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

2014 ◽  
Vol 36 (2) ◽  
pp. 185 ◽  
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.

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 Factors Driving Changes in Vegetation in Mt. Qomolangma (Everest): Implications for the Management of Protected Areas

2021 ◽  
Vol 13 (22) ◽  
pp. 4725
Author(s):  
Binghua Zhang ◽  
Yili Zhang ◽  
Zhaofeng Wang ◽  
Mingjun Ding ◽  
Linshan Liu ◽  
...  
Keyword(s):  
Linear Regression ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Factors ◽  
Time Lag ◽  
Buffer Zone ◽  
Rate Of Change ◽  
Vegetation Growth ◽  
Time Accumulation ◽  
The Impact

The Mt. Qomolangma (Everest) National Nature Preserve (QNNP) is among the highest natural reserves in the world. Monitoring the spatiotemporal changes in the vegetation in this complex vertical ecosystem can provide references for decision makers to formulate and adapt strategies. Vegetation growth in the reserve and the factors driving it remains unclear, especially in the last decade. This study uses the normalized difference vegetation index (NDVI) in a linear regression model and the Breaks for Additive Seasonal and Trend (BFAST) algorithm to detect the spatiotemporal patterns of the variations in vegetation in the reserve since 2000. To identify the factors driving the variations in the NDVI, the partial correlation coefficient and multiple linear regression were used to quantify the impact of climatic factors, and the effects of time lag and time accumulation were also considered. We then calculated the NDVI variations in different zones of the reserve to examine the impact of conservation on the vegetation. The results show that in the past 19 years, the NDVI in the QNNP has exhibited a greening trend (slope = 0.0008/yr, p < 0.05), where the points reflecting the transition from browning to greening (17.61%) had a much higher ratio than those reflecting the transition from greening to browning (1.72%). Shift points were detected in 2010, following which the NDVI tendencies of all the vegetation types and the entire preserve increased. Considering the effects of time lag and time accumulation, climatic factors can explain 44.04% of the variation in vegetation. No climatic variable recorded a change around 2010. Considering the human impact, we found that vegetation in the core zone and the buffer zone had generally grown better than the vegetation in the test zone in terms of the tendency of growth, the rate of change, and the proportions of different types of variations and shifts. A policy-induced reduction in livestock after 2010 might explain the changes in vegetation in the QNNP.

scholarly journals Satellite-Observed Effects from Ozone Pollution and Climate Change on Growing-Season Vegetation Activity over China during 1982–2020

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1390
Author(s):  
Zhaosheng Wang
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Large Scale ◽  
Vegetation Index ◽  
Growing Season ◽  
Ozone Pollution ◽  
Vegetation Growth ◽  
Vegetation Activity ◽  
The Impact

Remote sensing vegetation index data contain important information about the effects of ozone pollution, climate change and other factors on vegetation growth. However, the absence of long-term observational data on surface ozone pollution and neglected air pollution-induced effects on vegetation growth have made it difficult to conduct in-depth studies on the long-term, large-scale ozone pollution effects on vegetation health. In this study, a multiple linear regression model was developed, based on normalized difference vegetation index (NDVI) data, ozone mass mixing ratio (OMR) data at 1000 hPa, and temperature (T), precipitation (P) and surface net radiation (SSR) data during 1982–2020 to quantitatively assess the impact of ozone pollution and climate change on vegetation growth in China on growing season. The OMR data showed an increasing trend in 99.9% of regions in China over the last 39 years, and both NDVI values showed increasing trends on a spatial basis with different ozone pollution levels. Additionally, the significant correlations between NDVI and OMR, temperature and SSR indicate that vegetation activity is closely related to ozone pollution and climate change. Ozone pollution affected 12.5% of NDVI, and climate change affected 26.7% of NDVI. Furthermore, the effects from ozone pollution and climate change on forest, shrub, grass and crop vegetation were evaluated. Notably, the impact of ozone pollution on vegetation growth was 0.47 times that of climate change, indicating that the impact of ozone pollution on vegetation growth cannot be ignored. This study not only deepens the understanding of the effects of ozone pollution and climate change on vegetation growth but also provides a research framework for the large-scale monitoring of air pollution on vegetation health using remote sensing vegetation data.

