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

Science of the Total Environment

Volumn 440, Issue , 2012, Pages 95-105

  Olaya Marín, Esther Julia ^a   Martínez Capel, Francisco ^a   Soares Costa, Rui Manuel ^a   Alcaraz Hernández, Juan Diego ^a  

^a UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

Author keywords

Artificial neural networks; Fish richness; Hydromorphology; Mitigation measures; River connectivity; River restoration

Indexed keywords

AQUATIC ECOSYSTEM; ARTIFICIAL NEURAL NETWORK MODELS; BASIN SCALE; CROSS-VALIDATION METHODS; ECOLOGICAL RESTORATION; ENVIRONMENTAL VARIABLES; EUROPEAN WATER FRAMEWORK DIRECTIVE; FIELD DATA; FISH COMMUNITIES; FISH SPECIES RICHNESS; GLOBAL CHANGE; HIDDEN LAYERS; HYDROMORPHOLOGY; K-VALUES; KEY VARIABLES; LEVENBERG-MARQUARDT LEARNING ALGORITHMS; MEDITERRANEAN RIVERS; MITIGATION MEASURES; MODEL TRAINING; PARTIAL DERIVATIVES; PHYSICAL HABITAT; REFERENCE SITES; RELIABILITY AND ROBUSTNESS; RIVER BASINS; RIVER ECOSYSTEM; RIVER RESTORATION; WATER SCARCITY;

ECOSYSTEMS; FISH; LEARNING ALGORITHMS; NEURAL NETWORKS; RESTORATION; WATER QUALITY; WATERSHEDS;

RIVERS;

ARTIFICIAL NEURAL NETWORK; BIOINDICATOR; ECOMORPHOLOGY; ECOSYSTEM HEALTH; ECOSYSTEM MANAGEMENT; FISH; HABITAT QUALITY; MITIGATION; MODEL VALIDATION; RESTORATION ECOLOGY; RIFFLE; RIVER BASIN; RIVER MANAGEMENT; SPECIES RICHNESS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; ECOSYSTEM RESTORATION; ENVIRONMENTAL CHANGE; ENVIRONMENTAL FACTOR; ENVIRONMENTAL IMPACT ASSESSMENT; FISH; GLOBAL CHANGE; LEARNING ALGORITHM; MATHEMATICAL MODEL; NONHUMAN; PRIORITY JOURNAL; RIPARIAN ECOSYSTEM; RIVER BASIN; RIVER ECOSYSTEM; SENSITIVITY ANALYSIS; SPECIES RICHNESS; VALIDATION PROCESS; WATER QUALITY;

ANIMALS; BIODIVERSITY; CONSERVATION OF NATURAL RESOURCES; ENVIRONMENT; FISHES; MODELS, BIOLOGICAL; NEURAL NETWORKS (COMPUTER); REPRODUCIBILITY OF RESULTS; RIVERS; SPAIN; WATER MOVEMENTS; WATER QUALITY;

JUCAR BASIN; SPAIN;

EID: 84868711471     PISSN: 00489697     EISSN: 18791026     Source Type: Journal    
DOI: 10.1016/j.scitotenv.2012.07.093     Document Type: Article

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