Source: CORNELL UNIVERSITY submitted to
PROVIDING NEW YORK VEGETABLE, FRUIT AND DAIRY FARMERS WITH GREENHOUSE GAS AND CARBON MANAGEMENT TOOLS
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
COMPLETE
Funding Source
HATCH
Reporting Frequency
Annual
Accession No.
0223972
Grant No.
(N/A)
Cumulative Award Amt.
(N/A)
Proposal No.
(N/A)
Multistate No.
(N/A)
Project Start Date
Oct 1, 2010
Project End Date
Sep 30, 2013
Grant Year
(N/A)
Program Code
[(N/A)]- (N/A)
Recipient Organization
CORNELL UNIVERSITY
(N/A)
ITHACA,NY 14853
Performing Department
Horticulture
Non Technical Summary
Many best management practices (BMPs) for agricultural greenhouse gas (GHG) mitigation and soil carbon sequestration could increase farmer profits if properly implemented, could lead to a new source of revenues if carbon markets develop, and have environmental, food safety, and sustainability co-benefits. However, most information currently available was developed for major world food crops and will require modification for relevance to New York's important vegetable, fruit, and dairy production systems. Preparing for climate change and new energy and climate change policies will require new tools for quantifying potential benefits of BMPs in relation to costs and risks on individual farms. We propose a comprehensive research and education outreach effort focused on vegetable, fruit crop and dairy industries of New York that will provide: (1) BMP fact sheets for GHG mitigation and soil carbon sequestration; (2) reliable low-cost guidelines for monitoring and verification of soil carbon stocks; (3) interactive web-based GHG and carbon auditing tools for use by farmers and Extension educators; and (4) a state-wide analysis to identify key opportunities for agricultural GHG mitigation and carbon sequestration. Our BMP fact sheets (Obj 1) will be derived after compiling, evaluating, and prioritizing existing relevant information from the scientific literature, credible websites, databases and other sources. A small expert-panel focus group of faculty, Extension staff and farmers in each commodity area will contribute to this effort. To develop new approaches to low-cost soil carbon assessment (Obj 2) we will intensively sample vegetable, fruit crop and dairy field sites and use these "maximal" data sets to develop statistical models to predict soil carbon at points and depths in the landscape not measured, and thus reduce total samples required for future sampling. We will also develop guidelines on how to use USDA soil survey, land use, crop management, and remote sensed data to prioritize and strategically choose sampling sites. We will evaluate existing and emerging generic GHG accounting tools (Obj 3) for their reliability and ease of use, and modify or redesign them for application to New York production systems. This will be an iterative process and will integrate results from Objectives 1 and 2, and other on-going research. We will use our focus groups for feedback on the web-based tools. We will use geospatial data on soil characteristics, land use, cropping history, and management, and GHG and soil carbon accounting and management tools to identify key opportunities for mitigation and soil carbon sequestration within the state (Obj 4). Ultimately, our project will provide vegetable, fruit and dairy farmers in New York and the region with new GHG and carbon management tools that will leave them better prepared for emerging energy and climate change policies, including the possibility of carbon offset payments for carbon markets. State policy-makers will have better information on the potential for mitigation and carbon sequestration across commodity areas and regions.
