Understanding Covariance Function Dynamics for Improving Insect Spatial and Temporal ManagementEPA Grant Number: U915534
Title: Understanding Covariance Function Dynamics for Improving Insect Spatial and Temporal Management
Investigators: Tobin, Patrick C.
Institution: Pennsylvania State University
EPA Project Officer: Michaud, Jayne
Project Period: August 1, 1999 through July 1, 2002
Project Amount: $102,000
RFA: STAR Graduate Fellowships (1999) RFA Text | Recipients Lists
Research Category: Academic Fellowships , Biology/Life Sciences , Fellowship - Entomology
The objective of this research project is to study the dynamics of covariance functions in insect populations. The spatial and temporal dynamics of insect herbivores are of considerable interest in ecology, and the implications of these dynamics in competition, dispersal, predator-prey relationships, sampling, and the implementation of pest management strategies are profound. Recently, problems in population biology have received considerable geostatistical treatment. Geostatistics are useful in estimating spatial covariance functions, which can be modeled and used in interpolation algorithms such as kriging. Insect populations, however, are extremely dynamic and change over varying temporal and spatial scales. Therefore, the expectation of a covariance function for a certain herbivore population and field is constantly subject to change, making its estimation rather myopic.
This project is investigating theoretical dynamics of covariance functions by simulating, using Markov random fields, the spatial and temporal patterns of insect herbivores and their natural enemies. I will estimate time-specific, and auto- and cross-covariance functions using geostatistics. Lastly, I will compare theoretical expectations with empirically derived functions obtained from analyses of field-collected data.