), cover crops, besides increasing soil C content, reduce nutrient losses, including nitrate that would have been converted to N2O; thus, cover crops represent an example of practice that has two beneficial effects by sequestering C and by limiting the N cycle and so reducing N2O emissions. Interestingly, in a systematic analysis, Abdalla et al. (2019) assessed that cover crops may significantly decrease N leaching and increase soil organic carbon (SOC) sequestration without significant effects on direct N2O emissions. The meta-analysis conducted by Guenet et al. (2020) revealed that increased N2O emissions are not sufficient to invalidate the GHG abatement potential achieved by SOC sequestration strategies, except for reduced tillage practices. Moreover, there is few evidence that some sequestration strategies as application of biochar or non-pyrogenic organic amendment may generate win–win situations through a decrease in N2O emissions [Guenet et al. 2020]. Recently, effective measures and technologies for GHG emission reduction have been proposed in agricultural soil, mainly including adding biological soil amendments, as returning straw to the field, and applying organic fertilizer or microalgae biofertilizer and soil improvers (such as lime and nitrification inhibitor, etc.), as well as applying biochar. Based on numerous evidence, soil microorganisms play a crucial role in the application of these mitigation measures and technologies, but studies on this role of microorganisms in GHG emissions from farmland are still not sufficient [Wang H. et al. 2022]. At this regard, the high microbial diversity existing in soils needs to be evidenced: a soil sample typically contains thousands of individual taxa (“operational taxonomic units”, OTU) of Bacteria, Archaea, and Fungi. According to Fierer et al. (2007), there can be more than 106 individual species-level OTUs in a single soil. As highlighted by Paustian et al. (2016), in order to expand the role of agricultural soil in GHG mitigation, integrated research support and implementation are required. Targeted basic research on soil processes, expanding measurement and monitoring networks, and further developing global geospatial soils management practices through web-based computer and mobile apps, and help drive advanced model-based GHG metrics. This will facilitate the implementation of climate-smart soil management policies, via cap-and-trade systems, product supply-chain initiatives for ‘low-carbon’ consumer products, and national and international GHG mitigation policies; it will also promote more sustainable and climate-resilient agricultural systems, globally [Fig. 1]. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 7 Figure 1. Altogether and integrated with each other, science and technology, agricultural practices and their implementation must be favoured for increasing the potential and efficacy of agricultural soil GHG mitigation strategies (proceeding from Paustian et al. 2016). Among the parameters used to depict the soil microbial status and composition, microbial biomass (MB) and activity have often been considered as potential indicators of soil quality as well as soil functioning (as ecosystem service provider). Indeed, MB as well as microbial activity are strictly related to the soil living component and are rapidly influenced by any management practices that alter the soil microbiota [Panettieri et al. 2020; Bandyopadhyay and Maiti 2022]. For example, soil MB and main microbial groups exhibited different or no effects to the different applied tillage system. However, the response of soil microorganisms is site specific, depending on the contexts in which tillage systems are adopted, based on climate, soil type, fertility, other management practices, etc. [Badagliacca et al. 2021]. Soil C sequestration Soil carbon sequestration is a process in which CO2 is removed from the atmosphere and stored in the soil carbon pool. This process is primarily mediated by plants through photosynthesis, with carbon stored in the form of SOC. Co-benefits of soil C sequestration include advancing food and nutritional security, increasing renewability and quality of water, improving biodiversity, and strengthening elemental recycling. In the root zone, SOC threshold level is about 1.5–2.0%. SOC is influenced by land use, soil management and farming systems. To 1 m depth, more than 50% total C pool is contained between 0.3 and 1 m depth. Soils of agroecosystems are strongly depleted of their SOC stock and are degraded. Restoring soil quality necessitates increasing SOC concentration by adopting best management practices (i.e., conservation agriculture) which create a positive C budget [Lal et al. 2015]. Carbon is stored in terrestrial ecosystems in diverse organic forms with a wide range of mean residence times (MRT), corresponding to the average time a carbon atom spends in a given pool [Watson et al. 2000]. Generally, carbon sequestration in soil refers “to capture and secure by storage of atmospheric CO2 with pedosphere in a manner that also increases its mean residence time (MRT) and minimizes sinks of re-emission” [Lal 2007]. Microorganisms are the main players in the processes of soil organic matter (OM) decomposition and transformation through diverse metabolic pathways; consequently, they play a pivotal role in carbon cycling within soil systems, returning carbon that enters the soil from above ground plant production to the atmosphere as CO2, and contribute to the Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 8 stabilization of organic carbon, thereby influencing soil carbon storage and turnover [Fig. 2; Wu et al. 2024]. Interestingly, bacterial network interactions are positively associated with C fixation rate [Fig. 2] and, for example, the Proteobacteria connect and promote other species to fix CO2 [Li et al. 2021]. Figure 2. Soil microbiome plays a major role in determining atmospheric CO2 and soil organic carbon content, under the influence of diverse biotic and abiotic drivers (proceeding from Wu et al. 2024). Soil N2O emissions Nitrous oxide (N2O) is a critical GHG with 310 times more global warming potential than CO2 and ozone depleter released by microbes, and indeed N2O emissions resulted correlated with functional diversity of microbes [Baharam et al. 2022]. It has been demonstrated that the application of mineral fertilizers (ammonium-based) stimulates N2O emissions form soils [Lebender et al. 2017]. Wang J. et al. (2018) put in evidence that non-fertilized soils can have up to 78% less denitrification than ammonium nitrate fertilized soils. Microbial activity, particularly nitrification and denitrification, is the main responsible for N2O production in soils. During nitrification, ammonium added as fertilizer, fixed from the atmosphere by legumes, or mineralized from soil organic matter (OM), crop residue, or other inputs is oxidized to nitrite and eventually to nitrate in a series of reactions that can also produce N2O. Likewise, when denitrifiers use nitrate as an electron acceptor when soil oxygen is low, N2O is an intermediate product that can readily escape to the atmosphere [Paustian et al. 2016]. When crops compete with microbes for available N, N2O fluxes are lower. For example, biochar represents a key soil remediation product; according to Kaur et al. (2022) it favours the reduction of soil GHG emissions up to 38.8% in a microbial-mediated way. For investigating the specific role of the nitrogen cycling microbial community in mitigating N2O emissions, Harter et al. (2014) quantified the abundance and activity of functional marker genes of microbial nitrogen fixation (nifH), nitrification (amoA) and denitrification (nirK, nirS and nosZ) by qPCR, and found that biochar promoted microbial N2O reduction and an increase in the abundance of microorganisms capable of N2-fixation. The short-term addition of biochar to Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 9 rice soil increased the abundance of ammonia-oxidizing bacteria (AOB) and ammonia monooxygenase gene (amoA), and significantly increased the denitrification rate of the soil. Fresh biochar provided a stronger alkaline environment and nutrients, and even improved the denitrification capacity and nitrogen emission [He et al. 2019]. Biochar and nitrogen fertilizer supplement to acidic soil characterized by high N2O emissions leads to several effects, including an elevation of soil pH, alterations in fungal community composition, suppression of fungal denitrification, a notable decrease in fungal abundance, an increase in the prevalence of the nosZ gene, heightened N2O reductase activity, and promotion of bacterial conversion of N2O to N2 [Ji et al. 2022; Fig. 3]. nosZ are N2O reductase coding genes widely existing in the environment; these belong to two phylogenetically distinct clades, which are referred to as nosZ I and nosZ II [Johnes et al. 2013]. Studies have shown that microbes containing the nosZ II gene have greater N2O reduction potential. Some microbes containing the nosZ II gene lack the nitrite reductase gene, so they do not produce N2O during denitrification, which provides a new research idea for N2O emission reduction in the future [Hallin et al. 2018; Wang H. et al. 2022]. Figure 3. Soil acidification is a potentially serious land degradation issue that can impact agricultural productivity and sustainable farming systems. The scheme represents the potential mechanism of N2O emission reduction following biochar amendment from acidic soils (proceeding from Wang H. et al. 2022). Soil CH4 emissions More than one third of global methane emissions occur through the microbial breakdown of organic compounds in soil under anaerobic conditions. Indeed, terrestrial ecosystems alter emissions and removal of the atmospheric CH4 in soils. More in details, methanogenic (CH4 producing) and methanotrophic (CH4 consuming) microorganisms are both present in soils, and both CH4 production and oxidation occur simultaneously. Emissions of biogenic CH4 from soils would be significantly larger if not for the methanotrophic microorganisms that oxidize Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 16 AND “Cseq*” → 8 results AND “C seq*” → 400 results AND “C stor*” → 200 results AND “C cycl*” → 280 results AND “carbon seq*” → 1,259 results AND “carbon stor*” → 397 results AND “carbon cycl*” → 1,437 results. Search on ScienceDirect ScienceDirect (https://www.sciencedirect.com/search) limits the number of Boolean operators (max 8); thus, an independent search has been performed for each intervention term. Moreover, “*” is not allowed, and Boolean precedence is as follows: 1) NOT, 2) AND, 3) OR. At the time of the analysis (September 2002), only these organic matter inputs - crop residue, cover crop, livestock manure and slurry - were included as keywords. Indeed, it has been necessary to carry out separated searches per OM input. In total, the output of this search was the following: “crop residue” returned 464 references “cover crop” returned 241 references “livestock manure” returned 110 references “slurry” returned 276 references. Among the four cover crops, some references overlapped. For example, in the case of “slurry”, 117 out of 276 references were unique for “slurry”. The total number of the raw unique references that should be screened considering the four OM inputs together, from ScienceDirect, was equal to 699. At first glance, such 1st approach above reported focusing on soil microbial diversity and C sequestration put in evidence the high presence of general articles, mentioning the searched keywords in the context of the Introduction and the Discussion of several papers, without providing the numerical data and/or information useful to answer the research question. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 17 Furthermore, it has been assessed that Scopus, PubMed and JSTOR returned a “manageable” number of records than ScienceDirect. Another outcome emerging from this initial study was the need to find strategies to perform (automated) actions more quickly; for example, simplifying the export of data from ScienceDirect into Excel, searching duplicate reports in the xls. file, and others. At the end, the working group decided not to bring to conclusion this 1st approach for the above-mentioned reasons, but also for additional motivations explained in the below section. 