A rapid photographic method detects depth gradient in coralligenous assemblages

Coralligenous assemblages represent the unique calcareous formations of biogenic origin in the Mediterranean Sea. Despite their importance in terms of biodiversity and biomass production, community analyses remain scarce. Actual sampling of these assemblages is complicated to carry out because their depth distribution (down to − 120 m) necessitates complex diving logistics. We highlight a rapid, cost-effective, objective and accurate method for the sampling of coralligenous assemblages and tested its efficiency in delineating a depth gradient. We compared seven photographic methods for estimating the percentage cover of sessile organisms: visual estimates (VS) with the aid of a 25, 64 or 100 square-grid and random-point-quadrats (RQ) with 25, 64 or 100 random points or 64 stratified random points. Comparisons were made using two simulated quadrats for which percent cover values were known. RQ with 64 random points was the method that accumulated the highest number of advantages. Using this method, two field sites were sampled by divers at three depths (− 50, − 60 and − 70 m) with increasing replication (10, 20, 30 and 40 photographic quadrats). The communities deduced from the 30 and 40 photos were similar. Community analyses showed an effect of depth nested in site on the assemblages observed. With increasing depth, encrusting algae get replaced by Porifera. Dissimilarity between − 50 m and − 60 m/− 70 m was mainly due to Crambe tailliezi abundance. This methodology will be a useful tool for managers and administrators; it guarantees fast abundance estimation, non-destructive repeated sampling, the possibility of comparison among researchers and the permanent record of deep-sea communities.

► We present a fast and objective method for the survey of coralligenous assemblages.
► We compare 7 photographic methods of estimating percent covers of sessile organisms.
► Using simulated quadrats, random-point-quadrats with 64 points is the best method.
► In the field, communities deduced from 30 to 40 photographic quadrats are similar.
► The method is able to detect a depth gradient in natural coralligenous assemblages.