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Harvard Forest Symposium Abstract 2015

  • Title: Quantifying the size and temporal dynamics of nonstructural carbon in temperate forest trees
  • Primary Author: Morgan Furze (Harvard University)
  • Additional Authors: Donald Aubrecht (Harvard University); Mariah Carbone (NCEAS); Brett Huggett (Bates College); Andrew Richardson (Northern Arizona University); Claire Stolz (Harvard University)
  • Abstract:

    Like all woody plants, trees store nonstructural carbon (NSC), primarily consisting of sugars and starch, as reserves to support growth and metabolism. Trees can draw on these reserves in order to cope with times of stress, including exposure to drought, pests and disease, disturbance, and climate extremes. Thus, NSC is important for predicting forest ecosystem responses to global climate change. Yet, large knowledge gaps exist regarding the size and turnover of NSC as well as the representation of allocation and storage processes in models, both contributing to uncertainty in forecasts of future atmospheric CO2 inputs by forest ecosystems

    The primary objective of this work is to construct whole-tree budgets and seasonal cycles of NSC in temperate forest trees in New England. Monthly field sampling at Harvard Forest along with laboratory analyses will allow for the quantification of NSC in foliage, branch, stemwood, and root tissues, which will then be scaled up to determine whole-tree and whole-ecosystem NSC budgets. Data from 2014 indicate that in all species (red oak, red maple, paper birch, white ash, and white pine), sugar concentrations in branch tissue (3-5y) were lower in the growing season than in the dormant season, with sugar generally increasing from August to December. Starch concentrations peaked in October and then sharply declined to December, with the exception of white pine, which exhibited a maximum starch concentration in June, followed by a steady decline onward. Additional concentration data are currently being obtained to resolve these seasonal patterns.

    In 2015, we will expand our sampling for radiocarbon analysis to estimate turnover time (i.e. mean age) of NSC stored in different tissues, and to better understand mixing between new and old NSC. These data will be used to test a multi-pool model representation of storage in forest trees. Using this data to improve models of tree carbon dynamics will enhance our understanding of the capacity for trees to tolerate abiotic and biotic stressors as well as our ability to predict forest responses to global change factors.

  • Research Category: Biodiversity Studies; Conservation and Management; Ecological Informatics and Modelling; Forest-Atmosphere Exchange; Physiological Ecology, Population Dynamics, and Species Interactions