Cumulative Effects of Climatic Factors on Terrestrial Vegetation Growth

The chapter analyzes terrestrial vegetation trends and correlation of vegetation indices with climatic factors like LST, Net Radiation, and TRMM. The result shows the positive vegetation trend might be due to the increased vegetation growth and productivity. Negative vegetation trend might be due to changes in a crop choice. Correlation of vegetation indices with climatic factors like LST showed weak to moderate positive correlation. Net radiation showed moderate negative correlation and TRMM showed a weak negative or positive correlation for both the Kharif and Rabi seasons.

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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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NDVI indicated inter-seasonal non-uniform time-lag responses of terrestrial vegetation growth to daily maximum and minimum temperature

Global and Planetary Change ◽

10.1016/j.gloplacha.2019.03.010 ◽

2019 ◽

Vol 177 ◽

pp. 27-38 ◽

Cited By ~ 12

Author(s):

Youyue Wen ◽

Xiaoping Liu ◽

Jian Yang ◽

Kui Lin ◽

Guoming Du

Keyword(s):

Minimum Temperature ◽

Time Lag ◽

Daily Maximum ◽

Terrestrial Vegetation ◽

Vegetation Growth

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Nonuniform Time-Lag Effects of Asymmetric Warming on Net Primary Productivity across Global Terrestrial Biomes

Earth Interactions ◽

10.1175/ei-d-17-0032.1 ◽

2018 ◽

Vol 22 (8) ◽

pp. 1-26 ◽

Cited By ~ 6

Author(s):

Youyue Wen ◽

Xiaoping Liu ◽

Guoming Du

Keyword(s):

Partial Correlation ◽

Net Primary Productivity ◽

Net Primary Production ◽

Time Lag ◽

Correlation Coefficients ◽

Terrestrial Ecosystem ◽

Terrestrial Vegetation ◽

Vegetation Growth ◽

Lag Effects ◽

Terrestrial Biomes

Abstract Climate warming exhibits asymmetric patterns over a diel time, with the trend of nighttime warming exceeding that of daytime warming, a phenomenon commonly known as asymmetric warming. Recently, increasing studies have documented the significant instantaneous impacts of asymmetric warming on terrestrial vegetation growth, but the indirect effects of asymmetric warming carrying over vegetation growth (referred to here as time-lag effects) remain unknown. Here, we quantitatively studied the time-lag effects (within 1 year) of asymmetric warming on global plant biomes by using terrestrial vegetation net primary production (NPP) derived by the Carnegie–Ames–Stanford Approach (CASA) model and accumulated daytime and nighttime temperature (ATmax and ATmin) from 1982 to 2013. Partial correlation and time-lag analyses were conducted at a monthly scale to obtain the partial correlation coefficients between NPP and ATmax/ATmin and the lagged durations of NPP responses to ATmax/ATmin. The results showed that (i) asymmetric warming has nonuniform time-lag effects on single plant biomes, and distinguishing correlations exist in different vegetation biomes’ associations to asymmetric warming; (ii) terrestrial biomes respond to ATmax (4.63 ± 3.92 months) with a shorter protracted duration than to ATmin (6.06 ± 4.27 months); (iii) forest biomes exhibit longer prolonged duration in responding to asymmetric warming than nonforest biomes do; (iv) mosses and lichens (Mosses), evergreen needleleaf forests (ENF), deciduous needleleaf forests (DNF), and mixed forests (MF) tend to positively correlate with ATmax, whereas the other biomes associate with ATmax with near-equal splits of positive and negative correlation; and (v) ATmin has a predominantly positive influence on terrestrial biomes, except for Mosses and DNF. This study provides a new perspective on terrestrial ecosystem responses to asymmetric warming and highlights the importance of including such nonuniform time-lag effects into currently used terrestrial ecosystem models during future investigations of vegetation–climate interactions.

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

Remote Sensing ◽

10.3390/rs13173442 ◽

2021 ◽

Vol 13 (17) ◽

pp. 3442

Author(s):

Dou Zhang ◽

Xiaolei Geng ◽

Wanxu Chen ◽

Lei Fang ◽

Rui Yao ◽

...

