Spatiotemporal changes in vegetation coverage and its driving factors in the Three-River Headwaters Region during 2000–2011

Liu, Xianfeng; Zhang, Jinshui; Zhu, Xiufang; Pan, Yaozhong; Liu, Yanxu; Zhang, Donghai; Lin, Zhaohui

doi:10.1007/s11442-014-1088-0

Cited by 122 publications

(61 citation statements)

References 7 publications

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“…The slope of the linear regression was employed as an index to fit the trend in the vegetation dynamics for every pixel using the least squares method for a given study period, which can comprehensively reflect the spatiotemporal variation characteristics of vegetation coverage [32,33]. The slope is calculated as follows:…”

Section: Analysis Of Trends In Vegetation Dynamicsmentioning

confidence: 99%

Changes in Growing Season Vegetation and Their Associated Driving Forces in China during 2001–2012

Liu

Zhu

et al. 2015

Remote Sensing

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Abstract:In recent decades, the monitoring of vegetation dynamics has become crucial because of its important role in terrestrial ecosystems. In this study, a satellite-derived normalized difference vegetation index (NDVI) was combined with climate factors to explore the spatiotemporal patterns of vegetation change during the growing season, as well as their driving forces in China from 2001 to 2012. Our results showed that the growing season NDVI increased continuously during 2001-2012, with a linear trend of 1.4%/10 years (p < 0.01). The NDVI in north China mainly exhibited an increasing spatial trend, but this trend was generally decreasing in south China. The vegetation dynamics were mainly at a moderate intensity level in both the increasing and decreasing areas. The significantly increasing trend in the NDVI for arid and semi-arid areas of northwest China was attributed mainly to an increasing trend in the NDVI during the spring, whereas that for the north and northeast of China was due to an increasing trend in the NDVI during the summer and autumn. Different vegetation types exhibited great variation in their trends, where the grassforb community had the highest linear trend of 2%/10 years (p < 0.05), followed by meadow, and needle-leaf forest with the lowest increasing trend, i.e., a linear trend of 0.3%/10 years. OPEN ACCESSRemote Sens. 2015, 7 15518Our results also suggested that the cumulative precipitation during the growing season had a dominant effect on the vegetation dynamics compared with temperature for all six vegetation types. In addition, the response of different vegetation types to climate variability exhibited considerable differences. In terms of anthropological activity, our statistical analyses showed that there was a strong correlation between the cumulative afforestation area and NDVI during the study period, especially in a pilot region for ecological restoration, thereby suggesting the important role of ecological restoration programs in ecological recovery throughout China in the last decade.

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Section: Analysis Of Trends In Vegetation Dynamicsmentioning

confidence: 99%

Changes in Growing Season Vegetation and Their Associated Driving Forces in China during 2001–2012

Liu

Zhu

et al. 2015

Remote Sensing

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“…The increase in precipitation would benefit vegetation growth and soil moisture retention, thereby reducing the occurrence of aeolian desertification. Previous studies documented that the response of aeolian desertification to precipitation has a time lag [46], which was mainly reflected in the response of vegetation coverage to precipitation [29]. In the whole study area, the mean annual precipitation has shown a generally feeble decrease between 1970 and 2010 (Figure 6a), with an average rate of 0.69 mm per decade.…”

Section: Driving Forces Responsible For Changes In the Vulnerability mentioning

confidence: 83%

“…As the main part of the terrestrial ecosystem, vegetation plays the role of an "indicator" in the research into global change, because it is not only as the bearer of climate change, but also as a generator of feedback effect on climate change [29]. Especially in the areas prone to the development of desertification, vegetation coverage generally varied according to the degree of aeolian desertification, which can be used to monitor desertification.…”

Section: Indicator Systemmentioning

confidence: 99%

A GIS-Based Assessment of Vulnerability to Aeolian Desertification in the Source Areas of the Yangtze and Yellow Rivers

