Search Results (2,259)

A multidisciplinary study was conducted to reconstruct the paleoenvironmental evolution of Maladroxia Bay, one of the principal bays of the islet of Sant’Antioco in southwestern Sardinia, over the past eight millennia. As part of an archaeological landscape project, this study explores the paleogeography and environment of the bay from a diachronic perspective to gain insights into the Holocene relative sea level history, shoreline displacements, and the environmental conditions during different phases. This study is based on an analysis of four sediment cores in conjunction with a chronological model that is based on radiocarbon dates. Four relative sea level indicators were produced. These are the first such indicators from the early and middle Holocene for the island of Sant’Antioco. The results indicate that in the early Holocene, the area was a terrestrial, fluvial environment without marine influence. In the 6th millennium BCE, the rising sea level and marine transgression resulted in the formation of a shallow inner lagoon. It reached its maximum extent in the middle of the 5th millennium BCE. Afterwards, a gradual transition from lagoon to floodplain, and a seaward shift of the shoreline occurred. The lagoon potentially served as a valuable source of food and resources during the middle Holocene. During the Nuragic period (2nd to 1st millennium BCE), the Bay of Maladroxia was very similar to how it is today. Its location was ideal for use as an anchorage, due to the calm and sheltered conditions that prevailed. Full article

The mapping and monitoring of coastal regions are critical to ensure their sustainable use and viability in the long term. Delineation of coastlines is becoming increasingly important in the light of climate change and rising sea levels. However, many coastlines are highly dynamic; therefore, mono-temporal assessments of coastal ecosystems and coastlines are mere snapshots of limited practical value for space-based planning. Understanding of the spatio-temporal dynamics of coastal ecosystem boundaries is important to inform ecosystem management but also for a meaningful delineation of the high-water mark, which is used as a benchmark for coastal spatial planning in South Africa. This research aimed to use hyper-temporal Sentinel-2 imagery to extract ecological zones on the coast of KwaZulu-Natal, South Africa. A total of 613 images, collected between 2019 and 2023, were classified into four distinct coastal ecological zones—vegetation, bare, surf, and water—using a Random Forest model. Across all classifications, the percentage of each of the four classes’ occurrence per pixel over time was determined. This enabled the identification of ecosystem locations, spatially static ecosystem boundaries, and the occurrence of ecosystem boundaries with a more dynamic location over time, such as the non-permanent vegetation zone of the foredune area as well as the intertidal zone. The overall accuracy of the model was 98.13%, while the Kappa coefficient was 0.975, with user’s and producer’s accuracies ranging between 93.02% and 100%. These results indicate that cloud-based analysis of Sentinel-2 time series holds potential not just for delineating coastal ecosystem boundaries, but also for enhancing the understanding of spatio-temporal dynamics between them, to inform meaningful environmental management, spatial planning, and climate adaptation strategies. Full article

We investigated the spatial structure and colony itinerancy of Audouin’s gull (Ichthyaetus audouinii) adult breeders across multiple breeding sites in the central Mediterranean Sea during 25 years of fieldwork. Using cluster analysis of marked individuals from different years and sites, we identified five spatial breeding units of increasing hierarchical scale—Breeding Sites, Colonies, Districts, Regions and Marine Sectors—which reflect biologically meaningful boundaries beyond simple geographic proximity. To determine the most appropriate scale for monitoring local populations, we applied multievent capture–recapture models and examined variation in survival and site fidelity across these units. Audouin’s gulls frequently change their location at the Breeding Site and Colony levels from one year to another, without apparent survival costs. In contrast, dispersal beyond Districts boundaries was found to be rare and associated with reduced survival rates, indicating that breeding Districts represent the most relevant biological unit for identifying local populations. The survival disadvantage observed in individuals leaving their District likely reflects increased extrinsic mortality in unfamiliar environments and the selective dispersal of lower-quality individuals. Within breeding Districts, birds may benefit from local knowledge and social information, supporting demographic stability and higher fitness. Our findings highlight the value of adopting a District-based framework for long-term monitoring and conservation of this endangered species. At this scale, demographic trends such as population growth or decline emerge more clearly than when assessed at the level of singular colonies. This approach can enhance our understanding of population dynamics in other mobile species and support more effective conservation strategies aligned with natural population structure. Full article

