| 论文题目： | Dynamic Threshold of Carbon Phenology in Two Cold Temperate Grasslands in China |
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| 第一作者： | Xu Lingling; Niu Ben; Zhang Xianzhou; He Yongtao |
| 联系作者： | |
| 发表年度： | 2021 |
| 摘 要： | Plant phenology, especially the timing of the start and the end of the vegetation growing season (SOS and EOS), plays a major role in grassland ecosystem carbon cycles. As the second-largest grassland country in the world, China's grasslands are mainly distributed in the northern cold temperate climate zone. The accuracies and relations of plant phenology estimations from multialgorithms and data resources are poorly understood. Here, we investigated vegetation phenology in two typical cold temperate grasslands, Haibei (HB) and Inner Mongolia (NM) grasslands, in China from 2001 to 2017. Compared to ground vegetation phenology observations, we analyzed the performance of the moderate resolution imaging spectroradiometer MODIS phenology products (MCD12Q2) and two remote sensing-based vegetation phenology algorithms from the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) time series (five satellite-based phenology algorithms). The optimal algorithm was used to compare with eddy covariance (EC)-based carbon phenology, and to calculate the thresholds of carbon phenology periods (SOSt and EOSt) in each site. Results showed that satellite-based phenology estimations (all five algorithms in this study) were strongly coupled with the temporal variation of the observed phenological period but significantly overestimated the SOS, predicting it to be over 21 days later than the field data. The carbon phenology thresholds of HB grassland (HB_SOSt and HB_EOSt) had a significant upward trend, with the multiyear average values being 0.14 and 0.29, respectively. In contrast, the thresholds of NM grasslands (NM_SOSt and NM_EOSt) also showed a certain upward trend, but it was not significant (p > 0.05), with the multiyear average values being 0.17 and 0.2, respectively. Our study suggested the thresholds of carbon phenology periods (SOSt and EOSt, %) could be simply and effectively estimated based on their significant relationship with the EC-based maximum of gross primary productivity observations (GPPmax) at a specific site and time. Therefore, this study suggested the thresholds of carbon phenology were not fixed even in a specific ecosystem, which also provided simple bridges between satellite-based vegetation phenology and EC-based carbon phenology in similar grasslands. |
| 英文摘要： | Plant phenology, especially the timing of the start and the end of the vegetation growing season (SOS and EOS), plays a major role in grassland ecosystem carbon cycles. As the second-largest grassland country in the world, China's grasslands are mainly distributed in the northern cold temperate climate zone. The accuracies and relations of plant phenology estimations from multialgorithms and data resources are poorly understood. Here, we investigated vegetation phenology in two typical cold temperate grasslands, Haibei (HB) and Inner Mongolia (NM) grasslands, in China from 2001 to 2017. Compared to ground vegetation phenology observations, we analyzed the performance of the moderate resolution imaging spectroradiometer MODIS phenology products (MCD12Q2) and two remote sensing-based vegetation phenology algorithms from the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) time series (five satellite-based phenology algorithms). The optimal algorithm was used to compare with eddy covariance (EC)-based carbon phenology, and to calculate the thresholds of carbon phenology periods (SOSt and EOSt) in each site. Results showed that satellite-based phenology estimations (all five algorithms in this study) were strongly coupled with the temporal variation of the observed phenological period but significantly overestimated the SOS, predicting it to be over 21 days later than the field data. The carbon phenology thresholds of HB grassland (HB_SOSt and HB_EOSt) had a significant upward trend, with the multiyear average values being 0.14 and 0.29, respectively. In contrast, the thresholds of NM grasslands (NM_SOSt and NM_EOSt) also showed a certain upward trend, but it was not significant (p > 0.05), with the multiyear average values being 0.17 and 0.2, respectively. Our study suggested the thresholds of carbon phenology periods (SOSt and EOSt, %) could be simply and effectively estimated based on their significant relationship with the EC-based maximum of gross primary productivity observations (GPPmax) at a specific site and time. Therefore, this study suggested the thresholds of carbon phenology were not fixed even in a specific ecosystem, which also provided simple bridges between satellite-based vegetation phenology and EC-based carbon phenology in similar grasslands. |
| 刊物名称： | REMOTE SENSING |
| 全文链接： | |
| 论文类别： | SCI |
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