基于叶绿素荧光遥感的长江流域植被生产力时空变化及其气候驱动因素

聂冲; 陈星安; 杨鹊平; 朱延忠; 徐睿; 邓陈宁; 周娟

doi:10.13198/j.issn.1001-6929.2023.08.20

基于叶绿素荧光遥感的长江流域植被生产力时空变化及其气候驱动因素

doi: 10.13198/j.issn.1001-6929.2023.08.20

聂冲^{1, 2,},
陈星安³,
杨鹊平^{1, 2, ,},
朱延忠^{1, 2},
徐睿^{1, 2},
邓陈宁¹,
周娟^{1, 2}

1.
中国环境科学研究院，北京　100012
2.
国家长江生态环境保护修复联合研究中心，北京　100012
3.
清华大学，水沙科学与水利水电工程国家重点实验室，北京　100084

基金项目: 中央级公益性科研院所基本科研业务费(No.2022YSKY-72)；国家重点研发计划项目(No.2022YFC3202104)；长江生态环境保护修复联合研究项目(第二期) (No.2022-LHYJ-02-0603)

详细信息

作者简介:
聂冲（1991-），女，河北保定人，助理研究员，博士，主要从事生态水文研究，niechong0722@163.com

通讯作者:
杨鹊平(1981-)，女，吉林长春人，高级工程师，硕士，主要从事环境政策管理研究， yangqp@craes.org.cn

中图分类号: X171；Q948
计量
- 文章访问数: 39
- HTML全文浏览量: 7
- PDF下载量: 7
- 被引次数: 0
出版历程
- 收稿日期: 2023-05-22
- 修回日期: 2023-08-22
- 网络出版日期: 2023-09-01

Spatial-Temporal Variation of Vegetation Productivity in the Yangtze River Basin and Its Climate Driving Factors Based on Solar-Induced Chlorophyll Fluorescence

NIE Chong^{1, 2
,},
CHEN Xing′an³,
YANG Queping^{1, 2
, ,},
ZHU Yanzhong^{1, 2},
XU Rui^{1, 2},
DENG Chenning¹,
ZHOU Juan^{1, 2}

1.
Chinese Research Academy of Environmental Sciences, Beijing 100012, China
2.
National Joint Research Center for Yangtze River Conservation, Beijing 100012, China
3.
State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China

Funds: Fundamental Research Funds for the Central Public-Interest Scientific Institution, Chinese Research Academy of Environmental Sciences (No.2022YSKY-72); National Key Research and Development Program of China (No.2022YFC3202104); Yangtze River Joint Research Phase Ⅱ Program, China (No.2022-LHYJ-02-0603)

