Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/27270
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Type: Journal article
Title: Predictive modelling of macroinvertebrate assemblages for stream habitat assessments in Queensland (Australia)
Author: Hoang, T.
Recknagel, F.
Marshall, J.
Choy, S.
Citation: Ecological Modelling, 2001; 195(1-3):195-206
Publisher: Elsevier Science BV
Issue Date: 2001
ISSN: 0304-3800
1872-7026
Statement of
Responsibility: 
Huong Hoang, Friedrich Recknagel, Jonathan Marshall, Satish Choy
Abstract: This paper describes the iterative approach towards predictive Artificial Neural Network (ANN) models for 37 macroinvertebrate taxa based on 896 stream data sets from the Queensland stream system. Data preprocessing and sensitivity analyses proved to be crucial in order to create data consistency and non-redundancy in the context of this approach. The model validation by means of 167 independent data sets revealed 73% as lowest rate and 82% as average rate of correct ANN predictions of stream site habitats. The increase of correct predictions was 30%, if ANNs and the statistical stream model AusRivAS were compared based on the same data sets. The validation of the ANN models justified their application to the prediction and assessment of stream habitats based on an independent database for test sites. Implications to stream management and research were drawn from prediction results. © 2001 Elsevier Science B.V. All rights reserved.
DOI: 10.1016/S0304-3800(01)00306-4
Published version: http://dx.doi.org/10.1016/s0304-3800(01)00306-4
Appears in Collections:Aurora harvest 6
Environment Institute publications
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