Aim In the context of intensifying threats of climate change on marine communities, ecological models are widely applied for conservation strategies, though polar studies remain scarce given the limited number of datasets available. Correlative (e.g. species distribution models, SDM) and mechanistic (e.g. dynamic energy budget models, DEB) modelling approaches are usually used independently in studies. Using both approaches in integrative, hybrid models could help to better estimate the species potential ecological niche, as mechanistic and correlative models complement each other very well, giving more insights into species potential response to fast-changing environmental conditions. Location The study focusses on the Baie du Morbihan, a silled basin located in the east of the Kerguelen Islands (sub-Antarctic). Methods A hybrid, correlative-mechanistic model was implemented to predict the response of the endemic sea urchin Abatus cordatus (Verrill, 1876). We compared the performances of classic and integrated approaches to predict A. cordatus distribution according to two dates representing seasonal contrasts. Two integrated approaches were studied and performed by either (1) including the spatial projection of the DEB model as an input layer inside the SDM ('integrated SDM-DEB') or (2) using a Bayesian procedure to use DEB model outputs as priors of the SDM ('integrated Bayesian' approach). Results Results show higher performances of 'integrated Bayesian' approaches to evaluate A. cordatus potential ecological niche compared with 'classic' and 'integrated SDM-DEB' methods. The influence of environmental conditions on model predictions is further captured with these Bayesian procedures and better highlights the environmental influence on the species-predicted distribution. Model performance is good for the different simulations, and uncertainty in predictions is well-highlighted. Main conclusions The good performances of 'integrated Bayesian' approaches to estimate species potential ecological niche opens perspectives for future applications to a broad panel of natural examples, noteworthy for decision-making and conservation management purposes.