2nd approach: Research focus on soil microbial diversity and N2O emissions After the preliminary approach based on C sequestration resulting in a very large and dispersive number of research studies, at the time of this work, it was proposed to address a focus on the relationships between soil microbial diversity and N2O emissions. At this aim, a keyword search was performed on PubMed and ScienceDirect. Besides the general terms related to microorganisms [microb* OR (microorganism* OR arch* OR bact* OR fung*)], several microbial parameters related to abundance and diversity were searched: “microbial biomass”, “microbial composition”, “Shannon”, “Simpson”, OTU, ASV, richness, metadata and meta-data, diversity. Articles were kept separated for OM input. Thus, the PICO question was formulated in this way: “What is the effect of EU OM strategies respect to the NO fertilization or mineral fertilization on microbes related to N2O emissions in EU agricultural soil?”, which is similar to the following sentence: Where: P the population corresponds to microbes/bacteria/fungi; I the intervention corresponds to the application of OM inputs/strategies; C inorganic fertilization or NO fertilization; O effect on N2O emissions. When looking at the specific microbiological parameter, the number of articles significantly decreased, resulting in less than 5 articles per microbiological parameter searched in PubMed. Differently, in ScienceDirect, for example, looking only at “cover crop” as OM input, about 100 articles were identified using the term “microbial biomass” and up to 200 articles using the term “diversity”. When using more specific terms, as “Shannon”, “Simpson”, “OUT”, “ASV”, and others, only few articles were retrieved. During the definition of the procedure for this study, it was attempted a list of data/information to be found in the Full-Text of the selected articles, including among others: • microbial biomass C (MBC) in μg g-1 DM (soil dry matter) with respect to Corg in g per kg soil DM; • microbial biomass N (MBN) in μg g−1 DW; Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 18 • changes in microbial community structure, microbial abundance; effects on microbial functioning; • biomass of functional microbial groups by extraction of phospholipid fatty acids (PLFAs); • functional microbial genes related to N2O emissions (nitrification and denitrification functional genes) as determined by DNA extraction and qPCR analyses; taxonomic distribution of denitrifier and N2O reducing bacteria and archaea; • biological nitrogen fixation (BNF) in kg/ha; • soil enzymes activities: dehydrogenase activity (DHA), alkaline phosphatase and acid phosphatase, beta-glucosidase phosphatase, urease, catalase, invertase, phenol oxydase FDAse, ammonia-oxidising archaea (AOA) and ammonia-oxidising bacteria (AOB), etc. • soil respiration rates for a 30-days incubation period; • soil bacterial communities, enriched phyla,… Concerning this 2nd approach, in the table below the results of the number of articles retrieved from PubMed (https://pubmed.ncbi.nlm.nih.gov) in a search carried out on 20 of October 2022 are reported. As in the previous searches, also this search was limited to articles (excluding clinical trials) in English from 2005. Searched terms Number of records “nitrous oxide” AND emission* AND soil* AND (agro* OR agri* OR farm*) AND europe* AND microb* OR (microorganism* OR arch* OR bact* OR fung*) 210,192 AND “cover crop*” 11 AND “crop residue*” 22 AND “manure*” 215 AND “mulch*” 25 AND “slurr*” 40 AND “compost” 100 AND “biochar*” 176 AND “digestate” 17 AND “sludge*” 452 AND “organic matter*” 556 AND amendment* 241 With the exception of the first row, which includes the sentence used in the query with all the specific keywords connected by the Boolean operators, the following rows in the table are specific for the OM inputs. Interestingly, the results show that the most investigated OM inputs are, in sequence from the most cited, sludge, manure, biochar and compost. As additional information, the following microbiological parameters have also been tested in the query but returned zero records: “microbial biomass”, “microbial composition”, “Shannon”, “Simpson”, OTU, ASV, richness, metadata, meta-data, diversity. 3rd approach: Research based on the trade-offs Finally, the 3rd approach addressed soil microbial diversity in relation to the trade-offs between C seq and N2O and other non-CO2 GHG emissions. The PICO question was formulated in this Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 19 way: “What are the effects of EU OM fertilization on microbes in relation to carbon sequestration and N2O emissions in EU agricultural soil?”, which is similar to the following sentence: Where: P the population corresponds to microbes/bacteria/fungi in EU agricultural soils; I the intervention corresponds to the application of OM inputs/strategies; C the comparator may be mineral fertilizer or no fertilizer, but this is not included among the searched keywords; Outcome 1 effects on soil microbiome diversity; Outcome 2 effects on N2O emissions; Outcome 3 effects on C sequestration. Concerning the addition of OM inputs, the following ones were considered: crop residues, cover crop (green manure, mulch), livestock manure, slurry, compost, biochar, digestate, sludge. The search on the database included the following keywords resulting from the PICO question: P – keywords for the Population term soil*, agr*, farm* europe* I – keywords for the Intervention term “crop residue*”, “cover crop*”, manure, mulch, slurry, compost, biochar, digestate, sludge, “organic matter”, OM, amendment C (not used) O1 – keywords for the Outcome 1 term microb*, microorgani*, arche*, bacteria*, fung* O2 – keywords for the Outcome 2 term “N2O emission*”, “nitrous oxide emission*” O3 – keywords for the Outcome 3 term Cseq*, “C seq*”, “C stor*”, “C cycl*”, “carbon seq*”, “carbon stor*”, “carbon cycl*” The main search was conducted in March 2023 on Scopus (https://www.scopus.com/search/form.uri?display=basic#basic), within “Documents” < “All fields”. Below the sentence used in the query: soil* AND (agr* OR farm*) AND (europe* OR EU) AND (“crop residue*” OR “cover crop*” OR manure OR mulch OR slurry OR compost OR biochar OR digestate OR sludge OR "organic matter" OR OM OR amendment*) AND (microb* OR microorganism* OR arche* OR bacteri* OR fung*) AND (“N2O emission*” OR “nitrous oxide emission*”) AND (“C seq*” OR “C stor*” OR “C cycl*” OR “carbon seq*” OR “carbon stor*” OR “carbon cycl*”). The different colours reflect these indications: Population terms, Intervention terms, Outcome 1 terms, Outcome 2 terms, Outcome 3 terms. Below the results a cording the PRISMA procedure: • starting from 5,273 total initial items; Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 20 • search limited to only English manuscript: 5,100 items; • search limited to only Journal articles: 4,590 items; • search limited to article and review (as document types): 4,541 items; • search limited to documents after 2005: 449 items; • after exclusion of manuscripts from Non-EU countries: 739 items; • after exclusion of subject areas out of interest: 619 items. The new, enhanced version of the search results page is available. Try the new version 619 document results ALL ALL ( ( soil* soil* AND AND ( ( agr* agr* OR OR farm* farm* ) ) AND AND ( ( europe* europe* OR OR eu eu ) ) AND AND ( ( "crop residue*" "crop residue*" OR OR "cover crop*" "cover crop*" OR OR manure manure OR OR mulch mulch OR OR slurry slurry OR OR compost compost OR OR biochar biochar OR OR digestate digestate OR OR sludge sludge OR OR "organic "organic matter" matter" OR OR om om OR OR amendment* amendment* ) ) AND AND ( ( microb* microb* OR OR microorganism* microorganism* OR OR arche* arche* OR OR bacteri* bacteri* OR OR fung* fung* ) ) AND AND ( ( "N2O emission*" "N2O emission*" OR OR "nitrous oxide emission*" "nitrous oxide emission*" ) ) AND AND ( ( "C seq*" "C seq*" OR OR "C stor*" "C stor*" OR OR "C cycl*" "C cycl*" OR OR "carbon seq*" "carbon seq*" OR OR "carbon stor*" "carbon stor*" OR OR "carbon cycl*" "carbon cycl*" ) ) ) ) AND AND ( ( LIMIT-TO LIMIT-TO ( ( LANGUAGE LANGUAGE , , "English" "English" ) ) ) ) AND AND ( ( LIMIT-TO LIMIT-TO ( ( SRCTYPE SRCTYPE , , "j" "j" ) ) ) ) AND AND ( ( LIMIT-TO LIMIT-TO ( ( DOCTYPE DOCTYPE , , "ar" "ar" ) ) OR OR LIMITLIMITTO TO ( ( DOCTYPE DOCTYPE , , "re" "re" ) ) ) ) AND AND ( ( LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2023 2023 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2022 2022 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2021 2021 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2020 2020 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2019 2019 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2018 2018 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2017 2017 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2016 2016 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2015 2015 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2014 2014 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2013 2013 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2012 2012 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2011 2011 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2010 2010 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2009 2009 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2008 2008 ) ) OR OR LIMIT-TO LIMIT-TO ( ( PUBYEAR PUBYEAR , , 2007 2007 ) ) ... ... ! 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All CSV export ! Download View citation overview View cited by Save to list … * + , 1Combined e ects of long-term tillage and fertilisation regimes on soil organic carbon, microbial biomass, and abundance of the total microbial communities and N-functional guilds Govednik, A. Potočnik, Z. Eler, K. Mihelič, R. Suhadolc, M. Applied Soil Ecology ! View abstract Related documents 2Conventional tillage versus no-tillage: Nitrogen use e ciency component analysis of contrasting durum wheat genotypes grown in a Mediterranean environment Ingra a, R. Lo Porto, A. Ruisi, P. Giambalvo, D. Frenda, A.S. Field Crops Research ! View abstract Related documents 3Variation in methane uptake by grassland soils in the context of climate change – A review of e ects and mechanisms Rafalska, A. Walkiewicz, A. Osborne, B. Klumpp, K. Bieganowski, A. Science of the Total Environment ! View abstract Related documents 4Role of dry watercourses of an arid watershed in carbon and nitrogen processing along an agricultural impact gradient Arce, M.I. Sánchez-García, M. Martínez-López, J. Cayuela, M.L. Sánchez-Monedero, M.Á. Journal of Environmental Management ! View abstract Related documents 5Evaluation of a crop rotation with biological inhibition potential to avoid N O emissions in comparison with synthetic nitri cation inhibition 2 Bozal-Leorri, A. CorrochanoMonsalve, M. Arregui, L.M. Aparicio-Tejo, P.M. González-Murua, C. Journal of Environmental Sciences (China) 3 ! View abstract Related documents 6Nitrogen dynamics in soils fertilized with digestate and mineral fertilizers: A full eld approach Zilio, M. Pigoli, A. Rizzi, B. Schoumans, O. Adani, F. Science of the Total Environment ! View abstract Related documents 7Long-term C and N sequestration under no-till is governed by biomass production of cover crops rather than di erences in grass vs. legume biomass quality Ardenti, F. Capra, F. Lommi, M. Fiorini, A. Tabaglio, V.Soil and Tillage Research ! View abstract Related documents 8High greenhouse gas emissions a er grassland renewal on bog peat soil O ermanns, L. Tiemeyer, B. Dettmann, U. Vogel, I. Brümmer, C. Agricultural and Forest Meteorology ! View abstract Related documents 9Carbon farming: Are soil carbon certi cates a suitable tool for climate change mitigation? Paul, C. Bartkowski, B. Dönmez, C. Wolf, A. Helming, K. Journal of Environmental Management ! View abstract Related documents 10 Conservation Agriculture and Soil Organic Carbon: Principles, Processes, Practices and Policy Options Francaviglia, R. Almagro, M. Vicente-Vicente, J.L. Soil Systems ! View abstract Related documents 11 Biochar with Inorganic Nitrogen Fertilizer Reduces Direct Greenhouse Gas Emission Flux from Soil Ayaz, M. Feizienė, D. Tilvikienė, V. Baltrėnaitė-Gedienė, E. Ullah, S. Plants ! View abstract Related documents 12 In uence of rewetting on N O emissions in three di erent fen types 2Berendt, J. Jurasinski, G. WrageMönnig, N.Nutrient Cycling in Agroecosystems 1 ! View abstract Related documents 13 Impacts of slurry acidi cation and injection on fertilizer nitrogen fates in grassland Schreiber, M. Bazaios, E. Ströbel, B. Kiese, R. Dannenmann, M. Nutrient Cycling in Agroecosystems 1 ! View abstract Related documents 14 Nitrogen ow in livestock waste system towards an e cient circular economy in agriculture Doyeni, M.O. Barcauskaite, K. Buneviciene, K. Suproniene, S. Tilvikiene, V. Waste Management and Research 2 ! View abstract Related documents 15 Assessment of Earthworm Services on Litter Mineralisation and Nutrient Release in Annual and Perennial Energy Crops (Zea mays vs. Silphium perfoliatum) Wöhl, L. Ruf, T. Emmerling, C. Thiele, J. Schrader, S. Agriculture (Switzerland) ! View abstract Related documents 16 The use of double-cropping in combination with no-tillage and optimized nitrogen fertilization reduces soil N O emissions under irrigation 2 Fernández-Ortega, J. Álvaro-Fuentes, J. Cantero-Martínez, C. Science of the Total Environment ! View abstract Related documents 17 Nutrient release and ux dynamics of CO , CH , and N O in a coastal peatland driven by actively induced