Coastal landscapes are under increasing threat from expanding and intensifying human activities, and so have been the target for conservation management projects globally. However, several key challenges remain that hinder the efficacy of management in coastal landscapes, including 1) setting goals and actions at landscape scales, 2) identifying suitable indicator metrics and taxa from biodiverse ecosystems and 3) a lack of this baseline spatial and ecological data being used in planning. In this study, we used novel approaches to optimise the conservation and management of coastal dune landscapes, one of the most commonly restored coastal ecosystems, and assess the efficacy of different monitoring and management techniques. We used spatial modelling of plant assemblages to demonstrate that each species has a unique set of preferred conditions, based on their response to environmental and landscape variables at multiple spatial scales. We integrated data on the distribution, abundance and condition of key habitat forming species (indicators), into multiple distribution models to identify the locations and planting regimes for restoration sites. We used DNA metabarcoding to demonstrate its advantages for detecting potentially hidden patterns in biodiversity at landscape scales. Together, these approaches provide frameworks that overcome key challenges surrounding effective management of coastal ecosystems.