Food production systems associated with livestock management are significant sources of greenhouse gases (GHGs). Livestock excreta are one of the primary sources of GHG emissions from grazing livestock. Against this context, a field experiment was established in a UK grassland to establish the extent of soil methane (CH4), carbon dioxide (CO2), andN2O fluxes upon the deposition of (i) cattle urine (U), (ii) urine + dicyandiamide (DCD) (U + DCD), (iii) artificial urine (AU), and dung (D), and compared with a (iv) control, where neither urine nor dung was applied. Excreta applications were made at three experimental periods during the grazing season: early-, mid-, and late-season. Soil N2O emissions data have been published already by co-authors; hence, this paper summarizes the emissions of soil-borne CH4 and CO2 emissions, and explores in particular, the effects of the addition of DCD, a nitrification inhibitor used to reduce direct and indirect N2O emissions from urine patches, on these (carbon) C-GHGs. Soil moisture (p = 0.47), soil temperature (p = 0.51), and nitrate (NO3−) (p = 0.049) and ammonium (NH4+) (p = 0.66) availability, and C (p = 0.54) addition were key controls of both soil CH4 and CO2 emissions. The dung treatment stimulated the production and subsequent emissions of soil CH4 and CO2, a significantly high net CH4 and CO2-based global warming potential (GWP). The findings of the current study lay a foundation for an in-depth understanding of the magnitude and dynamics of soil-borne CH4 and CO2 upon urine and dung deposition during three different seasons. This study implies that the use of DCD may have the potential to reduce carbon-based GHGs from the urine and dung of grazing animals.

Grasslands managed for dairy and meat production represent a major land use across most regions of the world. As global demand for food products continues to rise, grassland is increasingly being converted to arable land. However, such conversion represents a significant land use change that can result in a suite of unintended consequences. Against this background, we examined three agricultural systems on the Rothamsted Research North Wyke Farm Platform. The systems studied were: a Permanent pasture monoculture, a High sugar grass that was converted to arable cropping, and a mixed sward of the same High sugar grass with white clover. Following conversion, the magnitude of carbon dioxide exchange in the High sugar grass converted to arable system was reduced relative to pre-conversion conditions. However, these differences were not statistically significant, reflecting substantial temporal variability in carbon dioxide fluxes. This land use change also resulted in a significant immediate 45% decrease in soil organic matter, a 41% decrease in soil carbon, a 41% decline in soil nitrogen, and a 61% reduction in soil phosphorus. In addition, flow-weighted inorganic nitrogen concentrations in combined surface and subsurface runoff significantly increased after conversion, while flow-weighted concentrations of carbon also significantly increased after conversion. The Permanent pasture monoculture exhibited a greater overall carbon dioxide sink capacity compared to the High sugar grass with white clover mixed sward. Both grass-based systems maintained relatively stable and higher concentrations of soil organic matter and nutrient concentrations (carbon, nitrogen, phosphorus) compared with the arable conversion. Runoff from these grassland systems also showed stable nitrogen concentrations. Overall, our findings highlight the environmental risks associated with converting grass to arable land and underscore the importance of land use management strategies that prioritize the preservation of grasslands and manage the risks of unintended consequences.

This study aimed to explore the knowledge and attitudes of livestock farmers from the United Kingdom regarding agroforestry planning and management issues. The farmers (n = 48) answered an online survey with demographic, open, closed and Likert scale questions. Almost half of the participants said they need more information to successfully plan and manage an agroforestry system, and self-reported low knowledge on management practices related to trees. Participants stated they did not expect to receive technical support from governmental agencies to maintain the agroforestry area. However, they would like to improve their knowledge through field days, courses, and Internet sources. Benefits to the environment, animals and farm profitability were considered central to successful agroforestry systems. In conclusion, participants cannot successfully plan and manage agroforestry, but they are willing to improve their knowledge and skills.

