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https://hdl.handle.net/123456789/1755| Τύπος: | Άρθρο σε επιστημονικό περιοδικό |
| Τίτλος: | Predictive mapping of Mediterranean seagrasses-exploring the influence of seafloor light and wave energy on their fine-scale spatial variability |
| Συγγραφέας: | [EL] Φακίρης, Ηλίας[EN] Fakiris, Elias [EL] Γιαννακόπουλος, Βασίλειος[EN] Giannakopoulos, Vasileios [EL] Λευθεριώτης, Γεώργιος[EN] Leftheriotis, Georgios [EL] Δήμας, Αθανάσιος[EN] Dimas, Athanassios [EL] Παπαθεοδώρου, Γεώργιος[EN] Papatheodorou, George |
| Ημερομηνία: | Ιου-2023 |
| Περίληψη: | Seagrasses are flowering plants, adapted to marine environments, that are highly diverse in the Mediterranean Sea and provide a variety of ecosystem services. It is commonly recognized that light availability sets the lower limit of seagrass bathymetric distribution, while the upper limit depends on the level of bottom disturbance by currents and waves. In this work, detailed distribution of seagrass, obtained through geoacoustic habitat mapping and optical ground truthing, is correlated to wave energy and light on the seafloor of the Marine Protected Area of Laganas Bay, Zakynthos Island, Greece, where the seagrasses Posidonia oceanica and Cymodocea nodosa form extensive meadows. Mean wave energy on the seafloor was estimated through wave propagation modeling, while the photosynthetically active radiation through open-access satellite-derived light parameters, reduced to the seafloor using the detailed acquired bathymetry. A significant correlation of seagrass distribution with wave energy and light was made clear, allowing for performing fine-scale predictive seagrass mapping using a random forest classifier. The predicted distributions exhibited >80% overall accuracy for P. oceanica and >90% for C. nodosa, indicating that fine-scale seagrass predictive mapping in the Mediterranean can be performed robustly through bottom wave energy and light, especially when detailed bathymetric data exist to allow for accurate estimations. |
| Γλώσσα: | Αγγλικά |
| Σελίδες: | 18 |
| DOI: | 10.3390/rs15112943 |
| EISSN: | 2072-4292 |
| Θεματική κατηγορία: | [EL] Άλλες φυσικές επιστήμες[EN] Other natural sciences |
| Λέξεις-κλειδιά: | P. oceanica; C. nodosa; wave bottom orbital velocity; photosynthetically active radiation; habitat predictive modeling; acoustic habitat mapping; wave propagation modeling; Laganas Bay; Zakynthos Island |
| Κάτοχος πνευματικών δικαιωμάτων: | © 2023 by the authors. Licensee MDPI, Basel, Switzerland. |
| Όροι και προϋποθέσεις δικαιωμάτων: | This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). |
| Ηλεκτρονική διεύθυνση του τεκμηρίου στον εκδότη: | https://www.mdpi.com/2072-4292/15/11/2943 |
| Ηλεκτρονική διεύθυνση περιοδικού: | https://www.mdpi.com/journal/remotesensing |
| Τίτλος πηγής δημοσίευσης: | Remote Sensing |
| Τεύχος: | 11 |
| Τόμος: | 15 |
| Σελίδες τεκμηρίου (στην πηγή): | Article no 2943 |
| Σημειώσεις: | This research was co-financed by Greece and the European Union (European Social FundESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning» in the context of the project “Reinforcement of Postdoctoral Researchers—2nd Cycle” (MIS-5033021), implemented by the State Scholarships Foundation (IKΥ). Data acquisition was funded by the Management Agency of the National Marine Park of Zakynthos in the framework of the project ‘Monitoring of coastal and marine habitat types of EU community interest’ funded by the European Regional Development Fund (ERDF) and National resources (Operational Programme ‘Environment and Sustainable Development’ under the NSRF 2007–2013). |
| Εμφανίζεται στις συλλογές: | Μεταδιδακτορικοί ερευνητές |
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