Exploring light use efficiency models capacities in characterizing environmental impacts on paddy rice productivity
Remote sensing-driven light use efficiency (LUE) models have been widely used to calculate gross primary productivity (GPP) for various terrestrial ecosystems, but there was limited knowledge on the capacity of LUE models to evaluate the GPP in paddy rice ecosystems. In this study, at seven rice-gro...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-03-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843223000018 |
| _version_ | 1811163481992331264 |
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| author | Nuo Cheng Yanlian Zhou Wei He Weimin Ju Tingting Zhu Yibo Liu Ping Song Wenjun Bi Xiaoyu Zhang Xiaonan Wei |
| author_facet | Nuo Cheng Yanlian Zhou Wei He Weimin Ju Tingting Zhu Yibo Liu Ping Song Wenjun Bi Xiaoyu Zhang Xiaonan Wei |
| author_sort | Nuo Cheng |
| collection | DOAJ |
| description | Remote sensing-driven light use efficiency (LUE) models have been widely used to calculate gross primary productivity (GPP) for various terrestrial ecosystems, but there was limited knowledge on the capacity of LUE models to evaluate the GPP in paddy rice ecosystems. In this study, at seven rice-growing sites over the Northern Hemisphere and based on six commonly used LUE models, we calibrated the parameters (i.e., maximum LUE (LUEmax) and optimum temperature) by separating the growing period into four phenological transitions and evaluated the performance of models, and investigated the impact of changes in cloud conditions and environmental factors (i.e., air temperature and vapor pressure deficit) on GPP simulations. The calibrated LUEmax corresponded closely to phenology, allowing the six LUE models to track the seasonal variations in GPP reasonably well. The sensitivity of GPP estimates to sky clearness index (CI) indicated that the TL-LUE model incorporating diffuse radiation fractions outperformed other models under cloudy conditions. Environmental stressors including along with changes in the diffuse radiation fractions synergistically affected GPP simulation, resulting in distinctly variable performances of the LUE models under different water and temperature conditions, with the TL-LUE model always performing well during the suitable rice growing season. These results demonstrate that it is crucial to consider the diffuse radiation fraction and to better represent environmental stresses under certain environmental conditions in LUE models for accurate estimation of rice GPP. |
| first_indexed | 2024-04-10T15:06:22Z |
| format | Article |
| id | doaj.art-678c63877d0f4286b030e78011662feb |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-04-10T15:06:22Z |
| publishDate | 2023-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-678c63877d0f4286b030e78011662feb2023-02-15T04:27:25ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322023-03-01117103179Exploring light use efficiency models capacities in characterizing environmental impacts on paddy rice productivityNuo Cheng0Yanlian Zhou1Wei He2Weimin Ju3Tingting Zhu4Yibo Liu5Ping Song6Wenjun Bi7Xiaoyu Zhang8Xiaonan Wei9Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu 210023, ChinaJiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu 210023, China; Corresponding author.International Institute for Earth System Science, Nanjing University, Nanjing 210023, ChinaInternational Institute for Earth System Science, Nanjing University, Nanjing 210023, ChinaJiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu 210023, China; International Institute for Earth System Science, Nanjing University, Nanjing 210023, ChinaJiangsu Laboratory of Agricultural Meteorology/Institute of Ecology, School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaNational Key Laboratory on Electromagnetic Environmental Effects and Electro-Optical Engineering, College of Field Engineering, Army Engineering University of PLA, Nanjing 210007, ChinaJiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu 210023, ChinaJiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu 210023, ChinaJiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu 210023, ChinaRemote sensing-driven light use efficiency (LUE) models have been widely used to calculate gross primary productivity (GPP) for various terrestrial ecosystems, but there was limited knowledge on the capacity of LUE models to evaluate the GPP in paddy rice ecosystems. In this study, at seven rice-growing sites over the Northern Hemisphere and based on six commonly used LUE models, we calibrated the parameters (i.e., maximum LUE (LUEmax) and optimum temperature) by separating the growing period into four phenological transitions and evaluated the performance of models, and investigated the impact of changes in cloud conditions and environmental factors (i.e., air temperature and vapor pressure deficit) on GPP simulations. The calibrated LUEmax corresponded closely to phenology, allowing the six LUE models to track the seasonal variations in GPP reasonably well. The sensitivity of GPP estimates to sky clearness index (CI) indicated that the TL-LUE model incorporating diffuse radiation fractions outperformed other models under cloudy conditions. Environmental stressors including along with changes in the diffuse radiation fractions synergistically affected GPP simulation, resulting in distinctly variable performances of the LUE models under different water and temperature conditions, with the TL-LUE model always performing well during the suitable rice growing season. These results demonstrate that it is crucial to consider the diffuse radiation fraction and to better represent environmental stresses under certain environmental conditions in LUE models for accurate estimation of rice GPP.http://www.sciencedirect.com/science/article/pii/S1569843223000018Light use efficiency modelGross primary productivityPaddy riceEnvironmental stressors |
| spellingShingle | Nuo Cheng Yanlian Zhou Wei He Weimin Ju Tingting Zhu Yibo Liu Ping Song Wenjun Bi Xiaoyu Zhang Xiaonan Wei Exploring light use efficiency models capacities in characterizing environmental impacts on paddy rice productivity International Journal of Applied Earth Observations and Geoinformation Light use efficiency model Gross primary productivity Paddy rice Environmental stressors |
| title | Exploring light use efficiency models capacities in characterizing environmental impacts on paddy rice productivity |
| title_full | Exploring light use efficiency models capacities in characterizing environmental impacts on paddy rice productivity |
| title_fullStr | Exploring light use efficiency models capacities in characterizing environmental impacts on paddy rice productivity |
| title_full_unstemmed | Exploring light use efficiency models capacities in characterizing environmental impacts on paddy rice productivity |
| title_short | Exploring light use efficiency models capacities in characterizing environmental impacts on paddy rice productivity |
| title_sort | exploring light use efficiency models capacities in characterizing environmental impacts on paddy rice productivity |
| topic | Light use efficiency model Gross primary productivity Paddy rice Environmental stressors |
| url | http://www.sciencedirect.com/science/article/pii/S1569843223000018 |
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