Abstract
Climate services such as agricultural decision support tools provide a link between climate information and agricultural practices for farmers, with a goal of improving best management practices and agricultural sustainability through the useful presentation of climate variability and change. Independent organizations throughout the world have developed tools to meet their region’s specific needs, and these tools are generally commodity or issue specific. The Cornell Climate Smart Farming Program, an interdisciplinary program of the Cornell Institute for Climate Smart Solutions (CICSS), has developed a website and suite of climate-based agricultural decision support tools aimed at helping farmers make more informed decisions in the face of increasing climate uncertainty. Specific tools were developed based on the major climate impacts to Northeastern US agriculture and through a collaborative development process with stakeholders, researchers, and the Northeast Regional Climate Center. Through this process, CICSS performed a review of decision tools on a national and international scale, and in this text the role and impact of decision support tools are examined, along with the ability of researchers and tool developers to learn from stakeholders and share information via extension specialists. The need for monitoring, evaluation, and coordination among regional programs and organizations is also discussed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Adger, W. N., Arnell, N. W., & Tompkins, E. L. (2005). Successful adaptation to climate change across scales. Global Environmental Change, 15(2), 77–86. https://doi.org/10.1016/j.gloenvcha.2004.12.005.
Agronomic Technology Corp. (2016). Adapt-N. Retrieved from http://www.adapt-n.com/
American Meteorological Society. (2015). Climate services. Retrieved from https://www.ametsoc.org/ams/index.cfm/about-ams/ams-statements/statements-of-the-ams-in-force/climate-services1/.
Bartels, W.-L., Furman, C. A., Diehl, D. C., Royce, F. S., Dourte, D. R., Ortiz, B. V., et al. (2013). Warming up to climate change: A participatory approach to engaging with agricultural stakeholders in the Southeast US. Regional Environmental Change, 13(1), 45–55. https://doi.org/10.1007/s10113-012-0371-9.
Brasseur, G. (2015). Climate services and the private sector. Hamburg: Climate Service Center HZG Retrieved from http://www.climate-services.org/wp-content/uploads/2015/05/Brasseur-Private-Sector.pdf.
Breuer, N. E., Cabrera, V. E., Ingram, K. T., Broad, K., & Hildebrand, P. E. (2007). AgClimate: A case study in participatory decision support system development. Climatic Change, 87(3–4), 385–403. https://doi.org/10.1007/s10584-007-9323-7.
Breuer, N. E., Fraisse, C. W., & Hildebrand, P. E. (2009). Molding the pipeline into a loop: The participatory process of developing AgroClimate, a decision support system for climate risk reduction in agriculture. ResearchGate, 3(1). Retrieved from https://www.researchgate.net/publication/267397537_Molding_the_pipeline_into_a_loop_the_participatory_process_of_developing_AgroClimate_a_decision_support_system_for_climate_risk_reduction_in_agriculture.
Brodal, G., Schiøll, A., Hole, H., Brevig, C., & Rafoss, T. (2007). VIPS – warning and prognoses of pests and diseases in Norway. NJF report. Retrieved from http://www.bioforsk.no/ikbViewer/page/publication?p_document_id=33310
Brugger, J., & Crimmins, M. (2014). Designing institutions to support local-level climate change adaptation: Insights from a case study of the U.S. Cooperative Extension System. Weather, Climate, and Society, 7(1), 18–38. https://doi.org/10.1175/WCAS-D-13-00036.1.
Chatrchyan, A. (2016). USDA Project initiation: Project N. NYC-Chatrchyan, Multistate no. NC1179.
Climate and Disaster Risk Solutions. (2011). Africa RiskView online. Retrieved from http://www.un-spider.org/sites/default/files/AfricaRiskViewOnlineNewsletter.pdf.
Cox, P. G. (1996). Some issues in the design of agricultural decision support systems. Agricultural Systems, 52(2), 355–381. https://doi.org/10.1016/0308-521X(96)00063-7.
Decker, D. J., Krueger, C. C., Jr, R. A. B., Knuth, B. A., & Richmond, M. E. (1996). From clients to stakeholders: A philosophical shift for fish and wildlife management. ResearchGate, 1(1), 70–82. https://doi.org/10.1080/10871209609359053.
DeGaetano, A. T., & Belcher, B. N. (2007). Spatial interpolation of daily maximum and minimum air temperature based on meteorological model analyses and independent observations. Journal of Applied Meteorology and Climatology, 46(11), 1981–1992. https://doi.org/10.1175/2007JAMC1536.1.
DeGaetano, A. T., & Wilks, D. S. (2009). Radar-guided interpolation of climatological precipitation data. International Journal of Climatology, 29(2), 185–196. https://doi.org/10.1002/joc.1714.
