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Complex bottom topography and the presence of floating ice significantly complicates the use of traditional sampling methods in Arctic coastal waters, forcing to look for alternative approaches. One such technique is underwater imagery, which has grown in popularity in recent decades based on its effectiveness in hard-to-reach places. We demonstrate that an underwater video mosaic can be a reliable method for comparative analysis of Arctic habitats under the glacier influence and glacier influence-free habitats. The filming was carried out in the upper sublittoral (2-65 m) of Hornsund and Isfjorden areas, representing two ice-free and two glaciated bays. Video footage was obtained using an ROV mounted and "drop-down" video cameras and transformed into 148 video mosaics. Based on the lowest possible taxonomic level, 31 biological features (morphospecies) were identified and ascribed to benthic functional groups based on their feeding and mobility type. The morphospecies and functional groups were used for the comparative analysis of benthic communities. The study found that melting glaciers have a stronger impact on the structure of benthic communities across geographical areas. Morphological and functional composition of macrofauna reflected conditions in glacier influence and influence-free, and turbid water riverine bays. We discovered greater abundances of motile scavengers in glacier influence bays whereas glacier influence-free bay had more sessile suspension filters and glacier influence-free riverine bay was dominated by discreetly motile and deposit feeders. Underwater imagery mosaics have proven to be a fairly reliable tool for fieldwork-efficient quantitative characterization of benthic communities in the hard-to-reach Arctic's upper sublittoral.

Pikeperch (Sander lucioperca) is a European fresh and brackish water piscivorous fish, important as both a key predator and a valuable commercial and recreational fisheries species. There are concerns that some stocks are depleted due to overfishing and environmental changes. We review data collection and population assessments currently used for nine pikeperch stocks across six European countries and apply a unified assessment framework to evaluate population status and trends. For this we first standardised commercial, scientific, and recreational catch-per-unit-effort (CPUE) and catch time series and then applied Bayesian surplus production models. Our results showed that three stocks (including two in the Baltic Sea) were strongly depleted, with estimated biomasses considerably lower than the biomass at maximum sustainable yield (Bmsy). Other stocks were either close or higher than their estimated Bmsy. Looking at the trends, we find that four stocks (Lake Oulujärvi, Kvädöfjärden, Lake Peipsi and Lipno) showed increasing biomass trends and two (Curonian Lagoon, Galtfjärden) had a strong decline in biomass. In most cases the stocks with clear signs of recovery were also those for which strong management strategies have been implemented. We find that, despite pikeperch being one of the most valuable inland fisheries, formalised stock assessments and regular surveys remain rare. Importantly, although most stocks are strongly targeted by recreational fishing, estimates of recreational catch are highly uncertain. We conclude that data limited stock assessment methods are useful for assessing fish population status and highlight an urgent need to improve pikeperch scientific monitoring and assessment of recreational catches.

Underwater video surveys play a significant role in marine benthic research. Usually, surveys are filmed in transects, which are stitched into 2D mosaic maps for further analysis. Due to the massive amount of video data and time-consuming analysis, the need for automatic image segmentation and quantitative evaluation arises. This paper investigates such techniques on annotated mosaic maps containing hundreds of instances of brittle stars. By harnessing a deep convolutional neural network with pre-trained weights and post-processing results with a common blob detection technique, we investigate the effectiveness and potential of such segment-and-count approach by assessing the segmentation and counting success. Discs could be recommended instead of full shape masks for brittle stars due to faster annotation among marker variants tested. Underwater image enhancement techniques could not improve segmentation results noticeably, but some might be useful for augmentation purposes.

