Earth and Environmental Sciences

The Taixinan Basin, located in the northeastern South China Sea along the Taiwan orogenic belt, lies at the intersection between the passive and active margins of the Tainan and Gaoping slopes, where Quaternary deep-water sedimentation is modulated by both gravity-driven and bottom-current processes. This study integrates high-resolution gridded bathymetry, seasonal temperature and salinity fields, and selected multi-channel seismic profiles from the TAIGER and TAICRUST projects to investigate the spatial distribution and evolution of deep-water sedimentary systems. Seismic stratigraphic analysis reveals four Quaternary seismic units bounded by regional discontinuities. SUB represents Early Pleistocene syn-tectonic wedge-top basin fill deposited contemporaneously with thrust deformation and diapiric intrusion under active plate convergence. Above, SU1–SU3 record post-tectonic sedimentation, marking the establishment of the Taixinan contourite system as early as the Early Pleistocene. Contourite development is linked to bottom currents derived from two intermediate water masses—North Pacific Intermediate Water and South China Sea Intermediate Water—which flow eastward along the Tainan Slope before turning southward toward the Gaoping Slope. The Taixinan canyon group—comprising the Penghu, Shoushan, Gaoping, Kaohsiung, Fangliao, and Hongtsai canyons—formed primarily during the Late Pleistocene and constitutes the main sediment conduits along the Gaoping Slope. The interplay between gravity flows and bottom currents generated mixed turbidite–contourite deposits, defining the Taixinan mixed system. Three Quaternary morphosedimentary sectors—erosional, contourite depositional, and mixed depositional—are delineated, demonstrating the topographic control exerted by diapiric ridges on deep-water sedimentary processes. Future improvements require denser seismic survey coverage, integrated with detailed facies analysis and near-bottom oceanographic observations. • Quaternary Taixinan contourite and mixed systems across Tainan and Gaoping slopes . • Multi-channel seismic profiles from TAIGER and TAICRUST projects . • Early Pleistocene contourite system linked to intermediate water masses . • Late Pleistocene canyon-channel system records influence of gravity-flow processes . • Diapiric ridges control erosional and depositional morphosedimentary sectors.

Mangrove sediments harbor highly diverse microbial communities essential to biogeochemical cycling and ecosystem functioning. However, island-scale patterns linking environmental gradients, bacterial diversity, community distribution, and secondary metabolic potential remain unclear. We used high-throughput 16S rRNA amplicon sequencing and sediment physicochemical analyses to investigate bacterial communities across 12 representative mangrove habitats on Hainan Island, China. Bacterial diversity varied substantially among sites (Shannon indices: 5.24–6.98); and community composition was consistently dominated by Proteobacteria, Firmicutes, and Actinobacteria. Electrical conductivity, available nitrogen, and total potassium were identified as the primary environmental variables associated with community structure. Significant correlations between microbial β-diversity and environmental dissimilarity indicated that environmental variation was associated with bacterial community differentiation at the island scale. Biosynthetic gene clusters (BGCs) were predicted based on taxonomic profiles. The predicted biosynthetic landscape revealed spatial differentiation across sampling sites and was classified into nonribosomal peptide, post-translationally modified peptide, and terpene-enriched metabolic types. Environmental factors, including available phosphorus, water content, and pH, were associated with variation in specific predicted BGC classes. This island-scale survey shows that environmental gradients across Hainan Island are associated with bacterial diversity, community distribution, and predicted secondary metabolic potential in mangrove sediments. These findings provide insights into the ecological organization of mangrove sediment microbiomes and highlight mangrove sediments as reservoirs of microbial and predicted biosynthetic diversity.

