The final in a series of 3 webinars, this presentation focuses on producer perspectives of carbon markets for livestock operations. This presentation originally broadcast on January 20, 2023. Continue reading “Carbon Markets for Livestock Operations: Producer Perspectives”
Soil Carbon: How to change it and sell it
The second in a series of 3 webinars, this presentation focuses on soil carbon: how it can be changed and how to sell it. This presentation originally premiered on December 16, 2022. Continue reading “Soil Carbon: How to change it and sell it”
Carbon Markets for Livestock Operations: Manure Treatment and Handling
The first in a series of 3 webinars, this presentation introduces the fundamentals of carbon emissions, as well as technologies, practices and market opportunities available to agricultural producers are critical to that transition on the livestock operation. This presentation was originally broadcast on November 18, 2022. Continue reading “Carbon Markets for Livestock Operations: Manure Treatment and Handling”
Assessment of method of photo analysis for demonstrating soil quality
Purpose
The use of livestock manure as a soil amendment to benefit soil health by improvements to soil physical, chemical, and biological properties, has been documented. However, quantification of the impact of improved soil health metrics on nutrient cycling has lagged. The soil your undies experiment has been implemented in the past to visually demonstrate microbial activity (Figure 1). However, this demonstration is seldom quantified, and does not have the capacity to statistically show that the effects of different management practices are distinct. The goal for this study was to quantify the degradation of fabric on a similar experiment, using cotton fabric on agricultural soils through photographic editing software. This study was designed to assess a visual method for quantifying carbon cycling in soil, observed through the degradation of buried organic materials.
What Did We Do?
White, 100% cotton fabric cloths were cut into 29.21 × 29.84 cm (871.62 cm2) (11.5 x 11.75 in, 135 in2) pieces and placed flat inside a non-degradable mesh bag (48 cm × 48 cm, 18.9 in x 18.9 in). Sixty of the mesh bags were buried at 5 cm (2 in) depth in a field planted with corn in May of 2021 (Figure 2). The sixty bags were arranged in 12 plots to which one of three soil treatments (swine slurry, swine slurry + woodchips, and control plots with no amendments) with four replications per treatment were also applied. Swine slurry was applied at a rate of 39,687.06 L-ha-1 (4,242 gal-ac-1) and woody biomass was applied at a rate of 21.52 Mg-ha-1 (9.6 tons-ac-1).
Five times during the growing season (25, 54, 81, 99 and 128 days after establishment), one bag was retrieved from each plot and returned to the lab for analysis. For each bag, soil was gently removed from the surface of the mesh and then the bag was cut open to observe the cotton fabric remaining. All the fabric pieces were photographed after retrieval. Photographs of the fabric were taken with an iPad mounted on a tripod. Fabric samples were photographed in a premeasured area of 29.21 × 29.84 cm (11.5 x 11.75 in) on a black surface (Figure 3).
Manual evaluation of percent fabric degradation for each sample was performed by overlaying a clear plastic grid (Figure 4) with primary graduations (darker lines) of 2.54 cm (1 in) and secondary graduations (lighter lines) of 6.4 mm (0.25 in) on fabric samples and counting grid squares that were void of fabric.
Each photograph was assessed using Adobe Photoshop 2020 and the free license program ImageJ. Briefly, each image was opened in the respective program and the initial fabric area (871.62 cm2) (135 in2) was delineated in the program, based on the premeasured area included in the photo to set a scale for the degradation measurement. The image was converted to black and white, and brightness and contrast were adjusted as needed to remove glare on the black background that might be misread by the program as fabric. Then, all the pixels within a specific color range – which was previously defined as fabric – were selected using the native editing tools in the two programs and this area was compared to the pixels in the initial fabric area to determine the percentage of fabric remaining.
What Have We Learned?
The three methods for estimating the area of the fabric did not show significant differences among each other, which means estimates of fabric degradation obtained with Photoshop and Image J accurately reflect manual hand counts, suggesting that these are reliable visual methods for determining the area of the remaining area of fabric (Figure 5, 6).
