B11C-0441: Timing is everything: using near-surface and remote sensing to monitor vegetation phenology in sagebrush steppe
Authors: Geneva Chong1, Heidi Steltzer3, Rick Shory2, Anika Petach4, Matthew D Wallenstein2
Author Institutions: 1. Northern Rocky Mt. Science Center, US Geological Survey, Jackson, WY, USA; 2. Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, USA; 3. Department of Biology, Fort Lewis College, Durango, CO, USA; 4. Harvard University, Cambridge, MA, USA
Climate change models for the north ¬ern Rocky Mountains predict changes in temperature and water availability that in turn may alter vegetation. Changes to vegetation may include timing of plant life-history events, or phenology, such as green-up, flower ¬ing and senescence, and shifts in species composition. Moreover, climate changes may favor some species, such as non ¬native, annual grasses over native species. Changes in vegetation could make forage for ungulates, sage-grouse, and livestock available earlier in the growing season, but could also result in earlier senescence (die-off or dormancy) and reduced overall production. The normalized difference vegetation index (NDVI) is regularly used to quantify greenness over large areas using remotely sensed reflectance data. The timing and scale of data collection, however, may be insufficient to capture fine-scale differences in phenology that are important indicators of habitat quality. We used data from near-surface light sensors to construct NDVI curves in native sagebrush vegetation with and without herbicide application for reducing non-native cheatgrass. We fit piecewise linear models to the data to compare characteristics of near-surface NDVI curves such as rate of green-up and duration of maximum greenness. Treated, inter-space areas had a later onset of peak season, but longer duration of greenness (greater productivity) than untreated inter-space. Sagebrush shrubs maintained relatively high greenness throughout the snow-free season. We compared our near-surface NDVI curves to curves constructed using remotely sensed data both locally (9 cell neighborhood) and regionally (southwest Wyoming) to identify the lag between actual green-up and green-up detected remotely and differences in the shapes of the NDVI curves. Understanding phenology and productivity at fine scales can help guide resource management decisions related to habitat quality, and monitoring changes in phenology and productivity over the long-term can provide insight into ecosystem responses to climate change.