PRODUCTIVITY PATTERNS OF C3AND C4FUNCTIONAL TYPES IN THE U.S. GREAT PLAINS

Abstract

We analyzed the productivity of C3 and C4 grasses throughout the Great Plains of the United States in relation to three environmental factors: mean annual tem- perature, mean annual precipitation, and soil texture. Productivity data were collected from Natural Resource Conservation Service (NRCS) rangeland survey data. Climate data were interpolated from weather stations throughout the region. Soil texture data were obtained from NRCS State Soil Geographic (STATSGO) databases. A geographic information system was used to integrate the three data sources. With a data set of spatially random points, we performed stepwise multiple regression analyses to derive models of the relative and absolute production of C3 and C4 grasses in terms of mean annual temperature (MAT), mean annual precipitation (MAP), percentage sand (SAND), and percentage clay (CLAY). MAT, MAP, and soil texture explained 67-81% of the variation in relative and absolute production of C3 and C4 grasses. Both measures of production of C3 grasses were negatively related to MAT and SAND, and positively related to CLAY. Relative production of C3 grasses decreased whereas absolute production of C3 grasses increased with MAP. Produc- tion of C4 grasses was positively related to MAT, MAP, and SAND, and negatively related to CLAY. MAP was the most explanatory variable in the model for C4 absolute production. MAT was the most explanatory variable in the three other models. Based on these regression models, C3 grasses dominate 35% of the Great Plains under current climatic conditions, mainly north of Colorado and Nebraska. Under a 20C increase in MAT, C3 grasses recede northward and retain dominance in only 19% of the region. MAT, MAP, and soil texture are important variables in explaining the abundance and dis- tribution of C3 and C4 grasses in the Great Plains. Accordingly, these variables will be important under changing CO2 and climatic forcings.