Michael DeBacker
Friday, October 17, 2008 - 4:00-4:30
For long-term monitoring of grazing and fire regimes in grasslands, both changes in community composition and species abundance are important. A few, dominant core species along with numerous, low abundance satellite species comprise tallgrass prairies. Sampling designs utilizing multiple scales are particularly useful for collecting information on species composition and abundance in these situations by utilizing large plots to capture patchily distributed species, and smaller plots to provide optimal frequency measures for abundant species. Using statistical models and computer simulations, we investigated the effect of spatial structure in populations on plot size needed to yield optimal frequency data for detecting changes in underlying density. With increasing spatial population structure, smaller plots yielding lower frequency estimates are most powerful for detecting changes in underlying density. Plots of optimal size yield frequencies that vary from 20% – 80%, with plots yielding a mean frequency of 50% usually providing near maximal power. Utilizing field data from Tallgrass Prairie National Preserve, Kansas, we demonstrate how our nested design provides optimal frequency measures for multiple species simultaneously. We also explain procedures for assigning optimal plot size, and tracking changes in optimal plot size over time as an indicator of change in abundance.
Keywords: PLOT SIZE, POPULATION STRUCTURE, FREQUENCY DATA, PLANT DENSITY