Merging theory and remote sensing to predict whole forest functional type and biodiversity
Sydne Record, University of Maine, sydne.record@maine.edu (Presenter)
J. Marcos Rodriguez, University of Maine, mrodriguez@maine.edu
John M. Grady, University of Washington St. Louis, jmgrady@gmail.com
Jonathan Knott, United States Forest Service, jonathan.knott@usda.gov
Metabolic scaling theory (MST) explains the abundance and distribution of life on Earth through a general energetic framework. MST stipulates how energy use should scale positively with size, and how this metabolic scaling drives an inverse scaling of population density. Scaling rules in MST apply from the organ level (e.g., leaf respiration) all the way up to ecosystems (e.g., carbon flux), and thus have attracted interest as a predictive and unifying framework in ecology. However, the general rules of life laid out by Forest MST remain difficult to relate to biodiversity conservation. Our recent work in the tropics shows that life history frequency maps onto a size-mediated gradient of light intensity tied to functional traits for forests that meet the MST assumption of equilibrium dynamics (i.e., equal birth and death rates). This work provides a model for predicting whole forest functional type abundances and richness if only remotely sensed canopy information is known for forests. In this current work, we extend this framework to consider if disturbance can generate predictable deviations from MST in temperate forests.
We explore the application of this extended theory at Harvard Forest in Petersham, Massachusetts. This site is particularly data rich with high resolution canopy imagery and Light Detection and Ranging (LiDAR) data from the National Ecological Observatory Network, along with in-situ data from a 30-hectare Smithsonian ForestGEO Network plot and experimental logging manipulations implemented through the Long Term Ecological Research Network. Preliminary analyses indicate that predictions made from extending MST to incorporate non-equilibrium dynamics match empirical in-situ data. We also highlight how open data from various federal agencies will enable scaling of this extended MST framework to regional spatial scales.
Associated Project(s):
Poster Location ID: 1-35
Presentation Type: Poster
Session: Poster Session 1
Session Date: Tue (May 9) 5:00-7:00 PM
CCE Program: BDEC