Factor Analytic Models of Bioclimate for Canadian Forest Regions

Relational models of bioclimate were formulated for 90 Canadian forest sections defined by J. S. Rowe in 1972. Models were based on component solutions for correlations among climatic attributes believed to be important in tree growth and reproduction. In addition, computer experiments were attempte...

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Published in:Canadian Journal of Forest Research
Main Authors: Miller, Wayne S., Auclair, Allan N.
Format: Article in Journal/Newspaper
Language:English
Published: Canadian Science Publishing 1974
Subjects:
Online Access:http://dx.doi.org/10.1139/x74-078
http://www.nrcresearchpress.com/doi/pdf/10.1139/x74-078
id crcansciencepubl:10.1139/x74-078
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spelling crcansciencepubl:10.1139/x74-078 2023-12-17T10:26:18+01:00 Factor Analytic Models of Bioclimate for Canadian Forest Regions Miller, Wayne S. Auclair, Allan N. 1974 http://dx.doi.org/10.1139/x74-078 http://www.nrcresearchpress.com/doi/pdf/10.1139/x74-078 en eng Canadian Science Publishing http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining Canadian Journal of Forest Research volume 4, issue 4, page 536-548 ISSN 0045-5067 1208-6037 Ecology Forestry Global and Planetary Change journal-article 1974 crcansciencepubl https://doi.org/10.1139/x74-078 2023-11-19T13:38:30Z Relational models of bioclimate were formulated for 90 Canadian forest sections defined by J. S. Rowe in 1972. Models were based on component solutions for correlations among climatic attributes believed to be important in tree growth and reproduction. In addition, computer experiments were attempted to find remedial solutions to problems of model resolution and R/Q-mode equivalence.An attribute model based on physiographic and climatic variables was characterized by mean annual temperature, mean annual precipitation, and July average daily maximum temperature. These factors accounted for 57, 18, and 12% of the total variation on components I, II, and III, respectively.A station model based on weighted factor scores of climatic attributes alone gave a consistent and realistic separation of major forest regions. The first component distinguished Boreal forest from Pacific Coastal, Acadian, and to a lesser degree Great Lake – St. Lawrence forest regions. The second component differentiated Columbian, Grassland, and Montane regions from the Boreal maritime and Pacific Coastal forests. In addition to this generalized model, analysis of a qualitative dataset derived to help overcome problems of nonlinearity in the original data was able to identify the mean summer position of the arctic polar front and a regional low pressure locus over central Alberta.Cluster analysis of forest stations was employed to illustrate the utility of factor models. Limitations and forest applications of our results are discussed. Article in Journal/Newspaper Arctic Canadian Science Publishing (via Crossref) Arctic Pacific Rowe ENVELOPE(-60.904,-60.904,-62.592,-62.592) Canadian Journal of Forest Research 4 4 536 548
institution Open Polar
collection Canadian Science Publishing (via Crossref)
op_collection_id crcansciencepubl
language English
topic Ecology
Forestry
Global and Planetary Change
spellingShingle Ecology
Forestry
Global and Planetary Change
Miller, Wayne S.
Auclair, Allan N.
Factor Analytic Models of Bioclimate for Canadian Forest Regions
topic_facet Ecology
Forestry
Global and Planetary Change
description Relational models of bioclimate were formulated for 90 Canadian forest sections defined by J. S. Rowe in 1972. Models were based on component solutions for correlations among climatic attributes believed to be important in tree growth and reproduction. In addition, computer experiments were attempted to find remedial solutions to problems of model resolution and R/Q-mode equivalence.An attribute model based on physiographic and climatic variables was characterized by mean annual temperature, mean annual precipitation, and July average daily maximum temperature. These factors accounted for 57, 18, and 12% of the total variation on components I, II, and III, respectively.A station model based on weighted factor scores of climatic attributes alone gave a consistent and realistic separation of major forest regions. The first component distinguished Boreal forest from Pacific Coastal, Acadian, and to a lesser degree Great Lake – St. Lawrence forest regions. The second component differentiated Columbian, Grassland, and Montane regions from the Boreal maritime and Pacific Coastal forests. In addition to this generalized model, analysis of a qualitative dataset derived to help overcome problems of nonlinearity in the original data was able to identify the mean summer position of the arctic polar front and a regional low pressure locus over central Alberta.Cluster analysis of forest stations was employed to illustrate the utility of factor models. Limitations and forest applications of our results are discussed.
format Article in Journal/Newspaper
author Miller, Wayne S.
Auclair, Allan N.
author_facet Miller, Wayne S.
Auclair, Allan N.
author_sort Miller, Wayne S.
title Factor Analytic Models of Bioclimate for Canadian Forest Regions
title_short Factor Analytic Models of Bioclimate for Canadian Forest Regions
title_full Factor Analytic Models of Bioclimate for Canadian Forest Regions
title_fullStr Factor Analytic Models of Bioclimate for Canadian Forest Regions
title_full_unstemmed Factor Analytic Models of Bioclimate for Canadian Forest Regions
title_sort factor analytic models of bioclimate for canadian forest regions
publisher Canadian Science Publishing
publishDate 1974
url http://dx.doi.org/10.1139/x74-078
http://www.nrcresearchpress.com/doi/pdf/10.1139/x74-078
long_lat ENVELOPE(-60.904,-60.904,-62.592,-62.592)
geographic Arctic
Pacific
Rowe
geographic_facet Arctic
Pacific
Rowe
genre Arctic
genre_facet Arctic
op_source Canadian Journal of Forest Research
volume 4, issue 4, page 536-548
ISSN 0045-5067 1208-6037
op_rights http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining
op_doi https://doi.org/10.1139/x74-078
container_title Canadian Journal of Forest Research
container_volume 4
container_issue 4
container_start_page 536
op_container_end_page 548
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