scholarly journals Plant communities of the Soutpansberg Arid Northern Bushveld

Koedoe ◽  
2009 ◽  
Vol 51 (1) ◽  
Author(s):  
Theo H.C. Mostert ◽  
George J. Bredenkamp ◽  
Rachel E. Mostert
Keyword(s):  
Plant Communities ◽  
Computer Software ◽  
Detrended Correspondence Analysis ◽  
Adansonia Digitata ◽  
Data Set ◽  
Themeda Triandra ◽  
Sociological Approach ◽  
Event Driven ◽  
Vegetation Maps ◽  
Single Data

The Soutpansberg Arid Northern Bushveld is one of eight major vegetation types (MVT) described for the Soutpansberg-Blouberg region. The plant communities of this MVT are described in detail. Main ecological drivers of the vegetation structure and species composition of these communities are discussed and some conservation recommendations are made. Phytosociological data from a subset of 72 Braun-Blanquet sample plots collected in the Soutpansberg Arid Northern Bushveld were classified using Two-way Indicator Species Analysis (TWINSPAN) and ordinated using a Detrended Correspondence Analysis (DECORANA). The resulting classification was further refined with table-sorting procedures based on the Braun-Blanquet floristic-sociological approach to vegetation classification using the computer software MEGATAB and JUICE. Eight plant communities were identified and described as Commiphora tenuipetiolata-Adansonia digitata short open woodland, Ledebouria ovatifolia-Commiphora mollis short bushland, Phyllanthus reticulatus-Acacia nigrescens short bushland, Tinnea rhodesiana-Combretum apiculatum short bushland, Dichrostachys cinerea subsp. africana-Spirostachys africana low thickets, Themeda triandra-Pterocarpus rotundifolius short closed grassland on steep basaltic slopes, Cyperus albostriatus-Syzygium cordatum sandveld wetlands, and Sesamothamnus lugardii-Catophractes alexandri tall sparse shrubland. These plant communities are event-driven ecosystems, predominantly infl uenced by frequent droughts, exposure to desiccation and unpredictable rainfall events. The complex topography of the Soutpansberg further contributes to the aridity of these ecosystems. The classifi cation and ordination analyses show similar groupings in the vegetation of the Soutpansberg Arid Mountain Bushveld. This confi rms the usefulness of complimentary analysis, using both classifi cation and ordination methods on a single data set in order to examine patterns and to search for group structure.Conservation implications: The results from this study will alter existing regional vegetation maps profoundly. The described plant communities of these arid event-driven ecosystems should be used as benchmark examples of the region’s primary vegetation. Conservation and management planning should be based on these vegetation units.

scholarly journals The vegetation types and management units of Goedverwacht farm in the mixed bushveld of the Northern Province, South Africa

Koedoe ◽  
1997 ◽  
Vol 40 (2) ◽  
Author(s):  
L. Breebaart ◽  
M. Deutschlander
Keyword(s):  
Plant Communities ◽  
Correspondence Analysis ◽  
Canonical Correspondence Analysis ◽  
Environmental Gradient ◽  
Detrended Correspondence Analysis ◽  
Northern Province ◽  
Computer Programme ◽  
Data Set ◽  
Management Units ◽  
Floristic Data

An analysis of the vegetation of Goedverwacht farm in the mixed bushveld of the Northern Province is presented. Releves were compiled in 33 stratified random sample plots. Eight distinct plant communities were identified by means ofBraun-Blanquet pro-cedures. Detrended correspondence analysis (DCA) was applied to the floristic data set using the computer programme DECORANA (Detrended Correspondence Analysis) to determine a probable environmental gradient and to facilitate in the identification of management units. The computer programme CANOCO (Canonical Correspondence Analysis) was used to apply canonical correspondence analysis (CCA) to the floristic data set. Two management units were determined by means of vegetation ordinations and soil data. A classification, description and ecological interpretation of the plant communities as well as a description of the management units are presented.

