The potential of Citizen Science for Natural Capital and Ecosystem Services assessment in agri-environmental systems

Citizen science (CS), broadly understood as public participation in scientific research, has been rapidly growing in many fields of application and with different foci, encompassing approaches such as community-based monitoring, citizen observatories, and volunteered geographic information, amongst others. Recently, linkages of CS with Ecosystem Services (ES) and Natural Capital (NC) approaches have been explored, uncovering existing links as well as identifying ways in which CS can help advance such approaches. National strategy plans, including the UK’s Natural Capital and Ecosystem Assessment, are also starting to recognise CS as one important building block for data collection and implementation of such plans. This presentation will situate CS in relation to ES and NC approaches focusing on agri-environmental systems, outlining the current state of understanding and highlighting several areas in which CS can provide tested methods and mechanisms to the NC/ES field including integration with national NC/ES assessment frameworks, using CS for NC/ES research and modelling as well as establishing localised approaches, such as community-based and co-developed NC/ES monitoring and management networks and programmes. We will provide use cases from agriculture and natural resource management across the globe, including from the FRAMEwork project, to illustrate the examples, and outline challenges and opportunities for future applications. Parallels will also be drawn to related sustainability-focused concepts and assessment frameworks, such as the Sustainable Development Goals and the Post-2020 Global Biodiversity Framework, where the potential of CS to contribute to official indicator monitoring as well as goal and target level implementation has been studied in-depth and demonstrated by several examples. Policy pathways and recommended roadmaps developed for linking the SDGs with citizen science will further illuminate the potential of CS for enriching NC and ES framing and assessmen