scholarly journals Predicting the Spread of Purple Loosestrife (Lythrum salicaria) in the Prairies

2013 ◽  
Vol 126 (4) ◽  
pp. 306 ◽  
Author(s):  
Cory J. Lindgren ◽  
David Walker
Keyword(s):  
Potential Distribution ◽  
Invasive Plant ◽  
Lythrum Salicaria ◽  
Training Data ◽  
Purple Loosestrife ◽  
Full Potential ◽  
Ecological Niche Models ◽  
Predictive Variables ◽  
Modelling Techniques ◽  
And Training

Purple Loosestrife (Lythrum salicaria) is an invasive plant introduced into North America in the early 1800s. It has since spread into the prairie provinces of Canada (Manitoba, Saskatchewan, and Alberta). It invades wetland habitats, marshes, riparian areas, and natural areas, and it outcompetes native wetland vegetation. In this study we modelled the potential distribution of Purple Loosestrife in the Prairies, explored which suites of predictive variables produced the best ecological niche models, and explored two different approaches to the partitioning of data in evaluating models. We used a number of performance measures and expert evaluation to select our best models. The best model was developed using a suite of climate variables and growing degree-days as the predictive variables and by partitioning testing and training data using stratified random sampling. The model indicated that Purple Loosestrife has not yet reached its full potential distribution in the Prairies. The modelling techniques presented in this paper may be used to predict the potential distribution of other emerging invasive plants, and the results can be used to optimize early detection and surveillance strategies for Purple Loosestrife in areas of the Prairies.

scholarly journals Bookkeeping of insect herbivory trends in herbarium specimens of purple loosestrife ( Lythrum salicaria )

2018 ◽  
Vol 374 (1763) ◽  
pp. 20170398 ◽  
Author(s):  
Caroline Beaulieu ◽  
Claude Lavoie ◽  
Raphaël Proulx
Keyword(s):  
Invasive Plant ◽  
Insect Herbivory ◽  
Lythrum Salicaria ◽  
Leaf Damage ◽  
Purple Loosestrife ◽  
Herbarium Specimens ◽  
Feeding Damage ◽  
Voucher Specimens ◽  
Insect Interactions ◽  
Biodiversity Changes

The potential use of herbarium specimens to detect herbivory trends is enormous but largely untapped. The objective of this study was to reconstruct the long-term herbivory pressure on the Eurasian invasive plant, purple loosestrife ( Lythrum salicaria ), by evaluating leaf damage over 1323 specimens from southern Québec (Canada). The hypothesis tested is that that the prevalence of herbivory damage on purple loosestrife is low during the invasion phase and increases throughout the saturation phase. Historical trends suggest a gradual increase in hole feeding and margin feeding damage from 1883 to around 1940, followed by a period of relative stability. The percentage of specimens with window feeding damage did not begin to increase until the end of the twentieth century, from 3% (2–6%) in 1990 to 45% (14–81%) in 2015. Temporal changes in the frequency of window feeding damage support the hypothesis of an increasing herbivory pressure by recently introduced insects. This study shows that leaf damage made by insects introduced for the biocontrol of purple loosestrife, such as coleopterans of the Neogalerucella genus, can be assessed from voucher specimens. Herbaria are a rich source in information that can be used to answer questions related to plant-insect interactions in the context of biological invasions and biodiversity changes. This article is part of the theme issue ‘Biological collections for understanding biodiversity in the Anthropocene’.

18. Controlling Purple Loosestrife Populations in the Kingston and Surrounding Areas

2018 ◽  
Author(s):  
Keenan Randall ◽  
Ty Greene ◽  
Melissa Lee ◽  
Carlyn McNabb
Keyword(s):  
Invasive Species ◽  
Invasive Plant ◽  
Community Organization ◽  
Human Life ◽  
Control Agent ◽  
Lythrum Salicaria ◽  
Purple Loosestrife ◽  
Native Plant ◽  
Local Resident ◽  
The Impact

Purple loosestrife (Lythrum salicaria) is an invasive plant species that has affected agriculture and wildlife across Canada. The weed is not native to Canada; however in municipalities like Kingston and the surrounding area, it has caused tangible problems. We will strive to engage a government partner (City of Kingston), community organization (ON Invasive Species Awareness Program), and a local resident throughout the completion of our research and regarding the viability of solutions proposed. First, we will examine the origins of the plant in Canada, emphasizing the reproductive characteristics that make the purple loosestrife a powerfully invasive species. Next, we will analyze the impact of the purple loosestrife from three perspectives: (1) the impact on native plant communities; (2) the impact on native animal communities; (3) the impact on human life. We will then evaluate current bio management controls, as utilized by other governments, such as the introduction of another foreign species as a control agent. Specifically, we will examine the potential control systems using the following criteria: (1) ability to control the invasive species; (2) feasibility and cost; and (3) direct and indirect negative impacts. Finally, we will propose a comprehensive strategy for each organization moving forward, allowing for increased community collaboration and, ideally, the elimination and/or control of the invasive species.