Animal Health Component
(N/A)
Research Effort Categories
Basic
(N/A)
Applied
(N/A)
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
2050110107010%
2050110310010%
2050430107010%
2050430310010%
2051119107010%
2051119310010%
2051499107010%
2051499310010%
2053499107010%
2053499310010%
Knowledge Area
205 - Plant Management Systems;

Subject Of Investigation
1119 - Deciduous tree fruits, general/other; 1499 - Vegetables, general/other; 3499 - Dairy cattle, general/other; 0110 - Soil; 0430 - Climate;

Field Of Science
1070 - Ecology; 3100 - Management;
Goals / Objectives
The overarching goal of this project is to promote agricultural energy efficiency, mitigation of greenhouse gas (GHG) emissions and soil carbon sequestration. We will provide vegetable, fruit and dairy farmers in New York and the region with new GHG and carbon management tools that will leave them better prepared for emerging energy and climate change policies, including the possibility of carbon offset payments for carbon markets. State policy-makers will have better information on the potential for mitigation and carbon sequestration across commodity areas and regions. Our specific objectives are: (1) Best management practice (BMP) fact sheets for GHG mitigation and soil carbon sequestration; (2) reliable low-cost guidelines for monitoring and verification of soil carbon stocks; (3) interactive web-based GHG auditing tools; and (4) a state-wide analysis to identify key opportunities for agricultural GHG mitigation and carbon sequestration. By the final, year 3, of the project we will: -finalize, publish, and make available on the web BMP fact sheets for GHG mitigation for vegetable and fruit crop and dairy production systems; -finalize, publish and make available on the web guidelines for low-cost soil strategic sampling and analysis for soil carbon assessment; -finalize and conduct workshops for a new interactive website with GHG and soil C accounting and management tools for vegetable, fruit, and dairy farmers; -use results from regional geospatial analyses, and results from project objectives, particularly the GHG accounting tools, to identify key opportunities for NY agriculture to mitigate GHG emissions and increase soil carbon sequestration; -submit peer-reviewed papers from the project; and expand dissemination of results and outreach to farmers, extension educators, scientists, policy-makers, etc.
Project Methods
Objective 1- BMP fact sheets: We will first compile, evaluate, and prioritize existing, credible, and relevant information from the peer-reviewed literature, technical reports, websites, existing databases, and other sources. Our BMP fact sheets will include approaches to: reduce emissions (e.g., better manure management, improved nitrogen use efficiency); enhance carbon sequestration (e.g., reduced tillage, better woodlot management); and avoid or displace emissions (e.g. using crop or manure bioenergy sources).We will identify a small focus group (e.g. 5 - 10 individuals) of faculty, Extension staff and growers in each commodity area to provide input and feedback as we develop and finalize BMP fact sheets for dissemination. Objective 2- Low-cost approaches for soil carbon assessment: We will identify several vegetable, fruit crop and dairy field sites for intensive soil sampling each year, including Cornell field research facilities and commercial farms. USDA soil survey, land use, crop management, and remote sensed data will be used to create geographic information system (GIS) maps to prioritize and strategically choose sampling sites. Soil samples will in general be collected to a 60 cm depth in 20-cm increments and samples measured for: total carbon and nitrogen (Leco combustion analyzer, St. Joseph, MI), active carbon (permanganate oxidation, Weil et al. 2003), soil organic carbon by loss-on-ignition (LOI), and visible and near infrared reflectance (VNIR) spectrometry (ASD FieldSpec Pro, Boulder, CO). We have budgeted for 175 cores (525 samples) in years 1 and 2, and 50 cores (150 samples) in year 3. Adjacent undisturbed cores will be collected for bulk density determination (to convert carbon concentration to carbon per acre). A nested sampling design will be used to characterize field variability. Intensive sampling at some sites (10 to 15 cores per acre) will provide a "maximal" data set to develop various geospatial statistical modeling approaches to predict soil carbon at points and depths in the landscape not measured, and thus reduce total samples required. Objective 3- Develop web-based GHG accounting tools: We will evaluate existing and emerging generic on-line farm GHG accounting tools, such as COMET-Farm, derived from COMET-VR, and the USDA Dairy Greenhouse Gas Model for their reliability and ease of use, and modify or redesign them for application to New York production systems. This will be an iterative process that also will integrate new information and data gained from Objectives 1 and 2, communication with developers of COMET-Farm, and Cornell researchers. We will use our focus groups for feedback on the web-based tools. Objective 4- Identify key opportunities for mitigation and soil carbon sequestration in NY: We will use geospatial data on soil characteristics, land use, cropping history, and management, and GHG and soil carbon accounting and management tools to identify cost-effective mitigation approaches within each commodity area. On-going research at Cornell on carbon economics and policy (A. Bento, collaborator) will be utilized for our analysis.

