• An Evaluation of Random and Systematic Plot Placement for Estimating Frequency

      Whysong, G. L.; Miller, W. H. (Society for Range Management, 1987-09-01)
      A computer simulation study was conducted to evaluate the effects of pattern on the precision of frequency estimates as determined from random and systematic plot placement. Computer graphics were used to generate artificial population maps containing 40 or 80 clumps of differing spatial intensity with known frequencies of 20, 35, and 50%. The maps were repeatedly sampled both randomly and systematically using a 200-plot sample size to obtain frequency estimates. Three systematic plot spacings (4, 8, and 12) along randomly located transects were evaluated. Analysis indicated that frequency means from systematic plot placement were significantly affected by clumping, pattern intensity, and plot spacing. Random sampling resulted in frequency means that were unaffected by clumping or pattern intensity, and more consistently estimated population frequencies. An evaluation of probabilities of occurrence of Type I errors when statistically comparing frequency estimates from systematic plot placement indicated higher Type I error rates as compared to random sampling.
    • Frequency Sampling and Type II Errors

      Whysong, G. L.; Brady, W. W. (Society for Range Management, 1987-09-01)
      Probabilities of detecting frequency differences based on data obtained by random sampling were determined by computer simulation. Artificial, monotypic populations of known frequency were generated and sampled. Sample sizes of 100, 200, 500, and 1,000 plots were used to compare baseline populations of 20, 50, and 80% frequency to populations having progressively larger or smaller frequencies. Probabilities of detecting a difference in frequency from baseline populations were empirically estimated from 10,000 comparisons using a test of proportions (P<0.05). Results indicated that the power of the test was substantially reduced at lower sample sizes. Equating the probability of Type I and Type II errors at 0.05 resulted in sample sizes of approximately 500 plots being needed to statistically distinguish between differences of plus or minus 10% frequency.