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干旱区地理 ›› 2025, Vol. 48 ›› Issue (12): 2197-2209.doi: 10.12118/j.issn.1000-6060.2025.212 cstr: 32274.14.ALG2025212

• 土地利用与碳循环 • 上一篇    下一篇

新疆植被固碳时空特征及驱动因素分析

汪左1,2(), 聂家静1,2, 王梦雪1,2, 魏子然1,2, 李虎1,2, 尤元红1,2   

  1. 1 安徽师范大学地理与旅游学院安徽 芜湖 241002
    2 资源环境与地理信息工程安徽省工程技术研究中心安徽 芜湖 241002
  • 收稿日期:2025-04-17 修回日期:2025-05-27 出版日期:2025-12-25 发布日期:2025-12-30
  • 作者简介:汪左(1986-),男,副教授,主要从事积雪遥感及积雪生态效应研究. E-mail: wangzuo@ahnu.edu.cn
  • 基金资助:
    安徽省高等学校科学研究项目(2023AH050137);国家自然科学基金项目(42101361);国家级大学生创新创业训练计划项目(202410370016);国家级大学生创新创业训练计划项目(202410370018);教育部产学合作协同育人项目(231001223112359);安徽省2024年度新时代育人省级质量工程项目(研究生教育)(2024zyxwjxalk025)

Spatiotemporal characteristics and driving factors of vegetation carbon sequestration in Xinjiang, China

WANG Zuo1,2(), NIE Jiajing1,2, WANG Mengxue1,2, WEI Ziran1,2, LI Hu1,2, YOU Yuanhong1,2   

  1. 1 School of Geography and Tourism, Anhui Normal University, Wuhu 241002, Anhui, China
    2 Engineering Technology Research Center of Resources Environment and GIS of Anhui Province, Wuhu 241002, Anhui, China
  • Received:2025-04-17 Revised:2025-05-27 Published:2025-12-25 Online:2025-12-30

摘要:

新疆是我国陆域碳汇的重要组成,揭示其植被固碳时空特征与驱动因素对于区域生态安全与保护具有重要意义。目前对该区植被固碳驱动因子的研究多聚焦于水分、热量等气候要素,而对新疆固有的积雪物候作用关注不足。为此,基于2001—2018年全球逐日碳通量模拟数据,分析新疆植被总初级生产力(Gross primary production,GPP)和净初级生产力(Net primary production,NPP)的时空变化特征,并引入积雪物候指标,结合地理探测器和偏相关分析方法,从区域与栅格尺度探讨GPP和NPP的空间分异与时间变化驱动机制。结果表明:(1) 2001—2018年新疆地区植被GPP、NPP以2007年为分隔呈先下降后上升的变化趋势;空间上具有北高南低、西高东低、山区高平原低的分布特征。(2) 新疆植被GPP、NPP空间分异主要受降水、积雪日数和高程的驱动;栅格尺度上新疆植被GPP、NPP的时间变化受降水主导的范围最大,其次是太阳辐射和积雪日数。(3) 土地利用变化下,农田扩张和农田区域是新疆植被年固碳量增加的最主要贡献者;草地退化是新疆植被年固碳量减少的最主要因素。研究结果揭示了新疆植被碳汇的独特驱动过程,有助于深化气候变化和土地利用变化对植被固碳影响的认识,为新疆生态保护与可持续发展提供理论依据。

关键词: 植被固碳, 时空分异, 驱动因子, 积雪物候, 新疆

Abstract:

Xinjiang constitutes a critical component of China’s terrestrial carbon sink. Elucidating the spatiotemporal patterns and driving factors of its vegetation carbon sequestration is imperative for regional ecological security and conservation. Currently, research on the driving factors of vegetation carbon sequestration in this area mainly focuses on climate factors such as water and heat, whereas insufficient attention is paid to the phenological effects of snow accumulation that are inherent to Xinjiang regions. Therefore, based on the global daily carbon flux simulation data from 2001 to 2018, this study analyzes the spatiotemporal variations of gross primary production (GPP) and net primary production (NPP) of vegetation in Xinjiang. Snow phenology indicators are introduced, and spatial differentiation and driving mechanisms of GPP and NPP are examined at both regional and pixel scales using the geographical detector and partial correlation analysis methods. The results revealed that from 2001 to 2018, the vegetation GPP and NPP in Xinjiang exhibited a trend of first decreasing and then increasing, with 2007 as the turning point. They spatially exhibited a pattern of higher values in the north than in the south, higher in the west than in the east, and higher in mountainous areas than in plains. The spatial differentiation of GPP and NPP of Xinjiang vegetation was mainly driven by precipitation, snow days and elevation. On the grid scale, the temporal variation of GPP and NPP of Xinjiang vegetation was dominated by precipitation, followed by solar radiation and snowy days. Moreover, under land use change, farmland expansion and farmland areas were the main contributors to the increase in the annual carbon sequestration of vegetation in Xinjiang. Grassland degradation was the main factor contributing to the reduction of annual carbon sequestration in vegetation in Xinjiang. The research results reveal the unique driving process of vegetation carbon sink in Xinjiang regions, which helps to deepen the understanding of the impact of climate change and land use change on vegetation carbon sequestration under the background of climate warming, and provide a theoretical basis for ecological protection and sustainable development in Xinjiang.

Key words: vegetation carbon sequestration, spatiotemporal differentiation, driving factor, snow phenology, Xinjiang