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Functional linear models to test for differences in prairie wetland hydraulic gradients

By:
, ,
Edited by:
David A. Swayne, Wanhong Yang, A.A. Voinov, A. Rizzoli, T. Filatova

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Abstract

Functional data analysis provides a framework for analyzing multiple time series measured frequently in time, treating each series as a continuous function of time. Functional linear models are used to test for effects on hydraulic gradient functional responses collected from three types of land use in Northeastern Montana at fourteen locations. Penalized regression-splines are used to estimate the underlying continuous functions based on the discretely recorded (over time) gradient measurements. Permutation methods are used to assess the statistical significance of effects. A method for accommodating missing observations in each time series is described. Hydraulic gradients may be an initial and fundamental ecosystem process that responds to climate change. We suggest other potential uses of these methods for detecting evidence of climate change.

Additional Publication Details

Publication type:
Conference Paper
Publication Subtype:
Conference Paper
Title:
Functional linear models to test for differences in prairie wetland hydraulic gradients
Year Published:
2010
Language:
English
Publisher:
International Environmental Modelling and Software Society
Publisher location:
Manno, Switzerland
Contributing office(s):
Northern Rocky Mountain Science Center
Description:
8 p.
Larger Work Type:
Book
Larger Work Subtype:
Conference publication