Adventure Dairy: Educational and Technical Tools for Carbon Cycle Modeling on a Virtual Dairy Farm

Conceptualizing, modeling, and controlling carbon flows at the farm scale can improve efficiency in production, reduce costs, and promote beneficial products and byproducts of agricultural processes through best management practices. On dairy farms, opportunities exist for farmers to control factors affecting greenhouse gas (GHG) emissions and diversions from production and operations. Complex programs to model the effects of different carbon management strategies on net emissions are very useful to farmers, but lack visualization of flows through a user interface to show effects of different management choices in real time.

Previously, a collaborative research team at Penn State University and the University of Wisconsin-Madison has developed a Virtual Dairy Farm website to share information about how dairy farms incorporate best management practices and other on-farm production choices to reduce environmental impacts. The website is organized in two model farm configurations, a 150-cow and a 1500-cow modern dairy farm. Website users can find information on different components of the farm by exploring locations on the farm. Links to information about farm operations are structured in multiple levels such that information is understandable to the general public but also supported by technical factsheets for agriculture professionals.

What did we do?

Building on the strengths of the Penn State Virtual Dairy Farm interactive website, the Team has developed a concept for an “Adventure Dairy” package for users to explore how management choices affect total on-farm GHG emissions for a model Pennsylvania dairy farm (Figure 1). Five main categories serve as management portals superimposed on the Virtual Dairy interface, including Cow Life Cycle, Manure Management, Crop Production, Energy Use on Farm, and Feed on Farm.

Figure 1. Example landing page for the proposed Adventure Dairy website. Different regions to explore to access the GHG emissions calculator are highlighted in different colors.
Figure 1. Example landing page for the proposed Adventure Dairy website. Different regions to explore to access the GHG emissions calculator are highlighted in different colors.

For each category, users can select from multiple options to see how these decisions increase or decrease emissions. Along the bottom of the webpage, a calculator displays the net carbon balance for the model system and change emissions estimates as users choose feed composition, land use strategies, and other important components (Figure 2). Under each category, users can make choices about different management practices that affect on-farm carbon cycling. For example, different choices for feed additives change total net GHG emissions, and, in turn, can affect total manure production. A change in management and operational choices, such as storage, is visually communicated through interactions and on the interface (Figure 3). These management portals can be seamlessly integrated with the Virtual Dairy Farm as an addition to the right sidebar. The click-through factsheets currently a part of the interface can be preserved through new informational “fast facts” overlays with accompanying infographics and charts. Pathways to optimizing carbon flows to ensure maximum production and minimum environmental impact will be featured as “demo” examples for users.

Figure 2. Example Adventure Dairy user interface for manure management. User choices to increase and decrease total GHG emissions are included in the right sidebar. Along the bottom of the page, a ribbon shows the total emissions from each category.
Figure 2. Example Adventure Dairy user interface for manure management. User choices to increase and decrease total GHG emissions are included in the right sidebar. Along the bottom of the page, a ribbon shows the total emissions from each category.
Figure 3. A different user choice for manure storage type on the Adventure Dairy interface. Total GHG emissions decrease by 14% because of the switch from an uncovered to a covered anaerobic lagoon because of reduced volatilization of methane.
Figure 3. A different user choice for manure storage type on the Adventure Dairy interface. Total GHG emissions decrease by 14% because of the switch from an uncovered to a covered anaerobic lagoon because of reduced volatilization of methane.

What have we learned?

This model offers a novel platform for more interactive software programs and websites for on-farm modeling of carbon emissions and will inform future farm management visualizations and data analysis program interfaces. The Team envisions the Adventure Dairy platform as an important tool for Extension specialists to share information with dairy professionals about managing carbon flows on-farm. Simultaneously, consumers increasingly seek information on the environmental impacts of agriculture. This interactive website is a valuable educational and technical tool for a variety of audiences.

Uniquely, a multidisciplinary team of agriculture and engineering graduate students from multiple institutions are leading this project, as facilitated by faculty. This Cohort Challenge model allows for graduate students to engage with complex food-energy-water nexus problems at the level of faculty investigators in a virtual educational resource center. Future INFEWS-ER teams and “wicked problems” challenge projects will continue to develop this model of learning and producing novel research products.

Future plans

The Cohort Challenge Team is entering a peer/faculty review process of the simplified carbon model for the Virtual Dairy Farm website. The user interface for the Adventure Dairy calculator is not currently a part of the Penn State Virtual Dairy Farm. The Team will be working with software developers to integrate our model in the existing interface. Additional components under consideration for inclusion in the Adventure Dairy calculator include cost comparisons for different best management practices, an expanded crop production best management calculator, and incorporation of

Authors

Student Team: Margaret Carolan,1 Joseph Burke,2 Kirby Krogstad,3 Joslyn Mendez,4 Anna Naranjo,4 and Breanna Roque4

Project Leads: Deanne Meyer,4 Richard Koelsch,3 Eileen Fabian,5 and Rebecca Larson6

 

  1. Department of Civil and Environmental Engineering, University of Iowa, Iowa City, IA crln@uiowa.edu
  2. Texas A&M University
  3. University of Nebraska-Lincoln
  4. University of California-Davis
  5. Penn State University
  6. University of Wisconsin-Madison

Acknowledgements

Funding for the INFEWS-ER was provided by the National Science Foundation #1639340. Additional support was provided by the National Institute for Food and Agriculture’s Sustainable Dairy CAP and the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign.

Useful resources

  1. Penn State Virtual Dairy Farm: http://virtualfarm.psu.edu/
  2. INFEWS-ER: http://infews-er.net/
  3. Sustainable Dairy CAP: http://www.sustainabledairy.org/Pages/home.aspx

 

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2019. Title of presentation. Waste to Worth. Minneapolis, MN. April 22-26, 2019. URL of this page. Accessed on: today’s date.

Environmental Impacts of Dairy Production Systems in the Changing Climate of the Northeast

To meet the nutritional needs of a growing population, dairy producers must increase milk production while minimizing farm environmental impacts. As we look to the future, management practices must also be adapted to maintain production under projected climate change. To plan for the future, better information is needed on practices that can reduce emissions from the farm and adapt to changes in the climate while maintaining or improving production and profitability.

