Research shows humans often perceive attractive people as more intelligent, healthier, better leaders and more trustworthy. It turns out this bias extends to the insect world.
A new study by scientists at the USC Dornsife College of Letters, Arts and Sciences reveals that data reported on a popular community science platform is biased. On iNaturalist, butterflies with captivating markings, easily identifiable features or those that are familiar species are reported more frequently than obscure species with no distinct qualities.
Why it matters: Online community science — or participatory science — platforms enable nature-loving non-scientists to contribute data that scientists use to track insect populations.
USC Dornsife’s Laura Melissa Guzman studies butterflies and other pollinators. (Photo: Olga Burymska.)
In her words: “Each year, 3 million people share their observations of insect life on community-science platforms. This data can help us track declines in butterfly populations, resulting from factors like climate change or pesticide use, but only if it’s accurate,” said Laura Melissa Guzman , Gabilan Assistant Professor of Biological Sciences and Quantitative and Computational Biology at USC Dornsife.
Community science platforms: eButterfly and iNaturalist are the two most popular platforms community scientists use to report butterfly data. Their methods for collecting data differ, though.
What they found: The researchers discovered that the iNaturalist method of relying on photos to identify and verify species creates a personal bias toward easily photographed or interesting species.
By the numbers: Overall, 34 species were often underreported and 53 were frequently overreported on iNaturalist compared to eButterfly.
How they did it: In collaboration with North Carolina State researcher Benjamin Goldstein, Guzman and her team compared data shared on iNaturalist and eButterfly from 2000–2021.
Next steps: Guzman says improving participatory science requires training observers to identify species and raise awareness of biases that result in the underreporting of species. She recommends two major improvements to community science apps.
Frontiers in Ecology and the Environment
Computational simulation/modeling
Animals
Logistical and preference bias in participatory science butterfly data
23-Jul-2024