Anthropocene Coasts最新文献

With the development of hydraulic engineering such as harbor, channel and reclamation, more and more natural tidal flat turn into the semi-natural tidal flat (SNTF). How to evaluate ecosystem of semi-natural tidal flat is a scientific problem that has not been fully solved. The study tries to assess ecosystem health change of SNTF adjoining Hengsha East Shoal training dike in the Yangtze estuary. The study found SNTF area > 0m isobaths increased from 30.33 km² in 2010–2014 to 46.66 km² in 2014–2017 and to 56.84 km² in 2017–2020, and the Hengsha Shoal region.0m, -2m and -5m isobaths increased from 174.78 km², 303.82 km², and 556.77 km² in 2010–2014 to 233.34 km², 365.59 km², and 596.83 km² in 2014–2017 and to 243.81 km², 363.27 km² and 567.45 km² in 2017–2020. Using database of 3 pressure indicators, 16 state indicators and 3 response indicators, the study combined pressure-state-response (PSR) model and fuzzy comprehensive evaluation (FCE), constructed a systematic evaluation method of ecosystem health of semi-natural tidal flat. The evaluation result found the ecosystem health of SNTF of Hengsha East Shoal was rated as "Fair" level during 2010–2020, and the summation of comprehensive evaluation index (CEI) increased from 0.4009 in 2010–2014 to 0.4703 in 2014–2017 due to the rapid expansion of tidal flat vegetation, and then decreased to 0.4450 in 2017–2020 due to a reduction in vegetation area caused by erosion. The area of salt marsh vegetation plays an important role in the health of wetland ecosystems. The Hengsha East Shoal ecosystem is undergoing a quickly dynamic evolution processes, long-term series monitoring and further research for this area are necessary to guide its future development according to the tidal flat utilization patterns.

Tropical Cyclone (TC) Kimi was active from January 15 to 19, 2021 in Australian waters. TC Kimi activity does influence the atmosphere and ocean dynamics around it, including in central and eastern Indonesian waters, with the highest increase in local winds occurring in Sangihe (315.8%), Gorontalo (236.3%), Seram (236.3%) dan Manado (225.8%). On the other hand, Gorontalo experienced the highest increase of significant wave height during TC Kimi active, with 921.4% increase. In this study, we analyze wave height change in central and eastern Indonesian waters before TC Kimi was active, at the peak intensity of TC Kimi, and after TC Kimi dissipated by employing Simulating Waves Nearshore (SWAN) wave model. From spatial lagged correlation analysis between wind from TC Kimi and local winds in Indonesia, we obtained 12 locations that have positive lag and correlation, namely: Denpasar, Waingapu, Rote, Majene, Gorontalo, Manado, Sangihe, Sanana, Seram, Raja Ampat, Agats dan Merauke. From time series lagged correlation, the locations that have negative lag are Denpasar (-6 h) and Rote (-1 h), those with 0 h lag are Raja Ampat and Agats, and those with positive lag are Waingapu (+ 8 h), Majene (+ 10 h), Gorontalo (+ 14 h), Manado (+ 6 h), Sangihe (+ 15 h), Sanana (+ 7 h), Seram (+ 5 h) and Merauke (+ 6 h). Surface wind analysis during the development and early phase of TC Kimi shows wind flows from Sulawesi Sea, Maluku Sea, Halmahera Sea, and Banda Sea towards the TC Kimi system. When TC Kimi approaches its strongest intensity, there are low-pressure areas (Low) that are also active, including Low in the Philippines and in the Gulf of Carpentaria, while the wind flow towards TC Kimi appears to be disconnected. Low in the Philippines and the Gulf of Carpentaria, respectively, play a role in maintaining the high waves in the northern and southern waters of Indonesia. It indicates that TC Kimi plays a role in the initial increase of wind speed in Indonesia, which is continued by the presence of Low in their respective local areas.

The environment provides endless assistance for the wellbeing of all living organisms. However, the environment can be stressed due to anthropogenic and non-anthropogenic pollutants. Plastics have been identified as a persistent pollutant that has been stressing the environment for over a few decades. Among these hazardous plastics, the accumulation of microplastics (MPs) has been identified as a growing global issue. MPs are generally defined as small pieces of plastic less than 5 mm in diameter. Considering the source, two categories are identified, primary and secondary MPs, and it has been recognized that MPs are released into the environment during plastic production, transportation, product usage, and product maintenance. Different processes including physical, chemical, photodegradation, and biological degradations tend to break plastics into MP fragments, which include MPs as well as nanoplastics. Among these degradation processes, physical degradation is prominent in the coastal regions, and chemical degradation can occur due to corrosive chemicals, acids, gases, and atmospheric pollutants, which was the case during the recent MV X-Press Pearl disaster in the Indian Ocean. Different methodologies can be applied for the pretreatment, separation, detection, identification, and quantification of MPs. Digestion of complex substances and ultracentrifugation or ultrafiltration are utilized as pretreatment methods, whereas density, magnetic and electrostatic separations, filtration, and size-exclusion chromatography are practiced as separation methods for MPs. Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, atomic force microscopy (AFM), and mass spectrometry can be identified as the main analytical methods for MP detection. The ecological risk of MPs affects the marine environment, freshwater environment, and soil environment, ultimately influencing human health. To remediate the issue, removal methods for MPs are being developed, with currently progressing methods being physical sorption and filtration, biological removal and ingestion, chemical treatments, membrane processes, and magnetic separation. Considering the prospects, the need to conduct meta-analyses, and compare data from different studies done in various geographic regions is important, which, among other related topics such as policy development, are discussed thoroughly through this review article.