摘要

摘要: 植被生产力反映了陆地生态系统通过光合作用固定的有机碳量. 长江流域在我国经济社会发展和生态环境保护中占有重要的战略地位. 然而，由于区域尺度植被生产力估算不够精准，导致了目前长江流域植被生产力现状及演变规律不清、关键驱动因子研究不充分的问题. 本研究选取最新的日光诱导叶绿素荧光(solar-induced chlorophyll fluorescence, SIF)数据来表征长江流域植被生产力，基于全球陆地数据同化系统(GLDAS v.5)数据集，采用偏最小二乘回归方法，系统辨识了长江流域SIF的时空演变规律，解析了SIF对降水、温度、净辐射变化的响应规律. 结果表明：①2001—2020年，长江流域SIF年均值为(0.25±0.08) mW/(m²·nm·sr)，SIF随着纬度的增加呈现显著减少的趋势，随着经度的增加呈现先增加后减少的趋势，汉江流域、鄱阳湖流域、洞庭湖流域SIF均相对较高，金沙江石鼓以上流域和金沙江石鼓以下流域SIF均相对较低. ②2001—2020年长江流域SIF有显著增加的趋势，增加速率为0.002 mW/(m²·nm·sr·a)，乌江流域、宜宾至宜昌段长江干流区间和鄱阳湖流域的SIF增长率均较高，30.34%的金沙江石鼓以上流域和47.21%的太湖流域SIF存在减少趋势. ③降水、温度和净辐射对长江流域SIF变化的贡献度分别为16.41%±9.59%、49.29%±10.79%和34.30%±14.99%. 研究显示，2001—2020年长江流域植被生产力有显著增加的趋势，温度对长江流域植被生产力变化起着主导作用. 本研究可提高对长江流域植被气候变化适应性的认识，研究成果可为长江流域增汇减排政策的制定及碳中和目标的实现提供科技支撑.
- 长江流域 /
- 植被生产力 /
- 日光诱导叶绿素荧光(SIF)
Abstract: Vegetation productivity reflects the amount of organic carbon fixed by terrestrial ecosystems through photosynthesis. The Yangtze River Basin (YRB) holds a strategic position in China′s economic and social development, as well as in ecological and environmental protection. However, due to the inaccurate estimation of vegetation productivity at the regional scale, the current understandings of the current status and evolution patterns of vegetation productivity in the YRB is unclear, and the research on the key driving factors is insufficient. In this study, the latest solar-induced chlorophyll fluorescence (SIF) data were used to characterize the vegetation productivity in the YRB. Based on the Global Land Data Assimilation System (GLDAS v.5) dataset, the partial least squares regression method was used to systematically explore the spatiotemporal evolution patterns of SIF in the YRB, and to identify the SIF response to changes in precipitation, temperature and net radiation. The results indicate that: (1) From 2001 to 2020, the annual average SIF value in the YRB was (0.25±0.08) mW/(m²·nm·sr). SIF exhibited a significant decrease trend with the increase of latitude and a first-increase-then-decrease trend with the increase of longitude. The SIF values of the Hanjiang River Basin, Poyang Lake Basin, and Dongting Lake Basin were relatively high, while the SIF values of the Jinsha River Basin above Shigu and Jinsha River Basin below Shigu were relatively low. (2) There was a significant increasing trend in SIF during 2001-2020, with an increase rate of 0.002 mW/(m²·nm·sr·a). The SIF growth rates were relatively high in the Wujiang River Basin, the main stream of the Yangtze River from Yibin to Yichang and Poyang Lake Basin. 30.34% of the Jinsha River Basin above Shigu and 47.21% of the Taihu Lake Basin showed decreasing trends in SIF. (3) The contributions of precipitation, temperature and net radiation to SIF variation in the YRB were 16.41%±9.59%, 49.29%±10.79%, and 34.30%±14.99%, respectively. The results show that there is a significant increase in vegetation productivity in the YRB from 2001 to 2020, and temperature plays a dominant role in the changes of vegetation productivity in the YRB. This study can enhance the understanding of the adaptability of vegetation to climate change in the YRB. The research findings can provide technological support for the formulation of carbon sequestration and emission reduction policies and the achievement of carbon neutrality goals.
- Yangtze River Basin /
- vegetation productivity /
- solar-induced chlorophyll fluorescence (SIF)

HTML全文

图 1 长江流域二级水资源区分布

注：JSJ-1表示金沙江石鼓以上流域；JSJ-2表示金沙江石鼓以下流域；MTJ表示岷沱江流域；JLJ表示嘉陵江流域；WJ表示乌江流域；UM表示宜宾至宜昌段长江干流区间；DTL表示洞庭湖流域；HJ表示汉江流域；PYL表示鄱阳湖流域；MM表示宜昌至湖口段长江干流区间；LM表示湖口以下长江干流区间；TL表示太湖流域.

Figure 1. Distribution map of secondary water resource areas in the Yangtze River Basin (YRB)

下载: 全尺寸图片幻灯片

图 2 2001—2020年长江流域多年平均SIF的空间分布格局与统计特征

Figure 2. Spatial distribution pattern and statistical characteristics of multi-year average SIF in the YRB from 2001 to 2020

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图 3 2001—2020年长江流域二级水资源区SIF分布

Figure 3. Distribution of SIF in the Yangtze River subbasins from 2001 to 2020

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图 4 2001—2020年长江流域年均SIF和气候因子的变化趋势

Figure 4. The variation trends of annual SIF and climate factors in the YRB from 2001 to 2020

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图 5 2001—2020年长江流域SIF变化趋势及其显著性

注：增加*表示显著增加；减少*表示显著减少.

Figure 5. Trends and significances of SIF changes in the YRB from 2001 to 2020

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图 6 2001—2020年长江流域二级水资源区SIF变化率

Figure 6. Change rate of SIF in the Yangtze River subbasins from 2001 to 2020

下载: 全尺寸图片幻灯片

图 7 2001—2020年长江流域SIF对气候因子变化的响应

Figure 7. Responses of SIF in the YRB to climate factor changes from 2001 to 2020

下载: 全尺寸图片幻灯片

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