Abstract

The Lichens GO program is a French citizen science initiative based on the European guidelines that aims to evaluate the lichen diversity for urban air quality monitoring. In this study, we assessed the performance and applicability of the current Lichens GO protocol to then propose adaptations to make it more reliable and feasible for citizen science. To achieve this goal, we considered four aspects of the citizen science program: potential protocol simplifications, sampling site availability, observer bias, and volunteer feedbacks. Simulated simplification scenarios from a reference data set highlighted the large influence of reducing the number of sampled trees on taxonomic and functional structure metrics compared to reducing the number of sampled tree exposure sides and considered lichen species list. When considering the Lichens GO protocol (i.e., three trees, four exposure sides, Lichens GO species list) compared to the reference data set (i.e., five trees, four exposure sides, exhaustive species list), we evaluated an underestimation of lichen species richness (−25%), acidophilous species proportion (−94%), and functional diversity (−21%). In parallel, the maximum distance between sampled trees did not influence the taxonomic and functional structure metrics when considering a homogeneous sampling area (i.e., similar light or shade conditions). Finally, we compared Lichens GO relevés from 25 volunteers in the same site to highlight the major identification difficulties that could compromise the ecological interpretation. To improve the quality of data collected by citizens without increasing the sampling effort, we suggest to: (1) increase the maximum distance between trees from 10 to 50 m to extend the sampling site availability; (2) adapt the Lichens GO identification key to limit species confusion; and (3) assign an ecological trait to some lichen species groupings to improve the ecological interpretation. The proposed adaptations were tested and showed an improvement in the acidophilous species proportion (from −94 to −13%) and functional diversity (from −21 to −4%).

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