Inconsistency of Global Vegetation Dynamics Driven by Climate Change: Evidences from Spatial Regression

Global greening over the past 30 years since 1980s has been confirmed by numerous studies. However, a single-dimensional indicator and non-spatial modelling approaches might exacerbate uncertainties in our understanding of global change. Thus, comprehensive monitoring for vegetation’s various properties and spatially explicit models are required. In this study, we used the newest enhanced vegetation index (EVI) products of Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 to detect the inconsistency trend of annual peak and average global vegetation growth using the Mann–Kendall test method. We explored the climatic factors that affect vegetation growth change from 2001 to 2018 using the spatial lag model (SLM), spatial error model (SEM) and geographically weighted regression model (GWR). The results showed that EVImax and EVImean in global vegetated areas consistently showed linear increasing trends during 2001–2018, with the global averaged trend of 0.0022 yr−1 (p < 0.05) and 0.0030 yr−1 (p < 0.05). Greening mainly occurred in the croplands and forests of China, India, North America and Europe, while browning was almost in the grasslands of Brazil and Africa (18.16% vs. 3.08% and 40.73% vs. 2.45%). In addition, 32.47% of the global vegetated area experienced inconsistent trends in EVImax and EVImean. Overall, precipitation and mean temperature had positive impacts on vegetation variation, while potential evapotranspiration and vapour pressure had negative impacts. The GWR revealed that the responses of EVI to climate change were inconsistent in an arid or humid area, in cropland or grassland. Climate change could affect vegetation characteristics by changing plant phenology, consequently rendering the inconsistency between peak and mean greening. In addition, anthropogenic activities, including land cover change and land use management, also could lead to the differences between annual peak and mean vegetation variations.

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Climate-forced changes of bio-productivity of Belorussian terrestrial ecosystems

Исследования Земли из космоса ◽

10.31857/s0205-96142019677-88 ◽

2019 ◽

pp. 77-88

Author(s):

S. A. Lysenko

Keyword(s):

Climate Change ◽

Carbon Dioxide ◽

Vegetation Index ◽

Precipitation Amount ◽

Terrestrial Ecosystems ◽

Vegetation Period ◽

Climatic Trend ◽

Vegetation Growth ◽

Current Century ◽

The Impact

The spatial and temporal particularities of Normalized Differential Vegetation Index (NDVI) changes over territory of Belarus in the current century and their relationship with climate change were investigated. The rise of NDVI is observed at approximately 84% of the Belarus area. The statistically significant growth of NDVI has exhibited at nearly 35% of the studied area (t-test at 95% confidence interval), which are mainly forests and undeveloped areas. Croplands vegetation index is largely descending. The main factor of croplands bio-productivity interannual variability is precipitation amount in vegetation period. This factor determines more than 60% of the croplands NDVI dispersion. The long-term changes of NDVI could be explained by combination of two factors: photosynthesis intensifying action of carbon dioxide and vegetation growth suppressing action of air warming with almost unchanged precipitation amount. If the observed climatic trend continues the croplands bio-productivity in many Belarus regions could be decreased at more than 20% in comparison with 2000 year. The impact of climate change on the bio-productivity of undeveloped lands is only slightly noticed on the background of its growth in conditions of rising level of carbon dioxide in the atmosphere.

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Contributions of Vegetation Greening and Climate Change to Evapotranspiration Trend after Large-Scale Vegetation Restoration on the Loess Plateau, China

Water ◽

10.3390/w13131755 ◽

2021 ◽

Vol 13 (13) ◽

pp. 1755

Author(s):

Shuo Wang ◽

Chenfeng Cui ◽

Qin Dai

Keyword(s):

Climate Change ◽

Loess Plateau ◽

Large Scale ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Potential Evapotranspiration ◽

