To account for progress towards conservation targets, monitoring systems should capture not only information on biodiversity but also knowledge on the dynamics of ecological processes and the related effects on human well-being. Protected areas represent complex social-ecological systems with strong human-nature interactions. They are able to provide relevant information about how global and local scale drivers (e.g., climate change, land use change) impact biodiversity and ecosystem services. Here we develop a framework that uses an ecosystem-focused approach to support managers in identifying essential variables in an integrated and scalable approach. We advocate that this approach can complement current essential variable developments, by allowing conservation managers to draw on system-level knowledge and theory of biodiversity and ecosystems to identify locally important variables that meet the local or sub-global needs for conservation data. This requires the development of system narratives and causal diagrams that pinpoints the social-ecological variables that represent the state and drivers of the different components, and their relationships. We describe a scalable framework that builds on system based narratives to describe all system components, the models used to represent them and the data needed. Considering the global distribution of protected areas, with an investment in standards, transparency, and on active data mobilisation strategies for essential variables, these have the potential to be the backbone of global biodiversity monitoring, benefiting countries, biodiversity observation networks and the global biodiversity community.