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Climate Information and Climate Information and Agricultural Risk ManagementAgricultural Risk ManagementA Systemic Approach to Understanding
Farmers’ Decision-Making
T. A. Crane*, C. Roncoli*, N. E. Breuer+, J. O. Paz*,
K. T. Ingram#, K. Broad+, G. Hoogenboom** University of Georgia, + University of Miami, # University of Florida
Outline
• Research methods and setting
• Interactions with weather and climate information systems
• Potential adaptive strategies
• Challenges to forecast use
• Farmers’ suggestions for usability
Methods and Research Setting
• Sample: 38 farmers• Sites: 21 counties in
South Georgia• Methods: Semi-
structured interviews– Weather and climate
information systems– Climate variability and
risk mgmt. strategies– Potential adaptations
Methods and Research Setting
• Sample: 38 farmers• Sites: 21 counties in
South Georgia• Methods: Semi-
structured interviews• Mixed production
systems• Avg. 2 per operation
Production System Freq.Row crop 31
Produce (conv. & org.) 10
Cattle 8
Pine plantation 7
Hay 4
Pecans 3
Sows 2
Peach 2
Turf grass 1
Goats 1
Poultry 1
Weather & Climate Info Sources
• Daily use, often accessed multiple times– Spraying– Planting
– Irrigation • Confidence low beyond
3-5 days• Wives & children are
often internet users; information gateways
Source Freq.
Weather Channel (TV) 18
Local TV 16
Data Trans. Network 9
Online (indeterminate) 9
Weather.com 6
Farm Magazines 4
Cell phone 4
GAEMN 4
Local Radio 3
Local Paper 2
Weatherbug.com 2
Accuweather.com 1
NOAA (online) 1
NWS (online) 1
Farmer's Almanac 1
Weather & Climate Info Sources
• Passive exposure to climate forecasts
• 90-day forecasts not used in agric. decisions– “Conversation piece”– “Peace of mind”
• Collective credibility
Source Freq.
Weather Channel (TV) 18
Local TV 16
Data Trans. Network 9
Online (indeterminate) 9
Weather.com 6
Farm Magazines 4
Cell phone 4
GAEMN 4
Local Radio 3
Local Paper 2
Weatherbug.com 2
Accuweather.com 1
NOAA (online) 1
NWS (online) 1
Farmer's Almanac 1
Adaptive Management Options
• Cropping strategy– Corn or cotton ?– Dry land corn ?– Soil : crop : forecast ?
• Forward contracts ?• Planting schedule
– Dry year pine planting ?– Late frost risk ?
Potential Use Freq.Crop selection 23
Planting timing 16
Input management 14
Land management 13
Variety selection 11
Marketing 8
Harvesting dates 4
Insurance 3
Herd management 2
Hog lagoon mgmt. 1
Adaptive Management Options
Potential Use Freq.Crop selection 23
Planting timing 16
Input management 14
Land management 13
Variety selection 11
Marketing 8
Harvesting dates 4
Insurance 3
Herd management 2
Hog lagoon mgmt. 1
Forecast Use: Irwin CountySpring 2006 forecast for summer drought widespread shift from
long- to short-cycle peanut variety
Non-Climate Variables as Management Drivers
• Agronomic requirements • Commodity prices• Insurance constraints• Input prices• Credit options• Policy environment
– Price supports– Trade policies– Immigration laws
Relative uncertainty of forecasts compared to non-climate variables = competition as mgmt. driver
Relative uncertainty of forecasts compared to non-climate variables = competition as mgmt. driver
Challenges to Farmers’ Use of Forecasts
• Discrepancy in scales of forecasts & decisions – Temporal– Spatial
• Inexperience with climate forecasts– Unawareness of potential– Skepticism of accuracy
• Discrepancy in understandings of key concepts– Probability– Accuracy
Challenges to Farmers’ Use of Forecasts
• Difficulty in processing additional information– Time– Mental energy
• Inflexibility of highly-capitalized operations– Indebtedness– Infrastructural investments– Large acreage
• Potential for actors to leverage info over farmers– Lenders– Insurers– Brokers
Facilitating Appropriate Use of Climate-Based DSS
• Create recognizable identity for DSS– “Show the people behind it” – Association with land-grant university
• Communication – Use lay-users’ language– “Show you understand what it means to be a farmer”– Layer information for different users
• Cultivate habitual reference to site– Regular outreach– Keep information updated
Facilitating Appropriate Use of Climate-Based DSS
• Enable users to evaluate forecasts – Publish forecast history – Publish forecast
performance records– Explain probability upfront
• Integrate users’ feedback into product development and assessment