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Community Ecology

, Volume 5, Issue 2, pp 203–225 | Cite as

Sources of uncertainty in ecological modelling: predicting vegetation types from environmental attributes

  • M. B. Dale
  • P. E. R. DaleEmail author
Article

Abstract

In this paper, we use decision trees to construct models for predicting vegetation types from environmental attributes in a salt marsh. We examine a method for evaluating the worth of a decision tree and look at seven sources of uncertainty in the models produced, namely algorithmic, predictive, model, scenario, objective, context and scale. The accuracy of prediction of types was strongly affected by the scenario and scale, with the most dynamically variable attributes associated with poor prediction, while more static attributes performed better. However, examination of the misclassified samples showed that prediction of processes was much better, with local vegetation type-induced patterns nested within a broader environmental framework.

Keywords

Salt marsh Vegetation types Decision trees MML Types of uncertainty 

Abbreviation

MML

Minimum Message Length.

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© Akadémiai Kiadó, Budapest 2004

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.Australian School of Environmental StudiesGriffith UniversityNathanAustralia

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