In recent years, the East China Sea (ECS) has experienced frequent harmful algal blooms (HABs), driven by the complex interplay of climate change—specifically ocean warming and acidification—and eutrophication-induced light attenuation. Despite their ecological significance, the interactive effects of these environmental stressors on the competitive dynamics between bloom-forming microalgae remain poorly understood. This study aimed to elucidate how warming, reduced light, and elevated CO 2 influence the competition between two dominant diatoms. We conducted controlled monoculture and mixed-culture experiments using two key species: Skeletonema costatum and Chaetoceros curvisetus . The experimental design incorporated varying levels of CO 2 , temperature, and light intensity to simulate future coastal scenarios. Growth rates, peak cell densities, and successional patterns were monitored to assess competitive outcomes under multiple stressors. Monoculture results indicated that high temperature and low light intensity promoted the growth of both species. However, in mixed cultures, these conditions significantly accelerated the time to reach peak density and induced a definitive successional shift from S. costatum to C. curvisetus . Notably, while the general successional pattern was consistent, elevated CO 2 further enhanced the competitive advantage of C. curvisetus , particularly when combined with high-temperature and low-light scenarios. These findings suggest that the synergy of future warming, declining light availability, and intensified ocean acidification in the ECS will likely favor C. curvisetus over S. costatum . This shift may increase the frequency of HAB events dominated by C. curvisetus , driving significant climate-related restructuring of phytoplankton communities in coastal ecosystems.

Citizen science initiatives play an important role in large-scale monitoring of marine biodiversity, engaging the public in ecological data collection and supporting long-term assessments of species distribution. The Mediterranean Sea, one of the most biodiverse yet heavily impacted marine ecosystems, faces growing pressures from climate change, invasive species, and habitat degradation. To enhance the reliability of observations contributed by non-expert participants, automated tools for species identification are becoming essential. In this study, we compile MEDFISH101 , a carefully curated dataset of approximately 70,000 validated images covering 101 Mediterranean fish species. Using this resource, we developed and evaluated a series of deep learning pipelines based on transfer learning of pretrained vision foundation models to achieve accurate species recognition. Our best-performing model, DINOv2-G (self DIstillation with NO labels - Giant) trained via low rank adaptation, reached a Top-1 accuracy of 94.12%, demonstrating that current, state-of-the-art Artificial intelligence (AI) techniques can identify with high probability the correct fish species and thus robustly assist marine biodiversity monitoring. To facilitate transparency, reproducibility, and further community-driven research, a publicly accessible live demo is hosted on HuggingFace.

Introduction Collagen fibers from the marine sponge Chondrosia reniformis have been extensively studied for their biotechnological potential in regenerative medicine and drug delivery applications. However, the molecular characterization of the genes encoding these fibrillar collagens has not yet been clarified. Methods In this study, we used an integrated genomic, transcriptomic and experimental approach to identify and characterize the repertoire of fibrillar collagen genes in C. reniformis . Gene organization, predicted protein features, quantitative PCR expression analyses and in situ hybridization experiments were performed. Results Our analysis revealed the presence of five fibrillar collagen genes, two located on chromosome 2 and three on chromosome 13. Gene size, exon–intron organization and predicted protein features closely resemble those observed in bilaterian fibrillar collagens. Quantitative PCR analyses demonstrated that all five genes are expressed in adult specimens, with Colf1 and Colf4 representing the most abundant transcripts. Although Colf3 showed generally low expression levels, particularly in the choanosome, it was significantly enriched in the ectosome region, suggesting a possible functional specialization related to extracellular matrix organization and collagen fiber dynamics. This hypothesis is supported by specific features of the predicted triple-helical domain of Colf3, including five glycine substitutions that may confer increased fiber flexibility. In situ hybridization analyses revealed distinct spatial expression patterns, with numerous lophocytes expressing fibrillar collagen genes in the mesohyl, while transcript production in the ectosome appeared restricted to a limited number of highly active cells. Discussion Overall, these findings provide new molecular insights into fibrillar collagen diversity and tissue-specific expression in C. reniformis , supporting its relevance as a model for sponge extracellular matrix biology and as a reference framework for future studies on collagen-based biomaterials.

