Gordon Reese GDPE PhD Dissertation Defense
Thursday, April 26, 2012, 02:00 PM
Wagar Building, Room 130

Species richness, the number of species in a defined area, is the most frequently used biodiversity measure. Despite its intuitive appeal and conceptual simplicity, species richness is often not easily quantified, even in well-surveyed areas, because of sampling limitations such as survey effort and species detection probability. This has led to the development of numerous species richness estimators, though indications are that their performance is dependent on assemblage and survey factors. My objective, therefore, was to evaluate the performance of both established and new nonparametric species richness estimators, including variance estimators, across a wide range of conditions. Using mostly simulated data, I found that several estimators, including two relatively new estimators based on the similarity of repeated subsets of surveys, generally performed with less bias and more accuracy than the most commonly used estimators. Results also showed that analytically derived variance estimators usually achieve better confidence interval coverage levels than do resampling procedures, but seldom reach the nominal 95% confidence level.

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Event Contact: Jeri Morgan can be reached at (970) 491-4373

Sponsored by the Graduate Degree Program in Ecology.