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Modelling native fish richness to evaluate the effects of hydromorphological changes and river restoration (Júcar River Basin, Spain)

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Modelling native fish richness to evaluate the effects of hydromorphological changes and river restoration (Júcar River Basin, Spain)

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dc.contributor.author Olaya Marín, Esther Julia es_ES
dc.contributor.author Martinez-Capel, Francisco es_ES
dc.contributor.author Soares Costa, Rui Manuel es_ES
dc.contributor.author Alcaraz-Hernández, Juan Diego es_ES
dc.date.accessioned 2013-11-08T10:31:43Z
dc.date.issued 2012
dc.identifier.issn 0048-9697
dc.identifier.uri http://hdl.handle.net/10251/33328
dc.description.abstract The richness of native fish is considered to be an indicator of aquatic ecosystem health, and improving richness is a key goal in the management of river ecosystems. An artificial neural network (ANN) model based on field data from 90 sample sites distributed throughout the Júcar River Basin District was developed to predict the native fish species richness (NFSR). The Levenberg-Marquardt learning algorithm was used for model training. When constructing the model, we tried different numbers of neurons (hidden layers), compared different transfer functions, and tried different k values (from 3 to 10) in the k-fold cross-validation method. This process and the final selection of key variables with relevant ecological meaning support the reliability and robustness of the final ANN model. The partial derivatives method was applied to determine the relative importance of input environmental variables. The final ANN model combined variables describing riparian quality, water quality, and physical habitat and helped identify the primary drivers of the NFSR patterns in Mediterranean rivers. In the second part of the study, the model was used to evaluate the effectiveness of two restoration actions in the Júcar River: the removal of two abandoned weirs and the progressive increase in the proportion of riffles. The model indicated that the combination of these actions produced a rise in NFSR, which ultimately reached the maximum values observed in the reference site of that river ecotype (sensu the European Water Framework Directive). The results demonstrate the importance of longitudinal connectivity and riffle proportion for improving NFSR and the power of ANNs to help decisions in the management and ecological restoration of Mediterranean rivers. Furthermore, this model at the basin scale is the first step for further research on the effects of water scarcity and global change on Mediterranean fish communities. es_ES
dc.description.sponsorship This study was partially funded by the Spanish Ministry of Economy and Competitiveness with the projects SCARCE (Consolider-Ingenio 2010 CSD2009-00065) and POTECOL "Evaluacion del Potencial Ecologico de Rios Regulados por Embalses y Desarrollo de Criterios para su mejora segun la Directiva Marco del Agua" (CGL2007-66412). We thank to Confederacion Hidrografica del Jucar (Spanish Ministry of Agriculture, Food and Environment) for the data provided to develop this study. We thank Sasa Plestenjak in the collaboration for building the first fish database elaborated in this research. en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Science of the Total Environment es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Artificial neural networks es_ES
dc.subject Fish richness es_ES
dc.subject Hydromorphology es_ES
dc.subject Mitigation measures es_ES
dc.subject River connectivity es_ES
dc.subject River restoration es_ES
dc.subject Aquatic ecosystem es_ES
dc.subject Artificial neural network models es_ES
dc.subject Basin scale es_ES
dc.subject Cross-validation methods es_ES
dc.subject Ecological restoration es_ES
dc.subject Environmental variables es_ES
dc.subject European Water Framework Directive es_ES
dc.subject Field data es_ES
dc.subject Fish communities es_ES
dc.subject Fish species richness es_ES
dc.subject Global change es_ES
dc.subject Hidden layers es_ES
dc.subject K-values es_ES
dc.subject Key variables es_ES
dc.subject Levenberg-Marquardt learning algorithms es_ES
dc.subject Mediterranean rivers es_ES
dc.subject Model training es_ES
dc.subject Partial derivatives es_ES
dc.subject Physical habitat es_ES
dc.subject Reference sites es_ES
dc.subject Reliability and robustness es_ES
dc.subject River basins es_ES
dc.subject River ecosystem es_ES
dc.subject Water scarcity es_ES
dc.subject Ecosystems es_ES
dc.subject Fish es_ES
dc.subject Learning algorithms es_ES
dc.subject Neural networks es_ES
dc.subject Restoration es_ES
dc.subject Water quality es_ES
dc.subject Watersheds es_ES
dc.subject Rivers es_ES
dc.subject Artificial neural network es_ES
dc.subject Bioindicator es_ES
dc.subject Ecomorphology es_ES
dc.subject Ecosystem health es_ES
dc.subject Ecosystem management es_ES
dc.subject Habitat quality es_ES
dc.subject Mitigation es_ES
dc.subject Model validation es_ES
dc.subject Restoration ecology es_ES
dc.subject Riffle es_ES
dc.subject River basin es_ES
dc.subject River management es_ES
dc.subject Species richness es_ES
dc.subject Article es_ES
dc.subject Ecosystem restoration es_ES
dc.subject Environmental change es_ES
dc.subject Environmental factor es_ES
dc.subject Environmental impact assessment es_ES
dc.subject Learning algorithm es_ES
dc.subject Mathematical model es_ES
dc.subject Nonhuman es_ES
dc.subject Priority journal es_ES
dc.subject Riparian ecosystem es_ES
dc.subject Sensitivity analysis es_ES
dc.subject Validation process es_ES
dc.subject Jucar Basin es_ES
dc.subject Spain es_ES
dc.subject.classification TECNOLOGIA DEL MEDIO AMBIENTE es_ES
dc.title Modelling native fish richness to evaluate the effects of hydromorphological changes and river restoration (Júcar River Basin, Spain) es_ES
dc.type Artículo es_ES
dc.embargo.lift 10000-01-01
dc.embargo.terms forever es_ES
dc.identifier.doi 10.1016/j.scitotenv.2012.07.093
dc.relation.projectID info:eu-repo/grantAgreement/MEC//CGL2007-66412/ES/EVALUACION DEL POTENCIAL ECOLOGICO DE RIOS REGULADOS POR EMBALSES Y DESARROLLO DE CRITERIOS PARA SU MEJORA SEGUN LA DIRECTIVA MARCO DEL AGUA./ / es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//CSD2009-00065/ES/Evaluación y predicción de los efectos del cambio global en la cantidad y la calidad del agua en ríos ibéricos/ es_ES
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto de Investigación para la Gestión Integral de Zonas Costeras - Institut d'Investigació per a la Gestió Integral de Zones Costaneres es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient es_ES
dc.description.bibliographicCitation Olaya Marín, EJ.; Martinez-Capel, F.; Soares Costa, RM.; Alcaraz-Hernández, JD. (2012). Modelling native fish richness to evaluate the effects of hydromorphological changes and river restoration (Júcar River Basin, Spain). Science of the Total Environment. 440:95-105. doi:10.1016/j.scitotenv.2012.07.093 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.scitotenv.2012.07.093 es_ES
dc.description.upvformatpinicio 95 es_ES
dc.description.upvformatpfin 105 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 440 es_ES
dc.relation.senia 230301


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