Analysis of Agricultural Drought in East Java Using Vegetation Health Index

Drought is a natural hazard indicated by the decreasing of rainfall and water storage and impacting agricultural sector. Agricultural drought assessment has been used to monitor agricultural sustainability, particularly in East Java as national agricultural production center. Identification of drought characteristics –correlated with El Niño-Southern Oscillation, and agricultural impact on paddy fields and rice production using VHI (Vegetation Health Index) were conducted. VHI is produced by TCI (Temperature Condition Index) and VCI (Vegetation Condition Index) derived from MODIS satellite data, LST (Land Surface Temperature) and EVI (Enhanced Vegetation Index), respectively. The results showed agricultural drought usually started in June, maximum in October and ended in November. Onset and end time drought tends to follow monsoonal rainfall pattern. El Niño 2015 showed long duration of agricultural drought (i.e. ± 5 months), high severity (i.e. mild-extreme drought; VHI 0-40) and areal extent of drought approx. 197,343 km2, while during La Niña 2010 the areal extent was approx. 28,685 km2 with mild-severe drought (VHI 10-40). Impact of agricultural drought on paddy fields showed wider (smaller) areal extent in sub-round 3 (sub-round 1) from September-December (January-April). Areal extent of drought was negatively correlated with rice production (r=-0.79) which significant in 99 % confidence level

Climatic change controls productivity variation in global grasslands.

Detection and identification of the impacts of climate change on ecosystems have been core issues in climate change research in recent years. In this study, we compared average annual values of the normalized difference vegetation index (NDVI) with theoretical net primary productivity (NPP) values based on temperature and precipitation to determine the effect of historic climate change on global grassland productivity from 1982 to 2011. Comparison of trends in actual productivity (NDVI) with climate-induced potential productivity showed that the trends in average productivity in nearly 40% of global grassland areas have been significantly affected by climate change. The contribution of climate change to variability in grassland productivity was 15.2-71.2% during 1982-2011. Climate change contributed significantly to long-term trends in grassland productivity mainly in North America, central Eurasia, central Africa, and Oceania; these regions will be more sensitive to future climate change impacts. The impacts of climate change on variability in grassland productivity were greater in the Western Hemisphere than the Eastern Hemisphere. Confirmation of the observed trends requires long-term controlled experiments and multi-model ensembles to reduce uncertainties and explain mechanisms

Significance of soil moisture on vegetation greenness in the African Sahel from 1982 to 2008