The invasive round goby has established a viable population within 9 years of its first introduction to Lithuanian coastal waters (SE Baltic Sea). During its expansion phase, abundances increased 23-fold, which led to the near complete eradication of its main prey, the blue mussel, at

International audience; In a world of declining biodiversity, monitoring is becoming crucial. Molecular methods , such as metabarcoding, have the potential to rapidly expand our knowledge of biodiversity, supporting assessment, management, and conservation. In the marine environment, where hard substrata are more difficult to access than soft bottoms for quantitative ecological studies, Artificial Substrate Units (ASUs) allow for standardized sampling. We deployed ASUs within five regional seas (Baltic Sea, Northeast Atlantic Ocean, Mediterranean Sea, Black Sea, and Red Sea) for 12-26 months to measure the diversity and community composition of macroinvertebrates. We identified invertebrates using a traditional approach based on morphological characters, and by metabarcoding of the mitochondrial cytochrome oxidase I (COI) gene. We compared community composition and diversity metrics obtained using the two methods. Diversity was significantly correlated between data types. Metabarcoding of ASUs allowed for robust comparisons of community composition and diversity, but not all groups were successfully sequenced. All locations were significantly different in taxonomic composition as measured with both kinds of data. We recovered previously known regional biogeographical patterns in both datasets (e.g., low species diversity in the Black and Baltic Seas, affinity between the Bay of Biscay and the Mediterranean). We conclude that the two approaches provide complementary information and that metabarcoding shows great promise for marine monitoring. However, until its pitfalls are addressed, the use of metabarcoding in monitoring of rocky benthic assemblages should be used in addition to classical approaches rather than instead of them.

Eutrophication is a serious threat to aquatic ecosystems globally with pronounced negative effects in the Baltic and other semi-enclosed estuaries and regional seas, where algal growth associated with excess nutrients causes widespread oxygen free “dead zones” and other threats to sustainability. Decades of policy initiatives to reduce external (land-based and atmospheric) nutrient loads have so far failed to control Baltic Sea eutrophication, which is compounded by significant internal release of legacy phosphorus (P) and biological nitrogen (N) fixation. Farming and harvesting of the native mussel species (Mytilus edulis/trossulus) is a promising internal measure for eutrophication control in the brackish Baltic Sea. Mussels from the more saline outer Baltic had higher N and P content than those from either the inner or central Baltic. Despite their relatively low nutrient content, harvesting farmed mussels from the central Baltic can be a cost-effective complement to land-based measures needed to reach eutrophication status targets and is an important contributor to circularity. Cost effectiveness of nutrient removal is more dependent on farm type than mussel nutrient content, suggesting the need for additional development of farm technology. Furthermore, current regulations are not sufficiently conducive to implementation of internal measures, and may constitute a bottleneck for reaching eutrophication status targets in the Baltic Sea and elsewhere. Highlights • Mussel farming is a viable internal measure to address Baltic Sea eutrophication. • Rates of nutrient removal depend on salinity at the regional scale and food availability at the local scale. • Cost effectiveness of nutrient removal by mussel farming depends also on farm type. • Total farm area needed for achieving HELCOM nutrient reduction targets is realistic.

In this study, we focused on relatively inexpensive and commonly used fishermen class sonar in order to test its ability to detect stands of charophytes and other groups of submerged angiosperms in the shallow and turbid waters of the Curonian Lagoon. Based on the length of macrophytes, height thresholds (20 and 30 cm) were established in order to distinguish charophytes from submerged angiosperms in obtained echograms. The echograms were visually analysed by two experts. We successfully discriminated 3 echofeatures (bare bottom, stands of charophytes and submerged angiosperms), whereas angiosperms from different morphology groups could not be distinguished. Below 1 m depth, the stands of charophytes and submerged angiosperms were clearly distinguished, thus their maximum colonization depth could be delineated. The accuracy of the discrimination could be reduced by free-drifting mats of filamentous algae, resulting in the overestimation of charophytes. Our approach can be useful for the mapping of monospecific stands of submerged vegetation and could be an important additional tool for macrophyte monitoring and water quality assessment in shallow and turbid waterbodies.

Biological valorisation offers a biocentric approach for intrinsic valuation of the biodiversity of habitats. This conceptual approach was recently applied in few regional studies within Europe using modern statistical approaches. In this study we aim to test the biological valorisation approach that integrates functional diversity of species, species richness, spatial distinctiveness and the status of the communities. Biological value of communities was predicted using Random forest regression method and several environmental factors, such as sediment types, Secchi depth, minimum near-bottom oxygen concentration, near-bottom current velocity, wave generated orbital near-bottom velocity, topographic features. The assessment showed that most valuable habitats are stony bottom reefs with perennial red algae Furcellaria lumbricalis. The obtained map of biological valuation can provide useful information for ecosystem-based management in the studied area indicating conflict zones and protection areas; it could also be adjusted to sensitivity assessment of benthic habitats.

