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应用生态学报 ›› 2026, Vol. 37 ›› Issue (9): 3189-3204.doi: 10.13287/j.1001-9332.202609.023

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2001—2023年中国湿地植被总初级生产力对极端气候事件的响应

夏明毅1,2, 相恒星1, 毛德华1,3*, 罗玲1, 王宗明1   

  1. 1中国科学院东北地理与农业生态研究所, 长春 130102;
    2中国科学院大学, 北京 100049;
    3吉林省生态环境遥感大数据重点实验室, 长春 130102
  • 收稿日期:2026-05-27 接受日期:2026-07-24 出版日期:2026-09-18 发布日期:2026-10-12
  • 通讯作者: *E-mail: maodehua@iga.ac.cn
  • 作者简介:夏明毅, 男, 2003年生, 硕士研究生。主要从事湿地遥感研究。E-mail: xiamingyi25@mails.ucas.ac.cn
  • 基金资助:
    国家重点研发计划项目子课题(2023YFF0807201)、国家自然科学基金项目(42301430,U2243230)和吉林省自然科学基金项目(20250101007JJ)

Responses of wetland gross primary productivity to extreme climate events in China during 2001-2023.

XIA Mingyi1,2, XIANG Hengxing1, MAO Dehua1,3*, LUO Ling1, WANG Zongming1   

  1. 1Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;
    2University of Chinese Academy of Sciences, Beijing 100049, China;
    3Jilin Provincial Key Laboratory of Remote Sensing Big Data for Ecology and Environment Research, Changchun 130102, China
  • Received:2026-05-27 Accepted:2026-07-24 Online:2026-09-18 Published:2026-10-12

摘要: 极端气候通过快速改变湿地水热条件,对湿地植被总初级生产力(GPP)及其碳汇稳定性产生显著影响。目前,中国国家尺度的湿地GPP对不同极端气候事件的响应特征的认知,尚不足以支撑湿地生态系统的适应性管理。本研究以中国湿地植被为研究对象,结合敏感性分析和偏相关分析方法,量化了2001—2023年湿地GPP对极端气候事件的响应强度和主控因子,分析了湿地GPP响应的滞后特征,并利用分布式滞后模型评估了极端气候事件的持续影响时间和方向。结果表明:2001—2023年,极端气候事件空间分布具有明显区域差异,其中,降水类极端事件的空间分异强于温度类事件,在此背景下全国尺度98.7%湿地像元呈上升趋势(Sen斜率βsen在2.112~18.640 g C·m-2·a-1),其中,北温带湿地GPP显著变化像元面积占该分区湿地面积的比例最高(48.3%),暖昼日数(TX90p)、持续湿润日数(CWD)分别使该区GPP去趋势异常显著增加18.26 g C·m-2·a-1和降低34.99 g C·m-2·a-1。TX90p是湿地GPP变化的主导控制因子(偏相关系数在0.180~0.488),其中,温带地区湿地和高原地区湿地GPP对极端高温事件最敏感(TX90p的敏感性系数β在0.376~0.648),亚热带和热带湿地更多受降水类极端事件控制(连续最大5 d降水量的β在-0.516~-0.366)。湿地GPP面对极端气候以同步响应为主,极端高温和极端干旱事件存在显著负向记忆效应,极端降水事件为显著正向记忆效应,而极端低温事件记忆效应为负向记忆效应但不显著。本研究加深了湿地GPP对极端气候事件响应机制的认识,为评估湿地碳汇稳定性和极端气候风险下的湿地保护提供了科学依据。

关键词: 湿地, 总初级生产力, 极端气候事件, 敏感性分析, 记忆效应

Abstract: Extreme climate events can substantially affect gross primary productivity (GPP) and the stability of carbon sinks of wetlands by altering hydrothermal conditions. However, national-scale evidence on how wetland GPP responds to different types of extreme climate events across China remains insufficient to support adaptive wetland ecosystem management. We focused on wetland vegetation across China and combined sensitivity analysis with partial correlation analysis to quantify the response intensity and dominant controls of wetland GPP to extreme climate events during 2001-2023, and further analyzed the lag characteristics of wetland GPP responses. The distributed lag models were applied to assess the duration and direction of the persistent effects of extreme climate events. The results showed that extreme climate events showed pronounced regional heterogeneity during 2001-2023, with precipitation-related extreme events exhibiting stronger spatial variability than temperature-related extreme events. Nationally, 98.7% of wetland pixel GPP showed an increasing trend (Sen slope βsen ranging from 2.112 to 18.640 g C·m-2·a-2). Among them, the proportion of pixels with significant GPP changes in the northern temperate wetlands accounted for the highest percentage (48.3%) of the wetland area in this subregion. Warm days (TX90p) and consecutive wet days (CWD) significantly increased the GPP detrended anomaly by 18.26 g C·m-2·a-1 and decreased by 34.99 g C·m-2·a-1, respectively. TX90p was the dominant climatic control over wetland GPP variability (partial correlation coefficient ranging from 0.180 to 0.488). Wetlands in temperate zones and the plateau region were most sensitive to extreme heat events (with sensitivity coefficient β of TX90p ranging from 0.376 to 0.648). By contrast, subtropical and tropical wetlands were more strongly controlled by precipitation-related extremes (with β of the maximum 5-day precipitation amount ranging from -0.516 to -0.366). Wetland GPP responded synchronously to extreme climate events, exhibiting significant negative memory effects for extreme heat and drought events, a significant positive memory effect for extreme precipitation events, and a negative but non-significant memory effect for extreme cold events. These findings advanced our understanding of wetland GPP responses to extreme climate events and would provide scientific support for assessing wetland carbon-sink stability and informing wetland conservation under increasing climate-extreme risks.

Key words: wetland, gross primary productivity, extreme climate event, sensitivity analysis, memory effect