rewetting with brackish water from the Baltic Sea 2 4 2 Pönisch, D.L. Breznikar, A. Gutekunst, C.N. Voss, M. Rehder, G. Biogeosciences 1 ! View abstract Related documents 18 The crucial interactions between climate and soil Certini, G. Scalenghe, R. Science of the Total Environment 1 ! View abstract Related documents 19 Soil and crop management practices and the water regulation functions of soils: a qualitative synthesis of meta-analyses relevant to European agriculture Blanchy, G. Bragato, G. Di Bene, C. Meurer, K. Garré, S. SOIL ! View abstract Related documents 20 Analysis of the Use of Biochar from Organic Waste Pyrolysis in Agriculture and Environmental Protection Niedziński, T. Łabętowicz, J.Stępień, W. Pęczek, T. Journal of Ecological Engineering ! View abstract Related documents 21 Short-term Response of Greenhouse Gas Emissions from Precision Fertilization on Barley Fabbri, C. Dalla Marta, A. Napoli, M. Orlandini, S. Verdi, L. Agronomy ! View abstract Related documents 22 Identifying criteria for greenhouse gas ux estimation with automatic and manual chambers: A case study for N O 2 Pullens, J.W.M. Abalos, D. Petersen, S.O. Pedersen, A.R. European Journal of Soil Science 1 ! View abstract Related documents 23 Soil structure and microbiome functions in agroecosystems Hartmann, M. Six, J. Nature Reviews Earth and Environment 4 ! View abstract Related documents 24 Pore distances of particulate organic matter predict N O emissions from intact soil at moist conditions 2Ortega-Ramírez, P. Pot, V. Laville, P. Henault, C. Garnier, P.Geoderma ! View abstract Related documents 25 Soil greenhouse gas emissions and crop production with implementation of alley cropping in a Mediterranean citrus orchard Sánchez-Navarro, V. MartínezMartínez, S. Acosta, J.A. PérezPastor, A. Zornoza, R. European Journal of Agronomy ! View abstract Related documents 26 Impacts of monoculture cropland to alley cropping agroforestry conversion on soil N O emissions 2 Shao, G. Martinson, G.O. Corre, M.D. Bischel, X. Veldkamp, E. GCB Bioenergy 2 ! View abstract Related documents 27 Cycles of carbon, nitrogen and phosphorus in poultry manure management technologies–environmental aspects Kacprzak, M. Malińska, K. Grosser, A. Jasińska, A. Meers, E. Critical Reviews in Environmental Science and Technology 4 ! View abstract Related documents 28 The ability of crop models to predict soil organic carbon changes in a maize cropping system under contrasting fertilization and residues management: Evidence from a long-term experiment Pulina, A. Ferrise, R. Mula, L. Grignani, C. Roggero, P.P.Italian Journal of Agronomy 1 ! View abstract Related documents 29 Micro-fractionation shows microbial community changes in soil particles below 20 m Keuschnig, C. Martins, J.M.F. Navel, A. Simonet, P. Larose, C. Frontiers in Ecology and Evolution 1 ! View abstract Related documents 30 E ects of Combined Use of Olive Mill Waste Compost and Sprinkler Irrigation on GHG Emissions and Net Ecosystem Carbon Budget under Di erent Tillage Systems Fernández-Rodríguez, D. Fangueiro, D.P. Peña Abades, D. Vicente, L.A. López-Piñeiro, A. Plants ! View abstract Related documents 31 Early E ects of No-Till Use on Durum Wheat (Triticum durum Desf.): Productivity and Soil Functioning Vary between Two Contrasting Mediterranean Soils Badagliacca, G. Lo Presti, E. Ferrarini, A. Monti, M. Preiti, G. Agronomy ! View abstract Related documents 32 Variation of Soil Nitrogen, Organic Carbon, and Waxy Wheat Yield Using Liquid Organic and Mineral Fertilizers Petraityte, D. Ceseviciene, J. Arlauskiene, A. Skersiene, A. Gecaite, V. Agriculture (Switzerland) 1 ! View abstract Related documents 33 Multicriteria assessment of conservation agriculture systems Adeux, G. Guinet, M. Courson, E. Munier-Jolain, N. Cordeau, S. Frontiers in Agronomy ! 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View abstract Related documents 41 E ects of Biochar on the C Use E ciency of Soil Microbial Communities: Components and Mechanisms Giagnoni, L. Renella, G. Environments - MDPI ! View abstract Related documents 42 The e ect of pyrolysis temperature and feedstock on biochar agronomic properties Lataf, A. Jozefczak, M. Vandecasteele, B. Cuypers, A. Vandamme, D. Journal of Analytical and Applied Pyrolysis 3 ! View abstract Related documents 43 Comparison between organic and conventional farming systems using Life Cycle Assessment (LCA): A case study with an ancient wheat variety Verdi, L. Marta, A.D. Falconi, F. Orlandini, S. Mancini, M. European Journal of Agronomy 3 ! View abstract Related documents 44 Determining the environmental and economic implications of lupin cultivation in wheat-based organic rotation systems in Galicia, Spain Rebolledo-Leiva, R. Almeida-García, F. Pereira-Lorenzo, S. Moreira, M.T. González-García, S. Science of the Total Environment ! View abstract Related documents 45 Summer greenhouse gas uxes in di erent types of hemiboreal lakes Rõõm, E.-I. Lauringson, V. Laas, A. Nõges, P. Nõges, T.Science of the Total Environment ! View abstract Related documents 46 Soil organic C and N stock changes in grass-clover leys: E ect of grassland proportion and organic fertilizer Jensen, J.L. Beucher, A.M. Eriksen, J. Geoderma 1 ! View abstract Related documents 47 E ects of biochar and ligneous soil amendments on greenhouse gas exchange during extremely dry growing season in a Finnish cropland Kulmala, L. Peltokangas, K. Heinonsalo, J. Liski, J. Lohila, A. Frontiers in Sustainable Food Systems ! View abstract Related documents 48 Mapping the restoration of degraded peatland as a research area: A scientometric review Apori, S.O. Mcmillan, D. Giltrap, M. Tian, F. Frontiers in Environmental Science ! View abstract Related documents 49 Comparison of the Responses of Soil Enzymes, Microbial Respiration and Plant Growth Characteristics under the Application of Agricultural and Food Waste-Derived Biochars Mustafa, A. Holatko, J. Hammerschmiedt, T. Malicek, O. Brtnicky, M. Agronomy ! View abstract Related documents 50 E ects of sewage sludge hydrochar on emissions of the climaterelevant trace gases N O and CO from loamy sand soil 2 2 Joshi, A. Breulmann, M. Schulz, E. Ruser, R. Heliyon ! View abstract Related documents 51 Field evidence for litter and self-DNA inhibitory e ects on Alnus glutinosa roots Bonanomi, G. Zotti, M. Idbella, M. De Micco, V. Mazzoleni, S. New Phytologist 1 ! View abstract Related documents 52 Greenhouse gas emissions from a sandy loam soil amended with digestate-derived biobased fertilisers – A microcosm study Egene, C.E. Regelink, I. Sigurnjak, I. Tack, F.M.G. Meers, E. Applied Soil Ecology ! View abstract Related documents 53 Plant functional type a ects nitrogen dynamics in urban park soils similarly to boreal forest soils Lu, C. Kotze, D.J.Setälä, H.M. Plant and Soil 1 ! View abstract Related documents 54 How can leaf-litter from di erent species growing in short rotation coppice contribute to the soil nutrient pool? González, I. Sixto, H. RodríguezSoalleiro, R. Fuertes, A. Oliveira, N. Forest Ecology and Management 1 ! View abstract Related documents 55 Catchment properties as predictors of greenhouse gas concentrations across a gradient of boreal lakes Valiente, N. Eiler, A. Allesson, L. de Wit, H.A. Hessen, D.O.Frontiers in Environmental Science 1 ! View abstract Related documents 56 The E ects of Cover Crops on Multiple Environmental Sustainability Indicators—A Review Rivière, C. Béthinger, A. Bergez, J.-E. Agronomy ! View abstract Related documents 57 Interaction of Biochar with Chemical, Green and Biological Nitrogen Fertilizers on Nitrogen Use E ciency Indices Ghorbani, M. Konvalina, P. Neugschwandtner, R.W. Bucur, D. Walkiewicz, A. Agronomy 10 ! View abstract Related documents 58 Plant N economics and the extended phenotype: Integrating the functional traits of plants and associated soil biota into plant–plant interactions Fernandez, M. Vernay, A. Henneron, L. Malagoli, P. Balandier, P.Journal of Ecology 2 ! View abstract Related documents 59 Soil-tree-atmosphere CH ux dynamics of boreal birch and spruce trees during spring leaf-out 4Vainio, E. Haikarainen, I.P. Machacova, K. Tuomivirta, T. Pihlatie, M. Plant and Soil ! View abstract Related documents 60 Frost killed cover crops induced high emissions of nitrous oxide Olofsson, F. Ernfors, M. Science of the Total Environment ! 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Petersen, S.O. Munkholm, L.J. Agronomy for Sustainable Development 3 ! View abstract Related documents 78 The carbon footprint of milk during the conversion from conventional to organic production on a dairy farm in central Germany Gross, A. Bromm, T. Polifka, S. Schierhorn, F. Agronomy for Sustainable Development 1 ! View abstract Related documents 79 Soil greenhouse gas uxes in oodplain forests of the Danube National Park: e ects of ooding and soil microclimate Schindlbacher, A. Heinzle, J. Gollobich, G. Michel, K. Kitzler, B. Biogeochemistry 2 ! View abstract Related documents 80 Long-term manipulation of mean climatic conditions alters drought e ects on Cand N-cycling in an arable soil Leyrer, V. Patulla, M. Hartung, J. Marhan, S. Poll, C. Global Change Biology 3 ! View abstract Related documents 81 Rotational pasture management to increase the sustainability of mountain livestock farms in the Alpine region Baronti, S. Ungaro, F. Maienza, A. Robbiati, G. Vaccari, F.P.Regional Environmental Change 5 Brought to you bySistema Biblioteche ENEA Search Sources SciVal AL Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 21 Terms and conditions Privacy policy Copyright © Elsevier B.V . All rights reserved. Scopus® is a registered trademark of Elsevier B.V. We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies . Analyze search results 619 document results Select year range to analyze: to Click on cards below to see additional data. ◅ Back to results Export Print Email ALL ( soil* AND ( agr* OR farm* ) AND ( europe* OR eu ) AND ( "crop residue*" OR "cover crop*" OR manure OR mulch OR slurry OR compost OR biochar OR digestate OR sludge OR "organic matter" OR om OR amendment* ) AND ( microb* OR microorganism* OR arche* OR bacteri* OR fung* ) AND ( "N2O emission*" OR "nitrous oxide emission*" ) AND ( "C seq*" OR "C stor*" OR "C cycl*" OR "carbon seq*" OR "carbon stor*" OR "carbon cycl*" ) ) AND ( LIMIT-TO ( LANGUAGE , "English" ) ) AND ( LIMIT-TO ( SRCTYPE , "j" ) ) AND ( LIMIT-TO ( DOCTYPE , "ar" ) OR LIMITTO ( DOCTYPE , "re" ) ) AND ( LIMIT-TO ( PUBYEAR , 2023 ) OR LIMIT-TO ( PUBYEAR , 2022 ) OR LIMIT-TO ( PUBYEAR , 2021 ) OR LIMIT-TO ( PUBYEAR , 2020 ) OR LIMIT-TO ( PUBYEAR , 2019 ) OR LIMIT-TO ( PUBYEAR , 2018 ) OR LIMIT-TO ( PUBYEAR , 2017 ) OR LIMIT-TO ( PUBYEAR , 2016 ) OR LIMIT-TO ( PUBYEAR , 2015 ) OR LIMIT-TO ( PUBYEAR , 2014 ) OR LIMIT-TO ( PUBYEAR , 2013 ) OR LIMIT-TO ( PUBYEAR , 2012 ) OR LIMIT-TO ( PUBYEAR , 2011 ) OR LIMIT-TO ( PUBYEAR , 2010 ) OR LIMIT-TO ( PUBYEAR , 2009 ) OR LIMIT-TO ( PUBYEAR , 2008 ) OR LIMIT-TO ( PUBYEAR , 2007 ) ... % View all 2005 % %2023 % %Analyze 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 Year ⬇Documents ⬆ 27 86 69 76 49 47 51 38 32 28 Year Documents Documents by year 2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 0 20 40 60 80 100 Documents per year by source 2014 2016 2018 2020 2022 2012 2008 2010 2024 2006 0 10 5 15 Documents by author Taube, F. Cayuela, M.L. Butterbach-Bahl, K. Dannenmann, M. Klemedtsson, L. Kluß, C. Kiese, R. Leifeld, J. Loges, R. Mäder, P. 0 5 102.5 7.5 12.5 Documents by a liation Aarhus Universitet Wageningen Univers… Sveriges lantbruksun… Consejo Superior de … INRAE CNRS Centre Nation… Karlsruher Institut fü… Universität Hohenheim AgroParisTech Forschungsanstalt A… 0 20 40 60 Documents by country/territory Germany Italy Spain France Denmark Netherlands Switzerland Sweden Finland Ireland 0 50 100 150 200 Documents by type Article (85.0%) Review (15.0%) Documents by subject area Agricultural an... (43.3%) Biochemistry, G... (1.7%) Chemistry (0.5%) Decision Scienc... (0.2%)Earth and Plane... (11.2%) Energy (4.2%) Engineering (0.3%) Environmental S... (35.3%) Multidisciplina... (1.0%) Social Sciences... (2.3%) Documents by funding sponsor European Commission Seventh Framework … Horizon 2020 European Regional D… Horizon 2020 Frame… Ministerio de Econo… Bundesministerium f… Deutsche Forschung… Svenska Forskningsr… Agence Nationale de… 0 20 40 60 About Scopus What is Scopus Content coverage Scopus blog Scopus API Privacy matters Language ! " # $ %& ' ( ) * + , - . / 0 " 1 + 2 3 . / $ " Просмотр версии на русском языке Customer Service Help Tutorials Contact us ⤢ ⤢ ⤢ ⤢ ⤢ ⤢ ⤢ Brought to you bySistema Biblioteche ENEA Search Sources SciVal AL Terms and conditions Privacy policy Copyright © Elsevier B.V . All rights reserved. Scopus® is a registered trademark of Elsevier B.V. We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies . Analyze search results 619 document results Select year range to analyze: to Click on cards below to see additional data. ◅ Back to results Export Print Email ALL ( soil* AND ( agr* OR farm* ) AND ( europe* OR eu ) AND ( "crop residue*" OR "cover crop*" OR manure OR mulch OR slurry OR compost OR biochar OR digestate OR sludge OR "organic matter" OR om OR amendment* ) AND ( microb* OR microorganism* OR arche* OR bacteri* OR fung* ) AND ( "N2O emission*" OR "nitrous oxide emission*" ) AND ( "C seq*" OR "C stor*" OR "C cycl*" OR "carbon seq*" OR "carbon stor*" OR "carbon cycl*" ) ) AND ( LIMIT-TO ( LANGUAGE , "English" ) ) AND ( LIMIT-TO ( SRCTYPE , "j" ) ) AND ( LIMIT-TO ( DOCTYPE , "ar" ) OR LIMITTO ( DOCTYPE , "re" ) ) AND ( LIMIT-TO ( PUBYEAR , 2023 ) OR LIMIT-TO ( PUBYEAR , 2022 ) OR LIMIT-TO ( PUBYEAR , 2021 ) OR LIMIT-TO ( PUBYEAR , 2020 ) OR LIMIT-TO ( PUBYEAR , 2019 ) OR LIMIT-TO ( PUBYEAR , 2018 ) OR LIMIT-TO ( PUBYEAR , 2017 ) OR LIMIT-TO ( PUBYEAR , 2016 ) OR LIMIT-TO ( PUBYEAR , 2015 ) OR LIMIT-TO ( PUBYEAR , 2014 ) OR LIMIT-TO ( PUBYEAR , 2013 ) OR LIMIT-TO ( PUBYEAR , 2012 ) OR LIMIT-TO ( PUBYEAR , 2011 ) OR LIMIT-TO ( PUBYEAR , 2010 ) OR LIMIT-TO ( PUBYEAR , 2009 ) OR LIMIT-TO ( PUBYEAR , 2008 ) OR LIMIT-TO ( PUBYEAR , 2007 ) ... % View all 2005 % %2023 % %Analyze 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 Year ⬇Documents ⬆ 27 86 69 76 49 47 51 38 32 28 Year Documents Documents by year 2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 0 20 40 60 80 100 Documents per year by source 2014 2016 2018 2020 2022 2012 2008 2010 2024 2006 0 10 5 15 Documents by author Taube, F. Cayuela, M.L. Butterbach-Bahl, K. Dannenmann, M. Klemedtsson, L. Kluß, C. Kiese, R. Leifeld, J. Loges, R. Mäder, P. 0 5 102.5 7.5 12.5 Documents by a liation Aarhus Universitet Wageningen Univers… Sveriges lantbruksun… Consejo Superior de … INRAE CNRS Centre Nation… Karlsruher Institut fü… Universität Hohenheim AgroParisTech Forschungsanstalt A… 0 20 40 60 Documents by country/territory Germany Italy Spain France Denmark Netherlands Switzerland Sweden Finland Ireland 0 50 100 150 200 Documents by type Article (85.0%) Review (15.0%) Documents by subject area Agricultural an... (43.3%) Biochemistry, G... (1.7%) Chemistry (0.5%) Decision Scienc... (0.2%)Earth and Plane... (11.2%) Energy (4.2%) Engineering (0.3%) Environmental S... (35.3%) Multidisciplina... (1.0%) Social Sciences... (2.3%) Documents by funding sponsor European Commission Seventh Framework … Horizon 2020 European Regional D… Horizon 2020 Frame… Ministerio de Econo… Bundesministerium f… Deutsche Forschung… Svenska Forskningsr… Agence Nationale de… 0 20 40 60 About Scopus What is Scopus Content coverage Scopus blog Scopus API Privacy matters Language ! " # $ %& ' ( ) * + , - . / 0 " 1 + 2 3 . / $ " Просмотр версии на русском языке Customer Service Help Tutorials Contact us ⤢ ⤢ ⤢ ⤢ ⤢ ⤢ ⤢ Brought to you bySistema Biblioteche ENEA Search Sources SciVal AL Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 22 Here, to define the state of the art on the relationships between microbial biodiversity, C seq and N2O emissions, the microbiome diversity is referred to Archaea, Bacteria and Fungi. To refine the search of useful and relevant manuscripts, a set of BIODIVERSITY INDEXES (BIs) has been selected based on a work performed in the frame of another EJP-Soil project, namely MINOTAUR (https://ejpsoil.eu/soil-research/minotaur), for the microbial data collection template. These BIs include: Relative Abundance, Shannon and Simpson indexes, Richness Index, Evenness Index, Fisher Alpha, Chai1 Index, Ace Index, Phylogenetic diversity. Consequently, a search for BIs was performed inside the 619 items identified in Scopus. As a result, only 152 items included BIs terms. In particular, based on the BI keywords, the number of items found were, respectively: 8 for “Shannon”, 42 for “Fisher”, 47 for “richness”, 0 for “Chai1”, 73 for “Simpson”, 10 for “evenness”, 1 for “phylogenetic diversity” and 8 for “relative abundance”. It has to be noted that sometimes, the BI term is present only in the reference section of a manuscript. For example, regarding the term “Simpson”, several items were identified because of a highly cited reference published by the author “Simpson G.” Scientific manuscripts after the stringent selection Before being inspected more carefully with respect to the terms for carbon sequestration, N2O emissions and possibly other non-CO2 GHG emissions (especially, CH4 emissions and N leaching), the 152 manuscripts were analysed for the Title and the Abstract. From this first screening, a general scarcity of research encompassing microbial composition and diversity, and at the same time both C sequestration and N2O emissions was observed. For this reason, the working group decided to perform a more stringent screening of these 152 manuscripts, utilizing the below listed INCLUSION CRITERIA: 1. Only EU 2. Only agricultural soil 3. Microbes (presence of parameters, data, results, biodiversity indexes) 4. Presence of data on N2O emissions OR on C sequestration OR on CH4 emissions OR on N leaching 5. Evidence of a clear treatment with one or more OM inputs (or management strategies) 6. Research article (no review, no systematic study, no meta-analysis, etc). As a result, 16 research articles were selected as relevant and representative for the integrated effects of OM fertilization on soil microbial diversity and the trade-offs between C seq and N2O emissions. There are listed below. Finally, another manuscript, Johansen et al. 2013, has been selected and included in this study proceeding from the References of Bachmann et al. 2014. List of the 17 finally selected Original Research manuscripts: Manuscript N° Authors and title Journal, year and DOI 1 Badagliacca G., Lo Presti E., Ferrarini A., Fornasier F., Laudicina V.A., Monti M., Preiti G. Early Effects of No-Till Use on Durum Wheat (Triticum durum Desf.): Productivity and Soil Functioning Vary between Two Contrasting Mediterranean Soils. Agronomy, 2022 10.3390/agronomy12123136 2 Rosinger C., Clayton J., Baron K., Bonkowski M. Soil freezing-thawing induces immediate shifts in microbial and resource stoichiometry in Luvisol Geoderma, 2022 10.1016/j.geoderma.2021.11 5596 Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 23 soils along a postmining agricultural chronosequence in Western Germany. 3 Rosinger C., Bonkowski M. Soil age and soil organic carbon content shape biochemical responses to multiple freeze–thaw events in soils along a postmining agricultural chronosequence. Biogeochemistry, 2021 10.1007/s10533-021-008164 Badagliacca G., Laudicina V.A., Amato G., Badalucco L., Frenda A.S., Giambalvo D., Ingraffia R., Plaia A., Ruisi P. Long-term effects of contrasting tillage systems on soil C and N pools and on main microbial groups differ by crop sequence. Soil and Tillage Research, 2021 10.1016/j.still.2021.104995 5 Rummel P.S., Pfeiffer B., Pausch J., Well R., Schneider D., Dittert K. Maize root and shoot litter quality controls shortterm CO2 and N2O emissions and bacterial community structure of arable soil. Biogeosciences, 2020 10.5194/bg-17-1181-2020 6 Anastopoulos I., Omirou M., Stephanou C., Oulas A., Vasiliades M.A., Efstathiou A.M., Ioannides I.M. Valorization of agricultural wastes could improve soil fertility and mitigate soil direct N2O emissions. Journal of Environmental Management, 2019 10.1016/j.jenvman.2019.109 389 7 Bachmann S., Gropp M., Eichler-Löbermann B. Phosphorus availability and soil microbial activity in a 3 year field experiment amended with digested dairy slurry. Biomass and Bioenergy, 2014 10.1016/j.biombioe.2014.08. 004 8 Lori M., Piton G., Symanczik S., Legay N., Brussaard L., Jaenicke S., Nascimento E., Reis F., Sousa J.P., Mäder P., Gattinger A., Clément J.-C., Foulquier A. Compared to conventional, ecological intensive management promotes beneficial proteolytic soil microbial communities for agro-ecosystem functioning under climate change-induced rain regimes. Scientific Reports, 2020 10.1038/s41598-020-642798 9 Zistl-Schlingmann M., Kengdo S.K., Kiese R., Dannenmann M. Management intensity controls nitrogen-useefficiency and flows in grasslands—a 15n tracing experiment. Agronomy 2020 10.3390/AGRONOMY1004 0606 10 Drost S.M., Rutgers M., Wouterse M., de Boer W., Bodelier P.L.E. Decomposition of mixtures of cover crop residues increases microbial functional diversity Geoderma, 2020 10.1016/j.geoderma.2019.11 4060 11 Lubbers I.M., Berg M.P., De Deyn G.B., van der Putten W.H., van Groenigen J.W. Soil fauna diversity increases CO2 but suppresses N2O emissions from soil. Global Change Biology, 2020 10.1111/gcb.14860 12 Niklaus P.A., Le Roux X., Poly F., Buchmann N., Scherer-Lorenzen M., Weigelt A., Barnard R.L. Oecologia, 2016 10.1007/s00442-016-3611-8 Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 24 Plant species diversity affects soil–atmosphere fluxes of methane and nitrous oxide. 13 Pena R., Tejedor J., Zeller B., Dannenmann M., Polle A. Interspecific temporal and spatial differences in the acquisition of litter-derived nitrogen by ectomycorrhizal fungal assemblages. New Phytologist, 2013 10.1111/nph.12272 14 Dicke C., Andert J., Ammon C., Kern J., Meyer-Aurich A., Kaupenjohann M. Effects of different biochars and digestate on N2O fluxes under field conditions Science of the Total Environment, 2015 10.1016/j.scitotenv.2015.04. 005 15 Panico S.C., Esposito F., Memoli V., Vitale L., Polimeno F., Magliulo V., Maisto G., De Marco A. Variations of agricultural soil quality during the growth stages of sorghum and sunflower. Applied Soil Ecology, 2020 10.1016/j.apsoil.2020.10356 9 16 Ribas A., Llurba R., Gouriveau F., Altimir N., Connolly J., Sebastià M.T. Plant identity and evenness affect yield and trace gas exchanges in forage mixtures. Plant and Soil, 2015 10.1007/s11104-015-2407-7 17 Johansen, A., Carter, M.S., Jensen, E.S., Hauggard-Nielsen, H., Ambus, P. Effects of digestate from anaerobically digested cattle slurry and plant materials on soil microbial community and emission of CO2 and N2O. Applied Soil Ecology 2013 10.1016/j.apsoil.2012.09.003 Given the small number (17) of relevant articles, in this deliverable the main content of each article is reported in a schematic form. The next section indeed is made of a total of 16 “Cards”, corresponding to the scientific literature that has been specifically selected. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 25 Manuscript Card 1: Badagliacca et al. 2022 Badagliacca G., Lo Presti E., Ferrarini A., Fornasier F., Laudicina V.V., Monti M., Preiti G. Early Effects of No-Till Use on Durum Wheat (Triticum durum Desf.): Productivity and Soil Functioning Vary between Two Contrasting Mediterranean Soils. Agronomy, 12(12), 3136, 2022. https://doi.org/10.3390/agronomy12123136 Background of the study The diffusion of No Tillage (NT) is to be encouraged thanks to the benefits it can provide in terms of improving soil fertility and counteracting global warming and climate change as part of a climate-smart agriculture practice. However, the introduction of this management practice can be difficult, especially in the first years of application, and can lead to unpredictable yield results depending on the soil type. The aim of this experiment was to evaluate the early effect of NT use, compared to the mouldboard ploughing (Conventional Tillage, CT), on two different soils in semi-arid Mediterranean regions, a clay-loam in Reggio Calabria (GAL, South of Calabria, Italy) and a sandy-clay-loam soil in San Marco Argentano (SMA, North Calabria, Italy), by monitoring a set of 43 different soil and plant variables that were expected to vary with tillage and/or soil type. Experiment This experiment aimed to investigate in depth the short-term effects of the application of NT in two soils with constraining properties under the Mediterranean semiarid environment. In order to have a complete assessment of the effects on both plant and soil functioning in soil with different characteristics, the aspects analysed were: • wheat productivity and uptakes • soil C, N, and P dynamics • microbial community structure • enzymatic activity. The field experiment was established in 2019/2020 growing season as a completely randomized block design (RCBD) with four replications. Plant biomass measured data: total aboveground wheat biomass; total aboveground dry matter production; grain yield and straw yield; thousand kernel weight (TKW); harvest index (HI); grain test weight (TW); nitrogen concentration of straw and grain; phosphorous concentration of straw and grain. Soil measured data (0-20 cm soil depth): • Soil permanganate oxidizable C (POxC) • Nitrate-N (NO3−-N) and ammonium-N (NH4+-N) • Total soluble N (TSN) • Extractable organic N (EON) • Soil Bulk Density (BD) OM input/agricultural management practice At both locations, during the previous year, soil was covered with a polyphite forage cover. No Tillage (NT) vs. Conventional Tillage (CT). NT consisted of one passage of mulcher and chemical herbicide, to grind weed biomass and control their emergence, followed by sowing through direct drilling. CT consisted of mouldboard ploughing to a depth of 30 cm in October 