scholarly journals The Decrease in Lake Numbers and Areas in Central Asia Investigated Using a Landsat-Derived Water Dataset

2021 ◽  
Vol 13 (5) ◽  
pp. 1032
Author(s):  
Xianghong Che ◽  
Min Feng ◽  
Qing Sun ◽  
Joseph O. Sexton ◽  
Saurabh Channan ◽  
...  
Keyword(s):  
Central Asia ◽  
Temporal Dynamics ◽  
Qaidam Basin ◽  
Anthropogenic Activities ◽  
Water Area ◽  
Aral Sea ◽  
Lake Area ◽  
Human Welfare ◽  
Ecological Zones ◽  
Northern Tibetan Plateau

Although Central Asia has a strong continental climate with a constant moisture deficit and low relative humidity, it is covered by thousands of lakes that are critical to the sustainability of ecosystems and human welfare in the region. Vulnerability to climate change and anthropogenic activities have contributed to dramatic inter-annual and seasonal changes of the lakes. In this study, we explored the high spatio–temporal dynamics of the lakes of Central Asia using the terraPulse™ monthly Landsat-derived surface water extent dataset from 2000 to 2015 and the HydroLAKES dataset. The results identified 9493 lakes and significant linear decreasing trends were identified for both the number (rate: −85 lakes/year, R2: 0.69) and area (rate: −1314.1 km2/year, R2: 0.84) of the lakes in Central Asia between 2000 and 2015. The decrease rate in lake area accounted for 1.41% of the total lake area. About 75% of the investigated lakes (7142 lakes), mainly located in the Kazakh steppe (especially in the north) and the Badghyz and Karabil semi-desert terrestrial ecological zones, experienced a decrease in the water area. Lakes with increasing water area were mainly distributed in the Northern Tibetan Plateau–Kunlun Mountains alpine desert and Qaidam Basin semi-desert zones in the east-south corner of Central Asia. The possible driving factors of lake decreases in Central Asia were explored for the Aral Sea and Tengiz Lake on yearly and monthly time scales. The Aral Sea showed the greatest decrease in the summer months because of increased evaporation and massive irrigation, while the largest decrease for Tengiz Lake was observed in early spring and was linked to decreasing snowmelt.

scholarly journals UNDERGROUND RUNOFF AS THE MAIN GEOHAZARDS IN THE MOUNTAINOUS REGIONS OF THE POST-SOVIET PART OF CENTRAL ASIA

2021 ◽  
Vol 13 (2) ◽  
pp. 248-253
Author(s):  
Evgeny LAGUTIN ◽  
◽  
Аlexey TEREKHOV ◽  
Sheishenaly USUPAEV ◽  
◽  
...  
Keyword(s):  
Water Resources ◽  
Central Asia ◽  
Mutual Influence ◽  
Anthropogenic Activities ◽  
The State ◽  
Aral Sea ◽  
Mountainous Regions ◽  
Central Asian ◽  
East Kazakhstan ◽  
State Of The Environment

The purpose of this article is to present the results of a study of the mutual influence of groundwater flow and results of human activities in the upland and lowland areas of Central Asia. The need for research was determined by the serious consequences of anthropogenic activities, which in recent years have required the inclusion of these tasks in the category of national security problems of the Central Asian States. Such tasks include, first of all, the extensive use of existing water resources in the Syrdarya and Amu Darya river basins, which was reflected in the well – known tragedy of the Aral Sea, the pollution of water resources during peaceful nuclear weapons tests, which negatively affected the state of the environment in East Kazakhstan, in addition-in the irrational use of water resources, including groundwater, on irrigated lands in Central Asia. These and other factors have determined the need to develop capabilities for predicting the state of both the aquatic environment and the influencing factors of human activity themselves. The solution of the problem presented in this article is based on the new fundamental scientific concepts developed by the authors, their own and attracted material of the results and is expressed in the proposed specific solutions.

scholarly journals Landsat-Based Estimation of Seasonal Water Cover and Change in Arid and Semi-Arid Central Asia (2000–2015)

2019 ◽  
Vol 11 (11) ◽  
pp. 1323 ◽  
Author(s):  
Xianghong Che ◽  
Min Feng ◽  
Joe Sexton ◽  
Saurabh Channan ◽  
Qing Sun ◽  
...  
Keyword(s):  
Surface Water ◽  
Central Asia ◽  
Learning Algorithm ◽  
Water Area ◽  
Water Bodies ◽  
Ecological Zones ◽  
Hydrological Variability ◽  
Global Mapping ◽  
Water Cover ◽  
Semi Arid