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

2018 ◽  
Vol 40 (2) ◽  
pp. 91 ◽  
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 Indication of the Two Linear Correlation Methods Between Vegetation Index and Climatic Factors: An Example in the Three River-Headwater Region of China During 2000–2016

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 606
Author(s):  
Jiaxin Xu ◽  
Shibo Fang ◽  
Xuan Li ◽  
Zichun Jiang
Keyword(s):  
Correlation Coefficient ◽  
Linear Correlation ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Meteorological Data ◽  
Growing Season ◽  
Climatic Conditions ◽  
The Difference ◽  
The Impact ◽  
The Relationship

The within-growing-season correlations (WGSC) and the inter-growing-season correlations (IGSC) are widely used linear correlation analysis methods between vegetation index and climatic factors (such as temperature, precipitation, and so on). The WGSC method usually calculates the linear correlation coefficient between vegetation index and climatic factors of each month in all the growing seasons, for instance, whether vegetation index or temperature had data of 204 months (12 months × 17 years) during 2000–2016 to get the WGSC. The IGSC calculates the linear correlation coefficient between the vegetation index and climatic factors in the same month of each growing season among all the years, for example, only 17 couples’ data of vegetation index and temperature during 2000–2016 were used to get the linear correlation of IGSC. What is the difference between the results of the two methods and why do the results show that difference? Which is the more suitable method for the analysis of the relationship between the vegetation index and climatic conditions? To clarify the difference of the two methods and to explore more about the relationship between the vegetation index and climatic factors, we collected the data of 2000–2016 moderate resolution imaging spectroradiometer (MODIS) 13A1 normalized difference vegetation index (NDVI) and the meteorological data-temperature and precipitation, then calculated WGSC and IGSC between NDVI and the climatic factor in three river-headwater regions of China. The results showed that: (1) As for WGSC, the more of the years included, the higher the correlation coefficient between NDVI and the temperature/precipitation. The correlation coefficient of WGSC is dependent on how many years’ the data were included, and it was increased with the more year’s data included, while the correlation coefficients of IGSC are relatively independent on the amount of the data; (2) the WGSC showed a pseudo linear correlation between NDVI and climatic conditions caused by the accumulation of data amount, while the IGSC can more accurately indicate the impact of climatic factors on vegetation since it did not rely on the data amount.

Detection of the Impact of Climate Change on Desertification and Sand Dunes Formation East of the Tigris River in Salah Al-Din Governorate Using Remote Sensing Techniques

2020 ◽  
Vol 54 (1A) ◽  
pp. 69-83
Author(s):  
Muaid Rasheed
Keyword(s):  
Wind Speed ◽  
Climatic Factors ◽  
Sand Dunes ◽  
Geological Structure ◽  
Error Matrix ◽  
Vegetation Growth ◽  
Factors Affecting ◽  
Geological Situation ◽  
Remote Sensing Techniques ◽  
The Impact

The study deals with the geological situation of Earth's features, and the effect of climate on them, through monitoring changes that have occurred in Earth's features by applying supervised classification represented by maximum likelihood classification using GIS 10.7 for years 1990–2019 to produce maps of desertification and sand dunes encroachment. The factors forming the Earth's features in the study area vary due to the geological structure, geomorphological processes, and climatic factors, which requires an analysis of these processes and their impact on environmental components. The climate of the study area is characterized by continental characteristics causing significant differences in the geomorphological units of the region, especially sand dunes. The most important climate factors affecting the desertification and dunes are the temperature, evaporation, wind speed and rainfall. Three satellite images were used in this study, obtained from Landsat 5-8 besides, the rate annual of temperature, evaporation, wind speed and the total annual of rainfall obtained from European center ECMWF. To obtain high accuracy of classification, an Error Matrix and Kappa Coefficient was processed using ERDAS. The results showed clear changes in the Earth's features with climate during the entire period, where the increase in the rate of temperature and evaporation enhances desertification and encroachment of dunes due to the dryness of the area resulting from the decrease in rainfall rates due to the lack of vegetation growth, as the area of desertification increased to 3028 km2 in 2019, compared with 1990, while the area of dunes double, in the year 2019 compared to the year 1990. dune encroachment changed directly with the winds as a result of wind blowing in a northwestern direction, so the dunes expanded in the south and southwest direction at the expense of cultivated areas as they encroachments by 20 km compared to 1990.

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

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.

