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Comparing avian species richness estimates from structured and semi-structured citizen science data
Fang-Yu Shen1,2, Tzung-Su Ding1,3, Jo-Szu Tsai4
1School of Forestry and Resource Conservation, National Taiwan University, Taipei City, Taiwan.
Scientific Reports
|January 21, 2023
Summary
Citizen science data quality varies. The Chao1 estimator improves species richness estimates for semi-structured (eBird) and structured (BBS) data, but short counts and singletons introduce bias.
Area of Science:
- Ecology
- Biodiversity Science
- Computational Biology
Background:
- Citizen science is crucial for biodiversity data collection, with structured and semi-structured approaches yielding varying data quality.
- Semi-structured data, like eBird, face challenges with imperfect detection and uneven sampling durations, potentially biasing species richness estimates.
- Species richness estimators are vital for quantifying and correcting such biases.
Purpose of the Study:
- To evaluate the effectiveness of the Chao1 estimator in correcting species richness estimates from semi-structured eBird data.
- To compare Chao1-adjusted eBird estimates with structured Breeding Bird Survey Taiwan (BBS) data, accounting for sampling duration and observer variability.
- To identify and quantify biases in citizen science biodiversity data.
Main Methods:
- Applied the Chao1 estimator to eBird (semi-structured) data and compared results with averaged species richness from BBS (structured) data.
- Utilized a power function to analyze and control for biases related to differences in count duration between datasets.
- Quantified the impact of singleton species and short sampling durations on species richness estimation accuracy.
Main Results:
- The Chao1 estimator increased eBird species richness estimates by 56–69% compared to average observed BBS richness and 47–59% compared to average estimated BBS richness.
- Incomplete, short-duration samples and observer variability in detection skills were identified as significant sources of bias in species richness estimates.
- The Chao1 estimator demonstrated improved species richness estimates for both semi-structured and structured citizen science data.
Conclusions:
- The Chao1 estimator is effective in enhancing species richness estimates from citizen science data, particularly for semi-structured datasets like eBird.
- The influence of singleton species, especially in short-duration counts, requires careful pre-evaluation to mitigate estimation uncertainty.
- Addressing data quality issues, such as imperfect detection and uneven sampling, is crucial for reliable biodiversity assessments using citizen science data.
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