scholarly journals Vegetation Phenological Changes in Multiple Landforms and Responses to Climate Change

2020 ◽  
Vol 9 (2) ◽  
pp. 111 ◽  
Author(s):  
Hongzhu Han ◽  
Jianjun Bai ◽  
Gao Ma ◽  
Jianwu Yan
Keyword(s):  
Climate Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Factors ◽  
Growing Season ◽  
Vegetation Phenology ◽  
The South ◽  
Response Characteristics ◽  
The North ◽  
Spatio Temporal

Vegetation phenology is highly sensitive to climate change, and the phenological responses of vegetation to climate factors vary over time and space. Research on the vegetation phenology in different climatic regimes will help clarify the key factors affecting vegetation changes. In this paper, based on a time-series reconstruction of Moderate-Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data using the Savitzky–Golay filtering method, the phenology parameters of vegetation were extracted, and the Spatio-temporal changes from 2001 to 2016 were analyzed. Moreover, the response characteristics of the vegetation phenology to climate changes, such as changes in temperature, precipitation, and sunshine hours, were discussed. The results showed that the responses of vegetation phenology to climatic factors varied within different climatic regimes and that the Spatio-temporal responses were primarily controlled by the local climatic and topographic conditions. The following were the three key findings. (1) The start of the growing season (SOS) has a regular variation with the latitude, and that in the north is later than that in the south. (2) In arid areas in the north, the SOS is mainly affected by the temperature, and the end of the growing season (EOS) is affected by precipitation, while in humid areas in the south, the SOS is mainly affected by precipitation, and the EOS is affected by the temperature. (3) Human activities play an important role in vegetation phenology changes. These findings would help predict and evaluate the stability of different ecosystems.

scholarly journals Phenology Response to Climatic Dynamic across China’s Grasslands from 1985 to 2010

2018 ◽  
Vol 7 (8) ◽  
pp. 290 ◽  
Author(s):  
Jun Wang ◽  
Tiancai Zhou ◽  
Peihao Peng
Keyword(s):  
Climate Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Factors ◽  
Growing Season ◽  
Northern China ◽  
Plant Phenology ◽  
Meadow Steppe ◽  
Typical Steppe ◽  
Alpine Steppe

Because the dynamics of phenology in response to climate change may be diverse in different grasslands, quantifying how climate change influences plant growth in different grasslands across northern China should be particularly informative. In this study, we explored the spatiotemporal variation of the phenology (start of the growing season [SOS], peak of the growing season [POS], end of the growing season [EOS], and length of the growing season [LOS]) across China’s grasslands using a dataset of the GIMMS3g normalized difference vegetation index (NDVI, 1985–2010), and determined the effects of the annual mean temperature (AMT) and annual mean precipitation (AMP) on the significantly changed phenology. We found that the SOS, POS, and EOS advanced at the rates of 0.54 days/year, 0.64 days/year, and 0.65 days/year, respectively; the LOS was shortened at a rate of 0.62 days/year across China’s grasslands. Additionally, the AMT combined with the AMP explained the different rates (ER) for the significantly dynamic SOS in the meadow steppe (R2 = 0.26, p = 0.007, ER = 12.65%) and typical steppe (R2 = 0.28, p = 0.005, ER = 32.52%); the EOS in the alpine steppe (R2 = 0.16, p < 0.05, ER = 6.22%); and the LOS in the alpine (R2 = 0.20, p < 0.05, ER = 6.06%), meadow (R2 = 0.18, p < 0.05, ER = 16.69%) and typical (R2 = 0.18, p < 0.05, ER = 19.58%) steppes. Our findings demonstrated that the plant phenology in different grasslands presented discrepant dynamic patterns, highlighting the fact that climate change has played an important role in the variation of the plant phenology across China’s grasslands, and suggested that the variation and relationships between the climatic factors and phenology in different grasslands should be explored further in the future.

scholarly journals Assessing the Sensitivity of Main Crop Yields to Climate Change Impacts in China

