Impact of transition from permanent pasture to new swards on the nitrogen use efficiency, nitrogen and carbon budgets of beef and sheep production

Combining slow-release fertilizer and plastic film mulching reduced the carbon footprint and enhanced maize yield on the Loess Plateau

Agricultural practices significantly contribute to greenhouse gas (GHG) emissions, necessitating cleaner production technologies to reduce environmental pressure and achieve sustainable maize production. Plastic film mulching is commonly used in the Loess Plateau region. Incorporating slow-release fertilizers as a replacement for urea within this practice can reduce nitrogen losses and enhance crop productivity. Combining these techniques represents a novel agricultural approach in semi-arid areas. However, the impact of this integration on soil carbon storage (SOCS), carbon footprint (CF), and economic benefits has received limited research attention. Therefore, we conducted an eight-year study (2015-2022) in the semi-arid northwestern region to quantify the effects of four treatments [urea supplied without plastic film mulching (CK-U), slow-release fertilizer supplied without plastic film mulching (CK-S), urea supplied with plastic film mulching (PM-U), and slow-release fertilizer supplied with plastic film mulching (PM-S)] on soil fertility, economic and environmental benefits. The results revealed that nitrogen fertilizer was the primary contributor to total GHG emissions (≥71.97%). Compared to other treatments, PM-S increased average grain yield by 12.01%-37.89%, water use efficiency by 9.19%-23.33%, nitrogen accumulation by 27.07%-66.19%, and net return by 6.21%-29.57%. Furthermore, PM-S decreased CF by 12.87%-44.31% and CF per net return by 14.25%-41.16%. After eight years, PM-S increased SOCS (0-40 cm) by 2.46%, while PM-U decreased it by 7.09%. These findings highlight the positive effects of PM-S on surface soil fertility, economic gains, and environmental benefits in spring maize production on the Loess Plateau, underscoring its potential for widespread adoption and application.

Earth-abundant catalyst for modification of wheat straw to enhance ammonia mitigation from fertilized alkaline soil

In this study, inexpensive earth-abundant catalyst of Co/TiO2 is coupled with a low-temperature modification approach to enhance NH3 adsorption capacity on wheat straw (WS). The highest NH3 uptake achieved is 111.9 mg/g, with 80.8 % retention even after 3 h of desorption. Mechanistic investigation indicates that the enhanced adsorption capacity stems from Co/TiO2, which facilitates generation of reactive oxygen species, leading improved ultra-micropore structure that enhances the interaction between NH3 and oxygen-containing functional groups through a trapping effect. The robust stability of adsorbed NH3 is attributed to the formation of amides or amines. Incorporation of only 1 wt% WS-Co to urea-fertilized alkaline soil reduced NH3 volatilization by 83.1 %. The significant effect is primarily attributed to the excellent adsorption capacity of WS-Co, rather than alterations in the relative abundance of the microbial community. These findings present a novel approach for development of effective fertiliser additive to mitigate NH3 volatilization from alkaline soil.

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.

Long-term trends in yield variance of temperate managed grassland

The management of climate-resilient grassland systems is important for stable livestock fodder production. In the face of climate change, maintaining productivity while minimizing yield variance of grassland systems is increasingly challenging. To achieve climate-resilient and stable productivity of grasslands, a better understanding of the climatic drivers of long-term trends in yield variance and its dependence on agronomic inputs is required. Based on the Park Grass Experiment at Rothamsted (UK), we report for the first time the long-term trends in yield variance of grassland (1965-2018) in plots given different fertilizer and lime applications, with contrasting productivity and plant species diversity. We implemented a statistical model that allowed yield variance to be determined independently of yield level. Environmental abiotic covariates were included in a novel criss-cross regression approach to determine climatic drivers of yield variance and its dependence on agronomic management. Our findings highlight that sufficient liming and moderate fertilization can reduce yield variance while maintaining productivity and limiting loss of plant species diversity. Plots receiving the highest rate of nitrogen fertilizer or farmyard manure had the highest yield but were also more responsive to environmental variability and had less plant species diversity. We identified the days of water stress from March to October and temperature from July to August as the two main climatic drivers, explaining approximately one-third of the observed yield variance. These drivers helped explain consistent unimodal trends in yield variance-with a peak in approximately 1995, after which variance declined. Here, for the first time, we provide a novel statistical framework and a unique long-term dataset for understanding the trends in yield variance of managed grassland. The application of the criss-cross regression approach in other long-term agro-ecological trials could help identify climatic drivers of production risk and to derive agronomic strategies for improving the climate resilience of cropping systems.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13593-023-00885-w.

