Duration: 10/01/2018 to 09/30/2023

Administrative Advisor(s):

NIFA Reps:

Non-Technical Summary

Statement of Issues and Justification

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.). 

Related, Current and Previous Work

Related work on sustainability

Many scientists and practitioners agree that sustainability is a trajectory not an actual destination. Implicit in this concept is that practices are constantly changing in order to achieve greater benefits to meet societal needs. The National Research Council (NRC, 2010) stated, “Sustainability has been described as the ability to meet core societal needs in a way that can be maintained indefinitely without significant negative effects.” The USDA (2018) definition of sustainable agriculture is “an integrated system of plant and animal production practices having a site-specific application that will continue over the long-term:

• Satisfy human food and fiber needs;


• Enhance environmental quality and the natural resource base upon which the agriculture economy depends;


• Make the most efficient use of nonrenewable resources and on-farm resources and integrate, where appropriate, natural biological cycles and controls;


• Sustain the economic viability of farm operations;


• Enhance the quality of life for farmers and society as a whole.” (USDA, 2018)

Although few would argue with the definition of sustainability as meeting core societal needs, few agree on the specific metrics used to determine if a particular commodity is produced in a sustainable way or with sustainable practices. In the livestock industry, collaborations of food supply chains, commodity group associations, environmental NGOs, and public partners are often leading these discussions of sustainability indicators and metrics, such as the five following examples. 

• USRSB is a multi-stakeholder initiative developed to advance, support and communicate continuous improvement in sustainability of the U.S. beef value chain. This initiative identified 6 indicators of sustainability to apply to the cow/calf, confined feeding operations, packers/processors, and retail sectors. USRSB released its Indicator Development Report (USRSB Indicator Working Group, 2017). A few specific foci for the indicators in the cow-calf and feedlot sectors include strategies to manage water resources to address conservation and quality, documentation of operational efficiency over time, management of air emissions (including greenhouse gases) and implementation of nutrient management with manure nutrients. Time will tell how these indicators are tracked, per calf born, per unit feed or water input, per pound of beef produced, per animal on feed, etc.


• The National Pork Board partnered with several organizations to lead a Sustainability Initiative with the goals of building consumer trust, driving sustainable production and growing sustainable demand (NPB, 2018a). These efforts led to the development of an Environmental Foot Print Calculator for Pork Production (NPB, 2018b). This initiative identified sustainability indicators for greenhouse gas emissions, production costs, land use, and water consumption. The “calculator” is promoted as a method to monitor the movement of individual farms from the baseline metrics toward the sustainability goals.


• The Innovation Center for U.S. Dairy supports socially responsible, economically viable and environmentally sound dairy food systems that promote the current and future health and well-being of consumers, communities, cows, employees, businesses and planet. The Center includes the dairy supply chain (from farm inputs to retail outputs and customers) as well as government agencies. Six key areas are highlighted: people and community; environmental stewardship; animal care; food safety; global insights and innovation; and nutrition, wellness and food security. The Stewardship and Sustainability Framework for U.S. Dairy production serves as the primary industry resource for dairy producers, cooperatives and processors to demonstrate the industry’s commitment to customers and key stakeholders (ICUSD, 2016). The Framework identifies relevant measures to assess sustainability (indicators), the metric for measurement (the units for numerators and denominators) and intensity metrics to normalize findings and track progress over time. The 2016 Dairy Sustainability Report identifies that dozens of cooperatives and processors incorporate the Stewardship and Sustainability Framework for US Dairy in their customer-focused sustainability reporting. The results of Life Cycle Assessments for fluid milk, cheese and whey, and greenhouse gases contributed to the Stewardship and Sustainability Framework. (Henderson et al., 2012; Thoma et al., 2010; and Thoma et al., 2013).


• The US Poultry and Egg Association developed its Environmental Program to provide information to poultry and egg producers related to regulatory issues, training programs for wastewater operators and producers on environmental enhancement and protection, and recognition through Awards for Clean Water and Family Farm Environmental Excellence (USSA, 2018). Their carbon footprint estimation toolkit was developed in response to the US EPA’s GHG reporting requirements and accounts for GHG generated by stationary sources (i.e. boilers and generators) and the anaerobic processes operated at wastewater treatment facilities.


