An integral assessment of the impact of diet and manure management on whole-farm greenhouse gas and nitrogen emissions in dairy cattle production systems using process-based models.

Feed management decisions are crucial in mitigating greenhouse gas (GHG) and nitrogen (N) emissions from ruminant farming systems. However, assessing the downstream impact of diet on emissions in dairy production systems is complex, due to the multifunctional relationships between a variety of distinct but interconnected sources such as animals, housing, manure storage, and soil. Therefore, there is a need for an integral assessment of the direct and indirect GHG and N emissions that considers the underlying processes of carbon (C), N and their drivers within the system. Here we show the relevance of using a cascade of process-based (PB) models, such as Dutch Tier 3 and (Manure)-DNDC (Denitrification-Decomposition) models, for capturing the downstream influence of diet on whole-farm emissions in two contrasting case study dairy farms: a confinement system in Germany and a pasture-based system in New Zealand. Considerable variation was found in emissions on a per hectare and per head basis, and across different farm components and categories of animals. Moreover, the confinement system had a farm C emission of 1.01 kg CO2-eq kg-1 fat and protein corrected milk (FPCM), and a farm N emission of 0.0300 kg N kg-1 FPCM. In contrast, the pasture-based system had a lower farm C and N emission averaging 0.82 kg CO2-eq kg-1 FPCM and 0.006 kg N kg-1 FPCM, respectively over the 4-year period. The results demonstrate how inputs and outputs could be made compatible and exchangeable across the PB models for quantifying dietary effects on whole-farm GHG and N emissions.

Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing.

Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002-2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983-2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.

Biomass carbon stocks and stock changes in managed hedgerows.

Landscape features, such as hedgerows, can play a role in enhancing terrestrial carbon (C) sinks, especially in North-western Europe, where they form a large part of the agricultural landscape. To date, there are few studies relating aerial imagery to ground-truthed biomass measurements and relating changes in biomass to hedgerow management. This study sought to develop relationships between measured biomass of hedgerows and digital elevation model (DEM) data from drones and aircraft. Furthermore, changes in hedgerow above-ground and below-ground biomass stocks were assessed using a systematic grid sample, DEM data and developed volume-biomass regression models. The developed inventory framework was then applied to a pilot study area of 419,701 ha in Ireland. Robust relationships were developed relating DEM data to volume and above-ground biomass. Model equations were also developed linking above-ground and below-ground biomass. However, these were less robust due to the confounding impacts of hedgerow management intensity, hedgerow type and dominant species. Above-ground biomass density was linearly correlated with hedge volume. Wider, less intensively managed, irregular hedges exhibit a higher biomass stocks per km, when compared to regular, more intensively managed hedgerows. When the models were extrapolated to the county level, hedgerow biomass C pools for Co Wexford and Waterford are suggested to be a net emission of -0.3 tC ha-1 year-1 due to hedgerow removals and management. Flailing or coppicing of hedgerows, in particular irregular profile hedgerows, had the largest impact on the biomass C balance in the pilot study area. Re-introduction of traditional management practices such as layering and increasing the allowable hedgerow width in areas qualifying for farm payments could be considered with the aim of increasing the maximum sink potential of established hedgerows.

Revisiting sampling duration to estimate N2O emission factors for manure application and cattle excreta deposition for the UK and Ireland.

According to the available guidelines, good practices for calculating nitrous oxide (N2O) emission factors (EFs) for livestock excreta and manure application include that sampling duration should be of at least one year after the nitrogen (N) application or deposition. However, the available experimental data suggest that in many cases most emissions are concentrated in the first months following N application. Therefore resources could be better deployed by measuring more intensively during a shorter period. This study aimed to assess the contribution of the N2O flux in the period directly after N application to the annual net emission. We used a database of 100 year-long plot experiments from different excreted-N sources (dung, urine, farmyard manure and slurry) used to derive EFs for the UK and Ireland. We explored different shorter potential measurement periods that could be used as proxies for cumulative annual emissions. The analysis showed that the majority of emissions occur in the first months after application, especially in experiments that i) had urine as the N source, ii) had spring N application, iii) were conducted on fine-textured soils, or iv) showed high annual emissions magnitude. Experiments that showed a smaller percentage of emissions in the first months also had a low magnitude of annual net emissions (below 370 gN2O-N ha-1 year-1), so the impact of measuring during a shorter period would not greatly influence the calculated EF. Accurate EF estimations were obtained by measuring for at least 60 days for urine (underestimation: 7.1%), 120 days for dung and slurry (4.7 and 5.1%) and 180 days for FYM (1.4%). At least in temperate climates, these results are promising in terms of being able to estimate annual N2O fluxes accurately by collecting data for less than 12 months, with significant resource-saving when conducting experiments towards developing country-specific EFs.

