Submitted to: Society for Range Management Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 11/25/2015
Publication Date: 1/31/2016
Citation: Levi, M.R., Bestelmeyer, B.T. 2016. Connecting long-term monitoring data from vegetation plots and remote sensing in the Southwestern USA [abstract]. 69th Annual Society for Range Management Meeting, January 31-February 4, 2016, Corpus Christi, Texas.
Technical Abstract: Understanding vegetation response to changing climate patterns is an important element of rangeland management and supports the use and development of ecological site descriptions. Monitoring of rangeland conditions with remote sensing can be misleading if ground measurements are not used to interpret changes in vegetation indices. We used a 25 year time series of Landsat normalized difference vegetation index (NDVI) to evaluate vegetation dynamics in the Malpai Borderlands Area of Arizona and New Mexico(~324,000 ha). The NDVI time series was decomposed into trend and seasonal variability to better understand spatial and temporal changes in vegetation dynamics across the region. Long-term vegetation monitoring plots and soil profile descriptions provided ground-based information to interpret patterns of NDVI. Monthly PRISM climate data were also used to interpret NDVI and vegetation dynamics. We compared changes in percent cover of plant functional types on a five year interval to the decomposed time series between measurements to elucidate causes of NDVI variability. Management practices across the time period are largely unknown; hence our interpretations reflect variable climate patterns and the effect of fires in the region. Preliminary results indicate a decrease in perennial grass cover in 2003 following a period of extreme regional drought . Perennial grass cover at most plots rebounded to pre-drought conditions or more perennial grass cover by 2008; however, some did not. We will present a detailed analysis of NDVI trends across the region and directly link changes in measured cover at monitoring locations to changes in NDVI and precipitation. Connecting NDVI time series data to point locations of measured cover values will advance interpretations of remotely sensed imagery for broad-scale assessments of rangeland condition and facilitate improved ecological site interpretation.