What did we do?

We conducted a comprehensive assessment of the effects of climate change on both the productivity and environmental performance of farms as influenced by strategies to reduce emissions and adapt to the changing climate. Production systems were evaluated using three representative northeastern dairy farms: a 1500-cow farm in New York, a 150-cow farm in Wisconsin and a 50-cow farm in southern Pennsylvania. A cradle-to-farm gate life cycle assessment was conducted using farm-scale process-based modeling and climate projections for high and low emission scenarios. Environmental considerations included the carbon footprint of the milk produced and reactive N and P losses from the farms.

What we have learned?

We found that the environmental impact of the three representative dairy farms generally increased in the near future (2050) climate if no mitigation measures were taken. Overall, feed production was maintained as decreases in corn grain yield were compensated by increases in forage yields. Adaptation of the cropping system through changes in planting and harvest dates and corn variety led to a smaller reduction in corn grain yield, but the detrimental effects of climate change could not be fully negated. Considering the increased forage yield, total feed production increased except for the most severe projected climate change. Adoption of farm-specific beneficial management practices substantially reduced the greenhouse gas emissions and nutrient losses of the farms in current climate conditions and stabilized the environmental impact in future climate conditions, while maintaining feed and milk production (See Figure 1 for example results).

Figure 1. Carbon footprint, reactive nitrogen footprint and P loss in recent (2000) and future (2050) climate conditions (RCP4.5 and RCP8.5) for a 1500-cow farm in New York with baseline and Best Management Practice (BMP) scenarios, with and without crop system adaptions in 2050. Error bars represent the standard deviation of IFSM simulations for 3 climate scenarios per RCP. Unadapt = not adapted cropping system. Adapt = adapted cropping system.
Figure 1. Carbon footprint, reactive nitrogen footprint and P loss in recent (2000) and future (2050) climate conditions (RCP4.5 and RCP8.5) for a 1500-cow farm in New York with baseline and Best Management Practice (BMP) scenarios, with and without crop system adaptions in 2050. Error bars represent the standard deviation of IFSM simulations for 3 climate scenarios per RCP. Unadapt = not adapted cropping system. Adapt = adapted cropping system.

The take-home message is that with appropriate management changes, our dairy farms can become more sustainable under current climate and better prepared to adapt to future climate variability.

Future plans

A more comprehensive life cycle assessment is being done by linking the output of the farm model with life cycle assessment software. The process level simulation of the farm provides inventory information for an inclusive life cycle assessment with multiple environmental considerations. This integrated software will provide a more complete sustainability assessment of the potential benefits of alternative management strategies for both now and the future.

Authors

Karin Veltman, University of Michigan; C. Alan Rotz, USDA-ARS; Larry Chase, Cornell University; Joyce Cooper, Washington State University; Chris Forest, Penn State University; Pete Ingraham, Applied GeoSolutions; R. César Izaurralde, University of Maryland; Curtis D. Jones, University of Maryland; Robert Nicholas, Penn State University; Matt Ruark, University of Wisconsin; William Salas, Applied GeoSolutions; Greg Thoma, University of Arkansas; Olivier Jolliet, University of Michigan.

Additional information

Information on the Integrated Farm System Model is available in the reference manual:

Rotz, C., Corson, M., Chianese, D., Montes, F., Hafner, S., Bonifacio, H., Coiner, C., 2018. The Integrated Farm System Model, Reference Manual Version 4.4. Agricultural Research Service, USDA. Available at: https://www.ars.usda.gov/northeast-area/up-pa/pswmru/docs/integrated-farm-system-model/#Reference.

Information on the analysis of Best Management Practices on northeastern dairy farms is available in:

Veltman, K., C. A. Rotz, L. Chase, J. Cooper, P. Ingraham, R. C. Izaurralde, C. D. Jones, R. Gaillard, R. A. Larsson, M. Ruark, W. Salas, G. Thoma, and O. Jolliet. 2017. A quantitative assessment of beneficial management practices to reduce carbon and reactive nitrogen footprints and phosphorus losses of dairy farms in the Great Lakes region of the United States. Agric. Systems 166:10-25.

Acknowledgements

This work was supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, under award number 2013-68002-20525. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2019. Title of presentation. Waste to Worth. Minneapolis, MN. April 22-26, 2019. URL of this page. Accessed on: today’s date.

Cataloging and Evaluating Dairy Manure Treatment Technologies


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Purpose

To provide a forum for the introduction and evaluation of technologies that can treat dairy manure to the dairy farming community and the vendors that provide these technologies.

What Did We Do?

Newtrient has developed an on-line catalog of technologies that includes information on over 150 technologies and the companies that produce them as well as the Newtrient 9-Point scoring system and specific comments on each technology by the Newtrient Technology Advancement Team.

What Have We Learned?

Our interaction with both dairy farmers and technology vendors has taught us that there is a need for accurate information on the technologies that exist, where they are used, where are they effective and how they can help the modern dairy farm address serious issues in an economical and environmentally sustainable way.

Future Plans

Future plans include expansion of the catalog to include the impact of the technology types on key environmental areas and expansion to make the application of the technologies on-farm easier to conceptualize.

Corresponding author name, title, affiliation  

Mark Stoermann & Newtrient Technology Advancement Team

Corresponding author email address  

info@newtrient.com

Other Authors 

Garth Boyd, Context

Craig Frear, Regenis

Curt Gooch, Cornell University

Danna Kirk, Michigan State University

Mark Stoermann, Newtrient

Additional Information

http://www.newtrient.com/

Acknowledgements

All of the vendors and technology providers that have worked with us to make this effort a success need to be recognized for their sincere effort to help this to be a useful and informational resource.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2017. Title of presentation. Waste to Worth: Spreading Science and Solutions. Cary, NC. April 18-21, 2017. URL of this page. Accessed on: today’s date.

Planning for Resilience: Using Scenarios to Address Potential Impacts of Climate Change for the Northern Plains Beef System

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Purpose

Resiliency to weather extremes is a topic that Northern Plains farmers and ranchers are already familiar with, but now climate change is adding new uncertainties that make it difficult to know the best practices for the future. Scenario planning is a method of needs assessment that will allow Extension and beef system stakeholders to come together using the latest climate science to discover robust management options, highlight key uncertainties, prioritize Extension programming needs, and provide an open forum for discussion for this sometimes controversial topic.

