Assessing good environmental status through mesozooplankton biodiversity: a step forward.

We developed a zooplankton-based water-quality evaluating method using indices of alpha diversity. Two key objectives were set: (i) the comparison of two-different quality-samples from different areas, and the verification of their differentiation, based on mesozooplankton biodiversity indices; and (ii) the development of a methodology, which was able to assess the quality of new marine water samples. Our analysis was based on a 24-year-long in situ dataset (1987-2010) of 139 samples in which 86 mesozooplankton taxa were identified. High-diversity and high evenness values were reported in the case of the "good" status sample, while low diversity, low evenness and high dominance values occurred at the lower quality one. A linear discriminant analysis (LDA) was conducted that discriminated the tested samples at 100%. This LDA was then used to evaluate samples of unknown quality. Finally, 90% of them were classified with a probability of correct classification (posterior probability) >95%. The present study proves that mesozooplankton diversity indices can discriminate different levels of anthropogenic impacts. In this sense, it can be used as a reliable indicator for environmental assessment in the pelagic habitats of the Mediterranean Sea.

Eutrophication risk assessment in coastal embayments using simple statistical models.

A statistical methodology is proposed for assessing the risk of eutrophication in marine coastal embayments. The procedure followed was the development of regression models relating the levels of chlorophyll a (Chl) with the concentration of the limiting nutrient--usually nitrogen--and the renewal rate of the systems. The method was applied in the Gulf of Gera, Island of Lesvos, Aegean Sea and a surrogate for renewal rate was created using the Canberra metric as a measure of the resemblance between the Gulf and the oligotrophic waters of the open sea in terms of their physical, chemical and biological properties. The Chl-total dissolved nitrogen-renewal rate regression model was the most significant, accounting for 60% of the variation observed in Chl. Predicted distributions of Chl for various combinations of the independent variables, based on Bayesian analysis of the models, enabled comparison of the outcomes of specific scenarios of interest as well as further analysis of the system dynamics. The present statistical approach can be used as a methodological tool for testing the resilience of coastal ecosystems under alternative managerial schemes and levels of exogenous nutrient loading.

Analysis of phytoplankton community structure using similarity indices: a new methodology for discriminating among eutrophication levels in coastal marine ecosystems.

Nine similarity indices based on phytoplankton community structure were examined for their sensitivity to assess different levels of eutrophication. Two phytoplankton data sets, one from an open coastal system and one from a semi-enclosed gulf, associated with different nutrient dynamics and circulation patterns were used for evaluating the indices. The results have shown that similarity indices, measuring interspecific association and resemblance of phytoplankton communities between enriched areas and control sites, were effective for detecting spatial and temporal dissimilarities in coastal marine ecosystems. The structure of the oligotrophic habitat as a potential source of ambiguity for the results was discussed, whereas the validity ranges and the potential applicability of this method were deemed to be dependent on the size of the fraction of the common species among the samples, and the similarity of the classification patterns resulted from this subcategory and those extracted from the overall community data. Furthermore, the study provides a new technique based on the use of the "Box and Whisker Plot" designed to distinguish opportunistic and rare phytoplanktonic species. The similarity indices, applied solely to the dominant species abundance, were more sensitive to resolve eutrophic, mesotrophic and oligotrophic conditions. This procedure can be proposed as an effective methodology for water characterization and can also be used as a qualitative tracer for detecting renewal processes of coastal marine ecosystems.

Developing an optimal sampling design. A case study in a coastal marine ecosystem.

The development of a sampling design for optimising sampling site locations collected from a coastal marine environment has been the purpose of the present work; application of statistical analysis and spatial autocorrelation methods have been carried out. The dataset included data collected from 34 sampling sites spaced out in the Strait of Lesbos, Greece, arranged in a 1 x 1 NM grid. The coastal shallow ecosystem was subdivided into three zones, an inner one (7 stations), a middle one (16 stations) and an offshore zone (11 stations). The standard error of the chlorophyll-a concentrations in each zone has been used as the criterion for the sampling design optimisation, resulting into reallocation of the sampling sites into the three zones. The positions of the reallocated stations have been assessed by estimation of the spatial heterogeneity and anisotropy of chlorophyll-a concentrations using variograms. Study of the variance of the initial dataset of the inner zone taking into account spatial heterogeneity, revealed two different sub-areas and therefore, the number of the inner stations has been reassessed. The proposed methodology eliminates the number of sampling sites and maximises the information of spatial data from marine ecosystems. It is described as a step-by-step procedure and could be widely applied in sampling design concerning coastal pollution problems.

Evaluation of Phytoplankton Community Indices for Detecting Eutrophic Trends in the Marine Environment.

Twenty two diversity, evenness and dominance indices based on phytoplankton community structure were examined for their sensitivity to assess eutrophic conditions. Data from two sampling sites, one eutrophic and one oligotrophic, were used as reference data-sets for evaluating the indices. McNaughton's dominance index, cell number, species number (Hill's N0), Kothe's species deficit, Odum's species per thousand individuals and Evenness E2, E3 seemed to be the most sensitive indices for discriminating between eutrophic and oligotrophic conditions. A case study was also performed using a data-set from ten stations spaced along the coastal area of the city of Rhodes, Aegean Sea, Greece to find out which of the indices were appropriate to assess different levels of eutrophication. Kothe's species deficit, Hill's N0 (species number), Margalef's and Gleason's indices have shown the highest sensitivity to resolve oligotrophic, mesotrophic and eutrophic conditions.