scholarly journals Crowns of “forgotten” standards in hardwood floodplain forests

2017 ◽  
Vol 63 (No. 12) ◽  
pp. 538-548 ◽  
Author(s):  
Šálek Lubomír ◽  
Machar Ivo ◽  
Sivacioğlu Ahmet ◽  
Zahradník Daniel ◽  
Simon Jaroslav ◽  
...  
Keyword(s):  
Quercus Robur ◽  
Floodplain Forests ◽  
Nearest Neighbour ◽  
Ecological Data ◽  
Data Set ◽  
The Czech Republic ◽  
Crown Area ◽  
Morava River ◽  
Silvicultural System ◽  
Coppice With Standards

Floodplain forests have traditionally been managed using the coppice-with-standards silvicultural system for centuries. After abandoning this silvicultural system approximately in the 1950s the crown of standards (mature-aged trees) developed gradually under the growing influence of their tree competitors. This study examines the crowns of remnant oak and ash standards in a hardwood floodplain forest along the Morava River in the Czech Republic. 100 oak (Quercus robur Linnaeus) standards and 100 ash (Fraxinus excelsior Linnaeus) standards were randomly selected and the basic mensuration data as well as some ecological data, such as number of large dead branches, cavities, and height of the lowest large dead and green branches, were measured. The four nearest neighbour competitors were identified for each standard, and their height, distance and azimuth were measured. The DBH of the analysed oak standards ranged between 71 and 148 cm, and the projected oak crown area ranged between 125 and 533 m<sup>2</sup>. The ash DBH ranged between 71 and 127 cm, and projected ash crowns between 194 and 620 m<sup>2</sup>. To assess competitive pressure, we calculated an index as a ratio of the tangents of angles of regular and compressed crowns. Distance of competing trees was more important than their height in the ash data set, but not in the oak data set.

scholarly journals Coppice-with-standards in floodplain forests – a new subject for nature protection

2009 ◽  
Vol 55 (No. 7) ◽  
pp. 306-311 ◽  
Author(s):  
I. Machar
Keyword(s):  
Czech Republic ◽  
Forest Type ◽  
Historical Context ◽  
Floodplain Forests ◽  
Nature Protection ◽  
Final State ◽  
Lowland Forest ◽  
The Czech Republic ◽  
Natural Monument ◽  
Coppice With Standards

: At present, the coppice-with-standards system has become so rare in floodplain forests that it is considered a natural monument. In 1990, the coppice-with-standards system was not recorded in the territory of the Czech Republic. This state contradicts the increasing interest of nature protection organizations in the relict remainders of the coppice-with-standards system, which is to be considered the closest to naturally preserved lowland forest type, and is, therefore, recommended as the final state of the biocentres and biocorridors in today’s floodplain forests. The aim of this paper is to present the results of the inventory dealing with the present occurrence of the coppice-with-standards system in the floodplain forest of the Litovelské Pomoraví Protected Landscape Area (PLA) in a historical context.

scholarly journals Structure, Yield and Acorn Production of Oak (Quercus robur L.) Dominated Floodplain Forests in the Czech Republic and Croatia

2017 ◽  
Vol 8 (2) ◽  
Author(s):  
Lumír Dobrovolný ◽  
Antonín Martiník ◽  
Damir Drvodelić ◽  
Milan Oršanić ◽  
◽  
...  
Keyword(s):  
Czech Republic ◽  
Quercus Robur ◽  
Floodplain Forests ◽  
Acorn Production ◽  
The Czech Republic

scholarly journals Determination of Body Parts in Holstein Friesian Cows Comparing Neural Networks and k Nearest Neighbour Classification

Animals ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 50
Author(s):  
Jennifer Salau ◽  
Jan Henning Haas ◽  
Wolfgang Junge ◽  
Georg Thaller
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Body Parts ◽  
Nearest Neighbour ◽  
Data Set ◽  
3D Data ◽  
Holstein Friesian ◽  
Knn Classification ◽  
Friesian Cows

