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Global validation of a process-based model on vegetation gross primary production using eddy covariance observations.

Liu D, Cai W, Xia J, Dong W, Zhou G, Chen Y, Zhang H, Yuan W - PLoS ONE (2014)

Bottom Line: Our results indicated that the IBIS model explained 60% of the observed variation in daily GPP at all validation sites.Global mean GPP estimated by the IBIS model was 107.50±1.37 Pg C year(-1) (mean value ± standard deviation) across the vegetated area for the period 2000-2006, consistent with the results of the EC-LUE model (109.39±1.48 Pg C year(-1)).Using the inversed Vcmax values, the simulated global GPP increased by 16.5 Pg C year(-1), indicating that IBIS model is sensitive to Vcmax, and large uncertainty exists in model parameterization.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China.

ABSTRACT
Gross Primary Production (GPP) is the largest flux in the global carbon cycle. However, large uncertainties in current global estimations persist. In this study, we examined the performance of a process-based model (Integrated BIosphere Simulator, IBIS) at 62 eddy covariance sites around the world. Our results indicated that the IBIS model explained 60% of the observed variation in daily GPP at all validation sites. Comparison with a satellite-based vegetation model (Eddy Covariance-Light Use Efficiency, EC-LUE) revealed that the IBIS simulations yielded comparable GPP results as the EC-LUE model. Global mean GPP estimated by the IBIS model was 107.50±1.37 Pg C year(-1) (mean value ± standard deviation) across the vegetated area for the period 2000-2006, consistent with the results of the EC-LUE model (109.39±1.48 Pg C year(-1)). To evaluate the uncertainty introduced by the parameter Vcmax, which represents the maximum photosynthetic capacity, we inversed Vcmax using Markov Chain-Monte Carlo (MCMC) procedures. Using the inversed Vcmax values, the simulated global GPP increased by 16.5 Pg C year(-1), indicating that IBIS model is sensitive to Vcmax, and large uncertainty exists in model parameterization.

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Interannual variability in GPP derived from different models.Interannual variability in global mean gross primary production (GPP) derived from the IBIS, IBIS-Type and EC-LUE models.
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pone-0110407-g005: Interannual variability in GPP derived from different models.Interannual variability in global mean gross primary production (GPP) derived from the IBIS, IBIS-Type and EC-LUE models.

Mentions: The magnitude of GPP estimated by the IBIS and EC-LUE models were comparable, reaching 107.50±1.37 Pg C year−1 and 109.39±1.48 Pg C year−1 (mean value ± standard deviation) globally, respectively (Fig. 5). Two-model comparisons revealed consistent GPP estimations for the various PFTs (Table 3) with the exception of savanna, for which the IBIS model greatly underestimated GPP. The GPP estimate of the IBIS-Type scheme was much higher than those of the other two models, with a global value of 123.97±1.76 Pg C year−1 (Fig. 5). Larger GPP estimations using the IBIS-Type simulation were found for most biomes (Table 3).


Global validation of a process-based model on vegetation gross primary production using eddy covariance observations.

Liu D, Cai W, Xia J, Dong W, Zhou G, Chen Y, Zhang H, Yuan W - PLoS ONE (2014)

Interannual variability in GPP derived from different models.Interannual variability in global mean gross primary production (GPP) derived from the IBIS, IBIS-Type and EC-LUE models.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4222824&req=5

pone-0110407-g005: Interannual variability in GPP derived from different models.Interannual variability in global mean gross primary production (GPP) derived from the IBIS, IBIS-Type and EC-LUE models.
Mentions: The magnitude of GPP estimated by the IBIS and EC-LUE models were comparable, reaching 107.50±1.37 Pg C year−1 and 109.39±1.48 Pg C year−1 (mean value ± standard deviation) globally, respectively (Fig. 5). Two-model comparisons revealed consistent GPP estimations for the various PFTs (Table 3) with the exception of savanna, for which the IBIS model greatly underestimated GPP. The GPP estimate of the IBIS-Type scheme was much higher than those of the other two models, with a global value of 123.97±1.76 Pg C year−1 (Fig. 5). Larger GPP estimations using the IBIS-Type simulation were found for most biomes (Table 3).

Bottom Line: Our results indicated that the IBIS model explained 60% of the observed variation in daily GPP at all validation sites.Global mean GPP estimated by the IBIS model was 107.50±1.37 Pg C year(-1) (mean value ± standard deviation) across the vegetated area for the period 2000-2006, consistent with the results of the EC-LUE model (109.39±1.48 Pg C year(-1)).Using the inversed Vcmax values, the simulated global GPP increased by 16.5 Pg C year(-1), indicating that IBIS model is sensitive to Vcmax, and large uncertainty exists in model parameterization.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China.

ABSTRACT
Gross Primary Production (GPP) is the largest flux in the global carbon cycle. However, large uncertainties in current global estimations persist. In this study, we examined the performance of a process-based model (Integrated BIosphere Simulator, IBIS) at 62 eddy covariance sites around the world. Our results indicated that the IBIS model explained 60% of the observed variation in daily GPP at all validation sites. Comparison with a satellite-based vegetation model (Eddy Covariance-Light Use Efficiency, EC-LUE) revealed that the IBIS simulations yielded comparable GPP results as the EC-LUE model. Global mean GPP estimated by the IBIS model was 107.50±1.37 Pg C year(-1) (mean value ± standard deviation) across the vegetated area for the period 2000-2006, consistent with the results of the EC-LUE model (109.39±1.48 Pg C year(-1)). To evaluate the uncertainty introduced by the parameter Vcmax, which represents the maximum photosynthetic capacity, we inversed Vcmax using Markov Chain-Monte Carlo (MCMC) procedures. Using the inversed Vcmax values, the simulated global GPP increased by 16.5 Pg C year(-1), indicating that IBIS model is sensitive to Vcmax, and large uncertainty exists in model parameterization.

Show MeSH
Related in: MedlinePlus