洞庭湖流域植被光合物候的时空变化及其对气候变化的响应

doi:10.17521/cjpe.2022.0170

植物生态学报 ›› 2023, Vol. 47 ›› Issue (3): 319-330.DOI: 10.17521/cjpe.2022.0170

所属专题：遥感生态学；光合作用

洞庭湖流域植被光合物候的时空变化及其对气候变化的响应

任培鑫¹, 李鹏¹^,^*(), 彭长辉¹^,², 周晓路¹, 杨铭霞¹

¹湖南师范大学地理科学学院, 长沙 410081
²Department of Biology Sciences, Institute of Environment Sciences, University of Quebec at Montreal, Montreal H3C 3P8, Canada

收稿日期:2022-04-28 接受日期:2022-09-28 出版日期:2023-03-20 发布日期:2022-09-28
通讯作者: 李鹏
作者简介:* (lipeng_gz@126.com)
基金资助:
国家自然科学基金(41901117);湖南省自然科学基金(2020JJ5362)

Temporal and spatial variation of vegetation photosynthetic phenology in Dongting Lake basin and its response to climate change

REN Pei-Xin¹, LI Peng¹^,^*(), PENG Chang-Hui¹^,², ZHOU Xiao-Lu¹, YANG Ming-Xia¹

¹College of Geographic Sciences, Hunan Normal University, Changsha 410081, China
²Department of Biology Sciences, Institute of Environment Sciences, University of Quebec at Montreal, Montreal H3C 3P8, Canada

Received:2022-04-28 Accepted:2022-09-28 Online:2023-03-20 Published:2022-09-28
Contact: LI Peng
Supported by:
National Natural Science Foundation of China(41901117);Natural Science Foundation of Hunan Province(2020JJ5362)

摘要/Abstract

摘要：

为研究洞庭湖流域植被春季光合物候和秋季光合物候的时空变化, 揭示其对气候变化的响应规律, 为亚热带植被物候模型的建立和碳收支评估提供有益参考, 该研究利用2000-2018年的日光诱导叶绿素荧光(SIF)遥感数据反演洞庭湖流域植被春季光合物候(春季光合作用开始的时间)和秋季光合物候(秋季光合作用停止的时间), 分析植被春季、秋季光合物候的时空变化趋势及其对气候变化的响应机制。研究结果: (1) 2000-2018年, 洞庭湖流域植被春季光合物候以0.75 d·a^-1的速度显著提前, 秋季光合物候以0.17 d·a^-1的速度呈延后趋势, 植被生长季长度以0.90 d·a^-1的速度显著延长; (2)季前最高气温和最低气温是研究区春季光合物候提前的主要影响因素, 秋季光合物候与季前降水量、最低气温、辐射强度均呈正相关关系, 而与季前最高气温主要呈负相关关系; (3)研究区植被春季光合物候对气候变化的响应更敏感, 尤其是季前最低气温的升高导致常绿针叶林、常绿阔叶林、灌丛和草地的春季光合物候显著提前。洞庭湖流域植被春季光合物候提前对生长季延长起主导作用, 这表明在气候变暖的背景下, 植被春季光合物候对增强研究区碳汇功能扮演着比秋季光合物候更加重要的角色。研究区植被春季光合物候对气候变化响应更为敏感, 且气温是控制春季光合物候的主要因素, 这为常绿植被物候的模拟与预测提供了科学基础。

关键词: 植被物候, 日光诱导叶绿素荧光, 气候变化, 亚热带, 碳汇

Abstract:

Aims This study investigated the spatial and temporal variation of spring and autumn photosynthetic phenology of vegetation in the Dongting Lake basin and revealed its response to climate change, and provides a useful reference for the establishment of model of subtropical vegetation phenology and the evaluation of carbon budget.

Methods Using solar-induced chlorophyll fluorescence (SIF) data, we extracted spring photosynthetic phenology (the start date of photosynthesis) and autumn photosynthetic phenology (the end date of photosynthesis) of vegetation in Dongting Lake basin, and evaluated temporal and spatial patterns of vegetation spring and autumn photosynthetic phenology and its response to climate change.

Important findings (1) From 2000 to 2018, the vegetation spring photosynthetic phenology was significantly advanced at the rate of 0.75 d·a^-1, the autumn photosynthetic phenology was delayed at the rate of 0.17 d·a^-1, and the vegetation growing season length was significantly prolonged at the rate of 0.90 d·a^-1. (2) The preseason maximum air temperature and minimum air temperature were the main factors affecting the advance of spring photosynthetic phenology. The autumn photosynthetic phenology of vegetation was positively correlated with preseason precipitation, minimum air temperature and radiation intensity, but negatively correlated with preseason maximum air temperature. (3) In addition, we found that the spring photosynthetic phenology of vegetation in the study area was more sensitive to climate change, especially the increase of preseason minimum air temperature led to the significant advance of spring photosynthetic phenology of evergreen needleleaf forest, evergreen broadleaf forest, bush and grassland. In conclusion, the advance of vegetation spring photosynthetic phenology in Dongting Lake basin played a dominant role in prolonging the growth season, indicating that spring photosynthetic phenology plays a more important role in enhancing the carbon sink function than the autumn photosynthetic phenology in the context of global warming. The vegetation spring photosynthetic phenology was more sensitive to climate change and the air temperature was the main factor controlling the vegetation spring photosynthetic phenology, which provides a scientific basis for the simulation and prediction of evergreen vegetation phenology.