Machine learning methods have become increasingly important in animal science, and the success of an automated application using machine learning often depends on the right choice of method for the respective problem and data set. The recognition of objects in 3D data is still a widely studied topic and especially challenging when it comes to the partition of objects into predefined segments. In this study, two machine learning approaches were utilized for the recognition of body parts of dairy cows from 3D point clouds, i.e., sets of data points in space. The low cost off-the-shelf depth sensor Microsoft Kinect V1 has been used in various studies related to dairy cows. The 3D data were gathered from a multi-Kinect recording unit which was designed to record Holstein Friesian cows from both sides in free walking from three different camera positions. For the determination of the body parts head, rump, back, legs and udder, five properties of the pixels in the depth maps (row index, column index, depth value, variance, mean curvature) were used as features in the training data set. For each camera positions, a k nearest neighbour classifier and a neural network were trained and compared afterwards. Both methods showed small Hamming losses (between 0.007 and 0.027 for k nearest neighbour (kNN) classification and between 0.045 and 0.079 for neural networks) and could be considered successful regarding the classification of pixel to body parts. However, the kNN classifier was superior, reaching overall accuracies 0.888 to 0.976 varying with the camera position. Precision and recall values associated with individual body parts ranged from 0.84 to 1 and from 0.83 to 1, respectively. Once trained, kNN classification is at runtime prone to higher costs in terms of computational time and memory compared to the neural networks. The cost vs. accuracy ratio for each methodology needs to be taken into account in the decision of which method should be implemented in the application.

New Evidence on Eastern Europe's Pollution Progress

2003 ◽  
Vol 3 (1) ◽  
Author(s):  
Matthew E Kahn
Keyword(s):  
Sulfur Dioxide ◽  
Carbon Dioxide Emissions ◽  
National Level ◽  
Data Sets ◽  
Local Public Good ◽  
Data Set ◽  
The Czech Republic ◽  
Level Data ◽  
Good Improvement ◽  
New Evidence

Abstract Under communism, Eastern Europe's cities were significantly more polluted than their Western European counterparts. An unintended consequence of communism's decline is to improve urban environmental quality. This paper uses several new data sets to measure these gains. National level data are used to document the extent of convergence across nations in sulfur dioxide and carbon dioxide emissions. Based on a panel data set from the Czech Republic, Hungary and Poland, ambient sulfur dioxide levels have fallen both because of composition and technique effects. The incidence of this local public good improvement is analyzed.

Regional biogeographical model of vegetation zones in doctoral programme Regional Biography in Olomouc (Case study for Norway spruce)

2020 ◽  
Author(s):  
Ivo Machar ◽  
Marián Halás ◽  
Zdeněk Opršal
Keyword(s):  
Climate Change ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Climate Data ◽  
Ecological Data ◽  
The Czech Republic ◽  
Climate Conditions ◽  
Vegetation Zones ◽  
Landscape Research

Regional climate changes impacts induce vegetation zones shift to higher altitudes in temperate landscape. This paper deals with applying of regional biogeography model of climate conditions for vegetation zones in Czechia to doctoral programme Regional Geography in Palacky University Olomouc. The model is based on general knowledge of landscape vegetation zonation. Climate data for model come from predicted validated climate database under RCP8.5 scenario since 2100. Ecological data are included in the Biogeography Register database (geobiocoenological data related to landscape for cadastral areas of the Czech Republic). Mathematical principles of modelling are based on set of software solutions with GIS. Students use the model in the frame of the course “Special Approaches to Landscape Research” not only for regional scenarios climate change impacts in landscape scale, but also for assessment of climate conditions for growing capability of agricultural crops or forest trees under climate change on regional level.

scholarly journals The influence of the Danube-Odra-Elbe water canal project on the geobiocoenoses of floodplain forests (Czech Republic)

2010 ◽  
Vol 58 (4) ◽  
pp. 167-176
Author(s):  
Ivo Machar
Keyword(s):  
Czech Republic ◽  
Water Regime ◽  
Hydrological Regime ◽  
Moisture Regime ◽  
Floodplain Forests ◽  
Gis Analysis ◽  
The Czech Republic ◽  
Soil Moisture Regime ◽  
Water Canal ◽  
Gis Methods

This arcticle deals with influence of the proposed Danube-Odra-Elbe (DOL) water canal on the floodplain forests in the Czech Republic. The project of the DOL water canal is evaluated with using GIS methods and reference assessment of environmental effects. Biogeographic differentiation of the landscape in a biogeocenological concept have been also utilized in this paper. The presented paper has shown the possibilities of use of the GIS analysis for the assessment of the assumed effect of the DOL project on the hydrological regime of floodplain forests. It has been proven that this method is much more efficient in objectivizing the presupposed influences of the DOL canal on the water regime of floodplain forests than the previous assessments. The method employed in this paper for the purposes of the preliminary percentage quantification of the extent of the hydrological in­fluen­ce on individual types of geobiocoenoses of floodplain forests is used generally for the purposes of the environmental assessment of effects on investment plans concerning the landscape (the so-called EIA). It is clear that the assessment of the influences of the DOL project on floodplain forest geobiocoenoses primarily concerns the response of vegetation to changes in the soil moisture regime, which can be compared to the amount of data material (for a summary see PRAX et al., 2008). Results indicate that the potential construction of the DOL canal would significantly, i.e. with an influence value exceeding 50 %, affect 634 km2 of the area of inundations in lowland floodplains in the Czech Republic. Results are discussed in the frame of knowledge about water regime of floodplain forests ecosystems.

