Spatial pattern of invading Dendroctonus micans (Coleoptera: Scolytidae) populations in the United Kingdom

2003 ◽  
Vol 33 (4) ◽  
pp. 712-725 ◽  
Author(s):  
M Gilbert ◽  
N Fielding ◽  
H F Evans ◽  
J -C Grégoire
Keyword(s):  
Spatial Pattern ◽  
Large Scale ◽  
Spatial Regression ◽  
Regional Scale ◽  
Management Control ◽  
Control Measures ◽  
Spatial Gradient ◽  
Dendroctonus Micans ◽  
Ecological Processes ◽  
Using Data

The spatial pattern of Dendroctonus micans (Kug.) attacks on individual spruce stands was analysed at the regional scale in Britain using data collected between 1982 and 1984 by the British Forestry Commission. These survey data reflect at least 10 years of D. micans spread, in the absence of natural enemies and of pest management control measures. A large-scale spatial gradient in the attack density at the stand level was identified and modelled. The large-scale spatial trend model explained 31.3% of the variability, and divided the study area in three separate areas: a zone where the insect was well established and where attack density presented low variations, a transition zone where attack density sharply decreased, and a zone not yet colonized. Attack density was related to site and stand factors, and to landscape neighbourhood in a linear spatial regression model. The factors correlated to attack density and the spatial autocorrelation structure of remaining variability were found to vary according to the zones, reflecting the predominance of different ecological processes occurring in colonized and uncolonized areas. The shape and orientation of the large-scale spatial model was shown to be mostly influenced by the spatial distribution of early attacks.

scholarly journals The burden and dynamics of hospital-acquired SARS-CoV-2 in England

2021 ◽  
Author(s):  
Ben Cooper ◽  
Stephanie Evans ◽  
Yalda Jafari ◽  
Thi Mui Pham ◽  
Cherry Lim ◽  
...  
Keyword(s):  
Large Scale ◽  
Dominant Role ◽  
Control Measures ◽  
Transmission Risk ◽  
Community Interactions ◽  
Acute Hospitals ◽  
Community Transmission ◽  
Using Data ◽  
Hospital Acquired ◽  
Hospital Transmission

Abstract Hospital-based transmission played a dominant role in MERS-CoV and SARS-CoV epidemics but large-scale studies of its role in the SARS-CoV-2 pandemic are lacking. Such transmission risks spreading the virus to the most vulnerable individuals and can have wider-scale impacts through hospital-community interactions. Using data from acute hospitals in England we quantify within-hospital transmission, evaluate likely pathways of spread and factors associated with heightened transmission risk, and explore the wider dynamical consequences. We show that hospital transmission is likely to have been a major contributor to the burden of COVID-19 in England. We estimate that between June 2020 and March 2021 between 95,000 and 167,000 patients acquired SARS-CoV-2 in hospitals with nosocomially-infected patients likely to have been the main sources of transmission to other patients. Increased transmission to patients was associated with hospitals having fewer single rooms and lower heated volume per bed. Moreover, we show that reducing hospital transmission could substantially enhance the efficiency of punctuated lockdown measures in suppressing community transmission. These findings reveal the previously unrecognised scale of hospital transmission, have direct implications for targeting of hospital control measures, and highlight the need to design hospitals better-equipped to limit the transmission of future high consequence pathogens.

scholarly journals Using Model Analysis to Unveil Hidden Patterns in Tropical Forest Structures

2021 ◽  
Vol 9 ◽  
Author(s):  
Nicolas Picard ◽  
Frédéric Mortier ◽  
Pierre Ploton ◽  
Jingjing Liang ◽  
Géraldine Derroire ◽  
...  
Keyword(s):  
Large Scale ◽  
Forest Disturbance ◽  
Null Model ◽  
Basal Area ◽  
Model Analysis ◽  
Tropical Rain Forests ◽  
Model Framework ◽  
Ecological Processes ◽  
Large Trees ◽  
Using Data

