| 西南高山亚高山区植被活动变化的气候驱动效应与可持续性 |
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| 引用本文： | 孙美荣,孙鹏森. 西南高山亚高山区植被活动变化的气候驱动效应与可持续性[J]. 水土保持研究, 2023, 30(3): 240-250. DOI: 10.13869/j.cnki.rswc.2023.03.018 |
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| 作者姓名： | 孙美荣 孙鹏森 |
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| 作者单位： | (中国林业科学研究院森林生态环境与自然保护研究所, 国家林业和草原局森林生态环境重点实验室, 北京 100091) |
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| 摘 要： | [目的]探究西南高山亚高山区植被活动变化的驱动因素及可持续性，可为其生态系统管理提供一定的科学依据。[方法]基于2001—2018年MODIS NDVI数据和气象数据，用线性回归、Hurst指数、相关分析等方法分析了西南高山亚高山地区植被活动的时空变化特征、植被活动的稳定性和可持续性及对气候变化的响应。[结果](1)研究区以NDVI为代表的植被活动整体上显著增强，其中相对稳定的区域占63.69%,显著增强的区域占25.06%,显著降低的区域占2.73%。在植被类型中，落叶阔叶林的显著绿化趋势最强，而灌木的显著褐化趋势最强，草地对气候变化的敏感性高于林地。植被活动显著增加的区域主要分布在区域东北部的嘉陵江和岷江等地。(2)变异系数(CV)表明NDVI整体稳定性较强，从植被类型看，阔叶林和混交林的稳定性较高，农田的稳定性最低。(3) Hurst指数分析表明，植被活动趋势呈反持续的比例为69.47%,植被活动趋势呈可持续的比例为29.88%,研究区植被总体出现弱反持续性特征，在未来，植被活动增强的趋势有降低或反转的风险；(4)气候驱动因子分析表明，西南高山亚高山区温度对植被的影响占主导，即温...
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| 关 键 词： | 植被活动 气候驱动效应 变异系数 Hurst指数 西南高山亚高山区 |
Climate-Driving Effects and Sustainability of Vegetation Activity Change in Alpine and Subalpine Areas of Southwest China |
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| SUN Meirong1,SUN Pengsen1. Climate-Driving Effects and Sustainability of Vegetation Activity Change in Alpine and Subalpine Areas of Southwest China[J]. Research of Soil and Water Conservation, 2023, 30(3): 240-250. DOI: 10.13869/j.cnki.rswc.2023.03.018 |
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| Authors: | SUN Meirong1 SUN Pengsen1 |
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| Affiliation: | (Key Laboratory of Forest Ecology and Environment of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China) |
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| Abstract: | [Objective]Exploring the driving factors and sustainability of vegetation activity change can provide a scientific basis for ecosystem management in alpine and subalpine areas of southwest China. [Methods] Based on the MODIS NDVI datasets and meteorological datasets from 2001 to 2018, the temporal and spatial variation characteristics, stability and sustainability of vegetation activity, and its response to climate change in the region were analyzed by using linear regression, Hurst exponent and correlation analysis methods. [Results](1)The vegetation activity represented by NDVI increased significantly in the whole study area and the relatively stable area accounted for 63.69%, the significantly increased area accounted for 25.06%, and the significantly decreased area was 2.73%. Among the vegetation types, deciduous broad-leaved forest had the strongest significant greening trend, while shrub had the strongest browning trend. Grassland was more sensitive to climate change than forest. Vegetation activity increased significantly in the Jialing River and Minjiang River in the northeast of the region.(2)The coefficient of variation(CV)showed that the overall stability of NDVI was strong. From the perspective of vegetation types, the stabilities of broad-leaved forest and mixed forest were higher, and that of farmland was the lowest.(3)Hurst exponent analysis showed that the proportion of vegetation activity in anti-persistent trend was 69.47%. The proportion of vegetation activity in persistent trend was 29.88%. The overall vegetation in the study area showed a weak anti-persistent, and the trend of enhanced vegetation activity has the risk of decreasing or reversing in the future.(4)The analysis of climate driving factors showed that the temperature had a dominant influence on vegetation in alpine and subalpine areas of southwest China, i. e., temperature was not only the key factor promoting vegetation greening, but also the key factor of vegetation browning. In the areas of significant vegetation greening, the temperature driving effect of evergreen broad-leaved forest and evergreen coniferous forest was lower than that of deciduous broad-leaved forest and coniferous mixed forest. However, in the areas of significant vegetation browning, the temperature driving effect of the former two was significantly higher than the latter two. [Conclusion] Temperature is the main climate driver of vegetation activity change, and vegetation activity has the characteristic of weak anti-persistence in the future. |
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| Keywords: | vegetation activity climate driving effect coefficient of variation Hurst exponent alpine and subalpine areas of southwest China |
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