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Observer aging and long-term avian survey data quality.

Robert G Farmer1, Marty L Leonard1, Joanna E Mills Flemming2

  • 1Department of Biology, Dalhousie University 1355 Oxford Street, Halifax, Nova Scotia, B3H 4R2, Canada.

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|November 1, 2014
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Observer aging can introduce errors in long-term wildlife monitoring. Older observers detect fewer birds, potentially biasing population trend estimates, especially for high-frequency vocalizations.

Keywords:
Avian ecologycitizen scienceobserver errorpoint countspopulation trend estimation

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Area of Science:

  • Ornithology
  • Wildlife Ecology
  • Conservation Biology
  • Bioacoustics

Background:

  • Long-term wildlife monitoring relies on consistent data collection, often by the same observers over extended periods.
  • Observer aging is a potential, underappreciated source of systematic error in wildlife survey data.
  • Such errors can lead to biased management decisions and inaccurate population trend assessments.

Purpose of the Study:

  • To investigate age-related observer effects on avian detection rates in long-term bird surveys.
  • To assess the impact of observer aging on current avian population trend estimates.
  • To explore the relationship between vocalization frequency, hearing loss, and detection declines.

Main Methods:

  • Analysis of time-series data from two independent bird surveys: Atlas of the Breeding Birds of Ontario (OBBA) and North American Breeding Bird Survey (BBS).
  • Comparison of detection rates between younger and older observers for various avian species and vocalization groups.
  • Examination of detection declines in relation to vocalization frequency and observer age.

Main Results:

  • Older observers showed significantly fewer detections for 13 of 43 OBBA species.
  • Detection declines with observer age were observed in 4 of 6 vocalization groups across 59 of 64 BBS species.
  • Detection declines increased with call frequency for high-pitched species, but also occurred at other frequencies, indicating age-related effects beyond hearing loss.

Conclusions:

  • Observer aging can introduce significant bias into long-term avian monitoring data, affecting presence and abundance estimates.
  • Population trend estimates for some species may be negatively biased due to observer aging, particularly those with high-frequency vocalizations.
  • Survey designers and data modelers should consider and account for observer age effects to improve monitoring accuracy.