Spatial database model of ichthyofauna bioindicators of coastal environmental quality
Brenner, J.; Jiménez, J.A. (2007). Spatial database model of ichthyofauna bioindicators of coastal environmental quality, in: Vanden Berghe, E. et al. (Ed.) Proceedings Ocean Biodiversity Informatics: International Conference on Marine Biodiversity Data Management, Hamburg, Germany 29 November to 1 December, 2004. VLIZ Special Publication, 37: pp. 25-35
In: Vanden Berghe, E. et al. (2007). Proceedings Ocean Biodiversity Informatics: International Conference on Marine Biodiversity Data Management, Hamburg, Germany 29 November to 1 December, 2004. VLIZ Special Publication, 37. IOC Workshop Report, 202. VI, 192 pp., more
In: VLIZ Special Publication. Vlaams Instituut voor de Zee (VLIZ): Oostende. ISSN 1377-0950
Related to:
Brenner, J.; Jiménez, J.A. (2004). Spatial database model of ichthyofauna bioindicators of coastal environmental quality, in: Ocean Biodiversity Informatics, Hamburg, Germany: 29 November to 1 December 2004: book of abstracts. pp. 42, more
In the past decades the Catalonian coastal area (Mediterranean Sea) has been subject to an intense human pressure due to the high concentration of activities and settlements. Although some of the impacts are evident others are not, or have not been studied in detail in this region. In the present study we evaluate the environmental quality of the coastal/marine area through the coastal ichthyofauna diversity and distribution. We attempt to assess the potential influence of such activities on fish species identified as state indicators. This was done by identifying a number of land-originated indicators of pressure and relating them with their impact on fish. Special interest was paid to rare and special concern species that occur on Catalonian littoral waters.We developed a spatial system that is based on a georelational database model and implemented on a Geographic Information System (GIS) environment. The GIS final application provides database maintenance, analysis and visualization capabilities to the information system. The data model has three areas: biodiversity, physico-chemical environment and pressure/impact descriptors. The biodiversity area is based on species presence/absence occurrences and related to their ecological and conservation attributes. The physico-chemical area is based on marine environment dynamic variables. Pressure and impact descriptors are based on different data features and produced with impact extent algorithms proposed by the authors. In the three areas, features on spatial layers were attributed with behaviours as natural as they are supposed to be found in nature and/or anthropogenic environments. Fish spatial representation and ecological data were specially related using ecological domain attributes or relations on GIS. This design provides to the database a more natural relationship among elements and environmental responses.
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