DeGaetano, A. T., Brown, T. J., Hilberg, S. D., Redmond, K., Robbins, K., et al. (2010). Toward regional climate services: The role of NOAA’s regional climate centers. Bulletin of the American Meteorological Society, 91(12), 1633–1644.
DeGaetano, A. T., Noon, W., & Eggleston, K. L. (2014). Efficient access to climate products using ACIS Web services. Bulletin of the American Meteorological Society, 96(2), 173–180. https://doi.org/10.1175/BAMS-D-13-00032.1.
Ewbank, R., Ingham, A., & Schechter, E. (2015). Developing climate services: experiences in fecast use from Kenya, India and Nicaragua. Programme experience. London: Christian Aid Retrieved from http://programme.christianaid.org.uk/programme-policy-practice/sites/default/files/2016-03/developing-climate-services-experience-feb-2015.pdf.
Farahani, H., Fraisse, C., Templeton, S., Davis, R., & Khalilian, A. (2010). Agroclimate tools for South Carolina. Proceedings of the 2010 South Carolina Water Resources Conference. Columbia, SC: Columbia Metropolitan Convention Center.
Fraisse, C. W., Ingram, K. T., Garcia, Y., Garcia, A., Hoogenboom, G., Hatch, U., Cabrera, V. E., Zierden, D., Breuer, N., Paz, J., & Bellow, J. (2006). AgClimate: A climate forecast information system for agricultural risk management in the southeastern USA [electronic resource]. Computers and Electronics in Agriculture, 53(1), 13–27. https://doi.org/10.1016/j.compag.2006.03.002.
Hammer, G. (2000). A general systems approach to applying seasonal climate forecasts. In G. L. Hammer, N. Nicholls, & C. Mitchell (Eds.), Applications of seasonal climate forecasting in agricultural and natural ecosystems (pp. 51–65. Retrieved from http://link.springer.com/chapter/10.1007/978-94-015-9351-9_4). Dordrecht: Springer. https://doi.org/10.1007/978-94-015-9351-9_4.
Hansen, J., & Coffey, K. (2011) Agro-climate tools for a new climate-smart agriculture. Retrieved from https://cgspace.cgiar.org/handle/10568/21666
Howden, S. M., Soussana, J.-F., Tubiello, F. N., Chhetri, N., Dunlop, M., & Meinke, H. (2007). Adapting agriculture to climate change. Proceedings of the National Academy of Sciences, 104(50), 19691–19696. https://doi.org/10.1073/pnas.0701890104.
IPCC. (2007). Climate change 2007: Synthesis report. Contributions of working groups I, II, and III to the fourth assessment report of the intergovernmental panel on climate change. Geneva: IPCC Retrieved from https://www.ipcc.ch/pdf/assessment-report/ar4/syr/ar4_syr.pdf.
IPCC. (2014). Climate change 2014: Synthesis report. Contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change (p. 151). Geneva: IPCC.
Jones, J. W., Hansen, J. W., Royce, F. S., & Messina, C. D. (2000). Potential benefits of climate forecasting to agriculture. ResearchGate, 82(1–3), 169–184. https://doi.org/10.1016/S0167-8809(00)00225-5.
Meinke, H., & Stone, R. C. (2005). Seasonal and inter-annual climate forecasting: The new tool for increasing preparedness to climate variability and change in agricultural planning and operations. Climatic Change, 70(1–2), 221–253. https://doi.org/10.1007/s10584-005-5948-6.
Meinke, H., Nelson, R., Kokic, P., Stone, R., Selvaraju, R., & Baethgen, W. (2006). Actionable climate knowledge: From analysis to synthesis. Climate Research, 33(1), 101–110. https://doi.org/10.3354/cr033101.
Nagothu, U. S. (2016). Climate change and agricultural development: Improving resilience through climate smart agriculture. Agroecology and Conservation: Routledge.
NIBIO. (2016). VIPS – Beslutningsstøtte for integrert plantevern - Bioforsk. Retrieved from http://www.bioforsk.no/ikbViewer/page/prosjekt/tema?p_dimension_id=23995&p_menu_id=24011&p_sub_id=23996&p_dim2=24003
Noula – Crisis Management Portal – Haiti. (2017). Retrieved from http://www.noula.ht/
Prokopy, L. S., Hart, C. E., Massey, R., Widhalm, M., Klink, J., Andresen, J., et al. (2015). Using a team survey to improve team communication for enhanced delivery of agro-climate decision support tools. Agricultural Systems, 138, 31–37. https://doi.org/10.1016/j.agsy.2015.05.002.