Progress 10/01/10 to 09/30/13

Outputs
Target Audience: New York vegetable, fruit and field crop and dairy farmers will be better educated and better informed regarding best management practices (BMPs) for energy efficiency, greenhouse gas (GHG) mitigation, and soil carbon (C) sequestration as a result of the project. These farmers will be better prepared for, and more resilient to, fluctuating energy prices and new energy and climate change regulations or incentives, including the possibility of C offset payments through emerging C markets. The results of this project feed directly into Cornell Cooperative Extension Program Work Team efforts on energy conservation and climate change. Results are also relevant to NYS Agriculture and Markets and NYSERDA interests in agricultural energy efficiency, mitigation, and the potential of C markets for farmers. This project addresses interests of the American Farm Bureau Federation (AFBF). New York State will be better poised to develop a state-wide plan for GHG mitigation within the agriculture sector and have better information on existing inventories and databases for state planning. The entire Northeast region will benefit from our educational outreach on this topic. Our results provide an important contribution to advancing the science and methodology for low-cost soil C assessments, which could influence national and international standards for agriculture, forestry and other land uses in the C economy. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Two recently completed M.S. theses (Sam Bosco, Sonam Sherpa, see Publications) were closely linked with the soil C assessment goal, although funded separately. The lab manager partially funded through this project, Jeff Beem-Miller, has gained considerable experience in soil analyses and statistical procedures as part of this project, and has recently submitted applications to graduate programs in soil and environmental science at UC Berkeley, UC Davis, Michigan State, Colorado State, and several other universities. Over the course of the project four undergraduates have worked with our group and gained experience in field and lab methods, GIS mapping, and other skills. How have the results been disseminated to communities of interest? During the course of this project 2 M.S. Theses, 4 peer-reviewed journal articles, 4 book chapters, 4 abstracts for scientific conferences, 2 technical reports, and 7 extension and popular press articles associated with the project have been published. One other journal publication and one other extension fact sheet are in preparation. In addition, Wolfe has given over 30 presentations related to the project, and van Es and his group have given a similar number of presentations related to the Adapt-N web tool in particular. The extension materials, video of some of the presentations, and other outputs from the project have reached a broader audience through our www.climatechange.cornell.edu website. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Obj (1): A detailed list of BMPs were developed for improving farm energy efficiency and reducing carbon dioxide (CO2) emissions through: building and equipment design and maintenance; crop rotations and management; and soil management for increasing soil C sequestration. BMPs were also developed for reducing farm nitrous oxide (N2O) emissions through: use of green manure (legume) rotation crops; winter cover crops to retain soil nitrogen (N) within the root zone; and optimized quantity, placement, and timing of N fertilizers using soil tests and new web tools such as Cornell’s real-time-weather-based Adapt-N program (http://adapt-n-cals.cornell.edu). The Adapt-N tool, funded by other sources but affiliated with this project, has been widely tested in strip trials throughout NY and validated for reliable estimates of N leaching, crop N uptake, and estimates of total denitrification. A nitrous oxide emissions routine has recently been added to the features of Adapt-N. BMPs identified for reducing methane (CH4) emissions in dairy operations included: new feeding strategies and feed amendments; improved manure management; and creating energy for farm needs from manure waste with anaerobic digesters. Results are summarized