Academic Journal
A two-stage light-use efficiency model for improving gross primary production estimation in agroecosystems
| العنوان: | A two-stage light-use efficiency model for improving gross primary production estimation in agroecosystems |
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| المؤلفون: | Huang, Lingxiao, Lin, Xiaofeng, Jiang, Shouzheng, Liu, Meng, Jiang, Yazhen, Li, Zhao-Liang, Tang, Ronglin |
| المساهمون: | National Key R&D Program of China, National Natural Science Foundation of China |
| المصدر: | Environmental Research Letters ; volume 17, issue 10, page 104021 ; ISSN 1748-9326 |
| بيانات النشر: | IOP Publishing |
| سنة النشر: | 2022 |
| الوصف: | Accurate quantification of gross primary production (GPP) in agroecosystems not only improves our ability to understand the global carbon budget but also plays a critical role in human welfare and development. Light-use efficiency (LUE) models have been widely applied in estimating regional and global GPP due to their simple structure and clear physical basis. However, maximum LUE ( ε max ), a key photosynthetic parameter in LUE models, has generally been treated as a constant, leading to common overestimation and underestimation of low and high magnitudes of GPP, respectively. Here, we propose a parsimonious and practical two-stage LUE (TS-LUE) model to improve GPP estimates by (a) considering seasonal variations of ε max , and (b) separately re-parameterizing ε max in the green-up and senescence stages. The TS-LUE model is inter-compared with state-of-the-art ε max –static moderate resolution imaging spectroradiometer-GPP, eddy-covariance-LUE, and vegetation production models. Validation results at 14 FLUXNET sites for five crop species showed that: (a) the TS-LUE model significantly reduced the large bias at high- and low-level GPP as produced by the three ε max –static LUE models for all crop types; and (b) the TS-LUE model generated daily GPP estimates in good agreement with in-situ measurements and was found to outperform the three ε max –static LUE models. Especially compared to the well-known moderate resolution imaging spectroradiometer-GPP, the TS-LUE model could remarkably decrease the root mean square error (in gC m −2 d −1 ) by 24.2% and 35.4% (from 3.84 to 2.91 and 2.48) and could increase the coefficient of determination by 14.7% and 20% (from 0.75 to 0.86 and 0.9) when the leaf area index (LAI) and ... |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | unknown |
| DOI: | 10.1088/1748-9326/ac8b98 |
| DOI: | 10.1088/1748-9326/ac8b98/pdf |
| الاتاحة: | http://dx.doi.org/10.1088/1748-9326/ac8b98 https://iopscience.iop.org/article/10.1088/1748-9326/ac8b98 https://iopscience.iop.org/article/10.1088/1748-9326/ac8b98/pdf |
| Rights: | http://creativecommons.org/licenses/by/4.0 ; https://iopscience.iop.org/info/page/text-and-data-mining |
| رقم الانضمام: | edsbas.7A330391 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1088/1748-9326/ac8b98 |
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