Montane meadow communities can function as early indicators of change because they are highly sensitive to variations in precipitation and temperature. However, before an accurate estimation of directional change rates may be made with confidence, the seasonal and interannual rates of change inherent to a system must be quantified. We are using a time series of satellite multispectral imagery for monitoring the extent, condition, and spatial pattern of montane meadows in the Greater Yellowstone Ecosystem on a seasonal and interannual time scale. Spectrally-based, spatially-explicit models are being developed for six meadow types using a GIS to stratify the study area by topography and geology. The objectives of this research are to: 1) quantify the spatial and temporal variability in montane meadow communities; 2) develop a spectrally-based spatially-explicit model for predicting plant and animal species diversity patterns in montane meadows; and 3) test the spectrally-based spatially-explicit model for predicting plant and animal species diversity patterns in montane meadows. Field sampling is being used to collect data on the distribution of plant, bird, and butterfly species. We have sampled for two years in two regions of the ecosystem: the northern part of the ecosystem, hereafter termed the Gallatin study area, included the Gallatin National Forest and northwestern portion of Yellowstone National Park; the southern part of the ecosystem, hereafter termed Teton study area, included Grand Teton National Park. Twenty five sample sites were located in the Tetons and thirty sample sites were located in the Gallatins. Birds, butterflies, and plants were surveyed at each of the sites. The bird community showed a 47-59% similarity between the Gallatins and the Tetons. Bird species composition in the hydric meadow type was the most accurately predicted in both study areas. The butterfly community showed 60-65% similarity in species composition between the two sampling areas. If meadows were collapsed into three categories rather than five, meadow types at the two extremes of the gradient were 90-100% predictable while the mesic (middle gradient) meadow type was less easily predicted.

Funded by the Environmental Protection Agency, National Center for Environmental Research and Quality Assurance (NCERQA).

Diane Debinski, Ph.D., P.I.
Mark Jakubauskas, Ph.D., P.I.
Kelly Kindscher, Ph.D., P.I.

Mark Jakubauskas, Kelly Kindscher, and Diane Debinski at the University of Wyoming Research Station in Grand Teton National Park