In this study bio-optical water quality indicators, chlorophyll a, colored dissolved organic matter (CDOM), and total suspended matter (TSM) were derived from the Envisat-MERIS satellite data and were compared with in situ measurements collected in the Lithuanian optically Case 2 coastal waters of the Baltic Sea. Eight MERIS full-resolution Level 1b images, acquired during late spring and summer 2010, were processed using five, neural network-based processors for optically Case 2 or coastal and inland waters: FUB, C2R, Eutrophic, Boreal, and standard MERIS Level 2. Results showed that the FUB processor provided the most accurate estimates of the concentration of chlorophyll a [R 2 ¼ 69%; mean absolute errorðMAEÞ ¼ 7.76 mg∕m 3 ] and TSM (R 2 ¼ 89%; MAE ¼ 3.93 g∕m 3). In situ CDOM absorption was most accurately estimated using the Boreal processor (R 2 ¼ 69%; MAE ¼ 0.20 1∕m). We analyzed the factors that were most influential in explaining the differences in the accuracy and found that the Secchi depth and the sampling time were the most important factors. The greatest differences between satellite-derived and in situ values of water quality indicators were in correspondence with the lowest Secchi depth, suggesting that the plume zone created by freshwater coming from the hyper-eutrophic lagoon was the most sensitive region for the validation. The evident match between in situ measurements and satellite-based estimates was observed when field measurements were acquired 1-2 h before to approximately 2-4 h after the satellite overpass. Results of this validation work confirmed that remote sensing techniques are suitable for monitoring the changes of optical constituents in Lithuanian coastal waters.

Bučas, M., Bergström, U., Downie, A-L., Sundblad, G., Gullström, M., von Numers, M., Šiaulys, A., and Lindegarth, M. 2013. Empirical modelling of benthic species distribution, abundance, and diversity in the Baltic Sea: evaluating the scope for predictive mapping using different modelling approaches. – ICES Journal of Marine Science, 70: 1233–1243. The predictive performance of distribution models of common benthic species in the Baltic Sea was compared using four non-linear methods: generalized additive models (GAMs), multivariate adaptive regression splines, random forest (RF), and maximum entropy modelling (MAXENT). The effects of data traits were also tested. In total, 292 occurrence models and 204 quantitative (abundance and diversity) models were assessed. The main conclusions are that (i) the spatial distribution, abundance, and diversity of benthic species in the Baltic Sea can be successfully predicted using several non-linear predictive modelling techniques; (ii) RF was the most accurate method for both models, closely followed by GAM and MAXENT; (iii) correlation coefficients of predictive performance among the modelling techniques were relatively low, suggesting that the performance of methods is related to specific responses; (iv) the differences in predictive performance among the modelling methods could only partly be explained by data traits; (v) the response prevalence was the most important explanatory variable for predictive accuracy of GAM and MAXENT on occurrence data; (vi) RF on the occurrence data was the only method sensitive to sampling density; (vii) a higher predictive accuracy of abundance models could be achieved by reducing variance in the response data and increasing the sample size.

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Fucus vesiculosus L. is an important habitat‐forming macroalga both in the saline and high diverse North Sea and the diluted and low diversity Baltic Sea. Despite its importance, comparisons of the spatial patterns of its epiphytes have rarely been reported. In this study we examined the species composition and density of macro‐epiphytes and mobile fauna on the canopy‐forming macroalga F. vesiculosus inhabiting different regimes of wave exposure in the North and Baltic Seas. The North and Baltic Seas had distinct epiphyte and mobile faunal communities. Wave exposure and segments of host fronds significantly contributed to the variability in species composition and dominance structure of epiphytes on F. vesiculosus in the North Sea and Baltic Sea. The study indicated that there is no clear spatial scale where environmental variables best predicted epiphytic and mobile faunal communities, and the formation of epiphytic and faunal communities is an interplay of factors operating through micro‐ to regional scales.

By 2020, European Union Member States should achieve Good Environmental Status (GES) for 11 environmental quality descriptors for their marine waters to fulfill the Marine Strategy Framework Directive (MSFD). By the end of 2015, in coordination with the Regional Seas Conventions, each EU Member State was required to develop a marine strategy for their waters, together with other countries within the same marine region or sub-region. Coherent monitoring programs, submitted in 2014, form a key component of this strategy, which then aimed to lead to a Program of Measures (submitted in 2015). The European DEVOTES FP7 project has produced and interrogated a catalog of EU marine monitoring related to MSFD descriptors 1 (biological diversity), 2 [non-indigenous species (NIS)], 4 (food webs), and 6 (seafloor integrity). Here we detail the monitoring activity at the regional and sub-regional level for these descriptors, as well as for 11 biodiversity components, 22 habitats and the 37 anthropogenic pressures addressed. The metadata collated for existing European monitoring networks were subject to a SWOT (strengths, weaknesses, opportunities, and threats) analysis. This interrogation has indicated case studies to address the following questions: (a) what are the types of monitoring currently in place? (b) who does what and how? (c) is the monitoring fit-for-purpose for addressing the MSFD requirements? and (d) what are the impediments to better monitoring (e.g., costs, shared responsibilities between countries, overlaps, co-ordination, etc.)? We recommend the future means to overcome the identified impediments and develop more robust monitoring strategies. As such the results are especially relevant to implementing comprehensive and coordinated monitoring networks throughout Europe, for marine policy makers, government agencies and regulatory bodies. It is emphasized that while many of the recommendations given Patrício et al.European Marine Biodiversity Monitoring Networks here require better, more extensive and perhaps more costly monitoring, this is required to avoid any legal challenges to the assessments or to bodies and industries accused of causing a deterioration in marine quality. More importantly the monitoring is required to demonstrate the efficacy of management measures employed. Furthermore, given the similarity in marine management approaches in other developed systems, we consider that the recommendations are also of relevance to other regimes worldwide.

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