Impacts of climate change and anthropogenic activities on vegetation change: Evidence from typical areas in China

Zheng, Kaiyuan; Tan, Linshan; Sun, Yun; Wu, Yanjuan; Duan, Zheng; Xu, Yu; Gao, Chao

doi:10.1016/j.ecolind.2021.107648

Cited by 90 publications

(47 citation statements)

References 64 publications

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“…However, there have been downward trends in these two indices in the eastern development areas such as the Beijing-Tianjin-Hebei region and the Yangtze River Delta due accelerated urbanization. In addition, afforestation programs implemented in China over the past few decades have played an important role in promoting the greening of vegetation throughout the country [11].…”

Section: Introductionmentioning

confidence: 99%

Response of NDVI of Natural Vegetation to Climate Changes and Drought in China

Wang

Cao

et al. 2021

Land

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Temporal and spatial changes in vegetation and their influencing factors are of great significance for the assessment of climate change and sustainable development of ecosystems. This study applied the Asymmetric Gaussians (AG) fitting method, Mann-Kendall test, and correlation analysis to the Global Inventory Monitoring and Modeling System (GIMMS) third-generation Normalized Difference Vegetation Index and gridded climate and drought data for 1982–2015. The temporal and spatial changes to NDVI for natural grassland and forest during the growing season were analyzed. Relationships among NDVI, climate change, and droughts were also analyzed to reveal the influence of vegetation change. The results showed that: (1) Land use/cover change (LUCC) in China was mainly represented by increases in agricultural land (Agrl) and urban and rural land (Uril), and decreases in unutilized land (Bald), grassland, forest, and permanent glacier and snow (Snga). The increase in agricultural land was mainly distributed in the western northwest arid area (WNW) and northern North China (NNC), whereas regions with severe human activities such as southern South China (SNC), western South China (WSC), and eastern South China (ESC) showed significant decreases in agricultural land due to conversion to urban and rural land. (2) The start of the growing season (SOS) was advanced in WNW, SNC, WSC, and ESC, and the end of growing season (EOS) was delayed in WNW, NNC, and SNC. The growing season length (GSL) of natural vegetation in China has been extended by eight days over the last 34 years. However, the phenology of the Qinghai-Tibet Plateau (TP) was opposite to that of the other regions and the GSL showed an insignificant decreasing trend. (3) The NDVI increased significantly, particularly in the SNC, WSC, ESC, and the grassland of the WNW. Precipitation was found to mainly control the growth of vegetation in the arid and semi-arid regions of northwest China (WNW and ENW), and precipitation had a much greater impact on grassland than on forests. Temperature had an impact on the growth of vegetation throughout China, particularly in SNC, ESC, and WSC. (4) The Standardized Precipitation Evapotranspiration Index (SPEI) showed a downward trend, indicating an aridification trend in China, particularly in ENW, NNC, and WNW. Similar to precipitation, the main areas affected by drought were WNW and ENW and grassland was found to be more sensitive to drought than forest. The results of this study are of great significance for predicting the response of ecosystem productivity to climate change under future climate change scenarios.

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Section: Introductionmentioning

confidence: 99%

Response of NDVI of Natural Vegetation to Climate Changes and Drought in China

Wang

Cao

et al. 2021

Land

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“…In contrast, MODIS NDVI datasets based on a single sensor are not affected by platform/sensor shift, which maintains data consistency. Due to high data quality and moderate spatiotemporal resolution, the MODIS NDVI datasets have been widely used in research of vegetation change [16][17][18][19][20]. Compared to these three main NDVI datasets, the Landsat datasets have a higher spatial resolution (30 m).…”

Section: Introductionmentioning

confidence: 99%

Quantifying Influences of Natural and Anthropogenic Factors on Vegetation Changes Based on Geodetector: A Case Study in the Poyang Lake Basin, China

