Graduation Year

2018

Graduation Month

May

Document Type

Thesis

Degree Name

Bachelor of Science

School or Department

Wildlife Biology

Major

Wildlife Biology – Terrestrial

Faculty Mentor

Dr. Victoria J. Dreitz

Faculty Mentor Department

Wildlife Biology

Faculty Reader(s)

Dr. Chad Bishop, Dr. Mike Mitchell

Keywords

False positive, detection, survey method, avian survey, dependent double-observer method

Subject Categories

Ornithology | Population Biology

Abstract

Imperfect detection is a known issue when conducting count-based surveys in wildlife studies. False positive detections, observed occurrences of individuals that truly are not present, are often assumed to not occur. This assumption can bias detection rates and create misleading results when calculating population estimates. Survey methods such as the dependent double-observer method are suggested to reduce the occurrence of false positives (Nichols et al. 2000). My study quantified and compared rates of false positives in a single-observer method and a dependent double-observer method using computer-generated auditory surveys. I categorized volunteer observers as either inexperienced or experienced and asked them to identify vocalizations of ten grassland songbird species native to central Montana. False positive rates of experienced observers declined from 0.095 in single-observer surveys to 0.032 in dependent double-observer surveys. False positive rates of inexperienced observers declined from 0.511 in single-observer surveys to 0.391 in dependent double-observer surveys. Further evaluation will provide information on the effectiveness of the dependent double-observer method in providing more precise and less biased population estimates.

Honors College Research Project

Yes

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© Copyright 2018 Kaitlyn M. Strickfaden