Host Specificity and Environmental Impact of the WeevilHylobius transversovittatus, a Biological Control Agent of Purple Loosestrife (Lythrum salicaria)

Weed Science ◽  
1994 ◽  
Vol 42 (1) ◽  
pp. 128-133 ◽  
Author(s):  
Bernd Blossey ◽  
Dieter Schroeder ◽  
Stephen D. Hight ◽  
Richard A. Malecki
Keyword(s):  
Biological Control ◽  
North America ◽  
Invasive Plant ◽  
Negative Impact ◽  
Biological Control Agent ◽  
Control Program ◽  
Classical Biological Control ◽  
Lythrum Salicaria ◽  
Purple Loosestrife ◽  
Test Plant

Introduction of purple loosestrife into North America and its spread into wetlands has led to the degradation of these important habitats for wildlife. Conventional control efforts are unsuccessful in providing long-term control. A classical biological control program offers the best chance for reducing the numbers of this invasive plant and improving regeneration of the native flora and fauna. European studies demonstrated that the root boring weevil Hylobius transversovittatus is highly host specific to the target weed. Attack of two test plant species (winged lythrum and swamp loosestrife) during host range screening was most likely due to artificial test conditions. An environmental assessment of the potential effects of the release of the purple loosestrife borer in North America indicated that benefits outweigh any potential negative impact Therefore its field release was approved in 1992.

scholarly journals Athlete availability and incidence of overuse injuries over an athletics season in a cohort of elite Swedish athletics athletes - a prospective study

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Andreas Lundberg Zachrisson ◽  
Andreas Ivarsson ◽  
Pia Desai ◽  
Jon Karlsson ◽  
Stefan Grau
Keyword(s):  
Incidence Rate ◽  
Elite Athletes ◽  
Incidence Rates ◽  
Training Data ◽  
Overuse Injuries ◽  
Full Potential ◽  
Injury Incidence ◽  
Distance Runners ◽  
Long Distance ◽  
And Training

Abstract Background Athletics is a sport with a high incidence of injury, where most injuries are caused by overuse. Research on injury incidence and the occurrence of overuse injuries during a season in athletics is scarce. An athlete availability (unrestricted ability to participate in training or competition) of less than 80% has been linked with athletes being less likely to reach their performance goals. The purpose of this study was to estimate the monthly injury incidence rates, athlete availability, and the overuse injury incidence rate per 1000 athletics-hours of training in a cohort of Swedish elite athletics athletes. Methods The cohort consisted of 59 male and female elite athletes competing in either middle or long-distance running, sprint, or jumping events. Injury and training data were collected during one athletics season, from October to the end of August. All injury data were collected by medical professionals. Training data were collected monthly, and consisted of event-specific training diaries covering training sessions, training days, and non-training or non-competition days. Monthly injury incidence rates were based on the number of new injuries per month in relation to the number of exposed (injury-free) athletes. Results The overall injury incidence rate for all athletes was highest in October (22.0%). Monthly injury incidence rate for middle and long-distance runners was highest in October (26.1%), for sprinters in April (19.0%), and for jumpers in October (21.4%). The overall athlete availability was 78.0% for the cohort. Sprinters had the lowest athlete availability (71.4%), followed by jumpers (77.3%), and middle-distance and long-distance runners (82.7%). Female athletes (76.5%) had a lower athlete availability than male athletes (79.7%). The injury incidence rate was 1.81 injuries per 1000 athletics hours of training. Middle and long-distance runners had the highest injury incidence rate (2.38), followed by jumpers (1.62), and sprinters (1.34). Conclusion Monthly injury incidence rates during a season appears to correspond to periods of high training volume (conditioning phases and training camps). The low overall athlete availability (> 80%) indicates that many Swedish elite athletes are less likely to reach their full potential.

