|At 13,400 km in length, the Forest Tundra Ecotone (FTE) is the world’s largest ecological transition zone. However, little is known about how the FTE – a critical component of the ABoVE study domain – will respond to ever-increasing environmental change. Remotely sensed information could play a key role in filling portions of this critical knowledge gap, yet relatively little remote sensing work has been conducted to link the current structural status of the FTE with dynamic changes in its ecological function. The overarching objective of our NASA funded research is to integrate LiDAR, passive spectral, and tree ecophysiological data to link biophysical structure to ecological function in the FTE. In so doing, we will be able to remotely assess the vulnerability and resilience of the FTE to environmental change. To characterize FTE structure, we will use LiDAR to create standardized baseline data at multiple locations within the FTE of the ABoVE study domain, and benchmark our results relative to the existing FTE-wide map developed by Ranson et al. (2011) using MODIS and Landsat. We will establish transects at FTE sites in Alaska and Canada to study how LiDAR derived surface and canopy micro-structure affect: (1) air and soil temperature, (2) snowpack dynamics (via hyper-temporal terrestrial LiDAR), (3) net radiation throughout the FTE canopy and on the FTE floor (via a radiative transfer model parametrized using structural information from LiDAR), and (4) plant function (via the use of ground-based radiometers coupled with ecophysiological measurements). By using statistical modeling approaches, these datasets will allow us to determine mechanistic relationships among FTE structure, physical growth environment, and plant function at fine spatial scale, where critical changes in individual tree performance aggregate to drive overall long-term change trajectories of the FTE. Ultimately, this will allow us to determine the suitability of remotely sensed micro-structural information as a proxy for assessing the vulnerability and resilience of the FTE to environmental change while understanding the mechanisms that underlie such a remote sensing approach. The outcome of this study will advance our ability to remotely sense FTE structure and function, which in turn will be of key importance for accurately predicting impacts of environmental change on ecosystem services within the ABoVE study domain and beyond.
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