Vegetation dynamics and the relations with climate change at multiple time scales in the Yangtze River and Yellow River Basin, China

Zhang, Wei; Wang, Lunche; Xiang, Feifei; Qin, Wenmin; Jiang, Weixia

doi:10.1016/j.ecolind.2019.105892

Cited by 127 publications

(81 citation statements)

References 66 publications

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“…Therefore, the EEMD method is suitable for detecting the nonlinear trends of NPP. NPP dynamics is driven by climatic factors and human activities (Ahmed, Nawaz, Woulds, & Drake, 2020;Fan, Liu, Tao, Wang, & Zhou, 2018;Zhang, Wang, Xiang, Qin, & Jiang, 2020a). Numerous studies have studied the impacts of climate change on NPP but fewer focused on human activities (Azhdari et al, 2020;Gu et al, 2017;.…”

Section: Introductionmentioning

confidence: 99%

Effects of land use changes on the nonlinear trends of net primary productivity in arid and semiarid areas, China

et al. 2021

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Monitoring the nonlinear trend of net primary productivity (NPP) is essential for assessing the changes of ecosystems quality. Land use change caused by human activities is considered to be a key factor leading to vegetation changes. However, how land use change impacts the nonlinear trend of NPP has not yet been determined. This article analyzed the nonlinear trend of NPP in arid and semiarid areas of China during in the period 1982-2015 based on the ensemble empirical mode decomposition (EEMD) method and elucidated the effects of land use changes on the nonlinear trends of NPP. The results revealed that: (a) With the EEMD method, although monotonic increase was the main type of the trend of NPP (28.40 %), trend reversals from increase to decrease and from decrease to increase accounted for 13.52 and 20.90 % of the study area, respectively. (b) Although vegetation in most types of land use has been improved a lot, it has not been improved significantly in forest areas and changed from improvement to degradation in some forest and urban land areas. (c) Urbanization limited vegetation recovery but other land use changes generally favoured vegetation improvement. Although afforestation improved vegetation, there was a considerable area of the forest converted from nonforest threatened by the changes from improvement to degradation due to water limitation.Overall, nonlinear trend analysis can reveal the hidden trend reversals to prevent the overestimation or underestimation of the risk of vegetation degradation and is conducive to accurate assessment of the effects of land use changes on vegetation trends. K E Y W O R D Sarid and semiarid areas, ensemble empirical mode decomposition (EEMD) method, land use change, net primary productivity, nonlinear trend analysis

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Section: Introductionmentioning

confidence: 99%

Effects of land use changes on the nonlinear trends of net primary productivity in arid and semiarid areas, China

et al. 2021

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“…56 On driving factors analysis of forest biomass, the annual average value of factors were considered, and the extreme value of factors will be applied in future research to find the influence of extreme climatic conditions on biomass. [57][58][59]…”

Section: Discussionmentioning

confidence: 99%

Long-term changes of forest biomass and its driving factors in karst area, Guizhou, China

Qian

Qiang

Zhang

et al. 2021

International Journal of Distributed Sensor Networks

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The spatiotemporal dynamic changes of forest biomass can provide scientific reference and scheme for improving the quality of forest resources and the ecological environment in karst areas. In this article, the China’s National Forest Continuous Inventory data (from 1984 to 2015) was used to analyze the dynamic changes of forest biomass with the univariate linear slope k, barycenter trajectory, improved hot spots detection which was applied in the analysis of forest biomass dynamic change, and geospatial detector method in Guizhou in the first time. The results showed that the total forest biomass had a steady upward trend, 29.3% unit biomass of the forest had significantly increased, while 1.4% decreased dramatically. The forest biomass gravity center shifted from Qiandongnan to Qiannan, with a total distance of 54.1 km. Thus, the following conclusions were drawn: (1) benefiting from the effective implementation of forestry-related policies, the forest biomass had significant increased in a long time series, especially for the artificial shelter forest; (2) the gravity center shifted to the northwest and the number of level 1 forest biomass hot spots increased year by year, which showed a generalized symmetric pattern along the Wujiang River mainstream; and (3) the results of geographical survey showed that the change of forest biomass was greatly affected by topography, climate and human activities, among which terrain factors had the greatest impact.

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“…Zhang et al studied the spatiotemporal heterogeneity of vegetation coverage with relationship to climate change in the Yangtze river basin (YZRB) and Yellow river basin (YRB) in China and found that the growing-season NDVI increased by 0.011/decade during study period. A significant upward trend in vegetation coverage in the central and eastern part of YRB and the central part of YZRB was found, whereas in the eastern part of YZRB vegetation coverage considerably decreased [63]. They also found in the central area of the YRB-YZRB that the vegetation were influenced more by climate change than by anthropogenic activities, whereas in other parts of YZRB and in the southwest part of the YRB-YZRB areas the vegetation were influenced more by anthropogenic activities than by climate change [63].…”

Section: Introductionmentioning

confidence: 88%

“…A significant upward trend in vegetation coverage in the central and eastern part of YRB and the central part of YZRB was found, whereas in the eastern part of YZRB vegetation coverage considerably decreased [63]. They also found in the central area of the YRB-YZRB that the vegetation were influenced more by climate change than by anthropogenic activities, whereas in other parts of YZRB and in the southwest part of the YRB-YZRB areas the vegetation were influenced more by anthropogenic activities than by climate change [63]. Jiang et al studied the impact of climate change and human activities on vegetation dynamics in the ago-pastoral transitional zone of northern China (APTZNC), an arid and semi-arid ecosystem.…”

Section: Introductionmentioning

confidence: 88%

Anthropogenic Factors Affecting the Vegetation Dynamics in the Arid Middle East

Rousta¹,

Ólafsson²,

Zhang³

et al. 2020

Preprint

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The spatiotemporal variability of vegetation in the Middle East was investigated for the period 2001–2019 using the Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day/500 m composites of the Normalized Difference Vegetation Index (NDVI; MOD13A1). The results reveal a strong increase in the NDVI coverage in the Middle East during the study period (R = 0.75, p-value = 0.05). In Egypt, the annual coverage exhibits the strongest positive trend (R = 0.99, p-value = 0.05). In Turkey, both the vegetation coverage and density increased from 2001 to 2019, which can be attributed to the construction of some of the biggest dams in the Middle East, such as the Atatürk and Ilisu dams. Significant increases in the annual coverage and maximum and average NDVI in Saudi Arabia are due to farming in the northern part of the country for which groundwater and desalinated seawater are used. The results of this study suggest that the main factors affecting the vegetation coverage in the Middle East are governmental policies. These policies can have a positive effect on the vegetation coverage in some countries such as Egypt, Saudi Arabia, Qatar, Kuwait, Iran, and Turkey.

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Vegetation dynamics and the relations with climate change at multiple time scales in the Yangtze River and Yellow River Basin, China

Cited by 127 publications

References 66 publications

Effects of land use changes on the nonlinear trends of net primary productivity in arid and semiarid areas, China

Effects of land use changes on the nonlinear trends of net primary productivity in arid and semiarid areas, China

Long-term changes of forest biomass and its driving factors in karst area, Guizhou, China

Anthropogenic Factors Affecting the Vegetation Dynamics in the Arid Middle East

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