Regional differences in the factors that affect vegetation cover in China

Ma, Zihao; Guo, Jiahong; Li, Weiming; Cai, Zhaoyang; Cao, Shixiong

doi:10.1002/ldr.3847

Cited by 17 publications

(8 citation statements)

References 42 publications

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“…Vegetation absorbs carbon dioxide and releases oxygen through photosynthesis to realize the value of carbon fixation and oxygen release (Zhang et al, 2017). In addition, the growth state of vegetation reflects the positive and negative feedback of human beings to natural vegetation , (Liu et al, 2015) as well as whether environmental protection policies (Ma et al, 2021) and ecological construction (Jiang et al, 2015) have achieved initial results. Therefore, dynamic monitoring of the vegetation is used to study and analyze the relationship between vegetation change and climate change and human activities (Jiang et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Spatial-temporal changes of NDVI in the three northeast provinces and its dual response to climate change and human activities

Wang²,

Liu³

et al. 2022

Front. Environ. Sci.

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As the most important ecological barrier in eastern China, the three northeast provinces have extraordinary ecological significance. Their geographical location and climatic conditions make the distribution pattern of vegetation unique. Among them, climate change and human activities are the main factors affecting the richness and complexity of vegetation, climate change dominates the overall pattern of vegetation distribution, and regional human intervention locally changes the growth state of vegetation. Therefore, based on NDVI data of vegetation, meteorological data and socio-economic data, statistical methods such as Sen’s slope estimator, Mann-Kendall trend test, center of gravity transfer model, Hurst index and coefficient of variation were adopted to analyze the spatio-temporal changes and future trends in vegetation coverage; The use of Geographic detector to understand the relationship between NDVI to climate change and human activities. The results suggested that: 1) The three northeast provinces of China experienced an overall increasing NDVI at a rate of 0.016%/year from 2001 to 2020. The NDVI shows intensive heterogeneity in space, exhibiting a landscape of high in the East, low in the west, high in the north and low in the south; 2) The results of geographic detectors show that the temporal and spatial distribution pattern of vegetation NDVI is mainly determined by ≥ 10°C accumulated temperature, ≥ 0°C accumulated temperature, annual average temperature and land use type. The interaction between factors presents a bi-variable enhancement and nonlinear enhancement, and human activity factors enhance the contribution of climate factors. 3) Future changes in NDVI indicated that the vegetation coverage showed a trend of “overall improvement and regional degradation” from 2001 to 2020, and showed reverse persistence. The degraded area of vegetation will be more than the improved area. The research results will help the three northeast provinces cope with global climate change, enrich the research on the vegetation in the three northeastern provinces, and provide a scientific basis for formulating appropriate regional ecological protection policies.

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Section: Introductionmentioning

confidence: 99%

Spatial-temporal changes of NDVI in the three northeast provinces and its dual response to climate change and human activities

Wang²,

Liu³

et al. 2022

Front. Environ. Sci.

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“…From 1980 to 2015, China's land use/cover has experienced significant changes superimposed by climate change and human activities, especially after the concept of 'sustainable development' incorporated into the National Strategic Plan in 1997 (Z. Ma et al, 2021; Wei et al, 2018). How to achieve the balance between environmental protection and economic development under the influence of policies in the study area is worthy of in‐depth study (Liang et al, 2021; H. Liu et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

“…1980 to 2015, China's land use/cover has experienced significant changes superimposed by climate change and human activities, especially after the concept of 'sustainable development' incorporated into the National Strategic Plan in 1997 (Z Ma et al, 2021;Wei et al, 2018)…”

mentioning

confidence: 99%

Dynamic changes of land use/cover and landscape pattern in a typical alpine river basin of theQinghai‐TibetPlateau, China

