Description of a multimetric phytoplankton Index (MPI) for the assessment of transitional waters

A Multimetric Phytoplankton Index (MPI) is proposed to support management policies for the assessment of transitional ecosystems and the implementation of the European Water Framework Directive. The MPI incorporates Hulburt’s dominance index, bloom frequency and Menhinick’s diversity index, calculated on the basis of phytoplankton species composition. Chlorophyll-a concentrations were also included, to provide biomass data and to guarantee continuity and comparison with past evaluations. The MPI was calculated by averaging the ratios of the resulting values of each metric to those of a reference site characterised by low anthropogenic impact. The MPI was set up using data from over a 10-year period in several stations in Venice Lagoon (North-western Adriatic region), a highly valuable and heterogeneous transitional environment, subject to significant anthropogenic pressures. The dataset included physico-chemical data, nutrient and contaminant concentrations. Statistical analyses allowed us to gauge the MPI’s responses to anthropogenic pressures and to verify its reliability.

A Multimetric Phytoplankton Index (MPI) is proposed to support management policies for the assessment of transitional ecosystems and the implementation of the European Water Framework Directive. The MPI incorporates Hulburt's dominance index, bloom frequency and Menhinick's diversity index, calculated on the basis of phytoplankton species composition.Chlorophyll a concentrations were also included, to provide biomass data and to guarantee continuity and comparison with past evaluations. The MPI was calculated by averaging the ratios of the resulting values of each metric to those of a reference site characterised by low anthropogenic impact.The MPI was set up using data from over a 10-year period in several stations in Venice Lagoon (Northwestern Adriatic region), a highly valuable and heterogeneous transitional environment, subject to significant anthropogenic pressures. The dataset included physico-chemical data, nutrient and contaminant concentrations. Statistical analyses allowed us to gauge the MPI's responses to anthropogenic pressures and to verify its reliability. (C) 2013 Elsevier Ltd. All rights reserved.