scholarly journals The sensitivity of vegetation in the lower Tigris basin landscapes to regional and global climate variability

2021 ◽  
Vol 30 (1) ◽  
pp. 159-170
Author(s):  
Ali Alhumaima ◽  
Sanjar Abdullaev
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Southern Oscillation ◽  
Global Climate ◽  
Standardized Precipitation Index ◽  
Monthly Precipitation ◽  
Anthropogenic Landscapes ◽  
Precipitation And Temperature

This study investigates the lower Tigris basin’s the normalized difference vegetation index (NDVI) sensitivity in 2000–2016 to regional climate variability reflected by the monthly precipitation and temperature time series of seven global datasets as well as to four global circulation indices. To examine the effect of climate variability on the different ecosystems, the study area has been classified into 10 smaller natural and anthropogenic landscapes based on landforms and land cover patterns. The preliminary analysis showed that the maximum biological productivity reflected by the NDVI of March and April has the highest correlation (0.5–0.8) to the same cumulative amounts of October–March period total precipitation and January–March period mean temperatures according to all datasets. In addition, this article showed there is a correlation between landscapes’ NDVI and global modulation represented by the September–February state of El Nińo-Southern Oscillation (ENSO) (0.55–0.70) and December state of the dipole mode index (DMI) (0.35–0.72). The significant differences in the original precipitation and temperature levels according to the different datasets have urged the use of normalized time series: z-score of temperatures and analogous six-months the standardized precipitation index (SPI). However, the multiple correlation analysis showed that using ERA-

scholarly journals Phenological behavior of Atlas cedar (Cedrus atlantica) forest to snow and precipitation variability in Boutaleb and Babors Mountains, Algeria

2019 ◽  
Vol 21 (1) ◽  
Author(s):  
Khaled Missaoui ◽  
Rachid Gharzouli ◽  
Yamna Djellouli ◽  
Frençois Messner
Keyword(s):  
Time Series ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Descriptive Analysis ◽  
Precipitation Variability ◽  
Monthly Precipitation ◽  
Cedrus Atlantica ◽  
The Past

Abstract. Missaoui K, Gharzouli R, Djellouli Y, Messner F. 2020. Phenological behavior of Atlas cedar (Cedrus atlantica)  forest to snow and precipitation variability in Boutaleb and Babors Mountains, Algeria. Biodiversitas 21: 239-245. Understanding the changes in snow and precipitation variability and how forest vegetation response to such changes is very important to maintain the long-term sustainability of the forest. However, relatively few studies have investigated this phenomenon in Algeria. This study was aimed to find out the response of Atlas cedar (Cedrus atlantica (Endl.) G.Manetti ex Carrière) forest in two areas (i.e Boutaleb and Babors Mountains) and their response to the precipitation and snow variability. The normalized difference vegetation index (NDVI) generated from satellite images of MODIS time series was used to survey the changes of the Atlas cedar throughout the study area well as dataset of monthly precipitation and snow of the province of Setif (northeast of Algeria) from 2000 to 2018. Descriptive analysis using Standarized Precipitation Index (SPI) showed the wetter years were more frequent in the past than in the last two decades. The NDVI values changes in both areas with high values were detected in Babors Mountains with statistically significant differences. Our findings showed important difference in Atlas cedar phenology from Boutaleb mountains to Babors Mountains which likely related to snow factor.

scholarly journals Tigris Basin Landscapes: Sensitivity of Vegetation Index NDVI to Climate Variability Derived from Observational and Reanalysis Data

2020 ◽  
Vol 24 (7) ◽  
pp. 1-18
Author(s):  
A. S. Alhumaima ◽  
S. M. Abdullaev
Keyword(s):  
Climate Variability ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Southern Oscillation ◽  
Regional Climate ◽  
Rank Correlation ◽  
Reanalysis Data ◽  
Climate Conditions ◽  
Landscape Type ◽  
Global Circulation