Key words: vegetation phenology, solar-induced chlorophyll fluorescence, climate change, subtropics, carbon sink

任培鑫, 李鹏, 彭长辉, 周晓路, 杨铭霞. 洞庭湖流域植被光合物候的时空变化及其对气候变化的响应. 植物生态学报, 2023, 47(3): 319-330. DOI: 10.17521/cjpe.2022.0170

REN Pei-Xin, LI Peng, PENG Chang-Hui, ZHOU Xiao-Lu, YANG Ming-Xia. Temporal and spatial variation of vegetation photosynthetic phenology in Dongting Lake basin and its response to climate change. Chinese Journal of Plant Ecology, 2023, 47(3): 319-330. DOI: 10.17521/cjpe.2022.0170

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2022.0170

https://www.plant-ecology.com/CN/Y2023/V47/I3/319

图/表 7

图1 洞庭湖流域位置及植被类型。

Fig. 1 Location and vegetation types of Dongting Lake basin.

图2 2000-2018年洞庭湖流域植被光合物候的空间格局及频率分布。

Fig. 2 Spatial pattern and frequency distribution of vegetation photosynthetic phenology and growing season length in Dongting Lake basin from 2000 to 2018. EOP, the end date of photosynthesis; LOP, the length of photosynthesis; SOP, the start date of photosynthesis.

图3 2000-2018年洞庭湖流域植被光合物候和生长季长度变化趋势空间格局和年际变化。P代表系数为正的比例, 表示光合物候呈延后(延长)趋势; N代表系数为负的比例, 表示光合物候呈提前(缩短)趋势; 括号内为p < 0.05的统计比例。slope, 斜率。

Fig. 3 Spatial distribution patterns of the linear trend and annual variation of vegetation photosynthetic phenology and growing season length in Dongting Lake basin from 2000 to 2018. EOP, the end date of photosynthesis; LOP, the length of photosynthesis; SOP, the start date of photosynthesis. P indicated the percentage of positive coefficients, indicating that the photosynthetic phenology tends to delay (prolong); N indicated the percentage of negative coefficients, indicating that the photosynthetic phenology tends to advance (shorten); percentage of significant correlations in parentheses (p < 0.05) are provided.

图4 2000-2018年洞庭湖流域各类型植被光合物候变化趋势。正值代表物候指标延后, 负值代表物候指标提前。*, p < 0.05。

Fig. 4 Linear trends of vegetation photosynthetic phenology across the biomes in Dongting Lake basin from 2000 to 2018. EOP, the end date of photosynthesis; SOP, the start date of photosynthesis. DBF, deciduous broadleaf forest; EBF, evergreen broadleaf forest; ENF, evergreen needleleaf forest. Positive values represented the delay of phenological indicators, and negative values represented the advance of phenological indicators. *, p < 0.05.

图5 植被春季、秋季光合物候与季前气候因子偏相关性系数的空间格局及频率分布。P代表正相关比例, 表明气候因子的增加导致物候的延后; N代表负相关比例, 表明气候因子的增加导致物候的提前; 括号内为p < 0.05的统计比例。

Fig. 5 Spatial pattern and frequency distribution of partial correlation coefficient between the spring and autumn photosynthetic phenology of vegetation and preseason climatic factors. Pre, precipitation; Srad, radiation intensity; Tmax, maximum air temperature; Tmin, minimum air temperature. P means the proportion of positive correlation coefficients, indicating that the increase of climate factors led to the delay of phenology; N means the proportion of negative correlation coefficients, indicating that the increase of climate factors led to the advance of phenology; percentage of significant correlations in parentheses (p < 0.05) are provided. EOP, the end date of photosynthesis; LOP, the length of photosynthesis; SOP, the start date of photosynthesis.

图6 不同类型植被光合物候与季前气候因子的偏相关关系。*, p < 0.05; **, p < 0.01。

Fig. 6 Partial correlation coefficient between the photosynthetic phenology of different vegetation and preseason climatic factors. EOP, the end date of photosynthesis; SOP, the start date of photosynthesis. DBF, deciduous broadleaf forest; EBF, evergreen broadleaf forest; ENF, evergreen needleleaf forest. Pre, precipitation; Srad, radiation intensity; Tmax, maximum air temperature; Tmin, minimum air temperature. *, p < 0.05; **, p < 0.01.

表1 落叶阔叶林区域气候因子的年际变化

Table 1 Interannual variation of climatic factors in deciduous broadleaf forest region

气候因子 Climate factor	变化速率 Rate of change	p
降水 Precipitation	-1.321 2 (mm·a^-1)	0.756 1
最高气温 Maximum air temperature	-0.080 8 (℃·a^-1)	0.603 5
最低气温 Minimum air temperature	-0.052 3 (℃·a^-1)	0.595 7
辐射强度 Radiation intensity	-1.211 8 (W·m^-2·a^-1)	0.477 0

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洞庭湖流域植被光合物候的时空变化及其对气候变化的响应

Temporal and spatial variation of vegetation photosynthetic phenology in Dongting Lake basin and its response to climate change

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