Location: Range Management Research
Title: Bridging field observations and remotely sensed assessments of land surface phenology in the arid southwestern U.S. Authors
Submitted to: Ecological Society of America (ESA)
Publication Type: Abstract Only
Publication Acceptance Date: March 29, 2010
Publication Date: August 2, 2010
Citation: Browning, D.M., Rango, A., Anderson, J., Peters, D.C. 2010. Bridging field observations and remotely sensed assessments of land surface phenology in the arid southwestern U.S. [abstract]. 95th Ecological Society of America Meeting, August 1-6, 2010, Pittsburgh, Pennsylvania. PS 9-74. Technical Abstract: Strong seasonal patterns in vegetation greenness from TM reflected dynamics in aboveground plant biomass. TM-based responses in fall 2008 production to 2006 and 2008 above-average rainfall were consistent across all sites. The cumulative effect of 2006 and 2008 rainfall was most prominently reflected in biomass at mesquite-dominated sites. Biomass ranged widely over time and across sites (0.1 g m-2 to 422.2 g m-2). SAVI effectively tracked increases in biomass across all plant communities although values exhibited a low dynamic range across large differences in plant biomass. Field data regarding reproductive phenology constitute counts for given phenophases by species. Such measures of abundance are most informative to remotely sensed interpretations of phenology where there are clear dominant species. Nonetheless, the field perspective is historically unrivaled for highlighting species responses to climate drivers and is being evaluated further. The range in vegetation physiognomy and productivity at the JRN LTER is well-suited for field validation exercises for land surface phenology and retrieval of biophysical parameters via remote sensing. Plant responses to changes in climate (e.g., temperature and amount/seasonality of rainfall) manifest through phenological patterns. Therefore, field-tested protocols for monitoring plant phenology hold great promise for landscape monitoring and quantifying ecosystem responses to climate change.