NCEAS Project 3080

Analysis of insect population data with structured population models

  • Perry de Valpine

ActivityDatesFurther Information
Postdoctoral Fellow1st September 2000—31st August 2001Participant List  

Abstract
Agricultural pest control relies on understanding complex communities of herbivores and their natural enemies. Field experiments of agricultural communities have produced voluminous multi-species, spatiotemporal population data. However, conventional data analysis uses model frameworks that lack biological structure and thus are only indirectly related to the hypothesized processes of birth, death, predation and movement. This project will use population models to analyze extensive existing data from three agricultural insect communities and one protist microcosm experiment. The questions for each system are 1) Is there evidence for particular movement behaviors? 2) Is there evidence of particular species interactions? The study systems are 1) pea aphids and natural enemies in Wisconsin alfalfa, 2) cotton aphids, other herbivores, and natural enemies in California of cotton, 3) whiteflies and natural enemies in Arizona cotton, and 4) protist predator and prey in laboratory microcosms. For each system I will develop structured population models, fit the models to data under the null and alternative hypotheses, make statistical hypothesis tests, biologically interpret the conclusions, and test the power and biases of the entire procedure. This project will evaluate important ecological hypotheses that have previously been inpenetrable to statistical analysis and develop and test new analysis tools for future research.

TypeProducts of NCEAS Research
Presentations de Valpine, Perry. 2000. Fitting fisheries models with process noise and observation error using nonlinear, non-Gaussian state-space models. Invited Talk from Mote International Fisheries Symposium.
Presentations de Valpine, Perry. 2000. Fitting population models incorporating process noise and observation error. University of Texas, Austin. Austin, TX.
Presentations de Valpine, Perry. 2001. Analysis of experimental population data with population models. Entomological Society of America Annual Meeting.
Presentations de Valpine, Perry. 2002. Analysis of experimental population data with population models: Better inferences from complex data. Ecological Society of America Annual Meeting.
Journal Article de Valpine, Perry. 2002. Review of methods for fitting time-series models with process and observation error and likelihood calculations for nonlinear, non-Gaussian state-space models. Bulletin of Marine Science. Vol: 70. Pages 455-471.
Journal Article de Valpine, Perry. 2003. Better inferences from population-dynamics experiments using Monte Carlo state-space likelihood methods. Ecology. Vol: 84. Pages 3064-3077.
Journal Article de Valpine, Perry. 2004. Monte Carlo state-space likelihoods by weighted posterior kernel density estimation. Journal of the American Statistical Association. Vol: 99(466). Pages 523-536.
Journal Article de Valpine, Perry; Hilborn, Ray. 2005. State-space likelihoods for nonlinear fisheries time-series . Canadian Journal of Fisheries and Aquatic Sciences. Vol: 62. Pages 1937-1952.