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Harvard Forest Symposium Abstract 2010

  • Title: Canopy Phenology, Remote Sensing, and Microclimate
  • Primary Author: Mark Friedl (Boston University)
  • Additional Authors: Nathan Phillips (Boston University)
  • Abstract:

    Our research at the Harvard Forest walk-up tower site examines how seasonality of canopy leaf area, or canopy phenology, influences and is influenced by, local climate. As part of this activity we are specifically focusing on data collection supporting in-situ validation and calibration of remotely sensed canopy phenology. However, seasonal and interannual drivers and dynamics of canopy phenology are also of interest. To address these questions, we have initiated measurements to quantify how radiation fluxes through the forest canopy are modified by seasonal canopy leaf dynamics. We continuously measure above- and below-canopy radiation fluxes in the shortwave and radiation bands, and are also acquiring time series of digital photography. These measurements provide a surrogate measure of canopy leaf area dynamics, complement webcam and flux data collected at the adjacent EMS tower, and help to characterize diurnal and seasonal patterns in the solar radiation component of the surface energy balance. To supplement these measurements, we are also collecting sap flux, soil moisture and temperature data. These measurements will complement ongoing microclimate and eddy covariance measurements of water and carbon exchange at the EMS flux tower. This research also extends previous efforts examining ecohydrology and sap-flux dynamics by one of the co-investigators (Phillips). Light interception data have been collected for three growing seasons (2007-2009), with soil moisture, temperature and sap flux instrumentation installed in 2009. This project is ongoing and we anticipate continuing our data acquisition for at least two more growing seasons, and hopefully beyond. Analysis of data, assessment of environmental drivers and variability in phenology, and comparison with remote sensing data will occur as the data set time series is extended.

  • Research Category: Ecological Informatics and Modelling, Forest-Atmosphere Exchange, Physiological Ecology, Population Dynamics, and Species Interactions