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.

scholarly journals Quantifying the Impacts of Anthropogenic Activities and Climate Variations on Vegetation Productivity Changes in China from 1985 to 2015

2020 ◽  
Vol 12 (7) ◽  
pp. 1113
Author(s):  
Shahid Naeem ◽  
Yongqiang Zhang ◽  
Jing Tian ◽  
Faisal Mueen Qamer ◽  
Aamir Latif ◽  
...  
Keyword(s):  
Climate Change ◽  
Primary Productivity ◽  
Human Activities ◽  
Vegetation Cover ◽  
Net Primary Productivity ◽  
Anthropogenic Activities ◽  
Climate Factors ◽  
Climate Variations ◽  
Base Period ◽  
Increasing Trends

Accurate assessment of vegetation dynamics provides important information for ecosystem management. Anthropogenic activities and climate variations are the major factors that primarily influence vegetation ecosystems. This study investigates the spatiotemporal impacts of climate factors and human activities on vegetation productivity changes in China from 1985 to 2015. Actual net primary productivity (ANPP) is used to reflect vegetation dynamics quantitatively. Climate-induced potential net primary productivity (PNPP) is used as an indicator of climate change, whereas the difference between PNPP and ANPP is considered as an indicator of human activities (HNPP). Overall, 91% of the total vegetation cover area shows declining trends for net primary productivity (NPP), while only 9% shows increasing trends before 2000 (base period). However, after 2000 (restoration period), 78.7% of the total vegetation cover area shows increasing trends, whereas 21.3% of the area shows decreasing trends. Moreover, during the base period, the quantitative contribution of climate change to NPP restoration is 0.21 grams carbon per meter square per year (gC m−2 yr−1) and to degradation is 2.41 gC m−2 yr−1, while during the restoration period, climate change contributes 0.56 and 0.29 gC m−2 yr−1 to NPP restoration and degradation, respectively. Human activities contribute 0.36 and 0.72 gC m−2 yr−1 during the base period, and 0.63 and 0.31 gC m−2 yr−1 during the restoration period to NPP restoration and degradation, respectively. The combined effects of climate and human activities restore 0.65 and 1.11 gC m−2 yr−1, and degrade 2.01 and 0.67 gC m−2 yr−1 during the base and restoration periods, respectively. Climate factors affect vegetation cover more than human activities, while precipitation is found to be more sensitive to NPP change than temperature. Unlike the base period, NPP per unit area increases with an increase in the human footprint pressure during the restoration period. Grassland has more variability than other vegetation classes, and the grassland changes are mainly observed in Tibet, Xinjiang, and Inner Mongolia regions. The results may help policy-makers by providing necessary guidelines for the management of forest, grassland, and agricultural activities.

scholarly journals Vegetation Changes in Response to Climatic Factors and Human Activities in Jilin Province, China, 2000–2019

2021 ◽  
Vol 13 (16) ◽  
pp. 8956
Author(s):  
Ying Li ◽  
Zhibo Zhao ◽  
Lingzhi Wang ◽  
Guanghui Li ◽  
Lei Chang ◽  
...  
Keyword(s):  
Human Activities ◽  
Climatic Factors ◽  
Dynamic Change ◽  
Jilin Province ◽  
Vegetation Changes ◽  
Forest Land ◽  
Barren Land ◽  
Average Temperature ◽  
The Impact ◽  
Permanent Wetland

Dynamic change in vegetation is an integral component of terrestrial ecosystems, which has become a significant research area in the current context of global climate warming. Jilin Province in northeast China is an ecologically fragile area, and there is an urgent need to understand its vegetation changes and responses to both climatic factors and human activities. The normalized difference vegetation index (NDVI) was used to analyze trends in vegetation growth, and indicated significant growth overall. The NDVI of different vegetation cover types is increasing, indicating that the vegetation is continuously greening, and in descending order, the growth trends were grassland (0.0035/year) > permanent wetland (0.0028/year) > cropland (0.0027/year) > forest land (0.0022/year) > barren land (−0.0001/year). Grassland and cropland vegetation types included the most severely degraded areas, with fluctuating NDVI values. Precipitation was the main positive controlling climatic factor of NDVI in the western regions of the study area, while average temperature was the main factor in the eastern regions. Precipitation was the main climatic control factor for grassland and cropland, while forest land was limited by precipitation and average temperature. Barren land and permanent wetland were slightly negatively correlated with precipitation. From 2000 to 2019, the residual values for NDVI increased from −0.0121 to 0.0116, and the impact of human activities on vegetation changed from negative to positive. By 2019, the proportion of positively affected zones was as high as 94.01%, and the negatively affected zones were mainly distributed across transitional areas of cropland and grassland, and urban and built-up land and forest land.

