How consistent are citizen science data sources, an exploratory study using free automated image recognition apps for woody plant identification

Abstract

Rapid advances in artificial intelligence have led to an upsurge in automated image recognition phone apps. This has increased public involvement in the collection, identification (ID), and analysis of biological data. While this is good for the field of biological data monitoring and biodiversity conservation, it is not clear how consistent IDs are from different apps. The goal of this exploratory work is to verify the accuracy and consistency in plant species identification from two widely used and free apps, i.e., PlantNet and iNaturalist apps. This work was conducted by scanning leaf samples along Bruce Trail in the Niagara Escarpment Biosphere Reserve as well as from the Royal Botanical Gardens arboretum, both in Hamilton, Ontario. Results show over 90% consistency in the identification of woody plants at the level of genus. At the species level, the PlantNet app demonstrated 79% accuracy (i.e., 79 out of 100 species correctly identified), while the iNaturalist app demonstrated 44% accuracy. Enhancing species representation in the database for Southern Ontario might help particularly species in the families Betulaceae, Rosaceae, and Pinaceae. Complementary use of the apps is recommended as a cautionary measure to reduce the likelihood of error in species-level woody plant identification as well as using apps in conjunction with field guide.