The use of the GARP genetic algorithm and Internet grid computing in the Lifemapper world atlas of species biodiversity
| Autor: | Ricardo Scachetti Pereira, David R. B. Stockwell, David Vieglais, Aimee Stewart, James H. Beach, Gregory Vorontsov |
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| Rok vydání: | 2006 |
| Předmět: |
FOS: Computer and information sciences
0106 biological sciences Geospatial analysis Computer science Fauna Biodiversity computer.software_genre Quantitative Biology - Quantitative Methods 010603 evolutionary biology 01 natural sciences Neural and Evolutionary Computing (cs.NE) Quantitative Methods (q-bio.QM) Environmental informatics Atlas (topology) Ecology 010604 marine biology & hydrobiology Ecological Modeling Computer Science - Neural and Evolutionary Computing 15. Life on land Other Quantitative Biology (q-bio.OT) Data science Quantitative Biology - Other Quantitative Biology Internet grid computing Outreach Computer Science - Distributed Parallel and Cluster Computing FOS: Biological sciences Distributed Parallel and Cluster Computing (cs.DC) computer |
| Zdroj: | Ecological Modelling. 195:139-145 |
| ISSN: | 0304-3800 |
| DOI: | 10.1016/j.ecolmodel.2005.11.016 |
| Popis: | Lifemapper (http://www.lifemapper.org) is a predictive electronic atlas of the Earth's biological biodiversity. Using a screensaver version of the GARP genetic algorithm for modeling species distributions, Lifemapper harnesses vast computing resources through 'volunteers' PCs similar to SETI@home, to develop models of the distribution of the worlds fauna and flora. The Lifemapper project's primary goal is to provide an up to date and comprehensive database of species maps and prediction models (i.e. a fauna and flora of the world) using available data on species' locations. The models are developed using specimen data from distributed museum collections and an archive of geospatial environmental correlates. A central server maintains a dynamic archive of species maps and models for research, outreach to the general community, and feedback to museum data providers. This paper is a case study in the role, use and justification of a genetic algorithm in development of large-scale environmental informatics infrastructure. Comment: 17 pages, 4 figures, in press at Ecological Modelling |
| Databáze: | OpenAIRE |
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