Quantifying Early Indicators of Global Climate Change
MetadataShow full item record
One of the more significant voids remaining in our scientific understanding of global climate change is the relationship between climate change and the resulting changes expected in ecological communities. Because a large proportion of the North American landscape has been modified by human activities, it is difficult to assess whether ecological changes are being caused by human activities or climate change. Thus, we must look to landscapes where the modification has been less severe. One of the most pristine landscapes in North America where scientists can study natural processes is that of the Greater Yellowstone Ecosystem. Within this system some of the more sensitive habitats are the montane meadows. These habitats exist along a continuum from very dry (xeric) sagebrush meadows, to flowering (mesic) meadows, to wet (hydric) sedge meadows. Because of the relatively short growing season, species in these meadows can exhibit quick changes in distribution and abundance relative to climatic changes. My research uses satellite images and field surveys to evaluate how meadow habitats and their associated species respond to interannual changes in precipitation and soil moisture. I am examining the plant and butterfly communities to measure the response. Over 100 species of butterflies occur in this area and many are closely associated with specific types of meadows. This research is significant because it will provide an early warning system for assessing the effects of climate change. Documenting changes in montane meadows will assist in understanding how climate change may affect more highly managed areas of the globe.
Debinski, Diane (2006) "Quantifying Early Indicators of Global Climate Change," University of Wyoming National Park Service Research Center Annual Report: Vol. 30 , Article 15.
Except where otherwise noted, this item's license is described as CC BY: This license lets you distribute, remix, tweak, and build upon this work, even commercially, as long as you credit the original creator for this work. This is the most accommodating of licenses offered. Recommended for maximum dissemination and use of licensed materials.