Popular science The Sahel is a semi-arid eco-climatic transition zone in northern Africa separating the Sahara desert from the Africa’s tropical forest. The Sahel word in Arabic language means “shore” which is linguistically describes the appearances of vegetation as a shoreline defining the boundary of the Sahara desert. Soil moisture (rainwater accumulated over a period of time in soil) is considered one of the most important factors on vegetation growth in Sahel as the agriculture droughts occurs due to soil moisture deficiency. The projected number of Africans in semi-arid locations will suffer from increasing water stress by 2020s is between 75-250 million and this number is projected to increase to be between 350-600 million by 2050s. This study aims to evaluate the relationship between soil moisture and vegetation growth in Sahel region during 1982-2008 at different time lags. Land cover and soil texture data were used to investigate whether the relationship between soil moisture and vegetation growth are related to land cover and soil type or not. Satellite remote sensing data (vegetation index), modelled soil moisture data land cover map and soil type map were mainly used to achieve the purpose of this study. The most important findings of this study is the best correlations between vegetation greenness and soil moisture occurred at lag0 (no time lag differences), lag1 (one month time lag) and lag2 (two months’ time lags). The correlation relationship varied between low and moderate values in Sahel region indicating that soil moisture variable is not only the main driver for vegetation dynamics in the study area and maybe other factors such as human impacts could have a great contribution on vegetation changes in Sahel. Croplands and Grasslands are the main land cover types that increasing the correlation relationship between soil moisture and vegetation growth, whereas Entisols (occur in flood plains and steep slopes) and Alfisols (occur under forest and mixed vegetation cover) are the main soil types showing a positive effect on the correlation relationship between soil moisture and vegetation dynamics. Finally, good understanding the temporal relationship between water availability and vegetation dynamics can help us to know water affects plant growth and to predict the future relationship within a season between vegetation growth and soil moisture which can be used for detecting famine possibilities.This study investigates the temporal correlation relationship between vegetation greenness and soil moisture in the African Sahel from 1982 to 2008 at different time lags (maximum five lags used in this study) and determines the extent which soil moisture explains vegetation dynamics in the Sahel. Monthly composites of remotely sensed Normalized Difference Vegetation Index (NDVI) from National Oceanic and Atmospheric Administration’s Advanced Very High Resolution Radiometer (NOAA-AVHRR) were used in this study as a proxy for vegetation growth, whereas modeled soil moisture data (1.6m column depth) provided by the NOAA National Centers for Environmental Predictions (NCEP) Climate Prediction Center (CPC) Global Monthly high resolution Soil Moisture (GMSM) was used as an indicator of moisture availability for plants. The analyses were applied for all-year months data (dry season included) and only for growing months season (from July to October) to estimate the effect of long dry season on the association between vegetation growth and soil moisture. Trends in vegetation greenness, soil moisture and NDVI residuals were calculated separately in Sahel to investigate the changes occurred in vegetation growth and soil moisture during the study period. The correlations relationship were evaluated against land cover and soil texture data to estimate the influences of land cover and soil type on the strength of correlation relationship between vegetation growth and soil moisture. The results showed a significant correlation relationship between vegetation greenness and soil moisture at lag0 (no time lag differences), lag1 (one month time lag) and lag2 (two months’ time lag) with a better association in northern parts of Sahel region by using only the growing season data. However, the significant correlations covered a larger area by using all the year data (long dry season included). The results indicated that using AVHRR NDVI data for studying the vegetation growth in response to soil moisture availability is limited in the southern parts of the study area. The significant correlation coefficients (r) are varied between low and moderate values (0.1-0.6) in the study area, suggesting that soil moisture is not only the main driver of vegetation dynamics in Sahel. Vegetation greenness showed a significant increase during the study period in many locations in Sahel region (center of Chad, Senegal and south of Mali), whereas soil moisture showed a small significant locations in the study area (center of Sudan, center of Mali and east of Mauritania) during the study period from 1982-2008. Land cover type (Croplands and Grasslands) and soil texture (Entisols and Alfisols) showed a significant association and high influences on the correlation relationship between vegetation greenness and soil moisture at lag0, lag1 and lag2.Scientific abstract Soil moisture (rainwater accumulated over a period of time in soil) is considered one of the most important factors on vegetation growth in Sahel as the agriculture droughts usually associated with soil moisture deficiency. This thesis study investigates the correlation relationship between soil moisture and vegetation greenness in the Sahel region from 1982 to 2008 at different time lags (maximum five lags used in our analysis). Monthly time series data of remotely sensed Normalized Difference Vegetation Index (NDVI) from National Oceanic and Atmospheric Administration’s Advanced Very High Resolution Radiometer (NOAA-AVHRR) was used in this study as a proxy for vegetation growth, whereas the monthly modeled soil moisture data was provided by the NOAA National Centers for Environmental Predictions (NCEP) Climate Prediction Center (CPC) Global Monthly high resolution Soil Moisture (GMSM). Land cover map and soil map data of Sahel region were used to investigate the effect of land cover and soil type on the correlation relationship. The results were based on pixel by pixel analysis for two time frames: all-year data (dry season included) and only growing season (from July to October). The best correlation between NDVI and soil moisture occurred at lag0 (no time lag difference), lag1 (one month time lag) and lag2 (two month time lag) and the strength of relationship is decreasing by increasing time lags (lag0, lag1 and lag2 are the dominant in the study area). The degree of association between NDVI and soil moisture increased in the northern part of Sahel region by using only the growing season data and this relationship was vague in central and southern part of Sahel region. The significant correlation coefficients varied between low and moderate (0.1-0.6) across the study area suggesting that soil moisture is not only the main driver factor on the vegetation dynamics in Sahel region. Trends of vegetation showed a significant increase during the study period in many locations (center of Chad, Senegal and south of Mali), whereas soil moisture showed small significant locations (center of Sudan, center of Mali and east of Mauritania) from 1982-2008. Land cover type (Croplands and Grasslands) and soil type (Entisols and Alfisols) showed a significant influence on the correlation relationship between vegetation greenness and soil moisture

