OCES Departmental Seminar: Boosting biodiversity monitoring using smartphone-driven, rapidly accumulating
community-sourced data

Halting nature loss and mitigating negative impacts on biodiversity necessitates comprehensive biodiversity distribution data. To efficiently collect species observations from the public, we launched the 'Biome' mobile application in Japan. By employing species identification algorithms and gamification elements, the app has gathered >6M observations since its launch in 2019. However, community-sourced data often exhibit spatial and taxonomic biases. Species distribution models (SDMs) enable infer species distribution while accommodating such bias. We modelled the distributions of plants and animals across Japan, and found that SDM accuracy was improved by incorporating our data into traditional survey data. The unique data distributions may explain this improvement: Biome data covers urban-natural gradients uniformly, while traditional data is biased towards natural areas. I will discuss how our data platform could contribute to nature conservation and detecting species distribution changes across terrestrial, freshwater, and marine ecosystems.