Elucidating three-way interactions between soil, pasture and animals that regulate nitrous oxide emissions from temperate grazing systems

Feasibility of mitigation measures for agricultural greenhouse gas emissions in the UK. A systematic review

The UK Government has set an ambitious target of achieving a national "net-zero" greenhouse gas economy by 2050. Agriculture is arguably placed at the heart of achieving net zero, as it plays a unique role as both a producer of GHG emissions and a sector that has the capacity via land use to capture carbon (C) when managed appropriately, thus reducing the concentration of carbon dioxide (CO2) in the atmosphere. Agriculture's importance, particularly in a UK-specific perspective, which is also applicable to many other temperate climate nations globally, is that the majority of land use nationwide is allocated to farming. Here, we present a systematic review based on peer-reviewed literature and relevant "grey" reports to address the question "how can the agricultural sector in the UK reduce, or offset, its direct agricultural emissions at the farm level?" We considered the implications of mitigation measures in terms of food security and import reliance, energy, environmental degradation, and value for money. We identified 52 relevant studies covering major foods produced and consumed in the UK. Our findings indicate that many mitigation measures can indeed contribute to net zero through GHG emissions reduction, offsetting, and bioenergy production, pending their uptake by farmers. While the environmental impacts of mitigation measures were covered well within the reviewed literature, corresponding implications regarding energy, food security, and farmer attitudes towards adoption received scant attention. We also provide an open-access, informative, and comprehensive dataset for agri-environment stakeholders and policymakers to identify the most promising mitigation measures. This research is of critical value to researchers, land managers, and policymakers as an interim guideline resource while more quantitative evidence becomes available through the ongoing lab-, field-, and farm-scale trials which will improve the reliability of agricultural sustainability modelling in the future.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13593-023-00938-0.

Are single global warming potential impact assessments adequate for carbon footprints of agri-food systems?

The vast majority of agri-food climate-based sustainability analyses use global warming potential (GWP100) as an impact assessment, usually in isolation; however, in recent years, discussions have criticised the 'across-the-board' application of GWP100 in Life Cycle Assessments (LCAs), particularly of food systems which generate large amounts of methane (CH4) and considered whether reporting additional and/or alternative metrics may be more applicable to certain circumstances or research questions (e.g. Global Temperature Change Potential (GTP)). This paper reports a largescale sensitivity analysis using a pasture-based beef production system (a high producer of CH4 emissions) as an exemplar to compare various climatatic impact assessments: CO2-equivalents using GWP100 and GTP100, and 'CO2-warming-equivalents' using 'GWP Star', or GWP*. The inventory for this system was compiled using data from the UK Research and Innovation National Capability, the North Wyke Farm Platform, in Devon, SW England. LCAs can have an important bearing on: (i) policymakers' decisions; (ii) farmer management decisions; (iii) consumers' purchasing habits; and (iv) wider perceptions of whether certain activities can be considered 'sustainable' or not; it is, therefore, the responsibility of LCA practitioners and scientists to ensure that subjective decisions are tested as robustly as possible through appropriate sensitivity and uncertainty analyses. We demonstrate herein that the choice of climate impact assessment has dramatic effects on interpretation, with GWP100 and GTP100 producing substantially different results due to their different treatments of CH4 in the context of carbon dioxide (CO2) equivalents. Given its dynamic nature and previously proven strong correspondence with climate models, out of the three assessments covered, GWP* provides the most complete coverage of the temporal evolution of temperature change for different greenhouse gas emissions. We extend previous discussions on the limitations of static emission metrics and encourage LCA practitioners to consider due care and attention where additional information or dynamic approaches may prove superior, scientifically speaking, particularly in cases of decision support.

Response of soil health indicators to dung, urine and mineral fertilizer application in temperate pastures

Healthy soils are key to sustainability and food security. In temperate grasslands, not many studies have focused on soil health comparisons between contrasting pasture systems under different management strategies and treatment applications (e.g. manures and inorganic fertilisers). The aim of this study was to assess the responses of soil health indicators to dung, urine and inorganic N fertiliser in three temperate swards: permanent pasture not ploughed for at least 20 years (PP), high sugar ryegrass with white clover targeted at 30% coverage reseeded in 2013 (WC), and high sugar ryegrass reseeded in 2014 (HG). This study was conducted on the North Wyke Farm Platform (UK) from April 2017 to October 2017. Soil health indicators including soil organic carbon (SOC, measured by loss of ignition and elemental analyser), dissolved organic carbon (DOC), total nitrogen (TN), C:N ratio, soil C and N bulk isotopes, pH, bulk density (BD), aggregate stability, ergosterol concentration (as a proxy for fungi biomass), and earthworms (abundance, mass and density) were measured and analysed before and after application of dung and N fertilizer, urine and N fertiliser, and only N fertiliser. The highest SOC, TN, DOC, ergosterol concentration and earthworms as well as the lowest BD were found in PP, likely due to the lack of ploughing. Differences among treatments were observed due to the application of dung, resulting in an improvement in chemical indicators of soil health after 50 days of its application. Ergosterol concentration was significantly higher before treatment applications than at the end of the experiment. No changes were detected in BD and aggregate stability after treatment applications. We conclude that not enough time had passed for the soil to recover after the ploughing and reseeding of the permanent pasture, independently of the sward composition (HG or WC). Our results highlight the strong influence of the soil management legacy in temperate pasture and the positive effects of dung application on soil health over the short term. In addition, we point out the relevance of using standardised methods to report soil health indicators and some methodological limitations.

