Highlights

A network approach to restoration ecology recently emerged as a tool for integrating methodological and theoretical advances to support environmental management and decision-making.

Adaptive network models allow us to better understand and predict how both ecological and evolutionary processes shape biodiversity and ecosystem functioning.

In adaptive networks, the feedback between the macroscopic dynamics of interaction structure and the microscopic dynamics of population-level processes shapes interactions, abundances, and traits, hence influencing resilience and functional diversity.

The increasing availability of phylogenetically-structured network data generated through next-generation sequencing techniques, alongside the standardization of biomonitoring protocols, can foster the integration of evolutionary principles into adaptive network models for ecological restoration, providing highly-resolved information for model parameterization and assessment across temporal and spatial scales.

Phylogenetically-informed adaptive network models can be used for the selection of alternative species sets to be added or removed from communities and hence can provide flexible strategies for functional biodiversity restoration that fits local socio-economic contexts.

Overcoming current theoretical and methodological gaps to build a two-way street between adaptive network models and experimental restoration ecology is now an achievable task, the resolution of which can broaden our ability to restore biodiversity and ecosystem functioning based on key ecological and evolutionary principles.