Few studies have analyzed the production of plant species at regional
scales in grassland ecosystems, due in part to limited availability of
data at large spatial scales. We used a dataset of rangeland surveys
to examine the productivities of 22 plant species throughout the Great
Plains of the United States with respect to three environmental facto
rs: temperature, precipitation and soil texture. Productivity of plant
species was obtained from Natural Resource Conservation Service (NRCS
) range site descriptions. We interpolated climate data from 296 weath
er stations throughout the region and used soil texture data from NRCS
State Soil Geographic (STATSGO) databases. We performed regression an
alyses to derive models of the relative and absolute production of eac
h species in terms of mean annual temperature (MAT), mean annual preci
pitation (MAP), and percentage SAND, SILT and CLAY. MAT was the most i
mportant factor for 55% of species analyzed; MAP was most explanatory
for 40% of the species, and a soil texture variable was most important
for only one species. Production of C-3 species tended to be negative
ly related to MAT, MAP and positively related to CLAY. Production of C
-4 shortgrasses, in general, was positively related to MAT and negativ
ely related to MAP and SAND, whereas C-4 tallgrass productivity tended
to be positively associated with MAP and SAND, and was highest at int
ermediate values of MAT. Our results indicate the extent to which func
tional types can be used to represent individual species. The regressi
on equations derived in this analysis can be important inclusions in m
odels that assess the effects of climate change on plant communities t
hroughout the region.