• Field to Market is leading a national effort to define sustainability for commodity crop production including animal feeds such as corn, soybeans, and alfalfa. Production of feed grains and forages are significant contributors for animal production sustainability indicators related to water consumption, water quality, greenhouse gas emissions, soil conservation/quality and land use. Field to Market has released a Fieldprint® Calculator (FTM, 2018) that creates a numerical measure of seven sustainability indicators. Comparison of this value when recalculated over time, allows individuals, groups of individuals, food processors, etc. to track progress and document improved management of resources.

As demonstrated above, definitions of sustainability and its key components vary in interpretation. We subscribe to the definition describing sustainable agriculture as an integrated system of food production, with site-specific applications, that can continue over long periods of time. Because our modern food production system is not self-contained at any one site, a system of metrics that can collectively indicate the level of sustainability is needed, especially one which considers the system as a whole.

Related NIMSS projects

A NIMSS database search revealed eleven regional projects tangentially related to the proposed replacement project:

1. Management Systems to Improve the Economic and Environmental Sustainability of Dairy Enterprises (NC_temp2042) included objectives related to sustainability such as expanding previous work on greenhouse gas modelling, documenting energy use on various sizes and types of dairy farms, and evaluation of manure treatment with algae prior to land application;


2. Dairy Production Systems: C, N, and P Management for Production, Profitability and the Environment (NE1544) focused on greenhouse gas emissions reduction; transport of nutrients, pathogens and pharmaceutical from dairy systems; and development of science-based tools and educational materials to promote environmental stewardship on US dairies;


3. Sustainable Small Ruminant Production in SE US (SCC081), objectives are specific to rearing of small ruminant systems (sheep and goats) on pasture;


4. Nutrition and Management of Feedlot Cattle to Optimize Performance, Carcass Value and Environmental Compatibility (NCCC_temp308 ) included objectives on nutrition and management issues related to performance, carcass value, and environmental sustainability of feedlot cattle operations achieved through conservation and nutrient management;


5. Collaborative for Research on Food, Energy, and Water Education (NC_temp1207) focused on how individuals reason and learn in the context of Food, Energy and Water;


6. Climate Change, Weather Variability and Resiliency for Ranching, Farming and Rural Communities (WDC42);


7. Indicators of Social Change in the Marketplace: Producers, Retailers and Consumers (NCC65) fostered research and collaborations to facilitate understanding and explanation of changes that impact the consumer-marketplace interface;


8. Food Systems, Health, and Well-being: Understanding Complex and Dynamics of Change (NC 1196) included a primary focus on the complex food system and health and well-being;


9. Enhancing Nitrogen Utilization in Corn Based Cropping Systems to Increase Yield, Improve Profitability and Minimize Environmental Impacts (NC1195) included a focus on nitrogen use efficiency in corn systems;


10. Competitiveness and Sustainability of the Southern Dairy Industry (SERA 15) provided an annual conference for stakeholders interested in competitiveness and sustainability of the Southern Dairy Industry; and


11. Understanding the Ecological and Social Constraints to Achieving Sustainable Fisheries Resource Policy and Management (NC1189) which focused on impacts of climate change on ecological, socioeconomic and environmental factors encouraging invasive species on inland fisheries and aquatic resources.

 

These projects are largely focused either on specific regions, species, or environmental media and therefore would be largely complementary but not duplicative of the proposed project. One of the strengths of the terminating project, S1032, for which this proposed project (S1074) is a replacement, is that it established a solid record of multi-disciplinary, integrated research. Building on that, there are opportunities to collaborate, not compete, with ongoing NIMSS projects.