Keyword(s):

Climate Change ◽

Vegetation Index ◽

Climatic Factors ◽

Potential Evapotranspiration ◽

Anthropogenic Activities ◽

Test Method ◽

Spatial Error ◽

Vegetation Growth ◽

Annual Peak ◽

Global Vegetation

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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Drivers and Environmental Impacts of Vegetation Greening in a Semi-Arid Region of Northwest China since 2000

Remote Sensing ◽

10.3390/rs13214246 ◽

2021 ◽

Vol 13 (21) ◽

pp. 4246

Author(s):

Zhenzong Wu ◽

Jian Bi ◽

Yifei Gao

Keyword(s):

Arid Region ◽

Vegetation Index ◽

Climatic Factors ◽

Agricultural Practices ◽

Northwest China ◽

Terrestrial Vegetation ◽

Moderate Resolution Imaging Spectroradiometer ◽

Semi Arid Region ◽

Semi Arid ◽

Dynamics Of Vegetation

The dynamics of terrestrial vegetation have changed a lot due to climate change and direct human interference. Monitoring these changes and understanding the mechanisms driving them are important for better understanding and projecting the Earth system. Here, we assessed the dynamics of vegetation in a semi-arid region of Northwest China for the years from 2000 to 2019 through satellite remote sensing using Vegetation Index (VI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS), and analyzed the interannual covariation between vegetation and three climatic factors—air temperature, precipitation, and vapor pressure deficit (VPD)—at nine meteorological stations. The main findings of this research are: (1) herbaceous land greened up much more than forests (2.85%/year vs. 1.26%/year) in this semi-arid region; (2) the magnitudes of green-up for croplands and grasslands were very similar, suggesting that agricultural practices, such as fertilization and irrigation, might have contributed little to vegetation green-up in this semi-arid region; and (3) the interannual dynamics of vegetation at high altitudes in this region correlate little with temperature, precipitation, or VPD, suggesting that factors other than temperature and moisture control the interannual vegetation dynamics there.

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Periodic Relations between Terrestrial Vegetation and Climate Factors across the Globe

Remote Sensing ◽

10.3390/rs12111805 ◽

2020 ◽

Vol 12 (11) ◽

pp. 1805

Author(s):

Boyi Liang ◽

Hongyan Liu ◽

Xiaoqiu Chen ◽

Xinrong Zhu ◽

Elizabeth L. Cressey ◽

...

Keyword(s):

Time Lag ◽

Climate Factors ◽

Vegetation Types ◽

Terrestrial Vegetation ◽

Area Index ◽

Vegetation Growth ◽

Annual Cycles ◽

Vegetation Models ◽

Global Vegetation ◽

The Impact

In this paper, cross-spectrum analysis was used to verify the agreement of periodicity between the global LAI (leaf area index) and climate factors. The results demonstrated that the LAI of deciduous forests and permanent wetlands have high agreement with temperature, rainfall and radiation over annual cycles. A low agreement between the LAI and seasonal climate variables was observed for some of the temperate and tropical vegetation types including shrublands and evergreen broadleaf forests, possibly due to the diversity of vegetation and human activities. Across all vegetation types, the LAI demonstrated a large time lag following variation in radiation (>1 month), whereas relatively short lag periods were observed between the LAI and annual temperature (around 2 weeks)/rainfall patterns (less than 10 days), suggesting that the impact of radiation on global vegetation growth is relatively slow, which is in accord with the results of previous studies. This work can provide a benchmark of the phenological drivers in global vegetation, from the perspective of periodicity, as well as helping to parameterize and refine the DGVMs (Dynamic Global Vegetation Models) for different vegetation types.

