title: Calcareous Bio-Concretions in the Northern Adriatic Sea: Habitat Types, Environmental Factors that Influence Habitat Distributions, and Predictive Modeling.
abstract: Habitat classifications provide guidelines for mapping and comparing marine resources across geographic regions. Calcareous bio-concretions and their associated biota have not been exhaustively categorized. Furthermore, for management and conservation purposes, species and habitat mapping is critical. Recently, several developments have occurred in the field of predictive habitat modeling, and multiple methods are available. In this study, we defined the habitats constituting northern Adriatic biogenic reefs and created a predictive habitat distribution model. We used an updated dataset of the epibenthic assemblages to define the habitats, which we verified using the fuzzy k-means (FKM) clustering method. Redundancy analysis was employed to model the relationships between the environmental descriptors and the FKM membership grades. Predictive modelling was carried out to map habitats across the basin. Habitat A (opportunistic macroalgae, encrusting Porifera, bioeroders) characterizes reefs closest to the coastline, which are affected by coastal currents and river inputs. Habitat B is distinguished by massive Porifera, erect Tunicata, and non-calcareous encrusting algae (Peyssonnelia spp.). Habitat C (non-articulated coralline, Polycitor adriaticus) is predicted in deeper areas. The onshore-offshore gradient explains the variability of the assemblages because of the influence of coastal freshwater, which is the main driver of nutrient dynamics. This model supports the interpretation of Habitat A and C as the extremes of a gradient that characterizes the epibenthic assemblages, while Habitat B demonstrates intermediate characteristics. Areas of transition are a natural feature of the marine environment and may include a mixture of habitats and species. The habitats proposed are easy to identify in the field, are related to different environmental features, and may be suitable for application in studies focused on other geographic areas. The habitat model outputs provide insight into the environmental drivers that control the distribution of the habitat and can be used to guide future research efforts and cost-effective management and conservation plans.
authors.affiliation: Department of Life Sciences, University of Trieste, Trieste, Italia.
authors.forename: Annalisa
authors.initials: A
authors.lastname: Falace
authors.affiliation: Department of Life Sciences, University of Trieste, Trieste, Italia.
authors.forename: Sara
authors.initials: S
authors.lastname: Kaleb
authors.affiliation: SELC Society Marghera, Venezia, Italia.
authors.forename: Daniele
authors.initials: D
authors.lastname: Curiel
authors.affiliation: SELC Society Marghera, Venezia, Italia.
authors.forename: Chiara
authors.initials: C
authors.lastname: Miotti
authors.affiliation: National Institute of Oceanography and Experimental Geophysics-OGS, Trieste, Italia.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Galli
authors.affiliation: National Institute of Oceanography and Experimental Geophysics-OGS, Trieste, Italia.
authors.forename: Stefano
authors.initials: S
authors.lastname: Querin
authors.affiliation: Centre d'Estudis Avançats de Blanes-CSIC, Girona, España.
authors.forename: Enric
authors.initials: E
authors.lastname: Ballesteros
authors.affiliation: National Institute of Oceanography and Experimental Geophysics-OGS, Trieste, Italia.
authors.forename: Cosimo
authors.initials: C
authors.lastname: Solidoro
authors.affiliation: National Institute of Oceanography and Experimental Geophysics-OGS, Trieste, Italia.
authors.forename: Vinko
authors.initials: V
authors.lastname: Bandelj
mesh_terms: D000818:Animals; D037421:Anthozoa; D044822:Biodiversity; D017753:Ecosystem; D017143:Fuzzy Logic; D008962:Models, Theoretical; D009792:Oceans and Seas