Development Trend ◽

Future Trend ◽

Natural Ecosystem ◽

The Loess Plateau

Since the early 2000s, the vegetation cover of the Loess Plateau (LP) has increased significantly, which has been fully recorded. However, the effects on relevant eco-hydrological processes are still unclear. Here, we made an investigation on the changes of actual evapotranspiration (ETa) during 2000–2018 and connected them with vegetation greening and climate change in the LP, based on the remote sensing data with correlation and attribution analysis. Results identified that the average annual ETa on the LP exhibited an obvious increasing trend with the value of 9.11 mm yr−1, and the annual ETa trend was dominated by the changes of ETa in the third quarter (July, August, and September). The future trend of ETa was predicted by the Hurst exponent. Partial correlation analysis indicated that annual ETa variations in 87.8% regions of the LP were controlled by vegetation greening. Multiple regression analysis suggested that the relative contributions of potential evapotranspiration (ETp), precipitation, and normalized difference vegetation index (NDVI), to the trend of ETa were 5.7%, −26.3%, and 61.4%, separately. Vegetation greening has a close relationship with the Grain for Green (GFG) project and acts as an essential driver for the long-term development trend of water consumption on the LP. In this research, the potential conflicts of water demanding between the natural ecosystem and social-economic system in the LP were highlighted, which were caused by the fast vegetation expansion.

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Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

Forest Ecosystems ◽

10.1186/s40663-021-00309-9 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Peixin Ren ◽

Zelin Liu ◽

Xiaolu Zhou ◽

Changhui Peng ◽

Jingfeng Xiao ◽

...

Keyword(s):

Climate Change ◽

Minimum Temperature ◽

Vegetation Index ◽

Climatic Factors ◽

Time Lag ◽

Evergreen Forest ◽

Maximum Temperature ◽

Daily Minimum Temperature ◽

Study Region ◽

Cumulative Precipitation

Abstract Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

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Climate Change Patterns of Wild Blueberry Fields in Downeast, Maine over the Past 40 Years

Water ◽

10.3390/w13050594 ◽

2021 ◽

Vol 13 (5) ◽

pp. 594

Author(s):

Rafa Tasnim ◽

Francis Drummond ◽

Yong-Jiang Zhang

Keyword(s):

Climate Change ◽

Vegetation Index ◽

Potential Evapotranspiration ◽

Growing Season ◽

Spatial Average ◽

Climate Variables ◽

Threshold Values ◽

The Past ◽

Wild Blueberry ◽

Crop Health

Maine, USA is the largest producer of wild blueberries (Vaccinium angustifolium Aiton), an important native North American fruit crop. Blueberry fields are mainly distributed in coastal glacial outwash plains which might not experience the same climate change patterns as the whole region. It is important to analyze the climate change patterns of wild blueberry fields and determine how they affect crop health so fields can be managed more efficiently under climate change. Trends in the maximum (Tmax), minimum (Tmin) and average (Tavg) temperatures, total precipitation (Ptotal), and potential evapotranspiration (PET) were evaluated for 26 wild blueberry fields in Downeast Maine during the growing season (May–September) over the past 40 years. The effects of these climate variables on the Maximum Enhanced Vegetation Index (EVImax) were evaluated using Remote Sensing products and Geographic Information System (GIS) tools. We found differences in the increase in growing season Tmax, Tmin, Tavg, and Ptotal between those fields and the overall spatial average for the region (state of Maine), as well as among the blueberry fields. The maximum, minimum, and average temperatures of the studied 26 wild blueberry fields in Downeast, Maine showed higher rates of increase than those of the entire region during the last 40 years. Fields closer to the coast showed higher rates of warming compared with the fields more distant from the coast. Consequently, PET has been also increasing in wild blueberry fields, with those at higher elevations showing lower increasing rates. Optimum climatic conditions (threshold values) during the growing season were explored based on observed significant quadratic relationships between the climate variables (Tmax and Ptotal), PET, and EVImax for those fields. An optimum Tmax and PET for EVImax at 22.4 °C and 145 mm/month suggest potential negative effects of further warming and increasing PET on crop health and productivity. These climate change patterns and associated physiological relationships, as well as threshold values, could provide important information for the planning and development of optimal management techniques for wild blueberry fields experiencing climate change.