Recreational diving depends on healthy marine ecosystems, yet it can harm biodiversity through species displacement and habitat damage. Bombinhas, a biodiverse diving hotspot in southern Brazil, faces growing threats from human activity and climate change. This study assessed the ecological structure of Sepultura Beach (2018) for potential diving trails, comparing it with historical data from Porto Belo Island. Using visual censuses, transects, and photo-quadrats across six sampling campaigns, researchers documented 2419 organisms from five zoological groups, identifying 14 dominant species, including Haemulon aurolineatum and Diplodus argenteus. Cluster analysis revealed three ecological zones, with higher biodiversity at the site’s edges (Groups 1 and 3), but these areas also hosted endangered species like Epinephelus marginatus, complicating trail planning. A major concern was the widespread bleaching of the zoanthid Palythoa caribaeorum, a key ecosystem engineer, likely due to rising sea temperatures (+1.68 °C from 1961–2018) and declining chlorophyll-a levels post-2015. Comparisons with past data showed a 0.33 °C increase in species’ thermal preferences over 17 years, alongside lower trophic levels and greater ecological vulnerability, indicating tropicalization from the expanding Brazil Current. While Sepultura Beach’s biodiversity supports diving tourism, conservation efforts must address coral bleaching and endangered species protection. Long-term monitoring is crucial to track warming impacts, and adaptive management is needed for sustainable trail development. The study highlights the urgent need to balance ecotourism with climate resilience in subtropical marine ecosystems. Full article

Change in sea level (SL) is an important indicator of global warming, since it reflects alterations in several components of the climate system at once. The main factors behind this phenomenon are the melting of glaciers and thermal expansion of ocean water, with the latter contributing about 40% to the overall rise in SL. Rising SL indirectly indicates an increase in ocean heat content and, consequently, its surface temperature. Previous studies have found that tropical sea surface temperature (SST) is critical to regulating the Earth’s climate and weather patterns in high and mid-latitudes. For this reason, SST and SL in the tropics can be considered as precursors of both global climate change and the emergence of climate anomalies in extratropical latitudes. Although SST has been used in this capacity in a number of studies, similar research regarding SL had not been conducted until recently. In this paper, we examine the links between SL in the tropical North Atlantic and North Pacific Oceans and surface air temperature (SAT) at mid- and high latitudes, with the aim of assessing the potential of SL as a predictor in forecasting SAT anomalies. To identify similarities between the variability of tropical SL and SST and that of SAT in high- and mid-latitude regions, as well as to estimate possible time lags, we applied factor analysis, clustering, cross-correlation and cross-spectral analyses. The results reveal a structural similarity in the internal variability of tropical SL and extratropical SAT, along with a significant lagged relationship between them, with a time lag of several years. Full article

Population growth and land use change often have significant environmental impacts, affecting biodiversity, water supply, agricultural production, and other resources. Future scenario models can provide a better understanding of these changes, helping planners and the public understand the consequences of choices regarding development density, land use, and conservation. This study presents a model that has been used to identify alternative future scenarios for Florida considering future population growth and land use. It includes two scenarios: a “Sprawl” scenario reflecting a continuation of current development patterns and a “Conservation” scenario with higher densities, redevelopment, and more land protection. The study incorporates sea level rise scenarios for both 2040 and 2070. Results show that the Sprawl scenario could lead to 3.5 million acres of new developed land and 1.8 million acres of lost agricultural land by 2070 in Florida. In contrast, the Conservation scenario for 2070 results in 1.3 million fewer acres of developed land and 5 million more acres of protected natural land, showing that it is possible to accommodate future population growth while reducing impacts to agricultural and conservation priorities in Florida. Although this is by no means a “prediction” of future Florida, it has been useful as a tool for evaluating potential future land use scenarios and is a model that may be more broadly applied by other locations and users. Full article

The long-term trend of coastal upwelling under global warming has been a research focus in recent years. Based on datasets including sea surface temperature (SST), sea surface wind, air–sea heat fluxes, ocean currents, and sea level pressure, this study explores the long-term trend and underlying mechanisms of the Oman coastal upwelling intensity in summer during 1993–2018. The results indicate a persistent decrease in SST within the Oman upwelling region during this period, suggesting an intensification trend of Oman upwelling. This trend is primarily driven by the strengthened positive wind stress curl (WSC), while the enhanced net shortwave radiation flux at the sea surface partially suppresses the SST cooling induced by the strengthened positive WSC, and the effect of horizontal oceanic heat transport is weak. Further analysis revealed that the increasing trend in the positive WSC results from the nonuniform responses of sea level pressure and the associated surface winds to global warming. There is an increasing trend in sea level pressure over the western Arabian Sea, coupled with decreasing atmospheric pressure over the Arabian Peninsula and the Somali Peninsula. This enhances the atmospheric pressure gradient between land and sea, and consequently strengthens the alongshore winds off the Oman coast. However, in the coastal region, wind changes are less pronounced, resulting in an insignificant trend in the alongshore component of surface wind. Consequently, it results in the increasing positive WSC over the Oman upwelling region, and sustains the intensification trend of Oman coastal upwelling. Full article

