生态环境学报 ›› 2025, Vol. 34 ›› Issue (5): 665-677.DOI: 10.16258/j.cnki.1674-5906.2025.05.001
• 研究论文【生态学】 •
下一篇
张亚丽1,2(), 黄柱军1, 田义超1,2,*(
), 林俊良1, 覃彩焕1
收稿日期:
2024-10-18
出版日期:
2025-05-18
发布日期:
2025-05-16
通讯作者:
*田义超。E-mail: 作者简介:
张亚丽(1987年生),女,副教授,硕士,主要研究方向为区域生态环境保护与监测的研究工作。E-mail: zhangyali1100@hotmail.com
基金资助:
ZHANG Yali1,2(), HUANG Zhujun1, TIAN Yichao1,2,*(
), LIN Junliang1, QIN Caihuan1
Received:
2024-10-18
Online:
2025-05-18
Published:
2025-05-16
摘要:
气候变化对植被的影响存在滞后和累积效应。探究西南区域极端气候变化对植被生长的影响,为中国西南区域植被恢复和生态安全提供数据支撑。基于气象数据和MODIS数据,采用像元二分法、趋势分析和时滞与累积效应分析等方法,分析了西南地区植被覆盖度时空演变特征以及极端气候变化对植被覆盖度的时滞与累积效应影响。研究结果表明,1)时间上,植被覆盖度年均值呈显著上升趋势,年际变化率均值为0.032/(10a)(p<0.01);空间上,75.6%区域的植被呈改善趋势,其中51.1%区域植被呈现出显著改善趋势。2)植被覆盖度对极端气候指数时滞与累积效应的响应主要表现累积效应,其中降雨指数1-3个月累积效应面积占比在50.9%-71.5%之间,温度指数累积效应面积介于43.6%-64.1%之间;而时滞效应影响较为集中,主要分布于云南地区,时滞3个月的面积占比相对较大。3)气候变化和人类活动及其他因素分别对西南地区植被覆盖度的变化贡献了54.5%和45.5%,气候贡献度大于80%的区域面积约占26.7%,主要集中研究区西部的横断山脉及高海拔的原始森林地区。人类活动贡献度超过80%的区域主要集中在四川盆地、重庆以及人口密集的低海拔区域。西南地区气候变化对植被覆盖度变化的影响大于人类活动。
中图分类号:
张亚丽, 黄柱军, 田义超, 林俊良, 覃彩焕. 极端气候对西南地区植被覆盖度变化的时滞与累积效应[J]. 生态环境学报, 2025, 34(5): 665-677.
ZHANG Yali, HUANG Zhujun, TIAN Yichao, LIN Junliang, QIN Caihuan. Time-lag and Accumulation Responses of Fractional Vegetation Coverage Change to Extreme Climate in Southwestern China[J]. Ecology and Environmental Sciences, 2025, 34(5): 665-677.
气候指数 | 符号 | 定义 | 单位 |
---|---|---|---|
平均气温 | Tem | 每日平均温度的月平均值 | ℃ |
日最低气温的极小值 | TNn | 每月日最低气温的极小值 | ℃ |
日最低气温的极大值 | TNx | 每月日最低气温的极大值 | ℃ |
日最高气温的极小值 | TXn | 每月日最高气温的极小值 | ℃ |
日最高气温的极大值 | TXx | 每月日最高气温的极大值 | ℃ |
气温日较差 | DTR | 日最高气温与日最低气温的差值 | ℃ |
降水 | Pre | 每月降水总量 | mm |
小-中雨 | MLR | 每月日降水总量 0-25 mm的降水量 | mm |
大雨 | HR | 每月日降水总量 25-50 mm的降水量 | mm |
暴雨 | TR | 每月日降水总量大于 50 mm的降水量 | mm |
1日最大降水量 | RX-1-d | 每月最大1日降水量 | mm |
5日最大降水量 | RX-5-d | 每月连续最大5日降水量 | mm |
表1 极端气候指数名称及释义
Table 1 Description of Extreme Climate Indicators
气候指数 | 符号 | 定义 | 单位 |
---|---|---|---|
平均气温 | Tem | 每日平均温度的月平均值 | ℃ |
日最低气温的极小值 | TNn | 每月日最低气温的极小值 | ℃ |
日最低气温的极大值 | TNx | 每月日最低气温的极大值 | ℃ |
日最高气温的极小值 | TXn | 每月日最高气温的极小值 | ℃ |
日最高气温的极大值 | TXx | 每月日最高气温的极大值 | ℃ |
气温日较差 | DTR | 日最高气温与日最低气温的差值 | ℃ |
降水 | Pre | 每月降水总量 | mm |
小-中雨 | MLR | 每月日降水总量 0-25 mm的降水量 | mm |
大雨 | HR | 每月日降水总量 25-50 mm的降水量 | mm |
暴雨 | TR | 每月日降水总量大于 50 mm的降水量 | mm |
1日最大降水量 | RX-1-d | 每月最大1日降水量 | mm |
5日最大降水量 | RX-5-d | 每月连续最大5日降水量 | mm |
植被覆盖度斜率(SF) | 贡献因素 | 气候变化对植被覆盖度变化的贡献斜率 (SC) | 人活动及其它因素对 FVC变化的贡献斜率(SH) | 贡献度/% | |
---|---|---|---|---|---|
气候变化 | 人类活动及其他因素 | ||||
>0 | 共同作用 | >0 | >0 | (SC/SF)×100 | (SH/SF)×100 |
气候变化 | >0 | <0 | 100 | 0 | |
人活动及其它 | <0 | >0 | 0 | 100 | |
<0 | 共同作用 | <0 | <0 | (SC/SF)×100 | (SH/SF)×100 |
气候变化 | <0 | >0 | 100 | 0 | |
人活动及其它 | >0 | <0 | 0 | 100 |
表2 气候变化和人类活动对植被覆盖度变化的贡献
Table 2 The contributions of climate change and human activities to changes in vegetation coverage
植被覆盖度斜率(SF) | 贡献因素 | 气候变化对植被覆盖度变化的贡献斜率 (SC) | 人活动及其它因素对 FVC变化的贡献斜率(SH) | 贡献度/% | |
---|---|---|---|---|---|
气候变化 | 人类活动及其他因素 | ||||
>0 | 共同作用 | >0 | >0 | (SC/SF)×100 | (SH/SF)×100 |
气候变化 | >0 | <0 | 100 | 0 | |
人活动及其它 | <0 | >0 | 0 | 100 | |
<0 | 共同作用 | <0 | <0 | (SC/SF)×100 | (SH/SF)×100 |
气候变化 | <0 | >0 | 100 | 0 | |
人活动及其它 | >0 | <0 | 0 | 100 |
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