Effect of contrasting phosphorus levels on nitrous oxide and carbon dioxide emissions from temperate grassland soils.

Agricultural practices such as repeated fertilization impact carbon (C), nitrogen (N) and phosphorus (P) cycling and their relationships in the plant-soil continuum, which could have important implications for the magnitude of greenhouse gas emissions. However, little is known about the effect of C and N additions under contrasting soil P availability status on nitrous oxide (N2O) and carbon dioxide (CO2) emissions. In this study, we conducted a field-based experiment that investigated the impact of long-term (23 years) P management (no (P0, 0 kg P ha-1), low (P15, 15 kg P ha-1) and high (P45, 45 kg P ha-1) P inputs) on N2O and CO2 emissions following two C + N application events in two managed grassland ecosystems with loam and sandy loam soils. The magnitude of fluxes varied between the soil P availability levels. Cumulative N2O emission was significantly higher in P0 soils (1.08 ± 0.09 g N2O-N m-2) than P45 soils (0.63 ± 0.03 g N2O-N m-2), with the loam soil (1.04 ± 0.04 g N2O-N m-2) producing significantly higher emissions than the sandy loam soil (0.88 ± 0.05 g N2O-N m-2). We conclude that P-limitation stimulates N2O emissions, whereas P-enrichment promotes soil respiration in these temperate grassland sites. Our findings inform effective nutrient management strategies underpinning optimized use of N and P inputs to agricultural soils as mitigation measures for both food security and reducing greenhouse gas emissions.

Beneficial effects of multi-species mixtures on N2O emissions from intensively managed grassland swards.

In a field experiment, annual nitrous oxide (N2O) emissions and grassland yield were measured across different plant communities, comprising systematically varying combinations of monocultures and mixtures of three functional groups (FG): grasses (Lolium perenne, Phleum pratense), legumes (Trifolium pratense, Trifolium repens) and herbs (Cichorium intybus, Plantago lanceolata). Plots received 150 kg ha-1 year-1 nitrogen (N) (150 N), except L. perenne monocultures which received two N levels: 150 N and 300 N. The effect of plant diversity on N2O emissions was derived from linear combinations of species performances' in monoculture (species identity) and not from strong interactions between species in mixtures. Increasing from 150 N to 300 N in L. perenne resulted in a highly significant increase in cumulative N2O emissions from 1.39 to 3.18 kg N2O-N ha-1 year-1. Higher N2O emissions were also associated with the legume FG. Emissions intensities (yield-scaled N2O emissions) from multi-species mixture communities around the equi-proportional mixture were lowered due to interactions among species. For N2O emissions scaled by nitrogen yield in forage, the 6-species mixture was significantly lower than L. perenne at both 300 N and 150 N. In comparison to 300 N L. perenne, the same N yield or DM yield could have been produced with the equi-proportional 6-species mixture (150 N) while reducing N2O losses by 63% and 58% respectively. Compared to 150 N L. perenne, the same N yield or DM yield could have been produced with the 6-species mixture while reducing N2O losses by 41% and 24% respectively. Overall, this study found that multi-species grasslands can potentially reduce both N2O emissions and emissions intensities, contributing to the sustainability of grassland production.

Competition and community succession link N transformation and greenhouse gas emissions in urine patches.

Nitrous oxide (N2O) is a strong greenhouse gas produced by biotic/abiotic processes directly linked to both fungal and prokaryotic communities that produce, consume or create conditions leading to its emission. In soils exposed to nitrogen (N) in the form of urea, an ecological succession is triggered resulting in a dynamic turnover of microbial populations. However, knowledge of the mechanisms controlling this succession and the repercussions for N2O emissions remain incomplete. Here, we monitored N2O production and fungal/prokaryotic community changes (via 16S and 18S amplicon sequencing) in soil microcosms exposed to urea. Contributions of microbes to emissions were determined using biological inhibitors. Results confirmed that urea leads to shifts in microbial community assemblages by selecting for certain microbial groups (fast growers) as dictated through life history strategies. Urea reduced overall community diversity by conferring dominance to specific groups at different stages in the succession. The diversity lost under urea was recovered with inhibitor addition through the removal of groups that were actively growing under urea indicating that species replacement is mediated in part by competition. Results also identified fungi as significant contributors to N2O emissions, and demonstrate that dominant fungal populations are consistently replaced at different stages of the succession. These successions were affected by addition of inhibitors which resulted in strong decreases in N2O emissions, suggesting that fungal contributions to N2O emissions are larger than that of prokaryotes.

