Structure and diversity patterns of coralligenous cliffs across three ecoregions in the Central‐Western Mediterranean Sea

作者：Edoardo Casoli, Stefano Moro, Matteo Falasca, Monica Montefalcone, Lucia Rizzo, Núria Teixidó, Luigi Piazzi, Caterina Longo, Maria Mercurio, Paola Gennaro, Enrico Cecchi, Marina Penna, María Cristina Gambi, Alice Mirasole, Enric Ballesteros, Marco Andrello, Daniele Ventura, Gianluca Mancini, Andrea Belluscio, Simonetta Fraschetti, Giandomenico Ardizzone, Giovanna Jona‐Lasinio · 发表于：Diversity and Distributions · 年份：2024 · DOI：10.1111/ddi.13833 · 被引用次数：9 · 研究领域：Coral and Marine Ecosystems Studies、Marine Biology and Ecology Research、Marine and coastal plant biology

Abstract Aim Coralligenous reefs are the main marine bioconstructions in terms of spatial distribution within the Mediterranean basin. Two distinct reef morphologies can be distinguished based on the surface and topographical features of the seafloor: cliffs developing vertical slopes and banks found on gently steep or horizontal bottoms. Despite their importance for monitoring and conservation efforts, observations regarding the variability of biogeographical patterns are scarce. Here, we aimed to assess the differences in the composition and structure of these cliffs across ecoregions and estimate the relative role of abiotic environmental features, geographic location, and connectivity in shaping diversity patterns. Location The study was carried out in the Central‐Western Mediterranean Sea. Samples were collected at 65 sites across the Algero‐Provençal Basin, the Ionian Sea and the Tyrrhenian Sea. Methods We assessed the composition and structure of coralligenous cliffs through photographic samplings collected by scuba divers. Patterns in α‐ and β‐diversity were associated with 9 abiotic environmental variables, latitudinal and longitudinal gradients, and connectivity measures using Generalized Additive (GAM) and Conditional Autoregressive (CAR) models. Results Coralligenous cliffs were primarily composed of algae and displayed a high degree of variability. The Partition Around Medoids (PAM) clustering method successfully delineated seven distinct clusters with a non‐unif...