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

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.

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Dynamics of Vegetation Greenness and Its Response to Climate Change in Xinjiang over the Past Two Decades

Remote Sensing ◽

10.3390/rs13204063 ◽

2021 ◽

Vol 13 (20) ◽

pp. 4063

Author(s):

Jie Xue ◽

Yanyu Wang ◽

Hongfen Teng ◽

Nan Wang ◽

Danlu Li ◽

...

Keyword(s):

Climate Change ◽

Vegetation Change ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Dynamic Change ◽

Google Earth ◽

Arid Areas ◽

Climate Data ◽

Northern Margin ◽

The Past

Climate change has proven to have a profound impact on the growth of vegetation from various points of view. Understanding how vegetation changes and its response to climatic shift is of vital importance for describing their mutual relationships and projecting future land–climate interactions. Arid areas are considered to be regions that respond most strongly to climate change. Xinjiang, as a typical dryland in China, has received great attention lately for its unique ecological environment. However, comprehensive studies examining vegetation change and its driving factors across Xinjiang are rare. Here, we used the remote sensing datasets (MOD13A2 and TerraClimate) and data of meteorological stations to investigate the trends in the dynamic change in the Normalized Difference Vegetation Index (NDVI) and its response to climate change from 2000 to 2019 across Xinjiang based on the Google Earth platform. We found that the increment rates of growth-season mean and maximum NDVI were 0.0011 per year and 0.0013 per year, respectively, by averaging all of the pixels from the region. The results also showed that, compared with other land use types, cropland had the fastest greening rate, which was mainly distributed among the northern Tianshan Mountains and Southern Junggar Basin and the northern margin of the Tarim Basin. The vegetation browning areas primarily spread over the Ili River Valley where most grasslands were distributed. Moreover, there was a trend of warming and wetting across Xinjiang over the past 20 years; this was determined by analyzing the climate data. Through correlation analysis, we found that the contribution of precipitation to NDVI (R2 = 0.48) was greater than that of temperature to NDVI (R2 = 0.42) throughout Xinjiang. The Standardized Precipitation and Evapotranspiration Index (SPEI) was also computed to better investigate the correlation between climate change and vegetation growth in arid areas. Our results could improve the local management of dryland ecosystems and provide insights into the complex interaction between vegetation and climate change.

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

Remote Sensing ◽

10.3390/rs12081332 ◽

2020 ◽

Vol 12 (8) ◽

pp. 1332 ◽

Cited By ~ 4

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.

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NDVI-Based Vegetation Change in Inner Mongolia from 1982 to 2006 and Its Relationship to Climate at the Biome Scale

Advances in Meteorology ◽

10.1155/2014/692068 ◽

2014 ◽

Vol 2014 ◽

pp. 1-12 ◽

Cited By ~ 35

Author(s):

Linghui Guo ◽

Shaohong Wu ◽

Dongsheng Zhao ◽

Yunhe Yin ◽

Guoyong Leng ◽

...

Keyword(s):

Climate Change ◽

Land Use ◽

Land Use Change ◽

Inner Mongolia ◽

Vegetation Change ◽

Vegetation Index ◽

Potential Evapotranspiration ◽

Vegetation Type ◽

Growing Season ◽

Desert Steppe

Based on the normalized difference vegetation index (NDVI), we analyzed vegetation change of the six major biomes across Inner Mongolia at the growing season and the monthly timescales and estimated their responses to climate change between 1982 and 2006. To reduce disturbance associated with land use change, those pixels affected by land use change from the 1980s to 2000s were excluded. At the growing season scale, the NDVI increased weakly in the natural ecosystems, but strongly in cropland. Interannual variations in the growing season NDVI for forest was positively linked with potential evapotranspiration and temperature, but negatively correlated with precipitation. In contrast, it was positively correlated with precipitation, but negatively related to potential evapotranspiration for other natural biomes, particularly for desert steppe. Although monthly NDVI trends were characterized as heterogeneous, corresponding to monthly variations in climate change among biome types, warming-related NDVI at the beginning of the growing season was the main contributor to the NDVI increase during the growing season for forest, meadow steppe, and typical steppe, but it constrained the NDVI increase for desert steppe, desert, and crop. Significant one-month lagged correlations between monthly NDVI and climate variables were found, but the correlation characteristics varied greatly depending on vegetation type.

