G. L. Sprandel

Statistical Power in Analyses of Population Trend Data

Non-game Wildlife Outstanding Technical Paper

We developed a Monte Carlo simulation approach to examine statistical power in analysis of population trend data. Our stepwise approach was to perform a regression analysis to test the null hypothesis that the slope of the time series regression line was equal to 0 (i.e., Ho:b = 0 for population count data collected over i years), to use Monte Carlo simulations to calculate the statistical power of the test of H0:b = 0 when Ho was not rejected, and to estimate sample size requirements within and across years to detect a population trend at a specified power, Type I error, and coefficient...


Inter-observer Variability in Wading Bird Survey Data

Evaluating the contribution of wading bird populations to avian biodiversity and wildlife managers' ability to maintain viable wading bird populations requires accurate information on population levels and trends. Wading bird population surveys often use multiple observers in single or over multiple years, but inter-observer variability is seldom evaluated. We conducted a study to test for significant inter-observer variability among experienced biologists and to determine the impact of variability on biologists' ability to accurately survey colonies and to monitor statewide trends in...