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The climate change process is leading to an increase in the sea level and the storm intensity. The associated shoreline recession can damage coastal facilities and also beaches protected by submerged/emerged breakwaters whose defense action can become ineffective. The application of cross-shore numerical models does not allow the performance of long-term analyses. In this paper, a semi-analytical model for the evaluation of shoreline recession due to waves and sea-level rise for free and protected beaches is proposed. The model is an extension of the Dean's approach in which some limitations on the beach profile are overcome and the effects of breakwaters on the wave height (wave transmission) and on the water level (piling-up) are considered. The model takes into account a wide range of parameters for wave, sea level, beach profile, and breakwater characteristics. Among the breakwater parameters, the freeboard and the berm width are found to mainly affect the shoreline recession. For submerged breakwaters, an optimal value of the freeboard can be computed depending on the sea level and the offshore wave characteristics. The results of the model are then used to find prediction relations of the shoreline recession, with r2 > 0.99, for both free and protected beaches, depending on the main hydrodynamic/geometrical characteristics. [ABSTRACT FROM AUTHOR]

In the face of environmental change, high-quality and fine-scale information is essential in order to monitor the highly dynamic environments on land and sea. While traditional approaches to data collection face a number of practical limitations, advanced technologies could supplement and further improve our efforts. Taking sea turtles as a modeling organism, we present a novel methodological framework for monitoring species by means of advanced technologies, including Unmanned Aerial Vehicles coupled with image and temperature sensors. Diverse monitoring protocols were refined through pilot studies conducted in both terrestrial and nearshore sea turtle habitats. Our approach focuses on the collection of information for critical biological parameters concerning species reproduction and habitat use, following the complex life cycle of the species. Apart from biological information, our framework encompasses also the collection of information on crucial environmental factors that might be changing due to current and future human-derived pressures, such as beach erosion and temperature profile, as well as highly important human activities such as recreational use within nesting beaches that could undermine habitat quality for the species. This holistic and standardized approach to monitoring using advanced technologies could foster our capacity for conservation, resolving difficulties previously addressed and improving the collection of biological and environmental data in the frame of an adaptive management scheme. [ABSTRACT FROM AUTHOR]

This article provides a general methodology for calculating the retreat of the coastline and the volume of sand necessary to renourish a beach due to sea level rise (SLR) in the medium-long term. An example is presented, Victoria Beach, and a projection is made for the years 2030, 2040, 2050, and 2100. The results obtained take into account global sea level rise (GSLR), which is worldwide, and local sea level rise (LSLR), which considers climate variability and vertical land movements. Regarding GSLR, data were provided by the projections from IPCC (Intergovernmental Panel on Climate Change) scenarios and empirical models, such as Rahmstorf and Pfeffer. The LSLR data came from the tide gauge station located in Cadiz. Finally, the results obtained showed that global warming impacts erosive effects and the subsequent volume of sand required to renourish beaches. The total sea level rise (TSLR) projections indicated for Victoria Beach are relatively higher than the GSLR projections. Even in the best IPCC scenario (RCP 2.6), Victoria Beach presents a significant erosion of 52 m, requiring a volume of sand of 1.0 Mm3 to supply renourishment. [ABSTRACT FROM AUTHOR]

Through an empirical investigation of the historical relationship between the destination climate and tourist arrivals in the Caribbean, this study presents the first revealed preference evaluation of a climate index informed by tourists' stated climatic preferences for coastal-beach tourism (i.e., a sun-sand-surf or 3S travel market). The goal of this multi-organization collaboration was to examine the potential application of a newly designed climate index—the Holiday Climate Index (HCI):Beach—for three Caribbean destinations (Antigua and Barbuda, Barbados, Saint Lucia). This paper provides an overview of the evolution of climate indices, including the development of the (HCI):Beach. To test the validity of climate indices for a beach travel market, daily climate ratings based on outputs from the Tourism Climate Index and the HCI were correlated with monthly arrivals data from Canada (a key source market) at an island destination scale. The results underscore the strength of the new index, with each destination scoring consistently higher using the HCI:Beach, including a stronger relationship (R2) between index scores and tourist arrivals. These findings demonstrate the value of combining stated and revealed preference methodologies to predict tourism demand and highlight opportunities for future research. [ABSTRACT FROM AUTHOR]