Complementarity of flux- and biometric-based data to constrain parameters in a terrestrial carbon model
文献类型：SCI/SSCI论文
| 作者 | Du Z. G.; Nie, Y. Y.; He, Y. H.; Yu, G. R.; Wang, H. M.; Zhou, X. H. |
| 发表日期 | 2015 |
| 关键词 | complementarity net ecosystem exchange biometric data Bayesian inversion data assimilation Markov chain Monte Carlo deconvolution analysis data assimilation duke forest exchange soil co2 respiration uncertainty sequestration ecosystems |
| 英文摘要 | To improve models for accurate projections, data assimilation, an emerging statistical approach to combine models with data, have recently been developed to probe initial conditions, parameters, data content, response functions and model uncertainties. Quantifying how many information contents are contained in different data streams is essential to predict future states of ecosystems and the climate. This study uses a data assimilation approach to examine the information contents contained in flux- and biometric-based data to constrain parameters in a terrestrial carbon (C) model, which includes canopy photosynthesis and vegetation - soil C transfer submodels. Three assimilation experiments were constructed with either net ecosystem exchange (NEE) data only or biometric data only [including foliage and woody biomass, litterfall, soil organic C(SOC) and soil respiration], or both NEE and biometric data to constrain model parameters by a probabilistic inversion application. The results showed that NEE data mainly constrained parameters associated with gross primary production (GPP) and ecosystem respiration (RE) but were almost invalid for C transfer coefficients, while biometric data were more effective in constraining C transfer coefficients than other parameters. NEE and biometric data constrained about 26% (6) and 30% (7) of a total of 23 parameters, respectively, but their combined application constrained about 61% (14) of all parameters. The complementarity of NEE and biometric data was obvious in constraining most of parameters. The poor constraint by only NEE or biometric data was probably attributable to either the lack of long-term C dynamic data or errors from measurements. Overall, our results suggest that flux- and biometric-based data, containing different processes in ecosystem C dynamics, have different capacities to constrain parameters related to photosynthesis and C transfer coefficients, respectively. Multiple data sources could also reduce uncertainties in parameter estimation if these data sources contain complementary information. |
| 出处 | Tellus Series B-Chemical and Physical Meteorology |
| 卷 | 67 |
| 语种 | 英语 |
| ISSN号 | 0280-6509 |
| DOI标识 | 10.3402/tellusb.v67.24102 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/43518]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Du Z. G.,Nie, Y. Y.,He, Y. H.,et al. Complementarity of flux- and biometric-based data to constrain parameters in a terrestrial carbon model. 2015. |
入库方式： OAI收割
来源：地理科学与资源研究所
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