Black spot syndrome in reef fishes: using archival imagery and field surveys to characterize spatial and temporal distribution in the Caribbean
Recently, observations of black spot syndrome (BSS) in Caribbean fishes have been linked to infection by a digenean trematode parasite, Scaphanocephalus expansus. Recently, This study examined the distribution of BSS over multiple spatial and temporal scales: at the island scale in Bonaire, Dutch Caribbean, using field surveys of 4885 fish belonging to three species, and across the wider Caribbean through analysis of 2112 images from Google Images searches (1985–2013). The field surveys in Bonaire indicated that the prevalence (% of individuals affected with BSS) and intensity (severity of BSS measured in 3 stages) were highest in Acanthurus tractus (prevalence 61.8%, including 30.1% in stage 3) followed by Sparisoma aurofrenatum (prevalence 48.3%, 24.1% in stage 3) and lowest in Caranx ruber (prevalence 38.5%, 3.3% in stage 3). Prevalence and intensity of BSS decreased significantly with survey depth (e.g., 2 m: prevalence 68.0%, 22.0% in stage 3; 18 m: prevalence 36.2%, 4.0% in stage 3) and were significantly lower in 2012 than in 2017 (prevalence: 59.3% in 2012, 68.7% in 2017; stage 3: 16.3% in 2012, 25.1% in 2017). The Southeast of Bonaire had significantly lower prevalence of BSS (16.4%) than the other four regions and lower intensity (11.7% in stage 3) than all regions but the Southwest. The Google Images searches querying for ocean surgeonfish, A. tractus and A. bahianus, identified pictures from 26 wider Caribbean locations; BSS was detected in 14 locations of which 13 were new, with the first detection dating back to 1985 in Bonaire. The Southern Caribbean had significantly higher prevalence of BSS (78.1%) than other ecoregions (0–34.6%), and Bonaire was identified as a hotspot, highlighting the utility of mining websites for archival imagery to quantify spatial and temporal patterns in disease phenomena. This study demonstrates how visible signs of parasite infection can be used to find differences in parasite prevalence and loads on a reef, island and sea scale.