Anthropocene Coasts最新文献

Lagoons are a major coastal environment in West Africa. They provide a plethora of resources, ecosystem services and economic benefits yet a diverse set of inter-connected stressors are a challenge to their sustainability. A scoping study of the published literature pertaining to lagoons within the region was undertaken to reveal the nature of these stressors and identify gaps in knowledge, providing a resource to inform coastal management practices and reveal areas for future study. Thirty-one lagoons were identified from the scoping exercise covering Nigeria, Benin, Togo, Ghana, Cote D’Ivoire, Liberia and Senegal. The DAPSI(W)R(M) framework was used to structure analysis of the literature and surface key environmental themes. Key drivers and activities established are the use of lagoon resources and expansion of lagoon settlements. The resultant identified pressures are waste, overuse of resources, and urban growth as well as climate change. Resultant stage changes are the degradation of water quality and ecosystems with impacts for the health of lagoon organisms and humans. Responses to changes were identified as a combination of punitive legislation, participatory management approaches and solutions focused on ecosystem restoration and engineering of the physical environment. Gaps identified include research on waste and aspects of climate change mitigation and adaptation. Also notable is a lack of multi- and interdisciplinary studies that address the inter-connecting stressors experienced at lagoons and studies of multiple lagoons. Studies also tend to be problem-focused with solutions rarely presented, limiting their applicability to inform management practices.

Coastal erosion and flooding are projected to increase during the 21^st century due to sea-level rise (SLR). To prevent adverse impacts of unmanaged coastal development, national organizations can apply a land protection policy, which consists of acquiring coastal land to avoid further development. Yet, these reserved areas remain exposed to flooding and erosion enhanced by SLR. Here, we quantify the exposure of the coastal land heritage portfolio of the French Conservatoire du littoral (Cdl). We find that 30% (~40%) of the Cdl lands owned (projected to be owned) are located below the contemporary highest tide level. Nearly 10% additional surface exposure is projected by 2100 under the high greenhouse gas emissions scenario (SSP5-8.5) and 2150 for the moderate scenario (SSP2-4.5). The increase in exposure is largest along the West Mediterranean coast of France. We also find that Cdl land exposure increases more rapidly for SLR in the range of 0–1 m than for SLR in the range 2–4 m. Thus, near-future uncertainty on SLR has the largest impact on Cdl land exposure evolution and related land acquisition planning. Concerning erosion, we find that nearly 1% of Cdl land could be lost in 2100 if observed historical trends continue. Adding the SLR effect could lead to more than 3% land loss. Our study confirms previous findings that Cdl needs to consider land losses due to SLR in its land acquisition strategy and start acquiring land farther from the coast.

Beach rankings are very frequent on the internet; however, the information provided on how these rankings are made is often unclear and their content is mostly subjective. In addition, the vast majority of these rankings do not take into account the fact that beaches are coastal eco-systems. The aim of the research was to develop an objective framework to rank the quality of beaches worldwide. The framework integrates indicators to assess the socio-ecological system quality and can be used as a basis for effective beach management. The methodology involved the collection, evaluation and grouping of indicators into domains and categories. Moreover, a measurement technique and a 5-point rating score for each indicator was used. Weights were calculated for different beach types using an analytical hierarchical process and the methodology was validated by a focus group of beach management experts. The quality value of each beach was calculated through equations and the results were presented in graphs inspired by the Circles of Sustainability and the Ocean Health Index. The theoretical application was tested on Portuguese beaches. The framework presents a holistic assessment of four domains: Recreation, Protection, Conservation and Sanitary. The resulting Beach Ranking Framework (BRF) is an objective, holistic framework designed to communicate with society, unlike the existing beach quality assessments.

The pervasive presence of microplastics within river ecosystems has a profound and often underestimated detrimental impact. These minuscule yet persistent particles have infiltrated diverse biological habitats, making their detrimental effects on aquatic life increasingly concerning worldwide. The ability of microplastics to accumulate within aquatic organisms further exacerbates this concern. Consequently, the monitoring of microplastic pollution in surface water environments has emerged as a crucial endeavour, offering invaluable insights into the extent of this ecological threat. This study delved into the contamination levels of microplastics within two bivalve species, Perna viridis and Villorita cyprinoides, along the Chandragiri River in Kerala and Karnataka, South-West India, spanning eight distinct locations. The investigation yielded a significant discovery, with a total of 667 microplastic particles extracted from 288 individuals. On average, each individual bivalve harboured approximately 2.31 ± 0.93 microplastic items. Notably, these microplastic particles exhibited a wide range of morphological characteristics, underscoring their diverse origins and pathways into the ecosystem. Furthermore, five polymer types of microplastics were unequivocally confirmed through FTIR-ATR analysis, shedding light on the types of plastics that pose a threat to the riverine ecosystem. The findings of this study contribute to a growing body of evidence highlighting the global threat of microplastic pollution, urging international collaboration and innovative solutions to prevent further contamination and remediate existing microplastic burdens in aquatic environments.

Based on a free energy approach, we propose the estimation of an ecosystem’s Inner Value, which is both non-instrumental and objective, reflecting the ecosystem’s value for itself as a natural entity, abstracted from any human valuation. The ecosystem services approach has become the dominant criterion for studying human and natural relationships, but this and similar approaches concentrate on the human advantage giving little or no regard for the well-being of the ecosystem. Although there is concern about preserving and recuperating damaged ecosystems, we seldom consider how much the ecosystem values itself. Then, we propose that Inner Value could be a tool to evaluate and model ecosystems’ health before any anthropic disturbance, allowing comparison with the impact these disturbances may have in the future. We also suggest that it should be a requirement for any Environmental Impact Assessment.

