Livestock is an integral part of societies worldwide and contributes to a host of human activities beyond food production, including income, heritage, insurance, labor, and culture. Livestock’s positive contributions to society are contrasted by environmental impacts, which include greenhouse gas (GHG) emissions, biodiversity loss, and natural resource depletion, among others. Though environmental impacts of ruminant livestock production extend beyond GHG emissions ( Rotz, 2020), considerable effort has been dedicated specifically to quantifying and mitigating enteric methane (CH₄) emissions from beef and dairy cattle, which is the focus of this review.

Dairy farms have been under pressure to reduce negative environmental impacts while remaining profitable during times with volatile milk and commodity prices. Double cropping has been promoted to reduce negative environmental impacts and increase total dry matter yield per hectare. Three dairy farms that double cropped winter annuals and corn were selected from northern and western Pennsylvania. Data were collected from recorded crop and dairy records and financial data for 2016 and 2017. Farms ranged in size from 336 to 511 ha with 233 to 663 cows. Data were used to set parameters for the Integrated Farm System Model, which was then used to simulate 8 scenarios for each farm: current operation; 0, 50, and 100% of corn hectares double cropped; 30% feed price increase with and without double cropping; and 30% feed price decrease with and without double cropping at the farm's current level of double cropping. A 20-yr time period, using weather data that was representative of the actual farms, was used in the Integrated Farm System Model simulation to produce both financial and environmental outputs. Double cropping winter annuals and corn silage increased dry matter yield per hectare by 19%, when comparing 0 to 100% of the corn area double cropped. With all corn land double cropped, net return to management per hundredweight (45.36 kg) of milk increased by 1.8%, N leached per hectare per year decreased by an average of 4.5%, and phosphorus loss was reduced by an average of 9.2% across farms. When feed prices increased by 30%, double cropping increased net return over feed cost and net return to management by 1.6 and 2.2%, respectively, across farms. When feed prices decreased by 30%, double cropping decreased net return over feed cost and net return to management by smaller amounts of 0.13% and 0.11%, respectively, across farms. Modeling indicated that double cropping winter annuals with corn silage can have both environmental and economic benefits when winter-annual silage yields are enough to cover expenses.

The growing interest in incentivizing sustainable agricultural practices is supported by a large network of voluntary production standards, which aim to offer farmers and ranchers increased value for their product in support of reduced environmental impact. To be effective with producers and consumers alike, these standards must be both credible and broadly recognizable, and thus are typically highly generalizable. However, the environmental impact of agriculture is strongly place-based and varies considerably due to complex biophysical, socio-cultural, and management-based factors, even within a given sector in a particular region. We suggest that this contradiction between the placeless generality of standards and the placed-ness of agriculture renders many sustainability standards ineffective. In this policy and practice review, we examine this contradiction through the lens of beef production, with a focus on an ongoing regional food purchasing effort in Denver, Colorado, USA. We review the idea of place in the context of agricultural sustainability, drawing on life cycle analysis and diverse literature to find that recognition of place-specific circumstances is essential to understanding environmental impact and improving outcomes. We then examine the case of the Good Food Purchasing Program (GFPP), a broad set of food-purchasing standards currently being implemented for institutional purchasing in Denver. The GFPP was created through a lengthy stakeholder-inclusive process for use in Los Angeles, California, USA, and has since been applied to many cities across the country. The difference between Los Angeles' process and that of applying the result of Los Angeles' process to Denver is instructive, and emblematic of the flaws of generalizable sustainability standards themselves. We then describe the essential elements of a place-based approach to agricultural sustainability standards, pointing toward a democratic, process-based, and outcome-oriented strategy that results in standards that enable rather than hinder the creativity of both producers and consumers. Though prescription is anathema to our approach, we close by offering a starting point for the development of standards for beef production in Colorado that respect the work of people in place.

Biodiversity impacts are rarely included in systems analyses of livestock production. We piloted two approaches toward quantifying biodiversity impacts, pressure‐state‐response (PSR) and potential species loss (PSL), at a cow–calf operation in Florida for which extensive environmental data were available. Using these approaches, we compared livestock production on two vegetation types, semi‐native pasture (SNP) and improved pasture (IMP), and we found fewer deleterious effects on biodiversity associated with SNP (characterized by low stocking rates and no fertilizer) than with IMP, as evidenced by a lower PSL and greater biotic integrity under PSR. Both approaches agreed in the direction of the outcome, but we argue that, when possible, they should be applied complementarily to inform both absolute and per‐unit product biodiversity impacts of livestock production. This research demonstrates how to incorporate biodiversity into life‐cycle perspectives of livestock sustainability assessments when data availability varies, supporting the expansion of multi‐metric, holistic evaluations that are absent from most livestock system analyses.