in the “Farm Energy, Carbon and Greenhouse Gases” fact sheet available at the www.climatechange.cornell.edu website. Obj (2): This, the most technical aspect of our project, significantly advanced the state of knowledge regarding approaches to assess soil C stocks and sequestration at minimal cost by integrating strategic soil sampling with geostatistical models for predicting soil C at unsampled locations and depths. We also evaluated use of the USDA-NRCS Soil Survey Geographic (SSURGO) database for estimating soil C concentrations, and relatively low-cost proxy measures of soil C concentration, such as visible to near infrared (VNIR) and mid-infrared (MIR) spectroscopy. Specifically, during the course of our project we collected over 600 soil cores from a 650 ha dairy farm (Cornell Animal Science Teaching and Research Center in Harford, NY), 90 cores from the Cornell Freeville vegetable farm as part of a study to examine effects of rock fragments on soil C assessment accuracy, 72 cores from a long-term vegetable crops soil health research site (Cornell Gates Farm, Geneva, NY), and 24 cores from a long-term apple ground cover management research site (Cornell Orchard, Lansing, NY). In general, samples were collected to a depth of 75 cm cores divided into 0-10, 10-20, 20-30, 30-50, and 50-75 cm increments, and analyzed for: soil texture, bulk density, percent organic matter (loss on ignition), total C and N concentration (Leco combustion analyzer), labile or “active” C (permanganate oxidation), inorganic C (pressure calcimeter), and VNIR and MIR reflectance. Overall we have found that both VNIR and MIR are good predictors of lab-measured soil C concentration, and the spectroscopy approach is less labor intensive so less costly. Also, overall we have found that labile C is more sensitive to crop and soil management than total soil C or percent organic matter. In the Lansing apple orchard site (Hudson-Cayuga soil), the pre- and post-emergent herbicide groundcover treatments showed a slight decline in OM in the top 30 cm from 1992 to 2012 (from 4.4 to 3.81 and from 3.9 to 3.5 percent, respectively), while the sod and bark mulch treatments showed increases (from 3.7 to 4.2 and from 4.3 to 7.14, respectively). All of the gain in OM in the long-term mulch treatment occurred in the top 20 cm, with no significant effect at 20 – 75 cm. At the Geneva vegetable site we found a significantly higher OM in no-till and ridge till plots compared to plow-till in the upper 30 cm, but no effect from winter cover crop treatments (winter rye, vetch, or none), and no effect at lower depths (i.e., below 30 cm). The rotation sequence had a significant effect on Honeyoe and Kendaia soils, but not on the Lima soil at the Geneva vegetable site. At the Harford dairy site we found that manure application rates had a greater impact on soil organic C than cropping system, but effects of manure were confined to the top 30 cm. Of particular interest, at an intensively grid-sampled 232 ha section of this farm we found that sampling density could be reduced from 319 to 83 cores with only a 2 percent error in soil C stock estimates when we used model-based estimates (ordinary kriging) of soil C concentration based on residual maximum likelihood (REML)-fitted variograms. In contrast, SSURGO-based estimates of soil C concentration led to 3 to 19 percent errors in total soil C stocks for this 232 ha section, but given low cost of using the SSURGO database (no actual field sampling or analytical analyses required), this approach may be of interest in some circumstances. Obj (3): In collaboration with Keith Paustian and others at Colorado State University we have been participating in the development and beta-testing of the COMET-Farm tool (http://cometfarm.nrel.colostate.edu/) for application for NY fruit, vegetable, and dairy production systems. Soils data to provide COMET-Farm with soil physical parameters and initial soil C stocks needed in the DayCent crop-soil simulation model have been compiled for all mapped USDA Soil Survey (SSURGO) scale (ca. 1:16,000) map units in the US. Public release of the COMET-Farm full GHG decision support tool occurred in June, 2013. COMET-Farm provides estimates of GHG emissions for baseline and