Detailed Information on Publication Record
2007
Predictive Modeling of Biological Communities in Biomonitoring Network: Case Study of ARROW Project of WFD EU Implementation in the Czech Republic
JARKOVSKÝ, Jiří, Klára KUBOŠOVÁ, Radim KLAPKA, Jaroslav RÁČEK, Danka NÉMETHOVÁ et. al.Basic information
Original name
Predictive Modeling of Biological Communities in Biomonitoring Network: Case Study of ARROW Project of WFD EU Implementation in the Czech Republic
Name in Czech
Predictive Modeling of Biological Communities in Biomonitoring Network: Case Study of ARROW Project of
Authors
JARKOVSKÝ, Jiří (203 Czech Republic, guarantor), Klára KUBOŠOVÁ (203 Czech Republic), Radim KLAPKA (203 Czech Republic), Jaroslav RÁČEK (203 Czech Republic), Danka NÉMETHOVÁ (703 Slovakia) and Jan HODOVSKÝ (203 Czech Republic)
Edition
Guelph, 6th International Symposium on Environmental Software Systems, p. 1-12, 11 pp. 2007
Publisher
The International Federation for Information Processing WG 5.11
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10600 1.6 Biological sciences
Country of publisher
Czech Republic
Confidentiality degree
není předmětem státního či obchodního tajemství
RIV identification code
RIV/00216224:14310/07:00022142
Organization unit
Faculty of Science
ISBN
978-3-901882-22-7
Keywords in English
environmental monitoring; WFD EU; predictive modelling; RIVPACS
Tags
International impact, Reviewed
Změněno: 25/6/2008 12:38, RNDr. Danka Haruštiaková, Ph.D.
V originále
The project ARROW (Assessment and Reference Reports of Water monitoring - http://www.cba.muni.cz/arrow/eng) is focused on the implementation of the EU Water Framework Directive in the monitoring of surface waters of the Czech Republic. The evaluation of ecological state of surface waters according to WFD EU depends on the methodology of analysis of biological communities. There are two main approaches with its own disadvantages and advantages which are thus combined in our system i) type specific approach with prediction of comprehensive indices in abiotic types of localities and ii) site specific predictive modeling of biological communities composition on which our paper is focused. The predictive modeling of the benthic macroinvertebrates could be considered as RIVPACS type model and works with well validated environmental gradient comprising both reference and contaminated (standard) sites. The methodology contains identification of indicative species and their relationship to stressors, clustering algorithms and evaluation of the optimal set of clusters (i.e. reference types) for reference biological communities and newly developed robust classification of standard localities into reference types. The information on classification probabilities together with reference biological communities composition are used as input for probabilistic modeling of expected biological communities and the comparison between expected and observed state is used in computation of the final multi-metric evaluation of ecological state. The presented approach is compatible with the EU Water Framework Directive and is implemented in the national-wide information system supported with GIS-oriented analytic software. The presentation is documented by model outputs from more than 300 reference and more than 300 standard sites with regular seasonal sampling of benthic macroinvertebrates communities (approximately 2000 samples). The methodology will be presented as rather universal approach that could be also adopted for the other types of biological communities. The project is supported by the Ministry of Environment of the Czech Republic (project ARROW) and by project INCHEMBIOL (MSM0021622412).
In Czech
The project ARROW (Assessment and Reference Reports of Water monitoring - http://www.cba.muni.cz/arrow/eng) is focused on the implementation of the EU Water Framework Directive in the monitoring of surface waters of the Czech Republic. The evaluation of ecological state of surface waters according to WFD EU depends on the methodology of analysis of biological communities. There are two main approaches with its own disadvantages and advantages which are thus combined in our system i) type specific approach with prediction of comprehensive indices in abiotic types of localities and ii) site specific predictive modeling of biological communities composition on which our paper is focused. The predictive modeling of the benthic macroinvertebrates could be considered as RIVPACS type model and works with well validated environmental gradient comprising both reference and contaminated (standard) sites. The methodology contains identification of indicative species and their relationship to stressors, clustering algorithms and evaluation of the optimal set of clusters (i.e. reference types) for reference biological communities and newly developed robust classification of standard localities into reference types. The information on classification probabilities together with reference biological communities composition are used as input for probabilistic modeling of expected biological communities and the comparison between expected and observed state is used in computation of the final multi-metric evaluation of ecological state. The presented approach is compatible with the EU Water Framework Directive and is implemented in the national-wide information system supported with GIS-oriented analytic software. The presentation is documented by model outputs from more than 300 reference and more than 300 standard sites with regular seasonal sampling of benthic macroinvertebrates communities (approximately 2000 samples). The methodology will be presented as rather universal approach that could be also adopted for the other types of biological communities. The project is supported by the Ministry of Environment of the Czech Republic (project ARROW) and by project INCHEMBIOL (MSM0021622412).
Links
| MSM0021622412, plan (intention) |
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