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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.
| 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 |
| Larger Work Title | 2010 International Congress on Environmental Modelling and Software; Modelling for Environment's Sake, Fifth Biennial Meeting, Ottawa, Canada |
| Google Analytic Metrics | Metrics page |