improved management scenarios for individual farms, including soil CO2 and N2O emissions and removals, CO2 emissions from on-farm energy use, and CH4 and N2O from livestock operations. The tool has been improved substantially over the course of our project, but currently is most developed for corn-dairy production systems. Only a small number of vegetable crops are currently encompassed in the tool, and more work will be needed to develop reliable apple or other fruit crop applications for NY farmers. Currently, COMET-Farm is most suitable for providing qualitative feedback to farmers regarding potential impacts of various management practices on GHG emissions and energy use. It is also useful as an educational tool for farmers or Extension staff. We have evaluated several other existing and emerging GHG accounting tools, including the “Cool Farm” tool (http://www.coolfarmtool.org), the Farm Energy Analysis Tool (FEAT), and the dairy Gas Emissions Model (GEM). Key features of each of these tools are described in our “Farm Greenhouse Gas Tools” fact sheet for farmers, Extension staff, government agency staff, and others, that is available at our www.climatechange.cornell.edu website. This document critically evaluates the tools in relation to: their boundaries (on-farm or full life cycle analysis including GHG emissions associated with farm inputs and equipment); methods for estimating GHG emissions (crop and soil simulation models vs. rough estimates based on published literature and databases); transparency and tractability; ease of use; required inputs; outputs; and crops and farm systems most suited for. Obj (4): An analysis of over 30,000 soil organic matter records from the Cornell Nutrient Analysis Lab (CNAL) database from commercial NY dairy farms revealed an average of 3.7 and 3.2 percent organic matter in silage- compared to grain-harvested fields, respectively (statistically significant at P = 0.0001), probably due to higher manure applications on silage fields. Scaling up by soil series to the entire corn-growing area, total soil C (top 20 cm depth) was 26.5 Tg based on the CNAL data, which was 28 percent lower than the value calculated from the USDA-NRCS SSURGO database. These data suggest that SSURGO values underestimate the potential for soil C storage, presumably because they do not reflect soil organic matter loss during recent cropping history.

Publications

  • Type: Journal Articles Status: Accepted Year Published: 2014 Citation: Graham CJ, H van Es, J Melkonian. 2013. Nitrous oxide emissions are greater in silt-loam soils with a legacy of manure applications than without. Biology and Fertility of Soils (in press).
  • Type: Book Chapters Status: Published Year Published: 2013 Citation: Wolfe DW. 2013. Climate change solutions from the agronomy perspective. IN: Hillel D and C Rosenzweig (eds). Handbook Climate Change and Agroecosystems: Global and Regional Aspects and Implications. Chapter 2. Imperial College Press. London.
  • Type: Other Status: Published Year Published: 2013 Citation: Bauman L and D Wolfe. Summer/Fall 2013. Shrink your gardens climate footprint. Verdant Views 5: 22-23. Cornell Plantations (www.cornellplantations.org)
  • Type: Other Status: Published Year Published: 2013 Citation: Bauman L and D Wolfe. Fall 2012. Advice to gardeners from a climate change expert. Verdant Views. Cornell Plantations 4:13-14 (www.cornellplantations.org).
  • Type: Other Status: Published Year Published: 2013 Citation: Moebius-Clune B, H van Es, J Melkonian. 2013. Adapt-N uses models and weather data to improve nitrogen management for better crops. Whats Cropping Up? Cornell University Extension Publication.
  • Type: Theses/Dissertations Status: Submitted Year Published: 2014 Citation: Sherpa, Sonam. 2014. Sampling optimization for soil carbon assessment in complex agroecosystems of the northeastern United States. M.S. Thesis. Cornell University. Ithaca, NY.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2013 Citation: Wolfe DW, J Beem-Miller, A Kong, J Comstock, S Sherpa, E Wine, AP Mallorino. 2013 Evaluation of long term agroecosystems management on changes in subsurface and surface soil carbon fractions and dynamics. American Geophysical Union Annual Conference. AGU.


