Regional Studies in Marine Science最新文献

The coastal lagoon of the Mar Menor (SE Spain) has undergone a critical transformation in the last decade due to a dramatic eutrophication crisis, primarily as a direct consequence of very-intensive agriculture along the adjacent coast. This has compromised the ecosystem balance, resulting in irreversible impacts such as the proliferation of macro and microalgae, biodiversity loss, and the formation of dead zones. The Mar Menor's resilience has been tested, showing serious environmental degradation evidenced by a significant shift in ecological state around 2016. During a two-year study period (2017–2018), 25 taxa belonging to 5 phyla were identified, with the phylum Annelida (class Polychaeta) being the best represented, followed by the phylum Mollusca. Initially, the benthic fauna was dominated by species tolerant to hypoxia, such as polychaetes. Over time, other species that can withstand slightly less eutrophication have also emerged and integrated with the polychaetes, indicating a complex dynamic in response to environmental changes.

Seagrass meadows are one of the most productive and valuable ecosystems on the planet. Monitoring seagrass meadows is essential to understand how these habitats change, and to develop better management and conservation practices. This study integrated satellite imagery from Sentinel-2 and Unmanned Aerial Vehicles (UAV) using machine learning to provide a consistent classification approach for monitoring seagrass in Maputo Bay, southern Mozambique. Sentinel-2 imagery was used to map seagrass extent and changes in Maputo Bay. The UAV systems were used to map seagrass at species level and biomass. All three algorithms tested in the ArcGIS environment could detect seagrass with high producer accuracy and Kappa coefficient. The area of seagrass in Maputo Bay decreased by 33.4 % between 1991 and 2023, with a decreasing trend of 0.48 km²/yr. A zonation pattern was observed for Oceana serrulata and Zostera capensis from the UAV imagery. The small and narrow leaved species (Z. capensis) occurred in the intertidal zone replaced by the broadleaved species (O. serrulata) in the subtidal. The total average aboveground biomass was 33.2 kg dry weight for the mapped area. The results of this study will guide implementation of combined satellite and UAV imagery with machine learning techniques for seagrass monitoring and restoration in Mozambique.

Although there have been extensive studies of the erosion of mangrove-dominated muddy coasts, the information on the processes and drivers of erosion at fine scales of analysis is still lacking. Without this knowledge, the existing efforts to minimize erosion are just piecemeal solutions that only address the symptoms of the erosion process. The coastlines of the Mekong Delta in Vietnam (VMD) and Brebes Regency in Indonesia have been selected as case studies to address this issue. The aim of the paper is to document coastal erosion and the factors that accelerate the erosion process. This is achieved by using the participatory diagramming technique, which combines the analysis of photographs of erosion sites taken during field trips, detailed field observations, and responses from semi-structured interviews with erosion-affected communities in VMD and Brebes Regency, Indonesia. The results show that five dominant erosion processes identified in these two regions were burrow-induced erosion, clearcut-induced erosion, farming-induced erosion, pond-induced erosion, and boating-induced erosion. Of the five erosion processes, human activities have altered the characteristic of the mangrove forests, and are likely to have exposed areas to erosion, with wave action providing a tipping point by severely reducing the structural integrity of the coastal soil in sensitive areas and making them susceptible to collapse. However, many other areas in VMD and Brebes Regency, Indonesia have remained stable over time. The methodological approach proposed here appears to be applicable to other mangrove-dominated muddy coasts, which are characteristic of most anthropogenically affected tropical deltas. As human activities are closely linked to forestry policies in Vietnam and Indonesia, enforcement should be strengthened to significantly increase the impact of these policies in controlling coastal erosion and minimize the vulnerability of these areas to erosion.

The increase in concentrations of potential toxic elements resulting from human activities has raised concerns about their impact on human health and ecosystems. A total of 41 research articles were reviewed, and the contamination status of eleven trace elements (Cd, Co, Cu, Pb, Cr, Fe, Zn, Mn, Ni, Hg, and As) in freshwater and marine sediments was evaluated using available published data from 2000 to 2021. Furthermore, the geo-accumulation index (I_geo), the integrated pollution index (IPI), and the potential ecological risk index were calculated.

