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Detecting early warning signals of tree mortality in the ABoVE domain using multi-scale satellite data

Brendan Morris Rogers, Woods Hole Research Center, brogers@whrc.org (Presenter)
Kylen Solvik, Woods Hole Research Center, ksolvik@whrc.org
Ted Hogg, Canadian Forest Service, ted.hogg@canada.ca
Junchang Ju, NASA Goddard Space Flight Center, junchang.ju@nasa.gov
Jeffrey Masek, NASA GSFC, jeffrey.g.masek@nasa.gov
Michael Michaelian, Canadian Forest Service, michael.michaelian@canada.ca
Logan Berner, Northern Arizona University, logan.berner@nau.edu
Scott J. Goetz, Northern Arizona University, scott.goetz@nau.edu

Increasing tree mortality from global change drivers such as drought and biotic infestations is a widespread phenomenon, including in the ABoVE domain where climate changes and feedbacks to the Earth system are relatively large. Despite the importance for science and management communities, our ability to forecast tree mortality at landscape to continental scales is limited. However, two independent information streams have the potential to inform and improve mortality forecasts: repeat forest inventories and satellite remote sensing. Time series of tree-level growth patterns indicate that productivity declines and related temporal dynamics often precede mortality years to decades before death. Plot-level productivity, in turn, has been related to satellite-based indices such as the Normalized Difference Vegetation Index (NDVI).

Here we link these two data sources to show that early warning signals of mortality are evident in several NDVI-based metrics up to 24 years before death. We focus on two repeat forest inventories and three NDVI products across the ABoVE domain where productivity and mortality dynamics are influenced by periodic drought. These data sources capture a range of forest conditions and spatial resolution to highlight the sensitivity and limitations of our approach. Overall, results indicate potential to use satellite NDVI for early warning signals of mortality. Relationships are broadly consistent across inventories, species, and spatial resolutions, although coarse-scale imagery in the heterogeneous aspen parkland was of limited utility. Longer-term NDVI data and annually re-measured sites with high mortality levels generate the strongest signals, although we still found robust relationships at sites re-measured at a typical five-year frequency. The approach and relationships developed here can be used as a basis for improving forest mortality models and monitoring systems.

Associated Project(s): 

Poster Location ID: 33

Session Assigned: Vegetation Dynamics and Distribution

 


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