Progress 10/01/11 to 09/30/12

Outputs
OUTPUTS: We evaluated geostatistical modeling techniques and Visible to Near Infrared (VNIR) spectroscopy for reducing soil C assessment costs for a dairy farm in Harford, NY. A Partial Least Squares Regression (PLSR) model for predicting dry combustion percent C from VNIR was first developed from 525 samples collected from other NY locations, representing a range of soil types and dairy cropping systems. This was then locally calibrated by adding 250 samples collected from a 1 hectare area of the Harford farm site to the PLSR model. A high-resolution percent C map across the entire 232 hectare area of the Harford farm was subsequently developed from this PLSR model and VNIR measured at 360 sample points. Using ordinary kriging, we found that the number of local calibration samples from the Harford farm could be reduced by 50 to 75% with minimal increase in Root Mean Square Error of percent C or decrease in spatial correlation. Soil C assessment sampling in 2012 included 24 cores at a long-term apple ground cover management study (Cornell Orchard, Lansing, NY) and 72 cores at a long-term vegetable crops-soil health study (Cornell Gates Farm, Geneva, NY). Analyses of cores (5 depth increments to 75 cm) for VNIR, total C and nitrogen (combustion analyzer), active C (permanganate oxidation), bulk density, and soil texture are in progress. Analyses for organic matter (OM) percent (loss-on-ignition) are completed. In the apple orchard site (Hudson-Cayuga soil), the pre- and post-emergent herbicide groundcover treatments showed a slight decline in OM in the top 30 cm from 1992 to 2012 (from 4.4 to 3.81 and from 3.9 to 3.5 percent, respectively), while the sod and bark mulch treatments showed increases (from 3.7 to 4.2 and from 4.3 to 7.14, respectively). All of the gain in OM in the long-term mulch treatment occurred in the top 20 cm, with no significant effect at 20 - 75 cm. In the vegetable crops site we found a significantly higher OM in no-till and ridge till plots compared to plow-till in the upper 30 cm, but no effect from winter cover crop treatments (winter rye, vetch, or none), and no effect at lower depths (to 75 cm). The rotation sequence had a significant effect on Honeyoe and Kendaia soils, but not on the Lima soil. In 2012 we began evaluating existing and emerging GHG accounting tools, such as the "Cool Farm" tool (http://www.coolfarmtool.org), and we have participated in developing and beta-testing of the COMET-Farm tool (http://cometfarm.nrel.colostate.edu/), for application for NY fruit, vegetable, and dairy production systems. Soils data to provide COMET-Farm with soil physical parameters and initial soil C stocks needed in the DayCent crop-soil simulation model have been compiled for all mapped USDA Soil Survey (SSURGO) scale (ca. 1:16,000) map units in the US. In addition to publications (see below), in 2012 Wolfe gave 18 invited presentations (over 800 contact hours), and 22 news media interviews, including outreach through major newspapers (e.g., New York Times), radio (e.g. National Public Radio), and trade magazines, (e.g., The American Gardener). PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
Our preliminary evaluation of low-cost approaches to soil C assessments indicate several significant results of interest to the research and agricultural communities, including: combined use of VNIR and geostatistics (e.g., ordinary kriging) show promise as a means of reducing costs associated with accessing soil C stocks; costs of estimating C stocks can be further reduced by decreasing the number of bulk density samples relative to percent C measurements. Our project is providing useful new insight into soil C change and soil C assessment strategies for fruit and vegetable crops, as well as field crops, which has been the focus of most prior work. Extension staff and farmers are becoming familiar with new greenhouse gas, carbon, and nitrogen management tools under development, preparing the way for full-scale beta testing and regional calibration for use by farmers and policy-makers. Our climate change website (www.climatechange.cornell.edu) is being used by researchers, Extension staff, farmers, and news media for reliable information on agricultural climate change adaptaion and mitigation.

Publications

  • Books and Book Chapters Wolfe DW, J Comstock, H Menninger, D Weinstein, K Sullivan, C Kraft, B Chabot, P Curtis, R Leichenko, P Vancura. 2011. Chap. 6: Ecosystems. IN: Rosenzweig C, W. Solecki, A DeGaetano et al. (eds.) Responding to Climate Change in New York State. pp. 163-216. New York Academy of Sciences. Blackwell Pub., Boston, MA.
  • Wolfe DW, J Comstock, A Lakso, L Chase, W Fry, C Petzoldt, R Leichenko, P Vancura. 2011. Chap. 7: Agriculture. IN: Rosenzweig C, W. Solecki, A DeGaetano et al. (eds.) Responding to Climate Change in New York State. pp. 217-254. New York Academy of Sciences. Blackwell Pub., Boston, MA.
