Résumé
Over the last decades, large‐scale ecological projects have emerged that require collecting ecological data over broad spatial and temporal coverage. Yet, obtaining relevant information about large‐scale population dynamics from a single monitoring programme is challenging, and often several sources of data, possibly heterogeneous, need to be integrated. In this context, integrated models combine multiple data types into a single analysis to quantify the population dynamics of a targeted population. When working at large geographical scales, integrated spatial models have the potential to produce spatialized ecological estimates that would be difficult to obtain if data were analysed separately. In this study, we illustrate how spatial integrated modelling offers a relevant framework for conducting ecological inference at large scales. Focusing on the Mediterranean bottlenose dolphins ( Tursiops truncatus ), we combined 21,464 km of photo‐identification boat surveys collecting spatial capture–recapture data with 24,624 km of aerial line transect following a distance sampling protocol. We analysed spatial capture–recapture data together with distance sampling data to estimate the abundance and density of bottlenose dolphins. We compared the performances of the distance sampling model and the spatial capture–recapture model fitted independently to our integrated spatial model. The outputs of our spatial integrated models inform bottlenose dolphin ecological status in the French Mediterranean Sea and provide ecological indicators that are required for regional‐scale ecological assessments like the EU Marine Strategy Framework Directive. We argue that integrated spatial models are widely applicable and relevant to conservation research and biodiversity assessment at large spatial scales.