Reliable biodiversity indicators are essential for informed conservation decisions, yet obtaining comprehensive data remains a significant challenge. While structured monitoring programs are considered the gold standard to estimate unbiased species trends, they are resource-intensive and often miss rare species. Conversely, unstructured citizen-science data provide vast spatial and temporal coverage but may be subject to systematic reporting biases. Using adapted site-occupancy models, we were able to estimate reliable temporal trends from the unstructured records of a national faunistic database, which strongly correlated (r = 0.85 across species) with the trends estimated from the structured data of the Swiss Biodiversity Monitoring (BDM). The multi-species index (MSI) based on the trends of 179 species exhibited a slight decline contrasting with the increasing species richness that was reported using the BDM data. This discrepancy likely occurred because the MSI effectively captured substantial losses in specialized groups—such as cold-adapted and oligotrophic habitat species—whereas species richness was influenced by the rise of few common species. These findings highlight that both datasets complement each other, the structured monitoring data are central to calibrate the Index whereas the unstructured data extend species coverage by reaching out rarer species. The integration of both datasets into one national index facilitates a more representative national index that covers a broader taxonomic range than traditional indicators alone. Such integrated indicators are vital for evaluating biodiversity policies and capturing the complex responses of species communities to environmental change.
Roth T., Chittaro Y., Frei J., Litsios G., Plattner M. 2026: Combining citizen-science data with data from a structured monitoring programme for a Swiss butterfly index. Ecological Indicators 190: 115230. https://doi.org/10.1016/j.ecolind.2026.115230