Skip to main content
Dryad logo

Data from: Identifying conservation priorities for gorgonian forests in Italian coastal waters with multiple methods including citizen science and social media content analysis

Citation

Liconti, Arianna (2022), Data from: Identifying conservation priorities for gorgonian forests in Italian coastal waters with multiple methods including citizen science and social media content analysis, Dryad, Dataset, https://doi.org/10.5061/dryad.5hqbzkh81

Abstract

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 sources, 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.

Methods

Data on the distribution, abundance, and condition of seven major habitat-forming species of gorgonians in Italian coastal waters was acquired, collated, and evaluated using a multi-source data synthesis workflow: 1.) peer-reviewed and grey literature; 2.) citizen science projects; 3.) archived survey datasets available on the World Wide Web (WWW) including social media diver observations (photos and videos); and 4.) questionnaires completed after diving by SCUBA divers. Data on marine protected area locations and type were obtained from the World Database on Protected Areas (UNEP-WCMC & IUCN 2019).

Scientific data were gathered using a systematic literature review based on a specific list of search terms (English and Italian language) entered into the internet search engine Google Scholar. Google Data was extracted from a total of 50 scientific publications. For C. rubrum, a large amount of data was extracted from the comprehensive CorMedNet dataset (http://cormednet.medrecover.org/). 

Data from citizen science activities were provided by Reef Check Italia (RCI) (https://www.reefcheckmed.org/) and extracted from iNaturalist (https://www.inaturalist.org/). These data originated from SCUBA diver surveys and underwater photographs conducted by trained observers. All records were quality checked following Cerrano et al., 2017 and iNaturalist research grade peer validation.

Information acquired from the WWW included amateur underwater videos and pictures obtained mainly from Facebook and YouTube (the latest information obtained was dated 17/05/2019). A standardised sequence of steps was applied to retrieve ecological information on the focal species. Terms were searched in both English and Italian language to include social media posts from non-English speakers. The Purple Octopus crowdsourcing tool (http://www.purpleoctopus.org/groupsourcing/index.php) was used to explore the messages and images posted on Facebook by combining the data with the selected species names. Names and locations of Italian dive sites (www.logbookimmersioni.it) were used as key terms to further retrieve ecological information on the focal species. Photographs and video taken in Italian coastal waters were observed by experts to identify species to select information only where one of the seven focal species were observed. Authors of material published on the WWW were contacted, where possible, by social media message or email for more details about the record, such as dive date, exact location, depth and temperature. Records lacking information on date and dive location were discarded. The abundance and extent of damage of the gorgonian forest was estimated visually and assigned to impact classes following a standardized method, and additional visual information was also recorded.

All records were quality checked through a data validation process based on literature cross checking (e.g., consistency among reported species) and manual procedures (e.g., matching dive site names to geographic coordinates). The origin of all inconsistent data was further investigated to attempt its correction. All data failing the quality control after further inspection was permanently deleted from the database. The resulting dataset comprises separate records for each single species found by each observer/scientific publication in a diving site. Diving sites (n = 61) were localised using geographical coordinates (Datum WGS84) and a minimum accuracy of ± 15?? (= ± 0.00417°) was assured.

Usage Notes

The decimal accuracy of Corallium rubrum locations was decreased in order to preserve the vulnerability of the species.