An empirical approach to the determination of metal regional Sediment Quality Guidelines, in marine waters, within the European Water Framework Directive

Menchaca, Iratxe; Borja, Ángel; Belzunce-Segarra, María Jesús; Franco, Javier; Garmendia, Joxe Mikel; Larreta, Joana; Rodríguez, José Germán

doi:10.1080/02757540.2011.651129

Cited by 16 publications

(4 citation statements)

References 57 publications

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“…The microbe‐based index microgAMBI followed PI5y slightly better (Figure 4b, Table 2) while both AMBI and microgAMBI appeared more correlated with organic matter content (PI OM; see Table 2 and Figure ). Cohen's kappa values for these comparisons are only indicative, because status group limits were based on reference values of individual abiotic parameters (Aylagas et al., 2017; Menchaca et al., 2012) not directly comparable to AMBI values.…”

Section: Resultsmentioning

confidence: 99%

“…Cohen's kappa values for these comparisons are only indicative, because status group limits were based on reference values of individual abiotic parameters(Aylagas et al, 2017;Menchaca et al, 2012) not directly comparable to AMBI values. The PI5y values predicted by RF machine learning through cross-validation were more strongly correlated to true values, compared to AMBI or microgAMBI, and agreed for 50% (n = 113) of ecological status category predictions with reference values (Figure4).…”

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confidence: 99%

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A microbial mandala for environmental monitoring: Predicting multiple impacts on estuarine prokaryote communities of the Bay of Biscay

et al. 2020

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Routine monitoring of benthic biodiversity is critical for managing and understanding the anthropogenic impacts on marine, transitional and freshwater ecosystems.However, traditional reliance on morphological identification generally makes it costprohibitive to increase the scale of monitoring programmes. Metabarcoding of environmental DNA has clear potential to overcome many of the problems associated with traditional monitoring, with prokaryotes and other microorganisms showing particular promise as bioindicators. However, due to the limited knowledge regarding the ecological roles and responses of environmental microorganisms to different types of pressure, the use of de novo approaches is necessary. Here, we use two such approaches for the prediction of multiple impacts present in estuaries and coastal areas of the Bay of Biscay based on microbial communities. The first (Random Forests) is a machine learning method while the second (Threshold Indicator Taxa Analysis and quantile regression splines) is based on de novo identification of bioindicators. Our results show that both methods overlap considerably in the indicator taxa identified, but less for sequence variants. Both methods also perform well in spite of the complexity of the studied ecosystem, providing predictive models with strong correlation to reference values and fair to good agreement with ecological status groups. The ability to predict several specific types of pressure is especially appealing. The cross-validated models and biotic indices developed can be directly applied to predict the environmental status of estuaries in the same geographical region, although more work is needed to evaluate and improve them for use in new regions or habitats.

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Section: Resultsmentioning

confidence: 99%

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confidence: 99%

A microbial mandala for environmental monitoring: Predicting multiple impacts on estuarine prokaryote communities of the Bay of Biscay

et al. 2020

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“…Briefly, OM content was determined by loss of weight on ignition at 450°C during 6 h (Dean, 1974). Metal concentrations (Cd, Cr, Cu, Ni, Hg, Pb and Zn) were analyzed within the fine‐sediment content sediment fraction (b63 μm) (Kersten & Smedes, 2002) obtained by sieving samples previously oven‐dried at 60°C and using the acid‐extractable metal concentration method by means of an acid mixture of HCl/HNO3 (1:2, v/v) (Menchaca et al., 2012). The concentration of polychlorinated biphenyls and polycyclic aromatic hydrocarbons was determined following the procedure described by Bartolomé et al.…”

Section: Methodsmentioning

confidence: 99%

Toward functional profiling for eDNA‐based monitoring in coastal environments: A comparison of three approaches

