Socio-environmental drivers of establishment of Lymantria dispar, a nonnative forest pest, in the United States

2021 ◽  
Author(s):  
Rebecca Epanchin-Niell ◽  
Jieyi Lu ◽  
Alexandra Thompson ◽  
Patrick C. Tobin ◽  
David R. Gray ◽  
...  
Keyword(s):  
United States ◽  
Lymantria Dispar ◽  
The United States ◽  
Environmental Drivers ◽  
Forest Pest

Molecular comparisons of alphabaculovirus-based products: Gypchek with Disparvirus (Lymantria dispar) and TM BioControl-1 with Virtuss (Orgyia pseudotsugata)

2010 ◽  
Vol 142 (6) ◽  
pp. 546-556 ◽  
Author(s):  
Jianhua Zhang ◽  
Renée Lapointe ◽  
David Thumbi ◽  
Benoit Morin ◽  
Christopher J. Lucarotti
Keyword(s):  
United States ◽  
Lymantria Dispar ◽  
Genomic Dna ◽  
Phylogenetic Analyses ◽  
Rflp Analysis ◽  
The United States ◽  
Amino Acid Sequences ◽  
Open Reading Frames ◽  
Chain Reactions ◽  
Orgyia Pseudotsugata

AbstractGypsy moth, Lymantria dispar (L.) (Lepidoptera: Lymantriidae), multicapsid nucleopolyhedrovirus (LdMNPV) has been registered as a microbial pest-control product in the United States (Gypchek®) and Canada (Disparvirus®). Similarly, Douglas-fir tussock moth, Orgyia pseudotsugata (McDunnough) (Lepidoptera: Lymantriidae), multicapsid nucleopolyhedrovirus (OpMNPV) is registered in the United States and Canada as TM BioControl-1® and a product derived from TM BioControl-1 (Virtuss®) is also registered in Canada. To determine changes that may have occurred in these products over time, we compared DNA from Gypchek with Disparvirus and DNA from TM BioControl-1 with Virtuss using restriction fragment length polymorphism (RFLP) analysis. Gypchek and Disparvirus showed the same RFLP banding patterns when viral genomic DNA was digested with BamH I, EcoR V, and Hind III and only a single band difference at approximately 1.6 kilobase (kb) when digested with Bgl II. TM BioControl-1 and Virtuss showed no differences in genomic DNA when digested with Bgl II, Sam I or Hind III. Twelve viral open reading frames (ORFs) were amplified from Gypchek and Disparvirus and nine from TM BioControl-1 and Virtuss by polymerase chain reactions (PCR). The amplified ORFs ranged from highly conserved (polyhedrin) to least conserved (vp91 capsid associated protein). The products were sequenced and the deduced protein products compared. Amino acid sequences deduced from the sequenced PCR products indicated that 8 of the 12 proteins were identical in the two LdMNPV products. The four proteins showing minor sequence variations were DNA polymerase, LEF-8, P74 envelope protein, and VP 91 capsid associated protein. No differences were detected in the protein products deduced from the nine sequenced ORFs from TM BioControl-1 and Virtuss. Comparative RFLP and protein phylogenetic analyses of Gypchek with Disparvirus and TM BioControl-1 with Virtuss revealed little difference between the respective LdMNPV and OpMNPV populations that make up these product pairs.

scholarly journals Predicting wildfire burned area in South Central US using integrated machine learning techniques

2019 ◽  
Author(s):  
Sing-Chun Wang ◽  
Yuxuan Wang
Keyword(s):  
United States ◽  
Machine Learning ◽  
The United States ◽  
Machine Learning Algorithms ◽  
Machine Learning Techniques ◽  
Environmental Drivers ◽  
Fire Season ◽  
Burned Area ◽  
Environmental Controls ◽  
South Central