When ordinating plots of tropical rain forests using stand-level structural attributes such as biomass, basal area and the number of trees in different size classes, two patterns often emerge: a gradient from poorly to highly stocked plots and high positive correlations between biomass, basal area and the number of large trees. These patterns are inherited from the demographics (growth, mortality and recruitment) and size allometry of trees and tend to obscure other patterns, such as site differences among plots, that would be more informative for inferring ecological processes. Using data from 133 rain forest plots at nine sites for which site differences are known, we aimed to filter out these patterns in forest structural attributes to unveil a hidden pattern. Using a null model framework, we generated the anticipated pattern inherited from individual allometric patterns. We then evaluated deviations between the data (observations) and predictions of the null model. Ordination of the deviations revealed site differences that were not evident in the ordination of observations. These sites differences could be related to different histories of large-scale forest disturbance. By filtering out patterns inherited from individuals, our model analysis provides more information on ecological processes.

scholarly journals The Large-Scale Spatial Patterns of Ecological Networks Between Phytoplankton and Zooplankton in Coastal Marine Ecosystems

2020 ◽  
Author(s):  
Zheng Zhang ◽  
Hongjun Li ◽  
Wenli Shen ◽  
Xiongfeng Du ◽  
Shuzhen Li ◽  
...  
Keyword(s):  
Spatial Pattern ◽  
Spatial Patterns ◽  
Species Interactions ◽  
Large Scale ◽  
Northern Region ◽  
Positive Interactions ◽  
Spatial Gradient ◽  
Turnover Rates ◽  
Spatial Gradients ◽  
The North

Abstract BackgroundThe marine autotrophic phytoplankton is responsible for approximately half of global primary production on Earth, and as the planktonic consumers, the heterotrophic zooplankton could link the phytoplankton and higher trophic level to complete the aquatic Food Web. Despite the interaction between phytoplankton and zooplankton has played important roles in speciation and ecosystem function, little is known about the spatial patterns of their interactions at the continental scale.ResultsHere, we collected 251 seawater samples along 13,000 km of Chinese coastline, and microscopically investigated the spatial gradient patterns of phytoplanktonic and zooplanktonic diversities. In total, 307 phytoplanktonic and 311 zooplanktonic species were visually identified. The distance-decay relationships showed higher turnover rates for zooplankton than phytoplankton, indicating zooplankton had more divergent compositions across larger distances. Furthermore, the zooplankton-phytoplankton interaction networks demonstrated more complex and numerous connections along the southern coast than in the north, suggesting the interactions between these two major planktonic groups had a geographic spatial pattern. The types of planktonic interactions changed along the latitudinal gradient, with positive interactions dominant in northern and middle regions, while the percentage of positive and negative interactions were approximately equal in the southern latitudinal region. Additionally, some particular association between zooplanktonic and phytoplanktonic groups were found to be localized in specific regions, such as autotrophic C. lorenzianus was only associated with heterotrophic Copepoda in northern region, and C. oculus-iridis was only associated with Copepoda and Chaetognatha in the middle (ECS) and southern (SCS) respectively.ConclusionsWe demonstrate here that not only the planktonic biodiversity and community structure exhibited a clear spatial pattern, but also the interaction between phytoplankton and zooplankton also changed with spatial variation. Our results provide a valuable ecological perspective to the biogeography patterns of coastal plankton along the large-scale spatial gradients, and have important implications for understanding how complex planktonic species interactions changed with location variation.

scholarly journals A model to estimate seabird field metabolic rates

2018 ◽  
Vol 14 (6) ◽  
pp. 20180190 ◽  
Author(s):  
Ruth E. Dunn ◽  
Craig R. White ◽  
Jonathan A. Green
Keyword(s):  
Breeding Season ◽  
Brood Size ◽  
Large Scale ◽  
Ecological Processes ◽  
Marine Systems ◽  
Field Metabolic Rates ◽  
Using Data ◽  
Free Ranging ◽  
Average Brood

For free-ranging animals, field metabolic rate (FMR) is the sum of their energy expenditure over a specified period. This quantity is a key component of ecological processes at every biological level. We applied a phylogenetically informed meta-analytical approach to identify the large-scale determinants of FMR in seabirds during the breeding season. Using data from 64 studies of energetics in 47 species, we created a model to estimate FMR for any seabird population. We found that FMR was positively influenced by body mass and colony latitude and that it increased throughout the breeding season from incubation to brood to crèche. FMR was not impacted by colony-relative predation pressure or species average brood size. Based on this model, we present an app through which users can generate estimates of FMR for any population of breeding seabird. We encourage the use of this app to complement behavioural studies and increase understanding of how energetic demands influence the role of seabirds as driving components of marine systems.