Cloning Safe Driving Behavior for Self-Driving Cars using Convolutional Neural Networks

2019 ◽  
Vol 12 (2) ◽  
pp. 120-127 ◽  
Author(s):  
Wael Farag
Keyword(s):  
Gradient Descent ◽  
Autonomous Driving ◽  
Driving Behavior ◽  
Training Data ◽  
Stochastic Gradient Descent ◽  
Data Set ◽  
Safe Driving ◽  
Processing Pipeline ◽  
Self Driving Cars ◽  
And Training

Background: In this paper, a Convolutional Neural Network (CNN) to learn safe driving behavior and smooth steering manoeuvring, is proposed as an empowerment of autonomous driving technologies. The training data is collected from a front-facing camera and the steering commands issued by an experienced driver driving in traffic as well as urban roads. Methods: This data is then used to train the proposed CNN to facilitate what it is called “Behavioral Cloning”. The proposed Behavior Cloning CNN is named as “BCNet”, and its deep seventeen-layer architecture has been selected after extensive trials. The BCNet got trained using Adam’s optimization algorithm as a variant of the Stochastic Gradient Descent (SGD) technique. Results: The paper goes through the development and training process in details and shows the image processing pipeline harnessed in the development. Conclusion: The proposed approach proved successful in cloning the driving behavior embedded in the training data set after extensive simulations.

scholarly journals Copy-Move Forgery Detection (CMFD) Using Deep Learning for Image and Video Forensics

2021 ◽  
Vol 7 (3) ◽  
pp. 59
Author(s):  
Yohanna Rodriguez-Ortega ◽  
Dora M. Ballesteros ◽  
Diego Renza
Keyword(s):  
Deep Learning ◽  
Transfer Learning ◽  
Training Data ◽  
Video Editing ◽  
Forgery Detection ◽  
Copy Move Forgery Detection ◽  
The Impact ◽  
And Training ◽  
Selection Of ◽  
Traditional Image

With the exponential growth of high-quality fake images in social networks and media, it is necessary to develop recognition algorithms for this type of content. One of the most common types of image and video editing consists of duplicating areas of the image, known as the copy-move technique. Traditional image processing approaches manually look for patterns related to the duplicated content, limiting their use in mass data classification. In contrast, approaches based on deep learning have shown better performance and promising results, but they present generalization problems with a high dependence on training data and the need for appropriate selection of hyperparameters. To overcome this, we propose two approaches that use deep learning, a model by a custom architecture and a model by transfer learning. In each case, the impact of the depth of the network is analyzed in terms of precision (P), recall (R) and F1 score. Additionally, the problem of generalization is addressed with images from eight different open access datasets. Finally, the models are compared in terms of evaluation metrics, and training and inference times. The model by transfer learning of VGG-16 achieves metrics about 10% higher than the model by a custom architecture, however, it requires approximately twice as much inference time as the latter.

scholarly journals A Critical Review of Forecasting Models to Predict Manpower Demand

2012 ◽  
Vol 4 (2) ◽  
pp. 43-56 ◽  
Author(s):  
James Wong ◽  
Albert Chan ◽  
Y.H Chiang
Keyword(s):  
Computer Programs ◽  
Manpower Planning ◽  
Policy Makers ◽  
Factors Affecting ◽  
Planning Models ◽  
Modelling Techniques ◽  
Improved Accuracy ◽  
Further Development ◽  
And Training ◽  
Manpower Demand

Forecasting manpower requirements has been useful for economic planners, policy makers and training providers in order to avoid the imbalance of skills in the labour market. Although reviews of the manpower planning models have been conducted previously, with the accumulated experience and the booming of advanced statistical techniques and computer programs, the study of forecasting practices has undrgone considerable changes and achieved maturity during the past decade. This paper assesses the latest employment and manpower dmand estimating methods by examining their rationale, strength and constraints. It aims to identify enhancements for further development of manpower forecasting model for the construction industry and compare the reliability and capacity of different forecasting metodologies. It is cocluded that the top-down forecasting approach is the dominant methodology to forecast occupational manpower demand. It precedes other methodologies by its dynamic nature and sensitivity to aa variety of factors affecting the level and structure of employment. Given the improvement of the data available, advanced modelling techniques and computer programs, manpower planning is likely to be more accessible with improved accuracy at every level of the society.  

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