Overall objectives:

1. Determine a suite of key future scenarios based on climate science that are plausible, divergent, relevant, and challenging to the beef industry.

2. Determine robust management options that address the key scenario drivers.

3. Develop a plan for Extension programming to address determined educational needs.

What did we do?

A team of researchers, Extension specialists, and educators was formed with members from University of Nebraska and South Dakota State University. They gathered the current research information on historical climate trends, projections in future climate for the region, and anticipated impacts to the beef industry. These were summarized in a series of white papers.

Three locations were selected to host two half day focus groups, representing the major production regions. A diverse group representing the beef industry of each region including feedlot managers, cow calf ranchers, diversified producers, veterinarians, bankers, NRCS personnel, and other allied industries. The first focus group started with a discussion of the participants past experiences with weather impacts. The team then provided short presentations starting with historic climate trends and projection, anticipated impacts, and uncertainties. The participants then combined critical climate drivers as axis in a 2×2 grids, each generating a set of four scenarios. They then listed impacts for each combination. The impacts boundaries were feed production through transporting finished cattle off-farm.

Project personnel then combined the results of all three locations to prioritize the top scenarios, which were turned into a series of graphics and narratives. The participants were then brought together for a second focus group to brainstorm management and technology options that producers were already implementing or might consider implementing. These were then sorted based on their effectiveness across multiple climate scenarios, or robustness. The options where also sorted by the readiness of the known information: Extension materials already available, research data available but few Extension materials, and research needed.

Graphic depicting warm/dry, warm/wet, cold/dry, cold/wet conditions on the farm during winter-spring

Graphic depicting hot/dry, hot/wet, cool/dry, cool/wet conditions on the farm during summer-fall

What have we learned?

The key climate drivers were consistent across all focus groups: temperature and precipitation, ranging from below average to above average. In order to best capture the impacts, the participants separated winter/spring and summer/fall.

This method of using focus groups as our initial interaction with producers on climate change was well received. Most all farmers love to talk about the weather, so discussing historical trends and their experiences with it as well as being upfront with the uncertainties in future projections, while emphasizing the need for proactive planning seemed to resonate.

With so many competing interests for producers’ time, as well as a new programming area, it was critical to have trusted local educators to invite participants. Getting participants to the second round of focus groups was also more difficult, so future efforts should considering hosting a single, full day focus group, or allowing the participants to set the date for the second focus group, providing more motivation to attend.

Future Plans

The scenarios and related management options will be used to develop and enhance Extension programming and resources as well as inform new research efforts. The goal is to provide a suite of robust management options and tools to help producers make better decisions for their operation.

Corresponding author, title, and affiliation

Crystal Powers, Extension Engineer, University of Nebraska – Lincoln

Corresponding author email

cpowers2@unl.edu

Other authors

Rick Stowell, Associate Professor at University of Nebraska – Lincoln

Additional information

Crystal Powers

402-472-0888

155 Chase Hall, East Campus

Lincoln, NE 68583

Acknowledgements

Thank you to the project team:

University of Nebraska – Lincoln: Troy Walz, Daren Redfearn, Tyler Williams, Al Dutcher, Larry Howard, Steve Hu, Matthew Luebbe, Galen Erickson, Tonya Haigh

South Dakota State University: Erin Cortus, Joseph Darrington,

This project was supported by the USDA Northern Plains Regional Climate Hub and Agricultural and Food Research Initiative Competitive Grant No. 2011-67003-30206 from the USDA National Institute of Food and Agriculture.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2017. Title of presentation. Waste to Worth: Spreading Science and Solutions. Cary, NC. April 18-21, 2017. URL of this page. Accessed on: today’s date.

How Well Do We Understand Nitrous Oxide Emissions from Open-lot Cattle Systems?

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Purpose

Nitrous oxide (N2O) emissions from concentrated animal feeding operations, including cattle feedyards, have become an important research topic. However, there are limitations to current measurement techniques, uncertainty in the magnitude of feedyard N2O fluxes, and a lack of effective mitigation methods. There are uncertainties in the pathway of feedyard N2O production, the dynamics of nitrogen transformations in these manure-based systems, and how N2O emissions differ with changes in climate and feedyard management.

What Did We Do?

A literature review was conducted to assess the state-of-the-science of N2O production and emission from open-lot beef cattle feedyards and dairies. The objective was to assess N2O emission from cattle feedyards, including comparison of measured and modeled emission rates, discussion of measurement methods, and evaluation of mitigation options. In addition, laboratory, pilot-scale, and field-scale chamber studies were conducted to quantify and characterize N2O emissions from beef cattle manure. These studies led to new empirical model to predict feedyard N2O fluxes as a function of temperature and manure nitrate and water contents. Organic matter stability/availability was important in predicting manure-derived N2O emissions: inclusion of data for dissolved organic carbon content and Ultraviolet-visible (UV-vis) spectroscopic indices of molecular weight, complexity and degree humification improved model performance against measured data.

What Have We Learned?

Published annual per capita flux rates for beef cattle feedyards and open-lot dairies in arid climates were highly variable and ranged from 0.002 to 4.3 kg N2O animal-1 yr-1. On an area basis, published emission rates ranged from 0 to 41 mg N2O m-2 h-1. From these studies and the Intergovernmental Panel on Climate Change emission factors, calculated daily per capita N2O fluxes averaged 18 ± 10 g N2O animal-1 d-1 (range, 0.04–67 g N2O animal-1 d-1). Some of this variability is inherently derived from differences in manure management practices and animal diets among open-lot cattle systems. However, it was proposed that other major causes of variation were inconsistency in measurement techniques, and irregularity in N2O production due to environmental conditions.

