Trevor Hefley, doctoral student, will defend his thesis, "New Statistical Methods for Analysis of Historical Data from Wildlife Populations," at 9 a.m., March 21 in 901 Hardin Hall.
Abstract:
Wildlife biologists, many times with the help of ordinary citizens, have developed and maintained long-term data sets while monitoring the status of wildlife populations. These data sets can range from a collection of citizen reported sightings of a rare species to data collected by biologists using standardized methods. The commonality is that these data sets span a temporal and spatial scale that is beyond the scope of most scientic studies. Statistical methods are the main data analysis technique used for
developing quantitative predictions in the life sciences, but these methods are poorly developed and rarely applied to long-term data sets.
This underdevelopment of statistical methods and applications was the motivation for my research. I will present new statistical methods for time series analysis and spatial point processes. I apply these new methods to three dierent historical data sets from a population of bobwhite quail (1965-2011) and whooping cranes (1943-2012). My main results include detection of an extinction threshold and a predictive species distribution model that can be used to inform management actions.