Maritime transport faces increasing “double random” risks—simultaneous supply disruptions and stochastic demand fluctuations. This study investigates the effectiveness of backup supply strategies in mitigating such risks, using crude oil procurement via the Strait of Hormuz as a case study. We develop a stochastic optimization model comparing two procurement scenarios: sole reliance on a primary supplier versus inclusion of a backup supplier. The model determines optimal order quantities and reservation levels by minimizing total expected costs (shortage costs, excess inventory costs, and backup activation costs). A European refinery sourcing crude oil through the Strait of Hormuz is used to validate the model with industry-calibrated parameters. Results show that incorporating a backup supplier reduces total expected costs by up to 34%, especially when supply disruption probability is high. Sensitivity analysis reveals that as disruption probability increases from 0.1 to 0.3, cost savings grow from 5.4 million to 7.8 million; the optimal order quantity from the primary supplier decreases while backup reservations increase, demonstrating a strategic risk-transfer mechanism. Backup sourcing provides an insurance-like effect, with marginal benefits greatest when primary supply becomes most unreliable. These findings offer quantitative evidence for the strategic value of backup suppliers and practical guidance for improving resilience, flexibility, and cost-efficiency in high-risk maritime supply chains.

In recent decades, species distribution models have emerged as essential tools for analyzing the potential effects of climate change on species distributions. This study employed an ensemble model to predict future changes in the distributions of small yellow croaker ( Larimichthys polyactis ) across seasons for the years 2030, 2050, and 2100 under the SSP1-2.6 and SSP2-4.5 climate scenarios of the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6). The species distribution model results indicated that the integrated model’s true skill statistics and area under the curve values of the receiver operating characteristic exceeded 0.95. The model demonstrates good predictive performance. Among the four seasons, summer habitat showed a notable reduction, and losses ranged from 14.945% (SSP1-2.6) to 29.080% (SSP2-4.5) by the 2100s. Habitat reduction occurred mainly in the offshore waters of the Bohai, Yellow, and East China Seas. The center of gravity of the species’ distribution shifted to higher latitudes and exhibited notable seasonal variation. The findings establish a predictive framework for the development of this species, and the prediction results based on scientific analysis will support the optimization of fishery management strategies in the context of climate change and thereby facilitate the sustainable use of fishery resources.

Introduction This study reconceptualises sea visibility as a structural territorial property that conditions everyday visual exposure to the marine environment, developing and applying a comprehensive GIS-based framework to the island of Mallorca (Western Mediterranean). Methods Visibility is analysed bidirectionally, from land to sea and from sea to land, using systematic observer grids, distance-dependent visual radii, and a dual elevation model approach comparing Digital Terrain Model (DTM) and Digital Surface Model (DSM)-based viewsheds. Distance-to-coastline weighting is applied to emphasise interactions within the coastal fringe, and cumulative visibility surfaces are aggregated to census sections to enable socioeconomic analysis. Results Results reveal pronounced spatial heterogeneity in structural sea visibility, strongly concentrated along the coastal fringe and shaped by the interaction of topography, coastal morphology, and surface artificialisation. The comparison between DTM- and DSM-based visibility demonstrates that buildings, infrastructure, and vegetation substantially modify potential visual relationships, with the greatest losses concentrated in densely urbanised coastal sectors. Bivariate spatial autocorrelation analysis reveals a weak but statistically significant positive association between household income and sea visual exposure at census-section level (Moran’s I = 0.106), mediated by historical settlement patterns and urban morphology rather than reflecting a simple privilege-deprivation dynamic. Extending this framework to the Blue Schools distribution, the analysis reveals that certified centres show a consistent tendency towards greater structural visual exposure at higher visibility thresholds, with the highest sea visibility values concentrated in private institutions located in socioeconomically privileged coastal areas. Discussion These findings suggest that sea visibility operates simultaneously as a potential enabler of Ocean Literacy and as a partially privatised territorial amenity, with implications for spatially equitable Ocean Literacy policy.

