Shrub biomass, net primary production, and canopy spectral imaging (NDVI) exhibit consistent correspondence across Arctic Tundra habitats.

Wednesday, 17 December 2014
Charles Elliot Flower1, Jeffrey M Welker2, Andy Anderson-Smith2, Niccole Van Hoey2, Christopher Whelan1 and Miquel A Gonzalez-Meler1, (1)University of Illinois at Chicago, Chicago, IL, United States, (2)University of Alaska Anchorage, Anchorage, AK, United States
Climate change is contributing to rapid vegetation shifts in the ecologically sensitive arctic tundra. These tussock grass dominated systems are shifting to tussock/woody shrub communities with cascading ecological and climate feedback consequences. This shifting vegetation composition should result in concomitant changes in carbon sequestration (net ecosystem exchange, NEE) and productivity which in turn could be manifested in “Greening” and changes in normalized difference vegetation index values (NDVI). In this study, we address the need to know the relationships between NDVI, leaf area, and shrub biomass, in part so that long-term trends in NDVI can be much more accurately interpreted as true changes in ecosystem C cycling processes. These relationships will enhance our ability to predict shifts in standing carbon mass, carbon cycling, and use historic satellite products to assess change. We sampled NEE, NDVI, leaf area and shrub (Betula spp. and Salix spp.) biomass across a shrub gradient in a dry heath and moist acidic tundra. The positive relationship between NDVI and NEE highlights the potential shifts in tundra carbon sequestration associated with woody vegetation shifts. Furthermore, strong positive linear relationships found among shrub biomass, species, leaf area, and NDVI in different tundra habitats should increase the robustness of spatial scaling. Increased productivity in sites with increased NDVI can provide a mechanism through which tundra ecosystems may respond to climate change. Improvements in our ability to detect relationships between above and belowground biomass for the dominant shrubs can strengthen our ability to predict standing biomass from satellite imagery.