1. BENFES, a new biotic index for assessing ecological status of soft-bottom communities. Towards a lower taxonomic complexity, greater reliability and less effort.
- Author
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Sánchez-Moyano JE, García-Asencio I, Donázar-Aramendía I, Miró JM, Megina C, and García-Gómez JC
- Subjects
- Animals, Aquatic Organisms classification, Biodiversity, Environmental Monitoring methods, Estuaries, Invertebrates classification, Spain, Aquatic Organisms growth & development, Ecology methods, Ecosystem, Invertebrates growth & development
- Abstract
The new biotic index BENFES (Benthic Families Ecological Status Index) for assessing the ecological status of soft-bottom communities based on presence/absence at the taxonomic family level, is described. BENFES was primarily developed for the communities from the Guadalquivir estuary (South-western Spain), but the aim of the present work was to evaluate the reliability and validity of this index for its application in the Water Framework Directive (WFD), especially as a preliminary and rapid assessment method for monitoring the ecological status of transitional and coastal waters. BENFES was compared with five widely used indices (BOPA, BO2A, BENTIX; AMBI and M-AMBI) in several studies from Southwestern Spain. In addition, we have also established comparisons between these indices and the most commonly used Shannon-Wiener diversity. M-AMBI and BENFES showed the best agreement in ecological status assignation and were the most useful and discriminant between the studied areas. BENTIX was a good discriminant in coastal areas but was severe with the environmental condition from estuaries; BOPA/BO2A did not show clear trends in most of the zones; and AMBI tended to provide overestimations of the ecological status. In conclusion, BENFES shows several advantages such as lower taxonomic resolution, greater reliability and only requiring presence/absence. All this implies a huge possibility to perform a simplified monitoring routine for the control of the ecological quality of water bodies., (Copyright © 2017 Elsevier Ltd. All rights reserved.)
- Published
- 2017
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