Surface water is of great importance to ecosystems and economies. Crucial to understanding hydrological variability and its relationships to human activities at large scales, open-access satellite datasets and big-data computational methods are now enabling the global mapping of the distribution and changes of inland water over time. A machine-learning algorithm, previously used only to map water at single points in time, was applied over 16 years of the USGS Landsat archive to detect and map surface water over central Asia from 2000 to 2015 at a 30-m, monthly resolution. The resulting dataset had an overall classification accuracy of 99.59% (±0.32% standard error), 98.24% (±1.02%) user’s accuracy, and 87.12% (±3.21%) producer’s accuracy for water class. This study describes the temporal extension of the algorithm and the application of the dataset to present patterns of regional surface water cover and change. The findings indicate that smaller water bodies are dramatically changing in two specific ecological zones: the Kazakh Steppe and the Tian Shan Montane Steppe and Meadows. Both the maximum and minimum extent of water bodies have decreased over the 16-year period, but the rate of decrease of the maxima was double that of the minima. Coverage decreased in each month from April to October, and a significant decrease in water area was found in April and May. These results indicate that the dataset can provide insights into the behavior of surface water across central Asia through time, and that the method can be further developed for regional and global applications.

scholarly journals Stool and ruminal microbiome components associated with methane emission and feed efficiency in Nelore beef cattle.

2021 ◽  
Author(s):  
Bruno G.N. Andrade ◽  
Haithem Afli ◽  
Flavia A. Bressani ◽  
Rafael R. C. Cuadrat ◽  
Priscila S. N. de Oliveira ◽  
...  
Keyword(s):  
Methane Emission ◽  
Feed Efficiency ◽  
Linear Models ◽  
Anthropogenic Activities ◽  
Mixed Linear Models ◽  
Human Welfare ◽  
Feed Composition ◽  
Fecal Microbiome ◽  
Treatment Groups ◽  
The Impact

Abstract Background: The impact of extreme changes in weather patterns in the economy and human welfare are some of the biggest challenges that our civilization is facing. From the anthropogenic activities that contribute to climate change, reducing the impact of farming activities is a priority, since it is responsible for up to 18% of greenhouse gases linked to such activities. To this end, we tested if the ruminal and fecal microbiome components of 52 Brazilian Nelore bulls, belonging to two treatment groups based on the feed intervention, conventional and by-products based diet, could be used in the future as biomarkers for methane emission and feed efficiency in bovine.Results: We identified a total of 5,693 Amplicon Sequence Variants (ASVs) in the Nelore bulls microbiomes. Differential abundance (DA) analysis with the ANCOM approach identified 30 bacterial and 15 archaea ASVs as DA among treatment groups. Association analysis using Maaslin2 and Mixed Linear Models indicated that bacterial ASVs are linked to the residual methane emission (RCH4) and Residual Feed Intake (RFI) phenotypes, contributing to the host’s phenotypic variation, suggesting their potential as targets for interventions and/or biomarkers.Conclusion: Feed composition induced significant differences in abundance and richness of ruminal and fecal microbial populations. The diet based on industrial byproducts applied to our treatment groups influenced the microbiome diversity of bacteria and archaea, but not of protozoa. Different ASVs were associated with RCH4 emission and RFI in both ruminal and fecal microbiomes. While ruminal ASVs are expected to directly influence RCH4 emission and RFI, the relation of fecal taxa, such as Alistipes and Rikenellaceae (gut group RC9), with these traits might also be associated with host health due to their link to anti-inflammatory compounds, and these have the potential to be used as accessible biomarkers for these complex phenotypes.

scholarly journals Dinâmica Espaço-Temporal da Paisagem Semiárida no Município de Apodi/RN e seus Condicionantes Socioeconômicos e Ambientais

2021 ◽  
Vol 14 (4) ◽  
pp. 2446-2464
Author(s):  
Murianny Katamara Silva de Oliveira ◽  
Eveline Almeida Ferreira ◽  
Nadjacleia Vilar Almeida ◽  
Eulene Francisco da Silva ◽  
Aline Almeida Vasconcelos
Keyword(s):  
Vegetation Cover ◽  
Structural Changes ◽  
Temporal Dynamics ◽  
Agrarian Reform ◽  
Anthropogenic Activities ◽  
Standardized Precipitation Index ◽  
Environmental Drivers ◽  
Precipitation Data ◽  
Dense Vegetation ◽  
Spatio Temporal

