Bridging Monitoring Needs and Citizen Science Potentials: A National Assessment of Opportunities and Gaps for Biodiversity Monitoring in Germany

Reliable information on the state of biodiversity depends on long-term, spatially representative, and taxonomically valid monitoring data. Citizen science (CS) is increasingly considered a complementary and valuable component of biodiversity monitoring, yet its suitability for meeting specific monitoring needs has rarely been assessed systematically. To address this, we conducted a nationwide anonymous survey among about 350 stakeholders involved in professional and CS-based biodiversity monitoring in Germany. Respondents evaluated key structural needs for improvement in current monitoring programs and assessed the perceived ability of CS to address these needs.
To synthesize the responses, we systematically compared perceived monitoring needs with the perceived suitability of CS for the same set of criteria. This comparison yields a data-driven, conceptual gap framework identifying three key areas of i) strong potential, where CS aligns well with high monitoring needs; ii) critical gaps, where needs are high, but CS is considered unsuitable without additional support; and iii) intermediate zones, where CS may contribute under certain conditions. 
High needs in monitoring were reported for improving data continuity and quality, spatial and temporal coverage, methodological consistency, and taxonomic expertise. CS was considered particularly well-suited to contributing to areas of strong potential, such as expanding sampling coverage, supporting long-term datasets, and offering opportunities for training, engagement and piloting new methods. Conversely, critical gaps emerged for tasks requiring specialized taxonomic expertise, rigorous validation or strict standardization—areas in which CS would require additional infrastructures, professional oversight, or hybrid models to contribute effectively. 
Additionally, an exploratory subset of species and data experts investigated these patterns qualitatively and more in detail. Lastly, respondents identified key criteria in successful CS projects. 
Together, these findings offer a structured, evidence-based framework for where CS can meaningfully contribute to national biodiversity monitoring and indicators and where targeted investment, coordination, or expertise are required. The results provide actionable guidance for designing scalable monitoring architectures aligned with national and GBF targets.