Bird diversity and sampling bias in eBird complete checklists from Tver Province, European Russia

I analysed January 2026 eBird Basic Dataset records for Tver Province, European Russia, to assess the value and limitations of complete checklists for documenting regional bird diversity. After restricting approved data to complete Traveling and Stationary checklists lasting 1–300 min and covering 0–5 km, 3,146 checklists remained, spanning 8 August 1979 to 24 January 2026 and containing 188 species. Mean checklist richness was 6.6 species (median 5; maximum 43; SD = 5.4; SE = 0.10). Species accumulation rose rapidly and then slowed. Checklist localities were spatially clustered (global Moran’s I = 0.066, P = 0.006) around accessible urban and recreational sites. The 2020 peak of 1,652 checklists coincided with increased urban sampling. Filtered eBird data provide a reproducible subset of the known regional avifauna, but reporting frequencies reflect observer distribution rather than unbiased province-wide abundance. The identified gaps can guide future citizen-science surveys.

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Publication Details

Journal
Avocetta
Published
2026-11-09
DOI
https://doi.org/10.30456/avo.31426
Primary Topic
Avian ecology and behavior
Type
article
Field-Weighted Citation Impact
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article

Bird diversity and sampling bias in eBird complete checklists from Tver Province, European Russia

Andrei V. Zinoviev
Avocetta
Avian ecology and behavior
article

Bird diversity and sampling bias in eBird complete checklists from Tver Province, European Russia

Andrei V. Zinoviev
article en

Abstract

I analysed January 2026 eBird Basic Dataset records for Tver Province, European Russia, to assess the value and limitations of complete checklists for documenting regional bird diversity. After restricting approved data to complete Traveling and Stationary checklists lasting 1–300 min and covering 0–5 km, 3,146 checklists remained, spanning 8 August 1979 to 24 January 2026 and containing 188 species. Mean checklist richness was 6.6 species (median 5; maximum 43; SD = 5.4; SE = 0.10). Species accumulation rose rapidly and then slowed. Checklist localities were spatially clustered (global Moran’s I = 0.066, P = 0.006) around accessible urban and recreational sites. The 2020 peak of 1,652 checklists coincided with increased urban sampling. Filtered eBird data provide a reproducible subset of the known regional avifauna, but reporting frequencies reflect observer distribution rather than unbiased province-wide abundance. The identified gaps can guide future citizen-science surveys.

AvocettaVol. 50
Tver State University (RU)
Avian ecology and behavior
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