  • Abstracts Sherpa S and DW Wolfe. 2012. Geostatistical modeling and visible and near-infrared reflectance spectroscopy to estimate soil carbon stocks. Proceedings: Soil Science Society of America Annual Meetings Oct 21-24, Cincinnati, OH. ASA/SSSA Madison, WI (available at society digital library: https://dl.sciencesocieties.org/).
  • Wolfe DW et al. 2012. An integrative approach to carbon, nitrogen, and greenhouse gas accounting and management in corn production systems. Proceedings: Soil Science Society of America Annual Meetings Oct 21-24, Cincinnati, OH. ASA/SSSA Madison, WI (available at society digital library: https://dl.sciencesocieties.org/).
  • Wolfe DW et al. 2012. New tools and incentives for carbon, nitrogen and greenhouse gas accounting and management in corn production systems. Proceedings: Soil Science Society of America Annual Meetings Oct 21-24, Cincinnati, OH. ASA/SSSA Madison, WI (available at society digital library: https://dl.sciencesocieties.org/).


Progress 10/01/10 to 09/30/11

Outputs
OUTPUTS: We addressed Objective 1 in our proposal by conducting a comprehensive search of the literature and existing websites to develop an initial educational fact sheet focused on farm energy conservation, greenhouse gas mitigation, and soil carbon (C) sequestration. This has been published and also is available on our website, www.climatechange.cornell.edu , along with other new fact sheets produced this year, such as one on adaptation to climate change (see impacts and publications). We addressed Objective 2 of our proposal by focusing in this first year on strategies for low cost soil C assessment on a 650 ha dairy farm in southern New York with corn and alfalfa rotations as well as pasture (Cornell's Harford Research and Training Center). We evaluated correlations between measured soil C and other properties and explored options for predicting soil C through proxy measures such as percent organic matter (OM), or by using values from the USDA National Resource Conservation Service's (NRCS) Soil Survey Geographic (SSURGO) database. We collected soil cores to 60cm in 20 cm intervals across 10 combinations of crop rotation, manure, and soil type, which encompassed about 25 percent of the farm acreage. We measured bulk density (BD), soil C, nitrogen (N), OM, permanganate oxidizable active C (AC) and texture. Total soil C in the top 60 cm ranged from xx to xx t C ha-1 across the 10 cropping system combinations, with manured, continuous alfalfa on Howard (Hd) soil having the highest value, 68 percent more t C ha-1 compared to non-manured alfalfa on the same soil type (p less than 0.001). The coefficient of variation (CV) for most soil properties more than doubled at 40-60 cm compared to 0-20 cm (significantly different at p less than 0.001), except for BD, which had a similar CV at all depths. Bulk density and OM had the lowest coefficient of variation (CV) compared to other soil properties at all depths, which reduced calculated minimum sample requirements for any desired level of confidence or magnitude of detectable difference between treatment means. We developed significant (p<0.01) linear prediction models of C from OM at all depths, and also found that C stocks for the entire 0-60cm soil profile could be predicted from C and BD measurements at just the 0-20, 20-40, or 40-60cm depths (p less than 0.001, r2 = 0.63, 0.89, and 0.73, respectively). We found that SSURGO consistently underestimated OM at depths below 20cm, but field data were used to develop a linear regression model that improved SSURGO estimates for lower depths. We also measured soil samples in the lab with a visible to near-infrared (VNIR) spectrophotometer and are in the process of calibrating VNIR data with actual soil C measured with a Leico combustion analyzer. PARTICIPANTS: In addition to project co-investigators, worked with Cornell Coop Ext staff and NYS Ag and Markets for feedback on development of fact sheets. Results were presented at Ag In-Service training for Coop Ext staff. TARGET AUDIENCES: Results from this project are directly linked to NYS Agriculture and Markets and NYSERDA interests in agricultural energy efficiency, mitigation, and the potential of carbon markets for farmers. We will be working closely Extension and vegetable, fruit, and dairy farmers regarding our development of BMPs and new tools for soil carbon and GHG accounting and management. The results of this project will feed into Cornell Cooperative Extension efforts on energy conservation and climate change, led by collaborator D. Grantham. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
