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Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

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  • Wang, Z.
  • Grant, R.F.
  • Arain, M.A.
  • Chen, B.N.
  • Coops, N.
  • Hember, R.
  • Kurz, W.A.
  • Price, D.T.
  • Stinson, G.
  • Trofymow, J.A.
  • Yeluripati, J.
  • Chen, Z.

Abstract

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July–September (Tamax) in all process models (R2=0.4–0.6), indicating that these correlations were robust. The negative correlation between Tamax and NEP was attributed to different processes in different models, which were tested by comparing CO2 fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (Ta). The general agreement in sensitivity of annual NPP to Tamax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′=NPP−57.1 (Tamax−18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July–September, and Tamax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to Tamax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.

Suggested Citation

  • Wang, Z. & Grant, R.F. & Arain, M.A. & Chen, B.N. & Coops, N. & Hember, R. & Kurz, W.A. & Price, D.T. & Stinson, G. & Trofymow, J.A. & Yeluripati, J. & Chen, Z., 2011. "Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison," Ecological Modelling, Elsevier, vol. 222(17), pages 3236-3249.
    • Handle: RePEc:eee:ecomod:v:222:y:2011:i:17:p:3236-3249
    DOI: 10.1016/j.ecolmodel.2011.06.005
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    1. W. Kurz & M. Apps, 2006. "Developing Canada's National Forest Carbon Monitoring, Accounting and Reporting System to Meet the Reporting Requirements of the Kyoto Protocol," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 11(1), pages 33-43, January.
    2. Kurz, W.A. & Dymond, C.C. & White, T.M. & Stinson, G. & Shaw, C.H. & Rampley, G.J. & Smyth, C. & Simpson, B.N. & Neilson, E.T. & Trofymow, J.A. & Metsaranta, J. & Apps, M.J., 2009. "CBM-CFS3: A model of carbon-dynamics in forestry and land-use change implementing IPCC standards," Ecological Modelling, Elsevier, vol. 220(4), pages 480-504.
    3. Valerie A. Barber & Glenn Patrick Juday & Bruce P. Finney, 2000. "Reduced growth of Alaskan white spruce in the twentieth century from temperature-induced drought stress," Nature, Nature, vol. 405(6787), pages 668-673, June.
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    2. Wang, Z. & Grant, R.F. & Arain, M.A. & Bernier, P.Y. & Chen, B. & Chen, J.M. & Govind, A. & Guindon, L. & Kurz, W.A. & Peng, C. & Price, D.T. & Stinson, G. & Sun, J. & Trofymowe, J.A. & Yeluripati, J., 2013. "Incorporating weather sensitivity in inventory-based estimates of boreal forest productivity: A meta-analysis of process model results," Ecological Modelling, Elsevier, vol. 260(C), pages 25-35.
    3. Shaw, C.H. & Hilger, A.B. & Metsaranta, J. & Kurz, W.A. & Russo, G. & Eichel, F. & Stinson, G. & Smyth, C. & Filiatrault, M., 2014. "Evaluation of simulated estimates of forest ecosystem carbon stocks using ground plot data from Canada's National Forest Inventory," Ecological Modelling, Elsevier, vol. 272(C), pages 323-347.

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