Abad‐Recio,

Alonso‐Sáez,

Lanzén

2024

Environmental DNA

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Coastal environments, crucial and intricate ecosystems, face threats from human activities like pollution, eutrophication, and climate change. Monitoring microbial communities can aid in understanding the state of these habitats. Environmental DNA (eDNA) techniques provide efficient and comprehensive monitoring by capturing broader diversity. Besides structural profiling, eDNA methods allow the study of functional profiles, encompassing the genes within the microbial community. In this study, three methodologies were compared for functional profiling of microbial communities in estuarine and coastal sites in the Bay of Biscay. The methodologies included inference from 16S metabarcoding data using Tax4Fun, GeoChip microarrays, and shotgun metagenomics. Results revealed significant functional diversity across all sampling sites, irrespective of their environmental status. Most predicted KEGG Orthologs (KOs) showed consistency between metagenomics and Tax4Fun datasets, with correlated abundances. However, abundances derived from GeoChip did not correlate with either dataset. When comparing estuaries based on environmental status, Tax4Fun and metagenomics identified over 24% of KOs with significantly different abundances. KOs overrepresented in estuaries with a poor ecological status displayed an abundance of pathways associated with anaerobic metabolism, such as methanogenesis.

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“…(iv) Using information from gradients of pressure, which can be used to set the targets. (v) Using targets from existing literature, for indicators used in similar habitats, e.g., Sediment Quality Guidelines at regional level (Bakke et al, 2010;Menchaca et al, 2012Menchaca et al, , 2014. (vi) Model a target, such the proposal in Rossberg et al (2017), although there are numerous issues in developing and applying such models (see a discussion on the topic in Borja et al, 2012).…”

Section: Spatialmentioning

confidence: 99%

Yes, We Can! Large-Scale Integrative Assessment of European Regional Seas, Using Open Access Databases

et al. 2019

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Substantial progress has been made in assessing marine health in an integrative way. However, managers are still reluctant in undertaking such assessments, because: (i) lack of indicators; (ii) absence of targets; (iii) difficulty of aggregating indicators from different ecosystem components, habitats, and areas; (iv) absence of criteria on the number of indicators to be used; (v) discussion on the use of "one-out, all-out" (OOAO) principle in aggregating; and (vi) lack of traceability when integrating data. Our objective was, using open access databases with indicators across all the European seas with agreed targets, to demonstrate if the Nested Environmental status Assessment Tool (NEAT), can be used at the European scale, serving to managers and policy-makers as a tool to assess the environmental status under the Marine Strategy Framework Directive (MSFD). We have used MSFD Descriptor D3 (commercial fish) from 341 stocks, 119 species and two indicators from each of them (years 2013-2015); D5 (eutrophication) with 90th percentile of Chlorophyll-a (years 2009-2014); and D8 (contaminants), with Anthracene, Fluoranthene, Naphthalene, Cadmium, Nickel, and Lead as indicators (years 2009-2013). We have calculated the environmental status for each European subdivision, subregion, and regional sea, nested at different levels. The analyses include weighting and no-weighting by each assessment area; for ecosystem component (water column, phytoplankton, fish, crustaceans, and molluscs); descriptor (three), and habitat (pelagic, demersal/benthic), with the confidence value of the status. A sensitivity analysis was undertaken to determine a minimum number of indicators to include for a robust assessment. We demonstrated that using NEAT in assessing the status of large marine areas, by aggregating indicators, ecosystem components and descriptors, at different spatial scales, can remove at least four out of the six barriers that managers and policy-makers confront when undertaking such assessments. This can be done by using open-access databases and already established targets. Aggregating indicators of different origin is possible. Around 40 indicators seem to be enough to obtain robust assessments. It is better to integrate the assessment items using an ecosystem-based approach, rather than using the OOAO principle. Using NEAT, this approach supports identifying the problematic environmental issues needing management attention and measures.

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An empirical approach to the determination of metal regional Sediment Quality Guidelines, in marine waters, within the European Water Framework Directive

Cited by 16 publications

References 57 publications

A microbial mandala for environmental monitoring: Predicting multiple impacts on estuarine prokaryote communities of the Bay of Biscay

A microbial mandala for environmental monitoring: Predicting multiple impacts on estuarine prokaryote communities of the Bay of Biscay

Toward functional profiling for eDNA‐based monitoring in coastal environments: A comparison of three approaches

Yes, We Can! Large-Scale Integrative Assessment of European Regional Seas, Using Open Access Databases

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