The benefits of contributing to the citizen science platform iNaturalist as an identifier

Abstract

As the number of observations submitted to the citizen science platform iNaturalist continues to grow, it is increasingly important that these observations can be identified to the finest taxonomic level, maximizing their value for biodiversity research. Here, we explore the benefits of acting as an identifier on iNaturalist.

Biocontrol Agents Cross Borders: First Detection of the Knapweed Seed Head Weevil, Bangasternus fausti (Reitter) (Coleoptera: Curculionidae), in Canada

“…2019; Martel et al . 2021; Nelson and Moffat 2021; present study), and the contributions of expert iNaturalist identifiers are paramount for detecting species' range extensions (Callaghan et al 2022). However, because of its data format, the iNaturalist database has inherent limitations.…”

Online community photo-sharing in entomology: a large-scale review with suggestions on best practices

“…Although more work is needed to quantify the identification accuracy across taxa, it is likely that large, colorful, and popular insects such as Lepidoptera, which are likely to be identified correctly by the AI and have many users checking the identifications, have lower rates of misidentification than smaller, less colorful groups. There are many benefits for experts who contribute their knowledge to iNaturalist and other platforms by providing identifications (Callaghan et al 2022), and as more expert-identified records are incorporated the AI identification tool should increase in accuracy. In the meantime, however, we strongly suggest that anyone using iNaturalist data, including those downloading large datasets from GBIF, should validate identifications before data analysis or restrict analyses to charismatic taxa that are more likely to be correctly identified.…”

A globally synthesised and flagged bee occurrence dataset and cleaning workflow

“…From foundational systematic 1,2 , life-history 3 , and conservation studies 4,5 , to continental or global macroecological 6,7 or macroevolutionary analyses 8 , occurrence data are used to understand the natural world and form the basis of research, policy, and management. Spatiotemporal occurrence records (e.g., from specimens, images, or observations) are being delivered to, and produced by, community scientists in quantities that were unthinkable just a decade ago, with ever-increasing identification support by professional experts 9 . However, community-generated records can be biased towards larger and more charismatic taxa 10 .…”

“…Online repositories, such as the Global Biodiversity Information Facility (GBIF) and Symbiota Collection of Arthropod Network (SCAN), are invaluable data aggregators and tools in supporting the mobilisation of arthropod occurrence data to help both researchers and general audiences understand biodiversity. Concurrently and complementarily, initiatives like iNaturalist and QuestaGame (Australia) enable community and professional scientists to generate occurrence data for research, science communication, and more 9 . Occurrence data are being generated daily, making new analyses possible for previously data-poor taxa.…”