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 172
Author(s):  
Yuan Xu ◽  
Jieming Chou ◽  
Fan Yang ◽  
Mingyang Sun ◽  
Weixing Zhao ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Food Production ◽  
Crop Yields ◽  
Climatic Factors ◽  
Climatic Data ◽  
The South ◽  
The North ◽  
Output Elasticity ◽  
The Impact

Quantitatively assessing the spatial divergence of the sensitivity of crop yield to climate change is of great significance for reducing the climate change risk to food production. We use socio-economic and climatic data from 1981 to 2015 to examine how climate variability led to variation in yield, as simulated by an economy–climate model (C-D-C). The sensitivity of crop yield to the impact of climate change refers to the change in yield caused by changing climatic factors under the condition of constant non-climatic factors. An ‘output elasticity of comprehensive climate factor (CCF)’ approach determines the sensitivity, using the yields per hectare for grain, rice, wheat and maize in China’s main grain-producing areas as a case study. The results show that the CCF has a negative trend at a rate of −0.84/(10a) in the North region, while a positive trend of 0.79/(10a) is observed for the South region. Climate change promotes the ensemble increase in yields, and the contribution of agricultural labor force and total mechanical power to yields are greater, indicating that the yield in major grain-producing areas mainly depends on labor resources and the level of mechanization. However, the sensitivities to climate change of different crop yields to climate change present obvious regional differences: the sensitivity to climate change of the yield per hectare for maize in the North region was stronger than that in the South region. Therefore, the increase in the yield per hectare for maize in the North region due to the positive impacts of climate change was greater than that in the South region. In contrast, the sensitivity to climate change of the yield per hectare for rice in the South region was stronger than that in the North region. Furthermore, the sensitivity to climate change of maize per hectare yield was stronger than that of rice and wheat in the North region, and that of rice was the highest of the three crop yields in the South region. Finally, the economy–climate sensitivity zones of different crops were determined by the output elasticity of the CCF to help adapt to climate change and prevent food production risks.

THE NORMALIZED DIFFERENCE VEGETATION INDEX AS AN INDICATOR OF DYNAMICS

2021 ◽  
Author(s):  
Haddad Amar ◽  
Beldjazia Amina ◽  
Kadi Zahia ◽  
Redjaimia Lilia ◽  
Rached-Kanouni Malika
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Factors ◽  
Mediterranean Ecosystems ◽  
Point Of View ◽  
Aleppo Pine ◽  
Landsat 8 ◽  
North East ◽  
The North ◽  
Pine Trees

Mediterranean ecosystems are considered particularly sensitive to climate change. Any change in climatic factors affects the structure and functioning of these ecosystems and has an influence on plant productivity. The main objective of this work is to characterize one of the Mediterranean ecosystems; the Chettaba forest massif (located in the North-East of Algeria) from a vegetation point of view and their link with monthly variations using Landsat 8 satellite images from five different dates (June 25, 2017, July 27, 2017, August 28, 2017, October 15, 2017). The comparison of NDVI values in Aleppo pine trees was performed using analysis of variance and the use of Friedman's non-parametric test. The Mann-Kendall statistical method was applied to the monthly distribution of NDVI values to detect any trends in the data over the study period. The statistical results of NDVI of Aleppo pine trees indicate that the maximum value is recorded in the month of June, while the lowest values are observed in the month of August where the species studied is exposed to periods of thermal stress.

scholarly journals Revealing the Fingerprint of Climate Change in Interannual NDVI Variability among Biomes in Inner Mongolia, China

2020 ◽  
Vol 12 (8) ◽  
pp. 1332 ◽  
Author(s):  
Linghui Guo ◽  
Liyuan Zuo ◽  
Jiangbo Gao ◽  
Yuan Jiang ◽  
Yongling Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Interannual Variability ◽  
Inner Mongolia ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Time Lag ◽  
Growing Season ◽  
Climate Fluctuations ◽  
Temperature And Precipitation ◽  
Lag Effect