Impact of climatic conditions on the parameters of failure flow of military vehicles

2021 ◽  
pp. 095440702110202
Author(s):  
Nikolaj Dobrzinskij ◽  
Algimantas Fedaravicius ◽  
Kestutis Pilkauskas ◽  
Egidijus Slizys
Keyword(s):  
Climatic Factors ◽  
Armed Forces ◽  
Climatic Conditions ◽  
Operating Conditions ◽  
Technical Equipment ◽  
Factors Affecting ◽  
Military Vehicles ◽  
Equipment Reliability ◽  
Number Of Factors ◽  
The Impact

Relevance of the article is based on participation of armed forces in various operations and exercises, where reliability of machinery is one of the most important factors. Transportation of soldiers as well as completion of variety of tasks is ensured by properly functioning technical equipment. Reliability of military vehicles – armoured SISU E13TP Finnish built and HMMWV M1025 USA built were selected as the object of the article. Impact of climatic conditions on reliability of the vehicles exploited in southwestern part of the Atlantic continental forest area is researched by a case study of the vehicles exploitation under conditions of the climate of Lithuania. Reliability of military vehicles depends on a number of factors such as properties of the vehicles and external conditions of their operation. Their systems and mechanisms are influenced by a number of factors that cause different failures. Climatic conditions represent one of the factors of operating load which is directly dependent on the climate zone. Therefore, assessment of the reliability is started with the analysis of climatic factors affecting operating conditions of the vehicles. Relationship between the impact of climatic factors and failure flow of the vehicles is presented and discussed.

scholarly journals Coastal Mangrove Response to Marine Erosion: Evaluating the Impacts of Spatial Distribution and Vegetation Growth in Bangkok Bay from 1987 to 2017

2020 ◽  
Vol 12 (2) ◽  
pp. 220 ◽  
Author(s):  
Han Xiao ◽  
Fenzhen Su ◽  
Dongjie Fu ◽  
Qi Wang ◽  
Chong Huang
Keyword(s):  
Spatial Distribution ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Mangrove Ecosystem ◽  
Early Growth ◽  
Growth Stages ◽  
Human Disturbances ◽  
Vegetation Growth ◽  
Two Parameters ◽  
The Impact

Long time-series monitoring of mangroves to marine erosion in the Bay of Bangkok, using Landsat data from 1987 to 2017, shows responses including landward retreat and seaward extension. Quantitative assessment of these responses with respect to spatial distribution and vegetation growth shows differing relationships depending on mangrove growth stage. Using transects perpendicular to the shoreline, we calculated the cross-shore mangrove extent (width) to represent spatial distribution, and the normalized difference vegetation index (NDVI) was used to represent vegetation growth. Correlations were then compared between mangrove seaside changes and the two parameters—mangrove width and NDVI—at yearly and 10-year scales. Both spatial distribution and vegetation growth display positive impacts on mangrove ecosystem stability: At early growth stages, mangrove stability is positively related to spatial distribution, whereas at mature growth the impact of vegetation growth is greater. Thus, we conclude that at early growth stages, planting width and area are more critical for stability, whereas for mature mangroves, management activities should focus on sustaining vegetation health and density. This study provides new rapid insights into monitoring and managing mangroves, based on analyses of parameters from historical satellite-derived information, which succinctly capture the net effect of complex environmental and human disturbances.

scholarly journals Facilitation Effects of Haloxylon salicornicum Shrubs on Associated Understory Annuals, and a Modified “Stress-Gradient” Hypothesis for Droughty Times

Plants ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 1726
Author(s):  
Nasr H. Gomaa ◽  
Ahmad K. Hegazy ◽  
Arafat Abdel Hamed Abdel Latef
Keyword(s):  
Species Richness ◽  
Water Availability ◽  
Stress Gradient ◽  
Growing Season ◽  
Annual Species ◽  
Negative Effects ◽  
Growing Seasons ◽  
Dry Seasons ◽  
The Impact ◽  
Haloxylon Salicornicum

Perennial shrub-annual plant interactions play key roles in desert regions influencing the structure and dynamics of plant communities there. In the present study, carried out in northwestern Saudi Arabia, we examined the effect of Haloxylon salicornicum shrubs on their associated understory annual species across four consecutive growing seasons, along with a record of the seasonal rainfall patterns. We measured density and species richness of all the annual species in permanent quadrats located beneath individual shrubs, as well as in the spaces between shrubs. During wet growing season H. salicornicum shrubs significantly enhanced the density and species richness of sub-canopy species, whereas in the relatively dry seasons they exerted negative effects on the associated species. In all growing seasons, the presence of shrubs was associated with enhanced soil properties, including increased organic carbon content, silt + clay, and levels of nutrients (N, P and K). Shrubs improved soil moisture content beneath their canopies in the wet growing season, while in the dry seasons they had negative effects on water availability. Differences in effects of H. salicornicum on understory plants between growing seasons seem due to the temporal changes in the impact of shrubs on water availability. Our results suggest the facilitative effects of shrubs on sub-canopy annuals in arid ecosystems may switch to negative effects with increasing drought stress. We discuss the study in light of recent refinements of the well-known “stress-gradient hypothesis”.

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