ArticleEcology and evolution2026
Effective Data Collection Approaches for Citizen Science in Biodiversity Research.
Article in Ecology and evolution, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
7 authors.
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Abstract
Biodiversity underpins the stability of ecosystems and human well-being. However, it is rapidly declining globally, necessitating robust and scalable monitoring solutions. Citizen science has emerged as a powerful complement to traditional biodiversity research, enabling the collection of widespread data and fostering public engagement, particularly through digital platforms such as iNaturalist and eBird. This study investigates global patterns in citizen science contributions to biodiversity monitoring, exploring the influence of socioeconomic factors, national biodiversity value, and platform-specific contributions on data generation. Key strategies for optimizing public participation, enhancing data quality and coverage are identified through statistical analysis and three in-depth case studies from Finland and Ukraine. Our findings show that citizen science platforms now provide a significant portion of biodiversity records in GBIF. Citizen science contributions to global biodiversity data are shaped more by a country's ecological uniqueness and biodiversity value than by its socioeconomic development, as effectiveness depends not just on user numbers or observations but also on biodiversity significance, platform origin, and user engagement. Combining digital platforms with targeted outreach, through social media, personal communication, and expert validation, emerges as a promising strategy to enhance data reliability and participant engagement. This mixed-methods approach proves especially effective in contexts with varying levels of digital access, biodiversity richness, and species monitoring needs.
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