Organic amendments enhance soil quality in agroecosystems, although they may modify the dynamics of greenhouse gas (GHG) emissions, highlighting complex interactions between soil management and environmental sustainability. A field experiment was conducted in the semiarid region of Iran to evaluate the effects of barley residues (BR), sheep manure (SM), and their combination (BR+SM) on soil carbon dioxide (CO 2 ) and nitrous oxide (N 2 O) emissions under maize and mungbean. In mungbean, both SM and BR+SM resulted in higher CO 2 fluxes than BR. Conversely, in maize, cumulative CO 2 emissions were similar among treatments. Under mungbean, BR+SM exhibited higher soil N 2 O values than SM and BR. The lowest cumulative CO 2 (4.77 ± 0.24 and 5.29 ± 0.37 Mg ha −1 year −1 for maize and mungbean, respectively) and N 2 O (4.73 and 3.00 kg ha −1 year −1 for maize and mungbean, respectively) values were measured in the BR, whereas the BR+SM resulted in significantly high cumulative CO 2 and N 2 O under both crops. Cumulative CO 2 fluxes were 21.5% and 53.5% lower in the BR than BR+SM under maize and mungbean, respectively. Similarly cumulative N 2 O was 48% lower in the BR than in the BR+SM treatment under the mungbean cropping system. Application of BR can be considered as an effective alternative management strategy in terms of lowering GHG emissions under maize and mungbean. By exploring the impact of organic input management on soil carbon and nitrogen dynamics in semiarid cropping systems, our study provides key insights for enhancing agricultural sustainability, while reducing GHG emissions.

It is estimated that a quarter to one-third of food intended for humans does not fulfil its original purpose. Yet, and despite its universally acknowledged importance for sustainability, mechanisms behind food waste generation are often studied unconnectedly from other challenges surrounding food systems. Here, we examine how concepts, assumptions and frameworks adopted in the food waste literature and the food systems literature overlap, contradict and complement one another. We discuss the current evidence on why and how food waste occurs and discuss modifications required for a conceptual framework to improve the integration between the two groups of studies. The resulting framework makes an explicit distinction between context-specific direct causes and context-independent indirect drivers of food waste, with practice theory interlinking them by portraying human behaviour and associated agency that translate the latter into the former. Central to our conceptualisation is an enhanced recognition that the ultimate cause of food waste is almost always natural decay, which cannot be prevented but can be managed through a systems approach with clear definitions of temporal boundaries.

Agri-food systems across the globe are faced with the challenge of reducing their supply-chain emissions of greenhouse gases (GHGs) such as nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4). For instance, 10

Nitrous oxide is a potent greenhouse gas due to its long atmospheric lifespan (121 years) that results in a high global warming potential (GWP). Research has shown that no-tillage may be implemented as a mitigation strategy to reduce N2O emissions. The objective of the was to evaluate how conventional tillage (CT) and no-tillage (NT) can potential influence N2O emissions in soybean rotation in a semi-arid region of the central Free State of South Africa. The effect of conventional and no-till tillage practices on N2O emissions under soybean rotation was evaluated in the 3rd year of a 5-year rotation system, in a semi-arid region of the Free State of South Africa, from December 2022 to December 2023. The experimental area was divided into three blocks and there were two plots in each block: in total there were six plots. The treatments were planted in a soybean rotation system under no-tillage and conventional tillage. The monthly averages of N2O emissions were significantly different from each other during the soybean growing season; the highest emissions were recorded in August/September 2023 from both the NT and CT treatments after harvest. During this time, there were crop residues in the soil that increased soil carbon. There was a positive correlation between N2O emissions and soil carbon content (p = 0.21) and between N2O emissions and soil organic matter (p = 0.43). Emissions were significantly higher in CT (LSD = 0.3) than in NT. The lowest N2O emissions were recorded in December 2023 (LSD = 0.05) and were significantly reduced in the no-till plots compared to those of the conventional tillage plots. Furthermore, the lowest cumulative N2O emissions of 0.26 ± 0.22 kg N2O-N ha−1 were recorded during NT in the winter season and were significantly different from CT (LSD = 0.19). The results from our study indicate that the no-till practices in soybean rotation can decrease N2O emissions.

Soil has supported terrestrial food production for millennia; however, agricultural intensification may affect its resilience. Using a systems-thinking approach, we reviewed the impacts of conventional-agriculture practices on soil resilience and identified alternative practices that could mitigate these effects. We found that many practices only affect soil resilience with their long-term repeated use. Lastly, we ranked the impacts that pose the greatest threats to soil resilience and, consequently, food and feed security.

