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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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Comparison of estimated and observed soil water.Daily variation in the estimated soil water fraction of the IBIS model (i.e., fraction of soil pore space containing liquid water) and in the observed soil water content at EC sites. The solid lines represent simulation data, and the dotted lines represent the observed data.
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pone-0110407-g006: Comparison of estimated and observed soil water.Daily variation in the estimated soil water fraction of the IBIS model (i.e., fraction of soil pore space containing liquid water) and in the observed soil water content at EC sites. The solid lines represent simulation data, and the dotted lines represent the observed data.

Mentions: These particular ecosystem properties result in greater complexity of modeling fluxes [37]. Process-based models need to simulate variation in soil moisture and plant phenology. However, previous studies have identified significant biases when simulating soil moisture [38]. We examined the performance of the IBIS on soil water at the savanna sites and also found obvious differences between the simulated values and the EC measurements (Fig. 6). Moreover, the IBIS integrated temperature-dominated phenology algorithms developed by Botta et al. [39]. However, field studies suggest that for many drought-deciduous species, the first large precipitation event at the start of the rainy season initiates rapid leaf flush [40]–[41], and leaf senescence is closely related to soil water availability in the dry season [41]–[42]. This relationship may explain why the IBIS model did not effectively capture the variance in GPP at savanna sites.


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)

Comparison of estimated and observed soil water.Daily variation in the estimated soil water fraction of the IBIS model (i.e., fraction of soil pore space containing liquid water) and in the observed soil water content at EC sites. The solid lines represent simulation data, and the dotted lines represent the observed data.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0110407-g006: Comparison of estimated and observed soil water.Daily variation in the estimated soil water fraction of the IBIS model (i.e., fraction of soil pore space containing liquid water) and in the observed soil water content at EC sites. The solid lines represent simulation data, and the dotted lines represent the observed data.
Mentions: These particular ecosystem properties result in greater complexity of modeling fluxes [37]. Process-based models need to simulate variation in soil moisture and plant phenology. However, previous studies have identified significant biases when simulating soil moisture [38]. We examined the performance of the IBIS on soil water at the savanna sites and also found obvious differences between the simulated values and the EC measurements (Fig. 6). Moreover, the IBIS integrated temperature-dominated phenology algorithms developed by Botta et al. [39]. However, field studies suggest that for many drought-deciduous species, the first large precipitation event at the start of the rainy season initiates rapid leaf flush [40]–[41], and leaf senescence is closely related to soil water availability in the dry season [41]–[42]. This relationship may explain why the IBIS model did not effectively capture the variance in GPP at savanna sites.

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