For modeling studies, N2O emissions were measured during 15 chamber studies (10 chambers per study) on commercial Texas feedyards, where N2O emissions ranged from below detection to 101 mg N2O m-2 h-1. Numerous feedyard and manure data were collected and regression analyses were used to determine key variables involved in feedyard N2O losses. Based on these data, two models were developed: (1) a simple model that included temperature, manure water content, and manure nitrate concentration, and (2) a more complex model that included UV-vis spectral data that provided an estimate of organic matter stability. Overall, predictions with both models were not significantly different from measured emissions (P < 0.05) and were within 52 to 61% agreement with observations. Inclusion of data for organic matter characteristics improved model predictions of high (>30 mg m-2 h-1) N2O emissions, but tended to overestimate low emission rates (<20 mg N2O m-2 h-1). This work represents one of the first attempts to model feedyard N2O. Further refinement is needed to be useful for predicting spatial and temporal variations in feedyard N2O fluxes.

Future Plans

This work clearly identified that neither the magnitude nor the dynamics of N2O emissions from open-lot cattle systems were well understood. Five primary knowledge gaps/problem areas were identified, where current understanding is weak and further research is required. These include: (i) the need for accurate measurement of N2O emissions with appropriate and more standardized methods; (ii) improved understanding of the microbiology, chemistry, and physical structure of manure within feedyard pens that lead to N2O emissions; (iii) improved understanding of factors that influence feedyard N2O emissions, including manure H2O content, porosity, density, available nitrogen and carbon contents, environmental temperatures, and use of veterinary pharmaceuticals; (iv) development of cost-effective and practical mitigation strategies to decrease N2O emissions from pen surfaces, manure stockpiles, composting windrows, and retention ponds; and (v) improved process-based models that can accurately predict feedyard N2O emissions, evaluate mitigation strategies, and forecast future N2O emission trends.

Given the potential for future regulation of N2O emissions, feedyard managers, nutritionists, and researchers may play increasingly important roles in on-farm nitrogen management. Current management practices may need modification or refinement to balance production efficiency with environmental concerns. There is a need for data derived from both large-scale micrometerological measurement campaigns and small-scale chamber studies to assess the overall magnitude of feedyard N2O emissions and to determine key factors driving its production and emission. Refined empirical and process-based models based on manure physicochemical properties and weather could provide a dynamic approach to predict N2O losses from open-lot cattle systems.

Corresponding author (name, title, affiliation):

Heidi Waldrip, Research Chemist, USDA-ARS Conservation and Production Laboratory, Bushland, TX

Corresponding author email address

heidi.waldrip@ars.usda.gov

Other Authors

Rick Todd, Research Soil Scientist, USDA-ARS Conservation and Production Laboratory, Bushland, TX

David Parker, Agricultural Engineer, USDA-ARS Conservation and Production Research Laboratory, Bushland, TX

Al Rotz, Agricultural Engineer, USDA-ARS Pasture Systems and Watershed Management Research Unit, University Park, PA

Andy Cole, Animal Scientist, USDA-ARS Conservation and Production Research Laboratory (retired), Bushland, TX.

Ken Casey, Associate Professor, Texas A&M AgriLife Research, Amarillo, TX

Additional Information

“Nitrous Oxide Emissions from Open-Lot Cattle Feedyards: A Review”. Waldrip, H. M., Todd, R. W., Parker, D. B., Cole, N. A., Rotz, C. A., and Casey, K. D. 2016. J. Environ. Qual. 45:1797-1811. Open-access article available at:  https://dl.sciencesocieties.org/publications/jeq/pdfs/45/6/1797?search-r…

USDA-ARS Research on Feedyard Nitrogen Sustainability: http://www.beefresearch.org/CMDocs/BeefResearch/Sustainability_FactSheet…

Acknowledgements

This research was partially funded by the Beef Checkoff: http://www.beefboard.org/

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2017. Title of presentation. Waste to Worth: Spreading Science and Solutions. Cary, NC. April 18-21, 2017. URL of this page. Accessed on: today’s date.

Estimating the Economic Value of the Greenhouse Gas Reductions Associated with Dairy Manure Anaerobic Digestion Systems Located in New York State

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Purpose

There is a worldwide concern in controlling the anthropogenic emissions of greenhouse gas (GHG) emissions. GHGs pertinent to this paper, include carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) and are measured in CO2 equivalents (CO2 eq.). On a 100-year basis, CH4 is 34 times as potent as CO2, while N2O is 298 times as potent as CO2 (IPCC, 2013); CO2 eq. is referred to as the global warming potential (GWP) of these gases. The carbon from feed used on a dairy farm originally comes from CO2 recently removed from the atmosphere during photosynthesis and so has a neutral impact on climate change. However, carbon that is converted to CH4 and N2O is a significant concern since their GWPs are much higher. Dairy farms create GHG emissions when they use fossil fuel-based sources to provide energy for the farm, when importing fertilizer to grow crops and to harvest milk. However, emissions from the animals in the form of enteric CH4 and GHGs from manure management ! are much more significant due to the GWP. While every farm is different, estimates from Thoma et al. (2012) show that of the 34.9 Tg of CO2 eq. in the US dairy supply chain, 19% comes from feed production and 53% comes from milk production. Of the milk production, CO2 eq., 49% is from enteric emissions while 44% is from manure management, predominately from CH4 emissions from manure storages.

New York State, the third largest dairy state in the nation (NASS, 2015), has established ambitious overall renewable energy goals including incorporating 50% renewable energy in the electricity used in the State by 2030 (Energy to Lead, 2015) and reducing GHG emissions 40% by 2040 based on 1990 year baseline values (Executive Order, 2009). The New York State Public Service Commission (PSC) is charged with the responsibility of developing a system that encourages utilities to help meet these goals. This includes reforming the energy vision, a new clean energy standard that is being developed to value electric products from distributed energy sources that includes an economic value for the environmental attributes (E).

An attempt at quantifying the environmental benefits of AD (E) might be expressed as follows:

Etotal=∑▒〖Eghg+Eair quality+Ewater quality+Esoil quality+E…〗

As the State’s renewable energy goals are realized, there needs to be a way for the process to include special provisions for those renewable energy sources that have extra societal benefits, including economic and environmental, and that support the rural character of upstate NY. The dairy industry is New York’s leading agricultural sector, accounting for more than one-half of the state’s total agricultural receipts. The increased milk supply has been very important in helping to meet the tremendous growth in the production of yogurt in NYS. However, the margin between the cost of producing milk and the price received for milk sales, is shrinking. Investing in farm facilities like ADSs will need to be analyzed carefully to ensure a return on investment that merits their implementation. An economic value for the environmental attributes of electricity produced from an ADS would aid in the analysis, showing a more positive overall benefit.