2021

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Understanding the driving mechanism of vegetation changes is essential for vegetation restoration and management. Vegetation coverage in the Poyang Lake basin (PYLB) has changed dramatically under the context of climate change and human activities in recent decades. It remains challenging to quantify the relative contribution of natural and anthropogenic factors to vegetation change due to their complicated interaction effects. In this study, we selected the Normalized Difference Vegetation Index (NDVI) as an indicator of vegetation growth and used trend analysis and the Mann-Kendall test to analyze its spatiotemporal change in the PYLB from 2000 to 2020. Then we applied the Geodetector model, a novel spatial analysis method, to quantify the effects of natural and anthropogenic factors on vegetation change. The results showed that most regions of the basin were experiencing vegetation restoration and the overall average NDVI value in the basin increased from 0.756 to 0.809 with an upward yearly trend of +0.0026. Land-use type exerted the greatest influence on vegetation change, followed by slope, elevation, and soil types. Except for conversions to construction land, most types of land use conversion induced an increase in NDVI in the basin. The influence of one factor on vegetation NDVI was always enhanced when interacting with another. The interaction effect of land use types and population density was the largest, which could explain 45.6% of the vegetation change, indicating that human activities dominated vegetation change in the PYLB. Moreover, we determined the ranges or types of factors most suitable for vegetation growth, which can be helpful for decision-makers to optimize the implementation of ecological projects in the PYLB in the future. The results of this study could improve the understanding of the driving mechanisms of vegetation change and provide a valuable reference for ecological restoration in subtropical humid regions.

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“…Temporally, Shaanxi Province showed a fluctuational increase trend in vegetation cover between 1982 and 2015, which was broadly consistent with the most parts of the global scale, especially in the mid-latitudes of the Northern Hemisphere [ 60 , 61 ]. After 1990, there was an obvious breakpoint in Shaanxi Province.…”

Section: Discussionmentioning

confidence: 66%

“…Climate factors have an important influence on the growth and development of vegetation [ 68 ]. Many studies have demonstrated that temperature and precipitation were the main meteorological factors affecting the vegetation index evolution [ 11 , 61 , 69 ]. From 1982 to 2015, Shaanxi Province showed a warmer trend, which was consistent with the fact of global warming.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive Insights into Spatial-Temporal Evolution Patterns, Dominant Factors of NDVI from Pixel Scale, as a Case of Shaanxi Province, China

Chen

2021

IJERPH

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Based on long term NDVI (1982–2015), climate, topographic factors, and land use type data information in Shaanxi Province, multiple methods (linear regression, partial and multiple correlation analysis, redundancy analysis and boosted regression trees method) were conducted to evaluate the spatial-temporal change footprints and driving mechanisms in the pixel scale. The results demonstrated that (1) the overall annual average and seasonal NDVI in this region showed a fluctuating upward trend, especially in spring. The difference between the end of season (eos) and start of season (sos) gradually increased, indicating the occurrence of temporal “greening” across most Shaanxi Province. (2) The overall spatial distribution of annual mean NDVI in Shaanxi Province was prominent in the south and low in the north, and 98.83% of the areas had a stable and increasing trend. Pixel scale analysis reflected the spatial continuity and heterogeneity of NDVI evolution. (3) Trend and breakpoint evaluation results showed that evolutionary trends were not homogeneous. There were obvious breakpoints in the latitude direction of NDVI evolution in Shaanxi Province, especially between 32–33°N and in the north of 37° N. (4) Compared with precipitation, the annual average temperature was significantly correlated with the vegetation indices (annual NDVI, max NDVI, time integrated NDVI) and phenology metrics (sos, eos). (5) Considering the interaction between environmental variables, the NDVI evolution was dominated by the combined influence of climate and geographic location factors in most areas.

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Impacts of climate change and anthropogenic activities on vegetation change: Evidence from typical areas in China

Cited by 90 publications

References 64 publications

Response of NDVI of Natural Vegetation to Climate Changes and Drought in China

Response of NDVI of Natural Vegetation to Climate Changes and Drought in China

Quantifying Influences of Natural and Anthropogenic Factors on Vegetation Changes Based on Geodetector: A Case Study in the Poyang Lake Basin, China

Comprehensive Insights into Spatial-Temporal Evolution Patterns, Dominant Factors of NDVI from Pixel Scale, as a Case of Shaanxi Province, China

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