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Biogeosciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/bg-2017-382
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-2017-382
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 29 Sep 2017

Submitted as: research article | 29 Sep 2017

Review status
This discussion paper is a preprint. It has been under review for the journal Biogeosciences (BG). The manuscript was not accepted for further review after discussion.

Diurnal, seasonal and long-term behaviour of high arctic tundra-heath ecosystem dynamics inferred from model ensembles constrained by time-integrated CO2 fluxes

Wenxin Zhang, Per-Erik Jansson, and Bo Elberling Wenxin Zhang et al.
  • Center for Permafrost (CENPERM), Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, DK - 1350 Copenhagen, Denmark

Abstract. Ecosystem CO2 fluxes in high Arctic are rather dynamic, as they are sensitive to climatic variability through multiple ecosystem processes, for instance, vegetation and snow dynamics as well as permafrost thawing, operating at different time scales. Uncertainties from both high-frequency measurements and model assumptions challenge model calibration to describe both short- and long-term phenomena related to weather and climate variabilities. In this study, we generated three model ensembles using a Monte-Carlo based uncertainty approach with acceptance criteria for 15 years of eddy covariance CO2 measurements of a high Arctic heath ecosystem based on the time-integrated CO2 fluxes within the day, the year and the entire period. The temporal distribution of residuals between the model and measurements indicated that the three model ensembles reasonably simulated diurnal, seasonal and long-term behaviours of CO2 fluxes respectively. The inter-annual variation of CO2 fluxes over 15 years showed the current ecosystem is at a transition from being a C sink to a C neutral balance. The long-term behaviour model ensemble simulated a more intensified diurnal C cycle than the short-term behaviour model ensembles. The intensified C cycle was mainly attributed to a faster depletion of the soil C pools. The sensitivities of posterior parameters to the model performance index (coefficient of determination, R2) reflected that parameters in the processes of soil water and heat transfer and snow dynamics regulated the short-term behaviour of CO2 fluxes, while parameters in the process of soil decomposition regulated the long-term behaviour of CO2 fluxes. Our results suggest that the development of ecosystem models should diagnose their effectiveness in capturing ecosystem CO2 exchange behaviour across different time scales. A clear trade-off may exist when the model is tuned to capture both the short- and long-term variation of CO2 fluxes. To constrain the model with the time-integrated CO2 fluxes is a simple and useful method to reduce the non-explained errors and to identify the crucial link to controlling parameters and processes.

Wenxin Zhang et al.
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Interactive discussion
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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Wenxin Zhang et al.
Wenxin Zhang et al.
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