|Using asymmetrical designs for environmental impact assessment of unplanned disturbances|Queiroz, N.C.; Lima, F.P.; Ribeiro, P.A.; Pereira, S.G.; Santos, A.M. (2006). Using asymmetrical designs for environmental impact assessment of unplanned disturbances, in: Queiroga, H. et al. (Ed.) Marine biodiversity: patterns and processes, assessment, threats, management and conservation: Proceedings of the 38th European Marine Biology Symposium, held in Aveiro, Portugal, 8-12 September 2003. Developments in Hydrobiology, 183: pp. 223-227. dx.doi.org/10.1007/s10750-005-1118-0
In: Queiroga, H. et al. (Ed.) (2006). Marine biodiversity: patterns and processes, assessment, threats, management and conservation: Proceedings of the 38th European Marine Biology Symposium, held in Aveiro, Portugal, 8-12 September 2003. Developments in Hydrobiology, 183. Springer: Dordrecht. ISBN 1-4020-4321-X. XV, 353 pp., more
In: Dumont, H.J. (Ed.) Developments in Hydrobiology. Kluwer Academic/Springer: The Hague; London; Boston; Dordrecht. ISSN 0167-8418, more
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|Document type: Conference paper|
Benthos; Environmental impact; Oil spills; Rocky shores; Marine
beyond BACI; impact assessment; oil spill; rocky shores; macrobenthic fauna
|Authors|| || Top |
- Queiroz, N.C.
- Lima, F.P.
- Ribeiro, P.A.
- Pereira, S.G.
- Santos, A.M.
Environmental impact assessment of unplanned disturbances is often difficult to accomplish due to the absence of ‘before’ data for the impacted sites. In an attempt to overcome this problem, a beyond BACI model is used in order to detect possible changes in the temporal patterns of variation when no previous data are available. The model attempted to detect changes in the abundance of macroinvertebrate species inhabiting the intertidal mussel matrix after an oil spill which occurred in northern Portugal. The detection of a significant impact failed, most probably due to low temporal replication. An extension of the analysis, including the hierarchical arrangement of temporal variability in periods, suggests that increasing the number of sampling times may result in a higher efficiency of the model.