Dairy farms are also under increasing pressure to improve conditions environmentally. The New York State Department of Environmental Conservation (NYSDEC) proposed revisions for the CAFO state permit, regulating the water quality impact of farms with more than 300 cows, will require manure storages to be built to limit spreading on at-risk fields during the winter and early spring seasons. These are farm sizes where manure-based ADSs have been built in the past and where many more could be implemented, given a reasonable rate of return. Manure storages are an important best management practice (BMP) to reduce the potential for water pollution by allowing farms to avoid manure spreading during inappropriate times. Unfortunately, if the manure system does not have a way to capture the GHGs produced, they are released into the atmosphere. Manure-based ADSs installed on farms would be a win-win-win to capture and reduce GHGs and to produce renewable energy from the captured! CH4, fur thermore helping to meet the NYS renewable energy and GHG reduction goals. ADSs installed on farms would stimulate the rural economy and also provide the farm and rural community with all the additional benefits contained in Appendix A.

This paper presents an analysis of the GHG reduction potential for a NYS dairy manure management system that includes AD, post-digestion solid-liquid separation (SLS) and long-term manure storage of SLS liquid effluent. This system is representative of almost all of the 27 ADSs currently operating on-farm in NYS today.

METHODS

The mass of GHG emission reductions (i.e., the mass of carbon dioxide equivalents [MT CO2 eq.]) associated with AD (in this analysis, AD followed by SLS with liquid effluent stored long-term) located in New York State (NYS), was quantified and is discussed in this paper. The following protocols were used: IPCC (2006), AgSTAR (2011), and EPA (Federal Register, 2009) combined with reasonable input values that are representative of a farm’s baseline condition (long-term manure storage with no pre-treatment by ADS). The reductions quantified include: 1) the replacement of fossil fuel-based electrical energy by using AD produced biogas to operate an on-site engine-generator set, and 2) GHG emissions from CAFO required (for water quality purposes) long-term manure storages. The difference between the baseline condition and the conditions post-implementation of an ADS yields the farm’s net GHG emission associated with manure storage. To quantify the economic value! of the G HG emission reductions, the EPA social cost of carbon (SC-CO2) was used (EPA, 2016).

What did we do? *

PROCEDURE

The baseline condition is represented in Figure 1. Typical liquid/slurry long-term manure storages have manure that consists of urine plus feces, solid bedding and milking center washwater, added continuously as is produced on the farm. A natural crust may form as lighter organic material floats to the surface. The storages are constructed as a designed earthen storage with 2:1 side slopes or fabricated from concrete or steel. The fabricated structures have straight sides so less surface area is exposed. A few storages have a SLS prior to storage, while very few have a manure storage cover. Without a cover, they are exposed to rainfall from both annual precipitation and from extreme storms. To determine the baseline condition, storage with no SLS and with a natural crust was considered.

Figure 1. Baseline emissions from dairy farm with no renewable energy system (per cow, per year)

Figure 1. Baseline Emissions from Dairy Farm with No Renewable Energy System (Per cow per year)

Establish Long-Term Manure Storage Baseline Emissions

Part I – Estimating typical CH4 emissions from a long-term manure storage

An independent panel of experts agreed (USDA, 2014) that GHG emission reductions are best estimated using the Intergovernmental Panel on Climate Change (IPPC) Tier 2 method. For long-term manure storages, the daily methane emissions can be calculated by using Equation 1.

Equation 1. ECH4 = VS x Bo x 0.67 x (MCF/100)

where:

ECH4 = Mass of CH4 emissions (kg CH4/cow-day)

VS = Mass of volatile solids in manure going to storage (kg/cow-day)

Bo = Maximum volume of CH4 producing capacity for manure (m3 CH4/kg VS)

= 0.24 m3 CH4/kg VS (for dairy cow manure)

0.67 = Conversion factor for m3 CH4 to kg CH4

MCF = CH4 conversion factor for the manure management system

Yearly CH4 emissions (kg CH4/cow-yr.) can be estimated by summing the daily emissions (or multiplying an average representative daily emission by 365 days). The MCF is largely dependent on the temperature and the type of manure management system. The MCF will change throughout the year as the manure storage temperature changes. Using a summer ambient temperature representative of Upstate New York, of 18°C (64°F) and a winter ambient temperature of < 10°C (< 50°F), a farm can limit the amount stored and the time in storage during the warmer months to reduce the average yearly MCF. Different manure systems also have a different MCF based on the oxygen levels, interception of CH4 gases, and moisture content.

The two variables that can be controlled by the farm management are the VS loading per cow and the methane conversion factor (MCF). The VS loading rate can be reduced by any pre-manure storage treatment process that reduces the storage organic loading rate; fine tuning the diet to reduce VS in the manure and SLS are examples of two methods used to control the VS.

Typically in NYS, manure is stored both in the summer and winter in a liquid/slurry system with no natural crust. Using average typical winter and summer manure storage temperatures, average MCF values can be used in Equation 1 to estimate average methane emissions for these 6-month storage periods. The MCF values are shown in Table 1.

Table 1. Typical Long-Term Manure Storage Methane Conversion Factors for Storage Periods in NYS1

Storage Period

Winter

Summer

Average Manure Storage Temperature (°C)

<10

18

MCF

17

35

1These numbers are based on liquid/slurry storage without a natural crust cover.  (Source:  IPCC, 2006)

Using these MCF values shown in Table 1 and a per-cow VS excretion rate of 7.7 kg/cow-day (representative of high producing NY dairy cows – ASABE, 2006), manure storages could be estimated to produce 38 kg CH4/cow (for the winter storage period) and 79 kg CH4/cow (for the summer storage period) or an average of 4 metric tons (MT) of CO2 eq. per cow per year since 1 kg of CH4 = 34 kg CO2 eq.

Part II – Estimating typical N2O emissions from a long-term manure storage

There could be N2O emissions from a raw manure storage facility. The CO2 equivalent from N2O emissions can be estimated by using Equation 2.