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Assessing the impact of seasonal precipitation and temperature on vegetation in a grass-dominated rangeland

The Rangeland Journal ◽

10.1071/rj13098 ◽

2014 ◽

Vol 36 (2) ◽

pp. 185 ◽

Cited By ~ 11

Author(s):

Fang Chen ◽

Keith T. Weber

Keyword(s):

Vegetation Index ◽

Climatic Factors ◽

Growing Season ◽

Vegetation Growth ◽

Factors Affecting ◽

Growing Seasons ◽

Normalised Difference Vegetation Index ◽

Moderate Resolution Imaging Spectroradiometer ◽

The Impact ◽

Precipitation And Temperature

Changes in vegetation are affected by many climatic factors and have been successfully monitored through satellite remote sensing over the past 20 years. In this study, the Normalised Difference Vegetation Index (NDVI), derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite, was selected as an indicator of change in vegetation. Monthly MODIS composite NDVI at a 1-km resolution was acquired throughout the 2004–09 growing seasons (i.e. April–September). Data describing daily precipitation and temperature, primary factors affecting vegetation growth in the semiarid rangelands of Idaho, were derived from the Surface Observation Gridding System and local weather station datasets. Inter-annual and seasonal fluctuations of precipitation and temperature were analysed and temporal relationships between monthly NDVI, precipitation and temperature were examined. Results indicated NDVI values observed in June and July were strongly correlated with accumulated precipitation (R2 >0.75), while NDVI values observed early in the growing season (May) as well as late in the growing season (August and September) were only moderately related with accumulated precipitation (R2 ≥0.45). The role of ambient temperature was also apparent, especially early in the growing season. Specifically, early growing-season temperatures appeared to significantly affect plant phenology and, consequently, correlations between NDVI and accumulated precipitation. It is concluded that precipitation during the growing season is a better predictor of NDVI than temperature but is interrelated with influences of temperature in parts of the growing season.

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Evaluation of a Global Vegetation Model using time series of satellite vegetation indices

Geoscientific Model Development ◽

10.5194/gmd-4-1103-2011 ◽

2011 ◽

Vol 4 (4) ◽

pp. 1103-1114 ◽

Cited By ~ 36

Author(s):

F. Maignan ◽

F.-M. Bréon ◽

F. Chevallier ◽

N. Viovy ◽

P. Ciais ◽

...

Keyword(s):

Climate Change ◽

Time Series ◽

Vegetation Index ◽

Vegetation Indices ◽

Global Scale ◽

Vegetation Dynamic ◽

Rate Of Increase ◽

Vegetation Models ◽

Global Vegetation ◽

The Impact

Abstract. Atmospheric CO2 drives most of the greenhouse effect increase. One major uncertainty on the future rate of increase of CO2 in the atmosphere is the impact of the anticipated climate change on the vegetation. Dynamic Global Vegetation Models (DGVM) are used to address this question. ORCHIDEE is such a DGVM that has proven useful for climate change studies. However, there is no objective and methodological way to accurately assess each new available version on the global scale. In this paper, we submit a methodological evaluation of ORCHIDEE by correlating satellite-derived Vegetation Index time series against those of the modeled Fraction of absorbed Photosynthetically Active Radiation (FPAR). A perfect correlation between the two is not expected, however an improvement of the model should lead to an increase of the overall performance. We detail two case studies in which model improvements are demonstrated, using our methodology. In the first one, a new phenology version in ORCHIDEE is shown to bring a significant impact on the simulated annual cycles, in particular for C3 Grasses and C3 Crops. In the second case study, we compare the simulations when using two different weather fields to drive ORCHIDEE. The ERA-Interim forcing leads to a better description of the FPAR interannual anomalies than the simulation forced by a mixed CRU-NCEP dataset. This work shows that long time series of satellite observations, despite their uncertainties, can identify weaknesses in global vegetation models, a necessary first step to improving them.