Future Plans
Future work will seek to validate this method according to standard measures of soil health and biological activity and ensure that the method has enough sensitivity to demonstrate statistical differences between soil treatments. Future studies should also focus on making the process of area estimation with the software an easier, less laborious process. Creating a cellphone app to determine degradation quickly and without the need for a computer could increase the adoption of the fabric degradation assessment method in field settings.
Authors
Amy Schmidt, Associate Professor, University of Nebraska-Lincoln
Corresponding author email address
Additional authors
Karla Melgar Velis, Graduate Research Assistant, University of Nebraska-Lincoln
Mara Zelt, Research Technologist, University of Nebraska-Lincoln
Andrew Ortiz Balsero, Undergraduate Research Assistant, University of Nebraska-Lincoln
Acknowledgements
Funding for this study was provided by the Nebraska Environmental Trust and Water for Food Global Institute at the University of Nebraska-Lincoln. Much gratitude is extended to collaborating members of the On-Farm Research Network, Nebraska Natural Resource Districts, Nebraska Extension Agents and Michael Hodges and family for providing the land, manure, and effort for this research project. Much appreciation to members of the Schmidt Lab who supported field and laboratory work: Juan Carlos Ramos Tanchez, Nancy Sibo, Andrew Lutt, Seth Caines and Jacob Stover.
Predicting Manure Nitrogen and Phosphorus Characteristics of Beef Open Lot Systems
This project involves the analysis of a new data set for manure characteristics from open lot beef systems demonstrating both average characteristics and factors contribution to variability in manure characteristics among these systems. Defining the characteristics and quantities of harvested manure and runoff from open earthen lot animal systems is critical to planning storage requirements, land requirements for nutrient utilization, land application rates, and logistical issues, such as equipment and labor requirements. Accuracy of these estimates are critical to planning processes required by federal and state permitting programs. Poor estimates can lead to discharges that result in court action and fines, neighbor nuisance complaints, and surface and ground water degradation. Planning procedures have historically relied upon standard values published by NRCS (Stettler et al., 2008), MWPS (Lorimor et al., 2000), and ASABE (2014) for average characteristics.
What Did We Do?
A large data set of analyses from manure samples collected over a 15-year period from 444 independent cattle feedlot pens at a single eastern Nebraska research facility was reviewed to provide insight to the degree of variability in observed manure characteristics and to investigate the factors influencing this variability. No previous efforts to define these characteristics have included data gathered over such a wide range of dietary strategies and weather conditions. This exclusive research data set is expected to provide new insights regarding influential factors affecting characteristics of manure and runoff harvested from open lot beef systems. The objective of this paper is to share a preliminary summary of findings based upon a review of this data set.
What Have We Learned?
A review of this unique data set reveals several important preliminary observations. Standard values reported by ASABE and MWPS for beef manure characteristics in open lot systems are relatively poor indicators of the significant variability that is observed within open lot feeding systems. Our data set reveals significant differences between manure characteristics as a function of feeding period (Table 1) and substantial variability within feeding period, as illustrated by the large coefficients of variation for individual characteristics. Differences in winter and summer conditions influence the characteristics and quantities of solids, organic matter, and nutrients in the harvested manure. The timing of the feeding period has substantial influence on observed differences in nitrogen loss and nitrogen in manure (Figure 1). Nitrogen recovery for the warmer summer feeding periods averaged 51 and 6 grams/head/day in the manure and runoff, respectively, with losses estimated to be 155 grams/head/day. Similarly, nitrogen recovery in manure and runoff for the winter feeding period was 90 and 4 grams/head/day, respectively, with losses estimated at 92 grams/head/day (Figure 1 and Koelsch, et al., 2018). In addition, differences in weather and pen conditions during and following winter and summer feeding periods impact manure moisture content and the mixing of inorganics with manure (Table 1).