In agricultural production, bioaerosols inevitably pose health hazards to animals and workers. Currently, there is a lack of research on real-time bioaerosol concentration monitoring at agricultural sites. We conducted a real-time airborne bioaerosol measurement study using the Multiparameter Bioaerosol Spectrometer (MBS) and applied a Uniform Manifold Approximation and Projection (UMAP) approach to classify bioaerosol emissions from the North Wyke Farm Platform between April and May. Penicillium and Cladosporium were the most dominant fungi. Another machine learning approach, Generalized Additive Model (GAM) was also constructed to explore the relationship with meteorological data and selected trace gases. It was found that animal houses and agricultural fields were the main sources of bioaerosols, and significant dispersion was observed downwind of these point sources. Two main bioaerosol types were Cladosporium and Penicillium, which accounted for 29.8 % and 24.1 % of the total, respectively. Cladosporium had an average concentration of 3.79 L-1 in the animal house direction, which is 2.19 L-1 higher and about 2.37 times that in the farmland direction (1.60 L-1). For Penicillium, the average concentration was 2.44 L-1 in the animal house direction, 0.93 L-1 higher and 1.61 times that in the farmland direction (1.52 L-1). And both bioaerosols are more active at temperatures above 15 °C and relative humidity above 80 %. These results may provide recommendations for detection and identification of bioaerosol composition and emission patterns in the agricultural environments, and emission profiles associated with animal farms to provide better understanding for agricultural regional planning and public health perspectives.

New molecular approaches are being developed to detect endometrial cancer using minimally invasive sampling methods. This study aims to evaluate the acceptability of self-collected cervicovaginal samples among women with Lynch syndrome, a group at high risk for developing endometrial cancer. Participants collected cervicovaginal self-samples and answered an at-home acceptability questionnaire in a cross-sectional study. Self-samples from a subset of these women were analyzed for somatic mutations using next-generation sequencing (NGS), targeting a panel of 47 genes. A total of 61 (88.4%) out of 69 eligible women participated in the study. The overall self-sampling experience was rated good or very good (N = 55, 90.2%). Most of the women were confident about correctly sampling (N = 58, 95.1%), and most reported no or mild pain (N = 56, 91.8%). During self-sample collection, most women reported feeling calm and comfortable and experiencing safety, privacy, and normality. In a pilot study using a subset of 15 samples, five somatic variants were identified in four self-samples (4/15, 26.7%) in ACVR2A, ARID1A, APC, and KMT2D. During follow-up, three out of four women with variants detected in the self-sample underwent prophylactic hysterectomy at a median of 9.1 months, while one out of four developed endometrial cancer after 3.9 years since the collection of the sample. Self-sampling is well-accepted and well-tolerated in women with Lynch syndrome and could potentially reduce some barriers associated with gynaecological surveillance. Further research is needed to evaluate the feasibility of implementing cervicovaginal self-collection and the accuracy of molecular testing for gynaecological surveillance in women with Lynch syndrome.

Renewable-based ammonia production (hereafter, green ammonia) could present a transformative opportunity for agricultural systems, offering a pathway to decentralize and decarbonize fertilizer production. Modular green ammonia units that can be deployed on-farm are emerging around the world, with individual annual production capacities of 100 to 500 tonnes. Decentralized production is poised to increase ammonia availability and fertilizer accessibility, while decarbonizing production, lowering transport emissions, and enhancing farm resilience to supply chain disruptions. However, high capital and operating costs for modular green ammonia units, as well as access to water and renewable energy, pose significant adoption barriers for farmers. Safety concerns and mismatches between typical green ammonia products ( e.g., anhydrous ammonia) and existing fertilizer practices further complicate integration into the agricultural sector. Critically, widespread green ammonia availability could also risk fertilizer overuse, undermining environmental benefits associated with decarbonized ammonia production. This talk will explore opportunities, challenges and critical considerations for integrating green ammonia into agricultural systems.