The complex relationships among ecological sustainability, economic viability, and employment opportunities within the fishing industry emphasize the importance of adopting a holistic analytical framework for fishery management. The evaluation of a comprehensive fisheries management policy becomes increasingly critical when an ecosystem, such as the eastern Mediterranean Sea, undergoes large changes. In this study, we analyzed the fishery sector in the Mediterranean region of Israel using the Ecopath with Ecosim (EwE) suite of ecological models, which are influenced by climate change and the influx of nonindigenous species (NIS) both, which alter the ecological and economic balance in the region. We identified key components within the fish supply chain that contribute significantly to the national economy and assessed their performance under several scenarios involving changes in the biomass of NIS within the ecosystem. Our findings indicate that while NIS contributes considerably to the local economy, most of the revenue is derived from native species, particularly large pelagics. Furthermore, the fishery sector in Israel exhibits a financial multiplier of four; that is, for every Israeli Shekel (ILS) earned by fishers, three additional ILS are generated through subsequent transactions along the fish supply chain. Within the supply chain, the restaurant sector is the primary employer, accounting for 41% of all employment. Furthermore, a considerable proportion of those engaged in fishing are recreational fishers who, despite not usually selling their catch, contribute indirectly to local economies and community well-being while deriving substantial cultural, psychological, and recreational value. The results of this study reveal the structure of the Israeli fisheries value chain, which is mostly determined by the moderately small scale of local commercial fisheries. However, the economic contribution of the value chain to the local economy is substantial and should not be overlooked when defining fishery management measures. This study emphasizes the need to examine the entire value chain, from fishing practices to the end consumer, to understand the broader implications of management actions on employment and income distribution, and to inform sustainable policymaking.

River-influenced estuarine systems support critical habitats but are vulnerable to water quality degradation driven by freshwater discharge variability, nutrient loading, and climate forcing. Understanding high-frequency variability and spatial heterogeneity remains limited due to reliance on discrete or short-term observations. This study addresses these gaps by analyzing multi-year (2021-2024), high-frequency observations collected by an autonomous surface vessel across eight transects in the Western Mississippi Sound. Ten parameters, including chlorophyll-a, phycocyanin, phycoerythrin, temperature, pH, dissolved oxygen, partial pressure of carbon dioxide, salinity, colored dissolved organic matter (CDOM), and turbidity were evaluated using Seasonal Mann-Kendall trend analyses, Kruskal-Wallis tests, Generalized Additive Models, Principal Component Analyses (PCA), hierarchical clustering, and a Composite Water Quality Score (CWQS). All parameters exhibited significant seasonal variability (Kruskal-Wallis p < 0.001), with elevated temperature and algal indicators during summer and reduced biological activity in winter. PCA identified a dominant freshwater-marine mixing and metabolic gradient (47.5% variance) and a secondary axis reflecting carbon cycling and oxygen dynamics (24.2%). Interannual variability was highest for phycoerythrin, CDOM, and temperature, with peak biomass in 2022 indicating episodic bloom events. Discharge-water quality relationships were regime-dependent: correlations were weak overall but strengthened under high-discharge conditions and reversed under low discharge, reflecting shifts between terrestrial and marine controls. Spatial analyses revealed distinct transect groupings and localized extremes. CWQS identified Transect 7 as critically degraded (CWQS = 0.54), driven by eutrophication. These findings demonstrate the value of high-frequency autonomous observations for resolving regime-dependent dynamics and informing spatially targeted coastal management.

The aim of this study was to thoroughly investigate the occurrence of two groups of high-volume industrial chemicals extensively used in many applications in the area of Thermaikos Gulf, Northern Aegean Sea, a typical semi-enclosed coastal inlet of the east-central Mediterranean Sea. For this purpose, organophosphate (OPEs) and phthalate esters (PEs) were determined in water samples and sediments. The concentrations of OPEs and PEs, their profile, possible sources and ecological risk are discussed. PEs were ubiquitous pollutants in the marine environment. The concentrations ΣOPEs ranged from 608 to 2447 ng/L in water and 450-5495 ng/g in sediments. The concentrations of ΣPEs ranged from 2820 to 13,343 ng/L in water and 7070-39,960 ng/g in sediments. Field partition coefficients of OPEs and PEs and possible relationships with concentrations of suspended particulate matter, dissolved and particulate organic carbon were discussed. A chemometric approach was employed to elucidate similarities/dissimilarities between these compounds and sampling sites. Finally, possible ecological risk for different aquatic species was estimated.