Abstract. Occurrences of devastating wildfires have been on the rise in the United States for the past decades. While the environmental controls, including weather, climate, and fuels, are known to play important roles in controlling wildfires, the interrelationships between fires and the environmental controls are highly complex and may not be well represented by traditional parametric regressions. Here we develop a model integrating multiple machine learning algorithms to predict gridded monthly wildfire burned area during 2002–2015 over the South Central United States and identify the relative importance of the environmental drivers on the burned area for both the winter-spring and summer fire seasons of that region. The developed model is able to alleviate the issue of unevenly-distributed burned area data and achieve a cross-validation (CV) R2 value of 0.42 and 0.40 for the two fire seasons. For the total burned area over the study domain, the model can explain 50 % and 79 % of interannual total burned area for the winter-spring and summer fire season, respectively. The prediction model ranks relative humidity (RH) anomalies and preceding months’ drought severity as the top two most important predictors on the gridded burned area for both fire seasons. Sensitivity experiments with the model show that the effect of climate change represented by a group of climate-anomaly variables contributes the most to the burned area for both fire seasons. Antecedent fuel amount and conditions are found to outweigh weather effects for the burned area in the winter-spring fire season, while the current-month fire weather is more important for the summer fire season likely due to the controlling effect of weather on fuel moisture in this season. This developed model allows us to predict gridded burned area and to access specific fire management strategies for different fire mechanisms in the two seasons.

scholarly journals Environmental Drivers of the Spatiotemporal Dynamics of Respiratory Syncytial Virus in the United States

2015 ◽  
Vol 11 (1) ◽  
pp. e1004591 ◽  
Author(s):  
Virginia E. Pitzer ◽  
Cécile Viboud ◽  
Wladimir J. Alonso ◽  
Tanya Wilcox ◽  
C. Jessica Metcalf ◽  
...  
Keyword(s):  
United States ◽  
Respiratory Syncytial Virus ◽  
The United States ◽  
Spatiotemporal Dynamics ◽  
Environmental Drivers ◽  
Syncytial Virus

scholarly journals Response of crop yield to different time-scales of drought in the United States: Spatio-temporal patterns and climatic and environmental drivers

2019 ◽  
Vol 264 ◽  
pp. 40-55 ◽  
Author(s):  
Marina Peña-Gallardo ◽  
Sergio M. Vicente-Serrano ◽  
Steven Quiring ◽  
Marc Svoboda ◽  
Jamie Hannaford ◽  
...  
Keyword(s):  
United States ◽  
Time Scales ◽  
Crop Yield ◽  
Temporal Patterns ◽  
The United States ◽  
Environmental Drivers ◽  
Spatio Temporal ◽  
Different Time Scales

scholarly journals Quantifying the effects of environmental factors on wildfire burned area in the south central US using integrated machine learning techniques

2020 ◽  
Vol 20 (18) ◽  
pp. 11065-11087
Author(s):  
Sally S.-C. Wang ◽  
Yuxuan Wang
Keyword(s):  
United States ◽  
Machine Learning ◽  
The United States ◽  
Environmental Drivers ◽  
Fire Season ◽  
Spatial And Temporal Variation ◽  
Burned Area ◽  
The South ◽  
Environmental Controls ◽  
South Central

Abstract. Occurrences of devastating wildfires have been increasing in the United States for the past decades. While some environmental controls, including weather, climate, and fuels, are known to play important roles in controlling wildfires, the interrelationships between these factors and wildfires are highly complex and may not be well represented by traditional parametric regressions. Here we develop a model consisting of multiple machine learning algorithms to predict 0.5∘×0.5∘ gridded monthly wildfire burned area over the south central United States during 2002–2015 and then use this model to identify the relative importance of the environmental drivers on the burned area for both the winter–spring and summer fire seasons of that region. The developed model alleviates the issue of unevenly distributed burned-area data, predicts burned grids with area under the curve (AUC) of 0.82 and 0.83 for the two seasons, and achieves temporal correlations larger than 0.5 for more than 70 % of the grids and spatial correlations larger than 0.5 (p<0.01) for more than 60 % of the months. For the total burned area over the study domain, the model can explain 50 % and 79 % of the observed interannual variability for the winter–spring and summer fire season, respectively. Variable importance measures indicate that relative humidity (RH) anomalies and preceding months' drought severity are the two most important predictor variables controlling the spatial and temporal variation in gridded burned area for both fire seasons. The model represents the effect of climate variability by climate-anomaly variables, and these variables are found to contribute the most to the magnitude of the total burned area across the whole domain for both fire seasons. In addition, antecedent fuel amounts and conditions are found to outweigh the weather effects on the amount of total burned area in the winter–spring fire season, while fire weather is more important for the summer fire season likely due to relatively sufficient vegetation in this season.

