A thorough understanding of the global carbon pools and cycle is essential for understanding and predicting the effects of climate change. Coastal waters play a key role in the global carbon cycle but remain poorly understood due to their optical complexity, high spatial variability, and sensitivity to climate change. Satellite remote sensing data can provide high spatial and temporal resolution for carbon monitoring at local, regional, and global scales. This study estimates the potential of Sentinel-2 MSI (S2) and Sentinel-3 OLCI (S3) for mapping carbon fractions in coastal waters. In situ hyperspectral reflectance measurements and concentrations of different carbon fractions, namely Total Organic Carbon (TOC), Dissolved Organic Carbon (DOC), Particulate Organic Carbon (POC), and Dissolved Inorganic Carbon (DIC), were used. Bio-optical and physical water parameters, as well as carbon fractions, were measured in the coastal areas of the eastern Baltic Sea from 2023 to 2024. In situ reflectance spectra were recalculated to S2 and S3 band reflectance using their respective spectral response functions. Regression models, including linear regression and machine learning methods, were developed and validated against in situ data to estimate carbon fractions. For S2, the combinations of green and red or red-edge bands achieved the best performance in carbon retrieval, with R2 values of 0.67, 0.64, and 0.56 for TOC, DOC, and DIC, respectively. The corresponding MAPE values ranged from 14% to 18%, and biases were close to zero. Slightly higher accuracies were obtained with S3 simulations. The S3 models that used reflectance at 490, 620, and 665 nm produced the most accurate estimates for both TOC (R2 = 0.71) and DOC (R2 = 0.67). For DIC, the best predictive model combined information from 510, 665, and 709 nm bands, achieving R2 of 0.62. Among the tested optical proxies, CDOM absorption at 443 nm showed the most consistent relationship with TOC, DOC, and DIC (R2 = 0.56–0.30). The study represents a significant step forward in the remote sensing of coastal waters, and if adopted, the proposed carbon-fraction products could enable substantial progress across various fields, from carbon-cycle research to monitoring and policymaking.
We analyze a class of nonlinear models of cognitive dynamics with inertia-like effects and periodic training. By combining a differential-algebraic formulation with topological degree methods, we prove the existence of periodic solutions whose period matches the external forcing.
Maritime Spatial Planning (MSP) has emerged as a central governance tool to balance ecological, social, and economic uses of marine space, while Marine Protected Areas (MPAs) remain essential for biodiversity conservation and ecosystem resilience. Effective integration of MPAs into MSP can enhance conservation outcomes and reduce conflicts with human activities, yet the degree of integration across the European Union (EU) remains highly uneven. This study examines how MPAs are embedded within national MSP frameworks in 20 EU Member States, aiming to classify, compare, and explain differences in integration levels. A typology of four integration levels is introduced, ranging from MPAs as primary drivers of MSP to their treatment as passive spatial layers. The methodology combines the development and application of a set of questions directed at MSP experts with the use of a decision tree and allocation criteria designed to assess responses and classify countries according to their level of MPA-MSP integration. Results reveal substantial disparities across EU Member States. Belgium, Germany, Latvia, Slovenia, Sweden and the Netherlands showed the strongest degree of integration, with conservation objectives embedded in MSP provisions and influencing cross-sectoral planning decisions. In contrast, most countries incorporated MPAs mainly through environmental assessment instruments or treated them as existing spatial layers, environmental constraints, or separate legal instruments. Key barriers include fragmented governance structures, limited translation of environmental assessments into binding spatial decisions, weak links between MSP and MPAs management, uneven monitoring and enforcement capacity, and limited mechanisms for stakeholder coordination. Advancing MPA-MSP integration requires stronger legal frameworks, adaptive management strategies, ecological connectivity, and inclusive governance processes. By providing a systematic comparison and highlighting best practices, this study provides recommendations to foster more cohesive, resilient, and biodiversity-informed marine governance.
Following the new ESPEN Standard Operating Procedures, the previous 2019 guideline to provide best medical nutritional therapy to critically ill patients has been shortened and partially revised. Following this update, we propose this publication as a practical guideline based on the published scientific guideline, but shortened and illustrated by flow charts. The main goal of this practical guideline is to increase understanding and allow the practitioner to implement the Nutrition in the ICU guidelines. All the items discussed in the previous guidelines are included as well as special conditions.
Context. The distances to evolved massive stars in the Milky Way are poorly constrained by Gaia parallaxes because these stars are bright and variable. This makes it difficult to determine their fundamental stellar parameters, such as radius or luminosity, and infer their evolutionary states. Aims. We aim to improve the distance estimates of yellow hypergiants (YHGs) and yellow supergiants (YSGs) by identifying possible cluster and association memberships. Using these distances, we derived updated luminosities and revised their positions in the Hertzsprung-Russell diagram. Methods. We compiled a sample of 35 luminous yellow massive stars (YHGs and the most luminous YSGs) from the literature. We used Gaia DR3 astrometry to identify possible membership in clusters and OB associations. We derived distances by combining the parallaxes of nearby co-moving stars. We independently validated these distances by comparing the stellar radial velocities to the Galactic H I kinematic map. We combined angular diameters and effective temperature values from the literature with the new distances to estimate the luminosities. Results. We improved the distance estimates for 28 of the 35 stars through association with co-moving stellar groups. For an additional 6 stars, we provided distance estimates based on the H I kinematic map. For one star, the distance remains unclear. Most YSGs are members of young stellar populations, while the environments of the YHGs are more diverse, and the origin populations for some of them remain unclear. We derived updated luminosities for a subset of 20 stars. Most YHGs have luminosities above log L/L-circle dot = 5.4, while YSGs occupy a wider range of luminosities, and the luminosities of the most luminous YSGs are similar to those of YHGs.
