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Community Ecology

, Volume 3, Issue 1, pp 19–29 | Cite as

Optimal classification to describe environmental change: pictures from the exposition

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

Abstract

In this paper we examine the impact of runnelling on the vegetation of a salt marsh. Runnelling is a form of habitat modification used for mosquito control in Australia. Defining the states of the system through unsupervised clustering of vegetation records using the minimum message length principle, 11 states (or classes) were identified. The runnelled sites have a greater diversity of states present than the unrunnelled ones. The states at each time for each site were then used to develop transition matrices. From these, two different pathways were identified, indicating the patterns of change. The method of showing changes relied on pictures that represent average species size and density. Both the two main pathways of change started with the dominant grass (Sporobolus). One led to a reduction in Sporobolous and ended in bare ground; the other included changes involving variation in the size and density of a mix of Sporobolus and Sarcocornia. The effects can be interpreted in terms of the increased access of seawater to the marsh resulting in an extension of the lower marsh. We note, however, that this methodology does not distinguish between changes of state within a single process and changes associated with a change in the actual processes operating.

Keywords

Clustering Discrete state Dynamics Impact assessment Minimum message length (MML) Runnelling Transition matrices 

Abbreviation

MML

minimum message length

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© Akadémiai Kiadó, Budapest 2001

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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