History and Successes of S1032

Historically, research conducted as part of the previous and terminating S1032 multistate research projects has demonstrated the local impacts of various production practices and mitigation strategies. These efforts served to identify technological and management approaches to support improvements in triple bottom line of sustainability of animal protein production. Prior iterations of the group had participants who evaluated animal diet modifications to reduce nutrient excretion, effectiveness of manure treatment technologies, and emissions lost during land application and crop production processes. Former and current members of the group were instrumental in revising the D384.2 Standard on Manure Characteristics for the American Society of Agricultural and Biological Engineers (2005). This gold standard is used by consulting engineers, nutrient management planners and USDA Natural Resources Conservation Service. Many members participated in the National Air Emissions Monitoring study developed through a compliance agreement or in the US Environmental Protection Agency NAEMS panel.

The team then moved toward more holistic analyses of the animal operation as a system with stocks and flows of nutrients, energy, and water entering, cycling through and exiting animal production systems and subsequent follow through on end fate of these resources. Collectively, members worked to develop a Causal Loop Diagram (CLD) of animal protein production. This CLD has served members and the group well to set the agenda for their annual meetings to continuously learn more and increase their knowledge about different nodes of the CLD as well as engaging additional individuals from various subject matter areas of expertise. Members have become better participants in multidisciplinary activities and strive to reach transdisciplinary activities. Recent work associated with the terminating S1032 project considered consequences of implementation of alternative practices through more than one node of the animal production system (Banner et al., 2017). Other recent work focused on the analysis of mass balance of nutrients on dairies to evaluate data quality for regulatory review (Miller, et al., 2017) and subsequent determination of policy effectiveness.

A review of the indicators for sustainability proposed by USRSB and Field to Market suggests the continuing critical importance of strengthening research and extension capabilities in several manure management topics. Critical animal-environmental issues connect with sustainability discussions and analyses of these should be completed in the public sector for unbiased information to be available to all animal producers regardless of herd or flock size or to whom they sell their product. Consumers are interested in having a transparent process to identify sustainability metrics. It is anticipated that a well-documented process to address sustainability could be incorporated into USDA Natural Resources Conservation Service Conservation Planning with financial access to Environmental Quality Incentive Program funds for animal protein producers. Continued investments by future iterations of S1032 in manure and nutrient management issues will be important to engage with food supply chain led sustainability discussions.  

The United States stands at a critical point in food production. Engaging scientists from numerous disciplines to address complex agricultural production systems while addressing societal and sociological concerns regarding food production is critical. It is imperative that resources are leveraged from multiple sources to conduct this decisive research. Current and future scientists engaged in S1074 are skilled in numerous research methods and have the subject matter disciplines and systems thinking knowledge to address manure and nutrient management issues associated with sustainability and must engage with food supply chain led sustainability discussions. The successful collaboration of this multi-state effort is evident through annual meetings serving as in-service learning activities for all participants, as well as monthly webinars conducted to hold members accountable and continue the momentum of group energy. Their work has been published in peer-reviewed scientific journals, Extension publications, and books from the National Academy of Sciences and respected university presses and other publishers. As members of research-intensive universities, this group has access to the most recent data, software, and computing resources necessary to carry out the research and many scientists collaborate with Regional Data and/or Climate Hubs. The team has extensive experience in working at multiple levels and with a range of stakeholders to integrate research with education and outreach. Transdisciplinary, innovative and more inclusive research teams are needed due to the technical complexity of these challenges and the growing social aspects of livestock production. Therefore, integration of our efforts among our traditional participants (continuation of previous work on chemical, physical and biological changes occurring in animal facilities from feeding animals through manure generation, treatment, storage and ultimately utilization) and an expansion of participants to include additional colleagues is a key aspect of this proposal to better synthesize scientific findings and aid in policy development. Individually, we will continue to conduct fundamental and applied research that aligns with our specific expertise, similar to what was done previously in S275, S1000 and S1032. Under this proposed project, however, we will contribute our individual findings to the larger project team to integrate findings beyond what any of us could do independently. The product of the group is greater than the sum of the individual components.

