Gorgonian forests are among the most complex of subtidal habitats in the Mediterranean Sea, supporting high biodiversity and providing diverse ecosystem services. Despite their iconic status, the geographical distribution and condition of gorgonian species is poorly known. Using multiple online data types our primary aims were to compile, map and analyse observations of gorgonian forests in Italian coastal waters to assess the biological complexity of gorgonian forests; evaluate impacts and vulnerable species, and identify areas of special interest inside and outside of existing MPAs to help prioritise conservation strategies and actions.

Location: Italy. Mediterranean Sea.

Methods: Using a multi-source data integration approach we collected and integrated data from
scientific publications, online databases, citizen science projects, SCUBA diver questionnaires and social media into a unified spatial framework providing up-to-date information on the geographical distribution, abundance, and health of major habitat-forming gorgonian species in Italian coastal waters.

Results: Higher abundance and complexity of gorgonian species occurred outside MPAs. Areas of Special Interest (n=167) were identified (80 inside and 87 outside MPAs). Three locations supported all seven focal species: Capo Caccia MPA, Portofino MPA and Catania (unprotected). The purple gorgonian (Paramuricea clavata), the most abundant and geographically widespread species with highest forest complexity, also experienced the highest impact, possibly linked to thermal stress events, disease and fishing.

Main conclusions: The multi-source approach was a rapid and cost-effective tool to gather, analyse and map disparate data on gorgonian forests spanning 27 years of underwater observations both inside and outside of marine protected areas (MPAs). The unique perspective given by this approach demonstrates the suboptimal protection of several habitat-forming gorgonian species. The approach has great potential for wider application and offers a more inclusive participatory model for crowdsourcing and repurposing underutilised observations while also increasing ocean literacy.

Using a multi-source data integration approach we collected and integrated data from
scientific publications, online databases, citizen science projects, SCUBA diver questionnaires and social media into a unified spatial framework providing up-to-date information on the geographical distribution, abundance, and health of major habitat-forming gorgonian species in Italian coastal waters.

Null = no data recorded or not applicable.