Sustainable cattle systems balance environmental responsibility, economic viability and social acceptability, yet the global focus is currently upon greenhouse gas emissions (GHGe). Beef GHGe kg−1 carcass weight have decreased over past decades, yet further opportunities exist through advances in genetics, nutrition and management that increase growth, meat yield, reproduction, feed efficiency and, ultimately, output per unit of herd bodyweight. These gains may be further augmented by growth technologies that improve productivity or by feed supplements that reduce enteric CH4 emissions. Nevertheless, some challenges still remain. The reduced GHGe associated with dairy-beef systems mean that the role of traditional grazing systems in producing food on land that is unsuitable for other food or fiber production must be better communicated to stakeholders. All producers must adopt tools to benchmark and measure progress in reducing GHGe, yet existing knowledge gaps relating to C sequestration and the use of new global warming metrics must be resolved. A standard GHGe assessment tool is required to ensure fair comparisons and provide insights into the effects of on-farm practices. Ultimately, improving consumer trust and the social acceptability of beef production will be key to maintaining future cattle industry sustainability.

Livestock health is a key concern for all food system stakeholders and has considerable impacts upon sustainable food production. Improving productivity means that a set quantity of milk or meat may be produced at a lower economic cost, using fewer resources and with reduced greenhouse gas emissions (GHGe); however, diseases that reduce yield, growth or fertility have the opposite effect. The purpose of this narrative review was to assess the breadth of economic and environmental sustainability information relating to cattle health within the literature and to discuss related knowledge gaps within the literature. The mechanisms by which improved awareness and investment can lead to improved cattle health both on-farm and across the wider cattle industry are also appraised; concluding with the opportunities and challenges still outstanding in improving sustainability through livestock health. The economic and environmental impacts of cattle health have not been sufficiently quantified in the literature to draw valid conclusions regarding the sustainability impact of different diseases. Where available, economic data tended to be dated or extremely variable. Furthermore, environmental analyses did not use consistent methodologies and principally focused on GHGe, with little attention paid to other metrics. Although reducing disease severity or occurrence reduced GHGe, published impacts of disease varied from 1% to 40% with little apparent association between GHGe and industry-wide economic cost. An urgent need therefore exists to standardise methodologies and quantify disease impacts using a common baseline with up-to-date data inputs. Given the threat of antimicrobial resistance, improving cattle health through technology adoption and vaccine use would be expected to have positive impacts on social acceptability, especially if these improvements rendered milk and meat more affordable to the consumer. Therefore, it is important for cattle producers and allied industry to take a proactive approach to improving cattle health and welfare, with particular focus on diseases that have the greatest implications for sustainability.

Background A considerable body of evidence has reported the beneficial effects of improving productivity on reducing environmental impacts from livestock production. However, despite the negative impacts of animal diseases on reproduction, growth and milk production, there is little information available upon the impacts of animal disease on greenhouse gas emissions (GHGe). This study aimed to partially address this knowledge gap by investigating the effects of globally important vaccine-preventable diseases on GHGe from various livestock systems, namely: intensive dairy, extensive beef, commercial swine and backyard poultry production. Methods Simple deterministic models were developed within Microsoft Excel to quantify the impacts of livestock disease on productivity (defined as total milk and/or meat yield, MMY) adjusted for disease prevalence both at the population level (high or low), and at the herd or flock level. Disease-induced changes in MMY were applied to the GHGe per kg of milk or meat according to the consequent changes in livestock populations required to maintain milk or meat production. Diseases investigated comprised foot and mouth, brucellosis, anthrax, lumpy skin disease, classical swine fever, porcine reproductive and respiratory syndrome (PRRS), low and high pathogenicity avian influenza (LPAI and HPAI), avian infectious bronchitis and Newcastle disease. Results All diseases investigated had multifactorial impacts on total MMY, yet diseases that increased mortality in breeding or growing livestock (e.g. anthrax, classical swine fever and HPAI) showed greater impacts on GHGe per unit of milk or meat produced than those that primarily affecting yields or reproduction (e.g. brucellosis or LPAI). Prevalence also had considerable effects on potential GHGe. For example, maintaining backyard poultry meat production from a 100,000 hen population with 70% prevalence of HPAI increased GHGe by 11,255 MT CO 2 eq compared to a 30% prevalence at 3475 MT CO 2 eq above the baseline (0% prevalence). Effective reduction of the prevalence of PRRS in swine from 60 to 10%, FMD in beef cattle from 45 to 5% prevalence, or AIB in poultry from 75 to 20% prevalence would reduce GHGe intensities (CO 2 eq/kg CW) by 22.5%, 9.11% and 11.3% respectively. Conclusions Controlling livestock disease can reduce MMY losses at the farm level, which improves food security, reduces GHGe and enhances livestock system sustainability.

