Spatiotemporal variation of long-term drought propensity through reliability-resilience-vulnerability based Drought Management Index

2014 ◽  
Vol 50 (10) ◽  
pp. 7662-7676 ◽  
Author(s):  
Kironmala Chanda ◽  
Rajib Maity ◽  
Ashish Sharma ◽  
Rajeshwar Mehrotra
Keyword(s):  
Spatiotemporal Variation ◽  
Drought Management

Drought Management in India: The Long Term Perspective

Disasters ◽  
1992 ◽  
Vol 16 (1) ◽  
pp. 60-65
Author(s):  
KULDEEP MATHUR ◽  
NIRAJA G. JAYAL
Keyword(s):  
Drought Management

scholarly journals Satellite-Derived Estimation of Grassland Aboveground Biomass in the Three-River Headwaters Region of China during 1982–2018

2021 ◽  
Vol 13 (15) ◽  
pp. 2993
Author(s):  
Ruiyang Yu ◽  
Yunjun Yao ◽  
Qiao Wang ◽  
Huawei Wan ◽  
Zijing Xie ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Aboveground Biomass ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Growth Period ◽  
Spatiotemporal Variation ◽  
Coefficient Of Determination ◽  
Gradient Boosting ◽  
Ancillary Data

The long-term estimation of grassland aboveground biomass (AGB) is important for grassland resource management in the Three-River Headwaters Region (TRHR) of China. Due to the lack of reliable grassland AGB datasets since the 1980s, the long-term spatiotemporal variation in grassland AGB in the TRHR remains unclear. In this study, we estimated AGB in the grassland of 209,897 km2 using advanced very high resolution radiometer (AVHRR), MODerate-resolution Imaging Spectroradiometer (MODIS), meteorological, ancillary data during 1982–2018, and 75 AGB ground observations in the growth period of 2009 in the TRHR. To enhance the spatial representativeness of ground observations, we firstly upscaled the grassland AGB using a gradient boosting regression tree (GBRT) model from ground observations to a 1 km spatial resolution via MODIS normalized difference vegetation index (NDVI), meteorological and ancillary data, and the model produced validation results with a coefficient of determination (R2) equal to 0.76, a relative mean square error (RMSE) equal to 88.8 g C m−2, and a bias equal to −1.6 g C m−2 between the ground-observed and MODIS-derived upscaled AGB. Then, we upscaled grassland AGB using the same model from a 1 km to 5 km spatial resolution via AVHRR NDVI and the same data as previously mentioned with the validation accuracy (R2 = 0.74, RMSE = 57.8 g C m−2, and bias = −0.1 g C m−2) between the MODIS-derived reference and AVHRR-derived upscaled AGB. The annual trend of grassland AGB in the TRHR increased by 0.37 g C m−2 (p < 0.05) on average per year during 1982–2018, which was mainly caused by vegetation greening and increased precipitation. This study provided reliable long-term (1982–2018) grassland AGB datasets to monitor the spatiotemporal variation in grassland AGB in the TRHR.

scholarly journals Spatiotemporal Variation in Particulate Organic Carbon Based on Long-Term MODIS Observations in Taihu Lake, China

2017 ◽  
Vol 9 (6) ◽  
pp. 624 ◽  
Author(s):  
Changchun Huang ◽  
Quanliang Jiang ◽  
Ling Yao ◽  
Yunmei Li ◽  
Hao Yang ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Particulate Organic Carbon ◽  
Taihu Lake ◽  
Spatiotemporal Variation ◽  
Carbon Based

Large-scale spatiotemporal variation in calf sex ratio in moose (Alces alces): an effect of density-dependent decrease in maternal condition?

2009 ◽  
Vol 87 (4) ◽  
pp. 346-355 ◽  
Author(s):  
K. Bjørneraas ◽  
E. J. Solberg ◽  
I. Herfindal ◽  
B.-E. Sæther
Keyword(s):  
Sex Ratio ◽  
Large Scale ◽  
Alces Alces ◽  
Recruitment Rate ◽  
Spatiotemporal Variation ◽  
Adult Males ◽  
Maternal Condition ◽  
Density Dependent ◽  
Postnatal Mortality

The harvest of Norwegian moose ( Alces alces (L., 1758)) is directed towards certain sex and age classes to maximize yield in terms of meat or number of animals. Observed side effects are declining numbers of calves per female and proportions of adult males, which may affect other demographic variables. Using long-term data, we examined whether spatiotemporal variation in the calf sex ratio was related to changes in (i) density of harvested moose, (ii) recruitment rate, and (or) (iii) the composition of the adult segment of the population. We found declining proportions of male calves in the autumn harvest over time associated with decreasing recruitment rates. Similarly, the proportion of male calves was lower when density of harvested moose was high. We suggest that the decrease in proportion of male calves was caused by increased prenatal or postnatal mortality rates of males, possibly owing to a density-dependent decline in maternal body condition. Proportion of male calves increased with the proportion of adult males in the population the previous year, indicating that low proportions of adult males may lead to lower male recruitment, particularly at high densities. Further declines in proportions of male calves recruited may be avoided by reducing the population density and changing the demographic composition of the harvest.

scholarly journals Long-Term Spatiotemporal Variation in the Juvenile Fish Assemblage of the Tramandaí River Estuary (29°S) and Adjacent Coast in Southern Brazil

2019 ◽  
Vol 6 ◽  
Author(s):  
João Vieira ◽  
Verónica Román-Robles ◽  
Fábio Rodrigues ◽  
Lisiane Ramos ◽  
Mauricio Lang dos Santos
Keyword(s):  
Fish Assemblage ◽  
Juvenile Fish ◽  
River Estuary ◽  
Spatiotemporal Variation ◽  
Southern Brazil

scholarly journals The interplay of movement and spatiotemporal variation in transmission degrades pandemic control

2020 ◽  
Vol 117 (48) ◽  
pp. 30104-30106 ◽  
Author(s):  
Nicholas Kortessis ◽  
Margaret W. Simon ◽  
Michael Barfield ◽  
Gregory E. Glass ◽  
Burton H. Singer ◽  
...  
Keyword(s):  
Public Health ◽  
Local Control ◽  
Sir Model ◽  
Spatiotemporal Variation ◽  
Mitigation Strategies ◽  
Infectious Individual ◽  
Disease Eradication ◽  
Spatiotemporal Heterogeneity

Successful public health regimes for COVID-19 push below unity long-term regionalRt—the average number of secondary cases caused by an infectious individual. We use a susceptible-infectious-recovered (SIR) model for two coupled populations to make the conceptual point that asynchronous, variable local control, together with movement between populations, elevates long-term regionalRt, and cumulative cases, and may even prevent disease eradication that is otherwise possible. For effective pandemic mitigation strategies, it is critical that models encompass both spatiotemporal heterogeneity in transmission and movement.

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