Crop rotational diversity can mitigate climate-induced grain yield losses

Diversified crop rotations have been suggested to reduce grain yield losses from the adverse climatic conditions increasingly common under climate change. Nevertheless, the potential for climate change adaptation of different crop rotational diversity (CRD) remains undetermined. We quantified how climatic conditions affect small grain and maize yields under different CRDs in 32 long-term (10-63 years) field experiments across Europe and North America. Species-diverse and functionally rich rotations more than compensated yield losses from anomalous warm conditions, long and warm dry spells, as well as from anomalous wet (for small grains) or dry (for maize) conditions. Adding a single functional group or crop species to monocultures counteracted yield losses from substantial changes in climatic conditions. The benefits of a further increase in CRD are comparable with those of improved climatic conditions. For instance, the maize yield benefits of adding three crop species to monocultures under detrimental climatic conditions exceeded the average yield of monocultures by up to 553 kg/ha under non-detrimental climatic conditions. Increased crop functional richness improved yields under high temperature, irrespective of precipitation. Conversely, yield benefits peaked at between two and four crop species in the rotation, depending on climatic conditions and crop, and declined at higher species diversity. Thus, crop species diversity could be adjusted to maximize yield benefits. Diversifying rotations with functionally distinct crops is an adaptation of cropping systems to global warming and changes in precipitation.

Challenges of accounting nitrous oxide emissions from agricultural crop residues

Crop residues are important inputs of carbon (C) and nitrogen (N) to soils and thus directly and indirectly affect nitrous oxide (N2 O) emissions. As the current inventory methodology considers N inputs by crop residues as the sole determining factor for N2 O emissions, it fails to consider other underlying factors and processes. There is compelling evidence that emissions vary greatly between residues with different biochemical and physical characteristics, with the concentrations of mineralizable N and decomposable C in the residue biomass both enhancing the soil N2 O production potential. High concentrations of these components are associated with immature residues (e.g., cover crops, grass, legumes, and vegetables) as opposed to mature residues (e.g., straw). A more accurate estimation of the short-term (months) effects of the crop residues on N2 O could involve distinguishing mature and immature crop residues with distinctly different emission factors. The medium-term (years) and long-term (decades) effects relate to the effects of residue management on soil N fertility and soil physical and chemical properties, considering that these are affected by local climatic and soil conditions as well as land use and management. More targeted mitigation efforts for N2 O emissions, after addition of crop residues to the soil, are urgently needed and require an improved methodology for emission accounting. This work needs to be underpinned by research to (1) develop and validate N2 O emission factors for mature and immature crop residues, (2) assess emissions from belowground residues of terminated crops, (3) improve activity data on management of different residue types, in particular immature residues, and (4) evaluate long-term effects of residue addition on N2 O emissions.

AgroEcoList 1.0: A checklist to improve reporting standards in ecological research in agriculture

Many publications lack sufficient background information (e.g. location) to be interpreted, replicated, or reused for synthesis. This impedes scientific progress and the application of science to practice. Reporting guidelines (e.g. checklists) improve reporting standards. They have been widely taken up in the medical sciences, but not in ecological and agricultural research. Here, we use a community-centred approach to develop a reporting checklist (AgroEcoList 1.0) through surveys and workshops with 23 experts and the wider agroecological community. To put AgroEcoList in context, we also assessed the agroecological community's perception of reporting standards in agroecology. A total of 345 researchers, reviewers, and editors, responded to our survey. Although only 32% of respondents had prior knowledge of reporting guidelines, 76% of those that had said guidelines improved reporting standards. Overall, respondents agreed on the need of AgroEcolist 1.0; only 24% of respondents had used reporting guidelines before, but 78% indicated they would use AgroEcoList 1.0. We updated AgroecoList 1.0 based on respondents' feedback and user-testing. AgroecoList 1.0 consists of 42 variables in seven groups: experimental/sampling set-up, study site, soil, livestock management, crop and grassland management, outputs, and finances. It is presented here, and is also available on github (https://github.com/AgroecoList/Agroecolist). AgroEcoList 1.0 can serve as a guide for authors, reviewers, and editors to improve reporting standards in agricultural ecology. Our community-centred approach is a replicable method that could be adapted to develop reporting checklists in other fields. Reporting guidelines such as AgroEcoList can improve reporting standards and therefore the application of research to practice, and we recommend that they are adopted more widely in agriculture and ecology.