Zuo

et al. 2021

Land Degrad Dev

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Landscape heterogeneity is a comprehensive reflection of spatial patch and gradient, which is an important feature of landscape pattern. The China land use/cover dataset (CLUD) with 1 km spatial resolution was used in this study to investigate the dynamic changes of land use/cover in the Yarlung Tsangpo River basin (YTRB) of China from 1980 to 2015 through the land use transition matrix and dynamic degrees. The semivariogram model of the study area was constructed at different scales to determine the landscape characteristic scale of the YTRB. The traditional landscape index method and moving window method were used to investigate the watershed landscape pattern at the class and landscape levels, respectively. The results showed that the overall change in land use over the YTRB was not significant during the period 1980-2015, whereas the relative change in each type of land use was significant. Permanent glacier-snow significantly degraded by 22.72%, while built-up areas increased by 106.38%. The degree of the landscape fragmentation and diversity gradually increased from upstream to downstream. The unused land has the highest degree of fragmentation, and the agglomeration degree of urban land patches increased. The result of land use dynamic degree indicated that natural factors were the main causes of changes in land use during the first sub-period 1980-2000, while human activities were the major drivers of changes in land use during the second sub-period 2000-2015. The results can provide important information on the impact of regional development and environmental governance policies on the changes in land use/cover and landscape in Tibet.

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“…The prediction of FVC due to human activities will also bring uncertainty. In the historical period, with China's rapid urbanization and population growth, overgrazing, deforestation and overcultivation have caused serious impacts on the ecological environment (Ma et al, 2021), the Chinese government has successively implemented a series of ecological restoration projects, such as the Three-North Shelter Forest Program (TNSFP) The Grain to Green Program (GGP) and the Natural Forest Protection Program (NFPP), launched in 1999 have become the main factors for vegetation restoration in southern, northeastern, northwestern and central China (Gang et al, 2019;Chen et al, 2021b). As a result, human activities can greatly affect the growth of vegetation in local areas.…”

Section: Uncertainty and Impactmentioning

confidence: 99%

Study on fractional vegetation cover dynamic in the Yellow River Basin, China from 1901 to 2100

Jian

Shi

Cui

et al. 2023

Front. For. Glob. Change

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Increasing climate change makes vegetation dynamic. At the same time, dynamic changes in vegetation not only have a feedback effect on climate change, but also affect the hydrological cycle process. Therefore, understanding the vegetation change and its response to climate change is a priority for predicting future climate change and studying the impact of vegetation change on the hydrological cycle. In this study, the Yellow River Basin in China is the study area. Based on the analysis of the evolution characteristics of meteorological elements and fractional vegetation cover (FVC), the delta downscaling Coupled Model Intercomparison Project Phase 6 (CMIP6) models are optimized. The empirical orthogonal function (EOF) and singular value decomposition (SVD) methods are used to investigate the impact of climate change on vegetation in the Yellow River Basin. The results show that: (1) in the four scenarios (SSP126, SSP245, SSP370, and SSP585), FVC in the Yellow River Basin from 2022 to 2100 shows an increasing trend, SSP370 (0.017 10a–1) > SSP126 (0.014 10a–1) > SSP245 (0.0087 10a–1) > SSP585 (0.0086 10a–1). Spatially, FVC in most regions of the Yellow River Basin show an increasing trend under the four scenarios, and the degraded areas are concentrated in a small part of the Yellow River headwaters. (2) There is a significant positive correlation between FVC and precipitation (Pre) and temperature (Tem) under four scenarios in the Yellow River Basin from 2022 to 2100. Under the same scenario, the annual average temperature can be considered as the dominant factor of FVC change in the Yellow River Basin. Under different scenarios, the impact of climate change on FVC under the high emission scenarios is greater than that under the low emission scenarios. This study will help to better understand the response of vegetation to climate change and provide a scientific basis for formulating ecological protection measures to cope with future climate change in the Yellow River Basin.

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Regional differences in the factors that affect vegetation cover in China

Cited by 17 publications

References 42 publications

Spatial-temporal changes of NDVI in the three northeast provinces and its dual response to climate change and human activities

Spatial-temporal changes of NDVI in the three northeast provinces and its dual response to climate change and human activities

Dynamic changes of land use/cover and landscape pattern in a typical alpine river basin of theQinghai‐TibetPlateau, China

Study on fractional vegetation cover dynamic in the Yellow River Basin, China from 1901 to 2100

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