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Hydro-climatic and land use/cover changes in Nasia catchment of the White Volta basin in Ghana

Theoretical and Applied Climatology ◽

10.1007/s00704-021-03772-0 ◽

2021 ◽

Author(s):

Emmanuel Nyadzi ◽

Enoch Bessah ◽

Gordana Kranjac-Berisavljevic ◽

Fulco Ludwig

Keyword(s):

Climate Change ◽

Land Use ◽

Water Resources ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Potential Evapotranspiration ◽

Sunshine Duration ◽

Climatic Variables ◽

Northern Ghana ◽

Maximum Temperature

AbstractThe Nasia catchment is the reservoir with significant surface water resources in Northern Ghana and home to numerous subsistence farmers engaged in rainfed and dry season irrigation farming. Yet, there is little understanding of the hydro-climatic and land use/cover conditions of this basin. This study investigated trends, relationships and changes in hydro-climatic variables and land use/cover in addition to implications of the observable changes in the Nasia catchment over a period of 50 years. Parameters used for the study were minimum (Tmin) and maximum temperature (Tmax), wind speed (WS), sunshine duration (S), rainfall (R), relative humidity (RH), discharge (D) and potential evapotranspiration (PET) data, 15 years of remotely sensed normalized difference vegetation index (NDVI) data and 30 years of land use/cover image data. Results show that Tmin, Tmax, WS and PET have increased significantly (p < 0.05) over time. RH and S significantly declined. R, D and NDVI have not decreased significantly (p > 0.05). A significant abrupt change in almost all hydro-climatic variables started in the 1980s, a period that coincides with the occurrence of drought events in the region, except WS in 2001, R in 1968 and D in 1975, respectively. Also, D showed a positive significant correlation with RH, R and PET, but an insignificant positive relationship with S. D also showed a negative insignificant correlation with Tmin, Tmax and WS. Areas covered with shrubland and settlement/bare lands have increased to the disadvantage of cropland, forest, grassland and water bodies. It was concluded that climate change impact is quite noticeable in the basin, indicating water scarcity and possibilities of droughts. The analysis performed herein is a vital foundation for further studies to simulate and predict the effect of climate change on the water resources, agriculture and livelihoods in the Nasia catchment.

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Vegetation Dynamic Changes and Their Response to Ecological Engineering in the Sanjiangyuan Region of China

Remote Sensing ◽

10.3390/rs12244035 ◽

2020 ◽

Vol 12 (24) ◽

pp. 4035

Author(s):

Xiaohui Zhai ◽

Xiaolei Liang ◽

Changzhen Yan ◽

Xuegang Xing ◽

Haowei Jia ◽

...

Keyword(s):

Climate Change ◽

Vegetation Change ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Positive Impact ◽

Ecological Engineering ◽

Scientific Basis ◽

Vegetation Dynamic ◽

Vegetation Growth ◽

The Impact

In recent decades, the vegetation of the Sanjiangyuan region has undergone a series of changes under the influence of climate change, and ecological restoration projects have been implemented. In this paper, we analyze the spatiotemporal dynamics of vegetation in this region using the satellite-retrieved normalized difference vegetation index (NDVI) from the global inventory modeling and mapping studies (GIMMS) and moderate resolution imaging and spectroradiometer (MODIS) datasets during the past 34 years. Specifically, the characteristics of vegetation changes were analyzed according to the stage of implementation of different ecological engineering programs. The results are as follows. (1) The vegetation in 65.6% of the study area exhibited an upward trend, and in 53.0% of the area, it displayed a large increase, which was mainly distributed in the eastern part of the study area. (2) The vegetation NDVI increased to differing degrees during stages of ecological engineering. (3) The NDVI in the western part of the Sanjiangyuan region is mainly affected by temperature, while in the northeastern part, the NDVI is affected more by precipitation. In the southern part, however, vegetation growth is affected neither by temperature nor by precipitation. On the whole region, vegetation growing is more affected by temperature than by precipitation. (4) The impacts of human activities on vegetation change are both positive and negative. In recent years, ecological engineering projects have had a positive impact on vegetation growth. This study can help us to correctly understand the impact of climate change on vegetation growth, so as to provide a scientific basis for the evaluation of regional ecological engineering effectiveness and the formulation of ecological protection policies.