| Table 1. Characteristics of manure collected from 216 and 228 cattle feedlot pens during Summer and Winter feeding periods, respectively1. | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| University of Nebraska Feedlot in East Central Nebraska | Standard Values | |||||||||
| Summer | Winter | ASABE | NRCS | MWPS3 | ||||||
| Mean | CV2 | Mean | CV2 | Mean | Mean | |||||
| Total Manure (wet basis), kg/hd/d | 9.3 | 99% | 13.1 | 43% | 7.5 | 7.9 | ||||
| DM % | 71% | 10% | 63.2% | 15% | 67% | Collected | 55% | |||
| kg/hd/d | 5.4 | 80% | 8.0 | 41% | 5.0 | manure | 4.3 | |||
| OM % | 24% | 28% | 25.3% | 41% | 30% | is not | 50% | |||
| kg/hd/d | 1.00 | 52% | 1.87 | 41% | 1.5 | reported. | 2.2 | |||
| Ash % | 76% | 9% | 74.7% | 14% | 70% | 50% | ||||
| kg/hd/d | 4.16 | 72% | 6.10 | 49% | 3.5 | 2.2 | ||||
| N % | 1.3% | 36% | 1.19% | 23% | 1.18% | 1.2% | ||||
| g/hd/d | 51 | 50% | 90 | 33% | 88 | 95 | ||||
| P % | 0.37% | 41% | 0.34% | 29% | 0.50% | 0.35% | ||||
| k/hd/d | 17.7 | 55% | 26.0 | 42% | 37.5 | 27.7 | ||||
| DM = dry matter; OM = organic matter (or volatile solids)
1 Summer = April to October feeding period, Winter = November to May feeding period 2 Coefficient of variation, % 3 Unsurfaced lot in dry climate with annual manure removal. |
||||||||||
Dietary concentration of nutrients was observed to influence the harvested manure P content (Figure 2) but produce minimal impact on harvested manure N content (not shown). Diet was an important predictor in observed N losses, especially during the summer feeding period. However, its limited value for predicting harvested manure N and moderate value for predicting harvesting manure P suggests that other factors such as weather and management may be influential in determining N and P recovered (Koelsch, et al., 2018).
Significant variability exists in the quantity of total solids of manure harvested with a factor of 10 difference between the observed low and high values when compared on a mass per finished head basis (note large CVs in Table 1). This variability has significant influence on quality of the manure collected as represented by organic matter, ash content, and moisture content.
Although individual experimental trials comparing practices to increase organic matter on the feedlot surface have demonstrated some benefit to reducing nitrogen losses, the overall data set does not demonstrate value from higher pen surface organic matter for conservation of N in the manure (Koelsch, et al., 2018). However, higher organic matter manure is correlated to improved nitrogen concentration in the manure suggesting a higher value for the manure (Figure 3).
It is typically recommended that manure management planning should be based upon unique analysis for manure characteristics representative of the manure being applied. The large variability in harvested manure from open lot beef systems observed in this study further confirms the importance of this recommendation. The influence of weather on the manure and the management challenges of collecting manure from these systems adds to the complexity of predicting manure characteristics. In addition, standard reporting methods such as ASABE should consider reporting of separate standard values based upon time of the year feeding and/or manure collection period. This review of beef manure characteristics over a 15 year period further documents the challenge of planning based upon typical or standard value for open lot beef manure.
Future Plans
The compilation and analysis of the manure and runoff data from these 444 independent measure of feedlot manure characteristics is a part of an undergraduate student research experience. Final review and analysis of this data will be completed by summer 2019 with the data published at a later time. The authors will explore the value of this data for adjusting beef manure characteristics for ASABE’s Standard (ASABE, 2014).
References
ASABE. 2014. ASAE D384.2 MAR2005 (R2014): Manure Production and Characteristics. ASABE, St. Joseph, Ml. 32 pages.
Lorimor, J., W. Powers, and A. Sutton. 2000. Manure characteristics. Manure Management Systems Series MWPS-18. Midwest Plan Service. Ames Iowa: Iowa State University.
Stettler, D., C. Zuller, D. Hickman. 2008. Agricultural Waste Characteristics. Chapter 4 of Part 651, NRCS Agricultural Waste Management Field Handbook. pages 4-1 to 4-32.
Authors
Richard (Rick) Koelsch, Professor of Biological Systems Engineering and Animal Science, University of Nebraska-Lincoln
rkoelsch1@unl.edu
Megan Homolka, student, and Galen Erickson Professor of Animal Science, University of Nebraska-Lincoln
Additional Information
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.
