scholarly journals Temperature‐mediated changes in zooplankton body size: large scale temporal and spatial analysis

Ecography ◽  
2020 ◽  
Vol 43 (4) ◽  
pp. 581-590 ◽  
Author(s):  
Lowri E. Evans ◽  
Andrew G. Hirst ◽  
Pavel Kratina ◽  
Grégory Beaugrand
Keyword(s):  
Body Size ◽  
Spatial Analysis ◽  
Large Scale ◽  
Temporal And Spatial

Continent-wide bimonthly mapping of Antarctic surface meltwater using Google Earth Engine

2021 ◽  
Author(s):  
Peter Tuckett ◽  
Jeremy Ely ◽  
Andrew Sole ◽  
Stephen Livingstone ◽  
James Lea
Keyword(s):  
Remote Sensing ◽  
Spatial Analysis ◽  
Mass Balance ◽  
Large Scale ◽  
Ice Sheet ◽  
Google Earth ◽  
Landsat 8 ◽  
Supraglacial Lakes ◽  
Google Earth Engine ◽  
Temporal And Spatial

<p>Surface meltwater is widespread around the margin of the Antarctic Ice Sheet during the austral summer. This meltwater, typically transported via surface streams and rivers and stored in supraglacial lakes, has the potential to influence ice-sheet mass balance through ice-dynamic and albedo feedbacks. To predict the impact that surface melt will have on mass balance over coming decades, it is important to understand spatial and temporal variability in surface meltwater extent. A variety of methods have been used to detect supraglacial lakes in Antarctica, yet a multi-annual, continent-wide study of Antarctic supraglacial meltwater has yet to be conducted. Cloud-based computational platforms, such as Google Earth Engine (GEE), enable large-scale temporal and spatial analysis of remote sensing datasets at minimal time expense. Here, we implement an automated method for meltwater detection in GEE to generate continent-wide, bimonthly repeat assessments of supraglacial lake extent between 2013 and 2020. We use a band-threshold based approach to delineate surface water from Landsat-8 imagery. Furthermore, our method incorporates a novel technique for quantifying meltwater extent that accounts for variability in optical image coverage and cloud cover, enabling an upper uncertainty bound to be attached to minimum mapped lake areas. We present results from continent-wide mapping, and highlight initial findings that indicate evolution of lakes in Antarctica over the past seven years. This work demonstrates how platforms such as GEE have revolutionized our ability to undertake large-scale projects from remote sensing datasets, allowing for greater temporal and spatial analysis of cryospheric processes than previously possible.</p>

scholarly journals Large-Scale Analysis of the Spatiotemporal Changes of Net Ecosystem Production in Hindu Kush Himalayan Region

2021 ◽  
Vol 13 (6) ◽  
pp. 1180
Author(s):  
Da Guo ◽  
Xiaoning Song ◽  
Ronghai Hu ◽  
Xinming Zhu ◽  
Yazhen Jiang ◽  
...  
Keyword(s):  
Large Scale ◽  
Net Primary Production ◽  
Carbon Sink ◽  
Carbon Sources ◽  
Spatial Dynamics ◽  
Tibet Plateau ◽  
Geostatistical Model ◽  
Hindu Kush ◽  
Temporal And Spatial ◽  
The Difference

The Hindu Kush Himalayan (HKH) region is one of the most ecologically vulnerable regions in the world. Several studies have been conducted on the dynamic changes of grassland in the HKH region, but few have considered grassland net ecosystem productivity (NEP). In this study, we quantitatively analyzed the temporal and spatial changes of NEP magnitude and the influence of climate factors on the HKH region from 2001 to 2018. The NEP magnitude was obtained by calculating the difference between the net primary production (NPP) estimated by the Carnegie–Ames Stanford Approach (CASA) model and the heterotrophic respiration (Rh) estimated by the geostatistical model. The results showed that the grassland ecosystem in the HKH region exhibited weak net carbon uptake with NEP values of 42.03 gC∙m−2∙yr−1, and the total net carbon sequestration was 0.077 Pg C. The distribution of NEP gradually increased from west to east, and in the Qinghai–Tibet Plateau, it gradually increased from northwest to southeast. The grassland carbon sources and sinks differed at different altitudes. The grassland was a carbon sink at 3000–5000 m, while grasslands below 3000 m and above 5000 m were carbon sources. Grassland NEP exhibited the strongest correlation with precipitation, and it had a lagging effect on precipitation. The correlation between NEP and the precipitation of the previous year was stronger than that of the current year. NEP was negatively correlated with temperature but not with solar radiation. The study of the temporal and spatial dynamics of NEP in the HKH region can provide a theoretical basis to help herders balance grazing and forage.

