4.7 Article

Leaf chlorophyll constraint on model simulated gross primary productivity in agricultural systems

出版社

ELSEVIER
DOI: 10.1016/j.jag.2015.03.016

关键词

Landsat; Leaf chlorophyll content; V-max; Leaf photosynthetic capacity; Community Land Model; Agriculture; Rubisco; Nitrogen

资金

  1. King Abdullah University of Science and Technology (KAUST)
  2. International Incoming Marie Curie fellowship
  3. AmeriFlux (U.S. Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program [DE-FG02-04ER63917, DE-FG02-04ER63911]
  4. CFCAS
  5. NSERC
  6. BIOCAP
  7. Environment Canada
  8. NRCan
  9. CarboEuropeIP
  10. FAO
  11. GTOS
  12. TCO
  13. iLEAPS
  14. Max Planck Institute for Biogeochemistry
  15. National Science Foundation
  16. University of Tuscia
  17. Universite Laval and Environment Canada
  18. US Department of Energy

向作者/读者索取更多资源

Leaf chlorophyll content (Chl(l)) may serve as an observational proxy for the maximum rate of carboxylation (V-max), which describes leaf photosynthetic capacity and represents the single most important control on modeled leaf photosynthesis within most Terrestrial Biosphere Models (TBMs). The parameterization of V-max is associated with great uncertainty as it can vary significantly between plants and in response to changes in leaf nitrogen (N) availability, plant phenology and environmental conditions. Houborg et al. (2013) outlined a semi-mechanistic relationship between V-max(25)(V-max normalized to 25 degrees C) and Chl(l) based on inter-linkages between V-max(25), Rubisco enzyme kinetics, N and Chl(l). Here, these relationships are parameterized for a wider range of important agricultural crops and embedded within the leaf photosynthesis-conductance scheme of the Community Land Model (CLM), bypassing the questionable use of temporally invariant and broadly defined plant functional type (PFT) specific V-max(25) values. In this study, the new Chl(l) constrained version of CLM is refined with an updated parameterization scheme for specific application to soybean and maize. The benefit of using in-situ measured and satellite retrieved Chl(l) for constraining model simulations of Gross Primary Productivity (GPP) is evaluated over fields in central Nebraska, U.S.A between 2001 and 2005. Landsat-based Chl(l) time-series records derived from the Regularized Canopy Reflectance model (REGFLEC) are used as forcing to the CLM. Validation of simulated GPP against 15 site-years of flux tower observations demonstrate the utility of Chl(l) as a model constraint, with the coefficient of efficiency increasing from 0.91 to 0.94 and from 0.87 to 0.91 for maize and soybean, respectively. Model performances particularly improve during the late reproductive and senescence stage, where the largest temporal variations in Chl(l) (averaging 35-55 mu g cm(-2) for maize and 20-35 mu g cm(-2) for soybean) are observed. While prolonged periods of vegetation stress did not occur over the studied fields, given the usefulness of Chl(l) as an indicator of plant health, enhanced GPP predictabilities should be expected in fields exposed to longer periods of moisture and nutrient stress. While the results support the use of Chit as an observational proxy for V-max(25), future work needs to be directed towards improving the Chl(l) retrieval accuracy from space observations and developing consistent and physically realistic modeling schemes that can be parameterized with acceptable accuracy over spatial and temporal domains. (C) 2015 Elsevier B.V. All rights reserved.

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