AbstractThe primary aim of this work is to study the response of the normalized difference vegetation index (NDVI) of landscapes in the lower Tigris basin to current global and regional climate variability presented, respectively, by the global circulation indices and monthly temperatures and precipitation extracted from five observational/reanalysis datasets. The second task is to find the dataset that best reflects the regional vegetation and climate conditions. Comparison of the Köppen–Trewartha bioclimatic landscapes with the positions of botanical districts, land-cover types, and streamflow estimates led to the conclusion that only two datasets correctly describe regional climatic zones. Therefore, searching for the NDVI response to regional climate variability requires the use of normalized analogs of temperatures and precipitations, as well as the Spearman rank correlation. We found that March/April NDVI, as proxies of the maximum biological productivity of the regional landscapes, are strongly correlated with October–March precipitation derived from three datasets and January–March temperatures derived from one dataset. We discovered the significant impact of autumn–winter El Niño–Southern Oscillation and winter Indian Oceanic dipole states on regional weather (e.g., all five recent severe droughts occurred during strong La Niña events). However, the strength of this impact on the vegetation was clearly linked to the zonal landscape type. By selecting pairs of the temperature/precipitation time series that best correlated with NDVI at a given landscape, we have built a synthetic climate dataset. The landscape approach presented in this work can be used to validate the viability of any dataset when assessing the impacts of climate change and variability on weather-dependent components of Earth’s surface.

An Empirical Decomposition of Deep Groundwater Time Series and Possible Link to Climate Variability

2013 ◽  
Vol 16 (1) ◽  
pp. 87-103
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Polynomial Interpolation ◽  
Southern Oscillation ◽  
Global Climate ◽  
Deep Groundwater ◽  
Anthropogenic Effect ◽  
Cyclic Patterns ◽  
History Of

<p>Deep groundwater data reflects hydrological processes, climate change and variability, as well as any anthropogenic influence. Decomposition of deep groundwater signal examines the history of the groundwater region. Detrending is a vital step in decomposition of groundwater time series because it is expected to remove anthropogenic effects and long-term cyclic patterns. Eight detrending methods were applied to long-term groundwater records monitored in the Lower Chao Phraya basin in Thailand. Detrended residuals and subsequently periodograms of the residuals were computed by applying the Fourier series analysis. The result from this study indicates that the 5th order polynomial interpolation provides the trendlines that significantly relate to the groundwater withdrawal background. The detrended residual function is imbedded with two major cyclic patterns, which can be the result from global climate variability, e.g. Indian Ocean Dipole and the El Niño Southern Oscillation. The magnitude of deep groundwater dynamics as the result from the anthropogenic effect is much greater than that of the climate variability in this region. In addition, this study demonstrates that caution must be exercised when fitting groundwater time series with different detrending techniques can yield mistaken cyclic patterns and may infer to different climate variability phenomenon.</p>

scholarly journals Spatial Patterns of NDVI Variation over Indonesia and Their Relationship to ENSO Warm Events during the Period 1982–2006

2009 ◽  
Vol 22 (24) ◽  
pp. 6612-6623 ◽  
Author(s):  
Stefan Erasmi ◽  
Pavel Propastin ◽  
Martin Kappas ◽  
Oleg Panferov
Keyword(s):  
Time Series ◽  
El Niño ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
El Nino ◽  
Southern Oscillation ◽  
Spatially Explicit ◽  
Forest Conversion ◽  
Climate Anomalies ◽  
Indonesian Archipelago

Abstract The present study is based on the assumption that vegetation in Indonesia is significantly affected by climate anomalies that are related to El Niño–Southern Oscillation (ENSO) warm phases (El Niño) during the past decades. The analysis builds upon a monthly time series from the normalized difference vegetation index (NDVI) gridded data from the Advanced Very High Resolution Radiometer (AVHRR) and two ENSO proxies, namely, sea surface temperature anomalies (SSTa) and Southern Oscillation index (SOI), and aims at the analysis of the spatially explicit dimension of ENSO impact on vegetation on the Indonesian archipelago. A time series correlation analysis between NDVI anomalies and ENSO proxies for the most recent ENSO warm events (1982–2006) showed that, in general, anomalies in vegetation productivity over Indonesia can be related to an anomalous increase of SST in the eastern equatorial Pacific and to decreases in SOI, respectively. The net effect of these variations is a significant decrease in NDVI values throughout the affected areas during the ENSO warm phases. The 1982/83 ENSO warm episode was rather short but—in terms of ENSO indices—the most extreme one within the study period. The 1997/98 El Niño lasted longer but was weaker. Both events had significant impact on vegetation in terms of negative NDVI anomalies. Compared to these two major warm events, the other investigated events (1987/88, 1991/92, 1994/95, and 2002/03) had no significant effect on vegetation in the investigated region. The land cover–type specific sensitivity of vegetation to ENSO anomalies revealed thresholds of vegetation response to ENSO warm events. The results for the 1997/98 ENSO warm event confirm the hypothesis that the vulnerability of vegetated tropical land surfaces to drought conditions is considerably affected by land use intensity. In particular, it could be shown that natural forest areas are more resistant to drought stress than degraded forest areas or cropland. Comparing the spatially explicit patterns of El Niño–related vegetation variation during the major El Niño phases, the spatial distribution of affected areas reveals distinct core regions of ENSO drought impact on vegetation for Indonesia that coincide with forest conversion and agricultural intensification hot spots.