A Review: Plant Carbohydrate Types—The Potential Impact on Ruminant Methane Emissions

Carbohydrates are the major component of most ruminant feeds. The digestion of carbohydrates in the rumen provides energy to the ruminants but also contributes to enteric methane (CH₄) emissions. Fresh forage is the main feed for grazing ruminants in temperate regions. Therefore, this review explored how dietary carbohydrate type and digestion affect ruminant CH₄ emissions, with a focus on fresh forage grown in temperate regions. Carbohydrates include monosaccharides, disaccharides, oligosaccharides, and polysaccharides. Rhamnose is the only monosaccharide that results in low CH₄ emissions. However, rhamnose is a minor component in most plants. Among polysaccharides, pectic polysaccharides lead to greater CH₄ production due to the conversion of methyl groups to methanol and finally to CH₄. Thus, the degree of methyl esterification of pectic polysaccharides is an important structural characteristic to better understand CH₄ emissions. Apart from pectic polysaccharides, the chemical structure of other polysaccharides per se does not seem to affect CH₄ formation. However, rumen physiological parameters and fermentation types resulting from digestion in the rumen of polysaccharides differing in the rate and extent of degradation do affect CH₄ emissions. For example, low rumen pH resulting from the rapid degradation of readily fermentable carbohydrates decreases and inhibits the activities of methanogens and further reduces CH₄ emissions. When a large quantity of starch is supplemented or the rate of starch degradation is low, some starch may escape from the rumen and the escaped starch will not yield CH₄. Similar bypass from rumen digestion applies to other polysaccharides and needs to be quantified to facilitate the interpretation of animal experiments in which CH₄ emissions are measured. Rumen bypass carbohydrates may occur in ruminants fed fresh forage, especially when the passage rate is high, which could be a result of high feed intake or high water intake. The type of carbohydrates affects the concentration of dissolved hydrogen, which consequently alters fermentation pathways and finally results in differences in CH₄ emissions. We recommend that the degree of methyl esterification of pectic polysaccharides is needed for pectin-rich forage. The fermentation type of carbohydrates and rumen bypass carbohydrates should be determined in the assessment of mitigation potential.

Exploring the effects of land management change on productivity, carbon and nutrient balance: Application of an Ensemble Modelling Approach to the upper River Taw observatory, UK

Agriculture is challenged to produce healthy food and to contribute to cleaner energy whilst mitigating climate change and protecting ecosystems. To achieve this, policy-driven scenarios need to be evaluated with available data and models to explore trade-offs with robust accounting for the uncertainty in predictions. We developed a novel model ensemble using four complementary state-of-the-art agroecosystems models to explore the impacts of land management change. The ensemble was used to simulate key agricultural and environmental outputs under various scenarios for the upper River Taw observatory, UK. Scenarios assumed (i) reducing livestock production whilst simultaneously increasing the area of arable where it is feasible to cultivate (PG2A), (ii) reducing livestock production whilst simultaneously increasing bioenergy production in areas of the catchment that are amenable to growing bioenergy crops (PG2BE) and (iii) increasing both arable and bioenergy production (PG2A + BE). Our ensemble approach combined model uncertainty using the tower property of expectation and the law of total variance. Results show considerable uncertainty for predicted nutrient losses with different models partitioning the uncertainty into different pathways. Bioenergy crops were predicted to produce greatest yields from Miscanthus in lowland and from SRC-willow (cv. Endurance) in uplands. Each choice of management is associated with trade-offs; e.g. PG2A results in a significant increase of edible calories (6736 Mcal ha^-1) but reduced soil C (-4.32 t C ha^-1). Model ensembles in the agroecosystem context are difficult to implement due to challenges of model availability and input and output alignment. Despite these challenges, we show that ensemble modelling is a powerful approach for applications such as ours, offering benefits such as capturing structural as well as data uncertainty and allowing greater combinations of variables to be explored. Furthermore, the ensemble provides a robust means for combining uncertainty at different scales and enables us to identify weaknesses in system understanding.