Translating and applying a simulation model to enhance understanding of grassland management

Each new generation of grassland managers could benefit from an improved understanding of how modification of nitrogen application and harvest dates in response to different weather and soil conditions will affect grass yields and quality. The purpose of this study was to develop a freely available grass yield simulation model, validated for England and Wales, and to examine its strengths and weaknesses as a teaching tool for improving grass management. The model, called LINGRA-N-Plus, was implemented in a Microsoft Excel spreadsheet and iteratively evaluated by students and practitioners (farmers, consultants, and researchers) in a series of workshops across the UK over 2 years. The iterative feedback led to the addition of new algorithms, an improved user interface, and the development of a teaching guide. The students and practitioners identified the ease of use and the capacity to understand, visualize and evaluate how decisions, such as variation of cutting intervals, affect grass yields as strengths of the model. We propose that an effective teaching tool must achieve an appropriate balance between being sufficiently detailed to demonstrate the major relationships (e.g., the effect of nitrogen on grass yields) whilst not becoming so complex that the relationships become incomprehensible. We observed that improving the user-interface allowed us to extend the scope of the model without reducing the level of comprehension. The students appeared to be interested in the explanatory nature of the model whilst the practitioners were more interested in the application of a validated model to enhance their decision making.

A review and meta-analysis of mitigation measures for nitrous oxide emissions from crop residues

Crop residues are of crucial importance to maintain or even increase soil carbon stocks and fertility, and thereby to address the global challenge of climate change mitigation. However, crop residues can also potentially stimulate emissions of the greenhouse gas nitrous oxide (N₂O) from soils. A better understanding of how to mitigate N₂O emissions due to crop residue management while promoting positive effects on soil carbon is needed to reconcile the opposing effects of crop residues on the greenhouse gas balance of agroecosystems. Here, we combine a literature review and a meta-analysis to identify and assess measures for mitigating N₂O emissions due to crop residue application to agricultural fields. Our study shows that crop residue removal, shallow incorporation, incorporation of residues with C:N ratio > 30 and avoiding incorporation of residues from crops terminated at an immature physiological stage, are measures leading to significantly lower N₂O emissions. Other practices such as incorporation timing and interactions with fertilisers are less conclusive. Several of the evaluated N₂O mitigation measures implied negative side-effects on yield, soil organic carbon storage, nitrate leaching and/or ammonia volatilization. We identified additional strategies with potential to reduce crop residue N₂O emissions without strong negative side-effects, which require further research. These are: a) treatment of crop residues before field application, e.g., conversion of residues into biochar or anaerobic digestate, b) co-application with nitrification inhibitors or N-immobilizing materials such as compost with a high C:N ratio, paper waste or sawdust, and c) use of residues obtained from crop mixtures. Our study provides a scientific basis to be developed over the coming years on how to increase the sustainability of agroecosystems though adequate crop residue management.

Predicting field N2O emissions from crop residues based on their biochemical composition: A meta-analytical approach

Crop residue incorporation is a common practice to increase or restore organic matter stocks in agricultural soils. However, this practice often increases emissions of the powerful greenhouse gas nitrous oxide (N₂O). Previous meta-analyses have linked various biochemical properties of crop residues to N₂O emissions, but the relationships between these properties have been overlooked, hampering our ability to predict N₂O emissions from specific residues. Here we combine comprehensive databases for N₂O emissions from crop residues and crop residue biochemical characteristics with a random-meta-forest approach, to develop a predictive framework of crop residue effects on N₂O emissions. On average, crop residue incorporation increased soil N₂O emissions by 43% compared to residue removal, however crop residues led to both increases and reductions in N₂O emissions. Crop residue effects on N₂O emissions were best predicted by easily degradable fractions (i.e. water soluble carbon, soluble Van Soest fraction (NDS)), structural fractions and N returned with crop residues. The relationship between these biochemical properties and N₂O emissions differed widely in terms of form and direction. However, due to the strong correlations among these properties, we were able to develop a simplified classification for crop residues based on the stage of physiological maturity of the plant at which the residue was generated. This maturity criteria provided the most robust and yet simple approach to categorize crop residues according to their potential to regulate N₂O emissions. Immature residues (high water soluble carbon, soluble NDS and total N concentration, low relative cellulose, hemicellulose, lignin fractions, and low C:N ratio) strongly stimulated N₂O emissions, whereas mature residues with opposite characteristics had marginal effects on N₂O. The most important crop types belonging to the immature residue group - cover crops, grasslands and vegetables - are important for the delivery of multiple ecosystem services. Thus, these residues should be managed properly to avoid their potentially high N₂O emissions.