The S1032 Research Project has, and the S1074 Research Project will continue to, address analyses of the high-priority topic of sustainable food production by analyzing food supply chain sustainability metrics to inform technology and management practice developments in animal protein production systems. The proposed project herein meets Guidelines for Multistate Research Activities (SAESD, 2013) by addressing high priorities within the crosscutting research areas of animal production systems (across species), manure management to reduce environmental footprints (carbon, nitrogen, phosphorus, water), policy development and economic viability. The project involves researchers and extension specialists from multiple disciplines and states to leverage experiences and resources while having synergistic impacts on education of graduate students. Many members also participate in international collaborations. Agricultural Experiment Station researchers and Cooperative Extension Specialists involved in this project have leveraged federal, state and non-government organizations (NGO) based funding sources to add significant financial and in-kind resources to address this important research area. The involvement of Cooperative Extension Specialists drives an end result to disseminate and includes electronic information transfer through web sites, written material for livestock and poultry producers and other stakeholder groups, on-farm demonstrations, and curriculum development, deployment and evaluation for numerous educational programs conducted at local and national scales. 

Objectives

1. Create issue-focused adaptive networks that transcend discipline and stakeholder boundaries, now and into the future
   
2. Synthesize¬ data, analytical tools and communication mechanisms to evaluate and discuss animal protein supply chain sustainability metrics on various spatial and temporal scales
   
3. Propose solutions, research and Extension directions to significantly contribute to sustainable animal protein systems and food security with forecasting of future trends
   

Methods

The approach to this next generation project (S1074) builds on successful approaches the terminating project (S1032) employed previously, with a drive to focus work around dynamic core issues. Individual team members will have variable levels of commitment to each of the core Issue Teams, and the specific objectives therein. However, joint planning and coordination by S1074 members will provide broader input and additional sharing of data, analytical and communication tools, and ultimately solutions in space and time.  

For each core issue, the basic approach and timeline is as follows:

• Year 1: There is large group (S1074) and Issue Team discussions of the issue in relation to livestock systems, and the relationships to relevant environmental, societal and economic metrics. The Issue Team will put forth a scope to the broad system under study in the form of a causal loop diagram, and the proposed variation in external drivers to analyze.
• Year 2: The Issue Team members will pool existing networks, resources and analysis methods to combine reductionist research, where available, and identify research or data necessary to quantify and qualify all relationships in the system. This includes current and necessary education mechanisms for knowledge transfer and change in behavior.
• Year 3: The Issue Team will set forth to either disseminate solutions or fill in information gaps through proposed research.

We expect to initiate a new core issue in each of Years 1, 2 and 3 with continuation through S1074 project terminus. Based on this approach, we propose specific tasks that generate metrics for the objectives.

Objective 1

We will create adaptive networks in space and time by leveraging our state-based and industry resources to create Issue-centered Teams, and engage network participants through face-to-face and online work sessions. The internal (S1074 member) and external connections made through Issue Teams are expected to ebb and flow over time, adapting to needs, interest, and availability of individuals.

Task 1A. Conduct web-based work sessions for Issue Teams

Web-based conferencing software and options have evolved considerably in the last five years, with multiple platforms providing the necessary functions of document sharing, large and small-group conversations, and recording. Virtual work sessions allow us to reduce the time and cost commitment for non-official members to participate on Issue Teams, expanding our transdisciplinary breadth and stakeholder involvement. Remote teaming will include opportunities for sharing Issue Team updates and introducing new concepts, analytical methods, and processes. Web-based sessions will also include dedicated work time toward project objectives.

Project members draw from numerous experiences and collaborations to facilitate this task.

• A North Central group of Land Grant University and NRCS professionals (including S1074 representatives) held four round-table discussions around the topic of Manure and Soil Health. These roundtables brought together a diverse audience of over 400 attendees, including technical experts, farmers, and farm advisors to explore current knowledge, science related knowledge gaps, and information needs of farmers.
• Project team members are also leaders of the Livestock and Poultry Environmental Learning Center. This virtual platform provides networking space and mechanisms to deliver professional development to a national audience on emerging research and public policy in the realm of livestock and poultry environments.
• Many project team members are co-investigators and advisors in an NSF-funded INFEWSer project dedicated to developing a virtual resource center for graduate education in the area of Food, Energy and Water to drive development of transdisciplinary student preparation through development of online modules and cohort experiences.

