Comparing Avian Species Richness Estimates from Structured and Semi-Structured Citizen- Science Data

Citizen science, including structured and semi-structured forms, has become a powerful tool to collect biodiversity data. However, semi-structured citizen science data have been criticized for higher variability in quality, including less information to adjust for imperfect detection. Species richness estimators may quantify bias in estimates. Here, we test the effectiveness of Chao1 estimator in eBird (semi-structured) by comparing it to averaged species richness in Breeding Bird Survey Taiwan, BBS (structured) and quantifying bias. We then fit a power function to compare bias while controlling for differences in count duration. The Chao1 estimator increased the species richness estimates from eBird data from 56% to 75% of the BBS. When singleton species predominated in eBird data, Chao1 overestimated richness by 7.45 times. Effects of short duration samples and variability in detectability skills of observers can lead to the biased estimates. Using the Chao1 estimator improved estimates of species richness from semi-structured data, but the strong effect of singleton species on bias, especially in short duration counts, should be evaluated in advance to reduce the uncertainty of estimation processes.