scholarly journals Complex habitat changes along elevational gradients interact with resource requirements of insect specialist herbivores

Ecosphere ◽  
2012 ◽  
Vol 3 (12) ◽  
pp. art123 ◽  
Author(s):  
Claas Damken ◽  
George L. W. Perry ◽  
Jacqueline R. Beggs
2015 ◽  
Vol 97 (1) ◽  
pp. 102-111 ◽  
Author(s):  
Amber Fordyce ◽  
Bronwyn A. Hradsky ◽  
Euan G. Ritchie ◽  
Julian Di Stefano

Abstract Resource selection by animals influences individual fitness, the abundance of local populations, and the distribution of species. Further, the degree to which individuals select particular resources can be altered by numerous factors including competition, predation, and both natural- and human-induced environmental change. Understanding the influence of such factors on the way animals use resources can guide species conservation and management in changing environments. In this study, we investigated the effects of a prescribed fire on small-scale (microhabitat) resource selection, abundance, body condition, and movement pathways of a native Australian rodent, the bush rat ( Rattus fuscipes ). Using a before-after, control-impact design, we gathered data from 60 individuals fitted with spool and line tracking devices. In unburnt forest, selection of resources by bush rats was positively related to rushes, logs and complex habitat, and negatively related to ferns and litter. Fire caused selection for spreading grass, rushes, and complex habitat to increase relative to an unburnt control location. At the burnt location after the fire, rats selected patches of unburnt vegetation, and no rats were caught at a trapping site where most of the understory had been burnt. The fire also reduced bush rat abundance and body condition and caused movement pathways to become more convoluted. After the fire, some individuals moved through burnt areas but the majority of movements occurred within unburnt patches. The effects of fire on bush rat resource selection, movement, body condition, and abundance were likely driven by several linked factors including limited access to shelter and food due to the loss of understory vegetation and heightened levels of perceived predation risk. Our findings suggest the influence of prescribed fire on small mammals will depend on the resulting mosaic of burnt and unburnt patches and how well this corresponds to the resource requirements of particular species.


2020 ◽  
Vol 1 (1) ◽  
pp. 20-27
Author(s):  
E. V. Karmanova ◽  
V. A. Shelemetyeva

The article is devoted to the implementation of gamification methods in the educational process. The characteristic features of light and hard gamification are presented. The appropriateness of using gamification when applying e-learning technology is considered. Classification of courses based on hard gamification taking into account the technological features of development is proposed: courses-presentations, courses — computer games, VR/AR courses. The article also illustrates the use of various game elements of easy gamification using the example of the module “Level up! — Gamification” of the Moodle LMS. The capabilities of this module can be used in an electronic course by any teacher who has the skills of working with the Moodle.The authors present the analysis of the development of a training course in sales techniques using hard and light gamification technologies, where the course development was assessed for its complexity, manufacturability, and resource requirements. The results of the analysis showed that the development of courses using hard gamification requires much more financial and time-consuming than the development of courses using light gamification.The article evaluates the results of the educational intensiveness intense “Island 10–22”, held in July 2019 in Skolkovo, in which 100 university teams, teams of research and educational centers, teams of schoolchildren — winners of competitions, olympiads, hackathons (“Young Talents”) participated. The results of the intense confirmed the effectiveness of the use of light gamification methods in adult training. Thus, the conclusions presented in the article reveal a number of advantages that light gamification has in comparison with hard gamification.


Author(s):  
Konstantin S. Varaksin ◽  
◽  
Artem S. Makarov ◽  
Alexander Y. Lyapin ◽  
◽  
...  

The updated edition of the ISO/IEC 17025 standard introduced significant changes to the structure, terminology, resource requirements, processes, quality management system of testing and calibration laboratories. New requirements were established for the organization of laboratory activities – a process approach and risk-based thinking, which provides for a reduction in part of the prescriptive requirements and the introduction of requirements based on the analysis of the performance of actions. In accordance with GOST ISO IEC 17025-2019, the laboratory must authorize personnel to perform specific laboratory activities, as well as guarantee their competence. This article discusses the organization of the competence management system for the personnel of the laboratories of the organizations of Transneft system using the laboratory information management system (LIMS). The model of the process implementation has been described. It has been established that the competence test system allows you to regularly monitor the skills and knowledge of laboratory workers both in terms of the elements of the Quality Management System and in the applied measurement (test) methods. The personnel responsibility matrix implemented in LIMS regulates the powers and functionality of employees, ensuring that employees are allowed to perform work in accordance with their competence. The functions implemented in LIMS made it possible to automate the management of the competence of laboratory workers in accordance with the requirements of GOST ISO/IEC 17025-2019 and other regulatory documents.


2020 ◽  
Vol 34 (12) ◽  
pp. 2513-2523
Author(s):  
Carlos Garcia‐Robledo ◽  
Christina S. Baer ◽  
Kes Lippert ◽  
Vikas Sarathy

2021 ◽  
Author(s):  
Ricardo Medina ◽  
Guinevere O.U. Wogan ◽  
Ke Bi ◽  
Flavia Termignoni‐García ◽  
Manuel Hernando Bernal ◽  
...  

2021 ◽  
Vol 11 (11) ◽  
pp. 4880
Author(s):  
Abigail Copiaco ◽  
Christian Ritz ◽  
Nidhal Abdulaziz ◽  
Stefano Fasciani

Recent methodologies for audio classification frequently involve cepstral and spectral features, applied to single channel recordings of acoustic scenes and events. Further, the concept of transfer learning has been widely used over the years, and has proven to provide an efficient alternative to training neural networks from scratch. The lower time and resource requirements when using pre-trained models allows for more versatility in developing system classification approaches. However, information on classification performance when using different features for multi-channel recordings is often limited. Furthermore, pre-trained networks are initially trained on bigger databases and are often unnecessarily large. This poses a challenge when developing systems for devices with limited computational resources, such as mobile or embedded devices. This paper presents a detailed study of the most apparent and widely-used cepstral and spectral features for multi-channel audio applications. Accordingly, we propose the use of spectro-temporal features. Additionally, the paper details the development of a compact version of the AlexNet model for computationally-limited platforms through studies of performances against various architectural and parameter modifications of the original network. The aim is to minimize the network size while maintaining the series network architecture and preserving the classification accuracy. Considering that other state-of-the-art compact networks present complex directed acyclic graphs, a series architecture proposes an advantage in customizability. Experimentation was carried out through Matlab, using a database that we have generated for this task, which composes of four-channel synthetic recordings of both sound events and scenes. The top performing methodology resulted in a weighted F1-score of 87.92% for scalogram features classified via the modified AlexNet-33 network, which has a size of 14.33 MB. The AlexNet network returned 86.24% at a size of 222.71 MB.


Ecography ◽  
2021 ◽  
Author(s):  
Lea Heidrich ◽  
Stefan Pinkert ◽  
Roland Brandl ◽  
Claus Bässler ◽  
Hermann Hacker ◽  
...  

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