Our new fact sheets on climate change mitigation and adaptation (see Publications) are a unique resource for farmers, Extension staff, and policy makers. The information contained in these have been distributed at several conferences and workshops in the Northeast, including Cornell's Agriculture In-Service training in November 2011. These are also available at our new website: www.climatechange.cornell.edu. During this year, in our evaluation of soil C variability on a 650 ha dairy farm with corn-alfalfa rotations and pasture identified several approaches to reduce sampling requirements especially at deeper soil depths. Specifically, we found that sample requirements for a given desired confidence level were less for bulk density compared to C concentration. We also found that a simple linear regression model could be used to predict soil C in the entire 0-60 cm profile from measurements in the 20-40 cm depth with an r2 of 0.89. We also found that OM from the USDA SSURGO data base could be improved to better match field measurements with a simple linear regression model derived from field measurements. Some of this work has been summarized in a M.S. Thesis (see Publications), and we also plan to submit some of this work for publications in a peer-reviewed journal in the coming year. These results will help to better inform strategic sampling and reduce costs for future soil C assessments.

Publications

  • Dietzel R, D Wolfe, JE Thies. 2011. The influence of winter soil cover on spring nitrous oxide emissions from agricultural soil. Soil Biology and Biochemistry 43:1989-1991.
  • Lewis, D, S Bell, J Fay, K Bothi, L Gatere, M Kabila, M Mukamba, E Matokwani, M Mushimbalume, CI Moraru, J Lehmann, J Lassoie, D Wolfe, D Lee, L Buck, AJ Travis. 2011. The COMACO model: using markets to link biodiversity conservation with sustainable improvements in livelihoods and food production. Proceedings National Academy of Sciences 108(34): 13957-13962.
  • Hatfield JL, KJ Boote, BA Kimball, RC Izaurralde, D Ort, A Thomson, DW Wolfe. 2011. Climate impacts on agriculture: implications for crop production. Agronomy Journal 103:351-370.
  • Wolfe DW. 2011. Gardening sustainably with a changing climate. IN: Christopher T (ed.) The New American Landscape. Timber Press. Portland, OR. Chap 6, pp. 125-140.
  • Bosco, Samuel. 2012. Soil Carbon Variability and Assessment in a Corn Cropping System in the United States and in Zambia. M.S. Thesis. Cornell University, Ithaca, NY.
  • Wolfe D, J Comstock, A Lakso, l Chase, W Fry, C Petzoldt, R Leichenko, P Vancura. 2011. Chapter 7: Agriculture. IN: Rosenzweig C, W Solecki, A DeGaetano, M OGrady, S Hassol, P Grabhorn (eds). 2011. Responding to Climate Change in New York State: The ClimAID Integrated Assessment for Effective Climate Change Adaptation. Technical Report. NYSERDA. Albany, NY. pp. 217-254.
  • Wolfe D, J Comstock, H Menninger, D Weinstein, K Sullivan, C Kraft, B Chabot, P Curtis, R Leichenko, P Vancura. 2011. Chapter 6: Ecosystems. IN: Rosenzweig C, W Solecki, A DeGaetano, M OGrady, S Hassol, P Grabhorn (eds). 2011. Responding to Climate Change in New York State: The ClimAID Integrated Assessment for Effective Climate Change Adaptation. Technical Report. NYSERDA. Albany, NY. pp. 163-216.
  • Wolfe DW, J Beem-Miller, A Chatrchyan, L Chambliss. 2011. Farm Energy, Carbon, and Greenhouse Gases. Cornell Cooperative Extension Climate Change Program Work Team fact sheet series. 4 pages. www.climatechange.cornell.edu
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