Relative importance of climate change and human activities for vegetation changes on China's silk road economic belt over multiple timescales

CATENA ◽  
2019 ◽  
Vol 180 ◽  
pp. 224-237 ◽  
Author(s):  
Xiangzhen Qi ◽  
Junhe Jia ◽  
Huiyu Liu ◽  
Zhenshan Lin
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Silk Road ◽  
Vegetation Changes ◽  
Relative Importance ◽  
Multiple Timescales ◽  
Silk Road Economic Belt

scholarly journals Quantifying the Relative Importance of Climate Change and Human Activities on Selected Wetland Ecosystems in China

2020 ◽  
Vol 12 (3) ◽  
pp. 912
Author(s):  
Yongcai Dang ◽  
Hongshi He ◽  
Dandan Zhao ◽  
Michael Sunde ◽  
Haibo Du
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
R Package ◽  
Wetland Loss ◽  
Forested Wetland ◽  
Relative Importance ◽  
Contribution Rate ◽  
Wetland Ecosystems ◽  
Respective Contribution ◽  
Wetland Types

Climate change and human activities are important factors driving changes in wetland ecosystems. It is therefore crucial to quantitatively characterize the relative importance of these stressors in wetlands. Previous such analyses have generally not distinguished between wetland types, or have focused on individual wetland types. In this study, three representative wetland areas of the upper, middle and lower reaches of the Heilongjiang River Basin (HRB) were selected as the study area. An object-based classification was used with Landsat TM data to extract the spatial distribution of wetland in 1990, 2000 and 2010. We then quantified the relative importance of climate change and human activities on the wetlands by using the R package “relaimpo” package. The results indicated that: (1) the effects of human activities on wetland changes were greater (contribution rate of 63.57%) than climate change in the HRB. Specifically, there were differences in the relative importance of climate change and human activities for wetlands in different regions. Wetlands of the upper reaches were more affected by climate change, while wetlands in the middle and lower reaches were more affected by human activities; (2) climate change had a greater impact (contribution rate of 65.72%) on low intensity wetland loss, while human activities had a greater impact on moderate and severe intensity wetland loss, with respective contribution rates of 57.22% and 70.35%; (3) climate change had a larger effect on the shrub and forested wetland changes, with respective contribution rates of 58.33% and 52.58%. However, human activities had a larger effect on herbaceous wetland changes, with a contribution rate of 72.28%. Our study provides a useful framework for wetland assessment and management, and could be a useful tool for developing wetland utilization and protection approaches, particularly in sensitive environments in mid- and high-latitude areas.

scholarly journals Using Budyko-Type Equations for Separating the Impacts of Climate and Vegetation Change on Runoff in the Source Area of the Yellow River

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3418
Author(s):  
Dan Yan ◽  
Zhizhu Lai ◽  
Guangxing Ji
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Vegetation Change ◽  
Yellow River ◽  
Climatic Factors ◽  
Source Area ◽  
The Yellow River ◽  
Vegetation Changes ◽  
Potential Evaporation ◽  
Runoff Change

Assessing the contribution rates of climate change and human activities to the runoff change in the source area of the Yellow River can provide support for water management in the Yellow River Basin. This paper firstly uses a multiple linear regression method to evaluate the contribution rates of climate change and human activities to the vegetation change in the source area of the Yellow River. Next, the paper uses the Budyko hypothesis method to calculate the contribution rates of climatic factors (including precipitation, potential evaporation, and subsequent vegetation changes) and vegetation changes caused by human activities to the runoff change of the Tangnaihai Hydrometric Station. The results showed that: (1) the annual runoff and precipitation in the source area of the Yellow River have a downward trend, while the annual potential evaporation and NDVI (Normalized Difference Vegetation Index) show an increasing trend; (2) The contribution rates of climate change and human activities to the vegetation change in the source area of the Yellow River is 62.79% and 37.21%, respectively; (3) The runoff change became more and more sensitive to changes in climate and underlying surface characteristic parameters; (4) The contribution rates of climatic factors (including precipitation, potential evaporation, and subsequent vegetation changes) and vegetation changes caused by human activities to the runoff change at Tangnaihai Hydrological Station are 75.33% and 24.67%, respectively; (5) The impact of precipitation on runoff reduction is more substantial than that of potential evaporation.

scholarly journals Quantitative Contributions of Climate Change and Human Activities to Vegetation Changes in the Upper White Nile River