The Use of USDA-NRCS Conservation Innovation Grants to Advance Air Quality Improvements
USDA-NRCS has nearly fifteen years of Conservation Innovation Grant project experience, and several of these projects have provided a means to learn more about various techniques for addressing air emissions from animal agriculture. The overall goal of the Conservation Innovation Grant program is to provide an avenue for the on-farm demonstration of tools and technologies that have shown promise in a research setting and to further determine the parameters that may enable these promising tools and technologies to be implemented on-farm through USDA-NRCS conservation programs.
What Did We Do?
Several queries for both National Competition and State Competition projects in the USDA-NRCS Conservation Innovation Grant Project Search Tool (https://www.nrcs.usda.gov/wps/portal/nrcs/ciglanding/national/programs/financial/cig/cigsearch/) were conducted using the General Text Search feature for keywords such as “air”, “ammonia”, “animal”, “beef”, “carbon”, “dairy”, “digester”, “digestion”, “livestock”, “manure”, “poultry”, and “swine” in order to try and capture all of the animal air quality-related Conservation Innovation Grant projects. This approach obviously identified many projects that might be related to one or more of the search words, but were not directly related to animal air quality. Further manual review of the identified projects was conducted to identify those that specifically had some association with animal air quality.
What Have We Learned?
Out of nearly 1,300 total Conservation Innovation Grant projects, just under 50 were identified as having a direct relevance to animal air quality in some way. These projects represent a USDA-NRCS investment of just under $20 million. Because each project required at least a 50% match by the grantee, the USDA-NRCS Conservation Innovation Grant program has represented a total investment of approximately $40 million over the past 15 years in demonstrating tools and technologies for addressing air emissions from animal agriculture.
The technologies that have been attempted to be demonstrated in the animal air quality-related Conservation Innovation Grant projects have included various feed management strategies, approaches for reducing emissions from animal pens and housing, and an approach to mortality management. However, the vast majority of animal air quality-related Conservation Innovation Grant projects have focused on air emissions from manure management – primarily looking at anaerobic digestion technologies – and land application of manure. Two projects also developed and enhanced an online tool for assessing livestock and poultry operations for opportunities to address various air emissions.
Future Plans
The 2018 Farm Bill re-authorized the Conservation Innovation Grant Program through 2023 at $25 million per year and allows for on-farm conservation innovation trials. It is anticipated that additional air quality projects will be funded under the current Farm Bill authorization.
Authors
Greg Zwicke, Air Quality Engineer, USDA-NRCS National Air Quality and Atmospheric Change Technology Development Team
greg.zwicke@ftc.usda.gov
Additional Information
More information about the USDA-NRCS Conservation Innovation Grants program is available on the Conservation Innovation Grants website (https://www.nrcs.usda.gov/wps/portal/nrcs/main/national/programs/financial/cig/), including application information and materials, resources for grantees, success stories, and a project search tool.
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.
Analysis of total Carbon, Nitrogen, and Phosphorus Contents in Soil Cores Over 10+ Years from Horicon Marsh in Dodge County, Wisconsin
Why Look at Marsh Soil Nutrients?
The purpose of this project was to evaluate changes in carbon (C), nitrogen (N), and phosphorus (P) in samples from identical locations taken ten years apart from Horicon Marsh in Dodge County, Wisconsin.
The area surrounding the marsh is primarily agricultural and has the potential to contribute nutrients to the marsh, affecting the fertility of the soils and changing the ecosystem.
What did we do?
We hypothesized that carbon, nitrogen, and phosphorus would show significant increases over the ten-year interval between samplings.
Sample sites were positioned every ¼ mile along east-west transects throughout the marsh. A soil core was obtained at each sample site in the winter of either 2002 or 2003. The same sites were revisited and new samples collected in winter of either 2012 or 2013, ten years after the initial visits. The top five centimeters of each soil core were oven dried at 105°C for 72 hours.
Total carbon and nitrogen were analyzed by combustion using a PerkinElmer 2400 series II CHNS/O Analyzer. Total phosphorus was analyzed by the Olsen P-extraction method on a QuikChem FIA+ 8000 series Lachat analyzer.
A paired t-test (α=0.05) was used to compare nitrogen and phosphorus values. Carbon data were compared with a Mann-Whitney ranked sum test at the 95% confidence interval.
What have we learned?