Equation 2. CO2eq = 298 CO2/N2O GWP x EF3 x N x44 N2O/28 N2O-N

where:

CO2eq = Equivalent global warming potential expressed as carbon dioxide

298 CO2/N2O = GWP factor for N2O

EF3 = Emission Factor for N2O-N emissions from manure management

N = Mass of N excreted per cow per day = 0.45 kg/cow-day (ASAE, 2005)

Using an EF3 value of 0.005 (USEPA, 2009) for long-term storage of slurry manure with a crust and multiplying it by 0.45 kg of N/cow-day and by 365 days per year yields an additional 0.38 MT of CO2 eq. per cow per year from N2O emissions from a long-term manure storage facility.

Summary of long-term storage GHG emissions

Combining both the CO2 eq. per cow per year from CH4 emissions and the CO2 eq. per cow per year from N2O emissions from a manure storage facility provides a baseline emission of 4.38 MT of CO2 eq. per cow per year from the manure storage systems that the NYS CAFO permit requires. These emissions can be mitigated by implementing a renewable energy system including an ADS with SLS of the digestate before storage.

Establish GHG Emissions and Emission Reductions for an ADS

If a manure-based ADS was installed on a farm, it could reduce the GHG emissions from manure management as well as replace fossil fuel use or energy for both the farm and other users. By capturing the CH4 produced, and combusting it for energy or simply flaring the excess, CH4 releases are converted back to the neutral CO2 originally consumed by the animals in the form of feed products. The ADS could help to meet NYS renewable energy and GHG reduction goals, however, farms with an ADS would need to manage the system to minimize leaks. With no incentives to control leaks, the CH4 produced potentially could add to overall farm GHG emissions.

Part I – Estimating typical CH4 emissions and emission reductions

There are a number of factors that need to be taken into consideration when estimating the GHG reductions that an ADS will provide. Leaks in the ADS can be very detrimental as more methane is produced in an ADS than is emitted naturally from a manure storage facility in the baseline condition. In addition, there are uncombusted CH4 losses from flares and even some from the engine as well. Although every farm system is different, typical values can be determined from the literature, on-farm measurements, and experience.

ADSs designed and built to supply only the quantity of electricity consumed on-farm and to reduce odors may not be as effective as systems designed specifically to reduce GHG emissions. The conservative values in Table 2 could be used to describe these types of systems. ADSs built specifically to reduce GHG emissions in addition to maximizing the renewable energy produced would achieve significantly better GHG reductions. The optimum numbers are achievable, while the obtainable values are based on ADSs that consider GHG emissions and are built to optimize CH4 production.

Table 2. ADS variables that can be controlled by the system equipment, operation, and management

Conservative

Optimum

Obtainable

Reference

Leaks from system (% CH4)

10

0

1

AgSTAR (2011) and on-farm
Flare Efficiency (%)

90

99

95

AgSTAR (2011) and on-farm
Engine capacity factor (decimal)

0.85

0.97

0.95

On-farm measurements
Engine efficiency (%)

38

42

38

On-farm measurements
ADS Parasitic load

(kWh/cow-yr)

0.30

0.07

0.18

On-farm measurements
Biodegradability post-digestion (%)

70

50

60

On-farm measurements
VS left after SLS (%)

60

20

50

On-farm measurements

The additional societal benefit of this technology can be calculated using EPA’s SC-CO2 of $47.82 as the 2017-2019 average SC CO2 value per metric ton of C02 eq. (at a 3% discount rate) for the methane and nitrous oxide emissions (EPA, 2016).

Part II – Estimating typical N2O emissions and emission reductions for an ADS

An EF3 value of 0 (IPCC, 2006) for an uncovered liquid manure storage describes the typical emission factor from an ADS with SLS since post-digestion there would be no free oxygen, and after solids removal, there would not be a crust forming.

The resulting calculations from the conservative, optimum and obtainable ADS values are shown in Table 3. The fossil fuels avoided are based on the kilo-Watt hours (kWh) produced minus the parasitic load. The uncombusted CH4 from the engine is based on a rich burn engine. The CO2 equivalents from the system leaks and the digestate storage are the major emissions in the conservative scenario, the uncombusted emissions from the flare and the digestate storage are minor emissions from the optimum scenario, while storage contributes the most to the continuing emissions from the obtainable scenario.

Table 3. GHG Emissions from electric production converted with a $47.82 SC-CO2 into a value of E for conservative, optimum and obtainable ADS with solid separation of the digestate before storage.

Units Conservative Optimum Obtainable
Fossil Fuels Avoided
MT CO2 eq/cow-yr

0.70

1.16

0.99

Engine uncommuted CH4 MT CO2 eq/cow-yr

2.5 x 10-3

3.2 x 10-3

3.1 x 10-3

Flare uncommuted CH4 MT CO2 eq/cow-yr

0.19

0.00

0.03

System Leaks CH4 MT CO2 eq/cow-yr

1.41

0.00

0.14

Storage emissions CH4 MT CO2 eq/cow-yr

2.98

0.50

1.9

ƩCO2eq emitted – FF avoided MT CO2 eq/cow-yr

3.81

0.65

1.06

Baseline MT CO2 eq/cow-yr

4.38

4.38

4.38

Reduction in CO2eq MT CO2 eq/cow-yr

0.57

5.03

3.32

SC-CO2 Benefit $/cow-yr

$27

$240

$149

Gross Electricity produced kWh/cow-yr

1,590

2,229

1,955

Value of E $/kWh

0.017

0.11

0.081

Summary of long-term storage GHG emissions

The obtainable value of E $0.081/kWh, for an ADS with SLS of the digestate could be used to better determine the value of renewable energy in meeting NYS’s goals of reducing GHG emissions, increasing renewable energy, and supporting the dairy industry and the upstate NY economy.

More specific values for each individual ADS could be determined as a more granulated value (i.e., a value based on a more detailed/thorough analysis) through the implementation of NYS’s renewable energy vision. By using a value of E that reflects the actual environmental benefit of an ADS, this would incentivize dairy farms with an ADS to improve their CH4 production to produce more electrical energy. This would also increase the interest of more dairy farms in controlling GHG emissions and producing renewable energy by investing in ADS on their farms.

What have we learned?

