Biodiversity data requirements for systematic conservation planning in the Mediterranean Sea
Author
COLL, Marta
FRASCHETTI, Simonetta
GAL, Gideon
GIAKOUMI, Sylvaine
Goke, Cordula
HEYMANS, Johanna Jacomina
KATSANEVAKIS, Stelios
MAZOR, Tessa
RILOV, Gil
GAJEWSKI, Juliusz
Ozturk, Bayram
STEENBEEK, Jeroen
KARK, Salit
LEVIN, Noam
Metadata
Show full item recordAbstract
The Mediterranean Sea's biodiversity and ecosystems face many threats due to anthropogenic pressures. Some of these include human population growth, coastal urbanization, accelerated human activities, and climate change. To enhance the formation of a science-based system of marine protected areas in the Mediterranean Sea, data on the spatial distribution of ecological features (abiotic variables, species, communities, habitats, and ecosystems) is required to inform conservation scientists and planners. However, the spatial data required is often lacking. In this review, we aimed to address the status of our knowledge for 3 major types of spatial information: bathymetry, classification of marine habitats, and species distributions. To exemplify the data gaps and approaches to bridge them, we examined case studies that systematically prioritize conservation in the Mediterranean Sea. We found that at present the data required for conservation planning is generally more readily available and of better quality for the European countries located in the Western Mediterranean Sea. Additionally, the Mediterranean Sea is lagging behind other marine regions where rigorous criteria for conservation planning has been applied in the past 20 yr. Therefore, we call upon scientists, governments, and international governmental and non-governmental organizations to harmonize current approaches in marine mapping and to develop a framework that is applicable throughout the Mediterranean region. Such coordination between stakeholders is urgently needed before more countries undertake further extensive habitat mapping, so that future conservation planning can use integrated spatial datasets.
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