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Harvard Forest REU Symposium Abstract 2021

  • Title: Near-Term Forecasting in Carbon Flux
  • Author: Sarah S Sosa (Rowan University)
  • Abstract:

    Increasingly advancing ecology requires a fundamental shift, in thinking from measuring and monitoring, to using data to anticipate change, make predictions, and inform management actions. Near-term forecasts provide the opportunity to access the repetition of a computational procedure, iteratively, to perform analyses and predictions in light of new evidence. Eddy covariance is the methodology for measuring carbon dioxide exchange from the atmosphere, net ecosystem exchange; NEE. The SIPNET (Simplified Photosynthesis and Evapotranspiration model) measures terrestrial ecosystem carbon and water flux exchange. The primary objective of my project is to parameterize the SIPNET model for Harvard Forest. HF (HARV) is a terrestrial NEON field site located approximately 65 miles west of Boston, Massachusetts in the county of Worcester, represented as a typical northeastern rural/wildland. Whereas I studied five different NEON sites that were forecasted to depict each mathematical analysis trend of NEE. I found that from the beginning of July 5th to August 2nd, each site serving different biomes completed the similar trend, as the forecast period progressed, NEE in units of kgC/m^2 would exponentially decay. Revealing that CO2 uptake is actually concentrated in the growing season of June. The ability to forecast this month-long period is due to eddy’s hourly resolution and 16-35 day duration, and thus for any point in time we compare observations to predictions made 1 to 16 or more days in advance. These results suggest that the dynamics between NEE and transition season have a declining factor than forecast would during midseason.

  • Research Category: Soil Carbon and Nitrogen Dynamics; Forest-Atmosphere Exchange; Biodiversity Studies