Beachgoers are sometimes exposed to coastal hazards, yet comprehensive analyses of characteristics and potential factors for beach accidents are rarely reported in China. In this study, information on beach accidents was collected on a recreational beach from 2004 to 2022 by searching the web or apps. The characteristics of beach accidents were therefore analysed in terms of age, gender, and activity of beachgoers. The potential factors were resolved in environmental aspects of meteorology, waves, tides, and beach morphology. Results show that beach accidents mainly occur in summer, with the highest occurrence in the afternoon and evening. The number of male beachgoers in accidents is five times higher than that of females. 90% of accidents occur when the beach is at a high-risk level for rip currents, providing evidence for the accuracy of the risk map built in a previous study. Three machine learning models, i.e., Support Vector Machine, Random Forest, and BP Neural Networks, are trained to predict beach accidents. The performances of these three machine learning algorithms are evaluated in terms of precision, recall, and F1 score. Support Vector Machine and BP Neural Networks significantly outperform Random Forest in terms of prediction. The accuracy in predicting "safe" and "dangerous" classes is approximately 80% of the Support Vector Machine model. This paper provides a preliminary study of machine learning based beach accident prediction for a specific tourist beach. In the future, machine learning will be applied to predict tourist beach accidents throughout mainland China.

Coastal salt marsh wetlands are crucial reservoirs of soil carbon (C) and nitrogen (N). However, the effects of plant type, geomorphology, and macrobenthos on spatial variations in soil C and N in coastal wetlands remain unclear. In this study, the spatial distribution of soil C and N components was investigated in a coastal wetland (Jiuduansha Shoal) in the Yangtze Estuary, and plant type distribution, plant biomass, soil properties, and macrobenthos species and biomass along the geomorphological gradient were measured. The results showed that the amounts and stocks of soil total C, soil organic C, soil total N, and soil microbial biomass C and N at the Spartina alterniflora (SA) and Phragmites australis (PA) sites were significantly higher than those at the bare mudflat (BM) sites. The soil and microorganism C and N variables showed a remarkable increasing trend from low- to high-elevation sites. The abundance of macrobenthos at the Scirpus mariqueter site was the highest among the plant communities and was significantly higher than that at the Zizania latifolia (ZL) and BM sites. The air-free dry weight (AFDW) of macrobenthos in the PA community was the highest among the communities. The variability in soil C and N was mainly sensitive to plant biomass, soil water content, bulk density, macrobenthos AFDW, particle size, electrical conductivity, and nutrient levels. We suggest that the synergetic effects of biotic and abiotic factors in the intertidal environment need to be fully considered in assessing and managing the C and N pools of coastal salt marshes in East China.

The Pechora is the greatest river of the European Russian Arctic, flowing into the Barents Sea. Its estuarine area includes a vast delta, represented by extensive lowlands that are dissected by the complicated network of arms and branches. Despite the Pechora Delta is considered to be microtidal, tides with a range of 0.5–1 m during the low water period have a significant impact on the nature of currents in the main branches and the distribution of runoff among them during the tidal cycle. Tidal sea level fluctuations as well as storm surges determine the reversing pattern of currents over a significant extent of the delta branches. The modern field equipment combined with 2D hydrodynamic modeling has allowed to understand the contemporary flow features and evaluate their possible alterations under climate changes. The climate impact under considered scenarios is more pronounced during the low flow period, and this can lead to the propagation of tidal currents and an increase in water levels in the city of Naryan-Mar (100 km upstream from the mouth). From a flood risk perspective, sea level rise can be offset by a reduction in flood runoff.