Carbon and nitrogen did not increase significantly over the time period. Carbon is generally bound in soil organic matter; in histic wetland soils, changes attributable to land use might be difficult to detect due to the already high organic matter content. Nitrogen accumulation was likely mitigated by denitrification processes.
Phosphorus concentrations were greater in the second set of samples. Phosphorus adsorbs tightly to sediment and organic material, which would prevent its removal by flowing water. Changes in land use, especially row crop agriculture in the Horicon marsh area, could contribute runoff inputs of soil particles carrying phosphorus with them. This may explain significantly increased phosphorus levels between the start and end of the study period.
Future Plans
Future studies might quantify land use changes, their extent, and their impacts on the marsh ecosystem; analyze spatial patterns of phosphorus accretion to determine if it is cycling equally throughout the marsh; and determine the impact of denitrifying bacteria and anaerobic conditions on nitrogen accumulation. Additional research could include testing the water column of the marsh for dissolved nutrients; and sampling the Rock River at its inlet to and outlet from the Horicon Marsh to determine nutrient flux to the stream from the marsh.
Authors
Ashley Hansen, University of Wisconsin-Stevens Point ashleyhansen891@gmail.com
Anna Radke, University of Wisconsin-Stevens Point; Sarah Shawver, University of Wisconsin-Stevens Point
Additional information
Ashley Hansen, ahans891@uwsp.edu; Anna Radke, aradk591@uwsp.edu; Sarah Shawver, sshaw497@uwsp.edu
Acknowledgements
Dr. Robert Michitsch
Soils Professor and Research Advisor
Dr. Kyle Herrman
Water Resource Professor and Research Advisor
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. 2015. Title of presentation. Waste to Worth: Spreading Science and Solutions. Seattle, WA. March 31-April 3, 2015. URL of this page. Accessed on: today’s date.
Western Region Animal Agriculture and a Changing Climate
Western Region Animal Agriculture and a Changing Climate Extension Project
Our overall goal is for Extension—working with partner organizations—to effectively inform and influence livestock and poultry producers and consumers of animal products in all regions of the U.S. to foster production practices that are environmentally sound, climatically compatible, and economically viable.
Western Region Website-AACC
Farm Management Decision Aid Tools
Western Region Website-AACC
Farm Management Decision Aid Tools
Integrated Farm System Model (IFSM) and Dairy Gas Emissions Model (DairyGEM) – training presentation by Al Rotz.
Education received through either of these comprehensive model evaluations will lead to the development of more sustainable dairy and beef production systems.
The IFSM (Integrated Farm System Model) is a tool for evaluating environmental and economic effects of different farm management scenarios. The user enters information on cropping practices, facilities, equipment, the herd and other farm parameters. Sample farms of various sizes and types are provided with the model software to provide a starting point. Information generated by the model includes crop yields, feed production and use, animal production, manure handled, production costs and net return to management. The model’s environmental outputs include average annual soil balances of N, P, K and C, erosion of sediment, P runoff, nitrate leaching, emissions of ammonia, hydrogen sulfide and greenhouse gases, and the carbon footprint of the feed, animal weight or milk produced.
The Dairy Gas Emission Model (DairyGEM) is an educational tool that predicts ammonia and hydrogen sulfide volatilization, GHG emissions, and the carbon footprint of the milk produced. DairyGEM is used to study the interacting effects of management changes on major emission sources from feed production to the return of manure back to the land.
To download software and for more information about IFSM, please visit: http://www.ars.usda.gov/Main/docs.htm?docid=8519
To download software and for more information about DairyGEM, please visit: http://www.ars.usda.gov/Main/docs.htm?docid=21345
About the Presenter:
Dr. Al Rotz is an agricultural engineer at the USDA-ARS Pasture Systems and Watershed Management Research Unit in University Park, PA. His work focuses on the development and use of models to evaluate the performance, environmental impact and economics of alternative technologies and management strategies applied to integrated farming systems for dairy or beef production.
IFSM and DairyGEM Tool Training Presentation
(If one of the video windows is blank, please refresh the page.)
If you are interested in specific segments of the entire video tool training above for either IFSM or DairyGEM, please refer to the separate video segments below.