2019 followed by one shallow harrowing operation, at 15 cm soil depth, before sowing. In order to assess the tillage effect on soil properties and plant growth, no fertilization was provided to all plots. Microbial data • PLFAs (PLFA analysis is a technique widely used for estimation of the total biomass and to observe broad changes in the community composition of the living microbiota of soil and aqueous environments). The FAs i15:0, a15:0, i16:0, and i17:0 were chosen to represent Gram-positive bacteria (Bac+), the FAs 18:1ω7, cy17:0, and cy19:0 for Gram-negative bacteria (Bac−). • The activity of twenty-one enzymes involved in the key steps of C, N, P, and S cycling. (i) α-glucosidase (alfaG), β-glucosidase (betaG), α-galactosidase (alfaGAL), β-galactosidase (betaGAL), α-mannosidase (alfaMAN), β- Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 32 Manuscript Card 4: Badagliacca et al. 2021 Badagliacca G., Laudicina V.A., Amato G., Badalucco L., Frenda A.S., Giambalvo D., Ingraffia R., Plaia A., Ruisi P. Long-term effects of contrasting tillage systems on soil C and N pools and on main microbial groups differ by crop sequence. Soil and Tillage Research, 211, 104995, 2021. https://doi.org/10.1016/j.still.2021.104995 Background of the study Focusing on conservation agriculture practice for increasing SOC and soil quality in semi-arid Mediterranean environment where soils are prone to OM reduction. The aim of this long-term study was to assess the combined effect of tillage system and crop sequence on SOC and biochemical soil properties generally used as indicators of soil qualities. Experiment Long-term study (23 years), but samples analysed refers to 2013-20014 cropping season. Location: the experiment was conducted under rainfed conditions at Pietranera Farm, located about 30 km north of Agrigento, Sicily (Italy), on a deep, well-structured soil classified as a Chromic Haploxerert. Collected soil samples: topsoil (0-15 cm) and subsoil (15-30 cm). Each soil sample was collected 3 distinct times: December 2013 (before sowing), April 2014 (wheat heading/faba bean full flowering), and July 2014 (at harvest), for a total of 144 soil samples. OM input/agricultural management practice • Tillage system (23 years of application of contrasting tillage systems: conventional tillage (CT) and no tillage (NT). • Crop sequences: wheat monocolture vs. wheat-faba bean rotation. Microbial data • Microbial Biomass C (MBC) • Microbial Biomass N (MBN) MBC and MBN were determined by the fumigation-extraction method • Basal Respiration (BR) • Abundance of main microbial groups by PLFAs. Cseq data • TOC (according to the Walkley–Black method) • Labile Organic Carbon (Corg), corresponding to portion of soil organic carbon that can be readily decomposed by soil organisms. N2O emission data N2O Emission data is N.A. Total nitrogen (Total N) CH4 emission data N.A. N leaching data N.A. Main results Under long-term NT: • Increased TOC at a yearly rate of 0.17 g kg-1, which in turn stimulated microbial biomass, in particular Gram-negative bacteria. • No variation in fungal biomass Under long-term CT: • Low variation in biochemical characteristics and microbial groups due to crop sequence. Key message In semi-arid Mediterranean environment, results under NT conditions suggest a higher soil quality, as confirmed by the increase in MBC/TOC and the decrease in stress indices. Interestingly, the effects of long-term NT varied widely by crop sequence, while less variation in biochemical characteristics as well as in the main microbial groups was present in soil samples subjected to CT. The greater availability of organic substrates due to the application of NT in turn stimulated soil microbial biomass and in particular the bacterial community, mainly BAC−, instead of the fungal community. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 33 Total organic carbon (TOC), extractable organic C (Cextr), and extractable organic N (Nextr) as affected by tillage system (CT, conventional tillage: grey plots; NT, no tillage: coloured plots) and crop (WW, continuous wheat; FW, wheat grown after faba bean; WF, faba bean grown after wheat) in soil samples collected from the 0–15 cm (topsoil) and 15–30 cm (subsoil) soil layers. Circles inside plots represent means, with whiskers representing ± SE (n = 12). The width of the plot shows the density distribution of values. Soil microbial biomass C (MBC) and microbial biomass N (MBN). See legend of the previous figure. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 34 Soil basal respiration (BR), microbial quotient (MBC/ TOC) and metabolic quotient (qCO2). See legend of the first figure. Total PLFAs, bacteria and fungi. See legend of the first figure. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 35 Gram-positive (BAC+) and Gram-negative (BAC− ) bacteria and fungi-to-bacteria ratio (F/B). See legend of the first figure. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 36 Manuscript Card 5: Rummel et al. 2020 Rummel, S.P., Pfeiffer, B, Pausch, J., Well, R., Schneider, D., Dittert, K. Maize root and shoot litter quality controls short-term CO2 and N2O emissions and bacterial community structure of arable soil. Biogeoscience, 17, 1181-1198, 202. https://doi.org/10.5194/bg-171181-2020 Background of the study Chemical composition of root and shoot litter controls decomposition and, subsequently, C availability for biological nitrogen transformation processes in soils. While aboveground plant residues have been proven to increase N2O emissions, studies on root litter effects are scarce. This study aimed: (1) to evaluate how fresh maize root litter affects N2O emissions compared to fresh maize shoot litter, (2) to assess whether N2O emissions are related to the interaction of C and N mineralization from soil and litter, (3) to analyze changes in soil microbial community structures related to litter input and N2O emissions. Experiment To obtain root and shoot litter, maize plants (Zea mays L.) were cultivated with two N fertilizer levels in a greenhouse and harvested. A two-factorial 22 d laboratory incubation experiment was set up with soil from both N levels (N1, N2) and three litter addition treatments (control, root, root + shoot). OM input/agricultural management practice Two N fertilizer levels (N1, N2) Three litter addition treatments (control, root, root + shoot) Microbial data • Bacterial community structures (by 16S rRNA gene sequencing) Cseq data • Organc Carbon as water-extractable organic carbon (WEOC) N2O emission data • N2O fluxes • Soil mineral N CH4 emission data N.A. N leaching data N.A. Main results Maize litter quality controlled NO3− and WEOC availability and decomposition-related CO2 emissions. Emissions induced by maize root litter remained low, while high bioavailability of maize shoot litter strongly increased CO2 and N2O emissions when both root and shoot litter were added. A strong positive correlation was assessed between cumulative CO2 and N2O emissions, supporting the hypothesis that litter quality affects denitrification by creating plant-litterassociated anaerobic microsites. The interdependency of C and N availability was validated by analyses of regression. Moreover, there was a strong positive interaction between soil NO3− and WEOC concentration resulting in much higher N2O emissions, when both NO3− and WEOC were available. A significant correlation was observed between total CO2 and N2O emissions, the soil bacterial community composition, and the litter level, showing a clear separation of root + shoot samples of all remaining samples. Bacterial diversity decreased with higher N level and higher input of easily available C. Altogether, changes in bacterial community structure reflected degradability of maize litter with easily degradable C from maize shoot litter favoring fast-growing C-cycling and Nreducing bacteria of the phyla Actinobacteria, Chloroflexi, Firmicutes, and Proteobacteria. High bioavailability of maize shoot litter strongly increased microbial respiration in plantlitter-associated hot spots, leading to increased N2O emissions when both C and NO3− were available. Coupled nitrification–denitrification and heterotrophic nitrification presumably contributed to N2O formation. Maize root litter was characterized by a higher share of slowly degradable C compounds and lower concentrations of water-soluble N; hence formation of anaerobic hot spots was limited and microbial N immobilization restricted N2O emissions. Bacterial community structures reflected degradability of maize litter types. Key message Litter quality is a major driver of N2O and CO2 emissions from crop residues, especially when soil mineral N is limited. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 37 Preparation and experimental setup of the incubation experiment. N1 (0.2 g N kg-1) and N2 (2 x 0.2 g N kg-1) referring to the N levels during plant growth. Control soil (N1-C and N2-C) without addition of plant litter. Root treatment with addition of 100 g of fresh root biomass per kilogram of dry soil (N1-R and N2-R) and root + shoot treatment with addition of 100 g of root and 100 g of shoot biomass per kilogram of dry soil (N1-RS, N2RS). Heat map of the 16 most abundant bacterial orders of the soil-inhabiting bacterial community grouped by N levels and litter input (n = 4, except for N2 root: n = 3). Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 38 Manuscript Card 6: Anastopoulos et al. 2019 Anastopoulos, I., Omirou, M., Stephanou, C., Oulas, A., Vasiliades, M.A., Efstathiou, A.M., Ioannides, I.M. Valorization of agricultural wastes could improve soil fertility and mitigate soil direct N2O emissions. Journal of Environmental Management, 250, 109389, 2019 https://doi.org/10.1016/j.jenvman.2019.109389 Background of the study It is expected that the increasing demand of N in agriculture will continue to raise N2O emissions affecting climate globally. Sol organic amendments may increase soil fertility and crop productivity, soil microbial activity and soil C seq. The emerging need for sustainable management of the increasing quantities of urban and industrial organic wastes creates opportunities for the development of alternative strategies for the improvement of degraded soils. The current study was performed to examine the effects of agricultural wastes application on soil bacterial community as well as CO2 and N2O direct gas emissions. In the current study, soil chemical characteristics, quantitative PCR of denitrifiers (nirK, nirS, nosZ I and nosZ II) and 16s rRNA amplicon sequencing were assessed to examine the links between the soil microbial communities and short-term soil direct N2O emissions when treated with agricultural wastes. Experiment • Untreated soils (alkaline, 0-20 cm depth, from Cyprus, Greece) were compared with soils, which received the same amount of N (100 μg/g soil) in the form of ammonium nitrate and organic agricultural waste. In particular, soils were incubated with three different organic agricultural wastes, orange (OP), mandarin (MP) and banana peels (BP) and ammonium nitrate (F) after adjusting soil water at 70% of its holding capacity. • 34 days period in a microcosm study in 1.5 L glass bottles. • The soil was 22% sand, 26% silt and 52% clay. OM input/agricultural management practice These three different organic agricultural wastes, orange (OP), mandarin (MP) and banana peels (BP) were tested and compared to ammonium nitrate (F). Various chemical properties, including organic matter, C and N, are measured for each organic waste. Microbial data Soil microbial communities were analysed through: • quantitative PCR of denitrifiers (nirK, nirS, nosZ I and nosZ II) • 16s rRNA amplicon sequencing (at 5 and 34 days) Cseq data • Initial soil total organic carbon: 1.71% • CO2 emissions (in ng/g soil) N2O emission data • Initial soil N: 0.089% • Initial soil nitrate nitrogen: 4.78 ug/g • N2O emissions (in ng/g soil) CH4 emission data N.A. N leaching data N.A. Main results The highest soil direct N2O emissions were recorded in soils received ammonium nitrate while soils received agricultural wastes exhibited substantially lower soil direct N2O emissions. Cumulative N2O emission in fertilized soil was 22.7, 5.3, 9.9 and 10.2 times higher than that measured in control, BP, MP and OP soils, respectively. However, during time both MP and OP treated soil exhibited higher cumulative N2O emission level from that measured in control soil. Agricultural wastes stimulated CO2 accumulation (CO2 emission in control and ammonium nitrate treated soil was similar and was substantially lower compared to that measured in soils received organic amendments) as well as the growth of copiotrophic bacterial groups like Proteobacteria and Firmicutes. Interestingly, direct soil N2O emissions were decoupled from the density of denitrifier community; moreover, agricultural wastes caused a substantial reduction of the relative abundance of bacterial taxa associated with N2O emissions in the soil. Both types of amendment and