Studio dell' assetto della comunità macrozoobentonica di fondo mobile per la definizione di un metodo innovativo per la valutazione dello stato di qualità del sistema marino costiero
Author(s)
Penna, Marina
Date Issued
October 8, 2008
Type
Doctoral Thesis
Abstract
Although the marine community plays a central role on the assessment of the water quality as the European Water Framework Directive (2000/60/EC) says, the tools to evaluate its status are by now very poor. To evaluate the ecological status of the inshore marine environment it is necessary to arrange tools which should be generally usable and that could summarize the great complexity of the community structure and that could be useful for the decision makers. The conservation and management of the inshore ecological resources need a deep knowledge of the ecological structure and processes taking into account the different spatial scales at which those processes expresses. The evaluations of the ecological quality of the marine inshore systems could be achieved by the study of the sedimentary environment and in particular of the macrozoobenthic fauna. This because this is the final compartment that receives all the pollutants from the water column and because significant impacts could cause modification on the abundance and biomass properties of the system, that decrease as the impacts rises (Pearson and Rosenberg, 1978). With the present work we applied to the macrozoobenthic community studies tools that can summarize the main properties of the system in order to highlight the main structure. The focal task is to define reference structures to which compare perturbed observations. Those perturbed observations should be then categorized into a quality scale sensu WFD. In this thesis we defined a reference community for the soft bottom macrozoobenthic community of the Italian coasts taking into partnership the data from the fauna and the physic-chemicals ones (depth, granulometry of the sediment). The formalization of such community was performed by the use of a Self Organizing Map (SOM) a neural network that allow us to describe the continuum of the reference community and to measure the distance between that and a new observation to be classified.
Additional information
Dottorato di ricerca in Ecologia e gestione delle risorse biologiche
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