Recent updates to the reconstructions of Cenozoic environmental changes (global sea level, temperature, and atmospheric carbon dioxide content) have made it intriguing to compare them to paleontological records for original interpretations. Paleogene brachiopods have remained in the shadow of their Paleozoic–Mesozoic predecessors, and the reactions of their diversity to the Earth’s dramatic changes are poorly understood. The present work aims to fill this gap via a comparison of several diversity and paleoenvironmental curves. The generic diversity was established by stages with two essentially different paleontological datasets, and several fresh paleoenvironmental reconstructions were adopted. It was observed that neither Paleogene eustatic fluctuations nor changes in the atmospheric carbon dioxide content correspond well to the generic diversity dynamics of brachiopods. The changes in the total number of genera and the global temperatures demonstrate similarity at the Danian–Ypresian interval, but not later. The fluctuations in the brachiopod diversity are near the same level during the Eocene–Oligocene, despite strong paleoenvironmental changes, implying the intrinsic resistivity of these organisms to external influences. Additionally, the Cretaceous/Paleogene mass extinction, the Paleocene–Eocene thermal maximum, and the Early Eocene optimum could enhance the diversity dynamics together with the long-term temperature changes. In contrast, the influences of the Late Danian warming event and the Oi-1 glaciation were not observed. Full article

This study assesses the risk of geoheritage degradation along a low-lying coastal stretch Okin the municipalities of Macau, Guamaré, and Galinhos, located in the central portion of Rio Grande do Norte’s northern coastline, Brazil. Twelve geosites, inventoried based on their scientific value, susceptibility to degradation, and representation of diverse coastal processes and landforms, were numerically assessed for their degradation risk. The methodology comprised 11 sub-criteria grouped into three main criteria: natural vulnerability, anthropogenic vulnerability, and public use. The results indicate that all 12 geosites in the study area are subject to moderate to high degradation risk, with the highest levels observed in those with the most evident signs of human use and intervention. To mitigate these impacts, the implementation of access restrictions or protective measures by local authorities is recommended. Furthermore, raising awareness among local communities about the environmental consequences of their activities and the geosites’ role in promoting sustainability is essential. Given the region’s heightened vulnerability to sea level oscillations, future assessments should incorporate climate change implications into the assessment criteria. Full article

Image analysis is a valuable approach in a wide array of environmental applications. Mapping land cover categories depicted from satellite images enables the monitoring of landscape dynamics. Such a technique plays a key role for land management and predictive ecosystem modelling. Satellite-based mapping of environmental dynamics enables us to define factors that trigger these processes and are crucial for our understanding of Earth system processes. In this study, a reclassification scheme of image analysis was developed for mapping the adjusted categorisation of land cover types using multispectral remote sensing datasets and Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS) software. The data included four Landsat 8–9 satellite images on 2015, 2019, 2021 and 2023. The sequence of time series was used to determine land cover dynamics. The classification scheme consisting of 17 initial land cover classes was employed by logical workflow to extract 10 key land cover types of the coastal areas of Bab-el-Mandeb Strait, southern Red Sea. Special attention is placed to identify changes in the land categories regarding the thermal saline lake, Lake Assal, with fluctuating salinity and water levels. The methodology included the use of machine learning (ML) image analysis GRASS GIS modules ‘r.reclass’ for the reclassification of a raster map based on category values. Other modules included ‘r.random’, ‘r.learn.train’ and ‘r.learn.predict’ for gradient boosting ML classifier and ‘i.cluster’ and ‘i.maxlik’ for clustering and maximum-likelihood discriminant analysis. To reveal changes in the land cover categories around the Lake of Assal, this study uses ML and reclassification methods for image analysis. Auxiliary modules included ‘i.group’, ‘r.import’ and other GRASS GIS scripting techniques applied to Landsat image processing and for the identification of land cover variables. The results of image processing demonstrated annual fluctuations in the landscapes around the saline lake and changes in semi-arid and desert land cover types over Djibouti. The increase in the extent of semi-desert areas and the decrease in natural vegetation proved the processes of desertification of the arid environment in Djibouti caused by climate effects. The developed land cover maps provided information for assessing spatial–temporal changes in Djibouti. The proposed ML-based methodology using GRASS GIS can be employed for integrating techniques of image analysis for land management in other arid regions of Africa. Full article

