Native fish are indicators of the health of aquatic ecosystems, and they have become a key quality element to assess the ecological status of rivers. The understanding of factors affecting native fish species is important for the management and conservation of aquatic ecosystems. The general objective of this thesis are to analyse the relationships between biological and habitat variables (including connectivity) across a range of spatial scales in Mediterranean rivers, with the development of modelling tools to support the decision-making in river restoration. This thesis is composed by four articles. The first aims to model the relationship between a set of environmental variables and native species richness (NFSR), and to evaluate the potential effectiveness of river restoration actions to improve NFSR in the Júcar river basin. In order to solve these questions, an artificial neural network (ANN) modelling approach was carried out, using the Levenberg-Marquardt learning algorithm in the model training phase. The partial derivatives method was applied to determine the relative importance of input environmental variables. According to the results, ANN model combined variables describing riparian quality, water quality, and physical habitat and helped to 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 consequent increase in the proportion of riffles. These simulations indicated that richness increases with the augmentation of channel length without artificial barriers and riffle proportion, and demonstrated the utility of ANN as a powerful tool to support decisions in the management and ecological restoration of Mediterranean rivers. The second paper aims to determine the relative importance of the two main factors controlling the reduction of native fish species richness (NFSR), i.e. the interactions between aquatic species, habitat (including river connectivity) and biological variables (including invasive species) in the Júcar, Cabriel and Turia rivers. To this end, three ANN models were analysed: the first one built only with CONTENTS Chapter 1. Introduction………………………………………………. Chapter 2. Modelling native fish richness to evaluate the effects of hydromorphological changes and river restoration (Júcar River Basin, Spain
"Gongolaria barbata (Stackhouse) Kuntze (formerly known as Cystoseira barbata (Stackhouse) C. Agardh, 1820) builds essential habitats for marine biodiversity and ecosystem optimal functioning along the Romanian Black Sea coast. G. barbata forms so-called brown algal forests especially in the southern part of the Romanian Black Sea shore, providing all categories of ecosystem services, at the same time being a source of potentially bioactive metabolites. Over the last decades, Cystoseira sensu lato have suffered a general decline due to anthropogenic pressure and the Romanian Black Sea coast is not an exception. G. barbata is the only remained representative of Cystoseira s. l. from the Romanian coast and currently the most important habitat - forming species, being a suggestive indicator of environmental degradation and loss of habitats. The study aims to present the last fourteen years ecological status assessment of the sensitive habitat Upper-infralittoral rock dominated by G. barbata. Sampling was conducted between 2009 – 2022 (summer seasons) and a total number of 144 samples were collected using the “quadrat method” (20 x 20 cm). Data were statistically analyzed, and the specific Ecological Index (EI) was applied to evaluate the ecological status. The results of this study showed that this vulnerable habitat reached good ecological status during 2009 - 20122, except for 2012 and 2014. Nevertheless, the current distribution of G. barbata habitat is sparse, and the species remains highly sensitive to increasing anthropogenic activities in coastal zones."
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