2021 ◽  
Vol 13 (18) ◽  
pp. 3648
Author(s):  
Bo Ma ◽  
Shanshan Wang ◽  
Christophe Mupenzi ◽  
Haoran Li ◽  
Jianye Ma ◽  
...  
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Human Activities ◽  
Vegetation Change ◽  
Agricultural Land ◽  
Future Trend ◽  
Nile River ◽  
Vegetation Changes ◽  
The Future ◽  
White Nile

Vegetation changes in the Upper White Nile River (UWNR) are of great significance to the maintenance of local livelihoods, the survival of wildlife, and the protection of species habitats. Based on the GIMMS NDVI3g and MODIS normalized difference vegetation index (NDVI) data, the temporal and spatial characteristics of vegetation changes in the UWNR from 1982 to 2020 were analyzed by a Theil-Sen median trend analysis and Mann-Kendall test. The future trend of vegetation was analyzed by the Hurst exponential method. A partial correlation analysis was used to analyze the relationship of the vegetation and climate factors, and a residual trend analysis was used to quantify the influence of climate change and human activities on vegetation change. The results indicated that the average NDVI value (0.75) of the UWNR from 1982 to 2020 was relatively high. The average coefficient of variation for the NDVI was 0.059, and the vegetation change was relatively stable. The vegetation in the UWNR increased 0.013/10 year on average, but the vegetation degradation in some areas was serious and mainly classified as agricultural land. The results of a future trend analysis showed that the vegetation in the UWNR is mainly negatively sustainable, and 62.54% of the vegetation will degrade in the future. The NDVI of the UWNR was more affected by temperature than by precipitation, especially on agricultural land and forestland, which were more negatively affected by warming. Climate change and human activities have an impact on vegetation changes, but the spatial distributions of the effects differ. The relative impact of human activities on vegetation change accounted for 64.5%, which was higher than that of climate change (35.5%). Human activities, such as the large proportion of agriculture, rapid population growth and the rapid development of urbanization were the main driving forces. Establishing a cross-border drought joint early warning mechanism, strengthening basic agricultural research, and changing traditional agricultural farming patterns may be effective measures to address food security and climate change and improve vegetation in the UWNR.

scholarly journals Human disturbance caused stronger influences on global vegetation change than climate change

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7763
Author(s):  
Xianliang Zhang ◽  
Xuanrui Huang
Keyword(s):  
Climate Change ◽  
Human Disturbance ◽  
Human Activities ◽  
Vegetation Change ◽  
Vegetation Changes ◽  
Vegetation Distribution ◽  
Human Disturbances ◽  
The Past ◽  
Desert Regions ◽  
Global Vegetation

Global vegetation distribution has been influenced by human disturbance and climate change. The past vegetation changes were studied in numerous studies while few studies had addressed the relative contributions of human disturbance and climate change on vegetation change. To separate the influences of human disturbance and climate change on the vegetation changes, we compared the existing vegetation which indicates the vegetation distribution under human influences with the potential vegetation which reflects the vegetation distribution without human influences. The results showed that climate-induced vegetation changes only occurred in a few grid cells from the period 1982–1996 to the period 1997–2013. Human-induced vegetation changes occurred worldwide, except in the polar and desert regions. About 3% of total vegetation distribution was transformed by human activities from the period 1982–1996 to the period 1997–2013. Human disturbances caused stronger damage to global vegetation change than climate change. Our results indicated that the regions where vegetation experienced both human disturbance and climate change are eco-fragile regions.

Quantitatively distinguish the impact of climate change and human activities on the vegetation changes in Mainland China based on the improved residual method

2020 ◽  
Author(s):  
Yahai Zhang ◽  
Aizhong Ye
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Environmental Changes ◽  
Meteorological Data ◽  
Mainland China ◽  
Vegetation Changes ◽  
Ecological Protection ◽  
The Impact

