Persistent Link:
http://hdl.handle.net/10150/261260
Title:
Response Functions Revisited
Author:
Blasing, T. J.; Solomon, A. M.; Duvick, D. N.
Affiliation:
Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 57851
Issue Date:
1984
Rights:
Copyright © Tree-Ring Society. All rights reserved.
Collection Information:
This item is part of the Tree-Ring Research (formerly Tree-Ring Bulletin) archive. It was digitized from a physical copy provided by the Laboratory of Tree-Ring research at The University of Arizona. For more information about this peer-reviewed scholarly journal, please email the Editor of Tree-Ring Research at editor@treeringsociety.org.
Publisher:
Tree-Ring Society
Journal:
Tree-Ring Bulletin
Citation:
Blasing, T.J., Solomon, A.M., Duvick, D.N. 1984. Response functions revisited. Tree-Ring Bulletin 44:1-15.
Abstract:
The use of orthogonalized climatic variables in regression to specify treegrowth/climate relationships, commonly known as response function analysis, involves several a priori decisions and a posteriori interpretations, any of which maybe open to question. Decisions about the number of climatic variables to include, confidence limits, number of eigenvectors to allow as candidate predictors in regression, etc., can affect the response function in unpredictable ways and lead to possible errors in interpretation. To demonstrate the nature of these effects, we compared response functions for particular chronologies with the correlation function, which is simply the series of correlation coefficients between a tree-ring chronology and each of several sequential monthly climatic variables. The results indicate that response functions including high-order eigenvectors should be interpreted cautiously, and we recommend using the correlation function as an interpretive guide. Prior tree-growth variables in regression can mask climatic effects, and the correlation function can also be useful in detecting this masking. Statistical significance is more often attained in response functions than in correlation functions, possibly due to differences in the statistical testing procedures, to the statistical efficiency of eigenvectors in spending degrees of freedom, or to the filtering effects on the climatic data that result from eliminating high-order eigenvectors (noise) from the response function. These filtering effects plus the orthogonalization make response function analysis an efficient method for specifying tree-growth/climate relationships. The examples and guidelines presented here should enhance the usefulness of the method.
Keywords:
Dendrochronology; Tree Rings; Dendroclimatology; Statistical Analysis
ISSN:
0041-2198
Additional Links:
http://www.treeringsociety.org

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleResponse Functions Revisiteden_US
dc.contributor.authorBlasing, T. J.en_US
dc.contributor.authorSolomon, A. M.en_US
dc.contributor.authorDuvick, D. N.en_US
dc.contributor.departmentEnvironmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 57851en_US
dc.date.issued1984-
dc.rightsCopyright © Tree-Ring Society. All rights reserved.en_US
dc.description.collectioninformationThis item is part of the Tree-Ring Research (formerly Tree-Ring Bulletin) archive. It was digitized from a physical copy provided by the Laboratory of Tree-Ring research at The University of Arizona. For more information about this peer-reviewed scholarly journal, please email the Editor of Tree-Ring Research at editor@treeringsociety.org.en_US
dc.publisherTree-Ring Societyen_US
dc.identifier.journalTree-Ring Bulletinen_US
dc.identifier.citationBlasing, T.J., Solomon, A.M., Duvick, D.N. 1984. Response functions revisited. Tree-Ring Bulletin 44:1-15.en_US
dc.description.abstractThe use of orthogonalized climatic variables in regression to specify treegrowth/climate relationships, commonly known as response function analysis, involves several a priori decisions and a posteriori interpretations, any of which maybe open to question. Decisions about the number of climatic variables to include, confidence limits, number of eigenvectors to allow as candidate predictors in regression, etc., can affect the response function in unpredictable ways and lead to possible errors in interpretation. To demonstrate the nature of these effects, we compared response functions for particular chronologies with the correlation function, which is simply the series of correlation coefficients between a tree-ring chronology and each of several sequential monthly climatic variables. The results indicate that response functions including high-order eigenvectors should be interpreted cautiously, and we recommend using the correlation function as an interpretive guide. Prior tree-growth variables in regression can mask climatic effects, and the correlation function can also be useful in detecting this masking. Statistical significance is more often attained in response functions than in correlation functions, possibly due to differences in the statistical testing procedures, to the statistical efficiency of eigenvectors in spending degrees of freedom, or to the filtering effects on the climatic data that result from eliminating high-order eigenvectors (noise) from the response function. These filtering effects plus the orthogonalization make response function analysis an efficient method for specifying tree-growth/climate relationships. The examples and guidelines presented here should enhance the usefulness of the method.en_US
dc.subjectDendrochronologyen_US
dc.subjectTree Ringsen_US
dc.subjectDendroclimatologyen_US
dc.subjectStatistical Analysisen_US
dc.identifier.citationBlasing, T.J., Solomon, A.M., Duvick, D.N. 1984. Response functions revisited. Tree-Ring Bulletin 44:1-15.en_US
dc.identifier.issn0041-2198-
dc.identifier.urihttp://hdl.handle.net/10150/261260-
dc.identifier.journalTree-Ring Bulletinen_US
dc.typeArticleen_US
dc.relation.urlhttp://www.treeringsociety.orgen_US
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