Riparian buffers are expedient interventions for water quality functions in agricultural landscapes. However, the choice of vegetation and management affects soil microbial communities, which in turn affect nutrient cycling and the production and emission of gases such as nitric oxide (NO), nitrous oxide (N2O), nitrogen gas (N-2) and carbon dioxide (CO2). To investigate the potential fluxes of the above-mentioned gases, soil samples were collected from a cropland and downslope grass, willow and woodland riparian buffers from a replicated plot scale experimental facility. The soils were re-packed into cores and to investigate their potential to produce the aforementioned gases via potential denitrification, a potassium nitrate (KNO3-) and glucose (labile carbon)-containing amendment, was added prior to incubation in a specialized laboratory DENItrification System (DENIS). The resulting NO, N2O, N-2 and CO2 emissions were measured simultaneously, with the most NO (2.9 & PLUSMN; 0.31 mg NO m(-2)) and N2O (1413.4 & PLUSMN; 448.3 mg N2O m(-2)) generated by the grass riparian buffer and the most N-2 (698.1 & PLUSMN; 270.3 mg N-2 m(-2)) and CO2 (27,558.3 & PLUSMN; 128.9 mg CO2 m(-2)) produced by the willow riparian buffer. Thus, the results show that grass riparian buffer soils have a greater NO3- removal capacity, evidenced by their large potential denitrification rates, while the willow riparian buffers may be an effective riparian buffer as its soils potentially promote complete denitrification to N-2, especially in areas with similar conditions to the current study.

Abstract In this study, the decision learning methods of regression tree and random forest analysis are investigated as complements to standard statistical methods such as analysis of variance and grouped regression. For this purpose, three diverse data sets were used. The first set is large and multidimensional and describes nitrous oxide emissions from sites across different geo-positions in the UK receiving various fertilisation treatments. The second set is based on Gliricidia tree provenances and has a small number of samples and an imbalanced distribution of factor classes. Random forest modelling was found to be a very viable option in the case of the first data set but failed in the case of second. The third data set, based on count observations recording osprey egg incubation times, lends itself to tree and forest modelling. These decision learning methods therefore appear well suited to handling the diverse, multi-dimensional and complex data sets that often arise in carrying out agricultural and ecological field experiments.

Objective Management of endometrial cancer is advancing, with accurate staging crucial for guiding treatment decisions. Understanding sentinel lymph node (SLN) involvement rates across molecular subgroups is essential. To evaluate SLN involvement in early-stage (International Federation of Gynecology and Obstetrics 2009 I-II) endometrial cancer, considering molecular subtypes and new European Society of Gynaecological Oncology (ESGO) risk classification. Methods The SENECA study retrospectively reviewed data from 2139women with stage I-II endometrial cancer across 66 centers in 16 countries. Patients underwent surgery with SLN assessment following ESGO guidelines between January 2021 and December 2022. Molecular analysis was performed on pre-operative biopsies or hysterectomy specimens. Results Among the 2139 patients, the molecular subgroups were as follows: 272 (12.7%) p53 abnormal (p53abn, 1191 (55.7%) non-specific molecular profile (NSMP), 581 (27.2%) mismatch repair deficient (MMRd), 95 (4.4%) POLE mutated (POLE-mut). Tracer diffusion was detected in, at least one side, in 97.2% of the cases; with a bilateral diffusion observed in 82.7% of the cases. By ultrastaging (90.7% of the cases) or one-step nucleic acid amplification (198 (9.3%) of the cases), 205 patients were identified with affected sentinel lymph nodes, representing 9.6% of the sample. Of these, 139 (67.8%) had low-volume metastases (including micrometastases, 42.9%; and isolated tumor cells, 24.9%) while 66 (32.2%) had macrometastases. Significant differences in SLN involvement were observed between molecular subtypes, with p53abn and MMRd groups having the highest rates (12.50% and 12.40%, respectively) compared with NSMP (7.80%) and POLE-mut (6.30%), (p=0.004); (p53abn, OR=1.69 (95% CI 1.11 to 2.56), p=0.014; MMRd, OR=1.67 (95% CI 1.21 to 2.31), p=0.002). Differences were also noted among ESGO risk groups (2.84% for low-risk patients, 6.62% for intermediate-risk patients, 21.63% for high-intermediate risk patients, and 22.51% for high-risk patients; p<0.001). Conclusions Our study reveals significant differences in SLN involvement among patients with early-stage endometrial cancer based on molecular subtypes. This underscores the importance of considering molecular characteristics for accurate staging and optimal management decisions.