Source partitioning using N2O isotopomers and soil WFPS to establish dominant N2O production pathways from different pasture sward compositions.

Nitrous oxide (N2O) is a potent greenhouse gas (GHG) emitted from agricultural soils and is influenced by nitrogen (N) fertiliser management and weather and soil conditions. Source partitioning N2O emissions related to management practices and soil conditions could suggest effective mitigation strategies. Multispecies swards can maintain herbage yields at reduced N fertiliser rates compared to grass monocultures and may reduce N losses to the wider environment. A restricted-simplex centroid experiment was used to measure daily N2O fluxes and associated isotopomers from eight experimental plots (7.8 m2) post a urea-N fertiliser application (40 kg N ha-1). Experimental pastures consisted of differing proportions of grass, legume and forage herb represented by perennial ryegrass (Lolium perenne), white clover (Trifolium repens) and ribwort plantain (Plantago lanceolata), respectively. N2O isotopomers were measured using a cavity ring down spectroscopy (CRDS) instrument adapted with a small sample isotope module (SSIM) for the analysis of gas samples ≤20 mL. Site preference (SP = δ15Nα - δ15Nß) and δ15Nbulk ((δ15Nα + δ15Nß) / 2) values were used to attribute N2O production to nitrification, denitrification or a mixture of both nitrification and denitrification over a range of soil WFPS (%). Daily N2O fluxes ranged from 8.26 to 86.86 g N2O-N ha-1 d-1. Overall, 34.2% of daily N2O fluxes were attributed to nitrification, 29.0% to denitrification and 36.8% to a mixture of both. A significant diversity effect of white clover and ribwort plantain on predicted SP and δ15Nbulk indicated that the inclusion of ribwort plantain may decrease N2O emission through biological nitrification inhibition under drier soil conditions (31%-75% WFPS). Likewise, a sharp decline in predicted SP indicates that increased white clover content could increase N2O emissions associated with denitrification under elevated soil moisture conditions (43%-77% WFPS). Biological nitrification inhibition from ribwort plantain inclusion in grassland swards and management of N fertiliser source and application timing to match soil moisture conditions could be useful N2O mitigation strategies.

Challenges and opportunities to capture dietary effects in on-farm greenhouse gas emissions models of ruminant systems.

This paper reviews existing on-farm GHG accounting models for dairy cattle systems and their ability to capture the effect of dietary strategies in GHG abatement. The focus is on methane (CH4) emissions from enteric and manure (animal excreta) sources and nitrous oxide (N2O) emissions from animal excreta. We identified three generic modelling approaches, based on the degree to which models capture diet-related characteristics: from 'none' (Type 1) to 'some' by combining key diet parameters with emission factors (EF) (Type 2) to 'many' by using process-based modelling (Type 3). Most of the selected on-farm GHG models have adopted a Type 2 approach, but a few hybrid Type 2 / Type 3 approaches have been developed recently that combine empirical modelling (through the use of CH4 and/or N2O emission factors; EF) and process-based modelling (mostly through rumen and whole tract fermentation and digestion). Empirical models comprising key dietary inputs (i.e., dry matter intake and organic matter digestibility) can predict CH4 and N2O emissions with reasonable accuracy. However, the impact of GHG mitigation strategies often needs to be assessed in a more integrated way, and Type 1 and Type 2 models frequently lack the biological foundation to do this. Only Type 3 models represent underlying mechanisms such as ruminal and total-tract digestive processes and excreta composition that can capture dietary effects on GHG emissions in a more biological manner. Overall, the better a model can simulate rumen function, the greater the opportunity to include diet characteristics in addition to commonly used variables, and thus the greater the opportunity to capture dietary mitigation strategies. The value of capturing the effect of additional animal feed characteristics on the prediction of on-farm GHG emissions needs to be carefully balanced against gains in accuracy, the need for additional input and activity data, and the variability encountered on-farm.