Climate change impacts and vegetation response on the island of Madagascar

2005 ◽  
Vol 363 (1826) ◽  
pp. 55-59 ◽  
Author(s):  
J. Carter Ingram ◽  
Terence P. Dawson
Keyword(s):  
Climate Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Southern Oscillation ◽  
Global Climate ◽  
Hot Spot ◽  
Vegetative Cover ◽  
Vegetation Response ◽  
Natural Habitats ◽  
Strong Negative Correlation

The island of Madagascar has been labelled the world's number one conservation ‘hot spot’ because of increasing anthropogenic degradation of its natural habitats, which support a high level of species endemism. However, climatic phenomena may also have a significant impact upon the island's flora and fauna. An analysis of 18 years of monthly satellite images from the National Oceanographic and Atmospheric Administration's (NOAA) Advanced Very High Resolution Radiometer (AVHRR) have demonstrated that there is a dynamic pattern in Madagascar's vegetative cover both annually and seasonally throughout 1982–1999. Over interannual time–scales, we show that this vegetation response, calculated using the normalized difference vegetation index (NDVI), has a strong negative correlation with the El Niño Southern Oscillation (ENSO), which can be attributable to drought events and associated wildfires. Global climate change is predicted to increase the frequency of the ENSO phenomenon, resulting in further decline of Madagascar's natural environment.

scholarly journals Análise de Eventos Extremos na Região Amazônica (Analysis of Extreme Events in the Amazon Region)

2013 ◽  
Vol 6 (5) ◽  
pp. 1356 ◽  
Author(s):  
Thalyta Soares dos Santos ◽  
Ana Carla Dos Santos Gomes ◽  
Maytê Duarte Leal Coutinho ◽  
Allan Rodrigues Silva ◽  
Aline Anderson de Castro
Keyword(s):  
Time Series ◽  
Time Scales ◽  
Maximum Likelihood Method ◽  
Global Climate ◽  
Standardized Precipitation Index ◽  
Amazon Region ◽  
Likelihood Method ◽  
Monthly Precipitation ◽  
The Standardized Precipitation Index ◽  
Porto Velho

