Multivariate approaches in species distribution modelling: application to native fish species in mediterranean rivers
- Autores: Rafael Muñoz Mas
- Directores de la Tesis: Francisco Martínez Capel (dir. tes.)
- Lectura: En la Universitat Politècnica de València ( España ) en 2016
- Idioma: español
- Tribunal Calificador de la Tesis: Francisco José Oliva Paterna (presid.), Miguel Rodilla Alamá (secret.), Rui Manuel Vitor Cortes (voc.)
- Programa de doctorado: Programa de Doctorado en Ingeniería del Agua y Medioambiental por la Universitat Politècnica de València
- Materias:
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- Resumen
This dissertation focused in the comprehensive analysis of the capabilities of some non-tested types of Artificial Neural Networks, specifically: the Probabilistic Neural Networks (PNN) and the Multi-Layer Perceptron (MLP) Ensembles. The analysis of the capabilities of these techniques was performed using the native brown trout (Salmo trutta; Linnaeus, 1758), the bermejuela (Achondrostoma arcasii; Robalo, Almada, Levy & Doadrio, 2006) and the redfin barbel (Barbus haasi; Mertens, 1925) as target species. The analyses focused in the predictive capabilities, the interpretability of the models and the effect of the excess of zeros in the training datasets, which for presence-absence models is directly related to the concept of data prevalence (i.e. proportion of presence instances in the training dataset). Finally, the effect of the spatial scale (i.e. micro-scale or microhabitat scale and meso-scale) in the habitat suitability models and consequently in the e-flow assessment was studied in the last chapter.