Diversity of subalpine and alpine vegetation of the eastern part of the Nízke Tatry Mts in Slovakia: major types and environmental gradients

Biologia ◽  
2009 ◽  
Vol 64 (5) ◽  
Author(s):  
Lucia Sekulová ◽  
Michal Hájek
Keyword(s):  
Plant Communities ◽  
Environmental Gradients ◽  
Ecological Factors ◽  
Detrended Correspondence Analysis ◽  
Dwarf Shrub ◽  
Soil Reaction ◽  
Data Set ◽  
Entire Data ◽  
Second Gradient ◽  
One Year

AbstractChanges in composition and structure of alpine and subalpine plant communities in relation to ecological factors were analysed in the Nízke Tatry Mts, Slovakia. Species cover values of vascular and non-vascular plants in each vegetation plot were recorded on the nine-degree scale. A data set of 156 relevés of alpine and subalpine vegetation was sampled recently during one year in the eastern part of the Nízke Tatry National Park. The data set was analysed by cluster analysis and Detrended Correspondence Analysis. analyses were carried out on the entire data set, including the subset of short grassland and dwarf-shrub vegetation. Major gradients and clusters were ecologically interpreted using Ellenberg indicator values. In the entire data set, the major gradient in species composition was associated with nutrient availability and the second most important gradient with light. In the case of short grassland and dwarf-shrub vegetation, the gradients were different. The first one was associated with soil reaction and the second gradient was associated with moisture. Clusters proposed by numerical classification reproduced many traditional phytosociological associations, namely Seslerietum distichae, Sphagno capillifolii-Empetretum nigri, Junco trifidi-Callunetum vulgaris, Juncetum trifidi, Dryopterido dilatatae-Pinetum mugo, Luzuletum obscurae, Agrostio pyrenaiceae-Nardetum strictae, while some other associations were less clearly differentiated (communities of the alliances Calamagrostion villosae, Adenostylion alliariae, Trisetion fusci, Cratoneuro filicini-Calthion laetae or Salicion herbaceae). The next clusters included Vaccinium and Festuca supina dominated communities and artificial roadside grasslands sown 50 years ago. Bryophytes and lichens were highly represented among diagnostic species of particular associations. Distribution pattern of particular plant communities was strongly influenced by site position either on northern or southern slope of the mountains.

scholarly journals Major Vegetation Types of the Soutpansberg Conservancy and the Blouberg Nature Reserve, South Africa

Koedoe ◽  
2008 ◽  
Vol 50 (1) ◽  
Author(s):  
Theo H.C. Mostert ◽  
George J. Bredenkamp ◽  
Hannes L. Klopper ◽  
Cornie Verwey ◽  
Rachel E. Mostert ◽  
...  
Keyword(s):  
Nature Reserve ◽  
Detrended Correspondence Analysis ◽  
Acacia Tortilis ◽  
Vegetation Types ◽  
Adansonia Digitata ◽  
Southern Plains ◽  
Eragrostis Lehmanniana ◽  
Sociological Approach ◽  
Sclerocarya Birrea ◽  
Species Analysis

The Major Megetation Types (MVT) and plant communities of the Soutpansberg Centre of Endemism are described in detail, with special reference to the Soutpansberg Conservancy and the Blouberg Nature Reserve. Phytosociological data from 442 sample plots were ordinated using a DEtrended CORrespondence ANAlysis (DECORANA) and classified using TWo-Way INdicator SPecies ANalysis (TWINSPAN). The resulting classification was further refined with table-sorting procedures based on the Braun–Blanquet floristic–sociological approach of vegetation classification using MEGATAB. Eight MVT’s were identified and described as Eragrostis lehmanniana var. lehmanniana–Sclerocarya birrea subsp. caffra Blouberg Northern Plains Bushveld, Euclea divinorum–Acacia tortilis Blouberg Southern Plains Bushveld, Englerophytum magalismontanum–Combretum molle Blouberg Mountain Bushveld, Adansonia digitata–Acacia nigrescens Soutpansberg Arid Northern Bushveld, Catha edulis–Flueggia virosa Soutpansberg Moist Mountain Thickets, Diplorhynchus condylocarpon–Burkea africana Soutpansberg Leached Sandveld, Rhus rigida var. rigida–Rhus magalismontanum subsp. coddii Soutpansberg Mistbelt Vegetation and Xymalos monospora–Rhus chirendensis Soutpansberg Forest Vegetation.

