GC084
Toward Better Understanding of the Impacts of Climate Variability on Agricultural Decision Making and Longer-term Adaptation
Session ID#: 76043
Session Description:
Climate variability (CV) is a critical driver of year-to-year impacts on agricultural systems. To properly understand its ecological impacts, it is necessary to quantify how managed ecosystems have historically responded to CV, and to characterize the uncertainty in projected biophysical impacts. In agricultural systems, assessing impacts of CV also requires understanding dynamics of farmer decision-making and adaptation in the face of both biophysical and economic uncertainty. Here we seek new efforts to quantify both historical and future impacts of CV on different types of agricultural systems varying by crop, farm size/intensification and climate/soils, including: i) empirical/process based methods for estimating CV impacts across multiple spatio-temporal scales, including emerging Earth-Observation-technologies (e.g., ECOSTRESS) and distributed-sensor-networks; ii) methods for forecasting impacts of CV on agricultural response at relevant scales, including S2S; iii) translating forecasts into useful decision-support for farmers and policymakers; and iv) attributing farmer responses to CV with respect to socioeconomic-ecological circumstances.
Co-Organized:
Index Terms:
1616 Climate variability [GLOBAL CHANGE]
1640 Remote sensing [GLOBAL CHANGE]
1807 Climate impacts [HYDROLOGY]
6309 Decision making under uncertainty [POLICY SCIENCES]
Primary Convener: Amor V M Ines, Michigan State University, East Lansing, MI, United States
Conveners: Lyndon D Estes, Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States, Eunjin Han, International Research Institute for Climate and Society, Columbia University, Palisades, NY, United States and Sharon Gourdji, National Institute of Standards and Technology Gaithersburg, Gaithersburg, MD, United States
Primary Liaison: Lyndon D Estes, Clark University, Graduate School of Geography, Worcester, MA, United States
Integrated approaches to Agricultural Monitoring and Forecasting in Dryland Regions (Invited) (490223)
Justin Sheffield1,2, Daniela Anghileri3, Yang Lu2, Solomon Gebrechorkos2, Noemi Vergopolan4, Veronica Bozzini5, Chengxiu Li6, Meryl Jagarnath6, Jadu Dash7 and Chris Hill6, (1)Princeton Climate Analytics, Princeton, NJ, United States, (2)University of Southampton, Geography and Environment, Southampton, United Kingdom, (3)University of Southampton, Southampton, SO14, United Kingdom, (4)Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States, (5)ETH Zurich, Zurich, Switzerland, (6)University of Southampton, Southampton, United Kingdom, (7)University of Southampton, Geography and the Enviornment, Southampton, United Kingdom
To What Extent Does Climate Variability Explain Farmers’ Planting Decisions in Central Kenya? (495151)
Natasha Krell1, Frank Davenport1, Seth Peterson1, Shraddhanand Shukla1, Gregory J Husak1, Will Turner1, Chris C Funk1 and Kelly K Caylor2, (1)University of California Santa Barbara, Santa Barbara, CA, United States, (2)University of California Santa Barbara, Department of Geography, Santa Barbara, CA, United States
Assessing the use the Canadian Precipitation Analysis Data for Monitoring and Modelling the Impacts of Weather on Agricultural Production (502829)
Catherine Champagne, Agriculture and Agri-Food Canada, National AgroClimate Information Service, Ottawa, ON, Canada, Marilee Pregitzer and Richard Warren, Agriculture and Agri-Food Canada, Science and Technology Branch, Fredericton, NB, Canada
Empirical irrigated and rainfed crop responses to temperature and precipitation in U.S. counties. (518157)
Abigail Snyder, Joint Global Change Research Institute, College Park, MD, United States, Mary Ollenberger, University of Maryland Center for Environmental Science Appalachian Laboratory, Frostburg, United States and Stephanie Waldhoff, Pacific Northwest National Laboratory, College Park, MD, United States
Assessment of suitable satellite datasets for Weather Index-based Insurances for rain-fed agriculture in Malawi (531790)
Daniela Anghileri, University of Southampton, Southampton, SO14, United Kingdom, Veronica Bozzini, ETH Zurich, Zurich, Switzerland, Peter Molnar, ETH Zurich, Institute of Environmental Engineering, Zurich, Switzerland and Justin Sheffield, Princeton Climate Analytics, Princeton, NJ, United States; University of Southampton, Geography and Environment, Southampton, United Kingdom
Characterizing farm-scale variability in maize yields in West Africa by integrating optical and passive microwave earth observation data with a process model (553960)
Sarah Fletcher, Massachusetts Institute of Technology, Cambridge, MA, United States, Hamed Alemohammad, Radiant Earth Foundation, Washington, DC, United States, Anjuli Jain Figueroa, Stanford University, Stanford, CA, United States and Dara Entekhabi, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Cambridge, MA, United States
Effects of Precipitation Variation and Irrigation Scheduling Methods on Maize under Future Climatic conditions (577189)
Rohit Nandan1, Dongkook Woo2, Praveen Kumar3 and Prof. Adinarayana J1, (1)Indian Institute of Technology Bombay, Centre of Studies in Resources Engineering, Mumbai, India, (2)Lawrence Berkeley National Laboratory, Climate & Ecosystem Sciences Division, Berkeley, CA, United States, (3)University of Illinois at Urbana Champaign, Department of Civil and Environmental Engineering, Urbana, IL, United States
An analysis of the 2012 drought using a satellite data-driven hydro-economic model (581160)
Marco P Maneta1, John Kimball2, Mingzhu He3, Zachary Lauffenburger1, Xinde Ji4 and Kelly M Cobourn5, (1)University of Montana, Geosciences, Missoula, MT, United States, (2)University of Montana, Numerical Terradynamic Simulation Group, W.A. Franke College of Forestry & Conservation, Missoula, MT, United States, (3)University of Montana, Missoula, MT, United States, (4)Virginia Tech, Blacksburg, United States, (5)Virginia Polytechnic Institute and State University, Blacksburg, United States
Development of a decision support model for the management of fungal ear rot and associated mycotoxin contamination in corn grain (581895)
Amor V M Ines1, Maninder Singh1, Martin Chilvers1, Eunjin Han2, Josue Kpodo1, Prakash KUMAR Jha1, Eeswaran Rasu1 and Kaitlin Fusilier1, (1)Michigan State University, East Lansing, MI, United States, (2)International Research Institute for Climate and Society, Columbia University, Palisades, NY, United States
Decreasing sensitivity of US diary to temperature and humidity extremes (601517)
Nathan Mueller, University of California Irvine, Irvine, CA, United States, Maria Gisbert-Queral, University of California, Irvine, Irvine, CA, United States, Arne Henningsen, University of Copenhagen, Copenhagen, Denmark and Meredith Niles, University of Vermont, Burlington, United States
Machine Learning to Predict Bioenergy Sorghum Yields under Future Climate Scenarios (620829)
Corinne D. Scown1, Tyler Huntington1, Xinguang Cui and Umakant Mishra3, (1)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (2)Argonne National Laboratory, Environmental Science Division, Argonne, IL, United States