An understanding of the response of interannual vegetation variations to climate change is critical for the future projection of ecosystem processes and developing effective coping strategies. In this study, the spatial pattern of interannual variability in the growing season normalized difference vegetation index (NDVI) for different biomes and its relationships with climate variables were investigated in Inner Mongolia during 1982–2015 by jointly using linear regression, geographical detector, and geographically weighted regression methodologies. The result showed that the greatest variability of the growing season NDVI occurred in typical steppe and desert steppe, with forest and desert most stable. The interannual variability of NDVI differed monthly among biomes, showing a time gradient of the largest variation from northeast to southwest. NDVI interannual variability was significantly related to that of the corresponding temperature and precipitation for each biome, characterized by an obvious spatial heterogeneity and time lag effect marked in the later period of the growing season. Additionally, the large slope of NDVI variation to temperature for desert implied that desert tended to amplify temperature variations, whereas other biomes displayed a capacity to buffer climate fluctuations. These findings highlight the relationships between vegetation variability and climate variability, which could be used to support the adaptive management of vegetation resources in the context of climate change.

Corrigendum to: Influence of climatic factors on variation in the Normalised Difference Vegetation Index in Mongolian Plateau grasslands

2018 ◽  
Vol 40 (2) ◽  
pp. 205
Author(s):  
Xu-Juan Cao ◽  
Qing-Zhu Gao ◽  
Ganjurjav Hasbagan ◽  
Yan Liang ◽  
Wen-Han Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Growing Season ◽  
Limiting Factor ◽  
Spatial And Temporal Variability ◽  
Climate Factors ◽  
Mongolian Plateau ◽  
Normalised Difference Vegetation Index

Climate change will affect how the Normalised Difference Vegetation Index (NDVI), which is correlated with climate factors, varies in space and over time. The Mongolian Plateau is an arid and semi-arid area, 64% covered by grassland, which is extremely sensitive to climate change. Its climate has shown a warming and drying trend at both annual and seasonal scales. We analysed NDVI and climate variation characteristics and the relationships between them for Mongolian Plateau grasslands from 1981 to 2013. The results showed spatial and temporal differences in the variation of NDVI. Precipitation showed the strongest correlation with NDVI (43% of plateau area correlated with total annual precipitation and 44% with total precipitation in the growing season, from May to September), followed by potential evapotranspiration (27% annual, and 30% growing season), temperature (7% annual, 16% growing season) and cloud cover (10% annual, 12% growing season). These findings confirm that moisture is the most important limiting factor for grassland vegetation growth on the Mongolian Plateau. Changes in land use help to explain variations in NDVI in 40% of the plateau, where no correlation with climate factors was found. Our results indicate that vegetation primary productivity will decrease if warming and drying trends continue but decreases will be less substantial if further warming, predicted as highly likely, is not accompanied by further drying, for which predictions are less certain. Continuing spatial and temporal variability can be expected, including as a result of land use changes.

scholarly journals Vegetation greenness response to water availability in northern China from 1982 to 2006

2016 ◽  
Author(s):  
Zhang Fengtai ◽  
An Youzhi
Keyword(s):  
Soil Moisture ◽  
Water Availability ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Growing Season ◽  
Northern China ◽  
Entire Study ◽  
Vegetation Greenness ◽  
Spatio Temporal ◽  
Using Data

Abstract. An evaluation of the relationship between satellite-observed Normalized Difference Vegetation Index (NDVI) data as a proxy for vegetation greenness and water availability (rainfall and soil moisture) can greatly improve our understanding of how vegetation greenness responds to water availability fluctuations. Using Sen and Pearson’s correlation methods, we analyzed the spatio-temporal variation of vegetation greenness for both the entire year and the growing season (GS,4-10) in northern China from 1982 to 2006. Although, vegetation greenness and soil moisture during the study period changed significantly for the entire study area, there was no change in rainfall. Linear correlation analysis between NDVI and rainfall revealed higher correlations using data for all seasons. Higher correlations for NDVI and soil moisture were obtained using growing season data. This study highlights how strongly vegetation greenness responds to water availability dynamics, especially in the growing season period.

