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Harvard Forest Research Project 2024

• Title: Supporting Mature and Old Growth Forest Mapping with the Global Ecosystem Dynamics Investigation (GEDI) Waveform Lidar
• Principal investigator: Neil Pederson (neilpederson@fas.harvard.edu)
• Institution: Harvard Forest
• Primary contact: Neil Pederson (neilpederson@fas.harvard.edu)
• Team members: Erik Danielson
  Jillian Dyer
  Zachary Hart
  David Orwig
• Abstract:

  Without question structural characteristics are important metrics for the identification of Mature and Old-Growth Forests. However, the USFS MOGITT team identified age as one of the most important metrics in the metrics they would like to use in the identification of Mature and Old-Growth Forests. The Harvard Forest team will make two primary contributions in the identification of Mature and Old-Growth Forests within the GEDI-model workflow. First, we will contribute precise age structure and disturbance history information at the population or landscape level for 200+ forests to help train the GEDI-workflow. Precise age structures and nuanced disturbance histories will be inferred from at least 20-200 trees per population or landscape. Synthesizing forest dynamics through the age and growth patterns of trees reveals forest history, which will then be used to determine a forest’s developmental stage, such as Mature or Old Growth Forest. Excitingly, not all of our data are from old-growth forests. Nearly half are from forests that are between the tail end of stem-exclusion stage, like the long-term Lyford Plot at the Harvard Forest, a landscape that has been monitored decadally since 1969, or old mature forest, the step before the development of old-growth forest. These forests can have individually old trees, 150-300+ years, embedded in a matrix that was logged at various points in time over the prior 150 years of sampling. Age structure and growth histories of each tree help to define the disturbance history. These nuanced data will help guide modeling of remotely-sensed Mature and Old Growth Forests. When combined with FIA data, these will help define early- and late-stage Mature Forests, perhaps one of the largest uncertainties in understanding the development of forests.