OOS 68-1
Unraveling the mystery of dryland plant phenology through time and space with multi-scale remote sensing
Given the prominence of phenology as a salient indicator of plant responses to climate and the need to forecast shifts in phenology at landscape scales, it is critical to link mechanistic understanding of climate drivers with broad scale spatially-explicit depictions of forecasted plant responses to changes in climate. A multi-scale phenology study was initiated on the Jornada Basin LTER in southern New Mexico in 2010 to bridge phenology patterns at the plant level with those representing aggregated signals at the landscape level. The study integrates phenology observations collected in the field along with those collected via remotely using imagery from phenocams, unmanned aerial vehicles (UAVs), and satellite sensors such as Landsat and MODIS. We applied the Breaks for Additive Seasonal and Trend (BFAST) time series algorithm to MODIS 250-m NDVI greenness index values to partition the NDVI signal into components representing the long-term trend, seasonal periodicity, and residuals and identify significant shifts in the NDVI signal (i.e., “breaks”). To verify breaks representing significant deviations from the BFAST seasonal and trend models, we examined estimates of percent cover by plant functional group derived from UAV images collected between 2010 and 2014 and field-estimated plant biomass collected between 2000 and 2014.
Results/Conclusions
At a grassland site dominated by black grama (Bouteloua eriopoda), the BFAST algorithm detected four breaks in the trend model denoting significant increases in NDVI in May 2004, July 2006, and March 2010 and a significant decrease in May 2012. The 2004 and 2006 breaks corresponded to herbaceous vegetation responses to rainfall following prolonged periods of drought. The 2010 break coincides with increased perennial grass production following a sequence of record-breaking rainfall in 2006 and 2008. The 2012 decrease in NDVI corresponds to the marked reduction of herbaceous production following an exceptionally dry period in late 2010-2011. The seasonal breaks identified in July 2006 and September 2008 coincide with rapid increases in production of annual species in 2006 and perennial grasses in 2008. Seasonal breaks represented changes in the timing as well as the magnitude of NDVI that corresponded to shifts in the dominant plant functional group (i.e., annual versus perennial grasses). It was the combination of extensive spatially-explicit depictions of land surface characteristics from UAV imagery and geographically constrained long-term plot data that yielded compelling evidence to support ecologically meaningful interpretations of break points from moderate resolution MODIS NDVI using the BFAST algorithm in this water-limited grassland ecosystem.