Spatio-temporal variation in leaf area index in the Yan Mountains over the past 40 years and its relationship to hydrothermal conditions

Changes in hydrothermal conditions have significant effects on vegetation, but there is still a lack of understanding of how vegetation responds to land surface (surface temperature and soil moisture) and meteorological (temperature and precipitation) conditions in mountain regions. This study examined the trends of leaf area index (LAI) in the Yan Mountains over the last four decades using Global Land Surface Satellite (GLASS) data. The results showed a persistent increase of LAI (greening) over 20 % to 80 % of the study area in growing season, spring, summer and autumn. Anthropogenic activities caused the greening trend by crop management before 2000 and afforestation after 2000. The increasing rate of LAI varied with elevation, and the most significant increase occurred in areas between 300 and 900 m, and the lowest increase occurred in areas below 300 m. Moreover, we found that LAI was negatively correlated with land surface temperature and soil moisture, but positively correlated with precipitation and air temperature. The time-lag effect was found between hydro thermal factors and LAI in the past four decades. There was a time lag of 2-3 months between LAI changes and temperature/precipitation during the early and late stages of the growing season, and a time lag of 0-1 month during the middle stage. Specifically, there was no time lag in vegetation response to surface soil moisture, and a time lag of 2-3 months in vegetation response to land surface temperature from July to October. Our findings provide insights into how vegetation adapts to land surface and climatic hydrothermal conditions in mountain regions and can be used by governments to develop policies for ecological protection

Spatiotemporal analysis of vegetation variability and its relationship with climate change in China

This paper investigated spatiotemporal dynamic pattern of vegetation, climate factor, and their complex relationships from seasonal to inter-annual scale in China during the period 1982–1998 through wavelet transform method based on GIMMS data-sets. First, most vegetation canopies demonstrated obvious seasonality, increasing with latitudinal gradient. Second, obvious dynamic trends were observed in both vegetation and climate change, especially the positive trends. Over 70% areas were observed with obvious vegetation greening up, with vegetation degradation principally in the Pearl River Delta, Yangtze River Delta, and desert. Overall warming trend was observed across the whole country (\u3e98% area), stronger in Northern China. Although over half of area (58.2%) obtained increasing rainfall trend, around a quarter of area (24.5%), especially the Central China and most northern portion of China, exhibited significantly negative rainfall trend. Third, significantly positive normalized difference vegetation index (NDVI)–climate relationship was generally observed on the de-noised time series in most vegetated regions, corresponding to their synchronous stronger seasonal pattern. Finally, at inter-annual level, the NDVI–climate relationship differed with climatic regions and their long-term trends: in humid regions, positive coefficients were observed except in regions with vegetation degradation; in arid, semiarid, and semihumid regions, positive relationships would be examined on the condition that increasing rainfall could compensate the increasing water requirement along with increasing temperature. This study provided valuable insights into the long-term vegetation–climate relationship in China with consideration of their spatiotemporal variability and overall trend in the global change process