AbstractThe environmental impact of livestock production is one of the most significant issues within agriculture. Global concerns over climate change, resource use, pollution and other environmental indicators means that producers must implement practices and systems to reduce environmental impacts, yet this may only be achieved through assessments that allow impacts to be quantified, benchmarked and improved over time. Although environmental indicators are widely accepted, the metrics by which these are assessed continue to evolve over time as assessment objectives gain clarity and focus, and as the science relating to controversial topics (e.g. global warming or carbon sequestration) becomes more refined. However, significant negative trade-offs may occur between different metrics and denominators such that a specific practice or system may appear to have greater or lesser impacts, depending on assessment methodology. A number of tools and models have been developed to empower producers in quantifying environmental impacts, which will be increasingly important in satisfying future consumers’ hunger for information as well as food. These tools must be supplied in tandem with information as to the potential consequences of changing management practices and systems. At present however, tools available are based on differing methodologies, are often opaque in their background calculations and do not necessarily account for all the factors that influence environmental impacts from livestock. There is a clear need for robust tools that can be used as standards for assessing environmental impacts from the global livestock industry and that go beyond GHG emissions to produce a more rounded holistic assessment.

Abstract Brazilian beef systems contribute 14.9% of global beef production, therefore given climate change concerns, there is a clear need to reduce environmental impacts while maintaining economic viability. This study evaluated the hypothesis that steroid implant use in Brazilian beef cattle would reduce resource use, greenhouse gas (GHG) emissions and economic costs of production, thereby improving environmental and economic sustainability. A deterministic model based on beef cattle population demographics, nutrition and performance was used to quantify resource inputs and GHG emissions per 1.0 × 106 kg of hot carcass weight (HCW) beef. System boundaries extended from cropping input manufacture to cattle arriving at the slaughterhouse. Beef systems were modeled using herd population dynamics, feed and performance data sourced from producers in four Brazilian states, with additional data from global databases. Implants were used in calves, growing and finishing cattle at low (LI), medium (MI), and high (HI) levels of performance enhancement, compared to nonimplanted (NI) controls. Feed use results were used in combination with producer-derived input costs to assess the economic impacts of implant use, including production costs and returns on investment. Improved FCE, ADG, and carcass weights conferred by implant use reduced the number of cattle and the time taken to produce 1.0 × 106 kg HCW beef. Compared to NI controls, the quantities of feed, land, water and fossil fuels required to produce 1.0 × 106 kg HCW beef was reduced in implanted cattle, with reductions proportional to the performance-enhancing effect of the implant (HI > MI > LI). Implant use reduced GHG emissions per 1.0 × 106 kg HCW beef by 9.4% (LI), 12.6% (MI), or 15.8% (HI). Scaling up the MI effects to represent all eligible Brazilian cattle being implanted, revealed avoided GHG emissions equivalent to the annual exhaust emissions of 62.0 × 106 cars. Economic impacts of implant use reflected the environmental results, resulting in a greater margin for the producers within each system (cow-calf through to finishing). The 6.13% increase in kg of HCW beef produced generates a cost reduction of 3.76% and an increase in the return on invested capital of 4.14% on average. Implants offer the opportunity for Brazilian beef producers to demonstrate their dedication to improving environmental and economic sustainability through improved productivity, although care must be taken to avoid negative trade-offs.

