Animal production in the United States is at a pivotal stage. The importance of leveraging resources to increase our understanding of animal protein production sustainability is critical to meeting the food needs of the ever increasing human population. To increase the efficiencies of animal protein production, it is essential to engage pertinent stakeholders (researchers from several disciplines, retailers, producers, animal commodity groups) within the food supply chain in sustainability discussions to evaluate resources, with a forward looking vision.

The identification, development, and implementation of sustainable solutions have long been, and continues to be, the ultimate goal for research in agricultural systems. Sustainability metrics are and will continue to be used in the food supply chain. Understanding the impacts of resource availability, use, allocation, and potential depletion is critical to evaluate future food production schemes. For example, adverse weather extremes associated with climate change and variability will impact water availability, crop production and viability of animal production systems. Changing demographics of the US human population (age, increased health risk, increased poverty) will have significant implications on food supply chain production mechanisms. Efficiently utilizing natural (land, water, and phosphorus) and synthesized resources (N fertilizer) with minimal impact on soil, water and air quality is critical for the triple bottom line (i.e., balancing environmental, social, and economic drivers and effects).

We recognize a number of obstacles that could be influential in the outcomes of this process. 

First, there are many voices discussing the importance of sustainability. Perspectives on sustainability are complex and can become entrenched as professionals seek to justify the appropriateness of their practices. Within the livestock and poultry sector (referred to as livestock for brevity), the metrics and calculation methods have some commonalities, but also differences. For example, the US Roundtable for Sustainable Beef has identified six indicators for sustainability that will be applied to the cow-calf and confined feeding operations: Animal Health and Wellbeing, Efficiency and Yield, Water Resources, Land Resources, Air & Greenhouse Gas Emissions, Employee Safety & Wellbeing. These are surely laudable areas where we should continue to improve production systems, but they are not directly comparable to goals of other livestock industries. The Strategic Goals of the National Pork Board are to build consumer trust, drive sustainable production and grow consumer demand; sustainable production objectives focus on detection, preparation and response to animal disease, improving workforce professionalism and increasing productivity (NPB, 2018a). Efforts like the “Environmental Footprint Calculator” (NPB, 2018b) help the swine industry to assess and document reductions in environmental impact and build consumer trust (NPB, 2018a). The seven focus areas identified by the Innovation Center for U.S. Dairy are Sustainable Nutrition, Food Safety, People and Community, Environmental Stewardship, Communications, Global Insights, and Innovation and Animal Care (ICUSD, 2016). The US Poultry and Egg industry focus areas include environmental stewardship, social responsibility and economic profitability (USSA, 2018), and there is a “Carbon Footprint Estimation Toolkit” available. Within a livestock or food supply chain, there is also potential for groups of individuals to market and profit from ambiguous sustainability claims with little or no oversight.

Recent efforts to use research findings to better inform sustainability definitions for aquaculture systems showcased the importance of defining environmental and traceability standards through the Marine Stewardship Council (MSC, 2018). As it turned out, having a defined and accepted method to identify sustainable methods of aquaculture production without actually having sustainable fisheries worldwide put a tremendous burden on production systems and resulted in suppliers trying to bridge the gap by participating in “Fisheries Improvement Projects” that give fisheries market access if a plan is developed. Implementation of these plans is somewhat behind schedule calling into question their value. A lesson learned through this process is that understanding the supply chain needs (consumer demands) and both the scientific and economic drivers of animal production systems will result in development and adoption of more robust metrics for sustainability.

Second, we are beyond the time where reductionist science is sufficient. Scientists from a broad range of disciplines (social sciences, economics, animal production, crop production, natural resource management, market drivers, etc.) must collaborate in both research design and deployment as well as data analyses. This is essential to enhance and improve collaborative approaches for synthesis of information or methods for determining and communicating and managing systems for triple bottom line sustainability. We must be flexible as sustainability metrics for one or more system components may change over time to address emerging needs.

Furthermore, creating opportunities to further mine data through shared databases is critical. Scientists must be able to leverage resources and collected data to address current concerns while preserving data for future analyses. Data can be conserved for future access with proper definitions and recording measurement methods, sensitivities, and limitations. This will spur greater quality of development and evaluation of agricultural system models (statistical and mechanistic), to perform meta-analyses of important responses across space and time. Ultimately, this enables other scientists to address other important questions that could not be addressed through individual studies alone (e.g., Challinor et al., 2014; Liu, Powers, & Liu, 2013; Lui, Powers, Murphy, & Maghirang, 2014). Development and use of data dictionaries and subsequent ability to store data in the United States Department of Agriculture (USDA) Digital Commons preserves data for future use by researchers conducting quantitative analyses needed to evaluate sustainability metrics, inform policy makers and address other scholarly questions. These dictionaries and data will also be beneficial for training future generations of scientists as these would be larger, comprehensive and diverse data sets than can be obtained in individual laboratory or field projects. A National Research Support Project proposal was submitted in 2015 for a National Agricultural Research Data Network for Harmonized Data. This group identified “...research data, as products of investments, are grossly undervalued, underutilized, and lost from the scientific community causing duplication and unnecessary repetition of experiments. A significant gain in scientific advancement can occur if institutions partner to leverage existing quantitative data across locations, time, and management conditions into a coordinated network of discoverable, accessible, and usable data” (NRSP_TEMP11, 2016).

Consequently, the following critical needs have been identified.

• The need to create agile and adaptive networks of both scientists and stakeholders in the agricultural supply chain that collectively contribute to knowledge transfer within and outside of the network. The modes for networking are constantly evolving and can enhance the communication within and across these groups for the development of a new generation of research projects which address this need. We need to draw on expertise beyond our team and academia.


• The need to share data and analytical tools. We need to be cognizant of the variation in both defining and describing sustainability in the animal production industry and through the supply chain. We need to build upon existing sustainability “calculators” and estimation tools with our broad set of data representing different fields of science, different animal species, and also communication channels and mechanisms. This includes the translation of data and datasets.


• The need to focus on future scenarios. We need to be proactive versus reactive. While we cannot predict the future, we can investigate how sensitive existing animal production systems are to external perturbations. We need to focus on specific issues to explore, evaluate and/or propose practices and technologies to improve animal protein production sustainability.

To address these needs, the goal of our work is to provide a pathway which ensures the growth of sustainable agricultural systems by fostering the development of a network of inter- and trans-disciplinary scientists (biologists, sociologists, economists, engineers, etc.) and professionals, who embrace the multitude of perspectives offered, and thus who are better able to forecast potential future conditions and future agricultural outcomes in an environment that allows for vetting of competing perspectives and approaches.

As investigators, we seek to create the knowledge that both facilitates the development, and describes the sustainability, of technology and practices utilized within animal agriculture. This is a beneficial process that identifies key challenges that agricultural systems may face in both near (e.g. the USRSB High Priority Indicators) and distant futures (e.g. the depletion of the Ogallala Aquifer). This process inspires the development of new technology and practices and encourages the development of new food supply chain relationships. This process has been implemented from a number of different perspectives, using assessment approaches that quantify overall system performance respecting each of those perspectives (e.g. ecological footprints, net energy balance, water footprint, life cycle analysis, ISO 14000, etc.).