ADSs can be used to reduce the manure management generated GHG emissions from dairy farms. With careful management, 3.32 MT of CO2 eq. per cow-year can be credited to the ADS. Using EPA’s SC-CO2 average price during 2017-2019 of $47.82, this could amount to a GHG benefit of over $140/cow-year. At this time, the benefit to society is unrewarded and high costs for ADSs both to construct and to operate, discourage farms from installing them. Working towards New York State’s renewable energy goals, as well as the reduction in GHG emission goals by compensating farms for the societal value of $0.081 per kWh of electricity produced from a well-run ADS would better incentivize farms to both install and operate ADSs to the advantage of the State.

Future Plans

DISCUSSION

ADSs can provide additional GHG reductions by utilizing organic wastes that currently go to landfills or aerobic waste treatment facilities. Some landfills may be able to capture a portion of the CH4 that the organic waste produces as renewable energy, but typically the leaks from a landfill gas recovery system are greater than those of farm-based ADS. NYS has some interest in diverting organic waste from landfills to reduce: the fill rate, the potential GHG emissions, and O&M costs in landfills. The value of the diverted organic waste can be best recovered by society if the energy is recovered through manure-based AD since the nutrients would also be recovered by mixing the food waste with manure, digesting it and recycling the nutrients in the effluent to the land for growing crops.

Nutrients to grow crops that are currently utilized in the form of commercial fertilizer, could be offset by the nutrients contained in a post-digested liquid, which would also reduce the energy and accompanying fossil fuel emissions now emitted when manufacturing commercial nutrients.

Aerobic treatment of organic wastes requires additional energy that adds to the fossil fuel-based carbon dioxide emissions and typically does not recover nutrients. While anaerobic digestion creates renewable energy and preserves nutrients.

Typical ADSs produce a large portion of energy from CH4 as waste heat from the engine(s). Operating a Combined Heat and Power (CHP) system in conjunction with an enterprise that would utilize the heat produced, would enable the system to harvest even more renewable energy.

ADSs could improve GHG mitigation efforts if the effluent storage was covered and if the gas collected was included in the biogas utilization system, eliminating any emissions from the effluent storage while producing even more renewable energy.

Farm Disadvantages

Managing a complex and expensive ADS requires dedication and a sophisticated management effort that clearly competes for time with other tasks on the farm. There is the potential to emit excess CH4 if: 1) leaks are not properly controlled, 2) the engine generator, boiler and/or flare are not efficient or 3) if the effluent storage continues to produce uncontained CH4. These can all be compounded if off-site organics are imported to the farm. The existing NYS net metering program makes the current price paid for exported electricity, very low. This reduces the motivation to produce and capture the maximum amount of CH4 from the ADS.

Planning and installing an on-farm ADS takes time to consider the benefits and costs so that a business decision can be reached. Capital costs of ADSs vary, but can range from $4,000 to $5,500 per kW of generation capacity. Operating costs have been estimated at $0.02 to $0.03 per kWh. Much of the capital investment is considered lost capital by lenders. The existing manure management system should be examined to determine any disadvantages from extra solids, contaminants, or dilution. If the successful operation of the ADS depends on tipping fees from imported organics, the reliability and quality of these sources needs to be determined. If electricity is to be sold, the utility should be consulted to determine how/if the distribution lines to the farm can handle what is expected to be generated.

Corresponding author, title, and affiliation

Peter Wright, Agricultural Engineer, Cornell University

Corresponding author email

cag26@cornell.edu

Other authors

Curt Gooch, Dairy Environmental Systems and Sustainability Engineer, Cornell University

Additional information

www.manuremanagement.cornell.edu

Talking Climate with Animal Agriculture Advisers


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Purpose             

The Animal Agriculture in a Changing Climate (AACC) project was established to leverage limited Extension expertise across the country in climate change mitigation and adaptation, with the goal of building capacity among Extension professionals and other livestock advisers to address climate change issues.

What did we do? 

The Animal Agriculture in a Changing Climate project team created a suite of educational programs and products to build capacity across the United States. Key products of the project:

  • Online courses: 363 participants registered with a 35% completion rate (Whitefield et al., JOE, 2016)
  • National and regional symposia and workshops: 11 face-to-face conferences with approximately 1,350 attendees.
  • Website: Over 5,900 users with over 21,100 total views. Project videos have received nearly 8,900 views.
  • Social media: AACC weekly blog (990 subscribers); daily Southeast Climate Blog (38,506 site visits); regional newsletters (627 subscribers); Facebook & Twitter (280 followers)
  • Ready-to-use videos, slide sets, and fact sheets
  • Educational programming: 390 presentations at local, regional, and international meetings
  • Collaboration with 14 related research and education projects

What have we learned? 

A survey was sent out to participants in any of the project efforts, in the third year of the project and again in year five. Overall, participants found the project resources valuable, particularly the project website, the online course, and regional meetings. We surveyed two key measures: abilities and motivations. Overall, 60% or more of respondents report being able or very able to address all eight capabilities after their participation in the AACC program. A sizeable increase in respondent motivation (motivated or very motivated) existed after participation in the program, particularly for helping producers take steps to address climate change, informing others about greenhouse gases emitted by agriculture, answering client questions, and adding new information to programs or curriculum.

The first challenge in building capacity in Extension professionals was finding key communication methods to engage them. Two key strategies identified were to: 1) start programming with a discussion of historical trends and agricultural impacts, as locally relevant as available, and 2) start the discussion around adaptation rather than mitigation. Seeing the changes that are already apparent in the climatic record and how agriculture has adapted in the past and is adapting to more recent weather variability and climatic changes often were excellent discussion starters.

Another challenge was that many were comfortable with the science, but were unsure how to effectively communicate that science with the sometimes controversial discussions that surround climate change. This prompted us to include climate science communication in most of the professional development opportunities, which were then consistently rated as one of the most valuable topics.

Future Plans    

The project funding ended on March 31, 2017. All project materials will continue to be available on the LPELC webpage.