Global Research Alliance N2 O chamber methodology guidelines: Statistical considerations, emission factor calculation, and data reporting

Static chambers are often used for measuring nitrous oxide (N₂ O) fluxes from soils, but statistical analysis of chamber data is challenged by the inherently heterogeneous nature of N₂ O fluxes. Because N₂ O chamber measurements are commonly used to assess N₂ O mitigation strategies or to determine country-specific emission factors (EFs) for calculating national greenhouse gas inventories, it is important that statistical analysis of the data is sound and that EFs are robustly estimated. This paper is one of a series of articles that provide guidance on different aspects of N₂ O chamber methodologies. Here, we discuss the challenges associated with statistical analysis of heterogeneous data, by summarizing statistical approaches used in recent publications and providing guidance on assessing normality and options for transforming data that follow a non-normal distribution. We also recommend minimum requirements for reporting of experimental and metadata of N₂ O studies to ensure that the robustness of the results can be reliably evaluated. This includes detailed information on the experimental site, methodology and measurement procedures, gas analysis, data and statistical analyses, and approaches to generate EFs, as well as results of ancillary measurements. The reliability, robustness, and comparability of soil N₂ O emissions data will be improved through (a) application, and reporting, of more rigorous methodological standards by researchers and (b) greater vigilance by reviewers and scientific editors to ensure that all necessary information is reported in scientific publications.

Calibration and validation of the DNDC model to estimate nitrous oxide emissions and crop productivity for a summer maize-winter wheat double cropping system in Hebei, China

The main aim of this paper was to calibrate and evaluate the DeNitrification-DeComposition (DNDC) model for estimating N₂O emissions and crop productivity for a summer maize-winter wheat double cropping system with different N fertilizer rates in Hebei, China. The model's performance was assessed before and after calibration and model sensitivity was investigated. The calibrated and validated DNDC performed effectively in estimating cumulative N₂O emissions (coefficient of determination (1:1 relationship; r²) = 0.91; relative deviation (RD) = -13 to 16%) and grain yields for both crops (r² = 0.91; RD = -21 to 7%) from all fertilized treatments, but poorly estimated daily N₂O patterns. Observed and simulated results showed that optimal N fertilizer treatment decreased cumulative N₂O flux, compared to conventional N fertilizer, without a significant impact on grain yields of the summer maize-winter wheat double cropping system. The high sensitivity of the DNDC model to rainfall, soil organic carbon and temperature resulted in significant overestimation of N₂O peaks during the warm wet season. The model also satisfactorily estimated daily patterns/average soil temperature (^o C; 0-5 cm depth) (r² = 0.88 to 0.89; root mean square error (RMSE) = 4 °C; normalized RMSE (nRMSE) = 25% and index of agreement (d) = 0.89-0.97) but under-predicted water filled pore space (WFPS; %; 0-20 cm depth) (r² = 0.3 to 0.4) and soil ammonium and nitrate (exchangeable NH₄⁺ & NO₃^-; kg N ha^-1; r² = 0.97). With reference to the control treatment (no N fertilizer), DNDC was weak in simulating both N₂O emissions and crop productivity. To be further improved for use under pedo-climatic conditions of the summer maize-winter wheat double cropping system we suggest future studies to identify and resolve the existing problems with the DNDC, especially with the control treatment.

