Location and condition of gorgonian forests in Italian coastal waters

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.