Luciobarbus guiraonis (Eastern Iberian barbel) is an endemic fish species restricted to Spain, mainly distributed in the Júcar River Basin District. Its study is important because there is little knowledge about its biology and ecology. To improve the knowledge about the species distribution and habitat requirements, nonlinear modelling was carried out to predict the presence/absence and density of the Eastern Iberian barbel, based on 155 sampling sites distributed throughout the Júcar River Basin District (Eastern Iberian Peninsula). In this case study, we used multilayer feed-forward artificial neural networks (ANN) to represent nonlinear relationships between L. guiraonis descriptors with biological and habitat variables. The gradient descent algorithm was implemented to find the optimal model parameters and the importance of the ANN’s input variables was determined by the partial derivatives method (PaD). The predictive power of the model was evaluated with the Cohen’s Kappa (k), the correctly classified instances (CCI), and the area under the curve (AUC) of the receiver operator characteristic (ROC) plots. The presence/absence of L. guiraonis was predicted by the ANN model with a high performance (k= 0.66, CCI= 87% and AUC= 0.85); the prediction of density was moderate (CCI = 62%, AUC=0.71 and k= 0.43). The most significant variables that described the presence/absence were: solar radiation (its highest contribution was observed between 2000 and 4200 WH/m2), drainage area (with the strongest influence between 3000 and 5.000 km2), and proportion of exotic fish species (with relevant contribution between 50 and 100%). In the density model, the most important variables were coefficient of variation of mean annual flows (relative importance of 50.5%) and proportion of exotic fish species (24.4%), but the partial derivative method was unable to identify a positive or negative relationship between these variables and fish density. The models provide important information about the relation of L. guiraonis with biotic and abiotic variables, this new knowledge could be used to support future studies and practical decisions about the management and conservation of this species in the Júcar River Basin District, and potentially for the conservation of other endemic fish species of Barbus and Luciobarbus in Mediterranean rivers.

Modelling critical factors affecting the distribution of the vulnerable endemic Eastern Iberian barbel (Luciobarbus guiraonis) in Mediterranean rivers / Olaya marin, E. J.; Martínez capel, F.; García bartual, R.; Vezza, Paolo. - In: MEDITERRANEAN MARINE SCIENCE. - ISSN 1791-6763. - ELETTRONICO. - 17:1(2016), pp. 264-279. [10.12681/mms.1351]

Modelling critical factors affecting the distribution of the vulnerable endemic Eastern Iberian barbel (Luciobarbus guiraonis) in Mediterranean rivers

VEZZA, PAOLO
2016

Abstract

Luciobarbus guiraonis (Eastern Iberian barbel) is an endemic fish species restricted to Spain, mainly distributed in the Júcar River Basin District. Its study is important because there is little knowledge about its biology and ecology. To improve the knowledge about the species distribution and habitat requirements, nonlinear modelling was carried out to predict the presence/absence and density of the Eastern Iberian barbel, based on 155 sampling sites distributed throughout the Júcar River Basin District (Eastern Iberian Peninsula). In this case study, we used multilayer feed-forward artificial neural networks (ANN) to represent nonlinear relationships between L. guiraonis descriptors with biological and habitat variables. The gradient descent algorithm was implemented to find the optimal model parameters and the importance of the ANN’s input variables was determined by the partial derivatives method (PaD). The predictive power of the model was evaluated with the Cohen’s Kappa (k), the correctly classified instances (CCI), and the area under the curve (AUC) of the receiver operator characteristic (ROC) plots. The presence/absence of L. guiraonis was predicted by the ANN model with a high performance (k= 0.66, CCI= 87% and AUC= 0.85); the prediction of density was moderate (CCI = 62%, AUC=0.71 and k= 0.43). The most significant variables that described the presence/absence were: solar radiation (its highest contribution was observed between 2000 and 4200 WH/m2), drainage area (with the strongest influence between 3000 and 5.000 km2), and proportion of exotic fish species (with relevant contribution between 50 and 100%). In the density model, the most important variables were coefficient of variation of mean annual flows (relative importance of 50.5%) and proportion of exotic fish species (24.4%), but the partial derivative method was unable to identify a positive or negative relationship between these variables and fish density. The models provide important information about the relation of L. guiraonis with biotic and abiotic variables, this new knowledge could be used to support future studies and practical decisions about the management and conservation of this species in the Júcar River Basin District, and potentially for the conservation of other endemic fish species of Barbus and Luciobarbus in Mediterranean rivers.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2685091
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