The global animal protein industry faces an unprecedented challenge as we enter the third decade of the 21st century. With more than 7 billion people currently inhabiting the planet, our population is predicted to reach 9.6 billion by 2050. Population growth and a rise in per capita income in low-income countries are predicted to increase food demand by 48.6% (FAO, 2017). Yet, this demand must be fulfilled sustainably, and the mechanisms to achieve this are among the most often discussed issues within agriculture given concerns about climate change, resource use, animal welfare, antimicrobial resistance, and the provision of safe, affordable food. Many definitions of “sustainable” exist—for the purposes of this article the author will refer to sustainability as a balance between economic viability, environmental responsibility, and social acceptability. Future sustainability will depend on livestock producers improving productivity and efficiency so that more meat and milk can be produced using fewer resources, however, consumers increasingly question the methods by which food is produced. The future of the global animal protein industry therefore depends on producers demonstrating their dedication to environmental responsibility while maintaining a positive consumer image of animal agriculture. This “license to operate” should ensure continuing market access for animal proteins and therefore economic viability of livestock production. The challenge is easy to identify, yet far harder to achieve—this article examines the opportunities that will have to be seized by the global livestock industry, using the U.S. industry as an example, to ensure a bright future for animal protein production over the next 30 yr.

Abstract The U.S. dairy industry considerably reduced environmental impacts between 1944 and 2007, primarily through improved dairy cow productivity. However, although milk yield per cow has increased over the past decade, whole-system environmental impact analyses have not been conducted over this time period, during which environmental modeling science has improved considerably. The objective of this study was to compare the environmental impact of U.S. dairy cattle production in 2007–2017. A deterministic model based on population demographics, metabolism, and nutrient requirements of dairy cattle was used to estimate resource inputs, nutrient excretion, and greenhouse gas (GHG) emissions per 1.0 × 106 t (one million metric t or MMT) of energy-corrected milk (ECM) produced in 2007 and 2017. System boundaries extended from the manufacture and transport of cropping inputs to milk at the farm gate. Milk transport, processing, and retail were not included. Dairy systems were modeled using typical management practices, herd population dynamics, and production data from U.S. dairy farms. Cropping data were sourced from national databases. The resources required to produce 1.0 MMT ECM in 2017 were considerably reduced relative to those required in 2007, with 2017 production systems using 74.8% of the cattle, 82.7% of the feedstuffs, 79.2% of the land, and 69.5% of the water as compared to 2007. Waste outputs were similarly reduced, with the 2017 U.S. dairy industry producing 79.4%, 82.5%, and 85.7% of the manure, N, and P excretion, respectively. Dairy production in 2017 emitted 80.9% of the CH4 and 81.5% of the N2O per 1.0 MMT ECM compared to 2007. Enteric and manure emissions contributed the major proportion (80%) of GHG emissions per unit of milk, with lesser contributions from cropping (7.6%) and fertilizer application (5.3%). The GHG emissions per 1.0 MMT ECM produced in 2017 were 80.8% of equivalent milk production in 2007. Consequently, although total U.S. ECM production increased by 24.9% between 2007 and 2017, total GHG emissions from this milk production increased by only 1.0%. In line with previous historical analyses, the U.S. dairy industry has made remarkable productivity gains and environmental progress over time. To maintain this culture of continuous improvement, the dairy industry must build on gains made to date and demonstrate its commitment to reducing environmental impacts while improving both economic viability and social acceptability.

