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Sci Rep ; 14(1): 752, 2024 01 08.
Artigo em Inglês | MEDLINE | ID: mdl-38191897


Climate change and human activity threaten sea turtle nesting beaches through increased flooding and erosion. Understanding the environmental characteristics that enable nesting can aid to preserve and expand these habitats. While numerous local studies exist, a comprehensive global analysis of environmental influences on the distribution of sea turtle nesting habitats remains largely unexplored. Here, we relate the distribution of global sea turtle nesting to 22 coastal indicators, spanning hydrodynamic, atmospheric, geophysical, habitat, and human processes. Using state-of-the-art global datasets and a novel 50-km-resolution hexagonal coastline grid (Coastgons), we employ machine learning to identify spatially homogeneous patterns in the indicators and correlate these to the occurrence of nesting grounds. Our findings suggest sea surface temperature, tidal range, extreme surges, and proximity to coral and seagrass habitats significantly influence global nesting distribution. Low tidal ranges and low extreme surges appear to be particularly favorable for individual species, likely due to reduced nest flooding. Other indicators, previously reported as influential (e.g., precipitation and wind speed), were not as important in our global-scale analysis. Finally, we identify new, potentially suitable nesting regions for each species. On average, [Formula: see text] of global coastal regions between [Formula: see text] and [Formula: see text] latitude could be suitable for nesting, while only [Formula: see text] is currently used by turtles, showing that the realized niche is significantly smaller than the fundamental niche, and that there is potential for sea turtles to expand their nesting habitat. Our results help identify suitable nesting conditions, quantify potential hazards to global nesting habitats, and lay a foundation for nature-based solutions to preserve and potentially expand these habitats.

Antozoários , Tartarugas , Humanos , Animais , Mudança Climática , Sistemas Computacionais , Inundações
Sci Total Environ ; 917: 170239, 2024 Mar 20.
Artigo em Inglês | MEDLINE | ID: mdl-38278243


In this study, we present a novel modeling framework that provides a stylized representation of coastal adaptation and migration dynamics under sea level rise (SLR). We develop an agent-based model that simulates household and government agents adapting to shoreline change and increasing coastal flood risk. This model is coupled to a gravity-based model of migration to simulate coastward migration. Household characteristics are derived from local census data from 2015, and household decisions are calibrated based on empirical survey data on household adaptation in France. We integrate projections of shoreline retreat and flood inundation levels under two Representative Concentration Pathways (RCPs) and account for socioeconomic development under two Shared Socioeconomic Pathways (SSPs). The model is then applied to simulate coastal adaptation and migration between 2015 and 2080. Our results indicate that without coastal adaptation, SLR could drive the cumulative net outmigration of 13,100 up to as many as 21,700 coastal inhabitants between 2015 and 2080 under SSP2-RCP4.5 and SSP5-RCP8.5, respectively. This amounts to between 3.0 %-3.7 % of the coastal population residing in the 1/100-year flood zone in 2080 under a scenario of SLR. We find that SLR-induced migration is largely dependent on the adaptation strategies pursued by households and governments. Household implementation of floodproofing measures combined with beach renourishment reduces the projected SLR-induced migration by 31 %-36 % when compared to a migration under a scenario of no adaptation. A sensitivity analysis indicates that the effect of beach renourishment on SLR-induced migration largely depends on the level of coastal flood protection offered by sandy beaches. By explicitly modeling household behavior combined with governmental protection strategies under increasing coastal risks, the framework presented in this study allows for a comparison of climate change impacts on coastal communities under different adaptation strategies.

Sci Rep ; 13(1): 11549, 2023 Jul 17.
Artigo em Inglês | MEDLINE | ID: mdl-37460556


A common inference in research studies of observed and projected changes in global ocean wave height and storm surge, is that such changes are potentially important for long-term coastal management. Despite numerous studies of the impacts of anthropogenic climate change on trends in global wind and waves, a clear link to impacts on sandy coastlines, at global scale, is yet to be demonstrated. This study presents a first-pass assessment of the potential link between historical trends in global wave and storm surge values and recession/progradation rates of sandy coastlines since the 1980s. Global datasets of waves, surge and shoreline change rate are used for this purpose. Over the past 30 + years, we show that there have been clear changes in waves and storm surge at global scale. The data, however, does not show an unequivocal linkage between trends in wave and storm surge climate and sandy shoreline recession/progradation. We conclude that these long-term changes in oceanographic parameters may still be too small to have a measurable impact on shoreline recession/progradation and that primary drivers such as ambient imbalances in the coastal sediment budget may be masking any such linkages.

J Environ Manage ; 311: 114824, 2022 Mar 04.
Artigo em Inglês | MEDLINE | ID: mdl-35255323


In the face of uncertainties around coastal management and climate change, coastal engineering interventions need to be able to adapt to changing conditions. Nature-based solutions and other non-traditional, integrated interventions are gaining traction. However, system-based views are not yet embedded into coastal management strategies. Moreover, the differences in coastal interventions, ranging from hard ('grey') to nature-based ('green') infrastructure remain understudied. In coastal management it is therefore challenging to work with the grey-green spectrum of interventions with clarity and focus, and to produce results that can be evaluated. The objective of this paper was to examine whether there is a common understanding of: the characteristics and differences between grey and green infrastructure, where interventions sit on this spectrum, and the resilience of grey versus green infrastructure. We conducted an integrative literature review of the grey-green spectrum of coastal infrastructure. We examined 105 coastal protection case studies and expanded the double-insurance framework to ensure an integrative approach, looking at both external and internal factors of resilience. Our review showed that external factors are typically used to characterise the grey-green spectrum. However, although useful, they do not facilitate a holistic comparison of alternative interventions. The additional consideration of internal factors (response diversity, multifunctionality, modularity and adaptive, participatory governance) bridges this gap. The review showed that dikes, reefs, saltmarshes, sand nourishment and dunes span a wider segment of the grey-green spectrum than they are generally categorised in. Furthermore, resilient solutions for adaptation are unlikely to be exclusively engineered or natural, but tend to be a mix of the two at different spatial scales (micro, meso, macro and mega). Our review therefore suggests that coastal planners benefit from a more diverse range of options when they consider the incorporation of grey and green interventions in the context of each spatial scale. We propose that internal resilience should be accounted for when infrastructure options are comparatively evaluated. This consideration brings attention to the ways in which the grey-hybrid-green spectrum of infrastructure enhances value for people.