The Issue Team leader will select the platform(s) most suitable for the team’s progress, ensure equal access by all team members, enable public access (where appropriate) to team progress and outputs, and track metrics.

Task 1B. Facilitate face-to-face workshops that translate techniques and methods among Issue Teams and S1074 members

The S1074 members look forward to annual meetings hosted by various members to actively engage, face-to-face, with colleagues from across the nation. This engagement is amplified when working collectively to learn or develop ideas. Annual meetings will continue to serve three purposes: (1) conduct annual meeting business; (2) conceptualize and/or refine the causal loop diagram for the core issues to be tackled; and (3) learn new techniques or methods (including Extension and outreach) that is transferable among all Issue Teams and S1074 members.

The Executive Team and Local Host will be responsible for local logistics, forming the agenda and tracking metrics. The Issue Team Leaders are responsible for inviting external members (particularly those local to the meeting location) to engage in issue-based discussions and learning opportunities.

Task 1C. Strengthen the next generation of thinkers to engage in animal protein sustainability discussions

Project members support and mentor undergraduate and graduate research and Extension assistants at our home institutions on projects that serve this project’s objectives.

In addition, project members serve supportive roles in the NSF-funded INFEWS project for engaging graduate students from different disciplines and institutions in cohort projects requiring transdisciplinary approaches to case studies for modeling and evaluating animal systems for their food, energy, and water implications (INFEWs-ER).

Project members will be individually responsible for engaging graduate students and participation in S1074 work.

Evaluation of Objective 1 Success

In addition to reporting task summaries and accomplishments, Objective 1 will be evaluated, reported and discussed based on the following metrics:

• The number and diversity of participants in web-based and face-to-face work sessions. The Shannon Diversity Index was developed historically as tool for analyzing communication networks (Shannon, 1948). It has been adapted by ecologists to evaluate species diversity within an ecosystem (Jost, 2006). For this project we will be looking at diversity in discipline, gender, race, and supply chain role to quantify the efficacy of outreach and inclusion efforts.
• The change in connection strength and diversity of participants for Issue Teams will be evaluated using Social Network Analysis techniques. This will include notation of participant contributions to all three project objectives, and on tangential products, like proposal submissions.
• The current, potential and realized adoption of techniques and methods shared via web-based and face-to-face work sessions (by survey).

Objective 2

We will synthesize data, analytical tools and communication mechanisms to evaluate animal system dynamics related to the core issues on various spatial and temporal scales by aligning CLD system nodes and metrics with sustainability metrics, sharing data in the open access arena, and moving from causality to mechanistic relationships.

Task 2A. Align sustainability definitions and metrics

S1074 members are currently engaged with several existing supply chain led sustainability initiatives in the animal industry. Even within animal industries, there are varying definitions and metrics for evaluating the ability of animal production systems to provide for future generations.

To accomplish this task, in tandem with Objective 1, Issue Teams will collate and prioritize the definitions and metrics used to evaluate sustainable systems according to parties within the animal protein supply chain. Furthermore, these definitions and metrics will inform, but not dictate, the base nodes of the CLD. The Issue Team may explore alternative approaches for measuring sustainability or alternative indicators/metrics for looking at future perturbations in the system.  

Issue Team leaders will be responsible for establishing engagement with appropriate industry stakeholders.

Task 2B. Develop data dictionaries appropriate for sharing data in the open access arena

Data dictionaries establish standard names, definitions, attributes, allowable values and potentially measurement methods (techniques, sensitivities, limitations). These allow open sharing of data across experiment stations for greater analytical purposes. Furthermore, data from research projects designed to address specific questions are able to be used in more robust and detailed systems analyses. Data dictionaries will be developed for data inclusion in the USDA Digital Commons.