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Exploring Climate Change Effects on Vegetation Phenology by MOD13Q1 Data: The Piemonte Region Case Study in the Period 2001–2019

Agronomy ◽

10.3390/agronomy11030555 ◽

2021 ◽

Vol 11 (3) ◽

pp. 555

Author(s):

Filippo Sarvia ◽

Samuele De Petris ◽

Enrico Borgogno-Mondino

Keyword(s):

Climate Change ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Arable Land ◽

Observation Data ◽

Climate Change Effects ◽

Earth Observation Data ◽

Nw Italy ◽

Terra Modis ◽

Phenological Metrics

Rising temperature, rainfall, and wind regime changes, increasing of frequency and intensity of extreme events are only some of the effects of climate change affecting the agro-forestry sector. Earth Observation data from satellite missions (often available for free) can certainly support analysis of climate change effects on vegetation, making possible to improve land management in space and time. Within this context, the present work aims at investigating natural and agricultural vegetation, as mapped by Corine Land Cover (CLC) dataset, focusing on phenological metrics trends that can be possibly conditioned by the ongoing climate-change. The study area consists of the entire Piemonte region (NW-Italy). MOD13Q1-v6 dataset from TERRA MODIS mission was used to describe pluri-annual (2001–2019) phenological behavior of vegetation focusing on the following CLC classes: Non-irrigated arable land, Vineyards, Pastures, and Forests. After computing and mapping some phenological metrics as derivable from the interpretation of at-pixel level NDVI (Normalized Difference Vegetation Index) temporal profile, we found that the most significant one was the maximum annual NDVI (MaxNDVI). Consequently, its trend was analyzed at CLC class level for the whole Piemonte region. Natural and semi-natural vegetation classes (Pastures and Forests) were furtherly investigated testing significance of the Percent Total Variation (TV %) of MaxNDVI in the period 2001–2019 for different altitude classes. Results proved that Non-irrigated arable land showed a not significant trend of MaxNDVI; differently, vineyards and forests showed a significant increasing one. Concerning TV %, it was found that it increases with altitude for the Forests CLC class, while it decreases with altitude for the pastures class.

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Quantitative Assessment of the Contributions of Climate Change and Human Activities to Vegetation Variation in the Qinling Mountains

Frontiers in Earth Science ◽

10.3389/feart.2021.782287 ◽

2021 ◽

Vol 9 ◽

Author(s):

Dandong Cheng ◽

Guizeng Qi ◽

Jinxi Song ◽

Yixuan Zhang ◽

Hongying Bai ◽

...

Keyword(s):

Climate Change ◽

Human Activities ◽

Quantitative Assessment ◽

Vegetation Change ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Qinling Mountains ◽

Protection Measures ◽

Vegetation Degradation ◽

Driving Mechanisms

Quantitative assessment of the contributions of climate change and human activities to vegetation change is important for ecosystem planning and management. To reveal spatial differences in the driving mechanisms of vegetation change in the Qinling Mountains, the changing patterns of the normalized difference vegetation index (NDVI) in the Qinling Mountains during 2000–2019 were investigated through trend analysis and multiple regression residuals analysis. The relative contributions of climate change and human activities on vegetation NDVI change were also quantified. The NDVI shows a significant increasing trend (0.23/10a) from 2000 to 2019 in the Qinling Mountains. The percentage of areas with increasing and decreasing trends in NDVI is 87.96% and 12.04% of the study area, respectively. The vegetation change in the Qinling Mountains is caused by a combination of climate change and human activities. The Tongguan Shiquan line is a clear dividing line in the spatial distribution of drivers of vegetation change. Regarding the vegetation improvement, the contribution of climate change and human activities to NDVI increase is 51.75% and 48.25%, respectively. In the degraded vegetation area, the contributions of climate change and human activities to the decrease in NDVI were 22.11% and 77.89%, respectively. Thus, vegetation degradation is mainly caused by human activities. The implementation of policies, such as returning farmland to forest and grass, has an important role in vegetation protection. It is suggested that further attention should be paid to the role of human activities in vegetation degradation when formulating corresponding vegetation protection measures and policies.

