PARENT SESSION
Oral Session #83: Insect Population and Community Ecology.
Presiding: C. Rodriguez-Saona
Thursday, August 8. 9:00 AM to 11:30 AM. Palo Verde Room, Radisson.

Analysis of experimental population data with population models: better inferences from complex data.

de Valpine, Perry^*,1, ¹ National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, CA

ABSTRACT- Population dynamics experiments routinely produce short, replicated time-series of stage-structured population counts under different treatments. The most common method for analyzing such data, analysis of variance (ANOVA), does not model biological processes such as growth, mortality, reproduction, and predation. Thus ANOVA does not incorporate all of the information in the data and has only limited utility for biologically meaningful inference. An alternative approach is to use a classical hypothesis test in which null and alternative hypotheses are formulated with population models. However, a major difficulty is that relevant models are complex and need to include both variability in biological processes (process noise) as well as inaccuracy in observations. I introduce computational methods for maximum-likelihood estimation and hypothesis testing with stage-structured models that incorporate process noise and observation error. The methods use a state-space framework and Monte Carlo integration algorithms to obtain approximate likelihood ratio tests. I present two simulated comparisons of population models to ANOVA models for inference from experimental population data. For an experiment of effects of plant conditions on herbivore population growth, the new method has much higher statistical power than ANOVA (100% vs. ⩽ 40%) and provides biologically meaningful estimates of demographic rates. For a predator-prey experiment, the new method allows inference about behavioral changes in prey demography in the presence of a predator that would be difficult to formulate as an ANOVA test. Studies of herbivore-plant interactions, predator-prey dynamics, intraguild predation, biological control, and numerous other population-level questions could potentially benefit from analysis of population data with population models.

KEY WORDS: Population Dynamics, Predator-Prey, Plant-Herbivore, Biological Control