Rangelands, 50 % of the earth's land surface, produce a renewable resource of cellulose in plant biomass that is uniquely converted by ruminant livestock into animal protein for human consumption. Sustainably increasing global animal production for human consumption by 2050 is needed while reducing the environmental footprint of livestock production. To accomplish this, livestock producers can interseed legumes and use bioenergy protein by-products for increased dietary protein, develop forage "hot spots" on the landscape, use adaptive grazing management in response to a changing climate, incorporate integrated livestock-crop production systems, improve fertility to increase birth rates, and reduce livestock losses due to disease and pest pressure. Conceptual advances in livestock production systems have expanded the utility of livestock in conservation-oriented approaches that include (1) efforts to "engineer ecosystems" by altering vegetation structure for increased habitat and species diversity, and structural heterogeneity; (2) use of targeted grazing to reduce invasive annual grasses and invasive weeds, and fuel reduction to decrease wildfires; and (3) improvement of the distribution of livestock grazing across the landscape. Livestock production systems need to increase output of animal protein by implementation of knowledge and technology, but this production must be sustainable and society needs to have confidence that animals were raised in a humane and environmentally acceptable manner such that the quality and safety of the animal protein are acceptable for consumers.

All stakeholders within the livestock industry face a considerable challenge in achieving a balance between economic viability, environmental responsibility and social acceptability; and thus maintaining sustainable food production. This is exacerbated by information about farming practices and management systems that accentuate consumer concerns and lead to confusion as to the roles of productivity, efficiency and animal health in modern agriculture. The suggestions that intensive farms or large-scale herds have negative effects on cattle health; that we can assess cattle welfare by applying anthropomorphic philosophies; and that extensive systems are inherently beneficial to the environment, appear to be intuitively correct. Yet these suppositions are not as simple as they are often presented in mass media articles aimed at the consumer and lead to a multitude of other questions. Although it is tempting to try and overcome these issues by providing factual information, we cannot overcome negative publicity simply by supplying data and statistics. As an industry, we need to combine improved communication mechanisms with a better understanding of how consumer food-buying decisions are made to ensure future social acceptability and sustainability.

The beef industry faces a significant challenge in producing sufficient food to supply the requirements of the growing population, while maintaining a culture of continuous improvement and reducing environmental impacts per unit of beef produced. Since the late 1970’s, the US beef industry made significant efficiency gains that improved resource use and reduced greenhouse gas (GHG) emissions, and considerable opportunities exist for making greater gains in future. However, beef producers’ future access to specific management practices or technologies may be constrained by consumer perceptions.

Optimizing efficiency in the cow-calf sector is an important step toward improving beef sustainability. The objective of the study was to use a model to identify the relative roles of reproductive, genetic, and nutritional management in minimizing beef production systems' environmental impact in an economically viable, socially acceptable manner. An economic and environmental diet optimizer was used to identify ideal nutritional management of beef production systems varying in genetic and reproductive technology use. Eight management scenarios were compared to a least cost baseline: average U.S. production practices (CON), CON with variable nutritional management (NUT), twinning cattle (TWN), early weaning (EW), sire selection by EPD using either on-farm bulls (EPD-B) or AI (EPD-AI), decreasing the calving window (CW), or selecting bulls by EPD and reducing the calving window (EPD-CW). Diets to minimize land use, water use, and/or greenhouse gas (GHG) emissions were optimized under each scenario. Increases in diet cost attributable to reducing environmental impact were constrained to less than stakeholder willingness to pay for improved efficiency and reduced environmental impact. Baseline land use, water use, and GHG emissions were 188 m, 712 L, and 21.9 kg/kg HCW beef. The NUT scenario, which assessed opportunities to improve sustainability by altering nutritional management alone, resulted in a simultaneous 1.5% reduction in land use, water use, and GHG emissions. The CW scenario improved calf uniformity and simultaneously decreased land use, water use, and GHG emissions by 3.2%. Twinning resulted in a 9.2% reduction in the 3 environmental impact metrics. The EW scenario allowed for an 8.5% reduction in the 3 metrics. The EPD-AI scenario resulted in an 11.1% reduction, which was comparable to the 11.3% reduction achieved by EPD-B in the 3 metrics. Improving genetic selection by using AI or by purchasing on-farm bulls based on their superior EPD demonstrated clear opportunity to improve sustainability. When genetic and reproductive technologies were adopted, up to a 12.4% reduction in environmental impact was achievable. Given the modeling assumptions used in this study, optimizing nutritional management while concurrently improving genetic and reproductive efficiency may be promising avenues to improve productivity and sustainability of U.S. beef systems.