time had strong and interactive effects on Shannon Index (S.I.) in the soil. The lowest diversity was observed 5 d after the initiation of the experiment in soils that received organic amendments; while the highest was noticed in non-treated soils (C) and NH4NO3 treated soils (F). The lowest diversity was measured in OP (S.I. = 3.00) treated soils followed by BP (S.I. = 3.15) and MP (S.I. = 3.18) treated soils. During time, the S.I. in soils Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 39 that received organic amendments increased significantly and it was similar with that measured in control and fertilized soils. Addition of ammonium nitrate in soil didn't change the abundance of the main bacterial taxa found in the current study compared to the nontreated soils except the Bacilli abundance, which exhibited a significant increase. Key message This study proves evidence that agricultural wastes could be integrated in a waste management strategy, which inter alia includes their direct use in agricultural ecosystems resulting in reduced N2O emissions. The abundance of nirK, nirS, nosZI and nosZII genes normalized to 16S rRNA gene abundance, in non-treated (C) and treated soils with fertilizer (F), banana (BP) mandarin (MP) and orange peels (OP), 5 and 34 days after the application of the treatments. Spreads in the boxplots denote standard error of the mean (n = 3). Different small letters denotes statistically significant differences within time. Different capital letters denote statistically significant differences of the mean within treatment (n = 3). Average relative abundances (%) of bacterial community assemblies at phylum level found in non-treated (C) and treated soils with fertilizer (F), banana (BP) mandarin (MP) and orange peels (OP), 5 and 34 days after the application of the treatments. In particular, Proteobacteria, Acidobacteria, Bacteroidetes, Actinobacteria, Planctomycetes, Gemmatimonadetes, Firmicutes, and Verrucimicrobiota were the eight most abundant phyla found in the current study. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 40 Heat-map of the response of bacterial community structure based on Brays-Curtis similarity index, at class level during time and to the different treatments: non-treated (Control) and treated soils with fertilizer (F), banana (BP) mandarin (MP) and orange peels (OP). The bottom panel shows the significance impact (ANOVA) of the treatment, time and their interaction on each bacterial Class. Cumulative N2O A and CO2 emissions B during time (5 and 34 days) from the different treatments: non-treated (Control) and treated soils with fertilizer (F), banana (BP) mandarin (MP) and orange peels (OP). Spreads in the barplots denote standard error of the mean (n = 3). Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 41 Manuscript Card 7: Bachmann et al. 2014 Bachmann, S., Gropp, M., Eichler-Löbermann, B. Phosphorus availability and soil microbial activity in a 3 year field experiment amended with digested dairy slurry. Biomass and Bioenergy, 70, 429-439, 2014. https://doi.org/10.1016/j.biombioe.2014.08.004 Background of the study The residues from biogas production are increasingly being used as fertilizers in crop production, providing benefits for nutrient cycling. Experiment A 3 year field experiment was conducted to assess the phosphorus (P) fertilizer value of digestate from biogas production, taking into account soil microbial activity. An on-farm experiment was established in September 2008 in close cooperation with a local dairy farm. The experimental area was located in Mecklenburg-West Pomerania (Germany). The experimental area has not received any organic fertilizer since 1995. The soil type was classified as Haplic Luvisol, and the soil texture was a sandy loam. Then, the input substrate (inputS) and digested substrate (digestS) from a biogas plant using dairy slurry, maize silage and wheat corn, were applied at a rate of 30 m3 ha-1 annually. For control, mineral N and K, but no P, were applied in equal amounts with the biogas substrates. Maize was cultivated every year, and the biomass yield and P and N uptake were determined. Soil samples were collected on different sampling dates, and the P contents, pH, organic matter contents and enzyme activity were analyzed. The CO2 efflux was measured biweekly during the maize growing period using a portable soil respiration chamber (EGM 4). OM input/agricultural management practice Application of biogas residues (digestate) to agricultural field. More precisely, the input substrate (inputS) and the digested substrate (digestS) of the farm-owned biogas plant were used as fertilizers in the field experiment. Microbial data Enzyme (dehydrogenase, acid and alkaline phosphatase) activity Cseq data The CO2 efflux was monitored as an indicator of the biological activity and decomposition of organic matter. N2O emission data no specific information about N2O emission data. CH4 emission data N.A. N leaching data N.A. Main results After 3 years, the P and N uptake increased by 25% in the digestS treatment compared with that of the control but did not differ from that of the inputS treatment. The plant-available P contents were also higher in the inputSand digestS-amended soil. The fertilizer application did not influence the organic matter content but did influence the enzyme activity in soil. Averaging of all the sampling dates in 2010 and 2011, the activities of dehydrogenase and alkaline phosphatase were 50% lower in the soils that were amended with digestS compared with inputS. However, the CO2 efflux from the soil surface was the same for the inputS and digestS treatments. Our results indicate that the anaerobic digestion of substrates does not affect the plant P uptake but the performance of soil microorganisms. Key message The obtained results indicate that the anaerobic digestion of substrates does not affect the plant P uptake but the performance of soil microorganisms. This manuscript is not very relevant for the aim of the current review study. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 48 Fig. 2. Bacterial biomass (based on copy numbers of the 16S rRNA gene with qPCR) over time (mean ± SE; n = 4). A: control, monocultures V, R, A and A + N; B: control, mixtures VRA and 15sp. expVRA is the average of the three monocultures (V, R and A). Fig. 3. Microbial functional diversity: number of wells that showed a positive response in Biolog ECO plates after incubation of 7 days (mean ± SE; n=4). As the treatments are not significantly different over time (p = 0.59), the average of both time points (T12 and T50) is shown here. The different letters indicate significant differences between treatments. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 49 Fig. 4. Greenhouse gas fluxes over time (days) (mean ± SE; n = 4). A: mmol CO2 per hour per m2; B: μmol N2O per hour per m2; C: close-up of N2O graph. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 50 Manuscript Card 11: Lubbers et al. 2020 Lubbers, I.M., Berg, M.P., De Deyn, G.B., van der Putten, W.H., van Groenigen, J.W. Soil fauna diversity increases CO2 but suppresses N2O emissions from soil. Global Change Biology, 26(3): 1886-1898, 2020. https://doi.org/10.1111/gcb.14860 Background of the study The study focuses on understanding the relationship between soil biodiversity and climate regulation, specifically examining the impact of soil fauna on greenhouse gas (GHG) emissions and biogeochemical cycling of carbon (C) and nitrogen (N). It emphasizes the importance of empirical research in elucidating the feedback mechanisms in soil processes contributing to climate change, especially in agroecosystems. Experiment Objective: To quantify biodiversity effects on soil-derived emissions of N2O and CO2 under controlled laboratory conditions. - Experimental design: soil microcosms with hay-amended soil were used, varying in species composition (none, one, two, four, and eight detritivorous/fungivorous soil mesofauna and macrofauna species). - Faunal Taxa: four taxonomic groups (earthworms, potworms, mites, springtails) with eight selected species were randomly assigned to multispecies treatments. OM input/agricultural management practice Organic Matter Input: The study utilized hay residue with specific characteristics (32.8 g N/kg dry matter, 448.5 g C/kg dry matter) as a representative organic amendment. - Management Practices: the experimental setup involved manipulating faunal species composition in hay-amended soil microcosms. Microbial data Microbial Biomass: Microbial biomass nitrogen (MBN) was determined through the chloroform fumigation and extraction technique. Cseq data Soil Biogeochemical Properties: Soil biogeochemical properties, including total dissolved N (Nts), ammonia (NH+), nitrate and nitrite (NO− + NO−), dissolved organic N (DON), pH, and dissolved organic C (DOC), were analyzed. N2O emission data N2O Emission Measurement: N2O emissions were measured using a static closed chamber technique. Key physico-chemical factors influencing N2O emissions, such as NH+, NO− + NO−, DOC, and pH, were considered in the analysis. CH4 emission data N.A. N leaching data N.A. Main results Net Biodiversity Effects on N2O and CO2: - Contrasting patterns observed - increased biodiversity reduced N2O emissions but increased CO2 emissions. - Significant differences found between twoand eight-species treatments for N2O. - Net biodiversity effects for N2O were negative in fourand eight-species treatments, indicating inhibitive interactions. Community Composition Effects: - Earthworms, especially Aporrectodea caliginosa, significantly increased N2O emissions. - No significant earthworm effects on dissolved organic C. - Negative relationship found between mean functional dissimilarity and net biodiversity effects for N2O. - Positive relationship found for CO2, indicating facilitative interactions. Key message The study emphasizes the contrasting impact of increased soil fauna species richness and functional dissimilarity on N2O and CO2 emissions. Surprisingly, higher species richness led to decreased N2O emissions but increased CO2 emissions, challenging conventional expectations. This unexpected pattern is attributed to the distinct nature of N2O and CO2 production processes, influenced by faunal interactions with microbial transformations. Soil engineering species, such as earthworms, play a crucial role in altering soil structural properties, affecting gas diffusion and contributing to 'hotspots' of microbial activity. The study underscores the importance of community composition in explaining faunal-induced greenhouse gas emissions, with earthworms identified as key contributors. Overall, the findings advocate for soil biodiversity conservation to mitigate N2O emissions and encourage sustainable agricultural practices. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 51 Net biodiversity effect on per capita soil-derived emissions of N2O and CO2 (mg N2O-N m−2 mg−1 DW and g CO2-C m−2 mg−1 DW, respectively) in relation to species number. The 0-line indicates a neutral net biodiversity effect. Each box plot shows the 5th and 95th percentiles and the mean (red line) of all treatments for two species (n = 40), four species (n = 20) and eight species (n = 5), respectively. Data points that lie outside the 5th and 95th percentiles are shown as dots. For N2O, significant differences between the twoand eight-species treatments (two-sample t test assuming unequal variances, t statistic = 2.61, p two-tail = .013) and the fourand eight-species treatments (two-sample t test assuming unequal variances, tstatistic = 3.70, p two-tail = .001) are indicated by different letters. For CO2, there are no significant differences between the two-, fourand eightspecies groups. For both N2O and CO2, the fourand eight-species groups are significantly different from the constant 0 (established by a one-sample t test); levels of significance are *<0.05; **<0.01; ***<0.001; ns = not significant. Net biodiversity effect on per capita soil-derived emissions of N2O and CO2 (mg N2O-N m−2 mg−1 DW and g CO2-C m−2 mg−1 DW, respectively) in relation to mean functional dissimilarity (sum of effects on NH4, NO3, DOC and pH (Granli & Bøckman, 1994) of species in the community). The 0-line indicates a neutral net biodiversity effect. Each vertical series of dots represent a treatment (n = 5 replicates per treatment; some dots overlap). For N2O, a significant negative regression between mean functional dissimilarity and the net biodiversity effect (linear regression, F64, 63 = 4.95, p = .030) indicates that communities with functionally dissimilar species are more likely to have negative net biodiversity effects. For CO2, a significant positive regression between mean functional dissimilarity and the net biodiversity effect (linear regression, F64, 63 = 14.5, p < .001) indicates that communities with functionally dissimilar species are more likely to have positive biodiversity effects. Uppercase letters at the top of the figure refer to the species combination given in Table 1. Colours indicate the number of species present: blue = 2 species present, pink = 4 species present and green = 8 species present. Underlined uppercase letters refer to species combinations that include an earthworm species. