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1 November 2007 POWER TO DETECT TREND IN SHORT-TERM TIME SERIES OF BIRD ABUNDANCE
WAYNE E. THOGMARTIN, BRIAN R. GRAY, MAUREEN GALLAGHER, NEAL YOUNG, JASON J. ROHWEDER, MELINDA G. KNUTSON
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Abstract

Avian point counts for population monitoring are often collected over a short timespan (e.g., 3–5 years). We examined whether power was adequate (power ≥0.80) in short-duration studies to warrant the calculation of trend estimates. We modeled power to detect trends in abundance indices of eight bird species occurring across three floodplain habitats (wet prairie, early successional forest, and mature forest) as a function of trend magnitude, sample size, and species-specific sampling and among-year variance components. Point counts (5 min) were collected from 365 locations distributed among 10 study sites along the lower Missouri River; counts were collected over the period 2002 to 2004. For all study species, power appeared adequate to detect trends in studies of short duration (three years) at a single site when exponential declines were relatively large in magnitude (more than −5% year−1) and the sample of point counts per year was ≥30. Efforts to monitor avian trends with point counts in small managed lands (i.e., refuges and parks) should recognize this sample size restriction by including point counts from offsite locations as a means of obtaining sufficient numbers of samples per strata. Trends of less than −5% year−1 are not likely to be consistently detected for most species over the short term, but short-term monitoring may still be useful as the basis for comparisons with future surveys.

WAYNE E. THOGMARTIN, BRIAN R. GRAY, MAUREEN GALLAGHER, NEAL YOUNG, JASON J. ROHWEDER, and MELINDA G. KNUTSON "POWER TO DETECT TREND IN SHORT-TERM TIME SERIES OF BIRD ABUNDANCE," The Condor 109(4), 943-948, (1 November 2007). https://doi.org/10.1650/0010-5422(2007)109[943:PTDTIS]2.0.CO;2
Received: 11 January 2007; Accepted: 1 August 2007; Published: 1 November 2007
KEYWORDS
floodplain habitat
Missouri River
point counts
Poisson regression
power
trend estimation
underdispersion
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