Literature DB >> 15883870

Potential of multivariate quantitative methods for delineation and visualization of ecoregions.

William W Hargrove1, Forrest M Hoffman.   

Abstract

Multivariate clustering based on fine spatial resolution maps of elevation, temperature, precipitation, soil characteristics, and solar inputs has been used at several specified levels of division to produce a spectrum of quantitative ecoregion maps for the conterminous United States. The coarse ecoregion divisions accurately capture intuitively-understood regional environmental differences, whereas the finer divisions highlight local condition gradients, ecotones, and clines. Such statistically generated ecoregions can be produced based on user-selected continuous variables, allowing customized regions to be delineated for any specific problem. By creating an objective ecoregion classification, the ecoregion concept is removed from the limitations of human subjectivity, making possible a new array of ecologically useful derivative products. A red-green-blue visualization based on principal components analysis of ecoregion centroids indicates with color the relative combination of environmental conditions found within each ecoregion. Multiple geographic areas can be classified into a single common set of quantitative ecoregions to provide a basis for comparison, or maps of a single area through time can be classified to portray climatic or environmental changes geographically in terms of current conditions. Quantified representativeness can characterize borders between ecoregions as gradual, sharp, or of changing character along their length. Similarity of any ecoregion to all other ecoregions can be quantified and displayed as a "representativeness" map. The representativeness of an existing spatial array of sample locations or study sites can be mapped relative to a set of quantitative ecoregions, suggesting locations for additional samples or sites. In addition, the shape of Hutchinsonian niches in environment space can be defined if a multivariate range map of species occurrence is available.

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Year:  2004        PMID: 15883870     DOI: 10.1007/s00267-003-1084-0

Source DB:  PubMed          Journal:  Environ Manage        ISSN: 0364-152X            Impact factor:   3.266


  19 in total

1.  Effect of classification procedure on the performance of numerically defined ecological regions.

Authors:  Ton Snelder; Anthony Lehmann; Nicolas Lamouroux; John Leathwick; Karin Allenbach
Journal:  Environ Manage       Date:  2010-03-19       Impact factor: 3.266

2.  Regionalization of landscape pattern indices using multivariate cluster analysis.

Authors:  Jed Long; Trisalyn Nelson; Michael Wulder
Journal:  Environ Manage       Date:  2010-06-06       Impact factor: 3.266

3.  Synergistic techniques for better understanding and classifying the environmental structure of landscapes.

Authors:  Brett A Bryan
Journal:  Environ Manage       Date:  2006-01       Impact factor: 3.266

4.  Development of an ecologic marine classification in the new zealand region.

Authors:  Ton H Snelder; John R Leathwick; Katie L Dey; Ashley A Rowden; Mark A Weatherhead; Graham D Fenwick; Malcolm P Francis; Richard M Gorman; Janet M Grieve; Mark G Hadfield; Judi E Hewitt; Ken M Richardson; Michael J Uddstrom; John R Zeldis
Journal:  Environ Manage       Date:  2007-01       Impact factor: 3.266

5.  Correlation of Borrelia burgdorferi sensu lato prevalence in questing Ixodes ricinus ticks with specific abiotic traits in the western palearctic.

Authors:  Agustín Estrada-Peña; Carmelo Ortega; Nely Sánchez; Lorenzo Desimone; Bertrand Sudre; Jonathan E Suk; Jan C Semenza
Journal:  Appl Environ Microbiol       Date:  2011-04-15       Impact factor: 4.792

6.  Division scheme for environmental management regionalization in China.

Authors:  Baorong Huang; Ting Fan; Yingming Li; Yi Wang
Journal:  Environ Manage       Date:  2013-06-18       Impact factor: 3.266

7.  Bioclimatic and physical characterization of the world's islands.

Authors:  Patrick Weigelt; Walter Jetz; Holger Kreft
Journal:  Proc Natl Acad Sci U S A       Date:  2013-09-03       Impact factor: 11.205

8.  Strong influence of variable treatment on the performance of numerically defined ecological regions.

Authors:  Ton Snelder; Anthony Lehmann; Nicolas Lamouroux; John Leathwick; Karin Allenbach
Journal:  Environ Manage       Date:  2009-08-18       Impact factor: 3.266

Review 9.  Hutchinson's duality: the once and future niche.

Authors:  Robert K Colwell; Thiago F Rangel
Journal:  Proc Natl Acad Sci U S A       Date:  2009-09-18       Impact factor: 11.205

10.  Trans-generational but not early life exposure to stressors influences offspring morphology and survival.

Authors:  Dustin A S Owen; Travis R Robbins; Tracy Langkilde
Journal:  Oecologia       Date:  2017-11-30       Impact factor: 3.225

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