Designing online species identification tools for biological recording: the impact on data quality and citizen science learning

Towards better species identification processes between scientists and community participants

Urban gardens are a model system for understanding the intersection between biodiversity conservation and citizen science. They contain high plant diversity that contributes to urban flora. However, this diversity is challenging to document due to site access and complex plant taxonomy with hybrids and cultivars. Community research participation provides a tool to measure plant diversity and distribution by engaging gardeners who are most familiar with their plants to report on their garden's species richness using citizen science. Yet there is little empirical exploration of plant identification consistency between citizen scientists and scientific researchers. This could lead to reporting differences (e.g., missing species, multiple reporting of the same species) due to spatial and temporal effects, different perspectives and knowledge systems, and cultural context. We leverage a scientific survey of garden plants and a questionnaire asking gardeners to report on the species in their gardens to perform an opportunistic comparison of gardener and researcher reported plant diversity in community gardens. The comparison shows that gardeners interpret instructions to report plants quite variably, with some reporting all species (including herbaceous weeds) and crop varieties, while others reporting only their main crop species. Scientist on the other hand seek clarity in terms of species and variety and report all species located in the plot, including the small weed species that are overlooked by some gardeners. Consistency could be improved if researchers are more specific about their reporting expectations when asking community members to participate in data collection. We use this case study to communicate that paired citizen scientist-researcher data collection and dialogue between groups is necessary to improve methods for conducting consistent and collaborative assessments of biological diversity.

Evaluating the ability of citizen scientists to identify bumblebee (Bombus) species

Citizen science is an increasingly popular way of engaging volunteers in the collection of scientific data. Despite this, data quality remains a concern and there is little published evidence about the accuracy of records generated by citizen scientists. Here we compare data generated by two British citizen science projects, Blooms for Bees and BeeWatch, to determine the ability of volunteer recorders to identify bumblebee (Bombus) species. We assessed recorders' identification ability in two ways-as recorder accuracy (the proportion of expert-verified records correctly identified by recorders) and recorder success (the proportion of recorder-submitted identifications confirmed correct by verifiers). Recorder identification ability was low (<50% accuracy; <60% success), despite access to project specific bumblebee identification materials. Identification ability varied significantly depending on bumblebee species, with recorders most able to correctly identify species with distinct appearances. Blooms for Bees recorders (largely recruited from the gardening community) were markedly less able to identify bumblebees than BeeWatch recorders (largely individuals with a more specific interest in bumblebees). Within both projects, recorders demonstrated an improvement in identification ability over time. Here we demonstrate and quantify the essential role of expert verification within citizen science projects, and highlight where resources could be strengthened to improve recorder ability.

Error rates in wildlife image classification

We address the comments made by Thornton et al. (Ecology and Evolution, 2019) in response to our recent article on measuring the agreement among experts in classifying camera images of bobcats and Canada lynx.