Simulating grazing beef and sheep systems

CONTEXT

Ruminant livestock make an important contribution to global food security by converting feed that is unsuitable for human consumption into high value food protein, demand for which is currently increasing at an unprecedented rate because of increasing global population and income levels. Factors affecting production efficiency, product quality, and consumer acceptability, such as animal fertility, health and welfare, will ultimately define the sustainability of ruminant production systems. These more complex systems can be developed and analysed by using models that can predict system responses to environment and management.

OBJECTIVE

We present a framework that dynamically models, using a process-based and mechanistic approach, animal and grass growth, nutrient cycling and water redistribution in a soil profile taking into account the effects of animal genotype, climate, feed quality and quantity on livestock production, greenhouse gas emissions, water use and quality, and nutrient cycling in a grazing system.

METHODS

A component to estimate ruminant animal growth was developed and integrated with the existing components of the SPACSYS model. Intake of herbage and/or concentrates and partitioning of the energy and protein contained in consumed herbage and/or concentrates were simulated in the component. Simulated animal growth was validated using liveweight data from over 200 finishing beef cattle and 900 lambs collected from the North Wyke Farm Platform (NWFP) in southwest England, UK, between 2011 and 2018. Annual nitrous oxide (N₂O), ammonia, methane and carbon dioxide emissions from individual fields were simulated based on previous validated parameters.

RESULTS AND CONCLUSIONS

A series of statistical indicators demonstrated that the model could simulate liveweight gain of beef cattle and lamb. Simulated nitrogen (N) cycling estimated N input of 190 to 260 kg ha^-1, of which 37-61% was removed from the fields either as silage or animal intake, 15-26% was lost through surface runoff or lateral drainage and 1.14% was emitted to the atmosphere as N₂O. About 13% of the manure N applied to the NWFP and excreta N deposited at grazing was lost via ammonia volatilisation.

SIGNIFICANCE

The extended model has the potential to investigate the responses of the system on and consequences of a range of agronomic management and grazing strategies. However, modelling of multi-species swards needs to be validated including the dynamics of individual species in the swards, preferential selection by grazing animals and the impact on animal growth and nutrient flows.

Environmental impact of primary beef production chain in Colombia: Carbon footprint, non-renewable energy and land use using Life Cycle Assessment

In Colombia, the beef production chain accounts for approximately 11.6 million cattle heads and annually produces 933 million kg of the beef carcass. There are no life cycle assessment (LCA) studies that have evaluated the environmental performance of Colombian beef systems. The present study aimed to estimate the carbon footprint (CF), non-renewable energy use, and land use of 251 cow-calf and 275 fattening farms in Colombia. The study also aimed to identify the main hotspots of adverse environmental impacts and propose possible mitigation options and their cost-effectiveness. The impact categories were estimated using the 2006 IPCC and the 2019 Refinement to 2006 IPCC guidelines, databases, and locally estimated emission factors. The functional units used were 1 kg fat and protein corrected milk (FPCM) and 1 kg live weight gain (LWG), leaving the farm gate. Three methods of allocating environmental burdens to meat and milk products were applied: economic, energy, and mass allocation. The adoption of improved pastures was considered a mitigation measure, and an economic assessment was performed to estimate the relative cost-effectiveness of its establishment. A principal component multivariate analysis and a Hierarchical Clustering on Principal Components were performed. The economic allocation method assigned a greater environmental burden to meat (83%), followed by energy content (80%) and mass production (73%). The largest sources of GHG emissions were enteric fermentation and manure deposited on pasture. Both cow-calf and fattening systems had a cluster of farms with better productivity, pasture and cattle management practices, and environmental performance. The CF for meat could be reduced by 33 to 56% for cow-calf and 21 to 25% for fattening farms, by adopting improved pastures. Therefore, our results suggest that GHG emissions can be reduced by adopting improved pastures, better agricultural management practices, efficient fertilizer usage, using the optimal stocking rate, and increasing productivity.