4.2 Article

Analysing the effects of water quality on the occurrence of freshwater macroinvertebrate taxa among tropical river basins from different continents

Journal

AI COMMUNICATIONS
Volume 29, Issue 6, Pages 665-685

Publisher

IOS PRESS
DOI: 10.3233/AIC-160712

Keywords

Classification trees; ecological modelling; pollution; decision trees; ecological assessment

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Macroinvertebrates are globally used in environmental monitoring and assessment. However, due to environmental and biological evolution, local adaptations of species might occur. This can contribute to uncertainties in the extrapolation of familyspecific ecological models developed from one region to another. Thus, we aimed to determine if models can be extrapolated to other regions with similar climatic conditions and if a reliable model can be developed from a pooled dataset (consisting of data from different regions). The occurrence of five families was modelled based on physical-chemical water quality variables with classification trees using the data from three tropical river basins (Chaguana in Ecuador, Gilgel Gibe in Ethiopia and Cau in Vietnam). The relevance of each model was tested on complementary data from both the same and other river basins, to test specificity and universality. Furthermore, models with a pooled dataset were developed and tested. Model reliability was assessed based on chance-corrected agreement (Cohen's kappa, kappa) and percent agreement (correctly classified instances, CCI). Values of higher than 0.4 (kappa) and 70% (CCI) were used to classify models as good. Only the pollution sensitive taxon (Leptophlebiidae) resulted in reliable models for most cases. In general, responses of macroinvertebrates towards pollution were different among countries except for the pollution sensitive taxa. Thus, extrapolation of ecological models for sensitive taxa to another river basin with similar climatic and environmental conditions is possible. Nevertheless, this type of systematic analyses for all families is necessary to determine and minimize uncertainty in ecological assessment.

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