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Climate Change and Agriculture in the Great Lakes Region Potential Impacts of Climatic Variability and Change Jeffrey A. Andresen Dept. of Geography Michigan State University Climate Change and Agricultural Productivity • Crop, forage productivity and production costs – Changing temperature, precipitation – CO2 enrichment – Occurrence of extremes Climate Change and Agricultural Productivity • Soil suitability – Soil Erosion – Oxidation of organic matter Climate Change and Agricultural Productivity • Livestock productivity and production cost – – – – – Animal mortality Feed conversion rates Rates of gain Milk production Conception rates Climate Change and Agricultural Productivity • Irrigation water supply – Changes in precipitation frequency and totals – Changes in groundwater recharge rates – Changes in nonagricultural usage Year 1991 1985 1979 1973 1967 1961 1955 1949 1943 1937 1931 1925 1919 1913 1907 1901 1895 Temperature (C) Mean Annual Observed Temperatures Regional Average, 1895-1996 10 9 8 7 6 5 4 3 Year 1991 1985 1979 1973 1967 1961 1955 1949 1943 1937 1931 1925 1919 1913 1907 1901 950 900 850 800 750 700 650 600 550 500 1895 Precipitation (mm) Total Annual Observed Precipitation Regional Average, 1895-1996 Annual trends (yr-1) for selected simulated variables, soybean, 1895-1996 SPPT SPET SET/ PET PAVfp DS Yield WUE (mm) (mm) (mm) (mm) (kg/ha) (kg/ha/mm) Chatham .722 .126 .190* .235* -.032 9.188* .024* Coldwater .066 -.326* .079* .167 -.236* 1.783 .007 Eau Claire .227 -.133* .084* .000 -.233* 4.543* .009* Grand Rapids 1.881* .090 .224* .250* -.308* 9.652* .020* Madison .465 .047 .080* .185* -.079 4.944* .010* Waseca 1.286* -.373* .193* .479* -.294 15.069* .032* Worthington -.235 -.564* .126* .167 -.164 6.390* .014* Station * Trend significant at a=0.05 level Projected Changes in Climate: Great Lakes Region • While considerable differences and uncertainty exist, the majority of future climate simulations suggest a warmer and wetter climate across the region. Estimated changes in national crop production in 2030 relative to 2000 Soybeans (Reilly et al., 2001) Dryland Irrigated Yield Yield +11 to +1 to +21% +20% +7 to +49% +23% Irrigation Water Use -32 to +57% 0 to +18% Soft Wheat -3 to +58% -5 to +5% -26 to +3% Potatoes +7 to +8% -4 to –1% -3 to 0% Crop Corn Ratios of GCM-projected future and POR historical scenario crop yields averaged over all stations Alfalfa Scenario Maize Soybean HADCM2 CGCM1 HADCM2 CGCM1 HADCM2 CGCM1 Future without CO2 vs. Historical 1.06 1.06 1.11 1.26 1.13 1.24 Future with CO2 vs. Historical 1.18 1.16 1.23 1.40 1.64 1.81 Future with CO2 vs. Future without CO2 1.11 1.09 1.11 1.11 1.45 1.46 Simulated Historical and Projected Future Growing Season and Water Balance for Maize, Bay City, MI Precipitation (mm) Evapotranspiration (mm) Time Period HAD CGCM HAD 2026 – 2035 410 2090 – 2099 394 Historical Runoff(mm) Drainage(mm) Change in storage(mm) CGCM HAD CGCM HAD CGCM HAD CGCM 314 -460 -432 -50 -20 -7 -5 106 143 267 -394 -364 -53 -29 -5 -4 57 130 321 -410 -48 -7 145 Agricultural strategies for coping with climate change • Adaptation – Learn to change, adapt • Mitigation – Reduction of carbon and other GHG • Carbon sequestration • Production of fuels/energy from biomass/animal waste • Reduction of CH4 and N2O • Use of alternative energy sources in production Cumulative Simulated Frequency Distributions of Adapted vs. Non-adapted Crop Cultivars, 2000-2099, with HADCM2 Model Data, Coldwater, MI 1 Non-Adapted Adapted 0.8 p(x) 0.6 0.4 0.2 0 0 2 4 6 8 Yield (tons/ha) 10 12 14 Probability Distribution of Simulated Dryland Double Crop Soybean Yields by Planting Date Adrian, MI, 1895-2000 2500 Yield (kg/ha) 2000 1500 1-Jun 15-Jun 1-Jul 15-Jul 1000 500 0 1 0.8 0.6 0.4 Probability 0.2 0 Probability Distribution of Simulated Irrigated Double Crop Soybean Yields by Planting Date Adrian, MI, 1895-2000 4500 4000 3500 Yield (kg/ha) 3000 1-Jun 15-Jun 1-Jul 15-Jul 2500 2000 1500 1000 500 0 1 0.8 0.6 0.4 Probability 0.2 0 Summary • A changing climate leads to many potential challenges for agricultural production systems. • Observed climate has become wetter and cloudier in the Great Lakes Region, especially during the last 50 years. • The single most important climatological variable associated with crop yields regionally is precipitation. Growing season length and GDD accumulation were relatively more important at northern study sites. Summary (continued) • The warmer and wetter climate suggested by the many GCM projections for our region would suggest yield increases for many crops. Yields of some crops in the region might decline. • A significant portion of any future yield increases will be associated with CO2 enrichment. • Recent research results suggest greater agronomic potential for northern sections of the region, even with less suitable soils. • More research is needed, especially regarding indirect impacts of climate change and extreme events.