Land-Use Model Data Description and Parameter Estimates

Appendix

REEC-D-14-00099R1: Impacts of Climate Change on Land-Use and Wetland Productivity in the Prairie Pothole Region of North America

Land-Use Model Data Description and Parameter Estimates We used futures market prices for corn, wheat, soybeans and sorghum, and lagged prices for hay to capture agricultural producer expectations since producers cannot observe the actual price at the time planting decisions are made. The price variables also account for government support programs, such as the Acreage Reduction Program, which existed during the data sample period. We normalized all prices using the index of prices paid by farmers, which generates a proxy for relative profitability. See Wu et al. (2004) for detailed derivation of the price variables. Crop yields at individual NRI sites are unavailable for the study region. However, the National Agricultural Statistics Service (NASS) provides county-level crop data, which we used to estimate farmers’ expected yields and yield variance in each county. Specifically, following Chavas and Holt (1990), we estimated a linear trend model for corn yields in each county using NASS data. The resulting predictions were used as expected future yields of corn. The estimated residuals were then used to generate variance of corn yields, which we assumed to be constant over time. To capture yield differences among NRI sites, we included physical variables reflecting land quality at individual NRI sites. NRI provides information on land capability classes and land slope. Slope is a continuous variable measured as a percentage. High quality land is defined as land with a land capability class of 1 or 2. Low-quality land is defined as land with a land capability class above 4. In addition, each NRI sample site is linked to the NRCS’s SOILS5 database, providing detailed soil profile information from soil surveys. From these data, we calculated average measures of soil properties for top soil layers, including available water capacity, average organic matter percentage, clay percentage, soil pH, and soil texture. Finally, we obtained historical weather data from the Midwestern Climate Center. We estimated the average of the means and variances of maximum and minimum daily temperatures and precipitation during the corn growing seasons for each NRI site using data from the nearest weather station. We also included the means and standard deviation of precipitation during the wheat growing seasons, including snow precipitation, which can influence winter wheat production. Because the long-run average of weather conditions changes little over time, farmers’ expectations of weather conditions were assumed to be constant and were represented by the averages of the means and variances of temperatures and precipitation during the corn and wheat growing seasons from 1975 to 1992. Table A1 Summary statistics for variables used in the land-use model to predict agricultural land use in the Prairie Pothole Region of North and South Dakota

Mean Std Dev Minimum Maximum Cropping History Previous year's crop is corn 0.168 0.374 0 1 Previous year's crop is soybeans 0.079 0.27 0 1 Previous year's crop is sorghum 0.107 0.31 0 1 Previous year's crop is wheat 0.289 0.453 0 1 Previous year's crop is hay 0.076 0.264 0 1 Output and Input Prices Expected price for corn 0.017 0.004 0.011 0.024 Expected price for soybeans 0.04 0.007 0.032 0.052 Expected price for wheat 0.021 0.005 0.016 0.034 Expected price for hay 0.371 0.073 0.232 0.52 Expected price for sorghum 0.017 0.003 0.01 0.021 ARP rate for wheat 12.64 9.624 0 28 Fuel price 4.45 0.382 3.855 5.046 Chemical price 3.45 0.17 3.179 3.66 Wage rate 0.029 0.003 0.022 0.0317 Yield Expected yield of corn 80.38 36.5 1.15 170.63 Expected variation of corn yield 384.02 246.55 39.06 1763.77 Land Characteristics Good land 0.57 0.495 0 1 Bad land 0.052 0.222 0 1 Slope 25.712 26.934 0 300 Available water capacity 0.171 0.032 0.04 0.22 Organic matter 2.244 1.419 0 12.5 Soil pH 7.321 0.556 5.04 9.03 Coase-textured soil 0.227 0.419 0 1 Fine-textured soil 0.147 0.354 0 1 Weather Mean max temperature - corn 81.55 3.891 70.87 87.97 Mean precipitation - corn 0.121 0.024 0.074 0.182 St. dev of precipitation - corn 0.313 0.061 0.186 0.479 Mean of precipitation - wheat 0.0735 0.0192 0.035 0.118 St. dev of precipitation - wheat 0.228 0.052 0.125 0.358 Mean of snow - wheat 0.079 0.085 0 0.708 St. devi of snow - wheat 0.429 0.257 0 1.641 State Dummies N. Dakota dummy 0.156 0.363 0 1 S. Dakota dummy 0.138 0.345 0 1 Table A2. Parameter estimates and t-statistics for multinomial logit model of land use choice in the Northern Plains, USA

