Perspectives for sandy beach management in the Anthropocene: Satellite information, tourism seasonality, and expert recommendations. (5th November 2021)

• Record Type: Journal Article
• Authors: Orlando, L.; Ortega, L.; Defeo, O.
• Is Part Of: Estuarine, coastal and shelf science. Volume 262(2021)
• Publication Date: 2021-11-05
• Subjects: Random forest -- Ecosystem management -- Satellite indicators -- Tourism seasonality -- Night-lights; Estuarine oceanography -- Periodicals; Coasts -- Periodicals; Estuarine biology -- Periodicals; Seashore biology -- Periodicals; Coasts; Estuarine biology; Estuarine oceanography; Seashore biology; Periodicals; 551.461805
• DOI: 10.1016/j.ecss.2021.107597
• Languages: English
• ISSNs: 0272-7714

Abstract

Abstract: Sandy beaches combine a highly documented ecological relevance with a widely acknowledged human development potential. Management of these mainly physically-driven ecosystems is a complex task that relies primarily on ranking protocols for site assessment, which is a procedure dependent on expert perceptions. This approach fails to address the systems' complexity, hampering the scale and quality of comparative analysis and pattern detection. This work evaluates the incorporation of globally available quantitative indicators to sandy beach management by modeling expert perceptions on conservation and recreation potential for 58 beaches in four continents. Tourism seasonality was estimated through pulse indicators based on monthly variations of Artificial Lights At Night (ALAN) and then contrasted with water temperature and urbanization. Seasonality indicators, ecosystem attributes, and a set of urbanization descriptors derived from satellite information were modeled to predict expert-based scores derived from two beach indices developed to assess conservation and recreation potential. A constrained envelope analysis showed a bell-shaped pattern of seasonal tourism indicators with sea surface temperature and a decreasing trend with ALAN. A regression tree explained 73% of conservation potential deviance and displayed a structure coherent with the index considerations on dune state, iconic species, and macrobenthic richness. Random Forest analysis explained 62% of the variance, and ALAN was the variable most significantly associated with expert advised conservation priorities, followed by human density and beach and sand areas. The regression tree explained 49% of deviance on recreation and depended on seasonal tourism magnitude and urbanization features. The Random Forest analysis explained 23% of the variance, mainly given by seasonal tourism magnitude and ALAN; vegetation cover and sand area were also relevant. The results suggest a high potential in incorporating freely distributed satellite information in sandy beach management, particularly those describing human patterns. ALAN and seasonal tourism magnitude, both anthropogenic, best-ranked as measurable variables explaining expert opinion on conservation and recreation. A combined and complementary approach merging scientific information derived from satellite-based information and expert knowledge could lead to a coherent management narrative about the potential use of beaches for recreation and or conservation. Integrating these different knowledge formats could increase the ability to explore, promote, strengthen and support management strategies to improve the status of a fragile ecosystem at risk increasingly threatened by several stressors acting together. Graphical abstract: Image 1 Highlights: Satellite-based quantitative indicators incorporated into beach management frameworks. Expert recreation and conservation indices modeled by regression trees and random forests. Tourism seasonality and artificial night-lights explained expert opinion. Beach area and vegetation cover were also relevant explanatory variables in beach use. Merging satellite-based information and expert knowledge improves beach management.