The objective of this study was to use a precision nutrition model to simulate the relationship between diet formulation frequency and dairy cattle performance across various climates. Agricultural Modeling and Training Systems (AMTS) CattlePro diet-balancing software (Cornell Research Foundation, Ithaca, NY) was used to compare 3 diet formulation frequencies (weekly, monthly, or seasonal) and 3 levels of climate variability (hot, cold, or variable). Predicted daily milk yield (MY), metabolizable energy (ME) balance, and dry matter intake (DMI) were recorded for each frequency-variability combination. Economic analysis was conducted to calculate the predicted revenue over feed and labor costs. Diet formulation frequency affected ME balance and MY but did not affect DMI. Climate variability affected ME balance and DMI but not MY. The interaction between climate variability and formulation frequency did not affect ME balance, MY, or DMI. Formulating diets more frequently increased MY, DMI, and ME balance. Economic analysis showed that formulating diets weekly rather than seasonally could improve returns over variable costs by $25,000 per year for a moderate-sized (300-cow) operation. To achieve this increase in returns, an entire feeding system margin of error of <1% was required. Formulating monthly, rather than seasonally, may be a more feasible alternative as this requires a margin of error of only 2.5% for the entire feeding system. Feeding systems with a low margin of error must be developed to better take advantage of the benefits of precision nutrition.

Life-cycle assessment (LCA) is the preferred methodology to assess carbon footprint per unit of milk. The objective of this case study was to apply an LCA method to compare carbon footprints of high-performance confinement and grass-based dairy farms. Physical performance data from research herds were used to quantify carbon footprints of a high-performance Irish grass-based dairy system and a top-performing United Kingdom (UK) confinement dairy system. For the US confinement dairy system, data from the top 5% of herds of a national database were used. Life-cycle assessment was applied using the same dairy farm greenhouse gas (GHG) model for all dairy systems. The model estimated all on- and off-farm GHG sources associated with dairy production until milk is sold from the farm in kilograms of carbon dioxide equivalents (CO2-eq) and allocated emissions between milk and meat. The carbon footprint of milk was calculated by expressing GHG emissions attributed to milk per tonne of energy-corrected milk (ECM). The comparison showed that when GHG emissions were only attributed to milk, the carbon footprint of milk from the Irish grass-based system (837 kg of CO2-eq/t of ECM) was 5% lower than the UK confinement system (884 kg of CO2-eq/t of ECM) and 7% lower than the US confinement system (898 kg of CO2-eq/t of ECM). However, without grassland carbon sequestration, the grass-based and confinement dairy systems had similar carbon footprints per tonne of ECM. Emission algorithms and allocation of GHG emissions between milk and meat also affected the relative difference and order of dairy system carbon footprints. For instance, depending on the method chosen to allocate emissions between milk and meat, the relative difference between the carbon footprints of grass-based and confinement dairy systems varied by 3 to 22%. This indicates that further harmonization of several aspects of the LCA methodology is required to compare carbon footprints of contrasting dairy systems. In comparison to recent reports that assess the carbon footprint of milk from average Irish, UK, and US dairy systems, this case study indicates that top-performing herds of the respective nations have carbon footprints 27 to 32% lower than average dairy systems. Although differences between studies are partly explained by methodological inconsistency, the comparison suggests that potential exists to reduce the carbon footprint of milk in each of the nations by implementing practices that improve productivity.