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Spatially distributed modeling of the long-term carbon balance of a boreal landscape

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  • Govind, Ajit
  • Chen, Jing Ming
  • Bernier, Pierre
  • Margolis, Hank
  • Guindon, Luc
  • Beaudoin, Andre

Abstract

Spatially and temporally distributed information on the sizes of biomass carbon (C) pools (BCPs) and soil C pools (SCPs) is vital for improving our understanding of biosphere–atmosphere C fluxes. Because the sizes of C pools result from the integrated effects of primary production, age-effects, changes in climate, atmospheric CO2 concentration, N deposition, and disturbances, a modeling scheme that interactively considers these processes is important. We used the InTEC model, driven by various spatio-temporal datasets to simulate the long-term C-balance in a boreal landscape in eastern Canada. Our results suggested that in this boreal landscape, mature coniferous stands had stabilized their productivity and fluctuated as a weak C-sink or C-source depending on the interannual variations in hydrometeorological factors. Disturbed deciduous stands were larger C-sinks (NEP2004=150gCm−2yr−1) than undisturbed coniferous stands (e.g. NEP2004=8gCm−2yr−1). Wetlands had lower NPP but showed temporally consistent C accumulation patterns. The simulated spatio-temporal patterns of BCPs and SCPs were unique and reflected the integrated effects of climate, plant growth and atmospheric chemistry besides the inherent properties of the C pool themselves. The simulated BCPs and SCPs generally compared well with the biometric estimates (BCPs: r=0.86, SCPs: r=0.84). The largest BCP biases were found in recently disturbed stands and the largest SCP biases were seen in locations where moss necro-masses were abundant. Reconstructing C pools and C fluxes in the ecosystem in such a spatio-temporal manner could help reduce the uncertainties in our understanding of terrestrial C-cycle.

Suggested Citation

  • Govind, Ajit & Chen, Jing Ming & Bernier, Pierre & Margolis, Hank & Guindon, Luc & Beaudoin, Andre, 2011. "Spatially distributed modeling of the long-term carbon balance of a boreal landscape," Ecological Modelling, Elsevier, vol. 222(15), pages 2780-2795.
  • Handle: RePEc:eee:ecomod:v:222:y:2011:i:15:p:2780-2795
    DOI: 10.1016/j.ecolmodel.2011.04.007
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    1. Ehsan Chowdhury & Quazi Hassan, 2013. "Use of remote sensing-derived variables in developing a forest fire danger forecasting system," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 67(2), pages 321-334, June.
    2. Govind, Ajit & Cowling, Sharon & Kumari, Jyothi & Rajan, Nithya & Al-Yaari, Amen, 2015. "Distributed modeling of ecohydrological processes at high spatial resolution over a landscape having patches of managed forest stands and crop fields in SW Europe," Ecological Modelling, Elsevier, vol. 297(C), pages 126-140.

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