SEGMENT 1:
Introduction to both the Integrated Farm System Model (IFSM) and Dairy Gas Emissions Model (DairyGEM)
SEGMENT 2:
IFSM tool training (using dairy as an example)
**IMPORTANT Note: this segment also supports the use of DairyGEM
SEGMENT 3:
IFSM beef example and dairy example
SEGMENT 4:
DairyGEM Tool Training
***Note: for further instruction related to DairyGEM use, please refer to Segment 2
DeNitrification-DeComposition (DNDC) Model
DNDC (i.e., DeNitrification-DeComposition) is a computer simulation model of carbon and nitrogen biogeochemistry in agro-ecosystems. The model can be used for predicting crop growth, soil temperature and moisture regimes, soil carbon dynamics, nitrogen leaching, and emissions of trace gases including nitrous oxide (N2O), nitric oxide (NO), dinitrogen (N2), ammonia (NH3), methane (CH4) and carbon dioxide (CO2). In order to download the DNDC model files you will need to register and provide a valid email, as well as your affiliation and intended use. After registration and confirming your email you will be able to download the files from the DNDC Model Download page.
On the Download page, you will find 3 simulation models of interest.
The DNDC model – A computer simulation model for predicting crop yield, soil carbon sequestration, nitrogen leaching, and trace gas emissions in agro-ecosystems.
The Manure -DNDC Model- Ac computer simulation for predicting GHG and NH3 emissions from manure systems.
US Cropland GHG Calculator- A decision support system for quantifying impacts of management alternatives on GHG emissions from Agro-ecosystems in the U.S.
Manure and Nutrient Reduction Estimator Tool (MANURE Tool)
The MANURE Tool provides a system to quantify methane and and other GHG emission reductions and the environmental benefits of renewable energy produced by digesters at dairy and swine operations. The tool is based upon a full and accurate assessment of baseline conditions at the animal feed operation, which is a key element of the emission reduction calculation. This tool can be used to assess the quantity of emission reductions associated with implementation of specific technologies and/or practices. More information about the tool can be found on the Manure and Nutrient Reduction Estimator site.
COMET-FARM
The COMET-FARM tool is a whole farm and ranch carbon and GHG accounting and reporting system. It is intended to help users account for the carbon flux and GHG emissions related to their farm and ranch management activities, and help them explore the impacts to emissions of alternative management scenarios. The tool guides the user through describing the farm/ranch’s management practices including alternative future management scenarios. Once complete, a report is generated comparing the carbon changes and GHG emissions between current management practices and future scenarios. More information about COMET FARM can be found on the COMET-FARM site.
Farm Smart
Farm Smart is designed to give producers the ability to access and mitigate their environmental profile, track and measure their progress, plan for future improvements and report outcomes of practice changes to customers, community members, regulators and other stakeholders. The system features 3 tools: the Farm Smart Environmental Calculator, the Farm Smart Farm Energy Efficiency tool, and the Farm Smart Decision Support tool. Go to the Farm Smart site to download these tools and for more information.
Webcast Presentations
Fact Sheets
Regional Information
United States Global Change Research Program (USGCRP) Information:
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Newsletters
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Archived Past E-Newsletters
November 22, 2013 E-newsletter
September 20, 2013 E-newsletter
September 13, 2013 E-newlsetter
Animal Ag Climate Change Newsletter Vol. 1, March 2012 (this may take a minute or so to load)
This online course is free and was developed to answer questions that the livestock and animal agriculture industry is facing related to climate. Nationwide, producers and stakeholders are asking questions about climate change: Is it happening? Are unusual weather patterns and events becoming more frequent? Should we be planning and managing for the future? Where can we get un-biased information that serves the livestock and ag community?
This online course will provide valuable information from which to feel confident in answering these frequent questions. Also, the online platform eliminates the extra travel expense for professional development.
Students that take this course will learn about the areas of climate and weather trends, impacts, adaptation, mitigation, policy, climate science and effective communication. Upon completion, they can receive CEUs from multiple professional societies.
Or please contact Liz Whitefield at e.whitefield@wsu.edu if you have any questions.
Brochures/Conference Visuals
Brochure: Animal Agriculture and Climate Change (this may take a minute or so to load)