Vegetation anomalies caused by antecedent precipitation in most of the world

Quantifying environmental controls on vegetation is critical to predict the net effect of climate change on global ecosystems and the subsequent feedback on climate. Following a non-linear Granger causality framework based on a random forest predictive model, we exploit the current wealth of multi-decadal satellite data records to uncover the main drivers of monthly vegetation variability at the global scale. Results indicate that water availability is the most dominant factor driving vegetation globally: about 61% of the vegetated surface was primarily water-limited during 1981-2010. This included semiarid climates but also transitional ecoregions. Intraannually, temperature controls Northern Hemisphere deciduous forests during the growing season, while antecedent precipitation largely dominates vegetation dynamics during the senescence period. The uncovered dependency of global vegetation on water availability is substantially larger than previously reported. This is owed to the ability of the framework to (1) disentangle the co-linearities between radiation/temperature and precipitation, and (2) quantify non-linear impacts of climate on vegetation. Our results reveal a prolonged effect of precipitation anomalies in dry regions: due to the long memory of soil moisture and the cumulative, nonlinear, response of vegetation, water-limited regions show sensitivity to the values of precipitation occurring three months earlier. Meanwhile, the impacts of temperature and radiation anomalies are more immediate and dissipate shortly, pointing to a higher resilience of vegetation to these anomalies. Despite being infrequent by definition, hydro-climatic extremes are responsible for up to 10% of the vegetation variability during the 1981-2010 period in certain areas, particularly in water-limited ecosystems. Our approach is a first step towards a quantitative comparison of the resistance and resilience signature of different ecosystems, and can be used to benchmark Earth system models in their representations of past vegetation sensitivity to changes in climate

A non-linear Granger-causality framework to investigate climate-vegetation dynamics

Satellite Earth observation has led to the creation of global climate data records of many important environmental and climatic variables. These come in the form of multivariate time series with different spatial and temporal resolutions. Data of this kind provide new means to further unravel the influence of climate on vegetation dynamics. However, as advocated in this article, commonly used statistical methods are often too simplistic to represent complex climate-vegetation relationships due to linearity assumptions. Therefore, as an extension of linear Granger-causality analysis, we present a novel non-linear framework consisting of several components, such as data collection from various databases, time series decomposition techniques, feature construction methods, and predictive modelling by means of random forests. Experimental results on global data sets indicate that, with this framework, it is possible to detect non-linear patterns that are much less visible with traditional Granger-causality methods. In addition, we discuss extensive experimental results that highlight the importance of considering non-linear aspects of climate-vegetation dynamics

Drought Impact Assessment on Vegetation over Sudano-Sahelian Part of Nigeria

This study evaluated the vegetation response to drought over the Sudano-Sahelian part of Nigeria. Landsat and monthly rainfall data with boundary map shapefile data. The results of SPI analysis revealed that the drought saga of the 70s and 80s was also experienced over the study area but later reversed in the 90s towards the 21st century as the result show a rapid decline in its occurrence which indicates improvement in rainfall. On the other hand, the vegetation response analysis also depicted that the year 1986 was a dry year over the study area as the spatial extent cover by the vegetation was much less compared to the bare-surface. But in the 1990s, greenness has returned to the areas that were previously bare soil, an indication of improvement in rainfall amount over the area. The study therefore concluded that there exists a kind of inverse relationship between drought intensity and vegetation growth and time lag in their response to dry or wet condition. Keywords: Drought Occurrence, Vegetation response, Standardize Precipitation Index (SPI), Normalized Precipitation Index (NDVI), Greenness Index (GI), Drought Spatial Ma

Effects of fire on a prairie arthropod community

x, 97 leaves : ill. ; 28 cm.In this study, I addressed how a large-scale wildfire affected a prairie arthropod community in southern Alberta, Canada. First, I looked at the general effects of disturbance on the arthropod community. Second, I addressed how processes such as competition and secondary succession may have affected diversity in this arthropod community. Third, I determined how the arthropod community trophic structure was regulated. Results showed that the effect of disturbance on arthropods varies greatly by taxa. Factors, such as site, year, distance from disturbance edge, as well as the disturbance itself, were important in determing the abudance, biomass, richness, and diversity of the arthropod community. There were strong year-to-year differences hat exceeded the disturbance effects. Results showed that the processess behind the intermediate disturbance hypothesis, succession and competition are not detectable in this arthropod community. This arthropod community was likely regulated in a bottom-up manner, in which herbivores ultimately control the abundance of predators and parasitoids