scholarly journals Vegetation Change and Its Response to Climate Change between 2000 and 2016 in Marshes of the Songnen Plain, Northeast China

2020 ◽  
Vol 12 (9) ◽  
pp. 3569 ◽  
Author(s):  
Yanji Wang ◽  
Xiangjin Shen ◽  
Ming Jiang ◽  
Xianguo Lu
Keyword(s):  
Climate Change ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Growing Season ◽  
Maximum Temperature ◽  
Climate Data ◽  
Songnen Plain ◽  
Asymmetric Effects ◽  
Climate Change Effects

Songnen Plain is a representative semi-arid marshland in China. The Songnen Plain marshes have undergone obvious loss during the past decades. In order to protect and restore wetland vegetation, it is urgent to investigate the vegetation change and its response to climate change in the Songnen Plain marshes. Based on the normalized difference vegetation index (NDVI) and climate data, we investigated the spatiotemporal change of vegetation and its relationship with temperature and precipitation in the Songnen Plain marshes. During 2000–2016, the growing season mean NDVI of the Songnen Plain marshes significantly (p < 0.01) increased at a rate of 0.06/decade. For the climate change effects on vegetation, the growing season precipitation had a significant positive effect on the growing season NDVI of marshes. In addition, this study first found asymmetric effects of daytime maximum temperature (Tmax) and nighttime minimum temperature (Tmin) on NDVI of the Songnen Plain marshes: The growing season NDVI correlated negatively with Tmax but positively with Tmin. Considering the global asymmetric warming of Tmax and Tmin, more attention should be paid to these asymmetric effects of Tmax and Tmin on the vegetation of marshes.

scholarly journals Driving Forces of the Changes in Vegetation Phenology in the Qinghai–Tibet Plateau

2021 ◽  
Vol 13 (23) ◽  
pp. 4952
Author(s):  
Xigang Liu ◽  
Yaning Chen ◽  
Zhi Li ◽  
Yupeng Li ◽  
Qifei Zhang ◽  
...  
Keyword(s):  
Air Temperature ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Driving Forces ◽  
Growing Season ◽  
Tibet Plateau ◽  
Vegetation Phenology ◽  
Climate Change Research ◽  
Temperature And Precipitation ◽  
Qinghai Tibet Plateau

Phenological change is an emerging hot topic in ecology and climate change research. Existing phenological studies in the Qinghai–Tibet Plateau (QTP) have focused on overall changes, while ignoring the different characteristics of changes in different regions. Here, we use the Global Inventory Modeling and Mapping Studies (GIMMS3g) normalized difference vegetation index (NDVI) dataset as a basis to discuss the temporal and spatial changes in vegetation phenology in the Qinghai–Tibet Plateau from 1982 to 2015. We also analyze the response mechanisms of pre-season climate factor and vegetation phenology and reveal the driving forces of the changes in vegetation phenology. The results show that: (1) the start of the growing season (SOS) and the length of the growing season (LOS) in the QTP fluctuate greatly year by year; (2) in the study area, the change in pre-season precipitation significantly affects the SOS in the northeast (p < 0.05), while, the delay in the end of the growing season (EOS) in the northeast is determined by pre-season air temperature and precipitation; (3) pre-season precipitation in April or May is the main driving force of the SOS of different vegetation, while air temperature and precipitation in the pre-season jointly affect the EOS of different vegetation. The differences in and the diversity of vegetation types together lead to complex changes in vegetation phenology across different regions within the QTP. Therefore, addressing the characteristics and impacts of changes in vegetation phenology across different regions plays an important role in ecological protection in this region.