Objective To assess the safety of fertility-sparing treatments for early-stage ovarian cancer in women younger than 40 years old. Methods We performed a retrospective multicenter study including women aged 18-40 years diagnosed with early-stage (FIGO I-II) ovarian cancer in 55 Spanish hospitals, from January 2010 to December 2019. Benign and borderline tumors were excluded, as well as advanced stages (FIGO III-IV). All perioperative characteristics and follow-up data were collected and analyzed. Standard staging surgery (SSS) was compared with fertility-sparing surgery (FSS) in terms of oncological outcomes. Results In all, 366 women were included; 327 (89.3%) were stage I. Among all patients, 216 (59%) underwent SSS and 150 (41%) FSS. Up to 208 (56.8%) patients did not have children, but only 12 (3.2%) had oocyte preservation before treatment. Patients in the FSS group compared with the SSS group showed a non-significant difference in recurrences (8% vs. 9.3%, respectively; P < 0.711) and deaths (1.3% vs. 4.8%, respectively; P = 0.211) during the follow-up. No significant differences were found between epithelial and non-epithelial ovarian cancer both in recurrences (7.1% vs. 8.8%, respectively; P = 0.771) and in deaths (1.4% vs. 1.3%, respectively; P = 1) among patients who underwent FSS. Conclusion FSS seems a safe option for treatment of early-stage ovarian cancer in patients who want to preserve fertility, either for epithelial and non-epithelial histology.

Agricultural soils account for about 60% of the global atmospheric emissions of the potent greenhouse gas nitrous oxide (N2O). One of the main processes producing N2O is denitrification, which occurs under oxygen-limiting conditions when carbon is readily available. On grazed pastures, urine patches create ideal conditions for denitrification, especially in soils with high organic matter content, like Andisols. This lab study looks at the effects of Urine-urea-N load on the Andisol potential to emit N2O. For this, we investigated the effects of three levels of urea-N concentrations in cow urine on emissions of N2O, N2, and CO2 under controlled conditions optimised for denitrification to occur. Results show total N2O emissions increased with increasing urine-N concentration and indicate that denitrification was the main N2O-producing process during the first 2–3 days after urine application, though it was most likely soil native N rather than urine-N being utilised at this stage. An increase in soil nitrate indicates that a second peak of N2O emissions was most likely due to the nitrification of ammonium hydrolysed from the added urine, showing that nitrification and denitrification have the potential to play a big part in N losses and greenhouse gas production from these soils.

With a growing body of research associating livestock agriculture with faster global warming, higher health costs and greater land requirements, a drastic shift towards plant-based diets is often suggested as an effective all-round solution. Implicitly, this argument is predicated on the assumption that the reallocation of resources currently assigned to animal production systems will automatically result in the efficient cultivation of human-edible crops without negative environmental, health or socioeconomic consequences. In reality, however, the validity of this assumption warrants careful examination, as a farm’s capability to adopt a new agricultural system is multifaceted and context-specific. Through a transdisciplinary review of literature, here we discuss examples of unintended consequences that could arise from the conversion of grasslands into arable production, including potentially adverse impacts on yield stability, biodiversity, soil fertility and beyond. We contend that few of these issues are being methodically considered as part of the current food security debate and call for a closer examination of supply-side constraints.

To advance sustainable and resilient agricultural management policies, especially during land use changes, it is imperative to monitor, report, and verify soil organic carbon (SOC) content rigorously to inform its stock. However, conventional methods often entail challenging, time-consuming, and costly direct soil measurements. Integrating data from long-term experiments (LTEs) with freely available remote sensing (RS) techniques presents exciting prospects for assessing SOC temporal and spatial change. The objective of this study was to develop a low-cost, field-based statistical model that could be used as a decision-making aid to understand the temporal and spatial variation of SOC content in temperate farmland under different land use and management. A ten-year dataset from the North Wyke Farm Platform, a 20-field, LTE system established in southwestern England in 2010, was used as a case study in conjunction with an RS dataset. Linear, additive and mixed regression models were compared for predicting SOC content based upon combinations of environmental variables that are freely accessible (termed open) and those that require direct measurement or farmer questionnaires (termed closed). These included an RS-derived Ecosystem Services Provision Index (ESPI), topography (slope, aspect), weather (temperature, precipitation), soil (soil units, total nitrogen [TN], pH), and field management practices. Additive models (specifically Generalised Additive Models (GAMs)) were found to be the most effective at predicting space-time SOC variability. When the combined open and closed factors (excluding TN) were considered, significant predictors of SOC were: management related to ploughing being the most important predictor, soil unit (class), aspect, and temperature (GAM fit with a normalised RMSE = 9.1%, equivalent to 0.4% of SOC content). The relative strength of the best-fitting GAM with open data only, which included ESPI, aspect, and slope (normalised RMSE = 13.0%, equivalent to 0.6% of SOC content), suggested that this more practical and cost-effective model enables sufficiently accurate prediction of SOC.