Late Pleistocene coastal deposits on the southeastern coast of Formentera (Es Ram–Es Estufadors) provide a high-resolution record of sea-level and climatic fluctuations associated with Marine Isotope Stage (MIS) 5. Three distinct beach levels (Sef-1, Sef-2, Sef-3) were identified, corresponding to substages MIS 5e, 5c, and possibly 5a, based on sedimentological features, fossil assemblages, and Optically Stimulated Luminescence (OSL) dating. The oldest beach level (Sef-1) is attributed to MIS 5e (ca. 128–116 ka) and is characterised by the widespread presence of thermophilic Senegalese fauna—including Thetystrombus latus, Conus ermineus, and Linatella caudata—which mark the onset of this interglacial phase and are associated with two peaks in relative sea-level highstand. A subsequent cooling event during MIS 5d is recorded by the development of thin palaeosols and the disappearance of these warm-water taxa. The second beach level (Sef-2) reflects renewed sea-level rise and warmer conditions during MIS 5c, with abundant macrofauna and red algae. The transition to MIS 5b (~97 ka) is marked by a significant sea-level drop (down to –60 m), cooler climate, and enhanced colluvial sedimentation linked to increased runoff and erosion. In total, 54 macrofaunal species were identified—16 from Sef-1 and 46 from Sef-2—highlighting ecological shifts across substages. These results improve our understanding of coastal response to sea-level oscillations and paleoenvironmental dynamics in the western Mediterranean during the Late Pleistocene. Full article

In this cross-disciplinary investigation, we uncover a suite of previously unexamined factors and their intricate interplay that hold causal relationships with the distribution of Trachurus japonicus in the northern reaches of the South China Sea, thereby extending the existing research paradigms. Leveraging advanced machine learning algorithms and causal inference, our robust experimental design uncovered nine key global and regional factors affecting the distribution of T. japonicus density. A robust experimental design identified nine key factors significantly influencing this density: mean sea-level pressure (msl-0, msl-4), surface pressure (sp-0, sp-4), Summit ozone concentration (Ozone_sum), F10.7 solar flux index (F10.7_index), nitrate concentration at 20 m depth (N3M20), sonar-detected effective vertical range beneath the surface (Height), and survey month (Month). Crucially, stable causal relationships were identified among Ozone_sum, F10.7_index, Height, and N3M20. Variations in Ozone_sum likely impact surface UV radiation levels, influencing plankton dynamics (a primary food source) and potentially larval/juvenile fish survival. The F10.7_index, reflecting solar activity, may affect geomagnetic fields, potentially influencing the migration and orientation behavior of T. japonicus. N3M20 directly modulates primary productivity by limiting phytoplankton growth, thereby shaping the availability and distribution of prey organisms throughout the food web. Height defines the vertical habitat range acoustically detectable, intrinsically linking directly to the vertical distribution and availability of the fish stock itself. Surface pressures (msl-0/sp-0) and their lagged effects (msl-4/sp-4) significantly influence sea surface temperature profiles, ocean currents, and stratification, all critical determinants of suitable habitats and prey aggregation. The strong influence of Month predominantly reflects seasonal changes in water temperature, reproductive cycles, and associated shifts in nutrient supply and plankton blooms. Rigorous robustness checks (Data Subset and Random Common Cause Refutation) confirmed the reliability and consistency of these causal findings. This elucidation of the distinct biological and physical pathways linking these diverse factors leading to T. japonicus density provides a significantly improved foundation for predicting distribution patterns globally and offers concrete scientific insights for sustainable fishery management strategies. Full article

