Skip to main content
padlock icon - secure page this page is secure

Open Access Evaluating the effect of alternative carbon allocation schemes in a land surface model (CLM4.5) on carbon fluxes, pools, and turnover in temperate forests

Download Article:

The full text article is available externally.

The article you have requested is supplied via the DOAJ. View from original source.

How carbon (C) is allocated to different plant tissues (leaves, stem, and roots) determines how long C remains in plant biomass and thus remains a central challenge for understanding the global C cycle. We used a diverse set of observations (AmeriFlux eddy covariance tower observations, biomass estimates from tree-ring data, and leaf area index (LAI) measurements) to compare C fluxes, pools, and LAI data with those predicted by a land surface model (LSM), the Community Land Model (CLM4.5). We ran CLM4.5 for nine temperate (including evergreen and deciduous) forests in North America between 1980 and 2013 using four different C allocation schemes:

i. dynamic C allocation scheme (named "D-CLM4.5") with one dynamic allometric parameter, which allocates C to the stem and leaves to vary in time as a function of annual net primary production (NPP);

ii. an alternative dynamic C allocation scheme (named "D-Litton"), where, similar to (i), C allocation is a dynamic function of annual NPP, but unlike (i) includes two dynamic allometric parameters involving allocation to leaves, stem, and coarse roots;

iii.–iv. a fixed C allocation scheme with two variants, one representative of observations in evergreen (named "F-Evergreen") and the other of observations in deciduous forests (named "F-Deciduous").

D-CLM4.5 generally overestimated gross primary production (GPP) and ecosystem respiration, and underestimated net ecosystem exchange (NEE). In D-CLM4.5, initial aboveground biomass in 1980 was largely overestimated (between 10 527 and 12 897 g C m−2) for deciduous forests, whereas aboveground biomass accumulation through time (between 1980 and 2011) was highly underestimated (between 1222 and 7557 g C m−2) for both evergreen and deciduous sites due to a lower stem turnover rate in the sites than the one used in the model. D-CLM4.5 overestimated LAI in both evergreen and deciduous sites because the leaf C–LAI relationship in the model did not match the observed leaf C–LAI relationship at our sites. Although the four C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, D-Litton gave more realistic Cstem ∕ Cleaf ratios and strongly reduced the overestimation of initial aboveground biomass and aboveground NPP for deciduous forests by D-CLM4.5. We identified key structural and parameterization deficits that need refinement to improve the accuracy of LSMs in the near future. These include changing how C is allocated in fixed and dynamic schemes based on data from current forest syntheses and different parameterization of allocation schemes for different forest types.

Our results highlight the utility of using measurements of aboveground biomass to evaluate and constrain the C allocation scheme in LSMs, and suggest that stem turnover is overestimated by CLM4.5 for these AmeriFlux sites. Understanding the controls of turnover will be critical to improving long-term C processes in LSMs.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Document Type: Research Article

Affiliations: 1: School of Natural Resources and the Environment, University of Arizona, Tucson, Arizona, 85721, USA 2: Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, Arizona, 85721, USA 3: Laboratory of Tree-Ring Res., University of Arizona, Tucson, Arizona, 85721, USA 4: Department of Geology and Geography, West Virginia University, Morgantown, West Virginia, 26506, USA 5: Division of Biology and Paleo Environment, Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York, 10964, USA 6: Dendro Sciences Unit, Swiss Federal Research Institute WSL, Zürcherstrasse 111, 8903 Birmensdorf, Switzerland 7: W. Szafer Institute of Botany, Polish Academy of Sciences, ul. Lubicz 46, 31-512 Krakow, Poland 8: Harvard Forest, Harvard University, Petersham, Massachusetts, 01366, USA 9: Department of Geography, University of Colorado, Boulder, Colorado, 80309, USA 10: Department of Civil, Environmental, and Geodetic Engineering, The Ohio State University, Columbus, Ohio, 43210, USA 11: Department of Biology, Virginia Commonwealth University, Richmond, Virginia, 23284, USA 12: Department of Biology, University of New Mexico, Albuquerque, New Mexico, 87131, USA 13: School of Public and Environmental Affairs, Indiana University, Bloomington, Indiana, 47405, USA 14: Department of Biology, Indiana University, Bloomington, Indiana, 47405, USA 15: School of Natural Resources, University of Missouri, Columbia, Missouri, 65211, USA

Publication date: January 1, 2017

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more