The aim of this contribution is to provide a brief overview of the current and future earth observation (EO) technologies that can be used to assess and manage the EU coastal flood risk, together with the pertinent international and EU policies and legislation. The review has shown that EOs have become an indispensable technology for the assessment and management of the coastal flood risk, and their role will increase further in the future when EO information of higher resolution and accuracy become available. With regard to the relevant policies and legislation, their common thread is associated with the promotion and facilitation of the development of appropriate data and tools for high-quality and timely geo-spatial information based on EO technologies. In Europe, in particular, this development is promoted and facilitated by an array of international and supra-national (EU), interacting policies and legislation. It appears, however, that additional initiatives and technological progress in EO functionalities and the information technology are needed together with more targeted policy and legislation frameworks to provide vital information for the management of the coastal flood risk.

This study analyzes the content of internet ratings of beaches to identify the indicators used. The methodology used an exploratory internet survey using the term ‘best beaches’ in five languages. For each site, the ranking method used was extracted and the indicators considered were listed, where applicable. Of the 70 websites analyzed, 47 ranked the beaches (67%) but less than 50% used indicators. The remaining were based on the opinion of the editorial board, personal experience, and users’ perceptions. The most used indicator was the color of water, followed by the color of the sand. These results show that the majority of ‘best beaches’ lists are based on subjective criteria. They are an overview of places that appeal to the person that wrote the page and are not scientifically or analytically based. Even when indicators are considered, these are mostly a reflection of the idea of an idealized beach, crystal blue waters with white or gold sand. The actual quality of the beach, including water quality, carrying capacity, and ecosystem balance, is not addressed. Although visual attractiveness is a key element for the public, these rankings should incorporate a wider range of indicators to fully assess the quality of a beach.

The aim of the present contribution has been to present a methodological framework to gauge/assess the perceptions and identify the policy priorities of local-decision-makers for the management of the coastal zone under a changing climate, on the basis of structured ‘interviews’ of the local decision makers. The framework was applied in two different coastal areas in Greece: a) Elefsina, an urban-industrial area west of Athens with a long industrial history (and the 2023 European Capital of Culture); and b) the Aegean island of Santorini/Thera, a major international tourist destination due to the rare aesthetics of its volcanic landscape. The framework implementation showed that a) policy prioritization is characterized by an (understandably) overarching objective to address immediate environmental and socio-economic challenges in short time tables due also to constraints in appropriate human and financial resources and the reliance on higher governance (regional/national) levels; b) policy axis and action prioritizations are controlled by the local environmental setting and development model; c) interestingly for coastal municipalities policy actions associated with the study/protection of coastal ecosystems ranked very low albeit for different stated reasons; and d) climate change impacts and adaptation have not been prioritized highly in both coastal municipalities, in contrast to the large impacts and needs for adaptation projected for these areas and the evolving policy and legislation frameworks. It appears that higher efforts should be made in terms of the assessment of climate change impacts, and the dissemination of the assessment results and the relevance of the evolving policy and legislation regimes to the local policy makers.

The present study uses nine machine learning (ML) methods to predict wave runup in an innovative and comprehensive methodology. Unlike previous investigations, which often limited the factors considered when applying ML methodologies to predict wave runup, this approach takes a holistic perspective. The analysis takes into account a comprehensive range of crucial coastal parameters, including the 2% exceedance value for runup, setup, total swash excursion, incident swash, infragravity swash, significant wave height, peak wave period, foreshore beach slope, and median sediment size. Model performance, interpretability, and practicality were assessed. The findings from this study showes that linear models, while valuable in many applications, proved insufficient in grasping the complexity of this dataset. On the other hand, we found that non-linear models are essential for achieving accurate wave runup predictions, underscoring their significance in the context of the research. Within the framework of this examination, it was found that wave runup is affected by median sediment size, significant wave height, and foreshore beach slope. Coastal engineers and managers can utilize these findings to design more resilient coastal structures and evaluate the risks posed by coastal hazards. To improve forecast accuracy, the research stressed feature selection and model complexity management. This research proves machine learning algorithms can predict wave runup, aiding coastal engineering and management. These models help build coastal infrastructure and predict coastal hazards.

Graphical Abstract

River systems play an important role in the development of human society. However, they have been significantly affected by human activities, reducing the capacity for water supply, flood regulation, and aquatic ecosystem services. Identifying changes in river systems and hydrological responses to these changes is crucial for regional water management. In this study, based on the data derived from topographic maps of the 1960s, 1980s, and 2010s, we comprehensively quantified changes in river systems of the Yangtze River Delta (YRD), China. The results show that the density of rivers and the proportion of water surface decreased over the past several decades, while changes in the evolutionary coefficient of rivers and the ratio of area to length of rivers exhibited clear spatial differences. Low-grade rivers in urbanized areas have declined severely, leading to a simplification of river structure. Furthermore, the hydrological response to changes in the river system was revealed in the Taihu Lake Plain, an area of the YRD with a plain river network. A longitudinal functional connectivity index (LFCI) was adopted to assess the hydrological dynamics in water level, and it was found to have an increasing trend. In addition, the specific storage capacity (SSC) and the specific regulation capacity (SRC) were established to reveal the impact of changes in the structure and connectivity of the river system on the regulation and storage capacity, and both indicators exhibited a downward trend. Simulations based on the MIKE 11 model show that the reduction of tributaries across the region can result in an earlier peak timing and higher peak water level. Our results can support the development of river system protection and flood adaptation strategies in the delta plains.