Feedbacks of Vegetation on Summertime Climate Variability over the North American Grasslands. Part I: Statistical Analysis

2006 ◽  
Vol 10 (17) ◽  
pp. 1-27 ◽  
Author(s):  
Weile Wang ◽  
Bruce T. Anderson ◽  
Nathan Phillips ◽  
Robert K. Kaufmann ◽  
Christopher Potter ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Climate Variability ◽  
Time Scales ◽  
North American ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Spectral Characteristics ◽  
Growing Season ◽  
Statistical Technique ◽  
The North

Abstract Feedbacks of vegetation on summertime climate variability over the North American Grasslands are analyzed using the statistical technique of Granger causality. Results indicate that normalized difference vegetation index (NDVI) anomalies early in the growing season have a statistically measurable effect on precipitation and surface temperature later in summer. In particular, higher means and/or decreasing trends of NDVI anomalies tend to be followed by lower rainfall but higher temperatures during July through September. These results suggest that initially enhanced vegetation may deplete soil moisture faster than normal and thereby induce drier and warmer climate anomalies via the strong soil moisture–precipitation coupling in these regions. Consistent with this soil moisture–precipitation feedback mechanism, interactions between temperature and precipitation anomalies in this region indicate that moister and cooler conditions are also related to increases in precipitation during the preceding months. Because vegetation responds to soil moisture variations, interactions between vegetation and precipitation generate oscillations in NDVI anomalies at growing season time scales, which are identified in the temporal and the spectral characteristics of the precipitation–NDVI system. Spectral analysis of the precipitation–NDVI system also indicates that 1) long-term interactions (i.e., interannual and longer time scales) between the two anomalies tend to enhance one another, 2) short-term interactions (less than 2 months) tend to damp one another, and 3) intermediary-period interactions (4–8 months) are oscillatory. Together, these results support the hypothesis that vegetation may influence summertime climate variability via the land–atmosphere hydrological cycles over these semiarid grasslands.

scholarly journals THE KEY FEATURES OF THE CURRENT CLIMATE CHANGE IN THE REPUBLIC OF BELARUS

2020 ◽  
Vol 3 ◽  
pp. 22-41
Author(s):  
S.A. Lysenko ◽  
◽  
I.V. Buyakov ◽  
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Heat Waves ◽  
Growing Season ◽  
Potential Evaporation ◽  
The South ◽  
The North ◽  
The Republic ◽  
Sum Of Active Temperatures

This paper investigates spatial and temporal features of the climate change in the Republic of Belarus during the period from 1960 to 2019. To accomplish this, we used data on daily average surface air temperature and applied decomposing the time series of these data with singular-spectrum analysis. We analyzed the principal components and long-term average anomalies of average annual, winter and summer air temperatures, the number of frosty days in the cold season and the number of winter days with thaws, the duration and heat supply of the growing season, as well as the frequency and intensity of heat waves. We also estimated the rates of moving the annual sum of active temperatures and the duration of the growing season from the south to the north of Belarus as a result of global warming. The ERA5 reanalysis estimates the spatial and temporal changes in the balance between annual rainfall and potential evaporation from 1980 to 2019. The average annual air temperature in 2000-2019 is shown to be exceeded the long-term average of this value by 1.8° C. The annual sum of active temperatures moves northward at an average speed of 120 km in 10 years with acceleration. Over the past 20 years, the rate of this displacement has doubled in comparison with the period 1980-2000. The length of the growing season moves from the south to the north at a speed of about 110 km per 10 years. It is shown that an increase in potential evaporation due to air warming when slightly changing annual amount of precipitation leads to aridization of the climate of Belarus emitting a reduction in the duration of the cold period with a simultaneous increase in the number of thaws does not contribute to the replenishment of water reserves during snowmelt. Additional damage to forestry and agriculture might be caused by heat waves, the frequency of which for 2000-2019 increased by a factor of 4 compared to the previous 20-year period. Additional damage to forestry and agriculture might be caused by heat waves, which frequency during last 19 years increased by a factor of 4 compared to the previous 20 years.

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