Development and verification of a novel isotopic N2 O measurement technique for discrete static chamber samples using cavity ring-down spectroscopy.

RATIONALE: N2 O isotopomers are a useful tool to study soil N cycling processes. The reliability of such measurements requires a consistent set of international N2 O isotope reference materials to improve inter-laboratory and inter-instrument comparability and avoid reporting inaccurate results. All these are the more important given the role of N2 O in anthropogenic climate change and the pressing need to develop our understanding of soil N cycling and N2 O emission to mitigate such emissions. Cavity ring-down spectroscopy (CRDS) could potentially overcome resource requirements and technical challenges, making N2 O isotopomer measurements more feasible and less expensive than previous approaches (e.g., gas chromatography [GC] and isotope ratio mass spectrometry [IRMS]). METHODS: A combined laser spectrometer and small sample isotope module (CRDS & SSIM) method enabled N2 O concentration, δ15 Nbulk , δ15 Nα , δ15 Nß and site preference (SP) measurements of sample volumes <20 mL, such as static chamber samples. Sample dilution and isotopic mixing as well as N2 O concentration dependence were corrected numerically. A two-point calibration procedure normalised δ values to the international isotope-ratio scales. The CRDS & SSIM repeatability was determined using a reference gas (Ref Gas). CRDS & SSIM concentration measurements were compared with those obtained by GC, and the isotope ratio measurements from two different mass spectrometers were compared. RESULTS: The repeatability (mean ± 1σ; n = 10) of the CRDS & SSIM measurements of the Ref Gas was 710.64 ppb (± 8.64), 2.82‰ (± 0.91), 5.41‰ (± 2.00), 0.23‰ (± 0.22) and 5.18‰ (± 2.18) for N2 O concentration, δ15 Nbulk , δ15 Nα , δ15 Nß and SP, respectively. The CRDS & SSIM concentration measurements were strongly correlated with GC (r = 0.99), and they were more precise than those obtained using GC except when the N2 O concentrations exceeded the specified operating range. Normalising CRDS & SSIM δ values to the international isotope-ratio scales using isotopic N2 O standards (AK1 and Mix1) produced accurate results when the samples were bracketed within the range of the δ values of the standards. The CRDS & SSIM δ15 Nbulk and SP precision was approximately one order of magnitude less than the typical IRMS precision. CONCLUSIONS: CRDS & SSIM is a promising approach that enables N2 O concentrations and isotope ratios to be measured by CRDS for samples <20 mL. The CRDS & SSIM repeatability makes this approach suitable for N2 O "isotopomer mapping" to distinguish dominant source pathways, such as nitrification and denitrification, and requires less extensive lab resources than the traditionally used GC/IRMS. Current study limitations highlighted potential improvements for future users of this approach to consider, such as automation and physical removal of interfering trace gases before sample analysis.

Sward composition and soil moisture conditions affect nitrous oxide emissions and soil nitrogen dynamics following urea-nitrogen application.

Increased emissions of N2O, a potent greenhouse gas (GHG), from agricultural soils is a major concern for the sustainability of grassland agriculture. Emissions of N2O are closely associated with the rates and forms of N fertilisers applied as well as prevailing weather and soil conditions. Evidence suggests that multispecies swards require less fertiliser N input, and may cycle N differently, thus reducing N loss to the environment. This study used a restricted simplex-centroid experimental design to investigate N2O emissions and soil N cycling following application of urea-N (40 kg N ha-1) to eight experimental swards (7.8 m2) with differing proportions of three plant functional groups (grass, legume, herb) represented by perennial ryegrass (PRG, Lolium perenne), white clover (WC, Trifolium repens) and ribwort plantain (PLAN, Plantago lanceolata), respectively. Swards were maintained under two contrasting soil moisture conditions to examine the balance between nitrification and denitrification. Two N2O peaks coincided with fertiliser application and heavy rainfall events; 13.4 and 17.7 g N2O-N ha-1 day-1 (ambient soil moisture) and 39.8 and 86.9 g N2O-N ha-1 day-1 (wet soil moisture). Overall, cumulative N2O emissions post-fertiliser application were higher under wet soil conditions. Increasing legume (WC) proportions from 0% to 60% in multispecies swards resulted in model predicted N2O emissions increasing from 22.3 to 96.2 g N2O-N ha-1 (ambient soil conditions) and from 59.0 to 219.3 g N2O-N ha-1 (wet soil conditions), after a uniform N application rate. Soil N dynamics support denitrification as the dominant source of N2O especially under wet soil conditions. Significant interactions of PRG or WC with PLAN on soil mineral N concentrations indicated that multispecies swards containing PLAN potentially inhibit nitrification and could be a useful mitigation strategy for N loss to the environment from grassland agriculture.

