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Sensitivity of modeled NEP to climate forcing and soil at site and regional scales: Implications for upscaling ecosystem models

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  • Mekonnen, Zelalem A.
  • Grant, Robert F.
  • Schwalm, Christopher

Abstract

The quality of gridded weather and soil datasets is one of the main sources of uncertainty in modeling regional scale land-atmosphere carbon exchange. This uncertainty may be assessed by comparing net ecosystem productivity (NEP) modeled for selected grid cells with these datasets against NEP modeled at representative sites within that grid cell for which detailed site scale measurements of weather and soil are available. In this study, a comprehensive mathematical ecosystem model, ecosys, was used to simulate differences in NEP at six eddy covariance (EC) flux tower sites across North America caused by using inputs for weather and soil extracted from 0.25°×0.25° gridded datasets for the grid cells within which the towers were located vs. those measured at each tower site during years with contrasting weather (cool vs. warm and wet vs. dry). NEP differences attributed to gridded vs. measured model inputs varied among sites when tested against EC-derived values. At some sites (e.g. coastal coniferous site in British Columbia), adverse impacts of summer warming on NEP under contrasting weather in 2001 (cooler) vs. 2004 (warmer) were accurately modeled with both inputs, giving R2 with EC NEP values >0.80. At other sites, reduced accuracy in NEP modeled with gridded vs. measured inputs was attributed to shallower soil depth in the gridded soil database. This shallower depth caused site NEP in a boreal deciduous stand in Saskatchewan not to be well simulated in 2001 and 2003, the first and third years of a major drought in central North America, due to early soil drying. At yet other sites, reduced accuracy was attributed to overestimates of soil organic nitrogen (SON) calculated from general soil organic carbon (SOC):SON relationships used in the absence of SON values in the gridded soil database. These overestimates caused excessive productivity to be modeled with gridded inputs at a boreal black spruce site in Quebec with unusually large SOC:SON. Gridded weather and soil inputs that caused such differences in NEP would certainly affect regional and global carbon budget model estimates, and so need to be improved in future large scale model input datasets.

Suggested Citation

  • Mekonnen, Zelalem A. & Grant, Robert F. & Schwalm, Christopher, 2016. "Sensitivity of modeled NEP to climate forcing and soil at site and regional scales: Implications for upscaling ecosystem models," Ecological Modelling, Elsevier, vol. 320(C), pages 241-257.
  • Handle: RePEc:eee:ecomod:v:320:y:2016:i:c:p:241-257
    DOI: 10.1016/j.ecolmodel.2015.10.004
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    References listed on IDEAS

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    1. Seidl, Rupert & Rammer, Werner & Scheller, Robert M. & Spies, Thomas A., 2012. "An individual-based process model to simulate landscape-scale forest ecosystem dynamics," Ecological Modelling, Elsevier, vol. 231(C), pages 87-100.
    2. Grant, R.F., 2014. "Nitrogen mineralization drives the response of forest productivity to soil warming: Modelling in ecosys vs. measurements from the Harvard soil heating experiment," Ecological Modelling, Elsevier, vol. 288(C), pages 38-46.
    3. Huntzinger, D.N. & Post, W.M. & Wei, Y. & Michalak, A.M. & West, T.O. & Jacobson, A.R. & Baker, I.T. & Chen, J.M. & Davis, K.J. & Hayes, D.J. & Hoffman, F.M. & Jain, A.K. & Liu, S. & McGuire, A.D. & N, 2012. "North American Carbon Program (NACP) regional interim synthesis: Terrestrial biospheric model intercomparison," Ecological Modelling, Elsevier, vol. 232(C), pages 144-157.
    4. Sasai, T. & Okamoto, K. & Hiyama, T. & Yamaguchi, Y., 2007. "Comparing terrestrial carbon fluxes from the scale of a flux tower to the global scale," Ecological Modelling, Elsevier, vol. 208(2), pages 135-144.
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