scholarly journals Plant communities with Pinus mugo (alliance Pinion mugo) in the subalpine belt of the Western Carpathians - a numerical approach

2011 ◽  
Vol 74 (4) ◽  
pp. 329-343 ◽  
Author(s):  
Jozef Šibík ◽  
Milan Valachovič ◽  
Ján Kliment
Keyword(s):  
Plant Communities ◽  
Detrended Correspondence Analysis ◽  
Numerical Approach ◽  
Western Carpathians ◽  
Pinus Mugo ◽  
Indicator Values ◽  
Data Set ◽  
Subalpine Belt ◽  
The Alps ◽  
Pine Stands

A syntaxonomical revision of plant communities with dominant <em>Pinus mugo</em> in the Western Carpathians is presented. The data set of 341 relevés was examined and analysed using the detrended correspondence analysis and the cluster analysis. Major gradients and clusters were interpreted using Ellenberg’s indicator values. The major gradient in species composition was associated with available nutrients and moisture. The authors suggest distinguishing the dwarf pine stands of the supramontanous and subalpine belts of the Western Carpathians referred to the alliance Pinion mugo Pawłowski in Pawłowski et al. 1928 of the order Junipero-Pinetalia mugo Boşcaiu 1971 and the class Roso pendulinae-Pinetea mugo Theurillat in Theurillat et al. 1995, into three separate associations: the Cetrario-Pinetum mugo Hadač 1956, the Homogyno alpinae-Pinetum mugo (Sillinger 1933) nom. nov., and the Adenostylo alliariae-Pinetum mugo (Sillinger 1933) Šoltésová 1974. The authors also elucidated the unauthorized name of the association Vaccinio myrtilli-Pinetum mugo Hadač 1956, which is a younger homonym of the valid name of the association Vaccinio myrtilli-Pinetum montanae Morton 1927 that characterises the acidophilous dwarf pine stands on calcareous bedrocks in the Alps.

Customer-Related Social Stressors

2015 ◽  
Vol 14 (4) ◽  
pp. 165-181 ◽  
Author(s):  
Sarah Dudenhöffer ◽  
Christian Dormann
Keyword(s):  
Service Providers ◽  
Principal Component ◽  
Well Being ◽  
Emotional Dissonance ◽  
Social Stressors ◽  
Data Set ◽  
Confirmatory Factor Analyses ◽  
Confirmatory Factor ◽  
Service Jobs ◽  
Single Data

Abstract. The purpose of this study was to replicate the dimensions of the customer-related social stressors (CSS) concept across service jobs, to investigate their consequences for service providers’ well-being, and to examine emotional dissonance as mediator. Data of 20 studies comprising of different service jobs (N = 4,199) were integrated into a single data set and meta-analyzed. Confirmatory factor analyses and explorative principal component analysis confirmed four CSS scales: disproportionate expectations, verbal aggression, ambiguous expectations, disliked customers. These CSS scales were associated with burnout and job satisfaction. Most of the effects were partially mediated by emotional dissonance. Further analyses revealed that differences among jobs exist with regard to the factor solution. However, associations between CSS and outcomes are mainly invariant across service jobs.

