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Engineer species, such as gorgonians, provide several ecosystem services and play a significant role in the maintenance of biodiversity, which is why it is important to identify optimal strategies for their conservation. We aimed to test an ecological niche modelling approach in the marine shallow environment and identify the ecological niche of various species of gorgonians in order to lay the scientific foundation for future conservation actions. We analyzed a unique dataset of spatialized inventories on a regular grid (< 800 m) along 450 km of coastline of five gorgonian species commonly found in the Mediterranean shallow habitats (10-50 m deep). We replicated data collection in 2013 and 2020. Fourteen environmental predictors derived from the most advanced geomorphological and hydrological data were tested to assess the ecological niche of the five species using maximum entropy (MaxENT). We tested the sensitivity of the model fit to sampling bias by reducing the number of occurrences and their geographic extent. Our results showed that there was a difference in the spatial distribution of the five gorgonian species in the Gulf of Lion: Eunicella singularis and Leptogorgia sarmentosa were widely distributed while the occurrence of Paramuricea clavata, Corallium rubrum and Eunicella cavolini was limited. The model confirmed that depth, rugosity, slope, sea surface temperature, current and turbidity can be significant drivers for gorgonians distribution, but in different associations, enabling one to differentiate the niche of four of the five species. Moreover, the model did not always identify the species specific drivers suggested in previous studies. Despite the model identifying a similar niche for E. singularis and E. cavolini (based on the environmental predictors tested), the two species, in fact, displayed very different spatial distributions in the area. For all the species, except E. cavolini, the predicted suitable habitat distribution from our model matched the observed spatial distribution. The reduction of the number of presence observations did not alter the quality of the ecological niche models as long as the observation points were spread over the entire variability range of predictors. The latter can be achieved by only including presence observations from highly protected zones of the marine protected areas of the region. Our results provide a greater understanding of the factors shaping the distribution of five gorgonian species commonly found in Mediterranean shallow areas. This is an essential step in the development of spatial planning for marine biodiversity conservation aimed at these key engineering species and their resilience to climate change.