<p>        Knowledge of the current severe global environmental changes, vegetation has faced the dual challenges posed by climate change and human activities. Quantitatively distinguishing the influence of climate change and human activities on vegetation changes is a key to develop adaptive ecological protection policies. This study used the Normalized Difference Vegetation Index (NDVI) and meteorological data from 1982 to 2015 to analyze the characteristic of vegetation changes and the relationship with climate factors in Mainland China. The contribution rates of climate change and human activities to vegetation dynamics are further calculated by the improved trend method of residual analysis. The results show that 68.81% vegetation of Mainland China is in a state of sustainable increase and cultivated vegetation (CV) and grass are the main greening vegetation types. The impact of human activities (54.45%-75.27%) on vegetation changes in Mainland China is higher than climate change (24.73%-45.46%). Human activities mainly affect grass, mixed coniferous broad-leaved forest (MCBF) and cultivated vegetation (CV), while swamp is more sensitive to climate change. The improved residual trend method considering temporal and spatial dimensions can reduce the uncertainty of the methods. This study provides a theoretical basis for future government implementation of ecological management.</p>

scholarly journals Estimating Relations of Vegetation, Climate Change, and Human Activity: A Case Study in the 400 mm Annual Precipitation Fluctuation Zone, China

2019 ◽  
Vol 11 (10) ◽  
pp. 1159 ◽  
Author(s):  
Yang Li ◽  
Zhixiang Xie ◽  
Yaochen Qin ◽  
Zhicheng Zheng
Keyword(s):  
Climate Change ◽  
Growth Rate ◽  
Human Activities ◽  
Vegetation Cover ◽  
Downward Trend ◽  
Annual Precipitation ◽  
Vegetation Changes ◽  
Cultivated Land ◽  
Forest Land ◽  
Upward Trend

The 400 mm annual precipitation fluctuation zone (75°55′–127°6′E and 26°55′–53°6′N) is located in central and western China, which is a transition area from traditional agricultural to animal husbandry. It is extremely sensitive to climatic changes. The corresponding changes of the ecosystem, represented by vegetation, under the dual influences of climate change and human activities are important issues in the study of the regional ecological environment. Based on the Savitzky–Golay (S–G) filtering method, the Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Differential Vegetation Index (NDVI) dataset (NDVI3g) was reconstructed in this paper. Sen’s slope estimation, Mann–Kendall (M–K), multiple regression residual analysis, and the Hurst index were used to quantify the impacts of climate change and human activities on vegetation; in addition, the future persistence characteristics of the vegetation changes trend were analyzed. Vegetation changes in the study area had an obvious spatio-temporal heterogeneity. On an annual scale, the vegetation increased considerably, with a growth rate of 0.50%/10a. The multi-year mean value of NDVI and growth rate of cultivated land were the highest, followed by the forest land and grassland. On a seasonal scale, the vegetation cover increased most significantly in autumn, followed by spring and summer. In the southeastern and central parts of the study area, the vegetation cover increased significantly (P < 0.05), while it decreased significantly in the northeastern and southwestern parts. In summer, the NDVI value of all vegetation types (cultivated land, forest land and grassland) reached the maximum. The change rate of NDVI value for cultivated land reached the highest in autumn (1.57%/10a), forest land reached the highest in spring (1.15%/10a), and grassland reached the highest in autumn (0.49%/10a). The NDVI of cultivated land increased in all seasons, while forest land (−0.31%/10a) and grassland (−0.009%/10a) decreased in winter. Partial correlation analysis between vegetation and precipitation, temperature found that the areas with positive correlation accounted for 66.29% and 55.05% of the total area, respectively. Under the influence of climate change alone, 62.79% of the study area showed an increasing tendency, among which 46.79% showed a significant upward trend (P < 0.05). The NDVI decreased in 37.21% of the regions and decreased significantly in 14.88% of the regions (P < 0.05). Under the influence of human activities alone, the vegetation in the study area showed an upward trend in 59.61%, with a significant increase in 41.35% (P < 0.05), a downward trend in 40.39%, and a significant downward trend in 7.95% (P < 0.05). Vegetation growth is highly unstable and prone to drastic changes, depending on the environmental conditions.

Local Policy for a Protected Environmental Area Management: The Case of Limiting Motorized Vehicles in Park of Canigou in Pyrenées Orientales

2018 ◽  
Vol 1 (1) ◽  
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Energy Use ◽  
Local Level ◽  
Air Traffic ◽  
Small Scale ◽  
Individual Action ◽  
Local Policy ◽  
Motorized Vehicles ◽  
Local Levels

“We regard the recent science –based consensual reports that climate change is, to a large extend, caused by human activities that emit green houses as tenable, Such activities range from air traffic, with a global reach over industrial belts and urban conglomerations to local small, scale energy use for heating homes and mowing lawns. This means that effective climate strategies inevitably also require action all the way from global to local levels. Since the majority of those activities originate at the local level and involve individual action, however, climate strategies must literally begin at home to hit home.”

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