Vegetation dynamics and their response to freshwater inflow and climate variables in the Yellow River Delta, China

Jiang, Dejuan; Fu, Xing; Wang, Kun

doi:10.1016/j.quaint.2012.10.059

Cited by 40 publications

(25 citation statements)

References 27 publications

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“…As one of the key components of terrestrial ecosystems, vegetation plays an important role in regulating energy exchange, the carbon cycle, and climate change through photosynthesis, surface albedo, and roughness [1,2] and is recognized as a natural linkage between the pedosphere, atmosphere, and hydrosphere of the Earth's systems [3][4][5]. Improved knowledge of vegetation variations and their relationship with climatic variables (mostly focusing on precipitation and temperature) at various spatial and temporal scales is an important and desirable goal for projecting future vegetation growth trends and their responses to climatic change [6,7].…”

Section: Introductionmentioning

confidence: 99%

“…Improved knowledge of vegetation variations and their relationship with climatic variables (mostly focusing on precipitation and temperature) at various spatial and temporal scales is an important and desirable goal for projecting future vegetation growth trends and their responses to climatic change [6,7]. Recently, the response of vegetation to climate change has attracted considerable attention, particularly since the satellite-derived normalized difference vegetation index (NDVI) has been available from the early 1980s [7][8][9][10][11] and has increasingly become a hot topic in climate-change studies [4,5].…”

Section: Introductionmentioning

confidence: 99%

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NDVI-Based Long-Term Vegetation Dynamics and Its Response to Climatic Change in the Mongolian Plateau

et al. 2014

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Abstract:The response of vegetation to regional climate change was quantified between 1982 and 2010 in the Mongolian plateau by integrating the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) and the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI (2000NDVI ( -2010. Average NDVI values for the growing season (April-October) were extracted from the AVHRR and MODIS NDVI datasets after cross-calibrating and consistency checking the dataset, based on the overlapping period of 2000-2006. Correlations between NDVI and climatic variables (temperature and precipitation) were analyzed to understand the impact of climate change on vegetation dynamics in the plateau. The results indicate that the growing-season NDVI generally exhibited an upward trend with both temperature and precipitation before the mid-or late 1990s. However, a downward trend in the NDVI with significantly decreased precipitation has been observed since the mid-or late 1990s. This is an apparent reversal in the NDVI trend from 1982 to 2010. Pixel-based analysis further indicated that the timing of the NDVI trend reversal varied across different regions and for different vegetation types. We found that approximately 66% of the plateau showed an OPEN ACCESS Remote Sens. 2014, 6 8338 increasing trend before the reversal year, whereas 60% showed a decreasing trend afterwards. The vegetation decline in the last decade is mostly attributable to the recent tendency towards a hotter and drier climate and the associated widespread drought stress. Monitoring precipitation stress and associated vegetation dynamics will be important for raising the alarm and performing risk assessments for drought disasters and other related natural disasters like sandstorms.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

NDVI-Based Long-Term Vegetation Dynamics and Its Response to Climatic Change in the Mongolian Plateau

et al. 2014

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“…Vegetation, as an important component of terrestrial ecosystems, links pedosphere, atmosphere, and hydrosphere of the Earth's system (Salim et al 2008;Zhong et al 2010). Vegetation dynamics are highly associated with climate regimes (Piao et al 2006;Fabricante et al 2009;Meng et al 2011), and thus, land cover can serve as an ecological indicator for environmental changes at the local, regional, and global scales (Piao et al 2006;Yu et al 2006;Potter et al 2008;Salim et al 2008;Jiang et al 2013). Nemani et al (2003) estimated that water availability most strongly limits vegetation growth for over 40 % of Earth's vegetated surface, while temperature over 33 % and radiation over 27 % of Earth's vegetated surface.…”

Section: Introductionmentioning

confidence: 99%

“…Changes in vegetation cover can also affect local, regional, and global climate through various physical, physiological, and chemical feedbacks (Kaufmann et al 2003;Suzuki et al 2007;Zhou et al 2007;Salim et al 2008;Zuo et al 2011). Vegetation dynamics and their correlations with climate variables have become one of the main themes of global change studies (Rees et al 2001;Yu et al 2006;Jiang et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Interannual variability and correlation of vegetation cover and precipitation in Eastern China