scholarly journals Relationship of activities in reverse logistics according to sell point in Czech Republic

2019 ◽  
Vol 61 ◽  
pp. 01016 ◽  
Author(s):  
František Milichovský
Keyword(s):  
Czech Republic ◽  
Reverse Logistics ◽  
Descriptive Statistics ◽  
Primary Research ◽  
Data Set ◽  
The Czech Republic ◽  
Chi Squared ◽  
Statistical Program ◽  
Relationship Of ◽  
Nominal Variables

The paper is focused on findings, if final customers in sell points reflect activities of reverse logistics. Main result of research provides relationship between sell point and reverse activity. The research was aimed at random chosen group of 811 respondents in the Czech Republic. Real participants have been 293, what is effectiveness in 36.13%. The primary research provides possible approaches for companies in sell points within reverse logistics activities to final consumers. To process the results of the questionnaire survey were used basic types of descriptive statistics on the selected data set. The data were processed by using the statistical program IBM SPSS Statistics 24, which was subsequently analysed the dependency between the two nominal variables by means of contingency tables and Pearson's chi-squared test. Limitation for this research is because of the chosen sample and targeting only on Czech Republic.

scholarly journals Genetic evaluation of the length of productive life in Holstein cattle in the Czech Republic

2011 ◽  
Vol 50 (No. 11) ◽  
pp. 493-498 ◽  
Author(s):  
E. Páchová ◽  
L. Zavadilová ◽  
J. Sölkner
Keyword(s):  
Milk Production ◽  
Random Effect ◽  
Independent Effect ◽  
Data Set ◽  
The Czech Republic ◽  
Productive Life ◽  
Stage Of Lactation ◽  
Original Scale ◽  
Season Interaction ◽  
Effect Of Age

Survival Kit V3.12 was used to analyse the length of productive life of cattle in theCzechRepublic. The data set consisted of 230&nbsp;028 registeredHolstein cows. The model included the time-dependent effects parity&nbsp;&times; stage of lactation interaction, herd &times; year &times; season interaction, class of milk production within herd and year, breed within years and the time-independent effect of age at first calving and the random effect of sire. The highest risk of culling was found for cows at the beginning and at the end of the first lactation and at the end of any other lactation. The risk of culling decreased with parity. The risk of culling of cows assigned to the lowest milk production class was five times higher than that of cows assigned to the average milk production class. Risk of culling diminished with a decreasing percentage ofHolstein breed. Cows younger at first calving showed a lower risk of culling. Breeding values for sires expressed as a risk ratio of their daughters were between 0.7 and 1.45. Estimated heritability of functional longevity was 0.025 on the log scale and 0.041 on the original scale. &nbsp;

scholarly journals Results of pig carcass classification according to SEUROP in the Czech Republic

2009 ◽  
Vol 54 (No. 5) ◽  
pp. 217-228 ◽  
Author(s):  
J. Kvapilík ◽  
J. Přibyl ◽  
Z. Růžička ◽  
D. Řehák
Keyword(s):  
Statistical Models ◽  
Time Trend ◽  
Correlation Coefficients ◽  
Muscle Thickness ◽  
Data Set ◽  
The Czech Republic ◽  
Large Size ◽  
Fat Thickness ◽  
Pig Carcasses ◽  
The Eu

Through data analysis of 7 571 883 pig carcasses slaughtered from 2004 to 2007 the means of quality classes (QC) 2.32, lean meat percentage (LM) 55.83%, carcass weight (CW) 87.21 kg, muscle thickness (MT) 61.95 mm and fat thickness (FT) 15.95 mm were determined. The highest correlation coefficients are between QC and LM (<i>r</i> = –0.920), LM and FT (–0.900) as well as QC and FT (0.828), the lowest between FT and MT (<i>r</i> = –0.084). Quality class as the dominant indicator is influenced mainly by LM, which explains from 77% to 89% of variability in the case of linear regression. Among the eight methods of pig carcass classification the FOM apparatus was used the most frequently (46.5% carcasses) followed by the ULTRA-FOM 300 apparatus (15.6%), another apparatus (13.2%) and by the IS-D-05 unit (9.8%). In the statistical models used all effects (differences) are statistically significant because of the large size of the data set. The results from the separate evaluation of each cross-classified effect are that EV has the largest influence and year-season and methods have a smaller influence. The time trend (42 months) documents stable CW and MT, a slight increase in LM and improvement of QC. The estimated results indicate the successful introduction of pig carcass classification in the CR after accession to the EU.

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