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Interactive Effects of Climatic Factors on Seasonal Vegetation Dynamics in the Central Loess Plateau, China

Forests ◽

10.3390/f10121071 ◽

2019 ◽

Vol 10 (12) ◽

pp. 1071 ◽

Cited By ~ 1

Author(s):

Xian Zhu ◽

Hong S. He ◽

Shuoxin Zhang ◽

William D. Dijak ◽

Yuanyuan Fu

Keyword(s):

Loess Plateau ◽

Vegetation Dynamics ◽

Positive Relationship ◽

Climatic Factors ◽

Variable Temperature ◽

Interactive Effects ◽

Moderator Variable ◽

Vegetation Growth ◽

The Impact ◽

Hurst Exponents

The interactive effects of climatic factors (precipitation and temperature) on vegetation growth can be characterized by their effect on vegetation seasonal dynamics. The interactive effects, seasonal trend of vegetation growth, and its future consistency (potential for future trend) have not been adequately studied in the literature. In this work, using the Enhanced Vegetation Index (EVI) and gridded climate data at a resolution of 250 m in the central Loess Plateau region, we examined seasonal vegetation dynamics with climate changes and the interactive effects of climatic factors on vegetation growth at the pixel and regional scales from the period 2000 to 2015. Vegetation cover in the Central Loess Plateau in China has dramatically changed due to the Grain-for-Green (GFG) ecological restoration program, which was designed to convert cropland to forestland or grassland since 1999. Our results show that the EVI increased significantly during the 16 year period and is likely to continue to increase in the near future. Relatively small Hurst exponents for forestland suggests that the potential for a future increased trend will be weak for the forest. Large Hurst exponents for grassland indicate its strong potential of further increase. Significant increases in spring precipitation have promoted vegetation growth, while significant decreases in summer temperature have had negative effects on vegetation growth. For temperatures between 10 to 20 °C, the impact of temperature on vegetation growth has a clear positive relationship with the moderator variable precipitation. For precipitation < 200 mm in the growing season, the impact of precipitation on vegetation growth has a clearly positive relationship with the moderator variable temperature. Results of this study will provide useful and important guidelines for designing forestland and grassland restoration plans in arid, semiarid and sub-humid regions.

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Changes in Vegetation Growth Dynamics and Relations with Climate in Inner Mongolia under More Strict Multiple Pre-Processing (2000–2018)

Sustainability ◽

10.3390/su12062534 ◽

2020 ◽

Vol 12 (6) ◽

pp. 2534 ◽

Cited By ~ 2

Author(s):

Dong He ◽

Xianglin Huang ◽

Qingjiu Tian ◽

Zhichao Zhang

Keyword(s):

Air Temperature ◽

Inner Mongolia ◽

Climatic Factors ◽

Vegetation Type ◽

Response Speed ◽

Dominant Factor ◽

Climate Factors ◽

Climate Type ◽

Local Climate ◽

Vegetation Growth

Inner Mongolia Autonomous Region (IMAR) is related to China’s ecological security and the improvement of ecological environment; thus, the vegetation’s response to climate changes in IMAR has become an important part of current global change research. As existing achievements have certain deficiencies in data preprocessing, technical methods and research scales, we correct the incomplete data pre-processing and low verification accuracy; use grey relational analysis (GRA) to study the response of Enhanced Vegetation Index (EVI) in the growing season to climate factors on the pixel scale; explore the factors that affect the response speed and response degree from multiple perspectives, including vegetation type, longitude, latitude, elevation and local climate type; and solve the problems of excessive ignorance of details and severe distortion of response results due to using average values of the wide area or statistical data. The results show the following. 1. The vegetation status of IMAR in 2000-2018 was mainly improved. The change rates were 0.23/10° N and 0.25/10° E, respectively. 2. The response speed and response degree of forests to climatic factors are higher than that of grasslands. 3. The lag time of response for vegetation growth to precipitation, air temperature and relative humidity in IMAR is mainly within 2 months. The speed of vegetation‘s response to climate change in IMAR is mainly affected by four major factors: vegetation type, altitude gradient, local climate type and latitude. 4. Vegetation types and altitude gradients are the two most important factors affecting the degree of vegetation’s response to climate factors. It is worth noting that when the altitude rises to 2500 m, the dominant factor for the vegetation growth changes from precipitation to air temperature in terms of hydrothermal combination in the environment. Vegetation growth in areas with relatively high altitudes is more dependent on air temperature.

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