Increased contribution of parasites in microbial eukaryotic communities of different Aegean Sea coastal systems

Background-Aim

Protistan communities have a major contribution to biochemical processes and food webs in coastal ecosystems. However, related studies are scarce and usually limited in specific groups and/or sites. The present study examined the spatial structure of the entire protistan community in seven different gulfs and three different depths in a regional Mediterranean Sea, aiming to define taxa that are important for differences detected in the marine microbial network across the different gulfs studied as well as their trophic interactions.

Methods

Protistan community structure analysis was based on the diversity of the V2-V3 hypervariable region of the 18S rRNA gene. Operational taxonomic units (OTUs) were identified using a 97% sequence identity threshold and were characterized based on their taxonomy, trophic role, abundance and niche specialization level. The differentially abundant, between gulfs, OTUs were considered for all depths and interactions amongst them were calculated, with statistic and network analysis.

Results

It was shown that Dinophyceae, Bacillariophyta and Syndiniales were the most abundant groups, prevalent in all sites and depths. Gulfs separation was more striking at surface corroborating with changes in environmental factors, while it was less pronounced in higher depths. The study of differentially abundant, between gulfs, OTUs revealed that the strongest biotic interactions in all depths occurred between parasite species (mainly Syndiniales) and other trophic groups. Most of these species were generalists but not abundant highlighting the importance of rare species in protistan community assemblage.

Conclusion

Overall this study revealed the emergence of parasites as important contributors in protistan network regulation regardless of depth.

Drivers of harmful algal blooms in coastal areas of Eastern Mediterranean: a machine learning methodological approach

Harmful algal species are present in the Mediterranean Sea and are often associated with toxic events affecting the nearby coastal zones. The presence of 18 marine microalgae, at genus level, associated with potentially harmful characteristics was predicted using a number of machine learning techniques based exclusively on a small set of abiotic variables, already identified as drivers of blooms. Random Forest (RF) algorithm achieved the best predictive performance by correctly identifying the presence of most genera with a mean of 89.2% of total samples. Although, RF has shown lower predictive performance for genera present in a low number of samples, its predictive power remains at least "fair' in these cases. The main tree-based advantage of RF was thereafter used to assess the importance of the input variables in predicting the presence of the algal genera. Temperature had the most powerful effect on genera's presences, although this effect varies among genera. Finally, the genera were clustered based on their response to the considered abiotic variables and common trends in an ecological context were identified.

Nitrogen as the main driver of benthic diatom composition and diversity in oligotrophic coastal systems

Phytoplankton is the main indicator group for eutrophication in coastal ecosystems, however its high dispersal potential does not enable the assessment of localized effects of coastal nutrient enrichment. Benthic diatoms are sessile microalgae associated with sandy substrates and have the potential to reflect more localized pollution impacts. Although benthic diatoms are widely used bioindicators in freshwater systems, they have rarely been used for assessing the eutrophication status of oligotrophic environments such as the eastern Mediterranean Sea. In the present study, we assess the efficiency of benthic diatoms as bioindicators of nutrient enrichment in oligotrophic coastal systems, by investigating the effect of different physicochemical conditions and nutrient concentrations on the assemblage composition, diversity and individual species populations. To do this, we sampled along a eutrophication gradient formed by anthropogenic nutrient inputs from a metropolitan area. The main driver of assemblage composition, diversity and biomass of diatoms was nitrogen concentration and its temporal and spatial changes. Nitrogen loadings were positively correlated with increased biomass of Cocconeis spp. and negatively correlated with Mastogloia spp. Our findings suggest that in coastal ecosystems of oligotrophic marine ecoregions, benthic diatom assemblage structure and specific taxonomic groups can be reliable predictors of coastal eutrophication offering higher spatial resolution compared to phytoplankton.

Everything is not everywhere: can marine compartments shape phytoplankton assemblages?

