三江源区植被季节性变绿的水分驱动因子及其对气候变化的响应研究 

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  • 1. 中国科学院西北生态环境资源研究院冰冻圈科学与冻土工程全国重点实验室,甘肃 兰州 730000
    2. 中国科学院西北生态环境资源研究院若尔盖高原湿地生态系统研究站,甘肃 兰州 730000
    3. 中国科学院大学,北京 100049
    4. 中国气象局兰州干旱气象研究所,甘肃 兰州 730020

网络出版日期: 2025-05-20

基金资助

中国科学院西部之光“西部青年学者”计划(E2290302);国家自然科学基金项目(42275045

Moisture driver of Seasonal Vegetation Greening and Their Responses to Climate Change in the Three River Source Region

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  • 1. State Key Laboratory of Cryospheric Science and Frozen Soil EngineeringNorthwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000GansuChina
    2. Zoige Plateau Wetlands Ecosystem Research StationNorthwest Institute of Eco-Environment and Resources
    Chinese Academy of SciencesLanzhou 730000GansuChina
    3. University of Chinese Academy of SciencesBeijing 100049China
    4. Institute of Arid MeteorologyCMALanzhou 730020GansuChina

Online published: 2025-05-20

摘要

三江源区植被季节性变绿对生态环境和水资源安全有深远影响。本研究利用2003-2021年多源数据,采用趋势分析、相关分析和部分信息分解(PID)解耦分析,探讨了三江源地区植被季节性变绿的水分驱动因子及其对气候变化的响应关系。结果表明:(1)春、夏、秋季叶面积指数(LAI)的线性趋势总体上升,但是不同季节的环境条件差异显著。春、秋季降水量、土壤湿度(SM)和积雪覆盖(SC)的线性趋势也在增加,温度变化不明显;夏季温度的线性趋势略升高,降水量和SM略减少,SC变化不显著。(2)水分驱动因子对LAI的影响:相关分析显示,春、夏季LAISM显著正相关,秋季不显著;LAISC的相关性各季节均较弱。引入PID解耦分析方法,有效地揭示了SMSCLAI的非线性和协同影响。SC在春、秋季影响LAI变化的独立信息贡献更高,成为主要水分驱动因子,夏季则SM贡献更大;同时,SMSC的协同作用在各季节对LAI变化起重要作用,协同信息贡献均超过30%。(3)水分驱动因子对气候变化的响应:相关分析显示,SM在各季节均与降水显著正相关,春季与温度显著负相关;SC在各季节均与降水显著正相关,春、秋季与温度显著负相关。PID分析也表明,降水是影响三个季节SMSC变化的主要气象因子,对SMSC的独立贡献均高于温度,但温度和降水对各季节的SMSC的协同作用也不容忽视。

本文引用格式

王宇腾, 柳媛普, 陈 昊, 李照国, 马 迪, 尚伦宇, 晋 伟, 孟宪红, 赵 林 . 三江源区植被季节性变绿的水分驱动因子及其对气候变化的响应研究 [J]. 高原气象, 0 : 1 . DOI: 10.7522/j.issn.1000-0534.2024.00111

Abstract

The seasonal vegetation greening in the Three River Source RegionTRSRhas a profound impact on the ecological environment and water resource security. In this studythe moisture drivers of seasonal vegetation greening in the TRSR and their responses to climate change were investigated using multi-source data from 2003 to 2021through the application of trend analysiscorrelation analysis and partial information decomposition PIDanalysis. The results showed that1the linear trend of the Leaf Area IndexLAIgenerally increased in springsummer and autumnalthough the environmental conditions varied significantly between seasons. Linear trends in precipitationsoil moistureSMand snow coverSCalso increased in spring and autumnwith in‐ significant changes in temperature. In summerlinear trends of temperature were slightly higherwith slight de‐ creases in precipitation and SMas well as insignificant changes in SC.2Effects of moisture drivers on LAIcorrelation analyses indicated that LAI was significantly positively correlated with SM in spring and summerbut not in autumn. The correlation between LAI and SC was weak in all seasons. By introducing the PID analysis methodthe nonlinear and synergistic effects of SM and SC on LAI were effectively revealed. The independent information contribution of SC to LAI changes was higher in spring and autumnmaking it the main moisture driver in these seasonswhile SM contributed more in summer. At the same timethe synergistic effects of SM and SC played an important role in the changes of LAI in all seasonswith the synergistic information contribution exceeding 30% in all seasons.3Response of moisture drivers to climate changecorrelation analyses showed that SM was significantly positively correlated with precipitation in all seasons and significantly negatively correlated with temperature in springSC was significantly positively correlated with precipitation in all sea‐ sons and significantly negatively correlated with temperature in both spring and autumn. PID analyses also indicated that precipitation was the main meteorological factor influencing changes in SM and SC across the three seasonswith a higher independent contribution than temperature. Howeverthe synergistic effects of temperature and precipitation on SM and SC in all seasons should not be overlooked.

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