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

The Rangeland Journal ◽

10.1071/rj16073_co ◽

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.

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Increased atmospheric vapor pressure deficit reduces global vegetation growth

Science Advances ◽

10.1126/sciadv.aax1396 ◽

2019 ◽

Vol 5 (8) ◽

pp. eaax1396 ◽

Cited By ~ 69

Author(s):

Wenping Yuan ◽

Yi Zheng ◽

Shilong Piao ◽

Philippe Ciais ◽

Danica Lombardozzi ◽

...

Keyword(s):

Vapor Pressure ◽

Vapor Pressure Deficit ◽

Vegetation Index ◽

Global Climate ◽

Gross Primary Production ◽

Ecosystem Responses ◽

Climate Conditions ◽

Vegetation Growth ◽

Current Century ◽

Global Vegetation

Atmospheric vapor pressure deficit (VPD) is a critical variable in determining plant photosynthesis. Synthesis of four global climate datasets reveals a sharp increase of VPD after the late 1990s. In response, the vegetation greening trend indicated by a satellite-derived vegetation index (GIMMS3g), which was evident before the late 1990s, was subsequently stalled or reversed. Terrestrial gross primary production derived from two satellite-based models (revised EC-LUE and MODIS) exhibits persistent and widespread decreases after the late 1990s due to increased VPD, which offset the positive CO2 fertilization effect. Six Earth system models have consistently projected continuous increases of VPD throughout the current century. Our results highlight that the impacts of VPD on vegetation growth should be adequately considered to assess ecosystem responses to future climate conditions.

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Copula-Based Abrupt Variations Detection in the Relationship of Seasonal Vegetation-Climate in the Jing River Basin, China

Remote Sensing ◽

10.3390/rs11131628 ◽

2019 ◽

Vol 11 (13) ◽

pp. 1628 ◽

Cited By ~ 17

Author(s):

Jing Zhao ◽

Shengzhi Huang ◽

Qiang Huang ◽

Hao Wang ◽

Guoyong Leng ◽

...

Keyword(s):

River Basin ◽

Human Activities ◽

Urban Areas ◽

Large Scale ◽

Vegetation Index ◽

Climatic Factors ◽

Potential Evapotranspiration ◽

Change Points ◽

Vegetation Coverage ◽

The Relationship

Understanding the changing relationships between vegetation coverage and precipitation/temperature (P/T) and then exploring their potential drivers are highly necessary for ecosystem management under the backdrop of a changing environment. The Jing River Basin (JRB), a typical eco-environmentally vulnerable region of the Loess Plateau, was chosen to identify abrupt variations of the relationships between seasonal Normalized Difference Vegetation Index (NDVI) and P/T through a copula-based method. By considering the climatic/large-scale atmospheric circulation patterns and human activities, the potential causes of the non-stationarity of the relationship between NDVI and P/T were revealed. Results indicated that (1) the copula-based framework introduced in this study is more reasonable and reliable than the traditional double-mass curves method in detecting change points of vegetation and climate relationships; (2) generally, no significant change points were identified during 1982–2010 at the 95% confidence level, implying the overall stationary relationship still exists, while the relationships between spring NDVI and P/T, autumn NDVI and P have slightly changed; (3) teleconnection factors (including Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), Niño 3.4, and sunspots) have a more significant influence on the relationship between seasonal NDVI and P/T than local climatic factors (including potential evapotranspiration and soil moisture); (4) negative human activities (expansion of farmland and urban areas) and positive human activities (“Grain For Green” program) were also potential factors affecting the relationship between NDVI and P/T. This study provides a new and reliable insight into detecting the non-stationarity of the relationship between NDVI and P/T, which will be beneficial for further revealing the connection between the atmosphere and ecosystems.

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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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