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采用局部加权回归方法分析气候变化和人为活动对中国归一化植被指数的非线性贡献。

Analyzing nonlinear contributions from climate change and anthropogenic activity to the normalized difference vegetation index across China using a locally weighted regression approach.

作者信息

Shen Chenhua, Wu Rui

机构信息

College of Geographical Science, Nanjing Normal University, Nanjing, 210046, China.

Key Laboratory of Virtual Geographic Environment of Ministry of Education, Nanjing, 210046, China.

出版信息

Heliyon. 2023 May 25;9(6):e16694. doi: 10.1016/j.heliyon.2023.e16694. eCollection 2023 Jun.

Abstract

Nonlinear contributions from climate change and anthropogenic activity to the Normalized Difference Vegetation Index (NDVI) are analyzed to better understand the mechanisms underlying the nonlinear response of vegetation growth. In this study, it was hypothesized that NDVI dynamics on a nonlinear trajectory could track fluctuations of climate change and anthropogenic activity. Contributions from climate change and anthropogenic activity to NDVI were quantified using a locally weighted regression approach based on monthly timescale datasets. The findings showed that: 1) Vegetation cover fluctuated and increased in 81% of regions in China from 2000 to 2019. 2) The average predicted nonlinear contribution (APNC) of anthropogenic activity to NDVI was positive in China. The temperature APNC was positive in most of China but negative in Yunnan, where high temperatures and asynchronous temporal changes in temperature and NDVI were observed. The precipitation APNC was positive in the north of the Yangtze River, where precipitation is insufficient; but negative in South China, where precipitation is plentiful. Anthropogenic activity had the highest magnitude among the three nonlinear contributions, followed by temperature and precipitation. 3) The regions with contribution rates of anthropogenic activity greater than 80% were mainly distributed in the central Loess Plateau, North China Plain, and South China, while the areas with contribution rates of climate change greater than 80% were mainly concentrated in the northeastern QTP, Yunnan, and Northeast China. 4) The high temperature, drought, and asynchronous temporal changes in temperature, precipitation, and NDVI caused the negative average of changing trends in the predicted nonlinear contribution (PNC) of climate change to NDVI. Deforestation, land cover change, and grazing/fencing led to the negative average of changing trends in PNC from anthropogenic activity. These findings deepen our understanding of the mechanisms underlying the nonlinear responses of vegetation growth to climate change and anthropogenic activity.

摘要

分析气候变化和人为活动对归一化植被指数(NDVI)的非线性贡献,以更好地理解植被生长非线性响应的潜在机制。在本研究中,假设处于非线性轨迹上的NDVI动态可以追踪气候变化和人为活动的波动。基于月度时间尺度数据集,使用局部加权回归方法量化气候变化和人为活动对NDVI的贡献。研究结果表明:1)2000年至2019年,中国81%的地区植被覆盖度波动并增加。2)在中国,人为活动对NDVI的平均预测非线性贡献(APNC)为正。温度APNC在中国大部分地区为正,但在云南为负,在云南观察到高温以及温度和NDVI的异步时间变化。降水APNC在长江以北降水不足的地区为正;而在降水丰富的华南地区为负。在这三种非线性贡献中,人为活动的贡献量最大,其次是温度和降水。3)人为活动贡献率大于80%的区域主要分布在黄土高原中部、华北平原和华南地区,而气候变化贡献率大于80%的区域主要集中在青藏高原东北部、云南和中国东北地区。4)高温、干旱以及温度、降水和NDVI的异步时间变化导致气候变化对NDVI的预测非线性贡献(PNC)变化趋势的平均值为负。森林砍伐、土地覆盖变化以及放牧/围栏导致人为活动PNC变化趋势的平均值为负。这些发现加深了我们对植被生长对气候变化和人为活动非线性响应潜在机制的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e020/10245264/6717400de528/gr1.jpg

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