CO2 fluxes from three different temperate grazed pastures using Eddy covariance measurements

Grasslands cover around 25% of the global ice-free land surface, they are used predominantly for forage and livestock production and are considered to contribute significantly to soil carbon (C) sequestration. Recent investigations into using 'nature-based solutions' to limit warming to <2 °C suggest up to 25% of GHG mitigation might be achieved through changes to grassland management. In this study we evaluate pasture management interventions at the Rothamsted Research North Wyke Farm Platform, under commercial farming conditions, over two years and consider their impacts on net CO₂ exchange. We investigate if our permanent pasture system (PP) is, in the short-term, a net sink for CO₂ and whether reseeding this with deep-rooting, high-sugar grass (HS) or a mix of high-sugar grass and clover (HSC) might increase the net removal of atmospheric CO₂. In general CO₂ fluxes were less variable in 2018 than in 2017 while overall we found that net CO₂ fluxes for the PP treatment changed from a sink in 2017 (-5.40 t CO₂ ha^-1 y^-1) to a source in 2018 (6.17 t CO₂ ha^-1 y^-1), resulting in an overall small source of 0.76 t CO₂ ha^-1 over the two years for this treatment. HS showed a similar trend, changing from a net sink in 2017 (-4.82 t CO₂ ha^-1 y^-1) to a net source in 2018 (3.91 t CO₂ ha^-1 y^-1) whilst the HSC field was a net source in both years (3.92 and 4.10 t CO₂ ha^-1 y^-1, respectively). These results suggested that pasture type has an influence in the atmospheric CO₂ balance and our regression modelling supported this conclusion, with pasture type and time of the year (and their interaction) being significant factors in predicting fluxes.

The Impact of Using Novel Equations to Predict Nitrogen Excretion and Associated Emissions from Pasture-Based Beef Production Systems

The excretion of nitrogen (N) in faeces and urine from beef cattle contributes to atmospheric pollution through greenhouse gas and ammonia emissions and eutrophication of land and aquatic habitats through excessive N deposition and nitrate leaching to groundwater. As N excretion by beef cattle is rarely measured directly, it is important to accurately predict losses by utilising a combined knowledge of diet and production parameters so that the effect of dietary changes on the potential environmental impact of beef production systems can be estimated. This study aimed to identify differences between IPCC and more detailed country-specific models in the prediction of N excretion and N losses at a system level and determine how the choice of model influences the interpretation of differences in diet at the system scale. The data used in this study were derived from a farm-scale experimental system consisting of three individual grazing farms, each with a different sward type: a permanent pasture, a high sugar ryegrass monoculture, and a high sugar ryegrass with white clover (~30% groundcover). Data were analysed using a mixed linear model (residual maximum likelihood analysis). The IPCC methods demonstrated significantly lower estimates of N excretion than country-specific models for the first housing period and significantly greater losses for the grazing and second housing periods. The country-specific models enabled prediction of N partitioning to urine and faeces, which is important for estimation of subsequent N losses through the production system, although the models differed in their estimates. Overall, predicted N losses were greater using the IPCC approaches compared to using more detailed country-specific approaches. The outcomes of the present study have highlighted that different models can have a substantial impact on the predicted N outputs and subsequent losses to the environment for pasture-based beef finishing systems, and the importance, therefore, of using appropriate models and parameters.

Data to identify key drivers of animal growth and carcass quality for temperate lowland sheep production systems

With the growing demand for animal-sourced foods and a serious concern over climate impacts associated with livestock farming, the sheep industry worldwide faces the formidable challenge of increasing the overall product supply while improving its resource use efficiency. As an evidence base for research to identify key drivers behind animal growth and carcass quality, longitudinal matched data of 741 ewes and 2978 lambs were collected at the North Wyke Farm Platform, a farm-scale grazing trial in Devon, UK, between 2011 and 2019. A subset of these data was subsequently analysed in a study to assess the feasibility of using a lamb's early-life liveweight as a predictor of carcass quality [1]. The data also have the potential to offer insight into key performance indicators (KPIs) for the sheep industry, or what variables farmers should measure and target to increase profitability.

Using a lamb's early-life liveweight as a predictor of carcass quality

The commercial value of lamb carcasses is primarily determined by their weight and quality, with the latter commonly quantified according to muscle coverage and fat depth. The ability to predict these quality scores early in the season could be of substantial value to sheep producers, as this would enable tailored flock management strategies for different groups of animals. Existing methods of carcass quality prediction, however, require either expensive equipment or information immediately before slaughter, leaving them unsuitable as a decision support tool for small to medium-scale enterprises. Using seven-year high-resolution data from the North Wyke Farm Platform, a system-scale grazing trial in Devon, UK, this paper investigates the feasibility of using a lamb's early-life liveweight to predict the carcass quality realised when the animal reaches the target weight. The results of multinomial regression models showed that lambs which were heavier at weaning, at 13 weeks of age, were significantly more likely to have leaner and more muscular carcasses. An economic analysis confirmed that these animals produced significantly more valuable carcasses at slaughter, even after accounting for seasonal variation in lamb price that often favours early finishers. As the majority of heavier-weaned lambs leave the flock before lighter-weaned lambs, an increase in the average weaning weight could also lead to greater pasture availability for ewes in the latter stage of the current season, and thus an enhanced ewe condition and fertility for the next season. All information combined, therefore, a stronger focus on ewes' nutrition before and during lactation was identified as a key to increase system-wide profitability.