Modelling Beach Litter Accumulation on Mediterranean Coastal Landscapes: An Integrative Framework Using Species Distribution Models

Abstract

Beach litter accumulation patterns are influenced by biotic and abiotic factors, as well as by the distribution of anthropogenic sources. Although the importance of comprehensive approaches to deal with anthropogenic litter pollution is acknowledged, integrated studies including geomorphologic, biotic, and anthropic factors in relation to beach debris accumulation are still needed. In this perspective, Species Distribution Models (SDMs) might represent an appropriate tool to predict litter accumulation probability in relation to environmental conditions. In this context, we explored the applicability of a SDM–type modelling approach (a Litter Distribution Model; LDM) to map litter accumulation in coastal sand dunes. Starting from 180 litter sampling plots combined with fine–resolution variables, we calibrated LDMs from litter items classified either by their material type or origin. We also mapped litter accumulation hotspots. LDMs achieved fair-to-good predictive performance, with LDMs for litter classified by material type performing significantly better than models for litter classified by origin. Accumulation hotspots were mostly localized along the beach, by beach accesses, and at river mouths. In light of the promising results achieved by LDMs in this study, we conclude that this tool can be successfully applied within a coastal litter management context.

Impact of storms and proximity to entry points on marine litter and wrack accumulation along Mediterranean beaches: Management implications

“…Our study reveals that Tuscany beaches located closer to major harbors exhibited a greater litter density. This finding is consistent with a recent study showing a positive relationship between macro-plastic abundance and proximity of sites with intense fishing activity (Masiá et al, 2021), but it disagrees with studies reporting a greater litter density in beaches near to river mouths (Rech et al, 2014;Willis et al, 2017;Di Febbraro et al, 2021). Nonetheless, our results shows that the combination of proximity to the closest major harbor and river was the best subset of variables explaining the differences in terms of macro-category observed among the investigated beaches, indicating that both these entry points can play an important role in determining litter composition at regional scale.…”

“…However, the amount and the distance from river mouths at which litter accumulates is strictly dependent on the intensity of storms and rainfall events (Galgani et al, 2000;van Emmerik et al, 2019). Some studies have found a positive relationship between beach litter abundance and proximity of river mouths (Rech 5 5 et al, 2014;Willis et al, 2017;Di Febbraro et al, 2021). On the other hand, a recent study failed to detect a positive correlation among beach litter abundance and proximity of rivers and harbors (Masiá et al, 2021).…”

“…Some studies have focused on quantitative and qualitative beach litter characterization (e.g., Vlachogianni et al, 2018;Fortibuoni et al, 2021). Other studies have attempted to establish a relationship between litter abundance and proximity to entry points such as urban areas (Giovacchini et al, 2018;Di Febbraro et al, 2021) or beach exposure to winds and sea currents (Prevenios et al, 2018;Camedda et al, 2021). Nevertheless, knowledge gaps remain about the impact of storm events as well as of litter input from rivers and harbor-related activities on beach pollution.…”

Understanding through drone image analysis the interactions between geomorphology, vegetation and marine debris along a sandy spit

“…Our results attest that a specific UAV imagery classification should be developed considering at least three easy observable parameters, which are dimension, shape, and colour. Indeed, classification using marine litter category such as plastic, paper, metal, is currently not appropriate considering that the characteristics of the material type (buoyancy and weight) influence the wind and wave driven transport processes, and may result in similar accumulation patterns as noted by Di Febbraro et al (2021). Consequently, such an UAV classification should be used to provide information to local authorities regarding eventual necessary cleaning operation activities, and successively after the cleaning operations identification of the marine litter can be done to provide additional useful information.…”

Synergetic use of unmanned aerial vehicle and satellite images for detecting non-native tree species: An insight into Acacia saligna invasion in the Mediterranean coast

“…This zonation promotes the development of highly specialized biodiversity, which shares few species with other terrestrial communities (Drius et al, 2016;Marzialetti et al, 2020), and its integrity assures manifold ecosystem services (Drius et al, 2013). This area is impinged by several human-related disturbances as most of the Mediterranean coastal landscapes: agricultural pressure (Malavasi et al, 2013), tourism and urban expansion (Carranza et al, 2018), beach pollution (Di Febbraro et al, 2021), and alien species invasions (Del Vecchio et al, 2013;Marzialetti et al, 2019). The analyzed area is inside a special area of conservation (SAC, Habitat Directive 92/43/EEC; Foce Trigno-Marina di Petacciato IT7228221) and is a node of the Long-Term Ecological Research Network (LTER, http:// www.lter-europe.net/; Stanisci et al, 2014;Drius et al, 2013), which makes it an excellent testing ground to develop methodologies which are able to evaluate and monitor invasion processes.…”