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2. Modeling Macroalgal Forest Distribution at Mediterranean Scale: Present Status, Drivers of Changes and Insights for Conservation and Management

Author

Erika Fabbrizzi, Michele Scardi, Enric Ballesteros, Lisandro Benedetti-Cecchi, Emma Cebrian, Giulia Ceccherelli, Francesco De Leo, Alan Deidun, Giuseppe Guarnieri, Annalisa Falace, Silvia Fraissinet, Chiara Giommi, Vesna Mačić, Luisa Mangialajo, Anna Maria Mannino, Luigi Piazzi, Mohamed Ramdani, Gil Rilov, Luca Rindi, Lucia Rizzo, Gianluca Sarà, Jamila Ben Souissi, Ergun Taskin, Simonetta Fraschetti, Department of Biology, University of Naples Federico II, Naples, Italy, Stazione Zoologica Anton Dohrn, Naples, Italy, CoNISMa, Rome, Italy, Department of Biology, Tor Vergata University of Rome, Rome, Italy, Centre d’Estudis Avançats de Blanes-CSIC, Girona, Spain, Department of Biology, University of Pisa, Pisa, Italy, Facultat de Ciències, Departament de Ciències Ambientals, Universitat de Girona, Girona, Spain, Department of Chemistry and Pharmacy, University of Sassari, Sassari, Italy, Department of Geosciences, University of Malta, Msida, Malta, Department of Biological and Environmental Sciences and Technologies, University of Salento, Lecce, Italy, Department of Life Sciences, University of Trieste, Trieste, Italy, Laboratory of Ecology, Earth and Marine Sciences Department, University of Palermo, Palermo, Italy, Institute of Marine Biology, University of Montenegro, Kotor, Montenegro, Université Côte d’Azur, CNRS, UMR 7035 ECOSEAS, Nice, France, Department of Biological, Chemical and Pharmaceutical Sciences and Technologies, University of Palermo, Palermo, Italy, Department of Zoology and Animal Ecology, Mohammed V University of Rabat, Rabat, Morocco, National Institute of Oceanography, Israel Oceanographic and Limnological Research (IOLR), Haifa, Israel, Institut National Agronomique de Tunisie, University of Carthage, Tunis, Tunisia, Faculty of Arts and Sciences, Department of Biology, Manisa Celal Bayar University, Manisa, Turkey, Fabbrizzi, E., Scardi, M., Ballesteros, E., Benedetti-Cecchi, L., Cebrian, E., Ceccherelli, G., De Leo, F., Deidun, A., Guarnieri, G., Falace, A., Fraissinet, S., Giommi, C., Macic, V., Mangialajo, L., Mannino, A. M., Piazzi, L., Ramdani, M., Rilov, G., Rindi, L., Rizzo, L., Sara, G., Souissi, J. B., Taskin, E., Fraschetti, S., Fabbrizzi, Erika, Scardi, Michele, Ballesteros, Enric, Benedetti-Cecchi, Lisandro, Cebrian, Emma, Ceccherelli, Giulia, De Leo, Francesco, Deidun, Alan, Guarnieri, Giuseppe, Falace, Annalisa, Fraissinet, Silvia, Giommi, Chiara, Macic, Vesna, Mangialajo, Luisa, Mannino, Anna Maria, Piazzi, Luigi, Ramdani, Mohamed, Rilov, Gil, Rindi, Luca, Rizzo, Lucia, Sarà, Gianluca, Ben Souissi, Jamila, Taskin, Ergun, and Fraschetti, Simonetta

Subjects
Settore BIO/07 - Ecologia, Cystoseira canopies, Habitat suitability model, Mediterranean Sea, Random Forest, Species distribution, 0106 biological sciences, lcsh:QH1-199.5, Settore BIO/07, Distribution (economics), Ocean Engineering, lcsh:General. Including nature conservation, geographical distribution, Aquatic Science, Cystoseira canopie, Oceanography, 010603 evolutionary biology, 01 natural sciences, Mediterranean scale, Brown algae -- Mediterranean see, Algues brunes -- Distribució geogràfica, Mediterranean sea, Marine resources -- Management -- Mediterranean Sea, media_common.cataloged_instance, 14. Life underwater, European union, lcsh:Science, Algues brunes -- Mediterrània, Mar, Water Science and Technology, media_common, Global and Planetary Change, Marine ecology -- Mediterranean Sea, business.industry, Settore BIO/02 - Botanica Sistematica, 010604 marine biology & hydrobiology, Environmental resource management, Marine habitats -- Mediterranean Sea, 15. Life on land, Habitat suitability model (HSM), Geography, 13. Climate action, Settore BIO/03 - Botanica Ambientale E Applicata, lcsh:Q, Cystoseira canopies, habitat suitability model, Mediterranean Sea, Random Forest, species distribution, business, Marine algae -- Mediterranean Sea, Brown algae -- Geographical distribution
Abstract

Macroalgal forests are one of the most productive and valuable marine ecosystems, but yet strongly exposed to fragmentation and loss. Detailed large-scale information on their distribution is largely lacking, hindering conservation initiatives. In this study, a systematic effort to combine spatial data on Cystoseira C. Agardh canopies (Fucales, Phaeophyta) was carried out to develop a Habitat Suitability Model (HSM) at Mediterranean scale, providing critical tools to improve site prioritization for their management, restoration and protection. A georeferenced database on the occurrence of 20 Cystoseira species was produced collecting all the available information from published and grey literature, web data portals and co-authors personal data. Data were associated to 55 predictor variable layers in the (ASCII) raster format and were used in order to develop the HSM by means of a Random Forest, a very effective Machine Learning technique. Knowledge about the distribution of Cystoseira canopies was available for about the 14% of the Mediterranean coastline. Absence data were available only for the 2% of the basin. Despite these gaps, our HSM showed high accuracy levels in reproducing Cystoseira distribution so that the first continuous maps of the habitat across the entire basin was produced. Misclassification errors mainly occurred in the eastern and southern part of the basin, where large gaps of knowledge emerged. The most relevant drivers were the geomorphological ones, followed by anthropogenic variables proxies of pollution and urbanization. Our model shows the importance of data sharing to combine a large number of spatial and environmental data, allowing to individuate areas with high probability of Cystoseira occurrence as suitable for its presence. This approach encourages the use of this modelling tool for the prediction of Cystoseira distribution and for supporting and planning conservation and management initiatives. The step forward is to refine the spatial information of presence-absence data about Cystoseira canopies and of environmental predictors in order to address species-specific assessments.

Published
2020
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