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Predicting eucalypt distributions in Tasmania : an application of generalised linear modelling

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Williams, KJ (1998) Predicting eucalypt distributions in Tasmania : an application of generalised linear modelling. PhD thesis, University of Tasmania.

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Abstract

This thesis develops a systematic approach to the routine prediction of Eucalyptus species'
distributions in Tasmania from compiled ecological data comprising over 15 500 observations.
The method of logistic regression, being an application of generalised linear modelling, was used
to correlate species' occurrence with environment. Preliminary analyses tested sampling
adequacy in terms of ecological variability and species' ranges, and derived environmental
indices that could be directly related to plant physiological processes. Subsequent realised mche
models were derived for the distribution of E. globulus in eastern regions of Tasmania
considering biotic and abiotic attributes as predictors and relative dominance as a response in
addition to occurrence. Different aspects of the ecology of this species were explored by
considering response variables defined by vegetation class or pure and mixed stand occurrences
of E. globulus and related species from the series Viminales. The results of these predictive
models were displayed as nested, univariate responses along environmental gradients,
representing a direct gradient analysis that facilitated their interpretation in terms of ecological
theory and plant physiological processes.

Item Type: Thesis (PhD)
Keywords: Eucalyptus
Copyright Holders: The Author
Copyright Information:

Copyright 1998 the Author - The University is continuing to endeavour to trace the copyright
owner(s) and in the meantime this item has been reproduced here in good faith. We
would be pleased to hear from the copyright owner(s).

Additional Information:

Chapter 5 is the equivalent of a post-print which was published as: M. Battaglia, K. J. Williams, 1996, Mixed species stands of eucalypts as ecotones on a water supply gradient, Oecologia, 108(3), 518-528. The final publication is available at Springer via http://dx.doi.org/10.1007/BF00333729

Date Deposited: 04 Feb 2015 23:25
Last Modified: 11 Mar 2016 05:55
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