The idea that 'everything is everywhere, but the environment selects' has been seminal in microbial biogeography, and marine phytoplankton is one of the prototypical groups used to illustrate this. The typical argument has been that phytoplankton is ubiquitous, but that distinct assemblages form under environmental selection. It is well established that phytoplankton assemblages vary considerably between coastal ecosystems. However, the relative roles of compartmentalization of regional seas and site-specific environmental conditions in shaping assemblage structures have not been specifically examined. We collected data from coastal embayments that fall within two different water compartments within the same regional sea and are characterized by highly localized environmental pressures. We used principal coordinates of neighbour matrices (PCNM) and asymmetric eigenvector maps (AEM) models to partition the effects that spatial structures, environmental conditions and their overlap had on the variation in assemblage composition. Our models explained a high percentage of variation in assemblage composition (59-65%) and showed that spatial structure consistent with marine compartmentalization played a more important role than local environmental conditions. At least during the study period, surface currents connecting sites within the two compartments failed to generate sufficient dispersal to offset the impact of differences due to compartmentalization. In other words, our findings suggest that, even for a prototypical cosmopolitan group, everything is not everywhere.

Optimized Classification Predictions with a New Index Combining Machine Learning Algorithms

Voting is a commonly used ensemble method aiming to optimize classification predictions by combining results from individual base classifiers. However, the selection of appropriate classifiers to participate in voting algorithm is currently an open issue. In this study we developed a novel Dissimilarity-Performance (DP) index which incorporates two important criteria for the selection of base classifiers to participate in voting: their differential response in classification (dissimilarity) when combined in triads and their individual performance. To develop this empirical index we firstly used a range of different datasets to evaluate the relationship between voting results and measures of dissimilarity among classifiers of different types (rules, trees, lazy classifiers, functions and Bayes). Secondly, we computed the combined effect on voting performance of classifiers with different individual performance and/or diverse results in the voting performance. Our DP index was able to rank the classifier combinations according to their voting performance and thus to suggest the optimal combination. The proposed index is recommended for individual machine learning users as a preliminary tool to identify which classifiers to combine in order to achieve more accurate classification predictions avoiding computer intensive and time-consuming search.

Lumpy species coexistence arises robustly in fluctuating resource environments

The effect of life-history traits on resource competition outcomes is well understood in the context of a constant resource supply. However, almost all natural systems are subject to fluctuations of resources driven by cyclical processes such as seasonality and tidal hydrology. To understand community composition, it is therefore imperative to study the impact of resource fluctuations on interspecies competition. We adapted a well-established resource-competition model to show that fluctuations in inflow concentrations of two limiting resources lead to the survival of species in clumps along the trait axis, consistent with observations of "lumpy coexistence" [Scheffer M, van Nes EH (2006) Proc Natl Acad Sci USA 103:6230-6235]. A complex dynamic pattern in the available ambient resources arose very early in the self-organization process and dictated the locations of clumps along the trait axis by creating niches that promoted the growth of species with specific traits. This dynamic pattern emerged as the combined result of fluctuations in the inflow of resources and their consumption by the most competitive species that accumulated the bulk of biomass early in assemblage organization. Clumps emerged robustly across a range of periodicities, phase differences, and amplitudes. Given the ubiquity in the real world of asynchronous fluctuations of limiting resources, our findings imply that assemblage organization in clumps should be a common feature in nature.

Do 2006/7/EC European Union Bathing Water Standards exclude the risk of contact with Salmonella or Candida albicans?

The purpose of this study was to evaluate the efficiency of the recent (2006) European Union Directive concerning the management of bathing water quality to exclude the presence of pathogens from complying waters. Coastal water samples were classified according to the Directive. 2.5% of 'excellent' water contained Salmonella and 39.2% Candida albicans 11.8% of samples in category 'good' were Salmonella positive and 35.2% were C.albicans positive. When the USEPA criterion for marine waters was applied to the same dataset, fewer samples complied, however 6.0% of the complying samples contained Salmonella. The results suggest that the bacterial indicator threshold levels for marine recreational water quality of the 2006/7/EC European Union Directive do not fully exclude contact of bathers with dangerous pathogens. Enterococci, if used as the sole index, appear to form a more reliable proxy of the risk of contact with Salmonella.

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.