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2021 ◽  
Vol 136 ◽  
pp. 102587
Author(s):  
Wenjia Cao ◽  
Robert V. Rohli ◽  
Fenglin Han ◽  
Anthony J. Vega ◽  
Nazla Bushra ◽  
...  

2021 ◽  
Vol 100 (sp1) ◽  
Author(s):  
Charles W. Finkl ◽  
Christopher Makowski
Keyword(s):  

2021 ◽  
Vol 100 (sp1) ◽  
Author(s):  
Charles W. Finkl ◽  
Christopher Makowski
Keyword(s):  

2021 ◽  
Vol 100 (sp1) ◽  
Author(s):  
Charles W. Finkl ◽  
Christopher Makowski
Keyword(s):  

2021 ◽  
Vol 100 (sp1) ◽  
Author(s):  
Charles W. Finkl ◽  
Christopher Makowski
Keyword(s):  

2021 ◽  
Vol 100 (sp1) ◽  
Author(s):  
Charles W. Finkl ◽  
Christopher Makowski
Keyword(s):  

2021 ◽  
Vol 100 (sp1) ◽  
Author(s):  
Charles W. Finkl ◽  
Christopher Makowski
Keyword(s):  

The Auk ◽  
2021 ◽  
Author(s):  
Hannah L Clipp ◽  
Jeffrey J Buler ◽  
Jaclyn A Smolinsky ◽  
Kyle G Horton ◽  
Andrew Farnsworth ◽  
...  

Abstract Migrating birds contend with dynamic wind conditions that ultimately influence most aspects of their migration, from broad-scale movements to individual decisions about where to rest and refuel. We used weather surveillance radar data to measure spring stopover distributions of northward migrating birds along the northern Gulf of Mexico coast and found a strong influence of winds over nonadjacent water bodies, the Caribbean Sea and Atlantic Ocean, along with the contiguous Gulf of Mexico. Specifically, we quantified the relative influence of meridional (north–south) and zonal (west–east) wind components over the 3 water bodies on weekly spring stopover densities along western, central, and eastern regions of the northern Gulf of Mexico coast. Winds over the Caribbean Sea and Atlantic Ocean were just as, or more, influential than winds over the Gulf of Mexico, with the highest stopover densities in the central and eastern regions of the coast following the fastest winds from the east over the Caribbean Sea. In contrast, stopover density along the western region of the coast was most influenced by winds over the Gulf of Mexico, with the highest densities following winds from the south. Our results elucidate the important role of wind conditions over multiple water bodies on region-wide stopover distributions and complement tracking data showing Nearctic–Neotropical birds flying nonstop from South America to the northern Gulf of Mexico coast. Smaller-bodied birds may be particularly sensitive to prevailing wind conditions during nonstop flights over water, with probable orientation and energetic consequences that shape subsequent terrestrial stopover distributions. In the future, the changing climate is likely to alter wind conditions associated with migration, so birds that employ nonstop over-water flight strategies may face growing challenges.


Author(s):  
Elizabeth Solleiro-Rebolledo ◽  
Sergey Sedov ◽  
Birgit Terhorst ◽  
Rafael López-Martínez ◽  
Jaime Díaz-Ortega ◽  
...  

Author(s):  
Shima Shamkhali Chenar ◽  
Zhiqiang Deng

Abstract This paper presents a hybrid model for predicting oyster norovirus outbreaks by combining the Artificial Neural Networks (ANNs) and Principal Component Analysis (PCA) methods and using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite remote-sensing data. Specifically, 10 years (2007–2016) of cloud-free MODIS Aqua data for water leaving reflectance and environmental data were extracted from the center of each oyster harvest area. Then, the PCA was utilized to compress the size of the MODIS Aqua data. An ANN model was trained using the first 4 years of the data from 2007 to 2010 and validated using the additional 6 years of independent datasets collected from 2011 to 2016. Results indicated that the hybrid PCA-ANN model was capable of reproducing the 10 years of historical oyster norovirus outbreaks along the Northern Gulf of Mexico coast with a sensitivity of 72.7% and specificity of 99.9%, respectively, demonstrating the efficacy of the hybrid model.


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