Corn Soybeans Wheat Hay Sorghum Variables Coef. t-stat Coef. t-stat Coef. t-stat Coef. t-stat Coef. t-stat Constant 11.99 3.00 2.95 0.62 -7.35 -2.91 -9.05 -1.09 -10.44 -1.81 Cropping History Previous crop is corn 2.74 53.27 3.13 38.42 -0.76 -12.83 0.78 5.40 1.13 12.37 Previous crop soybeans 3.54 39.12 3.11 28.21 0.99 10.99 1.08 4.65 3.20 29.34 Previous crop sorghum 0.47 5.63 2.21 23.83 -0.49 -8.69 -0.15 -0.70 3.19 43.81 Previous crop is wheat -0.27 -4.58 1.00 12.01 -0.28 -9.74 -0.39 -2.91 0.99 14.60 51.5 Previous crop is hay 1.93 13.47 1.65 7.57 -0.61 -3.79 6.89 8 1.44 6.67 Price and Policy Variables Expected price corn 24.78 1.28 -68.83 -3.07 8.19 0.60 -0.53 -0.01 80.48 3.53 Expected price soybeans -2.19 -0.15 11.11 0.63 -42.45 -4.40 -40.48 -1.29 -52.50 -2.58 Futures price wheat 3.98 0.31 12.81 0.84 15.32 1.82 29.09 1.06 45.24 3.37 Expected price hay -1.46 -4.32 -0.77 -1.95 0.73 3.35 1.40 1.99 0.23 0.57 Expected price Sorghum 97.01 2.02 54.28 0.94 -34.65 -1.14 -90.56 -0.92 71.10 0.88 ARP rate for wheat 0.03 1.94 0.01 0.69 -0.01 -0.98 -0.02 -0.81 0.03 1.38 Fuel price -0.48 -1.03 0.26 0.48 0.45 1.54 1.05 1.10 0.06 0.09 Chemical price -1.46 -1.51 0.03 0.02 -0.21 -0.34 2.10 1.06 -0.50 -0.34 Wage rate -15.65 -0.62 15.33 0.51 8.20 0.47 -10.05 -0.19 40.21 1.24 Expected Yield and Yield Variation of Corn Expected yield of corn 0.02 17.48 0.01 7.84 -0.01 -9.96 0.00 -1.92 0.00 1.39 Variation of corn yield 0.00 -7.71 0.00 5.96 0.00 -4.19 0.00 -4.09 0.00 -6.47 Land Characteristics Good land 0.32 6.51 0.04 0.71 0.18 5.60 0.05 0.52 -0.01 -0.21 Bad land -0.23 -2.54 -0.33 -2.91 -0.27 -4.08 0.48 3.07 0.15 1.66 Slope 0.00 -1.04 0.00 -4.66 -0.01 -12.88 0.00 -1.77 -0.01 -6.83 Water capacity 0.45 0.58 8.70 8.84 -0.47 -0.77 -2.63 -1.72 -0.98 -1.06 Organic matter -0.09 -5.52 0.00 -0.22 -0.01 -0.59 -0.10 -2.92 0.03 1.37 Soil pH -0.26 -5.62 -0.44 -8.24 -0.05 -1.35 -0.15 -1.52 -0.21 -4.12 Coarse-textured soil 0.01 0.18 0.47 8.60 -0.01 -0.39 -0.10 -0.91 0.23 4.17 Fine-textured soil 0.31 4.35 0.56 6.32 -0.19 -3.73 0.18 1.24 0.24 3.03 Weather Conditions Mean max temp-corn -0.11 -12.21 -0.16 -13.50 0.09 13.49 -0.04 -1.92 0.08 6.59 Mean precip-corn 6.70 1.60 3.03 0.62 21.72 7.66 28.25 3.14 22.75 5.08 St. dev. of precip-corn 5.38 3.23 15.95 8.47 -8.96 -7.96 -1.60 -0.46 -2.22 -1.18 Mean of precip-wheat 49.41 7.50 158.07 20.27 -36.57 -8.39 21.45 1.64 14.22 1.93 St. dev. of precip-wheat -18.64 -8.15 -50.78 -18.25 20.55 13.48 -8.05 -1.76 -4.21 -1.57 Mean of snow-wheat -0.98 -1.67 -0.20 -0.30 0.51 1.10 3.42 2.82 -0.01 -0.02 St. dev. of snow-wheat 0.56 2.40 -0.02 -0.06 -0.40 -2.09 -1.82 -3.57 0.09 0.32 State Dummies N. Dakota dummy -1.37 -7.97 -1.92 -8.89 0.33 2.69 -1.95 -5.49 -3.94 -9.72 S. Dakota dummy 0.29 1.78 -1.51 -7.88 -0.87 -7.52 -0.56 -1.65 -0.98 -5.09 LOG OF LIKELI HOOD FUNCT ION -51,382 Notes: The 1%, 5%, and 10% critical values for the t-statistics are 2.58, 1.96, and 1.65, respectively.

