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Community Ecology

, Volume 4, Issue 1, pp 89–100 | Cite as

The use of matrix models to detect natural and pollution-induced forest gradients

  • B. C. Tucker
  • M. AnandEmail author
Article

Abstract

We sought to compare the efficacy of the stationary Markov model and conventional ordination techniques in describing compositional and structural changes in forest communities along natural and manmade spatial gradients at two scales, local and regional. Vegetation abundance and structure data are from six sites spanning a spatial gradient in the Great Lakes-St. Lawrence forests near Sudbury, Ontario, Canada. Ordination did not detect slope-related local gradients despite the general trend that, as distance from the pollution source increases, vegetation along the slopes begins to display Markovian spatial dynamics. We suggest that this is due to information loss resulting from static ordination analyses: information regarding transitions between observations along the natural ordering of quadrats is not maintained. Both ordination techniques and the Markov analyses detected strong regional pollution-induced gradients in abundance and structure.

Keywords

Correspondence analysis Great Lakes-St. Lawrence forest Hill-slopes Perturbation gradient Principal components analysis Ordination Stationary Markov model 

Abbreviations

CA

Correspondence Analysis

PCA

Principal Components Analysis.

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© Akadémiai Kiadó, Budapest 2003

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Department of BiologyLaurentian UniversitySudburyCanada

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