KAS Symposium
Geospatial Analysis in the Great
Plains
Oral Presentation Title/Authors
USE OF REMOTELY SENSED DATA ON PHENOLOGICAL ACTIVITY AND
HETEROGENEITY TO DETECT CHANGES IN GRASSLAND SPECIES COMPOSITION
IN RESPONSE TO STRESS. John M. BRIGGS, Donna RIECH,
Clarence L. TURNER and Geoffrey M. HENEBRY, Division of Biology
Ackert Hall; Douglas G. GOODIN and M. Duane NELLIS, Department of
Geography, Dickens Hall, Kansas State University Manhattan, KS
66506.
Abstract
Prairie dominated by C3 vegetation exhibits two temporally
distinct pulses of activity (spring and fall); whereas, C4
vegetation has a single pulse of activity and maximum greenness
at midseason. This temporal segregation in C3 and C4 spectral
signatures has the potential to indicate the relative
contribution of these lifeforms to the regional flora in
tallgrass prairie. We are in the process of using this
information to develop an ecological indicator for the Flint
Hills in KS and OK. This ecological indicator is based on remote
sensing data (at present AVHRR) and detects both natural (e.g.
interannual variation in precipitation and temperature) and
anthropogenic (e.g. climate change, over-grazing, land-use
practices) stresses on grassland ecosystems. We hope that the
index will be applicable across larger geographic regions, such
as the Central Great Plains of North America. We are correlating
shifts in the timing of green-up and/or senescence with
meteorological data (from 117 weather stations) and land-use
practices to identify key variables that determine vegetation
response. The ability to detect vegetation shift using remote
sensing techniques can provide important information within an
environmental monitoring program.
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