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

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi7080290 ◽

2018 ◽

Vol 7 (8) ◽

pp. 290 ◽

Cited By ~ 3

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.

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Growing Season Vegetation Dynamics Based on NDVI and the Driving Forces in Nepal during 1982-2015

Forestry: Journal of Institute of Forestry, Nepal ◽

10.3126/forestry.v17i0.33619 ◽

2020 ◽

Vol 17 ◽

pp. 1-22

Author(s):

Binod Baniya ◽

Qiuhong Tang ◽

Madan Koirala ◽

Kedar Rijal ◽

Giri Kattel

Keyword(s):

Vegetation Dynamics ◽

Vegetation Change ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Driving Forces ◽

Pearson Correlation ◽

Growing Season ◽

Kendall Test ◽

Warming Trend ◽

Shuttle Radar Topography Mission

Monitoring and attributing growing season vegetation dynamics have become crucial for maintaining the structure and function of the ecosystem. The objective of this research was to examine the spatial and temporal vegetation changes and explore their driving forces during growing season in Nepal. It also explored the variation of Normalized Difference Vegetation Index (NDVI) in different altitudes at each 100m interval. The National Oceanic and Atmospheric Administration (NOAA) NDVI, monthly temperature, precipitation and Shuttle Radar Topography Mission (SRTM) 90m Digital Elevation Model (DEM) were used. The linear regression model, Sen’s slope, Mann Kendall test and Pearson correlation between NDVI and climate, i.e., temperature and precipitation were computed. The driving forces were identified based on threshold segmentation method. Our results showed positive intensity of vegetation change. The NDVI has significantly increased at the rate of 0.001yr-1, 0.0005yr-1 and 0.002yr-1 in growing season, spring and autumn but it has insignificantly increased at the rate of 0.0003yr-1 in summer. In the meantime, growing season temperature has significantly increased with an average warming trend of 0.03°Cyr-1 but precipitation decreased at the rate of 2.76 mm yr-1 during 1982-2015. The NDVI increased in 84.20% (53.08% significant) of the area. The correlation between NDVI and temperature was found positive whereas correlation with precipitation was negative. Spatially, 84.05% of the study area found positive correlation between NDVI and temperature with 25.72% significance (p<0.05) which was very less with precipitation. Our results demonstrate that NDVI was strongly correlated with temperature compared with precipitation. Beyond the climate, NDVI changes were also attributed to multi-control environments and ecological restoration in Nepal.

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Impact of Climate Change on Temperate and Alpine Grasslands in China during 1982–2006

Advances in Meteorology ◽

10.1155/2015/180614 ◽

2015 ◽

Vol 2015 ◽

pp. 1-10 ◽

Cited By ~ 7

Author(s):

Xiangjin Shen ◽

Binhui Liu ◽

Guangdi Li ◽

Daowei Zhou

Keyword(s):

Climate Change ◽

Growing Season ◽

Maximum Temperature ◽

Climate Data ◽

Night Time ◽

Temperate Grasslands ◽

Grassland Vegetation ◽

Impact Of Climate Change ◽

Alpine Steppe ◽

The Impact

Based on GIMMS NDVI and climate data from 1982 to 2006, this study analyzed the impact of climate change on grassland in China. During the growing season, there were significant effects of precipitation on the growth of all the grassland types (P<0.05), except for meadow vegetation. For the air temperatures, there existed asymmetrical effects of maximum temperature (Tmax) and minimum temperature (Tmin) on grassland vegetation, especially for the temperate grasslands and alpine steppe. The growing season NDVI correlated negatively withTmaxbut positively withTminfor temperate grasslands. Seasonally, these opposite effects were only observed in summer. For alpine steppe, the growing season NDVI correlated positively withTmaxbut negatively withTmin, and this pattern of asymmetrical responses was only obvious in spring and autumn. Under the background of global asymmetric warming, more attention should be paid to this asymmetric response of grassland vegetation to daytime and night-time warming, especially when we want to predict the productivity of China’s grasslands in the future.

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