A frequência de eventos severos e extremos de seca e chuva na Amazônia foi analisada utilizando o Índice de Precipitação Normalizada (SPI) nas escalas de 6 (sazonal estação seca/chuvosa) e 12 meses (interanual). A frequência de eventos secos e chuvosos é importante para a climatologia da região, que é considerada um regulador climático global. Para isso foram selecionadas as séries climatológicas, de 1925 a 2000, de seis localidades da região Amazônica: Belém, Cuiabá, Iauretê, Manaus, Porto Velho, Taguatinga. Os SPIs, 6 e 12, que quantificam excesso ou déficit de chuva, nestas duas escalas de tempo, foram calculados a partir dos ajustes de distribuição gama, pelo método da máxima verossimilhança às médias móveis de 6 e 12 meses das precipitações mensais. Esses foram computados a partir da normalização das probabilidades gama, pelos seus respectivos desvios padrões. As séries temporais dos SPIs 6 e 12, mostram longos períodos de oscilação entre eventos secos e chuvosos. A frequência decenal de ambos SPIs indica variações entre as décadas mais chuvosas e secas nos municípios estudados. As décadas mais chuvosas e secas são periódicas para as duas escalas de tempo analisadas em todas as estações, exceto Iauretê. A B S T R A C T The frequency of severe and extremes events of drought and rainfall in the Amazon was analyzed using the Standardized Precipitation Index (SPI) in the scales of six months (dry/wet seasons) and 12 months (inter-annual). This is important for the climatology of the region, which is considered a global climate regulator. With this objective, the climatological series from 1925 to 2000 were selected for six locations in the Amazon region: Belém, Cuiabá, Iauretê, Manaus, Porto Velho and Taguatinga. With the aim of quantify the excess or deficit of rainfall in the selected time scales, the SPIs 6 and 12 were calculated using the fit of the gamma distribution by the maximum likelihood method for the moving averages 6 and 12 months of monthly precipitation. These were computed from the normalization of gamma probabilities by its standard deviation. The time series of SPIs 6 and 12, show long periods of oscillation between dry and wet events. The frequency of both SPIs indicates variations between wet and dry decades in the cities studied. Wetter and drier decades were shown to be periodic for the two time scales considered in all locations, except for Iauretê. Key-Words: SPI, Amazon, Drought, Rain

scholarly journals Testing Possible Scenario-Based Responses of Vegetation Under Expected Climatic Changes in Khuzestan Province

2021 ◽  
Vol 14 ◽  
pp. 117862212110133
Author(s):  
Hadi Eskandari Damaneh ◽  
Meysam Jafari ◽  
Hamed Eskandari Damaneh ◽  
Marjan Behnia ◽  
Asadollah Khoorani ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Kendall Test ◽  
Baseline Period ◽  
System Model ◽  
Future Period ◽  
Khuzestan Province ◽  
Ecosystem Planning ◽  
Slope Estimator ◽  
Precipitation And Temperature

Projections of future scenarios are scarce in developing countries where human activities are increasing and impacting land uses. We present a research based on the assessment of the baseline trends of normalized difference vegetation index (NDVI), precipitation, and temperature data for the Khuzestan Province, Iran, from 1984 to 2015 compiled from ground-based and remotely sensed sources. To achieve this goal, the Sen’s slope estimator, the Mann-Kendall test, and Pearson’s correlation test were used. After that, future trends in precipitation and temperature were estimated using the Canadian Earth System Model (CanESM2) model and were then used to estimate the NDVI trend for two future periods: from 2016 to 2046 and from 2046 to 2075. Our results showed that during the baseline period, precipitation decreased at all stations: 33.3% displayed a significant trend and the others were insignificant ones. Over the same period, the temperature increased at 66.7% of stations while NDVI decreased at all stations. The NDVI–precipitation relationship was positive while NDVI–temperature showed an inverse trend. During the first of the possible future periods and under the RCP2.6, RCP4.5, and RCP8.5 scenarios, NDVI and precipitation decreased, and temperatures significantly increased. In addition, the same trends were observed during the second future period; most of these were statistically significant. We conclude that much assessments are valuable and integral components of effective ecosystem planning and decisions.

scholarly journals Assessment of Rangeland Degradation in New Mexico Using Time Series Segmentation and Residual Trend Analysis (TSS-RESTREND)

2021 ◽  
Vol 13 (9) ◽  
pp. 1618
Author(s):  
Melakeneh G. Gedefaw ◽  
Hatim M. E. Geli ◽  
Temesgen Alemayehu Abera
Keyword(s):  
Time Series ◽  
New Mexico ◽  
Trend Analysis ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Rangeland Management ◽  
Environmental Benefits ◽  
Drought Severity ◽  
Assessment Framework ◽  
Rangeland Degradation

