Suppression of indigo bush with pod pests

The recorded seed predators of Amorpha fruticosa L., indigo bush weevils and pteromalid wasps, were the subject of laboratory and field research studies in the period from 2006 to 2011. Sample analyses were carried out on more than 30 localities in Serbia with the aim of measuring the summarized pre-dispersal and post dispersal predation preferences. The percentages of the total pre-dispersal (max?33%) and post-dispersal re-infested material (over 95%), make these insects serious candidates for host-plant suppression. Their bionomics were monitored through continuous collection, dessection and observation of infested seeds, in correlation with environmental parameters, especially water-level fluctuations in endangered forests.

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Bloom of the potentially toxic cyanobacterium P. rubescens: seasonal distribution and possible drivers of its proliferation in the Vrutci reservoir (Serbia)

Oceanological and Hydrobiological Studies ◽

10.2478/ohs-2019-0029 ◽

2019 ◽

Vol 48 (4) ◽

pp. 316-327

Author(s):

Ana Blagojević Ponjavić ◽

Dušan Kostić ◽

Prvoslav Marjanović ◽

Ivana Trbojević ◽

Slađana Popović ◽

...

Keyword(s):

Water Level ◽

Environmental Parameters ◽

Water Quality Monitoring ◽

Water Level Fluctuations ◽

Physical Parameters ◽

Filamentous Cyanobacterium ◽

Worldwide Distribution ◽

Quality Of Water ◽

Lakes And Reservoirs ◽

Size And Morphology

Abstract Planktothrix rubescens is a filamentous cyanobacterium with a worldwide distribution in lakes and reservoirs of varying size and morphology. The objective of this study was to identify the population dynamics and the major drivers of P. rubescens blooms. Samples for qualitative and quantitative analysis of phytoplankton were collected every month in 2014 and 2015 from stationary depths, while the main physical parameters were measured in situ along the water column. Samples for chemical analysis were collected below the surface, at mid-depth (metalimnion) and near the bottom. In the periods of thermal stratification, P. rubescens formed the maximum biomass in the metalimnion, however, its volume-weighted biomass reached the maximum value in the winter mixing period (4.40 mm3 l−1). Changes in the P. rubescens population in the reservoir were related to changes in the measured environmental parameters. Significant physical, hydrological, meteorological and chemical parameters were distinguished based on the multivariate analysis. The variable associated with water-level fluctuations showed the highest positive correlation with P. rubescens biomass. We conclude that it is necessary to establish water quality monitoring and prevent excessive water-level fluctuations to ensure a high quality of water supplies from the reservoir.

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Earthquake-induced water-level fluctuations from a well in Dawson County Georgia

Bulletin of the Seismological Society of America ◽

10.1785/bssa0540041023 ◽

1964 ◽

Vol 54 (4) ◽

pp. 1023-1033

Author(s):

Robert C. Vorhis

Keyword(s):

Water Level ◽

Nuclear Reactor ◽

Water Level Fluctuations ◽

Water Well ◽

The Subject ◽

Level Recorder ◽

Water Level Recorder

Abstract A water well at the Georgia Nuclear Reactor site in north Georgia has recorded a surprising number of earthquake-induced water-level fluctuations. These fluctuations are the subject of this paper. In the period from September 4, 1956 to June 17, 1958—during which time a water-level recorder was in operation—a total of 42 were recorded in this one well.

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Application of artificial neural networks (ANN) in Lake Drwęckie water level modelling

Limnological Review ◽

10.2478/limre-2015-0003 ◽

2015 ◽

Vol 15 (1) ◽

pp. 21-30 ◽

Cited By ~ 2

Author(s):

Adam Piasecki ◽

Jakub Jurasz ◽

Rajmund Skowron

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Water Level ◽

Meteorological Data ◽

Water Level Fluctuations ◽

Explanatory Variables ◽

Real Value ◽

The Subject ◽

Artificial Neural ◽

Hidden Layer

Abstract This paper presents an attempt to model water-level fluctuations in a lake based on artificial neural networks. The subject of research was the water level in Lake Drwęckie over the period 1980-2012. For modelling purposes, meteorological data from the weather station in Olsztyn were used. As a result of the research conducted, the model M_Meteo_Lag_3 was identified as the most accurate. This artificial neural network model has seven input neurons, four neurons in the hidden layer and one neuron in the output layer. As explanatory variables meteorological parameters (minimal, maximal and mean temperature, and humidity) and values of dependent variables from three earlier months were implemented. The paper claims that artificial neural networks performed well in terms of modelling the analysed phenomenon. In most cases (55%) the modelled value differed from the real value by an average of 7.25 cm. Only in two cases did a meaningful error occur, of 33 and 38 cm.

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Temperature Trend Analysis in Urmia Lake Basin Compared with Water Level Fluctuations of the Lake

International Institute of Chemical, Biological & Environmental Engineering June 5-6, 2015 Istanbul (Turkey) ◽

10.15242/iicbe.c0615010 ◽

2015 ◽

Keyword(s):

Water Level ◽

Trend Analysis ◽

Temperature Trend ◽

Urmia Lake ◽

Water Level Fluctuations ◽

Lake Basin ◽

Urmia Lake Basin

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AUTOMATIC WATER LEVEL MONITORING WITH IOT AND LPWAN

International Conference on Technics Technologies and Education ◽

10.15547/ictte.2019.02.041 ◽

2019 ◽

pp. 95-103

Author(s):

Krum Videnov ◽

Vanya Stoykova

Keyword(s):

Water Level ◽

Real Time ◽

Early Warning ◽

Water Sources ◽

Water Levels ◽

Water Level Fluctuations ◽

Level Monitoring ◽

Water Level Monitoring

Monitoring water levels of lakes, streams, rivers and other water basins is of essential importance and is a popular measurement for a number of different industries and organisations. Remote water level monitoring helps to provide an early warning feature by sending advance alerts when the water level is increased (reaches a certain threshold). The purpose of this report is to present an affordable solution for measuring water levels in water sources using IoT and LPWAN. The assembled system enables recording of water level fluctuations in real time and storing the collected data on a remote database through LoRaWAN for further processing and analysis.

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Gentrification and functional change in Budapest – ‘ruin bars’ and the commodification of housing in a post-socialist context

Urban Development Issues ◽

10.2478/udi-2020-0002 ◽

2020 ◽

Vol 65 (1) ◽

pp. 17-26

Author(s):

Gergely Olt ◽

Adrienne Csizmady

Keyword(s):

Ownership Structure ◽

Hospitality Industry ◽

Housing Stock ◽

Field Research ◽

Functional Change ◽

Global Changes ◽

Heritage Buildings ◽

The Subject ◽

Tourism And Hospitality Industry ◽

Tourism And Hospitality

AbstractThe growth of the tourism and hospitality industry played an important role in the gentrification of the post-socialist city of Budapest. Although disinvestment was present, reinvestment was moderate for decades after 1989. Privatisation of individual tenancies and the consequent fragmented ownership structure of heritage buildings made refurbishment and reinvestment less profitable. Because of local contextual factors and global changes in consumption habits, the function of the dilapidated 19th century housing stock transformed in the 2000s, and the residential neighbourhood which was the subject of the research turned into the so called ‘party district’. The process was followed in our ongoing field research. The functional change made possible speculative investment in inner city housing and played a major role in the commodification of the disinvested housing stock.

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