Data dictionaries exist to build upon in terms of methodology and format:

• Harmonized System Codes (http://www.foreign-trade.com/reference/hscode.htm)
• North American Industry Classification Code (for interface with economists; measures economic activity) (https://www.naics.com/search/)
• United National Standard Products and Services Codes (businesses and products) (https://www.unspsc.org/search-code/default.aspx?CSS=&Type=desc&SS=animal)
• Standard Industry Codes (businesses) (http://siccode.com/en/search/animals) of data parameters (Shared data; consistent (focus on food processing and distribution, not the food production side of animal systems)
• Animal Train Ontology for Livestock (ATOL) (https://bioportal.bioontology.org/ontologies/ATOL)

 

Individuals participating in this process will also review existing documents (data and units of data) produced during various Life Cycle Assessment (LCA) projects associated with animal protein production systems. This task builds on Issue Teams and Task 2A to harmonize the disparate definitions and metrics of sustainability.

Task 2C. Move from Causality to Mechanistic

The initial framework of each Issue Team will be a causal loop diagram. This simplistic conceptual description helps map the scope, variables and drivers to the issue at hand. The variables will be based on sustainability metrics in concert with the issue-centered teams.

This task is to continuously refine and enrich the modeling framework that describes the complex dynamics of sustaining animal protein production. Issue Teams will draw on their networks to identify existing results from reductionist research and modify, replace, and document variable nodes and causality arrows (when appropriate). Where existing analytical tools are in place (i.e. LCA analyses) to quantify system dynamics, teams are expected to contribute additional mechanistic processes or datasets (see Task 2B) that enable a wider breadth of processes in time and space to be considered. In the course of this work, teams are also expected to identify and engage under-represented disciplines; identify and engage new analytic and synthetic expertise to improve vitality of the committee.

In the course of work by each Issue Team, the visual description of the system via the causal loop diagram will evolve and demonstrate progress toward Objective 2. However, the depth of the data and relationships supporting the nodes and links in the diagram will also grow. While analytical tools will evolve, the work of the team in expanding the depth will be tracked.

Members on Issue Teams have shared responsibility for this task.

Evaluation of Objective 2 Success

In addition to reporting task summaries and accomplishments, Objective 2 will be evaluated, reported and discussed based on the following metrics:

• The level and thoroughness of disaggregation of CLD node values and internal feedbacks (metrics) that can be translated into algebraic or differential equations to provide a transition from concept to computational model and better represent the range and variability of current systems based on shared data
• Development of data dictionary hierarchies
• A numerical description (i.e. percentage) of progress on mechanistic relationships between CLD nodes
• Adoption of shared data and techniques by all members of the Issue Teams (including stakeholders) will be captured through qualitative feedback in survey format

Objective 3

Using the adaptive networks formed through Objective 1, and the synthesis of data and tools in Objective 2, we can drive research directions to address gaps in knowledge of our existing systems, and potential solutions to respond to potential external perturbations in future animal production systems.

Task 3A. Propose Solutions

Solutions require ideas, but also testing. The project process facilitates supporting data and existing teams (including stakeholders) to drive toward solutions past the end date of this S1074 project. Proposals will support testing hypotheses for relationships of current and forecasted systems by team members and their networks.

These projects will be tangential but supportive of the overall project goal, especially with respect to transdisciplinary projects and graduate student training as part of those projects. In cases where these tangential projects start early enough in the project life, the relationships can be fed back to Task 2C.

Leadership of these tangential projects will evolve based on the network membership. Issue Team leaders will be responsible for tracking the development and success of these tangential projects, but not for proposal formation.

Evaluation of Objective 3 Success

In addition to reporting task summaries and accomplishments, Objective 3 will be evaluated, reported and discussed based on the following metrics:

• The number, scope, objectives and success of tangential proposals
• The adoption, inclusion or discussion of proposed solutions by Issue Team network members, including stakeholders, will be captured through qualitative feedback in survey format.