Risk areas for Human Visceral Leishmaniosis 2007–2018: A temporal and spatial analysis in Ceará, Brazil

2021 ◽  
Author(s):  
Kellyn Kessiene de Sousa Cavalcante ◽  
Jarier de Oliveira Moreno ◽  
Reagan Nzundu Boigny ◽  
Francisco Roger Aguiar Cavalcante ◽  
Caroline Mary Gurgel Dias Florêncio ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Risk Areas ◽  
Temporal And Spatial ◽  
Visceral Leishmaniosis

The open access usage advantage: a temporal and spatial analysis

2021 ◽  
Author(s):  
Guangyao Zhang ◽  
Yuqi Wang ◽  
Weixi Xie ◽  
Han Du ◽  
Chunlin Jiang ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Open Access ◽  
Temporal And Spatial

scholarly journals A Potential of microRNAs for High-Content Screening

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Andrius Serva ◽  
Christoph Claas ◽  
Vytaute Starkuviene
Keyword(s):  
Large Scale ◽  
Cellular Processes ◽  
Comprehensive Knowledge ◽  
Functional Models ◽  
Rapid Accumulation ◽  
Health And Disease ◽  
Temporal And Spatial ◽  
And Function ◽  
Functional Analyses ◽  
Immense Potential

In the last years miRNAs have increasingly been recognised as potent posttranscriptional regulators of gene expression. Possibly, miRNAs exert their action on virtually any biological process by simultaneous regulation of numerous genes. The importance of miRNA-based regulation in health and disease has inspired research to investigate diverse aspects of miRNA origin, biogenesis, and function. Despite the recent rapid accumulation of experimental data, and the emergence of functional models, the complexity of miRNA-based regulation is still far from being well understood. In particular, we lack comprehensive knowledge as to which cellular processes are regulated by which miRNAs, and, furthermore, how temporal and spatial interactions of miRNAs to their targets occur. Results from large-scale functional analyses have immense potential to address these questions. In this review, we discuss the latest progress in application of high-content and high-throughput functional analysis for the systematic elucidation of the biological roles of miRNAs.

scholarly journals Fast Playback Framework for Analysis of Ground-Based Doppler Radar Observations Using MapReduce Technology

2016 ◽  
Vol 33 (4) ◽  
pp. 621-634 ◽  
Author(s):  
Jingyin Tang ◽  
Corene J. Matyas
Keyword(s):  
Spatial Analysis ◽  
High Performance ◽  
Large Scale ◽  
Doppler Radar ◽  
Weather Events ◽  
Data Architecture ◽  
Research Grade ◽  
High Performance Computing Cluster ◽  
Time Systems ◽  
Performance Computing

AbstractThe creation of a 3D mosaic is often the first step when using the high-spatial- and temporal-resolution data produced by ground-based radars. Efficient yet accurate methods are needed to mosaic data from dozens of radar to better understand the precipitation processes in synoptic-scale systems such as tropical cyclones. Research-grade radar mosaic methods of analyzing historical weather events should utilize data from both sides of a moving temporal window and process them in a flexible data architecture that is not available in most stand-alone software tools or real-time systems. Thus, these historical analyses require a different strategy for optimizing flexibility and scalability by removing time constraints from the design. This paper presents a MapReduce-based playback framework using Apache Spark’s computational engine to interpolate large volumes of radar reflectivity and velocity data onto 3D grids. Designed as being friendly to use on a high-performance computing cluster, these methods may also be executed on a low-end configured machine. A protocol is designed to enable interoperability with GIS and spatial analysis functions in this framework. Open-source software is utilized to enhance radar usability in the nonspecialist community. Case studies during a tropical cyclone landfall shows this framework’s capability of efficiently creating a large-scale high-resolution 3D radar mosaic with the integration of GIS functions for spatial analysis.

scholarly journals Influence of Stratospheric Sudden Warming on AIRS Midtropospheric CO2

2013 ◽  
Vol 70 (8) ◽  
pp. 2566-2573 ◽  
Author(s):  
Xun Jiang ◽  
Jingqian Wang ◽  
Edward T. Olsen ◽  
Thomas Pagano ◽  
Luke L. Chen ◽  
...  
Keyword(s):  
Large Scale ◽  
Principal Component ◽  
Department Of Energy ◽  
Atmospheric Infrared Sounder ◽  
Stratospheric Sudden Warming ◽  
Chemical Tracers ◽  
Before And After ◽  
Temporal And Spatial ◽  
Global Reanalysis ◽  
Height Data

Abstract Midtropospheric CO2 retrievals from the Atmospheric Infrared Sounder (AIRS) were used to explore the influence of stratospheric sudden warming (SSW) on CO2 in the middle to upper troposphere. To choose the SSW events that had strong coupling between the stratosphere and troposphere, the authors applied a principal component analysis to the NCEP/Department of Energy Global Reanalysis 2 (NCEP-2) geopotential height data at 17 pressure levels. Two events (April 2003 and March 2005) that have strong couplings between the stratosphere and troposphere were chosen to investigate the influence of SSW on AIRS midtropospheric CO2. The authors investigated the temporal and spatial variations of AIRS midtropospheric CO2 before and after the SSW events and found that the midtropospheric CO2 concentrations increased by 2–3 ppm within a few days after the SSW events. These results can be used to better understand how the chemical tracers respond to the large-scale dynamics in the high latitudes.

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