The cultivation or ‘tillage’ system is one of the most important elements of agrotechnology. It affects the condition of the soil, significantly modifying its physical, chemical, and biological properties, and the condition of plants, starting from ensuring appropriate conditions for sowing and plant growth, through influencing the efficiency of photosynthesis and ultimately, the yield. It also affects air transmission and the natural environment by influencing greenhouse gas (GHG) emissions potentially. Ultimately, the cultivation system also has an impact on the farmer, providing the opportunity to reduce production costs. The described experiment was established in 1998 at the Brody Agricultural Experimental Station belonging to the University of Life Sciences in Poznań (Poland) on a soil classified as an Albic Luvisol, while the described measurements were carried out in the 2022/2023 season, i.e., 24 years after the establishment of the experiment. Two cultivation methods were compared: Conventional Tillage (CT) and No Tillage (NT). Additionally, the influence of two factors was examined: nitrogen (N) fertilization (0 N—no fertilization, and 130 N–130 kg N∙ha−1) and the growth phase of the winter wheat plants (BBCH: 32, 65 and 75). The growth phase of the plants was assessed according to the method of the Bundesanstalt, Bundessortenamt and CHemische Industrie (BBCH). We present the results of soil properties, soil respiration, wheat plants chlorophyll fluorescence, and grain yield. In our experiment, due to low rainfall, NT cultivation turned out to be beneficial, as it was a key factor influencing the soil properties, including soil organic carbon (SOC) content and soil moisture, and, consequently, creating favorable conditions for plant nutrition and efficiency of photosynthesis. We found a positive effect of NT cultivation on chlorophyll fluorescence, but this did not translate into a greater yield in NT cultivation. However, the decrease in yield due to NT compared to CT was only 5% in fertilized plots, while the average decrease in grain yield resulting from the lack of fertilization was 46%. We demonstrated the influence of soil moisture as well as the growth phase and fertilization on carbon dioxide (CO2) emissions from the soil. We can clearly confirm that the tillage system affected all the parameters discussed in the work.

This study addresses the effect of using animal excreta on the nutritional content of forages, focusing on macro- and micro-element concentrations (nitrogen; N, phosphorus; P, sulphur; S, copper; Cu, zinc; Zn, manganese; Mn, selenium; Se) from animal feed to excreta, soil, and plants. Data were collected from pot and field trials using separate applications of sheep or cattle urine and faeces. Key findings indicate that soil organic carbon (SOC) and the type of excreta significantly influences nutrient uptake by forages, with varied responses among the seven elements defined above. Although urine contributes fewer micronutrients compared to faeces (as applied at a natural volume/mass basis, respectively), it notably improves forage yield and micronutrient accumulation, thus potentially delivering positive consequences at the farm level regarding economic performance and soil fertility when swards upon clayey soil types receive said urine in temperate agro-climatic regions (i.e., South West England in the current context). In contrast, faeces application in isolation hinders Se and Mn uptake, once again potentially delivering unintended consequences such as micronutrient deficiencies in areas of high faeces deposition. As it is unlikely that (b)ovine grazing fields will receive either urine or faeces in isolation, we also explored combined applications of both excreta types which demonstrates synergistic effects on N, Cu, and Zn uptake, with either synergistic or dilution effects being observed for P and S, depending largely on SOC levels. Additionally, interactions between excreta types can result in dilution or antagonistic effects on Mn and Se uptake. Notably, high SOC combined with faeces reduces Mn and Se in forages, raising concerns for grazed ruminant systems under certain biotic situations, e.g., due to insufficient soil Se levels typically observed in UK pastures for livestock growth. These findings underscore the importance of considering SOC and excreta nutritional composition when designing forage management to optimize nutrient uptake. It should be noted that these findings have potential ramifications for broader studies of sustainable agriculture through system-scale analyses, as the granularity of results reported herein elucidate gaps in knowledge which could affect, both positively and negatively, the interpretation of model-based environmental impact assessments of cattle and sheep production (e.g., in the case of increased yields [beneficial] or the requirement of additional synthetic supplementation [detrimental]).