Rangelands provide significant socioeconomic and environmental benefits to humans. However, climate variability and anthropogenic drivers can negatively impact rangeland productivity. The main goal of this study was to investigate structural and productivity changes in rangeland ecosystems in New Mexico (NM), in the southwestern United States of America during the 1984–2015 period. This goal was achieved by applying the time series segmented residual trend analysis (TSS-RESTREND) method, using datasets of the normalized difference vegetation index (NDVI) from the Global Inventory Modeling and Mapping Studies and precipitation from Parameter elevation Regressions on Independent Slopes Model (PRISM), and developing an assessment framework. The results indicated that about 17.6% and 12.8% of NM experienced a decrease and an increase in productivity, respectively. More than half of the state (55.6%) had insignificant change productivity, 10.8% was classified as indeterminant, and 3.2% was considered as agriculture. A decrease in productivity was observed in 2.2%, 4.5%, and 1.7% of NM’s grassland, shrubland, and ever green forest land cover classes, respectively. Significant decrease in productivity was observed in the northeastern and southeastern quadrants of NM while significant increase was observed in northwestern, southwestern, and a small portion of the southeastern quadrants. The timing of detected breakpoints coincided with some of NM’s drought events as indicated by the self-calibrated Palmar Drought Severity Index as their number increased since 2000s following a similar increase in drought severity. Some breakpoints were concurrent with some fire events. The combination of these two types of disturbances can partly explain the emergence of breakpoints with degradation in productivity. Using the breakpoint assessment framework developed in this study, the observed degradation based on the TSS-RESTREND showed only 55% agreement with the Rangeland Productivity Monitoring Service (RPMS) data. There was an agreement between the TSS-RESTREND and RPMS on the occurrence of significant degradation in productivity over the grasslands and shrublands within the Arizona/NM Tablelands and in the Chihuahua Desert ecoregions, respectively. This assessment of NM’s vegetation productivity is critical to support the decision-making process for rangeland management; address challenges related to the sustainability of forage supply and livestock production; conserve the biodiversity of rangelands ecosystems; and increase their resilience. Future analysis should consider the effects of rising temperatures and drought on rangeland degradation and productivity.

scholarly journals Climate Dynamics of the Spatiotemporal Changes of Vegetation NDVI in Northern China from 1982 to 2015

2021 ◽  
Vol 13 (2) ◽  
pp. 187
Author(s):  
Rui Sun ◽  
Shaohui Chen ◽  
Hongbo Su
Keyword(s):  
Solar Radiation ◽  
Vegetation Index ◽  
Global Climate ◽  
Regional Scale ◽  
Northern China ◽  
Climate Dynamics ◽  
High Coverage ◽  
Vegetation Growth ◽  
Temperature And Precipitation ◽  
Precipitation And Temperature

As an important part of a terrestrial ecosystem, vegetation plays an important role in the global carbon-water cycle and energy flow. Based on the Global Inventory Monitoring and Modeling System (GIMMS) third generation of Normalized Difference Vegetation Index (NDVI3g), meteorological station data, climate reanalysis data, and land cover data, this study analyzed the climate dynamics of the spatiotemporal variations of vegetation NDVI in northern China from 1982 to 2015. The results showed that growth season NDVI (NDVIgs) increased significantly at 0.006/10a (p < 0.01) in 1982–2015 on the regional scale. The period from 1982 to 2015 was divided into three periods: the NDVIgs increased by 0.026/10a (p < 0.01) in 1982–1990, decreased by −0.002/10a (p > 0.1) in 1990–2006, and then increased by 0.021/10a (p < 0.01) during 2006–2015. On the pixel scale, the increases in NDVIgs during 1982–2015, 1982–1990, 1990–2006, and 2006–2015 accounted for 74.64%, 85.34%, 48.14%, and 68.78% of the total area, respectively. In general, the dominant climate drivers of vegetation growth had gradually switched from solar radiation, temperature, and precipitation (1982–1990) to precipitation and temperature (1990–2015). For woodland, high coverage grassland, medium coverage grassland, low coverage grassland, the dominant climate drivers had changed from temperature and solar radiation, solar radiation and precipitation, precipitation and solar radiation, solar radiation to precipitation and solar radiation, precipitation, precipitation and temperature, temperature and precipitation. The areas controlled by precipitation increased significantly, mainly distributed in arid, sub-arid, and sub-humid areas. The dominant climate drivers for vegetation growth in the plateau climate zone or high-altitude area changed from solar radiation to temperature and precipitation, and then to temperature, while in cold temperate zone, changed from temperature to solar radiation. These results are helpful to understand the climate dynamics of vegetation growth, and have important guiding significance for vegetation protection and restoration in the context of global climate change.

Sign in / Sign up

Export Citation Format

Share Document