A novel high-resolution eco-functional vegetation mapping of coastal dunes
Coastal dune landscapes are dynamic systems shaped by complex biotic-abiotic interactions and impacted by human disturbances. This study focuses on Mediterranean coastal dunes, analyzing spatial distribution and ecological characteristics of their plant communities through an innovative approach tha...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X2500086X |
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| author | Michele Innangi Mirko Di Febbraro Marco Balsi Ginevra Colonna Michele Finizio Federica Pontieri Maria Laura Carranza |
| author_facet | Michele Innangi Mirko Di Febbraro Marco Balsi Ginevra Colonna Michele Finizio Federica Pontieri Maria Laura Carranza |
| author_sort | Michele Innangi |
| collection | DOAJ |
| description | Coastal dune landscapes are dynamic systems shaped by complex biotic-abiotic interactions and impacted by human disturbances. This study focuses on Mediterranean coastal dunes, analyzing spatial distribution and ecological characteristics of their plant communities through an innovative approach that integrates vegetation functional traits with UAV-based remote sensing. Using synchronized vegetation sampling and UAV surveys along the central Adriatic coast, we identified and mapped distinct eco-functional types within the dune landscape. Field sampling recorded 46 taxa, reflecting diverse habitat types according to the EUNIS classification system. Clustering based on community traits revealed four eco-functional classes with notable differences in seed mass, taxonomic diversity, and species composition, as well as variations in remotely sensed environmental parameters. The first class, situated near the drift-line, included Thinopyrum junceum, a species adapted to wind and sand movement. The second class bridged dynamic foredune and more stable areas, featuring ruderal species like Scabiosa atropurpurea. The third class, impacted by moderate environmental stresses, included Silene colorata and Bromus madritensis, with a scattered, transitional distribution. Finally, the fourth class, characterized by dense, stable vegetation, was typified by Festuca fasciculata, indicating mature dune grasslands. Our findings underscore the potential of integrating UAV remote sensing with functional trait analysis to enhance vegetation classification accuracy and enable fine-scale spatial mapping of coastal dunes. This approach offers a valuable tool for ecosystem monitoring, supporting conservation management amid rising environmental pressures. |
| format | Article |
| id | doaj-art-e8d2007a3aec42569b67f4dbfda2470b |
| institution | Kabale University |
| issn | 1470-160X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj-art-e8d2007a3aec42569b67f4dbfda2470b2025-01-30T05:13:49ZengElsevierEcological Indicators1470-160X2025-02-01171113157A novel high-resolution eco-functional vegetation mapping of coastal dunesMichele Innangi0Mirko Di Febbraro1Marco Balsi2Ginevra Colonna3Michele Finizio4Federica Pontieri5Maria Laura Carranza6EnviXLab, Dipartimento di Bioscienze e Territorio, Università del Molise, Contrada Fonte Lappone, 86090 Pesche, IS, ItalyEnviXLab, Dipartimento di Bioscienze e Territorio, Università del Molise, Contrada Fonte Lappone, 86090 Pesche, IS, Italy; Corresponding author.Dipartimento di Ingegneria dell’Informazione, Elettronica e Telecomunicazioni, Università di Roma La Sapienza, Via Eudossiana 18, 00184 Rome, ItalyDipartimento di Scienze della Terra e dell’Ambiente, Università di Pavia, Via Adolfo Ferrata 7, 27100 Pavia, ItalyEnviXLab, Dipartimento di Bioscienze e Territorio, Università del Molise, Contrada Fonte Lappone, 86090 Pesche, IS, ItalyEnviXLab, Dipartimento di Bioscienze e Territorio, Università del Molise, Contrada Fonte Lappone, 86090 Pesche, IS, ItalyEnviXLab, Dipartimento di Bioscienze e Territorio, Università del Molise, Contrada Fonte Lappone, 86090 Pesche, IS, Italy; National Biodiversity Future Center, Piazza Marina 61, 90133 Palermo, ItalyCoastal dune landscapes are dynamic systems shaped by complex biotic-abiotic interactions and impacted by human disturbances. This study focuses on Mediterranean coastal dunes, analyzing spatial distribution and ecological characteristics of their plant communities through an innovative approach that integrates vegetation functional traits with UAV-based remote sensing. Using synchronized vegetation sampling and UAV surveys along the central Adriatic coast, we identified and mapped distinct eco-functional types within the dune landscape. Field sampling recorded 46 taxa, reflecting diverse habitat types according to the EUNIS classification system. Clustering based on community traits revealed four eco-functional classes with notable differences in seed mass, taxonomic diversity, and species composition, as well as variations in remotely sensed environmental parameters. The first class, situated near the drift-line, included Thinopyrum junceum, a species adapted to wind and sand movement. The second class bridged dynamic foredune and more stable areas, featuring ruderal species like Scabiosa atropurpurea. The third class, impacted by moderate environmental stresses, included Silene colorata and Bromus madritensis, with a scattered, transitional distribution. Finally, the fourth class, characterized by dense, stable vegetation, was typified by Festuca fasciculata, indicating mature dune grasslands. Our findings underscore the potential of integrating UAV remote sensing with functional trait analysis to enhance vegetation classification accuracy and enable fine-scale spatial mapping of coastal dunes. This approach offers a valuable tool for ecosystem monitoring, supporting conservation management amid rising environmental pressures.http://www.sciencedirect.com/science/article/pii/S1470160X2500086XMediterranean dunesPlant traitsUAVsLTERMachine learning |
| spellingShingle | Michele Innangi Mirko Di Febbraro Marco Balsi Ginevra Colonna Michele Finizio Federica Pontieri Maria Laura Carranza A novel high-resolution eco-functional vegetation mapping of coastal dunes Ecological Indicators Mediterranean dunes Plant traits UAVs LTER Machine learning |
| title | A novel high-resolution eco-functional vegetation mapping of coastal dunes |
| title_full | A novel high-resolution eco-functional vegetation mapping of coastal dunes |
| title_fullStr | A novel high-resolution eco-functional vegetation mapping of coastal dunes |
| title_full_unstemmed | A novel high-resolution eco-functional vegetation mapping of coastal dunes |
| title_short | A novel high-resolution eco-functional vegetation mapping of coastal dunes |
| title_sort | novel high resolution eco functional vegetation mapping of coastal dunes |
| topic | Mediterranean dunes Plant traits UAVs LTER Machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X2500086X |
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