Oxygen Regulates Nitrous Oxide Production Directly in Agricultural Soils

Oxygen (O₂) plays a critical and yet poorly understood role in regulating nitrous oxide (N₂O) production in well-structured agricultural soils. We investigated the effects of in situ O₂ dynamics on N₂O production in a typical intensively managed Chinese cropping system under a range of environmental conditions (temperature, moisture, ammonium, nitrate, dissolved organic carbon, and so forth). Climate and management (fertilization, irrigation, precipitation, and temperature), and their interactions significantly affected soil O₂ and N₂O concentrations (P < 0.05). Soil O₂ concentration was the most significant factor correlating with soil N₂O concentration (r = -0.71) when compared with temperature, water-filled pore space, and ammonium concentration (r = 0.30, 0.25, and 0.26, respectively). Soil N₂O concentration increased exponentially with decreasing soil O₂ concentrations. The exponential model of N treatments and fertilization with irrigation/precipitation events predicted 74-90% and 58% of the variance in soil N₂O concentrations, respectively. Our results highlight that the soil O₂ status is the proximal, direct, and the most decisive environmental trigger for N₂O production, outweighing the effects of other factors and could be a key variable integrating the aggregated effects of various complex interacting variables. This study offers new opportunities for developing more sensitive approaches to predicting and through appropriate management interventions mitigating N₂O emissions from agricultural soils.

Use of Raman microspectroscopy to predict malting barley husk adhesion quality

Good quality husk-caryopsis adhesion is essential for malting barley, but that quality is influenced by caryopsis surface lipid composition. Raman spectroscopy was applied to lipid extracts from barley caryopses of cultivars with differential adhesion qualities. Principal component regression indicated that Raman spectroscopy can distinguish among cultivars with good and poor quality adhesion due to differences in compounds associated with adhesion quality.

Development and Quality of Barley Husk Adhesion Correlates With Changes in Caryopsis Cuticle Biosynthesis and Composition

The caryopses of barley become firmly adhered to the husk during grain development through a cuticular cementing layer on the caryopsis surface. The degree of this attachment varies among cultivars, with poor quality adhesion causing "skinning", an economically significant grain quality defect for the malting industry. Malting cultivars encompassing a range of husk adhesion qualities were grown under a misting treatment known to induce skinning. Development of the cementing layer was examined by electron microscopy and compositional changes of the cementing layer were investigated with gas-chromatography followed by mass spectroscopy. Changes in gene expression during adhesion development were examined with a custom barley microarray. The abundance of transcripts involved early in cuticular lipid biosynthesis, including those encoding acetyl-CoA carboxylase, and all four members of the fatty acid elongase complex of enzymes, was significantly higher earlier in caryopsis development than later. Genes associated with subsequent cuticular lipid biosynthetic pathways were also expressed higher early in development, including the decarbonylation and reductive pathways, and sterol biosynthesis. Changes in cuticular composition indicate that lowered proportions of alkanes and higher proportions of fatty acids are associated with development of good quality husk adhesion, in addition to higher proportions of sterols.

Improving model prediction of soil N2O emissions through Bayesian calibration

The biogeochemical processes that lead to the production of N₂O in arable soils are controlled by temporally and spatially varying drivers. The need for prediction of soil N₂O emissions across scales means that agroecosystem biogeochemistry models are widely used to simulate N₂O emissions. Due to the parameter-dense nature of agroecosystem models their parameters have to be calibrated according to the soil and climatic conditions of the intended area of application. Bayesian calibration is considered one of the most advanced ways to complete this task. In this study, we calibrate nine parameters of the Landscape-DNDC process-based agroecosystem model, which are key to its N₂O prediction. The Metropolis-Hastings algorithm is used at four separate implementations in order to estimate parameter posterior distributions at four arable sites in the UK. The results of this process are visualised, summarised and assessed against measured N₂O data from ten independent arable sites. The study shows that, in many cases, soil N₂O emission peaks that were not predicted with the default model parameters were predicted after calibration. Overall, the prediction of soil N₂O fluxes across all the sites that were considered was improved by 33% when using the calibrated parameters.

Spatially explicit estimation of heat stress-related impacts of climate change on the milk production of dairy cows in the United Kingdom

Dairy farming is one the most important sectors of United Kingdom (UK) agriculture. It faces major challenges due to climate change, which will have direct impacts on dairy cows as a result of heat stress. In the absence of adaptations, this could potentially lead to considerable milk loss. Using an 11-member climate projection ensemble, as well as an ensemble of 18 milk loss estimation methods, temporal changes in milk production of UK dairy cows were estimated for the 21st century at a 25 km resolution in a spatially-explicit way. While increases in UK temperatures are projected to lead to relatively low average annual milk losses, even for southern UK regions (<180 kg/cow), the ‘hottest’ 25×25 km grid cell in the hottest year in the 2090s, showed an annual milk loss exceeding 1300 kg/cow. This figure represents approximately 17% of the potential milk production of today’s average cow. Despite the potential considerable inter-annual variability of annual milk loss, as well as the large differences between the climate projections, the variety of calculation methods is likely to introduce even greater uncertainty into milk loss estimations. To address this issue, a novel, more biologically-appropriate mechanism of estimating milk loss is proposed that provides more realistic future projections. We conclude that South West England is the region most vulnerable to climate change economically, because it is characterised by a high dairy herd density and therefore potentially high heat stress-related milk loss. In the absence of mitigation measures, estimated heat stress-related annual income loss for this region by the end of this century may reach £13.4M in average years and £33.8M in extreme years.