The preservation and protection of historic urban centers in climate-sensitive coastal areas contributes to the promotion of culture as a driver and enabler of achieving temporal and spatial sustainability, as it is recognized that urban heritage is an integral part of the urban landscape, culture, and economy. The aim of this study was to enhance the resilience and protection of cultural heritage and historic urban centers (HUCs) in the coastal area of Kaštela, Croatia, by providing recommendations and action guidelines in response to climate change impacts, including rising temperatures, sea levels, storms, droughts, and flooding. Preserving HUCs is essential to maintain their cultural values, original structures, and appearance. Many ancient coastal Roman HUCs lie partially or entirely below mean sea level, while low-lying medieval castles, urban areas, and modern developments are increasingly at risk. Based on vulnerability assessments, targeted mitigation and adaptation measures were proposed to address HUC vulnerability sources. The Historical Urban Landscape Approach tool was used to transition and manage HUCs, linking past, present, and future hazard contexts to enable rational, comprehensive, and sustainable solutions. The effective protection of HUCs requires a deeper understanding of the evolution of urban development, climate dynamics, and the natural environments, including both tangible and intangible urban heritage elements. The “hazard-specific” vulnerability assessment framework, which incorporates hazard-relevant indicators of sensitivity and adaptive capacity, was a practical tool for risk reduction. This method relies on analyzing the historical performance and physical characteristics of the system, without necessitating additional simulations of transformation processes. Full article

The use of high-resolution sea level anomaly (SLA) data in climate change research and ocean forecasting has become increasingly important. However, existing datasets often lack the fine spatial resolution required for capturing mesoscale ocean processes accurately. This has led to the development of conventional deep learning models for SLA spatial downscaling, but these models often overlook spatial disparities between land and ocean regions and do not adequately address the spatial structures of SLA data. As a result, their accuracy and structural consistency are suboptimal. To address these issues, we propose a Deep Separable Distillation Network (DSDN) that integrates Depthwise Separable Distillation Blocks (DSDB) and a Landmask Contextual Attention Mechanism (M_CAMB) to achieve efficient and accurate spatial downscaling. The M_CAMB employs geographically-informed land masks to enhance the attention mechanism, prioritizing ocean regions. Additionally, we introduce a novel Pixel-Structure Loss (PSLoss) to enforce spatial structure constraints, significantly improving the structural fidelity of the SLA downscaling results. Experimental results demonstrate that DSDN achieves a root mean square error (RMSE) of 0.062 cm, a peak signal-to-noise ratio (PSNR) of 42.22 dB, and a structural similarity index (SSIM) of 0.976 in SLA downscaling. These results surpass those of baseline models and highlight the superior precision and structural consistency of DSDN. Full article

Mangrove forests serve as critical ecological barriers in coastal zones and play a vital role in global blue carbon sequestration strategies. In recent decades, China’s mangrove ecosystems have experienced complex interactions between degradation and restoration under intense coastal urbanization and systematic conservation efforts. However, the long-term spatiotemporal patterns and driving mechanisms of mangrove ecosystem health changes remain insufficiently quantified. This study developed a multi-temporal analytical framework using Landsat imagery (1986–2021) to derive kernel normalized difference vegetation index (kNDVI) time series—an advanced phenological indicator with enhanced sensitivity to vegetation dynamics. We systematically characterized mangrove growth patterns along China’s southeastern coast through integrated Theil–Sen slope estimation, Mann–Kendall trend analysis, and Hurst exponent forecasting. A Deep Forest regression model was subsequently applied to quantify the relative contributions of environmental drivers (mean annual sea surface temperature, precipitation, air temperature, tropical cyclone frequency, and relative sea-level rise rate) and anthropogenic pressures (nighttime light index). The results showed the following: (1) a nationally significant improvement in mangrove vitality (p < 0.05), with mean annual kNDVI increasing by 0.0072/yr during 1986–2021; (2) spatially divergent trajectories, with 58.68% of mangroves exhibiting significant improvement (p < 0.05), which was 2.89 times higher than the proportion of degraded areas (15.10%); (3) Hurst persistence analysis (H = 0.896) indicating that 74.97% of the mangrove regions were likely to maintain their growth trends, while 15.07% of the coastal zones faced potential degradation risks; and (4) Deep Forest regression id the relative rate of sea-level rise (importance = 0.91) and anthropogenic (nighttime light index, importance = 0.81) as dominant drivers, surpassing climatic factors. This study provides the first national-scale, 30 m resolution assessment of mangrove growth dynamics using kNDVI, offering a scientific basis for adaptive management and blue carbon strategies in subtropical coastal ecosystems. Full article