Linking ground observations, simulation model output, and remote sensing data to characterize phenology across diverse arid landscapes

TitleLinking ground observations, simulation model output, and remote sensing data to characterize phenology across diverse arid landscapes
Publication TypeConference Paper
Year of Publication2007
AuthorsAnderson JP, Peters DC, Rango A., Steele C
Conference NameAmerican Society of Photogrammetry and Remote Sensing Meetings
Date PublishedOctober 5, 2007
ARIS Log Number215804
KeywordsChihuahuan Desert, phenology, remote sensing, simulation
AbstractWe combined long-term data on plant phenology with simulation modeling output and remote sensing data to characterize diverse landscapes at the Jornada Experimental Range in the northern Chihuahuan Desert of southern New Mexico. Phenology of 15 key species in Chihuahuan Desert plant communities have been monitored monthly for 15 sites since 1992. Phenological state (non-reproductive, in bud, in flower, dormant) is noted for all plants of selected grass and shrub species at three replicate sites of five major plant communities (upland grasslands, playa grasslands, creosotebush shrublands, mesquite shrublands, tarbush shrublands). We combined these long-term data with simulation model results of key species to extrapolate back in time and to forecast future dynamics under a changing climate. We used a daily timestep model of soil water dynamics (SOILWAT) to simulate recruitment of the dominant grass for the entire Jornada Basin. We also compared the long-term data with remotely sensed images through time for one year from the ASTER satellite. The ability of the ASTER images to sense phonological changes varied by community type. Linking different technologies has great potential for improving understanding and prediction for arid landscapes that vary both temporally and spatially.