Assessment of quality of life in patients with the effects of transient ischemic stroke

2016 ◽  
pp. 37-39
Author(s):  
A. Babirad
Keyword(s):  
Quality Of Life ◽  
Ischemic Stroke ◽  
Large Scale ◽  
Cerebrovascular Diseases ◽  
Control Measures ◽  
Sociological Research ◽  
Cerebrovascular Events ◽  
Sf 36 ◽  
Angioplasty And Stenting

Cerebrovascular diseases are a problem of the world today, and according to the forecast, the problem of the near future arises. The main risk factors for the development of ischemic disorders of the cerebral circulation include oblique and aging, arterial hypertension, smoking, diabetes mellitus and heart disease. An effective strategy for the prevention of cerebrovascular events is based on the implementation of large-scale risk control measures, including the use of antiagregant and anticoagulant therapy, invasive interventions such as atheromectomy, angioplasty and stenting. In this connection, the efforts of neurologists, cardiologists, angiosurgery, endocrinologists and other specialists are the basis for achieving an acceptable clinical outcome. A review of the SF-36 method for assessing the quality of life in patients with the effects of transient ischemic stroke is presented. The assessment of quality of life is recognized in world medical practice and research, an indicator that is also used to assess the quality of the health system and in general sociological research.

Long-Term (15 Years) Results of NPS Controls in an Agricultural Watershed upon a Receiving Lake's Water Quality

1993 ◽  
Vol 28 (3-5) ◽  
pp. 441-449 ◽  
Author(s):  
Paul J. Garrison ◽  
Timothy R. Asplund
Keyword(s):  
Water Quality ◽  
Structural Changes ◽  
Soil Phosphorus ◽  
Water Clarity ◽  
Management Control ◽  
Agricultural Watershed ◽  
Control Measures ◽  
Phosphorus Loading ◽  
Phosphorus Concentration ◽  
White Clay

Nonpoint source controls were installed in a 1215 ha agricultural watershed in northeastern Wisconsin in the late 1970. Changes were made in handling of animal wastes and cropping practices to reduce runoff of sediment and nutrients. Modelling results predicted a reduction in phosphorus runoff of 30 percent. The water quality of White Clay Lake has worsened since the installation of NPS controls. The lake's phosphorus concentration has increased from a mean of 29 µg L−1 in the late 1970s to 44 µg L−1 in recent years. Water clarity has declined from 2.7 to 2.1 m and the mean summer chlorophyll levels have increased from 9 to 13 µg L−1 with peak values exceeding 40 µg L−1. Increased phosphorus loading is not the result of elevated precipitation but instead the failure of the control measures to sufficiently reduce P loading. Most of the effort was placed on structural changes while most of the P loading comes from cropland runoff. Further, soil phosphorus concentrations have increased because of artificial fertilizers and manure spreading. The White Clay Lake experience is discouraging since the majority of the polluters in this watershed utilized some NPS control practices, including 76 percent of the farms which installed waste management control facilities.

Student Perceptions of Community: A Different Perspective

NASPA Journal ◽  
1998 ◽  
Vol 35 (4) ◽  
Author(s):  
Jackie Clark ◽  
Joan Hirt
Keyword(s):  
Student Perceptions ◽  
Large Scale ◽  
Research University ◽  
Small Scale ◽  
Social Environments ◽  
Common Assumption ◽  
Small Communities ◽  
Public Research University ◽  
The Common ◽  
Using Data

The creation of small communities has been proposed as a way of enhancing the educational experience of students at large institutions. Using data from a survey of students living in large and small residences at a public research university, this study does not support the common assumption that small-scale social environments are more conducive to positive community life than large-scale social environments.

scholarly journals Influence of the North Atlantic oscillation on the atmospheric levels of benzo[a]pyrene over Europe

2021 ◽  
Author(s):  
Pedro Jiménez-Guerrero ◽  
Nuno Ratola
Keyword(s):  
Spatial Pattern ◽  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Transport Model ◽  
Regional Scale ◽  
The South ◽  
Climatic Fluctuations ◽  
The North ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

