skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Workflows for Knowledge Co-Production—Meat and Dairy Processing in Ohio and Northern California
Solving the wicked problems of food system sustainability requires a process of knowledge co-production among diverse actors in society. We illustrate a generalized workflow for knowledge co-production in food systems with a pair of case studies from the response of the meat and dairy production sectors in the wake of the COVID-19 pandemic. The first case study serves as an example of a scientific workflow and uses a GIS method (location allocation) to examine the supply chain linkages between meat and dairy producers and processors in Ohio. This analysis found that meat producers and processors are less clustered and more evenly distributed across the state than dairy producers and processors, with some dairy processors potentially needing to rely on supply from producers up to 252 km away. The second case study in California adds an example of a stakeholder workflow in parallel to a scientific workflow and describes the outcome of a series of interviews with small and mid-scale meat producers and processors concerning their challenges and opportunities, with the concentration of processors arising as the top challenge faced by producers. We present a pair of workflow diagrams for the two case studies that illustrate where the processes of knowledge co-production are situated. Examining these workflow processes highlights the importance of data privacy, data governance, and boundary spanners that connect stakeholders.  more » « less
Award ID(s):
1737573
PAR ID:
10429258
Author(s) / Creator(s):
; ; ; ; ; ; ; ;
Date Published:
Journal Name:
Sustainability
Volume:
15
Issue:
13
ISSN:
2071-1050
Page Range / eLocation ID:
9991
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract The food system is an important contributor to carbon dioxide (CO 2 ) emissions. The refrigerated food supply chain is an energy-intensive, nutritious and high-value part of the food system, making it particularly important to consider. In this study, we develop a novel model of cold chain food flows between counties in the United States. Specifically, we estimate truck transport via roadways of meat and prepared foodstuffs for the year 2017. We use the roadway travel distance in our model framework rather than the haversine distance between two locations to improve the estimate for long-haul freight with a temperature-controlled system. This enables us to more accurately calculate the truck fuel consumption and CO 2 emissions related to cold chain food transport. We find that the cold chain transport of meat emitted 8.4 × 10 6 t CO 2 yr −1 and that of prepared foodstuffs emitted 14.5 × 10 6 t CO 2 yr −1 , which is in line with other studies. Meat has a longer average refrigerated transport distance, resulting in higher transport CO 2 emissions per kg than processed foodstuffs. We also find that CO 2 emissions from cold chain food transport are not projected to significantly increase under the temperatures projected to occur with climate change in 2045. These county-level cold chain food flows could be used to inform infrastructure investment, supply chain decision-making and environmental footprint studies. 
    more » « less
  2. This dataset contains yearly projections of emission factors (EFs) for fertilizer-induced direct nitrous oxide (N2O) emissions across the global agricultural lands with a spatial resolution of 0.5° × 0.5° from 1990 to 2050. Emission factor (EF) is defined as the amount of N2O emitted per unit of nitrogen (N) fertilizer applied, expressed in percentage (%). They are developed from a hybrid modeling framework, Dym-EF (more details can be found in Li et al., 2024). The framework integrates machine learning approaches with an ensemble of eight process-based models from The Global N2O Model Intercomparison Project phase 2 (NMIP2) to learn the relationship between EF dynamics and multiple environmental factors, such as climate, soil properties, nitrogen fertilizer input, and other agricultural management practices. After the hybrid modeling framework was extensively validated, we applied it to develop EF projections under different nitrogen management policies and climate change scenarios, including future climate data from 37 Global Climate Models (GCMs). The annual median and standard deviation (SD) of EF under each scenario represent the projection median and variability derived from climate input data using the 37 GCMs.The dataset filenames follow the structure: 'Scenario'_'N regulation'_'Median/SD', where 'Scenario' corresponds to the different nitrogen management and climate scenarios (e.g., INMS1, INMS2, and INMS3), 'N regulation' corresponds to the different nitrogen management levels (e.g., BAU, LowNRegul, and MedNRegul), and 'Median/SD' indicates whether the file contains the median (Median) or standard deviation (SD) of the projections. All relevant data and further details can be found in the supplementary materials and the cited references.INMS1: Business-as-usual, Land use regulation: Medium, Diet: Meat & dairy-rich, Ambition level: LowINMS2: Low-nitrogen regulation, Land use regulation: Medium, Diet: Medium meat & dairy, Ambition level: LowINMS3: Medium-nitrogen regulation, Land use regulation: Medium, Diet: Medium meat & dairy, Ambition level: ModerateINMS4: High-nitrogen regulation, Land use regulation: Medium, Diet: Medium meat & dairy, Ambition level: HighINMS5: Best-case, Land use regulation: Strong, Diet: Low meat & dairy, Ambition level: HighINMS6: Best-case “Plus”, Land use regulation: Strong, Diet: Ambitious diet shift and food-loss/waste reductions, Ambition level: HighINMS7: Bioenergy, Land use regulation: Strong, Diet: Low meat & dairy, Ambition level: HighWe developed this data using the “ranger” package in R 4.1.1, which is accessible at https://cran.r-project.org/web/packages/ranger/. The optimization of the two hyperparameters (ntree and mtry) was performed using the ‘caret’ package, available at https://topepo.github.io/caret/.This database is developed by Li, L., C. Lu, W. Winiwarter, H. Tian, J. Canadell, A. Ito, A.K. Jain, S. Kou-Giesbrecht, S. Pan, N. Pan, H. Shi, Q. Sun, N. Vuichard, S. Ye., S. Zaehle, Q. Zhu. Enhanced nitrous oxide emission factors due to climate change increase the mitigation challenge in the agricultural sector Global Change Biology (In Press) 
