This Data_DD_README.txt file was generated on 2022-03-17 by Arianna Liconti GENERAL INFORMATION 1. Title of Dataset: Data from: Identifying conservation priorities for gorgonian forests in Italian coastal waters with multiple methods including citizen science and social media content analysis 2. Author Information A. Principal Investigator Contact Information Name: Arianna Liconti Institution: The Marine Biological Association Address: The Laboratory, Citadel Hill, Plymouth, PL1 2PB, UK Email: arianna.liconti@outlook.it B. Co-investigator 1 Name: Simon Pittman Institution: School of Biological and Marine Sciences, Plymouth University Address: Drake Circus, Plymouth, PL4 8AA, UK Email: sjpittman@gmail.com C. Co-investigator 2 Name: Sian Rees Institution: School of Biological and Marine Sciences, Plymouth University Address: Drake Circus, Plymouth, PL4 8AA, UK Email: sian.rees@plymouth.ac.uk D. Co-investigator 3 Name: Nova Mieszkowska Institution: University of Liverpool Address: Liverpool, Brownlow Hill, L69 3BX, UK Email: nova.mieszkowska@liverpool.ac.uk 3. Date of data collection: 2018-2020 4. Geographic location of data collection: Italy 5. Information about funding sources that supported the collection of the data: Worldrise ONLUS 6. Was data derived from another source? yes A. If yes, list source(s): 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 7. Recommended citation for this dataset: Liconti et al. (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 DATA & FILE OVERVIEW 1. File List: Data_DD.csv METHODOLOGICAL INFORMATION 1. Description of methods used for collection/generation of data: 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. 2. Methods for processing the data: 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. 3. Instrument- or software-specific information needed to interpret the data: All mapping and geographical analyses were carried out using QGIS (QGIS Development Team 2019). Records were aggregated in cells of a 15-arc minute grid (= 0.25¡; 27.78 km) to analyse the dataset at a coarse scale, by a 54-arc second grid (=0.9¡; 10 km) for indices analyses, and a 15-arc second grid (= 0.004¡; 463 m) for finer scale analyses at the scale of a single dive site. All statistical analyses were carried out in R v3.2.1 (R Core Team 2019) using nmle, multicomp and MASS packages DATA-SPECIFIC INFORMATION FOR: [FILENAME] 1. Number of variables: 43 2. Number of cases/rows: 4687 3. Variable List: Fid: ID number of data entry Log ID: ID number of log entry RCI ID: Reef Check Italy ID number Source ID: ID number of source Species: name of considered gorgonian species Latitude: Latitude Longitude: Longitude Abundance: Abundance following Reef Check Italy classes. Abundances of E. cavolini, E. singularis, E. verrucosa, S. savaglia, L. sarmentosa and P. calavata were recorded according to the following classes: 1= 1 individual, 2 = 2 individuals, 5 = 3-5 individuals, 10 = 5-10 individuals, 50 = 11-50 individuals and 100 = >51. For C. rubrum, the recorded classes were: 1 = an isolated specimen, 2 = some scattered specimens, 5 = several scattered specimens, 10 = one crowded area, 50 = some crowded areas and 100 = several crowded areas. Date: gg/mm/yyy Year: yyyy Dive site: name of dive site Depth_m: Depth of observation when available (m) P.clavata colour: colour of P. clavate observed (red, yellow and red & yellow) Extent of damage: Percentage of estimated damage: 0% damage for a healthy colony, 10%, 25%, 50%, 75%, 99% damage in order of gravity, and 100% for a dead colony Injury type: typer of damage (c: from the centre; d: from the ends of the branches) Epibionts: presence or absence of epibionts Mucilage: presence or absence of mucilage assemblages Fishing lines: presence or absence of fishing lines Bad Diving Behaviours: presence or absence of bad diving behaviour in videos Nursery Habitat: presence or absence of eggs/ juveniles on/around the gorgonians Invasive species: presence or absence of invasive species Mortality: presence or absence of dead colonies Comments: any comments to the observation Source: Data collection source in macrocathegories (CS: citizen science; SCI: peer reviewed publications: WWW: World Wide Web; DQ: Divers Questionnaire) Source (specific): Specific source of data Reference: code of reference of citation Left: left corner of geographical grid Top: top corner of geographical grid Right: right corner of geographical grid Bottom: bottom corner of geographical grid Id: Geographical grid ID WDPAID: Protected Area Code ORIG_NAME: Name of protected area DESIG_ENG: name of designation of protected area DESIG_TYPE : type of designation of protected area IUCN_CAT: IUCN cathegory of protected area REP_M_AREA: latitude code of protected area GIS_M_AREA: latitude of protected area REP_AREA: longitude code of protected area GIS_AREA: longitude of protected area NO_TAKE: reported no take zone STATUS_YR: year of establishment of protected area MANG_AUTH: managing authority of protected area 4. Missing data codes: null 5. Specialized formats or other abbreviations used: CS: citizen science; SCI: peer reviewed publications: WWW: World Wide Web; DQ: Divers Questionnaire; RCI: Reef Check Italy