Tracking agrivoltaic (TAV) systems represent a significant form of agrivoltaics, which optimize solar energy capture through the dynamic adjustment of photovoltaic (PV) panel tilt angles. However, there is limited research on the effects of TAV systems on the three-dimensional spatial distribution of the light environment within PV arrays and their impacts on agricultural production. Therefore, a comparative experiment was conducted between wheat production under a TAV system and traditional open-field cultivation. Solar radiation intensity sensors were deployed to continuously monitor the dynamic changes in solar radiation under and between the PV panels throughout the entire growth period. Simultaneously, a light environment model for the TAV system was constructed, and the photosynthetic parameters of wheat leaves, as well as yield, were measured. The results indicated that the light environment within the system exhibited significant gradient attenuation, with average light capture rates of 43.2% and 46.1% for the inter-panel and under-panel measurement points, respectively. The model results confirmed that the synergistic adjustment of panel tilt angle and solar altitude angle significantly affected the shading effects, leading to notable spatiotemporal heterogeneity in the light environment during the winter solstice, spring equinox, and summer solstice. This heterogeneity showed as regular variations in shadows and radiation, collectively forming a dynamic light–thermal environment that influences crop growth. Wheat yields under and between the panels decreased by 11.5% and 6.6%, respectively, compared to the open-field control, with yields of 4625.9 kg·hm−2 and 4883.6 kg·hm−2. Additionally, the photosynthetic characteristics of the leaves effectively reflected the yield differences. Overall, the comprehensive benefit assessment demonstrates that the TAV system can effectively mitigate the reduction in wheat yield in PV farmlands. This study provides a theoretical basis for optimizing the light environment in AV systems.

Assessing the ecological and environmental quality of old industrial cities is crucial for understanding the spatial heterogeneity of ecological quality and its associated factors during regional transformation. Taking Tangshan, a typical old industrial city in China, as a case study, this study employed Landsat 8/9 remote sensing imagery and multi-source auxiliary data from 2015 to 2024 to calculate annual Remote Sensing Ecological Index (RSEI) values using a unified multi-year standardization and principal component analysis framework. Global and local Moran’s I analyses were conducted to examine spatial clustering patterns, and the Optimal-Parameter Geographical Detector (OPGD) was used to quantify the spatial correspondence between RSEI and selected natural and anthropogenic explanatory factors. The results indicate the following. (1) The mean RSEI in Tangshan fluctuated between 0.34 and 0.54 from 2015 to 2024, exhibiting significant interannual variability. (2) Higher RSEI values were primarily distributed in the northern mountainous and southern coastal ecological zones, while lower values were concentrated in the central and eastern industrial-mining zones. (3) The global Moran’s I was significantly positive in all years (0.702–0.778, p = 0.001), indicating the persistence of spatial clustering; the proportion of non-significant local spatial units decreased from 72.00% in 2015 to 69.46% in 2024. (4) Land use/land cover (LULC) exhibited the most consistently high explanatory power. Elevation (ELE), nighttime light (NTL), and built-up intensity (BUILT) also formed a leading group of spatially associated factors, although their relative ranking varied between the optimal-parameter results and the robustness analysis. Slope (SLOPE), annual precipitation (Pre), and annual mean temperature (Tmean) generally showed relatively lower explanatory power. Interaction detection showed that pairwise factor combinations generally had higher q values than individual factors, with LULC × ELE showing consistently high explanatory power in representative years. This study provides a scientific reference for ecological and environmental monitoring and differentiated management in old industrial cities.