Impact of nitrogen compounds on fungal and bacterial contributions to codenitrification in a pasture soil.

Ruminant urine patches on grazed grassland are a significant source of agricultural nitrous oxide (N2O) emissions. Of the many biotic and abiotic N2O production mechanisms initiated following urine-urea deposition, codenitrification resulting in the formation of hybrid N2O, is one of the least understood. Codenitrification forms hybrid N2O via biotic N-nitrosation, co-metabolising organic and inorganic N compounds (N substrates) to produce N2O. The objective of this study was to assess the relative significance of different N substrates on codenitrification and to determine the contributions of fungi and bacteria to codenitrification. 15N-labelled ammonium, hydroxylamine (NH2OH) and two amino acids (phenylalanine or glycine) were applied, separately, to sieved soil mesocosms eight days after a simulated urine event, in the absence or presence of bacterial and fungal inhibitors. Soil chemical variables and N2O fluxes were monitored and the codenitrified N2O fluxes determined. Fungal inhibition decreased N2O fluxes by ca. 40% for both amino acid treatments, while bacterial inhibition only decreased the N2O flux of the glycine treatment, by 14%. Hydroxylamine (NH2OH) generated the highest N2O fluxes which declined with either fungal or bacterial inhibition alone, while combined inhibition resulted in a 60% decrease in the N2O flux. All the N substrates examined participated to some extent in codenitrification. Trends for codenitrification under the NH2OH substrate treatment followed those of total N2O fluxes (85.7% of total N2O flux). Codenitrification fluxes under non-NH2OH substrate treatments (0.7-1.2% of total N2O flux) were two orders of magnitude lower, and significant decreases in these treatments only occurred with fungal inhibition in the amino acid substrate treatments. These results demonstrate that in situ studies are required to better understand the dynamics of codenitrification substrates in grazed pasture soils and the associated role that fungi have with respect to codenitrification.

Simulation of soil carbon efflux from an arable soil using the ECOSSE model: Need for an improved model evaluation framework?

Globally, it is estimated that ~1500PgC of organic carbon is stored in the top meter of terrestrial soils. This represents the largest terrestrial pool of carbon. Appropriate management of soils, to maintain or increase the soil carbon pool, represents a significant climate change mitigation opportunity. To achieve this, appropriate tools and models are required in order to more accurately estimate soil carbon fluxes with a view to informing and developing more effective land use management strategies. Central to this is the evaluation of models currently in use to estimate soil carbon emissions. In the present study, we evaluate the ECOSSE (Estimating Carbon in Organic Soils - Sequestration and Emissions) model which has its origins in both SUNDIAL and RothC and has been widely used globally to model soil CO2 fluxes across different locations and land-use types on both organic and mineral soils. In contrast to previous studies, the model was found to poorly represent observed soil respiration at the study site, an arable cropland on mineral soil located in south-east Ireland. To isolate potential sources of error, the model was decomposed into its component rate equations or modifiers. This investigation highlighted a deficiency in the model simulated soil water, resulting in significant inhibition of the model simulated CO2 flux relative to the observed data. When measured values of soil water at the site were employed, the model simulated soil respiration improved significantly (r2 of 0.775 vs 0.154). This highlighted model deficiency remains to be evaluated at other sites; however, the research highlights the need for a more comprehensive evaluation of soil carbon models prior to their use in informing policy, particularly models which are employed at larger scales and for climate change projections.

Author Correction: Influence of soil moisture on codenitrification fluxes from a urea-affected pasture soil.

A correction has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Response to nitrogen addition reveals metabolic and ecological strategies of soil bacteria.