scholarly journals Monitoring Vegetation Change and Its Potential Drivers in Inner Mongolia from 2000 to 2019

2021 ◽  
Vol 13 (17) ◽  
pp. 3357
Author(s):  
Yao Kang ◽  
Enliang Guo ◽  
Yongfang Wang ◽  
Yulong Bao ◽  
Yuhai Bao ◽  
...  
Keyword(s):  
Human Activities ◽  
Vegetation Dynamics ◽  
Inner Mongolia ◽  
Vegetation Change ◽  
Spatiotemporal Variability ◽  
Annual Precipitation ◽  
Dominant Factor ◽  
Variation Method ◽  
Vegetation Changes ◽  
Northeastern Part

Inner Mongolia in China is a typically arid and semi-arid region with vegetation prominently affected by global warming and human activities. Therefore, investigating the past and future vegetation change and its impact mechanism is important for assessing the stability of the ecosystem and the ecological policy formulation. Vegetation changes, sustainability characteristics, and the mechanism of natural and anthropogenic effects in Inner Mongolia during 2000–2019 were examined using moderate resolution imaging spectroradiometer normalized difference vegetation index (NDVI) data. Theil–Sen trend analysis, Mann–Kendall method, and the coefficient of variation method were used to analyze the spatiotemporal variability characteristics and sustained stability of the NDVI. Furthermore, a trend estimation method based on a Seasonal Trend Model (STM), and the Hurst index was used to analyze breakpoints and change trends, and predict the likely future direction of vegetation, respectively. Additionally, the mechanisms of the compound influence of natural and anthropogenic activities on the vegetation dynamics in Inner Mongolia were explored using a Geodetector Model. The results show that the NDVI of Inner Mongolia shows an upward trend with a rate of 0.0028/year (p < 0.05) from 2000 to 2019. Spatially, the NDVI values showed a decreasing trend from the northeast to the southwest, and the interannual variation fluctuated widely, with coefficients of variation greater than 0.15, for which the high-value areas were in the territory of the Alxa League. The areas with increased, decreased, and stable vegetation patterns were approximately equal in size, in which the improved areas were mainly distributed in the northeastern part of Inner Mongolia, the stable and unchanged areas were mostly in the desert, and the degraded areas were mainly in the central-eastern part of Inner Mongolia, it shows a trend of progressive degradation from east to west. Breakpoints in the vegetation dynamics occurred mainly in the northwestern part of Inner Mongolia and the northeastern part of Hulunbuir, most of which occurred during 2011–2014. The future NDVI trend in Inner Mongolia shows an increasing trend in most areas, with only approximately 10% of the areas showing a decreasing trend. Considering the drivers of the NDVI, we observed annual precipitation, soil type, mean annual temperature, and land use type to be the main driving factors in Inner Mongolia. Annual precipitation was the first dominant factor, and when these four dominant factors interacted to influence vegetation change, they all showed interactive enhancement relationships. The results of this study will assist in understanding the influence of natural elements and human activities on vegetation changes and their driving mechanisms, while providing a scientific basis for the rational and effective protection of the ecological environment in Inner Mongolia.

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 Zmiany na rynku mięsa wieprzowego w Polsce w latach 2001 2017

2019 ◽  
Vol 19(34) (2) ◽  
pp. 174-185
Author(s):  
Stanisław Stańko ◽  
Aneta Mikuła
Keyword(s):  
Growth Rate ◽  
High Variability ◽  
Downward Trend ◽  
Meat Production ◽  
Medium Term ◽  
Upward Trend ◽  
Eu Countries ◽  
Pork Products ◽  
Negative Balance ◽  
The Eu

Changes in pork supply in Poland in the years 2001-2017 were presented. The pig population was characterized by a downward trend in all groups of animals. In the years 2001-2007, livestock imports grew annually by 71 thousand pcs, and in the years 2008-2017 by 603.5 thousand pcs. The increasing scale of livestock import slowed the decline in meat production. Livestock export was characterized by high variability and was small. Meat imports were characterized by a growing scale and pace (almost 32% per annum in 2001-2008 and 3.1% in 2009-2017). Meat exports grew, and the growth rate since 2009 exceeded the scale of import growth, which improved the negative balance of meat trade. Exports of pork products were characterized by a rapid upward trend, and small imports. Pork prices in Poland "followed" average prices in EU countries. In the medium term, the growth rate of prices in the EU and in Poland will be small (0.8% per year). In the medium term Poland will remain a significant livestock importer.

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