Measurement of Progress and Results

Outputs

• Issue-based adaptive networks
• Publications, including white papers to summarize key findings in Objective 2
• Grant proposals
• Next generation scientists
• Workshops (in-person and web-based)
• Learning modules developed for INFEWs-ER virtual resource center
• Non-INFEWs-ER learning modules

Outcomes or Projected Impacts

• Enhanced graduated student training through collaboration with INFEWs-ER virtual resource center
• Strengthened networks encompassing livestock industry and research and Extension personnel
• Data dictionary/hierarchy for sharing livestock and environment research
• Increased numbers of graduate students who address trans-disciplinary work in dissertations
• Increased data available for public use, available through USDA Digital Commons or other
• Data and network support for innovative integrated projects that address forecasted issues or solutions
• Increased number of applicants for faculty positions who are formally trained and prepared for transdisciplinary work
• Innovative solutions exist to enable protein production in the future, despite uncontrollable external pertubations

Milestones

(2019):Network formation will be continuous, but a core Issue Team is expected to emerge early (Year 1) Initial

(2020):Summary and alignment of CLD and sustainability metrics (Year 2)

(2021):State of the science for CLD (Year 3)

(2019):Causal Loop Diagram (End of Year 1)

(2021):Future directions (Year 3 and beyond)

Projected Participation

View Appendix E: Participation

Outreach Plan

This project is designed around two-way communication and outreach between the S1074 project team and stakeholders. Active sharing of project information will be accomplished in the face-to-face and online meeting forums (Tasks 1.2 and 1.3), and shared online storage systems (i.e. Google Drive). Through the formation of adaptive networks, these forums serve to inform and learn from stakeholders. Task 1.4 engages the next generation of scientists and they too become partners in sharing project information to a wider audience. The collaboration with the INFEWs-ER project provides mechanisms to train the next generation of scientists in not only research, but communication. Results of research findings will be presented at various professional society meetings, published as white papers or in appropriate journals.

Organization/Governance

An Executive Committee will convene to oversee coordination of project team members, and ensure equal access and communication among Issue Teams. The Executive Committee will consist of a Chair, Chair-elect, Secretary, and Issue Team leaders. The chair of the committee is responsible for organizing the annual meeting agenda, conducting the meeting and assuring that task assignments are completed. The Chair is elected for a one-year term. Chairs are eligible for re-election. The Chair-elect normally succeeds the Chair, and is expected to support the Chair by carrying out duties assigned by the Chair. The Chair-elect serves as the Chair in the absence of the elected Chair. The Chair-elect is elected for one year. The Chair-elect is eligible for re-election. The Chair-elect is responsible for overseeing virtual communication mechanisms. The Secretary is responsible for keeping records on decisions made at meetings (keeping the minutes), maintaining an updated roster of participants (as a list server), and assisting in the preparation of the accomplishments report (i.e., the SAES-422). The Secretary normally succeeds the Chair-elect. Secretaries are eligible for re-election. Issue Team leaders will be identified within the adaptive networks, and will engage the S1074 committee as a whole at appropriate time points. All members agree to carry out the agreed research collaboration, research coordination, information exchange, or advisory activities. The S1074 members are responsible for reporting progress, contributing to the ongoing progress of the activity, and communicating their accomplishments to the committee’s members and their respective employing institutions.

Literature Cited

ASABE. (2005). D384.2 Manure Characteristics. Standards. St. Joseph, MI: American Society of Agricultural and Biological Engineers.

Banner, S. C., Zering, K. D., & Classen, J. J. (2017). Environmental tradeoffs of alternative scenarios for swine waste management technologies: A life cycle perspective. ASABE Paper No. 1700187. St. Joseph, MI: American Society of Agricultural and Biological Engineers.

Challinor, A. J., Watson, J., Lobell, D. B., Howden, S. M., Smith, D. R,. & Chhetri, N. (2014). A meta-analysis of crop yield under climate change and adaptation. Nature Climate Change, 4(4), 287.