AbstractThe atmospheric concentration of persistent organic pollutants (and of polycyclic aromatic hydrocarbons, PAHs, in particular) is closely related to climate change and climatic fluctuations, which are likely to influence contaminant’s transport pathways and transfer processes. Predicting how climate variability alters PAHs concentrations in the atmosphere still poses an exceptional challenge. In this sense, the main objective of this contribution is to assess the relationship between the North Atlantic Oscillation (NAO) index and the mean concentration of benzo[a]pyrene (BaP, the most studied PAH congener) in a domain covering Europe, with an emphasis on the effect of regional-scale processes. A numerical simulation for a present climate period of 30 years was performed using a regional chemistry transport model with a 25 km spatial resolution (horizontal), higher than those commonly applied. The results show an important seasonal behaviour, with a remarkable spatial pattern of difference between the north and the south of the domain. In winter, higher BaP ground levels are found during the NAO+ phase for the Mediterranean basin, while the spatial pattern of this feature (higher BaP levels during NAO+ phases) moves northwards in summer. These results show deviations up to and sometimes over 100% in the BaP mean concentrations, but statistically significant signals (p<0.1) of lower changes (20–40% variations in the signal) are found for the north of the domain in winter and for the south in summer.

scholarly journals Modeling Fused Filament Fabrication using Artificial Neural Networks

2021 ◽  
Author(s):  
Paul Oehlmann ◽  
Paul Osswald ◽  
Juan Camilo Blanco ◽  
Martin Friedrich ◽  
Dominik Rietzel ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Cost Effective ◽  
Print Quality ◽  
Ann Model ◽  
Production Environment ◽  
Fused Filament Fabrication ◽  
Artificial Neural ◽  
Using Data ◽  
Artificial Neural Network Ann

AbstractWith industries pushing towards digitalized production, adaption to expectations and increasing requirements for modern applications, has brought additive manufacturing (AM) to the forefront of Industry 4.0. In fact, AM is a main accelerator for digital production with its possibilities in structural design, such as topology optimization, production flexibility, customization, product development, to name a few. Fused Filament Fabrication (FFF) is a widespread and practical tool for rapid prototyping that also demonstrates the importance of AM technologies through its accessibility to the general public by creating cost effective desktop solutions. An increasing integration of systems in an intelligent production environment also enables the generation of large-scale data to be used for process monitoring and process control. Deep learning as a form of artificial intelligence (AI) and more specifically, a method of machine learning (ML) is ideal for handling big data. This study uses a trained artificial neural network (ANN) model as a digital shadow to predict the force within the nozzle of an FFF printer using filament speed and nozzle temperatures as input data. After the ANN model was tested using data from a theoretical model it was implemented to predict the behavior using real-time printer data. For this purpose, an FFF printer was equipped with sensors that collect real time printer data during the printing process. The ANN model reflected the kinematics of melting and flow predicted by models currently available for various speeds of printing. The model allows for a deeper understanding of the influencing process parameters which ultimately results in the determination of the optimum combination of process speed and print quality.

scholarly journals Nebula: ultra-efficient mapping-free structural variant genotyper

2021 ◽  
Author(s):  
Parsoa Khorsand ◽  
Fereydoun Hormozdiari
Keyword(s):  
Large Scale ◽  
Structural Variants ◽  
Sequencing Technologies ◽  
Generic Framework ◽  
Common Genetic Variants ◽  
Order Of Magnitude ◽  
Complex Events ◽  
Comparable Accuracy ◽  
Using Data ◽  
Computational Resources

Abstract Large scale catalogs of common genetic variants (including indels and structural variants) are being created using data from second and third generation whole-genome sequencing technologies. However, the genotyping of these variants in newly sequenced samples is a nontrivial task that requires extensive computational resources. Furthermore, current approaches are mostly limited to only specific types of variants and are generally prone to various errors and ambiguities when genotyping complex events. We are proposing an ultra-efficient approach for genotyping any type of structural variation that is not limited by the shortcomings and complexities of current mapping-based approaches. Our method Nebula utilizes the changes in the count of k-mers to predict the genotype of structural variants. We have shown that not only Nebula is an order of magnitude faster than mapping based approaches for genotyping structural variants, but also has comparable accuracy to state-of-the-art approaches. Furthermore, Nebula is a generic framework not limited to any specific type of event. Nebula is publicly available at https://github.com/Parsoa/Nebula.

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