Event detection of different English data sources based on transfer learning

2021 ◽  
pp. 1-11
Author(s):  
Yanan Huang ◽  
Yuji Miao ◽  
Zhenjing Da
Keyword(s):  
Transfer Learning ◽  
Event Detection ◽  
Visual Analysis ◽  
Learning Algorithm ◽  
Data Sources ◽  
Data Set ◽  
Data Source ◽  
Single Data Source ◽  
The Difference ◽  
Single Data

The methods of multi-modal English event detection under a single data source and isomorphic event detection of different English data sources based on transfer learning still need to be improved. In order to improve the efficiency of English and data source time detection, based on the transfer learning algorithm, this paper proposes multi-modal event detection under a single data source and isomorphic event detection based on transfer learning for different data sources. Moreover, by stacking multiple classification models, this paper makes each feature merge with each other, and conducts confrontation training through the difference between the two classifiers to further make the distribution of different source data similar. In addition, in order to verify the algorithm proposed in this paper, a multi-source English event detection data set is collected through a data collection method. Finally, this paper uses the data set to verify the method proposed in this paper and compare it with the current most mainstream transfer learning methods. Through experimental analysis, convergence analysis, visual analysis and parameter evaluation, the effectiveness of the algorithm proposed in this paper is demonstrated.

scholarly journals Time-ResNeXt for epilepsy recognition based on EEG signals in wireless networks

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Shaoqiang Wang ◽  
Shudong Wang ◽  
Song Zhang ◽  
Yifan Wang
Keyword(s):  
Deep Learning ◽  
Network Structure ◽  
Signal Recognition ◽  
Eeg Signals ◽  
Real World Data ◽  
Data Set ◽  
Practical Applications ◽  
Epilepsy Diagnosis ◽  
Single Data ◽  
Electroencephalogram Eeg

Abstract To automatically detect dynamic EEG signals to reduce the time cost of epilepsy diagnosis. In the signal recognition of electroencephalogram (EEG) of epilepsy, traditional machine learning and statistical methods require manual feature labeling engineering in order to show excellent results on a single data set. And the artificially selected features may carry a bias, and cannot guarantee the validity and expansibility in real-world data. In practical applications, deep learning methods can release people from feature engineering to a certain extent. As long as the focus is on the expansion of data quality and quantity, the algorithm model can learn automatically to get better improvements. In addition, the deep learning method can also extract many features that are difficult for humans to perceive, thereby making the algorithm more robust. Based on the design idea of ResNeXt deep neural network, this paper designs a Time-ResNeXt network structure suitable for time series EEG epilepsy detection to identify EEG signals. The accuracy rate of Time-ResNeXt in the detection of EEG epilepsy can reach 91.50%. The Time-ResNeXt network structure produces extremely advanced performance on the benchmark dataset (Berne-Barcelona dataset) and has great potential for improving clinical practice.

Disparities Across Time: Exploring Absenteeism Patterns between Cohorts of Students with Disabilities

2020 ◽  
Vol 122 (11) ◽  
pp. 1-32
Author(s):  
Michael A. Gottfried ◽  
Vi-Nhuan Le ◽  
J. Jacob Kirksey
Keyword(s):  
Students With Disabilities ◽  
Social Needs ◽  
Data Sets ◽  
Chronic Absenteeism ◽  
Data Set ◽  
Full Day Kindergarten ◽  
Effective Interventions ◽  
Nationally Representative ◽  
Single Data ◽  
Over Time

Background It is of grave concern that kindergartners are missing more school than students in any other year of elementary school; therefore, documenting which students are absent and for how long is of upmost importance. Yet, doing so for students with disabilities (SWDs) has received little attention. This study addresses this gap by examining two cohorts of SWDs, separated by more than a decade, to document changes in attendance patterns. Research Questions First, for SWDs, has the number of school days missed or chronic absenteeism rates changed over time? Second, how are changes in the number of school days missed and chronic absenteeism rates related to changes in academic emphasis, presence of teacher aides, SWD-specific teacher training, and preschool participation? Subjects This study uses data from the Early Childhood Longitudinal Study (ECLS), a nationally representative data set of children in kindergarten. We rely on both ECLS data sets— the kindergarten classes of 1998–1999 and 2010–2011. Measures were identical in both data sets, making it feasible to compare children across the two cohorts. Given identical measures, we combined the data sets into a single data set with an indicator for being in the older cohort. Research Design This study examined two sets of outcomes: The first was number of days absent, and the second was likelihood of being chronically absent. These outcomes were regressed on a measure for being in the older cohort (our key measure for changes over time) and numerous control variables. The error term was clustered by classroom. Findings We found that SWDs are absent more often now than they were a decade earlier, and this growth in absenteeism was larger than what students without disabilities experienced. Absenteeism among SWDs was higher for those enrolled in full-day kindergarten, although having attended center-based care mitigates this disparity over time. Implications are discussed. Conclusions Our study calls for additional attention and supports to combat the increasing rates of absenteeism for SWDs over time. Understanding contextual shifts and trends in rates of absenteeism for SWDs in kindergarten is pertinent to crafting effective interventions and research geared toward supporting the academic and social needs of these students.