Table A3 Elasticitiesa of the probability of observing alternative agricultural land uses estimated with a parcel-level multinomial logit model for the Northern Plains, USA

Corn Soybeans Wheat Hay Sorghum Other Price and Policy Variables Expected price for corn 0.269 -1.17 -0.025 -0.032 0.924 -0.136 Expected price for soybeans 0.295 0.931 -0.737 -0.191 -0.969 0.78 Futures price for wheat -0.116 -0.014 0.068 0.075 0.502 -0.212 Expected price for hay -0.297 -0.115 0.187 0.116 0.070 -0.048 Expected price for Sorghum 0.771 0.157 -0.577 -0.386 0.695 -0.045 ARP rate for wheat 0.146 -0.022 -0.112 -0.071 0.214 -0.021 Fuel price -1.67 1.061 1.115 0.872 -0.273 -0.654 Chemical price -2.615 1.775 0.04 1.687 -0.514 0.767 Wage rate -0.407 0.274 0.046 -0.072 0.72 -0.136 Expected Yield and Yield Variation of Corn Yield of corn 0.622 0.239 -0.39 -0.11 -0.022 0.014 Variation of corn yield -0.223 0.395 -0.004 -0.05 -0.119 0.084 Land Characteristics Good land 0.077 -0.052 0.042 -0.009 -0.053 -0.057 Bad land -0.003 -0.009 -0.007 0.006 0.012 0.006 Slope 0.046 -0.016 -0.096 0.003 -0.043 0.098 Available water capacity -0.138 1.125 -0.094 -0.109 -0.248 -0.02 Organic matter -0.102 0.048 0.004 -0.033 0.075 0.024 Soil pH -0.361 -1.549 0.225 -0.009 -0.35 0.573 Coarse-textured soil -0.016 0.072 -0.011 -0.007 0.024 -0.007 Fine-textured soil 0.013 0.047 -0.026 0.002 0.016 -0.001 Weather Conditions Mean max temperature_corn -4.249 -8.719 4.697 -0.368 4.662 -1.65 Mean precipitation_corn -0.24 -0.813 1.085 0.426 0.982 -1.305 St. dev of precipitation_corn 0.609 3.762 -1.816 -0.122 -0.446 0.714 Mean of precipitation_wheat 0.511 7.801 -2.353 0.02 -0.256 0.053 St. dev of precipitation_wheat -1.105 -7.913 3.489 -0.135 -0.129 -0.727 Mean of snow_wheat -0.049 0.001 0.025 0.053 -0.004 -0.01 St. dev of snow_wheat 0.164 -0.041 -0.106 -0.152 0.055 0.049 aElasticities measure the percentage change in land use probability for a one-percent change in an explanatory variable, holding all else constant. Specifically, the elasticity of observing use i with respect to variable xij is: , where βj,x is the coefficient for variable xij. Thus, for example, the 0.269 elasticity for expected corn price in the corn equation indicates that a one-percent increase in expected corn price will increase the probability of observing corn by 0.269 percent. All elasticities are evaluated at the average of the data. Supplementary Results

Pasture Corn Soybeans/Sorghum Wheat/Hay 140 Historical +2oC 120 d o

i 100 r e

p 80 o r

d 60 y H 40

0 140 o o 120 +4 C +4 C and

d 10% Precip o i 100 r e

p 80 o r

d 60 y

H 40 20 0

Figure A3 Wetland hydroperiod predicted with WETLANDSCAPE across weather station locations and land uses given four climate scenarios (historical, +2°C, +4°C and +4°C with +10% precipitation). Hydroperiod is the average annual number of days a wetland is inundated