Environmental decision support systems (EDSS) are usually based on environmental models, databases and assessment tools. However, EDSS requires lots of reliable data, which are not readily available, especially information on the distribution of species in marine environments and their dependencies on natural or human pressures. In these cases information is distributed among nominal categories (ranks) which are later used for the decision support. Rules used for assignment into the ranks usually are rough; some of them could be overlapping. But during the decision process the exact rank values are used ignoring the fact that they are derived from the incomplete knowledge. That complicates the comparison of results provided by different cases. In this study a fuzzy logic approach for merging rank and quantitative data with respect to initial accuracy is presented using the example of sensitivity assessment methodology provided by Marine Life Information Network. The proposed approach combines expert knowledge and fuzzy logic methods and provides a possibility to use numerical scales in marine environmental decision support systems, and is a flexible tool for explicit (numerically expressed) sensitivity assessment. This approach can be also applied to other environmental indicators and assessments.

During the 2009 and 2010 seasons Baltic herring ( Clupea harengus membras L.) spawning grounds were investigated by SCUBA divers off the Lithuanian Baltic Sea coast. The most important spawning substrate was a hard bottom overgrown with red algae Furcellaria lumbricalis , but only 32.8% of potentially suitable spawning locations had herring eggs. Bottom geomorphological analysis using multibeam bathymetry revealed that the distribution of spawning beds is not random, but is determined rather by small-scale geomorphological features. The majority of the detected spawning locations were on local elevations characterised by 2.4 ± 1.1 m depth differences and 4.8 ± 1.8 slopes.

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.

The distribution of benthic invertebrates is one of the key parameters for the marine spatial planning and management, however traditionally the data on benthic invertebrates are based on point sampling. Recently statistical methods of predictive modelling are used to create maps of species distribution, nevertheless, no comparative analysis of different modelling methods has been yet performed in the Baltic Sea region. In this study the occurrence and biomass distribution of 23 benthic species in the southeastern Baltic Sea were modelled. A comparison of the following predictive modelling methods was performed: random forests (RF), generalized additive models (GAM), multivariate adaptive regression splines (MARS) and maximum entropy (MaxEnt). In order to assess the consistency of the methods, 100 iterations with different train/test datasets were made for each of them. Random forests achieved the highest predictive performance for both species occurrence and biomass distribution models; also it was the most consistent for different iterations. Predictive performance of GAMs and MARS followed RF, whereas MaxEnt accurately predicted occurrence only for the species with a relatively low distribution range.

This study presents a quantitative approach to mapping benthophagous fish feeding grounds. This approach combines the spatial biomass distribution of benthic prey items and their importance for the diets of predators. A point based biomass data of macrozoobenthos together with a set of environmental factors was used to develop Random Forests models that produce continuous biomass distribution layers for individual prey species. Depending on the diet composition and the importance of prey for fish feeding, these layers are overlaid and an integrated GIS map of the seabed showing the quality of feeding grounds is generated. These maps provide a useful basis for conservation and marine spatial planning. In addition, this method could be applied to the mapping of resources used by other benthophagous organisms. The method is presented using the example of three common Baltic fish species: cod, flounder and viviparous eelpout.

Natural values of marine ecosystems often overlap with human activities. In order to reduce or even eliminate conflicts arising a considerable amount of information is needed: identification of marine activities, their location and scale, as well as the environment's response to separate pressures or different sets of impacts. Furthermore, the value itself can be estimated differently, since valuation assessments range from the anthropocentric to bio-centric point of view. In this study, the concept of a system for mapping the most sensitive marine areas in the Lithuanian marine area is introduced. It is based on the sensitivity assessment numerical scales of species and biotopes. It is being integrated into the geospatial database. Integration of such information into a GIS - based multi-criteria evaluation system can generate sensitivity maps of benthic habitats. These maps can provide important information on the most threatened to anthropogenic pressures marine areas. The system could also serve as a tool for marine spatial planning and providing a good background for decision making, i.e. the placement of activities in the least sensitive areas.