Jiang

Zhang

et al. 2013

Theor Appl Climatol

Self Cite

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Based on the SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) data and daily precipitation data of 357 meteorological stations, the spatial and temporal variability of vegetation cover, measured by NDVI, and precipitation as well as their relationships are investigated in Eastern China, which is portioned into three subregions (regions I, II, and III), for the period 1998-2010. The results show that high NDVI values appear mainly in Northeastern China and in August while high precipitation (PRETOT) occurs in Southeastern China and in July (June for Southern China). Extreme precipitation days (RD95p) and amount (EPRETOT) coincide well with PRETOT. Extreme precipitation intensity (RINTEN) has a similar spatial variability to PRETOT but with a smaller seasonal variation than PRETOT. Growing season NDVI is positively correlated with PRETOT in 11.7 % of the study area (mostly in arid to subhumid regions of Northern China), where precipitation is a limiting factor for vegetation growth. In contrast, a negative correlation between growing season NDVI and PRETOT is found in 4.8 % of the study area, mostly in areas around the Yangtze River and deep Northeastern China. No significant correlations between these two variables are found for the other regions because vegetation response to precipitation is affected by other factors such as temperature, radiation, and human disturbance. On a monthly scale, there is a positive correlation between NDVI and PRETOT in May (for region II) and September (all subregions except region I). NDVI variations lag 1 month behind PRETOT in June (for region I) and October. Correlations between NDVI and RD95p, EPRETOT are similar to that with PRETOT, but the relationships between NDVI and RINTEN are relatively weaker than with PRETOT. This study provides the technical basis for agriculture development and ecological construction in Eastern China.

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“…During the period from 1961 to 2010, the annual average temperature in the coastal wetlands of the Yellow River Delta increased by 1.85 • C, while the annual precipitation decreased by 121.42 mm [83]. A large number of studies have shown that over the past four decades precipitation decreased in the Yellow River Basin and the area showed a warm and dry trend [83][84][85][86]. The precipitation in the upper and middle reaches of the river has decreased due to the warm and dry regional climate.…”

Section: Climate Changementioning

confidence: 99%

Four Decades of Estuarine Wetland Changes in the Yellow River Delta Based on Landsat Observations Between 1973 and 2013

Zhu

Zhang

Huang

2018

Water

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Yellow River Delta wetlands are essential for the migration of endangered birds and breeding. The wetlands, however, have been severely damaged during recent decades, partly due to the lack of wetland ecosystem protection by authorities. To have a better historical understanding of the spatio-temporal dynamics of the wetlands, this study aims to map and characterize patterns of the loss and degradation of wetlands in the Yellow River Delta using a time series of remotely sensed images (at nine points in time) based on object-based image analysis and knowledge transfer learning technology. Spatio-temporal analysis was conducted to document the long-term changes taking place in different wetlands over the four decades. The results showed that the Yellow River Delta wetlands have experienced significant changes between 1973 and 2013. The total area of wetlands has been reduced by 683.12 km 2 during the overall period and the trend of loss continues. However, the rates and trends of change for the different types of wetlands were not the same. The natural wetlands showed a statistically significant decrease in area during the overall period (36.04 km 2 ·year −1 ). Meanwhile, the artificial wetlands had the opposite trend and showed a statistically significant increase in area during the past four decades (18.96 km 2 ·year −1 ). According to the change characteristics revealed by the time series wetland classification maps, the evolution process of the Yellow River Delta wetlands could be divided into three stages: (1) From 1973From -1984, basically stable, but with little increase; (2) from 1984-1995, rapid loss; and (3) from 1995-2013, slow loss. The area of the wetlands reached a low point around 1995, and then with a little improvement, the regional wetlands entered a slow loss stage. It is believed that interference by human activities (e.g., urban construction, cropland creation, and oil exploitation) was the main reason for wetland degradation in the Yellow River Delta over the past four decades. Climate change also has long-term impacts on regional wetlands. In addition, due to the special geographical environment, the hydrological and sediment conditions and the location of the Yellow River mouth also have a significant influence on the evolution process of the wetlands.

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Vegetation dynamics and their response to freshwater inflow and climate variables in the Yellow River Delta, China

Cited by 40 publications

References 27 publications

NDVI-Based Long-Term Vegetation Dynamics and Its Response to Climatic Change in the Mongolian Plateau

NDVI-Based Long-Term Vegetation Dynamics and Its Response to Climatic Change in the Mongolian Plateau

Interannual variability and correlation of vegetation cover and precipitation in Eastern China

Four Decades of Estuarine Wetland Changes in the Yellow River Delta Based on Landsat Observations Between 1973 and 2013

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