scholarly journals Algorithm for preprocessing and unification of time series based on machine learning for data structuring

2020 ◽  
pp. 40-50
Author(s):  
Andrey Sergeevich Kopyrin ◽  
Irina Leonidovna Makarova
Keyword(s):  
Time Series ◽  
Domain Knowledge ◽  
Fuzzy Time Series ◽  
Data Set ◽  
Structure Information ◽  
Combined Use ◽  
Primary Documents ◽  
Preliminary Preparation ◽  
Single Data ◽  
Different Sources

The subject of the research is the process of collecting and preliminary preparation of data from heterogeneous sources. Economic information is heterogeneous and semi-structured or unstructured in nature. Due to the heterogeneity of the primary documents, as well as the human factor, the initial statistical data may contain a large amount of noise, as well as records, the automatic processing of which may be very difficult. This makes preprocessing dynamic input data an important precondition for discovering meaningful patterns and domain knowledge, and making the research topic relevant.Data preprocessing is a series of unique tasks that have led to the emergence of various algorithms and heuristic methods for solving preprocessing tasks such as merge and cleanup, identification of variablesIn this work, a preprocessing algorithm is formulated that allows you to bring together into a single database and structure information on time series from different sources. The key modification of the preprocessing method proposed by the authors is the technology of automated data integration.The technology proposed by the authors involves the combined use of methods for constructing a fuzzy time series and machine lexical comparison on the thesaurus network, as well as the use of a universal database built using the MIVAR concept.The preprocessing algorithm forms a single data model with the ability to transform the periodicity and semantics of the data set and integrate data that can come from various sources into a single information bank.

scholarly journals Mountain pastures of Qilian Shan: plant communities, grazing impact and degradation status (Gansu province, NW China)

Hacquetia ◽  
2016 ◽  
Vol 15 (2) ◽  
pp. 21-35 ◽  
Author(s):  
Alina Baranova ◽  
Udo Schickhoff ◽  
Shunli Wang ◽  
Ming Jin
Keyword(s):  
Plant Community ◽  
Plant Communities ◽  
Plant Cover ◽  
Management Strategies ◽  
Detrended Correspondence Analysis ◽  
Gansu Province ◽  
Grazing Impact ◽  
Vegetation Patterns ◽  
Pasture Management ◽  
Nw China

Abstract Environmental degradation of pasture areas in the Qilian Mountains (Gansu province, NW China) has increased in recent years. Soil erosion and loss of biodiversity caused by overgrazing is widespread. Changes in plant cover, however, have not been analysed so far. The aim of this paper is to identify plant communities and to detect grazing-induced changes in vegetation patterns. Quantitative and qualitative relevé data were collected for community classification and to analyse gradual changes in vegetation patterns along altitudinal and grazing gradients. Detrended correspondence analysis (DCA) was used to analyse variation in relationships between vegetation, environmental factors and differential grazing pressure. The results of the DCA showed apparent variation in plant communities along the grazing gradient. Two factors - altitude and exposure - had the strongest impact on plant community distribution. Comparing monitoring data for the most recent nine years, a trend of pasture deterioration, plant community successions and shift in dominant species becomes obvious. In order to increase grassland quality, sustainable pasture management strategies should be implemented.

Sign in / Sign up

Export Citation Format

Share Document