Corresponding author, title, and affiliation        

Crystal Powers, Extension Engineer, University of Nebraska – Lincoln

Corresponding author email    

cpowers2@unl.edu

Other authors   

Rick Stowell, University of Nebraska – Lincoln

Additional information

lpelc.org/animal-agriculture-and-climate-change

Acknowledgements

Thank you to the project team:

Rick Stowell, Crystal Powers, and Jill Heemstra, University of Nebraska – Lincoln

Mark Risse, Pam Knox, and Gary Hawkins, University of Georgia

Larry Jacobson and David Schmidt, University of Minnesota

Saqib Mukhtar, University of Florida

David Smith, Texas A&M University

Joe Harrison and Liz Whitefield, Washington State University

Curt Gooch and Jennifer Pronto, Cornell University

This project was supported by Agricultural and Food Research Initiative Competitive Grant No. 2011-67003-30206 from the USDA National Institute of Food and Agriculture.

 

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2017. Title of presentation. Waste to Worth: Spreading Science and Solutions. Cary, NC. April 18-21, 2017. URL of this page. Accessed on: today’s date.

Adapting to Climate Change in the Pacific Northwest: Promoting Adaptation with Five-Minute Videos of Agricultural Water Conservation and Management Practices


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Purpose            

In a multimedia-based world, short videos are an effective visual means to provide information. A series of short (5-minute) climate change videos focusing on water conservation and efficiency were developed to connect innovative farming practices to other farmers, their advisers, consultants and the agricultural community.

What did we do? 

Profiled stories include: water-efficient measures, featuring ‘low irrigation spray application’ (LISA) irrigation and ‘low elevation precision application’ (LEPA) irrigation in Eastern Washington; a video focused on dry-land farming of vegetables and fruit in Oregon using regionally adapted long taproot varieties from California; and a video featuring an Eastern Washington dairy farm’s reactive adaptation management after 2015, preparing for future growing seasons with less water. In each of the short videos, farmers, their advisers, and university experts are interviewed to provide their perspectives, knowledge and economic information.

What have we learned?             

These videos are shared to highlight successful practices of conserving water while remaining profitable. Each video suggests evaluating a climate compatible management practice or crop variety on a part of a field, or when replacing outdated irrigation sprinklers and pumps.

Future Plans   

Future plans include regional promotion of these successful practices.

Corresponding author, title, and affiliation        

Elizabeth Whitefield, Research Associate, Washington State University

Corresponding author email    

e.whitefield@wsu.edu

Other authors   

Joe Harrison, Livestock Nutrient Management Extension Specialist, Washington State University

Additional information               

Please visit https://puyallup.wsu.edu/lnm/ to view the videos and to find more information.

Acknowledgements       

This effort was fully supported by Western Region Sustainable Agriculture and Research Education Program (EW15-012, Implications of Water Impacts from Climate Change: Preparing Agricultural Educators and Advisors in the Pacific Northwest)

Scenario Planning for the New York State Dairy Industry in a Changing Climate

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Purpose

Climate change is a slow and continual process that has been gradually changing our weather, and it will continue to occur. In order to adapt to such gradual changes, much foresight and planning is needed. The input-gathering process undertaken for this exercise was intended to compile information from stakeholders that was used to determine various scenarios of what future dairy production will look like, under specific climate change scenarios.

A survey of producers’ perspectives performed in 2014 yielded useful information regarding the beliefs of many New York State (NYS) dairy farmers. The survey showed that the majority of these farmers believe that they and their peers must adapt to climate changes they are currently facing, in the coming decades, in order to continue to grow and expand the industry in a sustainable manner. The scenario planning process will aid producers and their advisors in determining which adaptation strategies will be most effective to become more resilient to the climate changes that are projected in the near-term future for New York.

What did we do?

A Scenario Planning exercise was conducted throughout 2016 in preparation to help NYS producers imagine a future that involves the changes in climate that are projected over roughly the next 50 years. Scenario planning is a process that involves stakeholder input to develop multiple future scenarios based on a few key variables that will affect and change the way a system functions currently. It is a unique process in that it is not probability-based rather, it is based on the views of stakeholders and experts who choose the variables to be presented in a divergent fashion.

A workshop was held in July 2016 which gathered input from 12 stakeholders, and this input was then combined with current climate projections and other resources, to develop 8 comprehensive scenarios, 4 for the winter season and 4 for the growing season. The final scenarios are visual representations and are paired with qualitative narratives to explore the impacts of the divergent situations that are created. The final narratives provide a useful communications tool to share with farmers and other stakeholders, to explore the impacts of the climate variables involved.

Growing season scenarios 1Winter scenarios

What have we learned?

The exercise focused on temperature and precipitation changes for New York State, and the impacts to various aspects of the farmstead on a typical New York dairy farm. Scenarios were created for both winter and growing seasons, since the range of impacts is highly season dependent. The divergent scenarios created are presented in Figure 1 (growing season scenarios) and Figure 2 (winter season scenarios). Qualitative narratives were developed to describe in-depth the interactions that occur in each situation, for example, impacts to: the herd, the farmstead, manure management, farm economics, and finally with the farmer and personnel. Furthermore, once each situation is described fully, the next level of impact explores outside variables, for example, regional economic or political changes, population growth or social changes, or nation-wide or world-wide events that could have a significant impact on the specific farm situation presented.!

Future Plans

Next steps include identifying the best management strategies to handle the challenges presented in each resulting scenario. The final scenarios are presented in such a fashion that they will be useful tools to inform farm management, planning and decision making. The final scenarios can be used to examine how a certain set of management actions would perform under various future climatic conditions. “Robust” management actions need to be identified that would be the most highly effective under all scenarios considered, in other words, best management practices need to be identified that make the most sense to invest in, to be prepared for as many of the scenarios created as possible. In the same effort, it is important to identify management actions that are ineffective or that have little impact for a majority of the future scenarios developed. Pursuing actions that only work under a few of the projected scenarios is not in! line wit h smart planning to make the farm as resilient as possible. This preparation is a significant step towards helping farms be resilient in the face of unexpected future changes.

Corresponding author, title, and affiliation

Jennifer Pronto, Co-founder, BioProcess Analytics, LLC

Corresponding author email

jenny.pronto@gmail.com

Other authors

Curt Gooch, PE, Cornell University

Additional information

http://animalagclimatechange.org/

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2017. Title of presentation. Waste to Worth: Spreading Science and Solutions. Cary, NC. April 18-21, 2017. URL of this page. Accessed on: today’s date.