    more » « less
  3. Abstract Objective: Water plays a critical role in the production of food and preparation of nutritious meals, yet few studies have examined the relationship between water and food insecurity. The primary objective of this study, therefore, was to examine how experiences of household water insecurity (HWI) relate to experiences of household food insecurity (HFI) among a pastoralist population living in an arid, water-stressed region of northern Kenya. Design: We implemented the twelve-item Household Water Insecurity Experiences (HWISE, range 0–36) Scale and the nine-item Household Food Insecurity Access Scale (HFIAS, range 0–27) in a cross-sectional survey to measure HWI and HFI, respectively. Data on socio-demographic characteristics and intake of meat and dairy in the prior week were collected as covariates of interest. Setting: Northern Kenya, June–July 2019. Participants: Daasanach pastoralist households ( n 136) from seven communities. Results: In the prior 4 weeks, 93·4 % and 98·5 % of households had experienced moderate-to-severe HWI and HFI, respectively. Multiple linear regression analyses indicated a strong association between HWI and HFI. Each point higher HWISE score was associated with a 0·44-point (95 % CI: 0·22, 0·66, P = 0·003) higher HFIAS score adjusting for socio-economic status and other covariates. Conclusions: These findings demonstrate high prevalence and co-occurrence of HWI and HFI among Daasanach pastoralists in northern Kenya. This study highlights the need to address HWI and HFI simultaneously when developing policies and interventions to improve the nutritional well-being of populations whose subsistence is closely tied to water availability and access. 
    more » « less
  4. Abstract Beef production systems are at the center of ongoing discussion and debate on food systems sustainability. There is a growing interest among beef producers, consumers, and other beef supply chain stakeholders in achieving greater sustainability within the industry, but the relationship of this interest to general sustainability issues such as climate change, biodiversity loss, food security, livelihood risks, and animal welfare concerns is unclear. Specifically, there is very little research documenting how beef producers define and view the concept of sustainability and how to achieve it. Producer perspectives are critical to identifying constraints to sustainability transitions or to help build agreement with other producers about the shared values such transitions may support. Through a secondary analysis of survey data of U.S. beef producers (n = 911) conducted in 2021 by the Trust in Food division of Farm Journal, a corporation that provides content, data, and business insights to the agricultural community (e.g., producers, processors/distributors, and retailers), we investigated what “sustainable beef” means to U.S. beef producers, highlighting the key components and constraints they perceive to achieving desirable sustainability outcomes. Leveraging the three-pillar model of sustainability as a framework for analysis, we identified key themes producers use to define “sustainable beef.” We found that producers collectively viewed sustainability as: (1) multidimensional and interconnected; (2) semi-closed and regenerative; (3) long-lasting; and (4) producer-centered, although an integrated perspective uniting these aspects was rare. We discuss how these perspectives may be the basis for sustainability efforts supported by producers and raise future research considerations toward a shared understanding of what sustainability is and what is needed for enduring sustainability solutions in the U.S. beef industry. 
    more » « less
  5. Abstract Most farmland in the US Corn Belt is used to grow row crops at large scales (e.g., corn, soybean) that are highly processed before entering the human food stream rather than specialty crops grown in smaller areas and meant for direct human consumption (table food). Bolstering local table food production close to urban populations in this region through peri-urban agriculture (PUA) could enhance sustainability and resilience. Understanding factors influencing PUA producers' preferences and willingness to produce table food would enable supportive planning and policy efforts. This study combined land use visualization and survey data to examine the potential for increased local table food production for the US Corn Belt. We developed a spatial visualization of current agricultural land use and a future scenario with increased table food production designed to meet 50% of dietary requirements for a metropolitan population in 2050. A survey was administered to row crop (1360) and specialty crop (55) producers near Des Moines, Iowa, US to understand current and intended agricultural land use and factors influencing production. Responses from 316 row crop and 25 specialty crop producers were eligible for this analysis. A future scenario with increased table food production would require less than 3% of available agricultural land and some additional producers (approximately 130, primarily for grain production). Survey responses indicated PUA producers planned small increases in table food production in the next three to five years. Producer plans, including land rental for table food production, could provide approximately 25% of residents' fruit, vegetables, and grains, an increase from the baseline of 2%. Row crop producers ranked food safety regulations, and specialty producers ranked labor concerns as strong influences on their decision-making. Both groups indicated that crop insurance and processing facilities were also important. Increasing table food production by clustering mid-scale operations to increase economies of scale and strengthening supply chains and production infrastructure could provide new profitable opportunities for farmers and more resilient food systems for growing urban regions in the US Corn Belt. Continuing to address producer factors and landscape-scale environmental impacts will be critical in considering food system sustainability challenges holistically. 
    more » « less