Ren

Dong

et al. 2016

Remote Sensing

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Aeolian desertification is a kind of land degradation that is characterized by aeolian activity, resulting from the responses of land ecosystems to climate change and anthropogenic disturbances. The source areas of the Yangtze and Yellow Rivers are typical regions of China's Tibetan Plateau affected by aeolian desertification. We assessed the vulnerability of these areas to aeolian desertification by combining remote sensing with geographical information system technologies. We developed an assessment model with eight indicators, whose weights were determined by the analytical hierarchy process. Employing this model, we analyzed the spatial distribution of vulnerability to aeolian desertification and its changes from 2000 to 2010, and discuss the implications. Overall, low-vulnerability land was the most widespread, accounting for 64%, 62%, and 71% of the total study area in 2000, 2005, and 2010, respectively. The degree of vulnerability showed regional differences. In the source areas of the Yangtze River, land with high or very high vulnerability accounted for 17.4% of this sub-region in 2010, versus 2.6% in the source areas of the Yellow River. In the Zoige Basin, almost all of the land had very low to low vulnerability. To understand the change in vulnerability to aeolian desertification, we calculated an integrated vulnerability index (IVI). This analysis indicated that the vulnerability to aeolian desertification increased from 2000 to 2005 (IVI increased from 2.1709 to 2.2463), and decreased from 2005 to 2010 (IVI decreased from 2.2463 to 2.0057). Increasing regional temperatures appear to be primarily responsible for the change in vulnerability to aeolian desertification throughout the region. The effects of other factors (climatic variation and human activities) differed among the various sub-regions. The implementation of the ecological restoration project has achieved a noticeable effect since 2005. Our results provide empirical support for effort to protect the ecology of this ecologically fragile region.

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“…The vegetation coverage is increasing, but it is not obvious that the community structure has improved [20]: Overgrazing is still severe, which is one of the main causes of grassland deterioration [47]; an increase in precipitation could promote vegetation growth, but the erosive force of rainfall has also been strengthened [38]; and, with further increases in temperature, the climate could gradually show a warming and drying trend, which would inhibit the growth of vegetation [24]. Further, while the water supply capacity has clearly increased, besides the increase in precipitation, the melting of glaciers and permafrost due to the rising temperatures has also increased the runoff, which is unsustainable and could threaten the local ecosystem balance.…”

Section: Discussionmentioning

confidence: 99%

“…Shao et al [22,23] reported that, after the implementation of the ecological projects, the ecosystem degradation in the TRHR has basically been contained, and the conditions have been partially meliorated. Liu et al [24] found that the vegetation coverage in the TRHR displayed an upward trend under the combined effects of climate change and the projects based on the analysis of the NDVI dataset from 2000 to 2011. Huang et al [25] indicated that, comparing before and after 2004, the area of grassland deterioration increased slightly, while International and domestic researchers have conducted many studies at both the regional and local scales on LULC change in the TRHR.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of Land Use/Cover and Macroscopic Ecological Changes in the Headwaters of the Yangtze River and of the Yellow River over the Past 30 Years

et al. 2016

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Based on land use and land cover (LULC) datasets in the late 1970s, the early 1990s, 2004 and 2012, we analyzed characteristics of LULC change in the headwaters of the Yangtze River and Yellow River over the past 30 years contrastively, using the transition matrix and LULC change index. The results showed that, in 2012, the LULC in the headwaters of the Yellow River were different compared to those of the headwaters of the Yangtze River, with more grassland and wet-and marshland. In the past 30 years, the grassland and wet-and marshland increasing at the expense of sand, gobi, and bare land and desert were the main LULC change types in the headwaters of the Yangtze River, with the macro-ecological situation experiencing a process of degeneration, slight melioration, and continuous melioration, in that order. In the headwaters of the Yellow River, severe reduction of grassland coverage, shrinkage of wet-and marshland and the consequential expansion of sand, gobi and bare land were noticed. The macro-ecological situation experienced a process of degeneration, obvious degeneration, and slight melioration, in that order, and the overall change in magnitude was more dramatic than that in the headwaters of the Yangtze River. These different LULC change courses were jointly driven by climate change, grassland-grazing pressure, and the implementation of ecological construction projects.

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Spatiotemporal changes in vegetation coverage and its driving factors in the Three-River Headwaters Region during 2000–2011

Cited by 122 publications

References 7 publications

Changes in Growing Season Vegetation and Their Associated Driving Forces in China during 2001–2012

Changes in Growing Season Vegetation and Their Associated Driving Forces in China during 2001–2012

A GIS-Based Assessment of Vulnerability to Aeolian Desertification in the Source Areas of the Yangtze and Yellow Rivers

Characteristics of Land Use/Cover and Macroscopic Ecological Changes in the Headwaters of the Yangtze River and of the Yellow River over the Past 30 Years

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