Scale-specific inference using wavelets

Understanding of spatial pattern and scale has been identified as a key issue in ecology, yet ecology has traditionally lacked necessary tools for making inference about relationships between scale-specific patterns. We introduce wavelet-coefficient regression, in which the dependent and independent...

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Bibliographic Details
Published in:Ecology (Durham) 2005-09, Vol.86 (9), p.2497-2504
Main Authors: Keitt, Timothy H., Urban, Dean L.
Format: Article
Language:English
Subjects:
Animal and plant ecology
Animal, plant and microbial ecology
Autocorrelation
Biological and medical sciences
Coefficients
Covariance
data analysis
Ecology
environmental control
environmental factors
equations
Fourier transformations
Fundamental and applied biological sciences. Psychology
General aspects
General aspects. Techniques
Haar transform
Landscape ecology
pattern and scale
Regression analysis
remote sensing
Sierra Nevada, California, USA
spatial pattern
spatial scale
spatial variation
statistical analysis
Statistical variance
Teledetection and vegetation maps
Topographical elevation
Urban ecology
Vegetation
vegetation analysis
vegetative growth
Wavelet analysis
Wavelet transforms
wavelet-coefficient regression
wavelets
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Summary:Understanding of spatial pattern and scale has been identified as a key issue in ecology, yet ecology has traditionally lacked necessary tools for making inference about relationships between scale-specific patterns. We introduce wavelet-coefficient regression, in which the dependent and independent variables are wavelet transformed prior to analysis, as a means to formalize scale-specific relationships in ecological data. We apply this method to data on vegetation and environmental factors related to water availability from Sequoia-Kings Canyon National Park (California, USA). We find that the wavelet transform and wavelet-coefficient regression efficiently characterize scale-specific pattern in these data. We also find that different environmental factors show up as good predictors of vegetation growth at different scales and that these differences in scale greatly facilitate interpretation of the mechanisms relating water availability to vegetation growth.
ISSN:0012-9658
1939-9170
DOI:10.1890/04-1016