The western Bay of Bengal is particularly susceptible to the harmful impacts of increasing coastal pollution, as coastal population and urban development are occurring at unprecedented rates. The rapid urbanization and industrialization along the east coast of India coupled with the transfer of contaminants into the Bay of Bengal through riverine systems, causing a direct impact on marine ecosystems. In the present study, an attempt has been made to understand the heavy metal distribution on shelf sediments in the western part of the Bay of Bengal to infer their source, processes, and historical changes in marine pollution. Three short sediment core samples were collected and analysed for sediment texture, organic matter, and heavy metals. Cores 1 and 2 contain a high amount of sand content, representing shallow marine with moderate to high-energy conditions, and were deposited at a recent time. Core 3 was dominated by muddy sand to sandy mud, which denotes calm sedimentation without any turbulence, and these sediments were deposited under relatively low-energy conditions. The higher concentration of organic matter in the top layers of the core indicates both marine and terrestrial input. The heavy metal contents show quite heterogeneous and variable distributions from one element to another and from one core to another. The calculated pollution indices such as Contamination Factor (CF), and Geoaccumulation Index (Igeo) and Pollution Load Index (PLI) values indicate that all the core sub-samples are severely enriched and highly polluted by Cd and moderately polluted by Pb. The increased heavy metal concentration in the upper portion of the sediment cores and moderate to considerable ecological risks indicate that these metals have been deposited in the study area for the past few decades.

Beaches play a pivotal role in supporting the socio-economic sector, particularly within the 'Sun, Sea, and Sand' (3S) tourism model. Valued for their ecosystem services, these coastal landforms are among the most dynamic and vulnerable environments, facing significant pressure from various climate challenges, which is further intensified by extensive anthropic exploitation. Their sustainable use is intrinsically linked to balancing the 3Ps: Planet, People, and Profit. To address the need for protection and sustainable utilization of coastal areas, the European Union has introduced the Protocol on Integrated Coastal Zone Management (ICZM) in the Mediterranean, specifically recommending in Article 8(2) the establishment of a setback buffer zone where permanent constructions are prohibited. This paper explores the application of risk mapping in the context of coastal setback policies, focusing on their effectiveness in managing beach retreat and adapting to climate change, particularly rising sea levels. The study examines selected beach areas in Peloponnese, Greece, influenced by various socio-economic factors. Through this analysis, the paper aims to contribute to the discourse on coastal management strategies that balance environmental sustainability with socio-economic benefits.

The Bay of Bengal has been at the heart of human civilisation and trade for many centuries. Accordingly, this oceanic space has seen influx of people from around the world including European traders who plundered natural wealth of this region for many years. Unabated exploitation of natural resources has been the primary reason for deterioration of environment of this part of the world. To add to this, supporting a growing population through unsustainable anthropogenic activities for decades is considered a primary cause for deterioration of marine life, habitats, coastal and marine ecosystems and numerous ocean ecosystem services of this oceanic space. Since the health of the oceanic space is critical for survival of life of Earth, a detailed study of the impacts of a growing population on the coastal environment of the Bay is considered important. Unfortunately, since the anthropogenic activities causing this deterioration are numerous, they cannot be covered in one paper. Hence, only a select few critical anthropogenic activities causing coastal erosion, resource degradation, and marine pollution are being analysed here. The study shows that as a result of increasing population, terrestrial activities such as increasing built up area, industries, land use activities, fisheries and aquaculture, and construction of shore protection structures have resulted in reduced coastal vegetation and increased pollution of the ocean. As a result the coastal landscape is witnessing increased coastal erosion, coastal flooding and inundation, loss of vegetation and faunal communities especially fishes. While local initiatives and projects reflect a positive commitment to address resource degradation and to create resilient coastal ecosystems, these efforts need to be transformed into achievements by dedicated and nuanced involvement of all stakeholders, especially the public, for the desired results.

Coastal regions worldwide face increasing threats from climate change-induced hazards, necessitating more accurate and comprehensive vulnerability assessment tools. This study introduces an innovative approach to coastal vulnerability assessment by integrating Bayesian Networks (BN) with the modern coastal vulnerability (CV) framework. The resulting BN-CV model was applied to Queensland's coastal regions, with a particular focus on tide-modified and tide-dominated beaches, which constitute over 85% of the studied area. The research methodology involved beach classification based on morphodynamic characteristics, spatial subdivision of Queensland's coast into 78 sections, and the application of the BN-CV model to analyze interactions between geomorphological features and oceanic dynamics. This approach achieved over 90% accuracy in correlating beach types with vulnerability factors, significantly outperforming traditional CVI applications. Key findings include the identification of vulnerability hotspots and the creation of detailed exposure and sensitivity maps for Gold Coast City, Redland City, Brisbane City, and the Sunshine Coast Regional area. The study revealed spatial variability in coastal vulnerability, providing crucial insights for targeted management strategies. The BN-CV model demonstrates superior precision and customization capabilities, offering a more nuanced understanding of coastal vulnerability in regions with diverse beach typologies. This research advocates for the adoption of the BN-CV approach to inform tailored coastal planning and management strategies, emphasizing the need for regular reassessments and sustained stakeholder engagement to build resilience against climate change impacts.

Recommendations include prioritizing adaptive infrastructure in high-exposure areas like the Gold Coast, enhancing flood management in Brisbane, improving socio-economic adaptive capacity in Redland, and maintaining natural defences in Moreton Bay. This study contributes significantly to the field of coastal risk management, providing a robust tool for policymakers and coastal managers to develop more effective strategies for building coastal resilience in the face of climate change.