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

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

Chenhua Shen  1   2   3 , Rui Wu  1   2
Affiliations

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

Chenhua Shen et al. Heliyon. .

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.

Keywords: Anthropogenic activity; Changing trend; Meteorological factors; NDVI; Nonlinear contribution.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Time-varying regression coefficients (Panels a and b) of temperature and precipitation, temperature time series (Panel c), NDVI time series (Panel d), contribution of climate (Panel e), and contribution of anthropogenic activity (Panel f) against time for a typical grid point.
Fig. 2
Fig. 2
Basic statistical parameter in LWLR. Panel (a) for monthly slope of NDVI time series. Panels (b and c) for monthly slope of temperature and precipitation time series, respectively. Panel (d) for the ratio of dual optimal bandwidths. Panels (e and f) for the averages of time-varying regression coefficients of temperature and precipitation over time, respectively.
Fig. 3
Fig. 3
Average predicted contributions of climate and anthropogenic activity to NDVI.
Fig. 4
Fig. 4
Role of anthropogenic activity in NDVI dynamics. In Panel (d), cyan curved lines represented the Yellow River (upper) and the Yangtze River (down)
See this image and copyright information in PMC

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