Key challenges and priorities for modelling European grasslands under climate change

Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range of environmental and cultural benefits. Climate change poses significant challenges for such systems, their productivity and the wider benefits they supply. In this context, grassland models have an important role in predicting and understanding the impacts of climate change on grassland systems, and assessing the efficacy of potential adaptation and mitigation strategies. In order to identify the key challenges for European grassland modelling under climate change, modellers and researchers from across Europe were consulted via workshop and questionnaire. Participants identified fifteen challenges and considered the current state of modelling and priorities for future research in relation to each. A review of literature was undertaken to corroborate and enrich the information provided during the horizon scanning activities. Challenges were in four categories relating to: 1) the direct and indirect effects of climate change on the sward 2) climate change effects on grassland systems outputs 3) mediation of climate change impacts by site, system and management and 4) cross-cutting methodological issues. While research priorities differed between challenges, an underlying theme was the need for accessible, shared inventories of models, approaches and data, as a resource for stakeholders and to stimulate new research. Developing grassland models to effectively support efforts to tackle climate change impacts, while increasing productivity and enhancing ecosystem services, will require engagement with stakeholders and policy-makers, as well as modellers and experimental researchers across many disciplines. The challenges and priorities identified are intended to be a resource 1) for grassland modellers and experimental researchers, to stimulate the development of new research directions and collaborative opportunities, and 2) for policy-makers involved in shaping the research agenda for European grassland modelling under climate change.

A Comparative Nitrogen Balance and Productivity Analysis of Legume and Non-legume Supported Cropping Systems: The Potential Role of Biological Nitrogen Fixation

The potential of biological nitrogen fixation (BNF) to provide sufficient N for production has encouraged re-appraisal of cropping systems that deploy legumes. It has been argued that legume-derived N can maintain productivity as an alternative to the application of mineral fertilizer, although few studies have systematically evaluated the effect of optimizing the balance between legumes and non N-fixing crops to optimize production. In addition, the shortage, or even absence in some regions, of measurements of BNF in crops and forages severely limits the ability to design and evaluate new legume-based agroecosystems. To provide an indication of the magnitude of BNF in European agriculture, a soil-surface N-balance approach was applied to historical data from 8 experimental cropping systems that compared legume and non-legume crop types (e.g., grains, forages and intercrops) across pedoclimatic regions of Europe. Mean BNF for different legume types ranged from 32 to 115 kg ha^-1 annually. Output in terms of total biomass (grain, forage, etc.) was 30% greater in non-legumes, which used N to produce dry matter more efficiently than legumes, whereas output of N was greater from legumes. When examined over the crop sequence, the contribution of BNF to the N-balance increased to reach a maximum when the legume fraction was around 0.5 (legume crops were present in half the years). BNF was lower when the legume fraction increased to 0.6-0.8, not because of any feature of the legume, but because the cropping systems in this range were dominated by mixtures of legume and non-legume forages to which inorganic N as fertilizer was normally applied. Forage (e.g., grass and clover), as opposed to grain crops in this range maintained high outputs of biomass and N. In conclusion, BNF through grain and forage legumes has the potential to generate major benefit in terms of reducing or dispensing with the need for mineral N without loss of total output.

