Active and passive remote sensing of thresholds in arctic tundra vegetation structure and ecosystem function

Lee A. Vierling, University of Idaho, leev@uidaho.edu (Presenter)
Jan Eitel, University of Idaho, jeitel@uidaho.edu
Kevin Griffin, Columbia University, griff@ldeo.columbia.edu
Natalie Boelman, Columbia University, nboelman@ldeo.columbia.edu
Heather Greaves, University of Idaho, hgreaves@uidaho.edu
Case Prager, Columbia University, cmp2160@columbia.edu
Barry Logan, Bowdoin College, blogan@bowdoin.edu
Libby Fortin, Barnard College, eaf2143@barnard.edu
Ruthie Oliver, Columbia University, ryo2101@columbia.edu
Troy Magney, University of Idaho, tmagney@uidaho.edu

The Arctic is undergoing significant climatic warming, and North American Arctic tundra is already responding to warming with increased vegetation greenness in both spatial and temporal domains. In northern Alaska, this greening has at least in part resulted from recent increases in the size, abundance, and range of deciduous shrubs, mainly in valley bottoms and hillslopes—and there is mounting evidence that upland tundra will also respond strongly to warming via increased shrub dominance. Changes in canopy height and other ecosystem properties in response to greater shrub dominance can cause shifts in carbon pools and fluxes that may have far-reaching consequences. Habitat quality for local fauna is also likely to be affected in ways yet to be determined.

Quantifying fine-scale variation and change in shrub structure across the full continuum of shrub heights is therefore likely to reveal several important biophysical and ecological shifts occurring in Arctic tundra. Until recently, mapping variation in shrub density and height across the full range of Arctic shrub types has been challenging. Here, we present new findings that utilize fine-scale airborne lidar, terrestrial lidar, and passive hyperspectral remote sensing of tundra shrub structure to a) quantify aboveground pools of woody biomass and leaf area with low detection thresholds, and b) identify key thresholds for plant allocation of photosynthetic machinery in response to more complex plant architecture. Specifically, we have found that terrestrial lidar data allow us to quantify arctic shrub aboveground biomass with unprecedented accuracy even for very small shrubs (r2=0.92, RMSE=117g). This allows shrub LAI to also be estimated with very high accuracy because of strong allometric relationships between biomass and leaf area. Similar results are attainable using airborne lidar data. These structural datasets allow for new ray tracing models to link vegetation structure with observed variation in physiological function.

Presentation Type:  Poster

Session:  Theme 2: Landscapes to coasts: understanding Earth system connections   (Mon 1:30 PM)

Associated Project(s): 

• Vierling, Lee: Quantifying Thresholds in Arctic Tundra Vegetation Structure and Ecosystem Function Using LiDAR and Multispectral Remote Sensing ...details

Poster Location ID: 104