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    Author(s): Kathryn L. Purcell; Sylvia R. Mori; Mary K. Chase
    Date: 2005
    Source: The Condor 107:305–320
    Publication Series: Scientific Journal (JRNL)
    PDF: Download Publication  (340 KB)


    We used data from two oak-woodland sites in California to develop guidelines for the design of bird monitoring programs using point counts. We used power analysis to determine sample size adequacy when varying the number of visits, count stations, and years for examining trends in abundance. We assumed an overdispersed Poisson distribution for count data, with overdispersion attributed to observer variability, and used Poisson regression for analysis of population trends. Overdispersion had a large, negative effect on power. The number of sampling years also had an especially large effect on power. In all cases, 10 years of sampling were insufficient to detect a decline in abundance of 30% over 10 years. Increasing the sampling period to 20 years provided adequate power for 56% of breeding species at one site. The number of count stations needed for detecting trends for a given species depended primarily on observer variability. If observer variability was high, increasing the number of years and visits was a better approach than increasing the number of stations. Increasing the number of stations was most beneficial for species with low abundance or low observer variability. When the number of stations is limited by the size of the area, we recommend multiple visits to stations. For most species, multiple visits per year (six or more) for 15–20 years were needed to detect a 30% decreasing trend in 10 years with adequate power. We suggest potentially useful focal species for monitoring, such as keystone species like the Acorn Woodpecker (Melanerpes formicivorus)

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    Purcell, Kathryn L.; Mori, Sylvia R.; Chase, Mary K. 2005. Design considerations for examining trends in avian abundance using point counts: examples from oak woodlands. The Condor 107:305–320


    avian point counts, count data, focal species, monitoring, population trends, power, sample size.

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