Vegetation Responses to Climate Change and Anthropogenic Activity in China, 1982 to 2018

Abstract

Climate change and human activities significantly affect vegetation growth in terrestrial ecosystems. Here, data reconstruction was performed to obtain a time series of the normalized difference vegetation index (NDVI) for China (1982–2018) based on Savitzky–Golay filtered GIMMS NDVI3g and MOD13A2 datasets. Combining surface temperature and precipitation observations from more than 2000 meteorological stations in China, Theil–Sen trend analysis, Mann–Kendall significance tests, Pearson correlation analysis, and residual trend analysis were used to quantitatively analyze the long-term trends of vegetation changes and their sources of uncertainty. Significant spatial and temporal heterogeneity was observed in vegetation changes in the study area. From 1982 to 2018, the vegetation showed a gradually increasing trend, at a rate of 0.5%·10 a−1, significantly improving (37.15%, p < 0.05) more than the significant degradation (7.46%, p < 0.05). Broadleaf (0.66) and coniferous forests (0.62) had higher NDVI, and farmland had the fastest rate of increase (1.02%/10 a−1). Temperature significantly affected the vegetation growth in spring (R > 0; p < 0.05); however, the increase in summer temperatures significantly inhibited (R < 0; p < 0.05) the growth in North China (RNDVI-tem = −0.379) and the Qinghai–Tibetan Plateau (RNDVI-tem = −0.051). Climate change has highly promoted the growth of vegetation in the plain region of the Changjiang (Yangtze) River (3.24%), Northwest China (1.07%). Affected by human activities only, 49.89% of the vegetation showed an increasing trend, of which 22.91% increased significantly (p < 0.05) and 9.97% decreased significantly (p < 0.05). Emergency mitigation actions are required in Northeast China, Xinjiang, Northwest China, and the Qinghai–Tibetan Plateau. Therefore, monitoring vegetation changes is important for ecological environment construction and promoting regional ecological protection.

Vegetation Dynamics in Response to Climate Change and Human Activities in a Typical Alpine Region in the Tibetan Plateau

“…According to Figure 3, areas where HA contributed more to vegetation changes were mainly distributed in areas showing intensive human factors, such as farmlands and artificial surfaces. Studies by Jin et al [31], Yi et al [41], Li et al [62], Liu et al [70], and Qu et al [71] also showed a similar rule that HA is the main contributor to vegetation change in agricultural areas or urbanization areas. Thus, the findings proved that the residual analysis method using a regression between NDVI and meteorological data, and the use of residuals to indirectly estimate the impact of HA on vegetation changes were suitable.…”

“…Remote sensing-based normalized difference vegetation index (NDVI) has been extensively used to reflect vegetation dynamics [57][58][59][60][61][62][63]. This study used the Google Earth Engine (GEE) platform to obtain NDVI data of Gannan Prefecture from 2000 to 2020 (https://doi.org/10.5067/MODIS/MOD13A1.006), at spatial and temporal resolutions of 500 m and 16 d, respectively.…”

Monitoring long‐term vegetation dynamics over the Yangtze River Basin, China, using multi‐temporal remote sensing data

“…Variations in land cover are closely related to the human living environment (Gao et al, 2022; Zhang, Jiang, et al, 2022). Vegetation dynamics are mainly influenced by both climate change and human activities (Ge et al, 2021; Li et al, 2022; Zhou et al, 2021). In terms of greening trends, 35% is attributed to climate change, while 65% is associated with human factors (Qiao et al, 2021).…”

Vegetation Change in Katsina State, Nigeria: Influence of Local Perceptions and Land Use Land Cover Dynamics

“…As a result of climate change, land use, and habitat loss, global vegetation has changed dramatically over the past 18,000 years (Mottl et al 2021;Li et al 2022). However, the magnitude and patterns of vegetation change are poorly understood at the global scale (Chapin 2003;Mottl et al 2021).…”