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Marine Turtle Newsletter 93:14, © 2001
Population Dynamics Workshop - Analysis of Nesting Beach Data for
Application to Population Models
Selina Heppell1, Bill Kendall2 & Rhema Kerr Bjorkland3
1Oregon State University (E-mail:selina.heppell@orst.edu)
2US Geological Service, Patuxent Wildlife Research Center (E-mail:william_kendall@usgs.gov)
3WIDECAST (E-mail:rhemaker@hotmail.com)
We conducted a workshop on analysis of census data and tagging data from nesting beaches at the 21st Annual Symposium on Sea Turtle Biology and Conservation, Philadelphia, 2001. The goal of our workshop was to introduce participants to a range of data analysis techniques, explain how the data can be used in population models, and discuss the potential problems that can arise from incomplete data and sampling error. Nesting beaches provide the first data needed for demographic models: reproduction parameters, remigration interval, recruitment to the nesting population, and survival rates of adult females. Trends in nest numbers or female counts can give an indication of whether the adult female segment of the population is increasing or decreasing. However, the high variability of nest counts makes trend estimation difficult - often, the data are too variable to detect a trend with statistical significance, and sampling error can result in incorrect assessments. A program by Tim Gerrodette of the National Marine Fisheries Service is available to determine how many years of surveys are required to detect a trend, given a measured amount of variance in the data <http://mmdshare.ucsd.edu/trends.html>. With tagging programs, researchers can estimate nests per female, remigration interval, adult female survival, and population trends that are much more accurate than nest counts alone. Dr. Kendall discussed some of the problems with nest counts and the importance of mark-recapture studies to improve population assessment. He presented methods and a computer program to estimate survival and remigration rates, and Dr. Bjorkland showed how the program was used to analyze tagging data for hawksbill turtles in Antigua. The program is still under development, but may become “user friendly” for sea turtle researchers soon.