植物生态学报

• •    

气候变化下中国潜在自然植被生态系统碳储量动态研究

张计深1,史新杰1,刘宇诺1,吴阳2,3,彭守璋1   

  1. 1. 西北农林科技大学
    2. 中国科学院大学
    3. 中国科学院水利部水土保持研究所
  • 收稿日期:2022-08-30 修回日期:2023-05-08 出版日期:2023-05-15 发布日期:2023-05-15
  • 通讯作者: 彭守璋

Study of potential natural vegetation ecosystems carbon storage dynamics over China under climate change

zhang jishen1,shi xinjie1,liu yunuo1,wu yang2,3,   

  • Received:2022-08-30 Revised:2023-05-08 Online:2023-05-15

摘要: 陆地生态系统固碳是减缓大气CO2浓度升高的重要途径之一,了解气候变化下潜在自然植被生态系统碳储量(EC)有利于区域土地管理政策的制定。本研究基于遗传算法对LPJ-GUESS模型的敏感参数进行校准,使用降尺度的气候数据驱动模型,结合Mann-Kendall趋势检验、Sen’s斜率估计方法和偏相关分析法,分析了2001—2100年中国EC的时空格局、趋势变化特征及气候主导因子。结果表明:校准后的LPJ-GUESS模型模拟EC的纳什效率系数和皮尔逊相关系数分别为0.751、0.901,表明LPJ-GUESS模型可以较好模拟中国EC;2001—2020年,中国EC由东南向西北递减,总量为156.06 Pg C。其中植被、凋落物、土壤分别占34.2%、1.9%、63.8%。2081—2100年EC与历史时期具有相同的空间异质性,相比于2001—2020年,预计本世纪末EC总量增加0.51-11.16 Pg C;2001—2020年和2021—2100年,中国EC的增加速率分别为8.5 gC·m-2·yr-1 (p<0.05)、3.7~21.0 gC·m-2·yr-1 (p<0.05)。2021—2100年中国东南部、内蒙古高原、青藏高原等地区显著增加(37~44 gC·m-2·yr-1,p<0.05),云贵高原南部、两广丘陵等地区显著减少(45~72 gC·m-2·yr-1,p<0.05);仅考虑气候变化可能降低中国EC,预计2081—2100年相比于2001–2020年将下降1.5–5.8%。在中国西北地区温度为影响EC的主导因子,受区域干旱程度影响,EC与降水的相关性由东南向西北递增,在高纬度高海拔地区辐射是EC的主导因子,在中国47.9-56.1 %的区域CO2浓度主导EC变化。

关键词: 气候变化, 潜在自然植被生态系统碳储量, LPJ-GUESS模型, 主导因子, 中国

Abstract: Aims Carbon sequestration in terrestrial ecosystems is one of the important ways to slow down the rise of atmospheric CO2 concentration. Understanding the natural vegetation ecosystems carbon storage (EC) under climate change is conducive to the formulation of regional land management policies. Methods In this study, the sensitive parameters of LPJ-GUESS model are calibrated based on genetic algorithm. Using the downscale climate data-driven model, combined with Mann Kendall test, Sen's slope estimation and partial correlation analysis, the temporal and spatial pattern, trend change characteristics and climate dominant factors of China's EC from 2001 to 2100 are analyzed. Important findings The Nash-Sutcliffe efficiency coefficient and Pearson correlation coefficient of the calibrated LPJ-GUESS model in simulating EC are 0.751and 0.901 respectively, indicating that the LPJ-GUESS model can simulate China's EC well. During 2001–2020, China's EC decreased from southeast to northwest, with a total amount of 156.06 Pg C.. Vegetation, litter and soil accounted for 34.2%, 1.9% and 63.8% respectively. The EC in 2081–2100 have the same spatial heterogeneity as that in historical periods. Compared with 2001–2020, the total amount of EC at the end of this century are expected to increase by 0.51–11.16 Pg C. During 2001–2020 and 2021–2100, the growth rates of China's EC was 8.5 gC·m-2·yr-1 (p<0.05) and 3.7–21.0 gC·m-2·yr-1 (p<0.05) respectively. During 2021–2100, there was a significant increase in southeast China, inner Mongolia Plateau, Qinghai Tibet Plateau and other regions (37–44 gC·m-2·yr-1, p<0.05), while the southern Yunnan Guizhou Plateau, Liangguang hills and other regions decreased significantly (45–72 gC·m-2·yr-1, p<0.05). Considering only that climate change may reduce China's EC, compared with 2001–2020, it will decrease by 1.5–5.8% during 2081–2100. In northwest China, temperature is the dominant factor affecting EC, Affected by the degree of regional drought, the correlation between EC and precipitation increases from southeast to northwest, In high latitude and high-altitude areas, radiation is the dominant factor of EC, 47.9-56.1% of China's area,CO2 is the dominant factor of EC.

Key words: climate change, potential natural vegetation ecosystem carbon storage, LPJ-GUESS, dominant factor, China