Correlative microscopy in distrubuted (client/server) computing environments: tools for catalyzing the rapid dissemination of information about the cell biology of the human prostate

1995 ◽  
Vol 53 ◽  
pp. 682-683
Author(s):  
A. Hakam ◽  
J.T. Gau ◽  
M.L. Grove ◽  
B.A. Evans ◽  
M. Shuman ◽  
...  
Keyword(s):  
United States ◽  
Cell Biology ◽  
Tissue Bank ◽  
The United States ◽  
Prostate Adenocarcinoma ◽  
Correlative Microscopy ◽  
Client Server ◽  
Critical Elements ◽  
Transplant Organ

Prostate adenocarcinoma is the most common malignant tumor of men in the United States and is the third leading cause of death in men. Despite attempts at early detection, there will be 244,000 new cases and 44,000 deaths from the disease in the United States in 1995. Therapeutic progress against this disease is hindered by an incomplete understanding of prostate epithelial cell biology, the availability of human tissues for in vitro experimentation, slow dissemination of information between prostate cancer research teams and the increasing pressure to “ stretch” research dollars at the same time staff reductions are occurring.To meet these challenges, we have used the correlative microscopy (CM) and client/server (C/S) computing to increase productivity while decreasing costs. Critical elements of our program are as follows:1) Establishing the Western Pennsylvania Genitourinary (GU) Tissue Bank which includes >100 prostates from patients with prostate adenocarcinoma as well as >20 normal prostates from transplant organ donors.

Digital image acquisition, processing, and analysis in a polymer microscopy laboratory

1994 ◽  
Vol 52 ◽  
pp. 454-455
Author(s):  
Vinod K. Berry ◽  
Xiao Zhang
Keyword(s):  
United States ◽  
Image Analysis ◽  
Digital Image ◽  
Image Acquisition ◽  
Image Transmission ◽  
The United States ◽  
Quantitative Image Analysis ◽  
Quantitative Image

In recent years it became apparent that we needed to improve productivity and efficiency in the Microscopy Laboratories in GE Plastics. It was realized that digital image acquisition, archiving, processing, analysis, and transmission over a network would be the best way to achieve this goal. Also, the capabilities of quantitative image analysis, image transmission etc. available with this approach would help us to increase our efficiency. Although the advantages of digital image acquisition, processing, archiving, etc. have been described and are being practiced in many SEM, laboratories, they have not been generally applied in microscopy laboratories (TEM, Optical, SEM and others) and impact on increased productivity has not been yet exploited as well.In order to attain our objective we have acquired a SEMICAPS imaging workstation for each of the GE Plastic sites in the United States. We have integrated the workstation with the microscopes and their peripherals as shown in Figure 1.

Silence of the Land: On the Historical Irrelevance of Territory to Congressional Districting and Political Representation in the United States

2001 ◽  
Vol 15 (01) ◽  
pp. 53-87 ◽  
Author(s):  
Andrew Rehfeld
Keyword(s):  
United States ◽  
House Of Representatives ◽  
Political Representation ◽  
The United States ◽  
Representative Government ◽  
Congressional District ◽  
Congressional Districts ◽  
Communities Of Interest

Every ten years, the United States “constructs” itself politically. On a decennial basis, U.S. Congressional districts are quite literally drawn, physically constructing political representation in the House of Representatives on the basis of where one lives. Why does the United States do it this way? What justifies domicile as the sole criteria of constituency construction? These are the questions raised in this article. Contrary to many contemporary understandings of representation at the founding, I argue that there were no principled reasons for using domicile as the method of organizing for political representation. Even in 1787, the Congressional district was expected to be far too large to map onto existing communities of interest. Instead, territory should be understood as forming a habit of mind for the founders, even while it was necessary to achieve other democratic aims of representative government.

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