AFRIMED-Algal Forest Restoration in MEDiterranean sea
Published February 4, 2020 | Version v1
Journal article Open

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

Authors/Creators

  • 1. Department of Biology, University of Naples Federico II; Naples, Italy, Stazione Zoologica Anton Dohrn; Naples, Italy; CoNISMa
  • 2. CoNISMa, Rome, Italy, Department of Biology, Tor Vergata University of Rome, Rome, Italy
  • 3. Centre d'Estudis Avançats de Blanes-CSIC, Girona, Spain
  • 4. CoNISMa, Rome, Italy, Department of Biology, University of Pisa, Pisa, Italy
  • 5. Facultat de Ciències, Departamentde Ciències Ambientals, Universitat de Girona, Girona, Spain
  • 6. Department of Chemistry and Pharmacy, University of Sassari, Sassari, Italy
  • 7. CoNISMa, Rome, Italy
  • 8. Department of Geosciences, University of Malta, Msida, Malta
  • 9. CoNISMa, Rome, Italy, Department of Biological and Environmental Sciences and Technologies, University of Salento, Lecce, Italy
  • 10. Department of Life Sciences, University of Trieste, Trieste, Italy
  • 11. Department of Biological and Environmental Sciences and Technologies, University of Salento, Lecce, Italy
  • 12. Laboratory of Ecology, Earth and Marine Sciences Department, University of Palermo, Palermo, Italy
  • 13. Institute of Marine Biology, University of Montenegro, Kotor, Montenegro
  • 14. Université Côte d'Azur, CNRS, UMR 7035 ECOSEAS, Nice, France
  • 15. Department of Biological, Chemical and Pharmaceutical Sciences and Technologies, University of Palermo, Palermo, Italy
  • 16. Department of Zoology and Animal Ecology, Mohammed V University of Rabat, Rabat, Morocco
  • 17. National Institute of Oceanography, Israel Oceanographic and Limnological Research (IOLR), Haifa, Israel
  • 18. Stazione Zoologica Anton Dohrn, Naples, Italy
  • 19. Institut National Agronomique de Tunisie, University of Carthage, Tunis, Tunisia
  • 20. Faculty of Arts and Sciences, Department of Biology, Manisa Celal Bayar University, Manisa, Turkey
  • 21. Department of Biology, University of Naples Federico II; Naples, Italy, Stazione Zoologica Anton Dohrn; Naples, Italy; CoNISMa

Description

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 modeling 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.

Notes

This research was funded by the EU Interreg MED AMAre Project (http://msp-platform.eu/projects/amare-actions-marine-protected-areas) and the project MERCES of the European Union's Horizon 2020 Research (Grant Agreement No. 689518, http://www.merces-project.eu). EF was supported by Regione Lazio within the project Torno Subito, 2017 (http://www.tornosubito.laziodisu.it). We thank the collaborators on the AMAre, MERCES, and CoCoNet projects who provided the background information supporting this study. We also acknowledge the role of the project AFRIMED (EASME/EMFF/2017/1.2.1.12 – Sustainable Blue Economy).

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