Rathore, L. S., & Chattopadhyay, N. (2016). Weather and climate services for farmers in India. Geneva: World Meteorological Organization Retrieved from https://public.wmo.int/en/resources/bulletin/weather-and-climate-services-farmers-india.
Rosenzweig, C., Solecki, W., & DeGaetano, A. (2011). Responding to climate change in New York State: Synthesis report. Albany, NY: The New York State Energy Research and Development Authority.
The International Conference on Climate Services. (2012) Toward a climate service enterprise conference report. Paper presented at the The Second International Conference on Climate Services. Brussels, Belgium. Retrieved from http://www.climate-services.org/wp-content/uploads/2015/05/iccs2_report_screen_low_resolution-2.pdf
The Weather Company. (2015). IBM plans to acquire The Weather Company’s product and technology businesses; extends power of Watson to the internet of things. Retrieved from https://business.weather.com/news/ibm-plans-to-acquire-the-weather-companys-product-and-technology-businesses-extends-power-of-watson-to-the-internet-of-things
Tobin, D., Janowiak, M., Hollinger, D., Skinner, R., Swanston, D., Steele, R., et al. (2015). Northeast and Northern Forests Regional Climate Hub assessment of climate change vulnerability and adaptation and mitigation strategies (p. 65). Davis, CA: Climate Hub USDA.
Upbin, B. (2013). Monsanto buys climate corp for $930 million. Forbes Retrieved from http://www.forbes.com/sites/bruceupbin/2013/10/02/monsanto-buys-climate-corp-for-930-million/.
USDA Notheast Climate Hub. (2016). Research and extension education needs white paper (draft). Retrieved from http://www.climatehubs.oce.usda.gov/northeast/regional-assessments/regional
Varma, A., Le-Cornu, E., Madan, P., & Dube, S. (2015). The role of the private sector to scale up climate finance in India. New Delhi: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH Retrieved from https://www.giz.de/en/downloads/giz2015-en-nama-india-private-financial-institutions-climate-finance-final-report.pdf.
Webber, S., & Donner, S. D. (2016). Climate service warnings: cautions about commercializing climate science for adaptation in the developing world. Wiley Interdisciplinary Reviews: Climate Change. https://doi.org/10.1002/wcc.424.
Wilks, D. S., & Livezey, R. E. (2013). Performance of alternative “normals” for tracking climate changes, using homogenized and nonhomogenized seasonal U.S. surface temperatures. Journal of Applied Meteorology and Climatology, 52(8), 1677–1687. https://doi.org/10.1175/JAMC-D-13-026.1.
World Bank and CIAT. (2015). Climate-smart agriculture in Uruguay. Washington, DC: The World Bank Group Retrieved from http://sdwebx.worldbank.org/climateportal/doc/agricultureProfiles/CSA-in-Uruguay.pdf.
World Meteorological Organization. (2014). Agriculture and food security exemplar to the user interface platform of the global framework for climate services. Retrieved from https://www.wmo.int/gfcs/sites/default/files/Priority-Areas/Agriculture%20and%20food%20security/GFCS-AGRICULTURE-FOOD-SECURITY-EXEMPLAR-FINAL-14147_en.pdf
Yield Prophet. (2017). Retrieved from http://www.yieldprophet.com.au/yp/WhatIsYP.aspx
Acknowledgements
We thank Rick Moore and Brian Belcher for programming the Climate Smart Farming Tools and making these possible in the year, and Savannah Acosta for compiling and analyzing literature on decision support tools. We also thank our collaborators at the Norwegian Institute for Bioeconomy Research. We appreciate the organizers of the Conference on Weather and Climate Decision Tools for Farmers, Ranchers, and Land Managers, at the University of Florida, which led to a great exchange of ideas in preparation for finalizing this manuscript. And finally, we would like to acknowledge our funders: USDA NIFA Federal Capacity Funds (Hatch and Smith Lever funds), the USDA NE Climate Hub (through an Agricultural Research Service, Cooperative Agreement), and insightful funding from the New World Foundation, Local Economies Project. We gratefully acknowledge all support provided for this project.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
1 Electronic Supplementary Material
Agriculture decision making tool by CUCSS (MP4 23414 kb)
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Lambert, J., Sekhar, N.U., Chatrchyan, A., DeGaetano, A. (2019). Agricultural Decision Support Tools: A Comparative Perspective on These Climate Services. In: Sarkar, A., Sensarma, S., vanLoon, G. (eds) Sustainable Solutions for Food Security . Springer, Cham. https://doi.org/10.1007/978-3-319-77878-5_22
Download citation
DOI: https://doi.org/10.1007/978-3-319-77878-5_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-77877-8
Online ISBN: 978-3-319-77878-5
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)