Metal concentrations in Algerian freshwater and marine sediments were found to vary among 62 regions, linked to factors such as the use of leaded gasoline, mining sites, the use of pesticides and chemical fertilizers, fishing harbors, naval construction, urban and industrial wastes, and the absence of wastewater treatment. The I_geo indices showed that Cd, Pb, and Zn are the significant pollutants, with probabilities of Algerian sediment being higher than 0 at 91.31 %, 89.66 %, and 65.39 %, respectively, in freshwater and 42.86 %, 34.38 %, and 34.38 %, respectively, in coastal sediment. The IPI indicated that values were higher than 1 in 85.71 % of studied rivers and 31.25 % of coastal study areas, suggesting that freshwater sediments in Algerian are more highly polluted compared to coastal sediments.

It is evident that continuous monitoring and management are essential to mitigate significant contamination resulting from industrial complexes, agricultural practices, and commercial activities in areas adjacent to rivers and marine environments.

This paper provides a scenic assessment of 19 dune sites using the Dune Scenery Evaluation System (DSES). The DSES assesses values from a checklist of 18 physical and 8 human parameters and allows the calculation of a scenic evaluation index (D Value), which classifies D sites into five classes: Class I, usually natural areas of top scenic characteristics, to Class V, poor scenic dune areas with a greater impact of human interventions. Our findings reveal a predominance of coastal dune systems falling into middle to lower scenic quality classes (III, IV, and V), indicating considerable degradation due to intense human activities. Notably, these activities have adversely impacted the structural integrity and scenic value of these dunes, leading to a loss of biodiversity and increased vulnerability to natural hazards. This paper highlights the critical need for integrated coastal management strategies that balance conservation with sustainable development. Furthermore, our study proposes the enhancement of existing regulatory frameworks, community engagement in conservation efforts, and the implementation of ecological restoration projects aimed at reversing the degradation and restoring the ecological and scenic value of these vital landscapes. The findings underline the potential of using scenic quality as an ecological indicator to guide conservation and management practices, ensuring the preservation of coastal dunes, which are essential for ecological sustainability and local economic benefits. This multidisciplinary approach not only enriches our understanding of the complex interactions within dune ecosystems but also sets a precedent for future research and policymaking in coastal zone management.

Submarine groundwater discharge (SGD) worldwide has been considered an important source of dissolved inorganic nutrients, pathogens, and terrestrial materials transported from land to sea. However, nutrient behavior associated with SGD in the Mexican Caribbean has long been ignored. Here, we investigate the variability in nutrient and pathogen distribution during a neap-spring diurnal cycle in the Nohoch-Teek fringing reef influenced by SGD during the “nortes” season. The spatio-temporal behavior of nitrate and silicate followed three patterns during a neap-spring diurnal cycle: 1) An increasing trend from the beginning to the end of the day; 2) A spatial gradient with decreasing values from SGD-Teek towards the coral reef; and 3) The highest concentrations in the SGD-Teek and southwest of SGD-Teek. No significant differences were recorded in the temporal behavior (p > 0.05); however, the highest concentrations were observed during the lowest spring tide. The ammonium exhibited an increasing trend from the beginning to the end of the day. Significant differences were recorded regarding temporal behavior, with variations during the morning and afternoon of both spring and neap tides, with the highest concentrations recorded in the afternoon. The spatial distribution of phosphate was more homogeneous. The presence of pathogens was evidenced in addition to the variation in the spatial and temporal behavior of nutrient input through SGD. The correlation between salinity and water level suggests that sea level variations influenced the flow. Silicate as tracers proved efficient, showing a predominant flow towards the southwest during both neap and spring tides, with the maximum extent recorded during the spring tide.

In this study, marine water samples were collected at 18 sampling stations. The collected marine water samples were analysed using a well-calibrated UV spectrophotometer for chlorophyll-a estimation, and using a hyperspectral underwater radiometer, both buoy mode and profile mode in-situ data were collected. The study evaluated four different primary production models to study the dynamics of the southern Bay of Bengal. The simple Eppley model used in the study resulted in huge variations in the nearshore and frontal regions; the dark and light bottle methods showed enormous variations along all 18 sampling stations and underestimated the productivity of the southern Bay of Bengal. However, the VGPM model and its variants showed similar trends in near shore, frontal, and off-shore waters for all three transects, and the Kameda model closely matched the available literature for the primary production estimates of the southern Bay of Bengal. From the detailed analysis of the Kameda model, it is found that the average primary production for the Southern Bay of Bengal for the post monsoon season (February 2023) is estimated as 339.08 mgC/m²/d.