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Please use this identifier to cite or link to this item: https://dspace.ucuenca.edu.ec/handle/123456789/29283
Title: A methodology to model environmental preferences of EPT taxa in the Machangara river basin (Ecuador)
Authors: Jerves Cobo, Ruben Fernando
Everaert, Gert
Iñiguez Vela, Xavier Patricio
Cordova Vela, Gonzalo Esteban
Diaz Granda, Catalina Monserrat
Cisneros Espinosa, Felipe Eduardo francisco
Nopens, Ingmar
Goethals, Peter L
metadata.dc.ucuenca.correspondencia: Jerves Cobo, Ruben Fernando, rubenf.jervesc@ucuenca.edu.ec
Keywords: Generalized linear models
Predictive models
Decision support in water management
Generalized linear modeling
metadata.dc.ucuenca.areaconocimientofrascatiamplio: 1. Ciencias Naturales y Exactas
metadata.dc.ucuenca.areaconocimientofrascatidetallado: 1.5.10 Recursos Hídricos
metadata.dc.ucuenca.areaconocimientofrascatiespecifico: 1.5 Ciencias de la Tierra y el Ambiente
metadata.dc.ucuenca.areaconocimientounescoamplio: 05 - Ciencias Físicas, Ciencias Naturales, Matemáticas y Estadísticas
metadata.dc.ucuenca.areaconocimientounescodetallado: 0521 - Ciencias Ambientales
metadata.dc.ucuenca.areaconocimientounescoespecifico: 052 - Medio Ambiente
Issue Date: 2017
metadata.dc.ucuenca.volumen: Volumen 9, Número 3
metadata.dc.source: Water
metadata.dc.identifier.doi: 10.3390/w9030195
metadata.dc.type: ARTÍCULO
Abstract: 
Rivers have been frequently assessed based on the presence of the Ephemeroptera— Plecoptera—Trichoptera (EPT) taxa in order to determine the water quality status and develop conservation programs. This research evaluates the abiotic preferences of three families of the EPT taxa Baetidae, Leptoceridae and Perlidae in the Machangara River Basin located in the southern Andes of Ecuador. With this objective, using generalized linear models (GLMs), we analyzed the relation between the probability of occurrence of these pollution-sensitive macroinvertebrates families and physicochemical water quality conditions. The explanatory variables of the constructed GLMs differed substantially among the taxa, as did the preference range of the common predictors. In total, eight variables had a substantial influence on the outcomes of the three models. For choosing the best predictors of each studied taxa and for evaluation of the accuracy of its models, the Akaike information criterion (AIC) was used. The results indicated that the GLMs can be applied to predict either the presence or the absence of the invertebrate taxa and moreover, to clarify the relation to the environmental conditions of the stream. In this manner, these modeling tools can help to determine key variables for river restoration and protection management.
Description: 
Rivers have been frequently assessed based on the presence of the Ephemeroptera— Plecoptera—Trichoptera (EPT) taxa in order to determine the water quality status and develop conservation programs. This research evaluates the abiotic preferences of three families of the EPT taxa Baetidae, Leptoceridae and Perlidae in the Machangara River Basin located in the southern Andes of Ecuador. With this objective, using generalized linear models (GLMs), we analyzed the relation between the probability of occurrence of these pollution-sensitive macroinvertebrates families and physicochemical water quality conditions. The explanatory variables of the constructed GLMs differed substantially among the taxa, as did the preference range of the common predictors. In total, eight variables had a substantial influence on the outcomes of the three models. For choosing the best predictors of each studied taxa and for evaluation of the accuracy of its models, the Akaike information criterion (AIC) was used. The results indicated that the GLMs can be applied to predict either the presence or the absence of the invertebrate taxa and moreover, to clarify the relation to the environmental conditions of the stream. In this manner, these modeling tools can help to determine key variables for river restoration and protection management.
URI: https://www.mdpi.com/2073-4441/9/3/195
metadata.dc.ucuenca.urifuente: https://www.mdpi.com/journal/water
ISSN: 2073-4441
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