Nitrous oxide emissions from cattle excreta applied to a Scottish grassland: effects of soil and climatic conditions and a nitrification inhibitor

Dung and urine excreted onto grasslands are a major source of nitrous oxide (N2O). These N2O emissions stem from inefficient utilisation of nitrogen (N) ingested by ruminants, and the inability of pasture to utilise the deposited N. Predicted growth in dairy and meat consumption means that there is a requirement to quantify N2O emissions, and investigate emission reduction mechanisms. Three 12 month 'seasonal' experiments were undertaken at Crichton, SW Scotland, where N2O emissions were measured from applications of cattle urine, dung, artificial urine and urine+a nitrification inhibitor (NI), dicyandiamide (DCD). The three application timings were 'spring', 'summer' and 'autumn', representative of early-, mid- and late grazing seasons. N2O emissions were measured from static chambers for 12 months. The aim was to quantify emissions from cattle excreta, and determine their dependence on the season of application, and the respective contribution of dung and urine to total excreta emissions. Measurement from NI amended urine was made to assess DCD's potential as an emission mitigation tool. Emissions were compared to the IPCC's default emission factor (EF) of 2% for cattle excreted N. Mean annual cumulative emissions from urine were the highest when applied in summer (5034 g N2O-N ha(-1)), with lower emissions from spring (1903 g N2O-N ha(-1)) and autumn (2014 g N2O-N ha(-1)) application, most likely due to higher temperatures and soil moisture conducive to both nitrification and denitrification in the summer months. Calculated EFs were significantly greater from urine (1.1%) than dung (0.2%) when excreta was applied in summer, and EFs varied with season of application, but in all experiments were lower than the IPCC default of 2%. These results support both lowering and disaggregating this EF into individual EFs for dung and urine. Addition of DCD to urine caused no significant reduction in emissions, suggesting that more research is required into its use as a mitigation option.

Review and analysis of global agricultural N₂O emissions relevant to the UK

As part of a UK government funded research project to update the UK N2O inventory methodology, a systematic review of published nitrous oxide (N2O) emission factors was carried out of non-UK research, for future comparison and synthesis with the UK measurement based evidence base. The aim of the study is to assess how the UK IPCC default emission factor for N2O emissions derived from synthetic or organic fertiliser inputs (EF1) compares to international values reported in published literature. The availability of data for comparing and/or refining the UK IPCC default value and the possibility of analysing sufficient auxiliary data to propose a Tier 2 EF1 reporting strategy is evaluated. The review demonstrated a lack of consistency in reporting error bounds for fertiliser-derived EFs and N2O flux data with 8% and 44% of publications reporting EF and N2O flux error bounds respectively. There was also poor description of environmental (climate and soil) and experimental design auxiliary data. This is likely to be due to differences in study objectives, however potential improvements to soil parameter reporting are proposed. The review demonstrates that emission factors for agricultural-derived N2O emissions ranged -0.34% to 37% showing high variation compared to the UK Tier 1 IPCC EF1 default values of 1.25% (IPCC 1996) and 1% (IPPC 2006). However, the majority (83%) of EFs reported for UK-relevant soils fell within the UK IPCC EF1 uncertainty range of 0.03% to 3%. Residual maximum likelihood (REML) analysis of the data collated in the review showed that the type and rate of fertiliser N applied and soil type were significant factors influencing EFs reported. Country of emission, the length of the measurement period, the number of splits, the crop type, pH and SOC did not have a significant impact on N2O emissions. A subset of publications where sufficient data was reported for meta-analysis to be conducted was identified. Meta-analysis of effect sizes of 41 treatments demonstrated that the application of fertiliser has a significant effect on N2O emissions in comparison to control plots and that emission factors were significantly different to zero. However no significant relationships between the quantity of fertiliser applied and the effect size of the amount of N2O emitted from fertilised plots compared to control plots were found. Annual addition of fertiliser of 35 to 557 kg N/ha gave a mean increase in emissions of 2.02 ± 0.28 g N2O/ha/day compared to control treatments (p<0.01). Emission factors were significantly different from zero, with a mean emission factor estimated directly from the meta analysis of 0.17 ± 0.02%. This is lower than the IPCC 2006 Tier 1 EF1 value of 1% but falling within the uncertainty bound for the IPCC 2006 Tier 1 EF1 (0.03% to 3%). As only a small number of papers were viable for meta analysis to be conducted due to lack of reporting of the key controlling factors, the estimates of EF in this paper cannot include the true variability under conditions similar to the UK. Review-derived EFs of 0.34% to 37% and mean EF from meta-analysis of 0.17 ± 0.02% highlight variability in reporting EFs depending on the method applied and sample size. A protocol of systematic reporting of N2O emissions and key auxiliary parameters in publications across disciplines is proposed. If adopted this would strengthen the community to inform IPCC Tier 2 reporting development and reduce the uncertainty surrounding reported UK N2O emissions.