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Dynamic design of ecological monitoring networks for non-Gaussian spatio-temporal data

Environmetrics

6382_Wikle.pdf
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Abstract

Many ecological processes exhibit spatial structure that changes over time in a coherent, dynamical fashion. This dynamical component is often ignored in the design of spatial monitoring networks. Furthermore, ecological variables related to processes such as habitat are often non-Gaussian (e.g. Poisson or log-normal). We demonstrate that a simulation-based design approach can be used in settings where the data distribution is from a spatio-temporal exponential family. The key random component in the conditional mean function from this distribution is then a spatio-temporal dynamic process. Given the computational burden of estimating the expected utility of various designs in this setting, we utilize an extended Kalman filter approximation to facilitate implementation. The approach is motivated by, and demonstrated on, the problem of selecting sampling locations to estimate July brood counts in the prairie pothole region of the U.S.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Dynamic design of ecological monitoring networks for non-Gaussian spatio-temporal data
Series title:
Environmetrics
Volume
16
Issue:
5
Year Published:
2005
Language:
English
Contributing office(s):
Patuxent Wildlife Research Center
Description:
507-522
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Environmetrics
First page:
507
Last page:
522
Number of Pages:
16