Apodi, like many municipalities in the Northeast, underwent structural changes conducted by two main drivers: alternation of socioeconomic models and seasonal and prolonged periods of drought. Among the socioeconomic models, Apodi passed by large landowners, agrarian reform, expropriation of land for irrigated perimeters and installation of agribusiness companies. These conditions negatively impacted the vegetation cover, degrading the landscape and threatening the Lajedo de Soledade Archaeological Site (SALS) located in the middle of this landscape, an important cultural and environmental patrimony. In this context, the objective of this study was to analyze the spatio-temporal changes in the landscape around SALS and to infer about the influence of socioeconomic and environmental drivers. For this, a survey of the region's history, precipitation data, agricultural production of the main crops, and eight images captured by the TM and OLI sensors of the LANDSAT 5 and 8 satellites, between 1984 and 2018, were used. Precipitation data was modeled using the Standardized Precipitation Index (SPI). The images were classified using the SCP plugin (QGIS) and the quality was assessed using the Kappa Index. It was observed that there were three prolonged and extreme droughts events in the region: late 1980s and 1990s and between 2013 and 2017. The classification of the images indicated periods of dense vegetation reductions and exposed soil expansions, in the period of decay of cotton culture, and the reversal of these patterns after agrarian reform, with the establishment of family farming on an agroecological basis. This pattern was again reversed, with the lowest proportion of dense vegetation observed (5%) and and higher proportion of exposed soil (45%) observed in this landscape, during the period of installation of the irrigated perimeter for agribusiness. Thus, it was possible to infer that the alternation of socioeconomic models conditioned the spatio-temporal dynamics of the vegetation cover and was responsible for the environmental degradation conditions surrounding the SALS, these patterns being aggravated by the recurrence of periods of extreme and prolonged drought. During these periods, SALS was probably more vulnerable to the direct and indirect effects of anthropogenic activities common in this landscape.

Lake ice phenology changes in the northern hemisphere

2021 ◽  
Author(s):  
Yubao Qiu ◽  
Xingxing Wang ◽  
Matti Leppäranta ◽  
Bin Cheng ◽  
Yixiao Zhang
Keyword(s):  
Remote Sensing ◽  
North America ◽  
Northern Hemisphere ◽  
Ice Cover ◽  
Passive Microwave ◽  
Lake Area ◽  
Lake Ice ◽  
Northern Tibetan Plateau ◽  
Break Up ◽  
Ice Phenology

<p>Lake-ice phenology is an essential indicator of climate change impact for different regions (Livingstone, 1997; Duguay, 2010), which helps understand the regional characters of synchrony and asynchrony. The observation of lake ice phenology includes ground observation and remote sensing inversion. Although some lakes have been observed for hundreds of years, due to the limitations of the observation station and the experience of the observers, ground observations cannot obtain the lake ice phenology of the entire lake. Remote sensing has been used for the past 40 years, in particular, has provided data covering the high mountain and high latitude regions, where the environment is harsh and ground observations are lacking. Remote sensing also provides a unified data source and monitoring standard, and the possibility of monitoring changes in lake ice in different regions and making comparisons between them. The existing remote sensing retrieval products mainly cover North America and Europe, and data for Eurasia is lacking (Crétaux et al., 2020).</p><p>Based on the passive microwave, the lake ice phenology of 522 lakes in the northern hemisphere during 1978-2020 was obtained, including Freeze-Up Start (FUS), Freeze-Up End (FUE), Break-Up Start (BUS), Break-Up End (BUE), and Ice Cover Duration (ICD). The ICD is the duration from the FUS to the BUE, which can directly reflect the ice cover condition. At latitudes north of 60°N, the average of ICD is approximately 8-9 months in North America and 5-6 months in Eurasia. Limited by the spatial resolution of the passive microwave, lake ice monitoring is mainly in Northern Europe. Therefore, the average of ICD over Eurasia is shorter, while the ICD is more than 6 months for most lakes in Russia. After 2000, the ICD has shown a shrinking trend, except northeastern North America (southeast of the Hudson Bay) and the northern Tibetan Plateau. The reasons for the extension of ice cover duration need to be analyzed with parameters, such as temperature, the lake area, and lake depth, in the two regions.</p>

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