Prediction is a persistent challenge in ecology, particularly in connection with the frequency and quality of available data. We are interested in the statistical and dynamic tools that efficiently use available data. Similar methods and concerns were also addressed as part of a workshop on transient dynamics.
The key contribution of this work is in determining whether partial observations of populations, which are less burdensome to collect, can inform mathematical models over long time periods. Below are some important components of the research.
Ongoing work on this project includes comparing bayesian approximations for model states with dynamic observers.
Virtual Office (drop ins welcome) - Schedule a Meeting (no need to ask) - amanda.laubmeier@ttu.edu - Math 117B (by appt. only)
