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

Mirko Di Febbraro, Ludovico Frate, Maria Carla de Francesco, Angela Stanisci, Francesco Pio Tozzi, Marco Varricchione and Maria Laura Carranza
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Mirko Di Febbraro: EnviX–Lab, Department of Biosciences and Territory, University of Molise, C.da Fonte Lappone, 86090 Pesche, IS, Italy
Ludovico Frate: EnviX–Lab, Department of Biosciences and Territory, University of Molise, C.da Fonte Lappone, 86090 Pesche, IS, Italy
Maria Carla de Francesco: EnviX–Lab, Department of Biosciences and Territory, University of Molise, C.da Fonte Lappone, 86090 Pesche, IS, Italy
Angela Stanisci: EnviX–Lab, Department of Biosciences and Territory, University of Molise, C.da Fonte Lappone, 86090 Pesche, IS, Italy
Francesco Pio Tozzi: EnviX–Lab, Department of Biosciences and Territory, University of Molise, C.da Fonte Lappone, 86090 Pesche, IS, Italy
Marco Varricchione: EnviX–Lab, Department of Biosciences and Territory, University of Molise, C.da Fonte Lappone, 86090 Pesche, IS, Italy
Maria Laura Carranza: EnviX–Lab, Department of Biosciences and Territory, University of Molise, C.da Fonte Lappone, 86090 Pesche, IS, Italy

Land, 2021, vol. 10, issue 1, 1-17

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.

Keywords: Litter Distribution Model (LDM); beach litter accumulation; river mouth; coastal dune vegetation zonation; protected areas; Central Adriatic (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
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