Upcoming Events | QUEST: Quantifying Uncertainty in Ecosystem Studies | ESF
e s f home link - e s f college of environmental science and forestry
e s f home link - e s f college of environmental science and forestry

Upcoming EventsQUEST

  • Hosting a workshop called "Introduction to Monte Carlo Error Propagation” at the ILTER Open Science Meeting 2019 in Leipzig, Germany.
  • 2019 ESA/USSEE Joint Meeting in Louisville, Kentucky presentations:
    • "How to avoid errors in error propagation: Monte Carlo estimation of uncertainty in forest biomass and stream loads at the Hubbard Brook Experimental Forest"
    • "Uncertainty in measurements of standing trees and downed coarse woody debris in the US Forest Service Forest Inventory and Analysis (FIA) program"
  • We submitted a session proposal to 2019 AGU.
    • Improving Estimates of Ecosystem Carbon Storage

      Quantifying carbon storage in terrestrial ecosystems remains challenging despite the need for strategic management of the global carbon balance. Forest biomass and forest soils can be highly heterogeneous and difficult to measure. Urban trees have been characterized using allometry from closed forests, which may result in bias. In agricultural systems, understanding the impact of land use practices on soil carbon changes remains a major research need. Fortunately, new technologies are improving estimates of natural variability, thereby reducing uncertainty. For example, terrestrial LiDAR can provide detailed characterization of live and dead wood pools. At the same time, methods for characterizing uncertainty in estimates are improving. This session will highlight studies that are aimed at understanding the uncertainty in terrestrial carbon stocks, including quantifying spatial variability. It will also highlight novel data sets and quantitative methods used in these characterizations.

 

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