Mapping an ecosystem service: A quantitative approach to derive fish feeding ground maps**This study was supported by Norwegian Financial Mechanism (project No. LT0047) and BONUS PREHAB.

AbstractThis 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

Diskrečių skirstinių taikymas duomenų apie gamtos plotų padengimą Bajesinėje analizėje

Classical statistical methods do not always provide desired results for every situation. Therefore, new alternative methods of data analysis are in demand. As the computational power becomes more modern, Bayes statistical methods are increasingly applied for statistical data analysis. This article describes several discrete models for analyzing nature area coverage. These models can be applied for analysis of such areas as forests, water ponds, soil, etc. when data is provided in integer data in percent. Poisson and negative binomial distributions are used in this article. Unknown parameters of the models were estimated using Bayes statistical methods in OpenBUGS modeling environment. The models of nature area coverage analysis were implemented using the data of Baltic Sea bottom algae coverage. This article analyzes coverage dependence of abiotic and physical factors.Klasikinės statistikos metodai ne visada leidžia pasiekti norimų rezultatų, todėl ieškoma alternatyvių duomenų analizės metodų. Dėl modernėjančios skaičiuojamosiostechnikos, statistinei duomenų analizei vis plačiau taikomi Bajesinės statistikos metodai.Šiame darbe sudaromi keli diskrečiųjų skirstinių modeliai įvairių gamtos plotų padengimui analizuoti. Šie modeliai gali būti pritaikyti tokių gamtos plotų, kaip miškų, vandens telkinių dugno, dirvožemio analizei, kai duomenys pateikiami procentiniais dydžiais, išreikštais sveikaisiais skaičiais. Šiame darbe sudaromi modeliai panaudojant kelis skirtingus diskrečiuosius skirstinius, t. y. Puasono ir neigiamai binominį skirstinį. Naudojant Bajesinės statistikosmetodus OpenBUGS modeliavimo aplinkoje įvertinami nežinomi modelio parametrai. Atliekama parametrų įverčių patikimumo statistikų analizė, realizuota OpenBUGS modeliavimo aplinkoje. Gamtos plotų padengimo analizei skirtų modelių realizavimui buvo pasirinkti duomenys, aprašantys Baltijos jūros dugno padengimą raudondumbliu šakotuoju banguoliu. Šiame darbe tiriama padengimo priklausomybė nuo kelių regresorių, aprašančių abiotinius ir fizinius veiksnius

European marine biodiversity monitoring networks: Strengths, weaknesses, opportunities and threats

© 2016 Patrício, Little, Mazik, Papadopoulou, Smith, Teixeira, Hoffmann, Uyarra, Solaun, Zenetos, Kaboglu, Kryvenko, Churilova, Moncheva, Bucas, Borja, Hoepffner and Elliott. 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 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

Satellite-assisted monitoring of water quality to support the implementation of the Water Framework Directive

The EU Water Framework Directive1 (WFD) is an ambitious legislation framework to achieve good ecological and chemical status for all surface waters and good quantitative and chemical status for groundwater by 2027. A total of 111,062 surface waterbodies are presently reported on under the Directive, 46% of which are actively monitored for ecological status. Of these waterbodies 80% are rivers, 16% are lakes, and 4% are coastal and transitional waters. In the last assessment, 4% (4,442) of waterbodies still had unknown ecological status, while in 23% monitoring did not include in situ water sampling to support ecological status assessment2. For individual (mainly biological) assessment criteria the proportion of waterbodies without observation data is much larger; the full scope of monitoring under the WFD is therefore still far from being realised. At the same time, 60% of surface waters did not achieve ‘good’ status in the second river basin management plan and waterbodies in Europe are considered to be at high risk of having poor water quality based on combined microbial, physical and physicochemical indicators3

Recent distribution and stock assessment of the red alga Furcellaria lumbricalis on an exposed Baltic Sea coast: combined use of field survey and modelling methods