FTM. (2018). Fieldprint platform. Field to Market. Retrieved from https://fieldtomarket.org/our-program/fieldprint-platform/

Henderson, A., Asselin, A., Heller, M., Vionnet, S., Lessard, L., Humbert, S., Saad, R., Margni, M., Thoma, G., Matlock, M., Burek, J., Kim, D., & Jolliet, O. (2012). U.S. Fluid Milk Comprehensive LCA. University of Michigan & University of Arkansas.

ICUSD. (2016). Stewardship and sustainability framework for US Dairy. Retrieved from https://www.usdairy.com/sustainability/reporting/stewardship-and-sustainability-framework-for-us-dairy

Jost, L. (2006). Entropy and diversity. OIKOS, 113(2), 363-375.

Liu, Z., Powers, W., & Liu, H. (2013). Greenhouse gas emissions from swine operations: Evaluation of the Intergovernmental Panel on Climate Change approaches through meta-analysis. Journal of Animal Science, 91(8), 4017-4032.

Liu, Z., Powers, W., Murphy, J., & Maghirang, R. (2014). Ammonia and hydrogen sulfide emissions from swine production facilities in North America: a meta-analysis. Journal of Animal Science, 92(4), 1656-1665.

Miller, C. M., Price, P. L., & Meyer, D. (2017). Mass balance analyses of nutrients on California dairies to evaluate data quality for regulatory review. Science of the Total Environment, 579, 37-46.

MSC. (2018). About us. Marine Stewardship Council. Retrieved from https://www.msc.org/about-us.

NPB. (2018a). Strategic Plan. National Pork Board. Retrieved from https://www.pork.org/about/strategic-plan/

NPB. (2018b). Environmental impact of pig farming. National Pork Board. Retrieved from https://www.pork.org/environment/environmental-impact-pig-farming/

NRC. (2010). Toward Sustainable Agricultural Systems in the 21st Century. National Research Council. National Academies Press.

NRSP_TEMP11. (2016). National agricultural research data network for harmonized data. Retrieved from https://www.nimss.org/projects/view/mrp/outline/18298

SAESD. (2013). Guidelines for multistate research activities. Retrieved from http://escop.info/wp-content/uploads/2017/04/MRF-Guidelines-Revised-08-1-513.pdf

Shannon, C. E. (1948). A mathematical theory of communication. The Bell System Technical Journal, 27, 379-423 and 623-656.

Thoma, G., Popp, J., Nutter, D., Shonnard, D., Ulrich, R., Matlock, M., Kim, D.S., Neiderman, Z., Kemper, N., East, C., & and Adom, F. (2013). Greenhouse gas emissions from milk production and consumption in the United States: A cradle-to-grave life cycle assessment circa 2008. International Dairy Journal, 31, S3-S14.

Thoma, G., Popp, J., Shonnard, D., Nutter, D., Ulrich, R., Matlock, M., Kim, D., Neiderman, Z., East, C., Adom, F., & Kemper, N. (2010). Greenhouse gas emissions from production of fluid milk in the US. Dairy Management Inc., Rosemont, IL.

USDA. (2018). Sustainable agriculture program. United States Department of Agriculture National Institute of Food and Agriculture. Retrieved from https://nifa.usda.gov/program/sustainable-agriculture-program

USRSB Indicator Working Group. (2017). Metric Development Report Version 5.0. Ed. M. D. Matlock. Retrieved fromhttps://www.usrsb.org/CMDocs/USRSB/USRSB_IWG_Metric_Report_V5_FINAL.pdf

USSA. (2018). Poultry and eggs sustainability factsheet. Retrieved from https://thesustainabilityalliance.us/wp-content/uploads/2017/09/US-Poultry-and-Eggs-Sustainability-Fact-Sheet.pdf

Attachments

Land Grant Participating States/Institutions

AR, CA, GA, IA, ID, IL, KS, MI, MN, MO, NC, NE, NY, OH, OK, TX, VA, WI, WV

Non Land Grant Participating States/Institutions

NIFA, University of Illinois at Urbana-Champaign, USDA-ARS