The nitrogen (N) cycle represents one of the most well-studied systems, yet the taxonomic diversity of the organisms that contribute to it is mostly unknown, or linked to poorly characterized microbial groups. While new information has allowed functional groups to be refined, they still rely on a priori knowledge of enzymes involved and the assumption of functional conservation, with little connection to the role the transformations, plays for specific organisms. Here, we use soil microcosms to test the impact of N deposition on prokaryotic communities. By combining chemical, genomic and transcriptomic analysis, we are able to identify and link changes in community structure to specific organisms catalysing given chemical reactions. Urea deposition led to a decrease in prokaryotic richness, and a shift in community composition. This was driven by replacement of stable native populations, which utilize energy from N-linked redox reactions for physiological maintenance, with fast responding populations that use this energy for growth. This model can be used to predict response to N disturbances and allows us to identify putative life strategies of different functional and taxonomic groups, thus providing insights into how they persist in ecosystems by niche differentiation.

Influence of soil moisture on codenitrification fluxes from a urea-affected pasture soil.

Intensively managed agricultural pastures contribute to N2O and N2 fluxes resulting in detrimental environmental outcomes and poor N use efficiency, respectively. Besides nitrification, nitrifier-denitrification and heterotrophic denitrification, alternative pathways such as codenitrification also contribute to emissions under ruminant urine-affected soil. However, information on codenitrification is sparse. The objectives of this experiment were to assess the effects of soil moisture and soil inorganic-N dynamics on the relative contributions of codenitrification and denitrification (heterotrophic denitrification) to the N2O and N2 fluxes under a simulated ruminant urine event. Repacked soil cores were treated with 15N enriched urea and maintained at near saturation (-1 kPa) or field capacity (-10 kPa). Soil inorganic-N, pH, dissolved organic carbon, N2O and N2 fluxes were measured over 63 days. Fluxes of N2, attributable to codenitrification, were at a maximum when soil nitrite (NO2-) concentrations were elevated. Cumulative codenitrification was higher (P = 0.043) at -1 kPa. However, the ratio of codenitrification to denitrification did not differ significantly with soil moisture, 25.5 ± 15.8 and 12.9 ± 4.8% (stdev) at -1 and -10 kPa, respectively. Elevated soil NO2- concentrations are shown to contribute to codenitrification, particularly at -1 kPa.

Clay illuviation provides a long-term sink for C sequestration in subsoils.

Soil plays a key role in the global carbon (C) cycle. Most current assessments of SOC stocks and the guidelines given by Intergovernmental Panel on Climate Change (IPCC) focus on the top 30 cm of soil. Our research shows that, when considering only total quantities, most of the SOC stocks are found in this top layer. However, not all forms of SOC are equally valuable as long-term stable stores of carbon: the majority of SOC is available for mineralisation and can potentially be re-emitted to the atmosphere. SOC associated with micro-aggregates and silt plus clay fractions is more stable and therefore represents a long-term carbon store. Our research shows that most of this stable carbon is located at depths below 30 cm (42% of subsoil SOC is located in microaggregates and silt and clay, compared to 16% in the topsoil), specifically in soils that are subject to clay illuviation. This has implications for land management decisions in temperate grassland regions, defining the trade-offs between primary productivity and C emissions in clay-illuviated soils, as a result of drainage. Therefore, climate smart land management should consider the balance between SOC stabilisation in topsoils for productivity versus sequestration in subsoils for climate mitigation.

Phylogenetic and functional potential links pH and N2O emissions in pasture soils.

Denitrification is mediated by microbial, and physicochemical, processes leading to nitrogen loss via N2O and N2 emissions. Soil pH regulates the reduction of N2O to N2, however, it can also affect microbial community composition and functional potential. Here we simultaneously test the link between pH, community composition, and the N2O emission ratio (N2O/(NO + N2O + N2)) in 13 temperate pasture soils. Physicochemical analysis, gas kinetics, 16S rRNA amplicon sequencing, metagenomic and quantitative PCR (of denitrifier genes: nirS, nirK, nosZI and nosZII) analysis were carried out to characterize each soil. We found strong evidence linking pH to both N2O emission ratio and community changes. Soil pH was negatively associated with N2O emission ratio, while being positively associated with both community diversity and total denitrification gene (nir &nos) abundance. Abundance of nosZII was positively linked to pH, and negatively linked to N2O emissions. Our results confirm that pH imposes a general selective pressure on the entire community and that this results in changes in emission potential. Our data also support the general model that with increased microbial diversity efficiency increases, demonstrated in this study with lowered N2O emission ratio through more efficient conversion of N2O to N2.