Recent results of field studies on the exposed coast of Lithuania were used to model the area occupied by the red alga Furcellaria lumbricalis using the Natural Neighbor interpolation technique, while linear regression was applied to estimate the species’ standing stock. The area covered by F. lumbricalis extended for 26 km along thecoast between depths of 1 and 15 m. The maximum species cover in the study area ranged between 4 and 10 m depth, which is one of the widest in the Baltic Sea. The modelled area of F. lumbricalis covered 35 ± 11 km2 with a total biomass of 7554 ± 3813 t

Distribution of charophyte oospores in the Curonian Lagoon and their relationship to environmental forcing

Lack of knowledge about distribution of charophyte fructifications and importance of environmental conditions in the Baltic Sea coastal waters fostered us to assess the spatial-temporal patterns of oospore bank in relationship with environmental factors in the Curonian Lagoon (Lithuanian part). We mapped the distribution of oospores in 2017–2019. The importance of environmental factors was determined by the cluster analysis and boosted regression trees. Four oospores species were recorded up to 4 m depth. The highest mean densities (58,000 ind·m−2 ) of viable fructifications were found along the eastern shore, where the densest charophyte stands were recorded. Viable fructifications showed a clear pattern of filling the oospore bank after the vegetation season and a depletion during the summer as they germinated. The distance from charophyte stands, salinity, bottom slope aspect, and wave exposure were the most important environmental variables. Full fructifications mostly occurred within 1.5 salinity

Evaluation of common reed (Phragmites australis) bed changes in the context of management using earth observation and automatic threshold

ABSTRACTThere is no easy in situ way to monitor large waterbodies for their aquatic vegetation change, especially during mowing works. The objective of this study is to choose the best automatic workflow that would estimate a change in the reed bed area and density over time. This workflow will assess the mowing effect on reeds over 3 years in the Plateliai Lake (Lithuania). Sentinel-2/MSI images were used to derive reed beds using water adjusted vegetation index (WAVI) and normalised difference water index (NDWI). The indices were classified using seven different binary thresholding algorithms. Results were validated with orthophotos gathered from unmanned aerial vehicle surveys in mowed regions and one reference area. Analysis demonstrated that using the NDWI together with the Yen thresholding algorithm generated the best accuracy results, with the highest accuracy resulting with high vegetation areas where the area under the curve values were 0.85 ± 0.17. The changes in estimated density did not show a significant correlation between mowed and reference areas and years. The results indicate that Sentinel-2/MSI is a feasible tool for the evaluation of reed bed change. On this basis, it is recommended to implement it as an additional monitoring tool that covers larger areas than in situ monitoring

Baltic herring (Clupea harengus membras) spawning grounds on the Lithuanian coast: current status and shaping factors* This study was supported by the Norwegian Financial Mechanism (project No. LT0047).

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

An Evaluation of Sun-Glint Correction Methods for UAV-Derived Secchi Depth Estimations in Inland Water Bodies

This study investigates the application of unoccupied aerial vehicles (UAVs) equipped with a Micasense RedEdge-MX multispectral camera for the estimation of Secchi depth (SD) in inland water bodies. The research analyzed and compared five sun-glint correction methodologies—Hedley, Goodman, Lyzenga, Joyce, and threshold-removed glint—to model the SD values derived from UAV multispectral imagery, highlighting the role of reflectance accuracy and algorithmic precision in SD modeling. While Goodman’s method showed a higher correlation (0.92) with in situ SD measurements, Hedley’s method exhibited the smallest average deviation (0.65 m), suggesting its potential in water resource management, environmental monitoring, and ecological modeling. The study also underscored the quasi-analytical algorithm (QAA) potential in estimating SD due to its flexibility to process data from various sensors without requiring in situ measurements, offering scalability for large-scale water quality surveys. The accuracy of SD measures calculated using QAA was related to variability in water constituents of colored dissolved organic matter and the solar zenith angle. A practical workflow for SD acquisition using UAVs and multispectral data is proposed for monitoring inland water bodies