A Methodology to Model Environmental Preferences of EPT Taxa in the Machangara River Basin (Ecuador)

作     者：Jerves-Cobo, Ruben Everaert, Gert Iniguez-Vela, Xavier Cordova-Vela, Gonzalo Diaz-Granda, Catalina Cisneros, Felipe Nopens, Ingmar Goethals, Peter L. M. 

作者机构：Univ Ghent Lab Environm Toxicol & Aquat Ecol Dept Appl Ecol & Environm Biol Coupure Links 653 B-9000 Ghent Belgium Univ Ghent BIOMATH Dept Math Modelling Stat & Bioinformat Coupure Links 653 B-9000 Ghent Belgium Univ Cuenca PROMAS Programa Para Manejo Agua & Suelo Av 12 abril S-N & Agustin Cueva Cuenca 010103 Ecuador Asociac Consultores Tecnicos ACOTECNIC Cia Ltd Aguaruna S-N & Autopista Cuenca Azogues Cuenca 010109 Ecuador Agua Potable Alcantarillado Saneamiento ETAPA EP Empresa Publ Municipal Telecomun Benigno Malo 7-78 & Mariscal Sucre Cuenca 010101 Ecuador 

出 版 物：《WATER》 (水)

年 卷 期：2017年第9卷第3期

页      面：195页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 08[工学] 081501[工学-水文学及水资源] 0815[工学-水利工程] 

基　　金：Special Research Fund of Ghent University in Belgium [BOF15/PDO/061] 

主　　题：generalized linear models predictive models decision support in water management generalized linear modeling 

摘      要：Rivers have been frequently assessed based on the presence of the EphemeropteraPlecopteraTrichoptera (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.