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Harvard Forest Symposium Abstract 2006

• Title: Canopy Nitrogen and Forest Carbon Assimilation: Validation of Local Patterns and Broad-Scale Satellite Estimates
• Primary Author: Scott Ollinger (University of New Hampshire - Main Campus)
• Additional Authors: Julian Jenkins (University of New Hampshire - Main Campus); Mary Martin (University of New Hampshire - Main Campus); J. William Munger (Harvard University); Lucie Plourde (University of New Hampshire - Main Campus); Marie-Louise Smith (USDA Forest Service)
• Abstract:

  Understanding patterns of carbon assimilation in temperate forests is important for a number of scientific and policy issues. Locally, estimates are needed to address land management issues ranging from timber harvesting to preservation of ecosystem diversity. Globally, forests play an important role in the earth’s carbon cycle and are believed to represent an important sink for atmospheric CO2. The importance of understanding variation through space and time stems from the need to scale site-level measurements to their broader surrounding regions and to identify underlying mechanisms responsible for observed ecosystem behavior. We have been examining the degree to which canopy nitrogen chemistry can serve as an integrator of C flux patterns in northern temperate forests. The functional basis for using foliar N as a scalar of C uptake lies in the fact that the proteins responsible for CO2 capture by leaves (e.g. rubisco) account for the majority of nitrogen in plant canopies.
  
  
  
  
  
  In previous studies at Harvard Forest, we have examined the degree to which temporal variation in foliar N, as measured on the control plots at the chronic N study, can improve model estimates of gross primary productivity (GPP) relative to observations from the Harvard Forest deciduous forest eddy covariance tower. Here, we present evidence suggesting that foliar N also explains an important fraction of the spatial variation in GPP and forest productivity across the broader surrounding landscape. First, we used field data for aboveground net primary productivity (ANPP) collected on plots located across Harvard Forest by the Bigfoot project (Turner et al. 2003) to evaluate the relative importance of foliar N versus leaf area index (LAI) on observed patterns of forest productivity. Second, we used a 2002 scene from NASA''s high spectral resolution Hyperion sensor to map spatial patterns in foliar N (percent by foliar mass) at 30m spatial resolution across Harvard Forest. Third, we used these data as input to the PnET forest ecosystem model to generate spatial estimates of GPP.
  
  
  
  
  
  Numerous attempts to estimate spatial patterns in forest growth have operated under the assumption that LAI is a strong controlling variable and have, therefore, focused on remote sensing of LAI. Here, we observed no correlation between measured ANPP and LAI, but a significant positive correlation between ANPP and foliar N concentration (Figure 1). In conjunction with previous results from Harvard Forest, this suggests that foliar N exerts an important influence on forest carbon uptake over both space and time.
  
  
  
  
  
  Lastly, we used the maps of foliar N and forest GPP to validate GPP estimates from the Moderate resolution Imaging Spectroradiometer (MODIS) satellite (Figure 2). This was achieved by aggregating the high resolution GPP model estimates to 1 km resolution, which facilitated a pixel-by-pixel comparison with MODIS. MODIS GPP ranged from 12-24% below the PnET estimates and the degree of disagreement was correlated with %N, even when aggregated to 1 km resolution.
  
  
  
  
  
  Reference:
  
  
  Turner, D.P., W.D. Ritts, W.B. Cohen, S.T. Gower, M. Zhao, S.W. Running S.C. Wofsy, S. Urbanski, A. Dunn, and J.W. Munger. 2003. Scaling gross primary production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation. Remote Sensing of Environment 88:256-270.
  
  
  

• Research Category: Forest-Atmosphere Exchange
  Regional Studies