Using citizen science to estimate lichen diversity

Abstract Lack of field time, access to experts, and the challenges associated with research permits make traditional approaches for determining species richness (comprehensive collection and determination of biological specimens) impractical in many situations. To accelerate local biodiversity assessments for conservation and resource management, scientists need both cost-effective survey methods and validated statistical models that link sample data to estimates of true species richness. Lichen communities are reliable indicators for the condition of many different terrestrial ecosystems because they are sensitive to environmental stress and represent a promising system in which to develop alternative approaches to biodiversity monitoring. We propose a citizen scientist-based survey methodology for macrolichen diversity in which parataxonomic units (PUs), as identified in lichen photographs, serve as species surrogates to estimate lichen diversity. We validate this method by photographically surveying lichens at five park units previously surveyed as part of the Lichen Biomonitoring Project (LBP) at George Mason University. Using the Chao2 metric to account for variation in sampling effort, we compared observed (raw PU counts) and estimated (effort-corrected) PU and species richnesses and found that, for all park units, our methodology gave similar diversity estimates to those obtained by the LBP. While PUs provide rapid assessment of diversity within a sample, they do not address the challenge of upscaling from samples to estimate total species diversity in an area. We propose a statistical method to estimate PU richness that, unlike phenomenological methods like Chao2, can exploit replication in our sampling design to explicitly model PU occupancy and detection probability. In sum, we present new methods for both surveying diversity and extrapolating sample data that can be widely applied for rapid assessment of biodiversity.