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 52 Observed cumulative emissions of N2O and CO2 after 120 days (in mg CO2-eq per microcosm). A nonparametric test (Independent-samples Mann–Whitney U test) established the difference in cumulative emissions from treatments with earthworms present (black bars ‘+EW’) compared to treatments without earthworms present (grey bars ‘−EW’; black bars vs. grey bars: p < .001 for both N2O and CO2). Lowercase letter denotes differences between treatments with earthworms. Capital letters placed underneath each bar refer to the species combination. Colours indicate the number of species present: blue = 2 species present, pink = 4 species present and green = 8 species present. Underlined uppercase letters refer to species combinations that include an earthworm species. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 53 Manuscript Card 12: Niklaus et al. 2016 Niklaus, P.A., Le Roux, X., Poly, F., Buchmann, N., Scherer‐Lorenzen, M., Weigelt, A., Barnard, R.L. Plant species diversity affects soil–atmosphere fluxes of methane and nitrous oxide Oecologia, 181: 919-930, 2016. https://doi.org/10.1007/s00442-016-3611-8 Background of the study In this study the authors investigate the effects of plant species diversity and fertilization, together with their interaction, on fluxes of N2O and CH4 under field conditions. Investigate the dynamics of these trace gases and underly mechanisms at several levels. i)measured in situ flux rates of N2O and CH4; ii) assessed the enzymatic potential of key N transformations functionally linked to these fluxes; iii) quantified the abundance of bacterial nitrifiers and denitrifiers using quantitative PCR of selected functional and ribosomal genes. Further, the authors assessed soil environmental conditions (temperature, moisture) and concentrations of inorganic N species. They were particularly interested in determining whether higher plant species richness would lead to more complete N capture and therefore reduced nitrification and denitrification rates and associated N2O emissions. An additional aim was to test whether the plant diversity effects in their experimental system operated via changes in soil moisture and whether there was evidence that nitrification promotes soil CH4 uptake by the removal of potentially inhibiting NH4+. Experiment This work studied soil–atmosphere trace gas fluxes in a large grassland biodiversity experiment near Jena, Germany (50°55′N, 11°35′W; 130 m a.s.l.). In particular, the authors focused on 78 plots (20 × 20 m) sown with one, two, four, eight, or 16 herbaceous species. The experiment analysed: Soil–atmosphere trace gas fluxes; Soil sampling; Nitrifying and denitrifying enzyme activity; Nitrifier and denitrifier abundances; Soil moisture and inorganic N concentrations; Data analysis. OM input/agricultural management practice Plot community composition was determined by random selection of species from a 60species pool, with the constraint that species richness and plant functional type richness were as orthogonal as possible. Plant species had previously been assigned to functional types (grasses, small non-legume herbs, tall non-legume herbs, and legumes) based on a cluster analysis combining a large number of morphological and functional traits. In total, the study thus presents a split plot design with 70 plots (unit of replication for plant species composition and thus plant species richness) and 2 × 70 = 140 subplots (unit of replication for fertilizer application). Microbial data Microbial gene abundances responded positively to fertilizer but not to plant species richness. Plant species richness did not affect functional gene abundances, although nxrA showed a marginally significant (P = 0.06) and weak decrease with plant diversity. In contrast, the abundances of AOB, Nitrobacter-like NOB and nirKand nirS-like denitrifiers increased with fertilizer application. Cseq data N2O emission data Soil N2O emissions were left unaffected by plant species richness but they increased slightly with fertilizer application. Emissions of N2O were strongly controlled by the presence of legumes. Therefore, separately were analyzed plots that were sown with and without legumes (Fig. 1). CH4 emission data Soil CH4 uptake rates decreased with plant species richness (P = 0.02), but they remained unaffected by fertilizer application (Fig. 2) and by the abundance of legumes. N leaching data N.A. Main results Plant species richness decreased soil N2O emissions—at least in the absence of legumes— and decreased soil CH4 uptake. Detected plant diversity effects on underlying soil microbial processes and the abundances of soil microbial groups related to these processes. Structural equation modeling suggests that the effects on N2O fluxes were at least in part mediated by positive effects of plant species numbers on soil moisture, which in turn led to accelerated inorganic N cycling, as evidenced by increased NEA and DEA. Positive path coefficients to N2O fluxes (Fig. 3) suggest that this increase in N transformation capacity indeed stimulated N2O emissions. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 54 Net soil CH4 uptake decreased persistently with plant species richness. The soil’s CH4 balance is determined by the difference between methanogenesis and CH4 oxidation, with the latter dominated by methanotrophic bacteria. The authors did not observe net CH4 emissions during our study, indicating that CH4 oxidation consistently outweighed methanogenesis. This study revealed that many effects of plant species richness on microbial processes were mediated by effects on soil moisture. Key message The present field study is the first to present clear and consistent responses of soil trace gas exchange to plant species richness and fertilization. Soil nitrous oxide (N2O) emission rates for plots without (left) and with (right) legumes planted. Individual symbols Values for each plot (gray and white circles values for control and fertilized plots, respectively), black pie shape inside symbol fraction of legumes in aboveground plant biomass harvested in June 2007 and 2008. Square symbols and lines Means predicted by the model for both fertilizer treatments, shaded areas corresponding standard errors (SE). Net soil methane (CH4) uptake rate as a function of plant species richness and fertilizer application. Gray and white circles Values for each control and fertilized subplot, respectively. Squares and lines model-predicted means for both fertilizer treatments, shaded areas corresponding SE. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 55 Manuscript Card 13: Pena et al. 2013 Pena, R., Tejedor, J., Zeller, B., Dannenmann, M., Polle, A. Interspecific temporal and spatial differences in the acquisition of litter-derived nitrogen by ectomycorrhizal fungal assemblages. New Phytologist, 199: 520-528, 2013 https://doi.org/10.1111/nph.12272 Background of the study In the present study, the accessibility of litter-derived N for a typical EMF assemblage associated with beech roots in an old-growth beech forest were investigated. The goal was to identify interspecific differences in N acquisition from leaf litter by analysing the temporal pattern of N accumulation in root tips colonized by different EMF species in comparison with N accumulation in fine roots, soil microbial biomass, and soil. Experiment The study site was located in a 70–80-yr-old beech (Fagus sylvatica L.) stand in Tuttlingen Forest, in a low mountain range in southern Germany (longitude 8°45′E; latitude 47°59′ N) at an altitude of 760–820 m above sea level. The climate is temperate with a mean annual air temperature of 6.6°C and a total annual precipitation of 856 mm. The soil profiles are characterized as Rendzic Leptosol derived from limestone and marls (WRB-classification, ISSS 1998). The organic layer comprises L and of horizons of different depths (0–7 cm). The Ah horizon has pH values of c. 6.1 and a C:N ratio of 14.2. A rectangular plot (12.0 9 17.0 m) comprising nine beech trees was established. Four soil cores (0.03 m diameter and 0.1 m depth) were removed at a distance of about 1 m from the stem of each tree and c. 0.5 m apart from each other. The samples of each tree were pooled and used for further analyses (n = 9). A litter bag was inserted into each hole generated by the soil corer in tight contact with the adjacent soil. The bags were numbered and their positions were marked with flags to enable retrieval. Subsequent harvests were conducted to a depth of 0.1 m with a soil corer of 0.08 m diameter positioned to extract the soil core with the litter bag in its centre (Fig. 1). One sample per tree was collected after 6 months (n = 9), 14 months (n = 6), and 18 months of litter bag exposure (n = 6). OM input/agricultural management practice Small cylindrical mesh bags containing 15N-labelled beech (Fagus sylvatica) leaf litter that permit hyphal but not root ingrowth were inserted vertically into the topsoil layer of an old-growth beech forest. The lateral transfer of 15N into the circumjacent soil, roots, microbes and ectomycorrhizas was measured during an 18-month exposure period. Microbial data This study shows a clear hierarchy for mean 15N tracer accumulation, first in microbes and ectomycorrhizas, then in roots and finally in soil. The ectomycorrhizas, soil microbes and roots analysed here were not located at increasing distance beneath the decomposing labelled leaf litter. Microbes incorporated the released N and showed peaks for the 15N label and microbial biomass (not shown) in autumn of the first and second years of exposure to leaf litter. This result supports observations that microbial N cycling in beech forests shows seasonal patterns, with peaks of temporal N immobilization in the autumn and winter, whereas increased mineralization, accompanied by lower microbial N uptake, occurs preferentially in the summer months. Cseq data N.A. N2O emission data N.A. CH4 emission data N.A. N leaching data Because approximately half of the studied fungal species had direct access to N from leaf litter and the remainder to N from leached compounds, the authors suggest that EMF diversity facilitates the N utilization of the host by capturing N originating from earlyreleased solutes and late degradation products from a recalcitrant source. Main results Study shows a clear hierarchy for mean 15N tracer accumulation, first in microbes and ectomycorrhizas, then in roots and finally in soil. An important finding was that EMF species showed large interspecific variation in 15N accumulation, with some fungal taxa apparently being similarly efficient to soil microbes in N acquisition at an early stage. Study shows strong interspecific variation in the ability of different fungal species associated with root tips to acquire N from degrading leaf litter. The extent of N enrichment was a species-specific feature and not related to differences in N concentration or the thickness of the fungal mantle. Key message The finding that approximately half of the fungal species had access to N directly from leaf litter and the remainder to N from soluble compounds in their immediate vicinity Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 56 highlights the importance of EMF species diversity on root tips for the acquisition of both easily released ‘early’ and recalcitrant ‘late’ N as nutrient sources for beech. Scheme of sampling unit with the cavity, in which the litter bag was inserted. The soil sample representing a 2.5 cm-wide soil ring around the cavity was harvested for the analyses. Decrease in litter mass (open symbols) and in the amount of 15N (closed symbols) in the litter bags. The bags were filled with 5.00 g of beech (Fagus sylvatica) litter and exposed in the soil of a beech forest for 18 months. Data are means of five to seven samples (± SE). When the error bars are not visible, they are smaller than the symbols. Different letters indicate significant differences at P ≤ 0.05. Increase in δ15N in ectomycorrhizal fungal root tips, roots, and soil adjacent to the 15N-labelled beech (Fagus sylvatica) leaf litter. A soil ring (width 2.5 cm) around the litter bags was collected and used for the analysis of 15N enrichment. Data are means of six to nine samples (± SE). When the error bars are not visible, they are smaller than the symbols. Closed triangles, microbes; open circles, ectomycorrhizas; closed circles, roots; open squares, soil. Red symbols not connected by a line at 18R indicate mean label in samples 4 months after the removal of the labelled litter bags. Different letters indicate significant differences at P ≤ 0.05. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 57 Manuscript Card 14: Dicke et al. 2015 Dicke, C., Andert, J., Ammon, C., Kern, J., Meyer-Aurich, A., Kaupenjohann, M. Management intensity effects of different biochars and digestate on N2O fluxes under field conditions. Science of the Total Environment, 524-525: 310–318, 2015. https://doi.org/10.1016/j.scitotenv.2015.04.005 Background of the study Biochar is a solid, carbon (C)-rich material, which is used for soil amelioration. The effects of using biochar on soil fertility and properties have been reported mainly in the tropics and subtropics. The main objective of this field study was to find out if the effects of treated and non-treated chars, when applied to an agricultural soil with conventional crop management, could be distinguished in terms of the soil N dynamics. An attempt was made to raise the C content of the sandy soil with different chars. It was hypothesised that control and digestate treatments emit more N2O than the char treatments, especially after fertilisation. Experiment 1. Char production and characterization: Chars were produced by different processes (HTC, pyrolysis) and from different feedstocks (maize silage and residues of wood chip production) which were purchased from commercial producers, 2. Location and weather data: The experimental field is situated close to the research station of the Institute of Agricultural and Urban Ecological Projects (IASP) in Berge, Germany (52° 63′N, 12° 80′E). The soil is classified as a haplic Cambisol. 3. Field experiment: The experiment was set up with a three-factorial randomised complete block design. Chars and digestate have been defined as soil amendments in this study. The plot size was 4.5 m × 10 m, with an inner area for measurements and harvest. 4. Gas emissions: Emitted nitrous oxide (N2O) was collected, using closed cylindrical chambers with a volume of 0.064 m3 (lower diameter 0.51 m, upper diameter 0.39 m, height 0.4 m) placed on a collar with a water sealing. 5. Soil sampling: oil samples were taken to determine the gravimetric water content and inorganic N (NH4+-N and NO3−-N) 6. DNA extraction and quantification of nosZ denitrifiers: Extraction of DNA was performed from soil samples taken in October 2012, shortly after the application of char and digestate and in June 2013, because microorganisms had the opportunity to adapt to changes in the environmental conditions caused by the application of char and digestate. 7. Modelling and statistics: A mixed linear model was applied to ascertain the influence of several factors on the emissions of N2O. OM input/agricultural management practice The effects of the application of char, under practical conditions, on the emissions of N2O were examined in a soil from a temperate region under field conditions. It was hypothesised that the application of char would decrease N2O emissions and affect nosZ gene abundance. They found that the application of treated pyrolysis-char significantly lowered the N2O emissions compared to pure digestate. Therefore, the application of treated char is preferable to the separate application of char and digestate in terms of N2O emissions. Microbial data Microorganisms had the opportunity to adapt to changes in the environmental conditions caused by the application of char and digestate. To cover the complete nosZ gene abundance in the soil samples, tried to target a second clade of nosZ denitrifiers, using the primers nosZ II forward (5′-CTIGGICCIYTKCAYAC-3′) and nosZ II-reverse (5′-GCIGARCARAAITCB GTRC-3′) and the corresponding PCR conditions. However, despite numerous attempts, no specific real-time PCR products could be obtained and therefore this approach was not pursued. Cseq data N.A. N2O emission data It was hypothesized that the incorporation of chars reduces the emissions of N2O. CH4 emission data N.A. N leaching data N.A. Main results and Key message The treatment with pure digestate emitted the most N2O compared to the control and char treatments. There were no great differences between the char treatments due to high spatial variability and gene abundance of nosZ did not differ between treatments. Overall, Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 64 The legume and forb monocultures showed the highest N2O exchange rates, with higher values than those found for the grass monoculture. On the other hand, no evenness effects were detected on NH3 exchange rates. Diversity enhanced CO2 exchange, which corresponded to total respiration without subtracting photosynthetic assimilation (Table 2), resulting in a higher CO2 exchange in mixtures than that expected according to monoculture exchange values. Regarding the different monocultures, the legume showed a higher CO2 exchange (c. 100 %) than the other two species (Table 2). Similarly to CO2, CH4 emission rates increased in legume compared to non-legume monocultures (Table 2). However, contrary to CO2, CH4 emission rates tended to be reduced with increased sown species evenness. Trends observed for the spring samplings were similar to those observed in July, with the legume swards showing higher exchange rates, although differences in spring were mostly marginal (Table 3). On the other hand, no significant evenness effects were detected at that time, except for a significant negative evenness effect on the methane exchange rates (Table 3). Key message these results suggest that diversifying forage legume-based systems could contribute to mitigation of GHG emission while improving ecosystem productivity. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 65 Manuscript Card 17: Johansen et al. 2013 Johansen, A., Carter, M.S., Jensen, E.S., Hauggard-Nielsen, H., Ambus, P. Effects of digestate from anaerobically digested cattle slurry and plant materials on soil microbial community and emission of CO2 and N2O. Applied Soil Ecology, 63: 36e44, 2013 https://doi.org/10.1016/j.apsoil.2012.09.003 Background of the study Anaerobic digestion of animal manure and crop residues may be employed to produce biogas as a climate-neutral source of energy and to recycle plant nutrients as fertilizers. Biogas technology can (i) mitigate global CO2 emissions, (ii) increase the substitution of synthetic N fertilizer, (iii) apply recycling principles because several nutrient resources are limited (e.g. phosphorus, P) and (iv) reduce the cost of fertilizers for farmers. In addition, the nutritional value of digestates can also be improved by combining with other sources of nutrients; e.g. ashes. However, especially organic farmers are concerned that fertilizing with the digestates may impact the soil microbiota and fertility because they contain more mineral nitrogen (N) and less organic carbon (C) than the non-digested input materials (e.g. raw animal slurry or fresh plant residues). Soil mineral N dynamics are complex, depending on direct assimilation in the plant and microbial biomass, immobilization on clay particles, but also loss by leaching to groundwater or gaseous emissions (NH3, N2 and N2O). When applying digestates to soil, ammonium is nitrified to nitrate in few days and a main challenge for the farmer is to avoid the volatile loss of ammonia during spreading, nitrate via leaching and gaseous N2O emissions. From a climate perspective, the latter is especially critical because N2O is a potent greenhouse gas, which may strongly counterbalance the potential mitigation of greenhouse gas emission due to production and use of bioenergy. Compared to using animal or green manure (e.g. grassclover), the nutrients in the digestates are to a higher extent present in inorganic form. In addition, the content of organic C has decreased significantly during the anaerobic digestion process. The latter causes great concern among organic farmers, assuming that less organic C is available for growth and activity of the soil microbial community and that the soil organic matter stock is gradually depleted with time. Experiment Incubation study with application of (1) water, (2) raw cattle slurry, (3) anaerobically digested cattle slurry/maize, (4) anaerobically digested cattle slurry/grass-clover, or (5) fresh grass-clover to soil. Experimental unites were sequentially sampled destructively after 1, 3 and 9 days of incubation and the soil assayed for: • content of mineral N • available organic C • emission of CO2 and N2O • microbial phospholipid fatty acids (biomass and community composition) • catabolic response profiling (functional diversity). OM input/agricultural management practice Application of digestate from anaerobically digested cattle slurry. More in details: 1) water 2) raw cattle slurry 3) anaerobically digested cattle slurry/maize 4) anaerobically digested cattle slurry/grass-clover 5) fresh grass-clover were applied to soil at arable realistic rates. Microbial data Microbial PLFAs (biomass and community composition) Catabolic response profiling (functional diversity) Cseq data Available organic C CO2 emissions N2O emission data Mineral N content N2O emissions CH4 emission data N.A. N leaching data N.A. Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 66 Main results Fertilizing with the anaerobically digested materials increased the soil concentration of NO3− ca. 30–40% compared to when raw cattle slurry was applied. Grass-clover contributed with four times more readily degradable organic C than the other materials, causing an increased microbial biomass which depleted the soil for mineral N and probably also O2. Consequently, grass-clover also caused a ∼10 times increase in emissions of CO2 and N2O greenhouse gasses compared to any of the other treatments during the 9 days. Regarding microbial community composition, grass-clover induced the largest changes in microbial diversity measures compared to the controls, where raw cattle slurry and the two anaerobically digested materials (cattle slurry/maize, cattle slurry/grass-clover) only induced minor and transient changes. Key message • Incorporation of grass-clover in soil causes increased emission of N2O. • Interaction of available organic C and mineral N governs release of greenhouse gas. • Anaerobically digested manures/biomass do not impact soil fertility and microbiota. Total emissions of CO2 and N2O over a nine-day period from untreated soil (CON) or soil amended with raw cattle slurry (S), anaerobically digested cattle slurry/maize (DS-MA), anaerobically digested cattle slurry/grassclover (DS-GC), or fresh grass-clover (GC). The materials were incorporated homogeneously into the soil. Bars indicare standard error of the mean (n-4). Deliverable D#-WP2.4 “Systematic review on the relationship between the soil microbiome and Cseq and non-CO2 GHG emissions.” This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 862695 67 Discussion and Conclusions The data available for the current review study in the 17 identified manuscripts is surely precious, but the lack of robust results obtained from long-term studies, conducted in diverse EU regions and pedoclimatic conditions, aimed at the observation of the effects of different management practices (as those for soil conservation and/or the application of an OM-based fertilization) on the soil microbial diversity and at the same time on C sequestration and N2O and other GHG emissions from soil, necessary requires further efforts to be filled. It is also worthy of note that, given the complexity of these studies for the numerous parameters involved and the different outputs to analyse, the absent/low level of standardization in relation to the field experiment, used methodology and measured data, should be addressed to allow comparisons among different climate/regional locations. At this aim, the use of soil indicators – chemical, physical and biological – and the establishment of a common experimental protocol, starting from the field design up to the soil sample collection, soil microbiome analysis (16s rRNA sequencing) and GHG emissions measurement, could help to make the comparisons and assessments of variations in soil microbiota and the trade-offs between carbon sequestration and non-CO2 GHG emissions less complex. Most of the selected articles deal with one of this management practice: tillage system, crop sequence, or addition of litter, digestate, organic waste or biochar. Positive effects from the application of OM inputs have been often identified on microbial biomass (MB), by influencing functional diversity dynamics of soil microorganisms. At the same time, a general increase in soil organic content (SOC) and potential reductions in emissions have been disclosed. Overall, apart a few contrasting results, the main findings advocate for soil biodiversity conservation to promote carbon sequestration and mitigate N2O emissions and encourage sustainable agricultural practices. Another important factor which is often taken into consideration in some of these manuscripts, besides the feedstock from which the OM proceeds, is represented by the cultivated plants: plant richness and diversity decrease soil N2O emissions and drive C sequestration. 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