Predicting assemblages and species richness of endemic fish in the upper Yangtze River

Science of the Total Environment

Volumn 408, Issue 19, 2010, Pages 4211-4220

  He, Yongfeng ^a,b,c   Wang, Jianwei ^b   Lek Ang, Sithan ^a   Lek, Sovan ^a  

^a UNIVERSITÉ DE TOULOUSE   (France)

^b INSTITUTE OF HYDROBIOLOGY   (China)

^c UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

Author keywords

CART; Endemic fish; Environmental variables; RF; Species richness pattern; Yangtze River

Indexed keywords

AQUATIC ECOSYSTEM; CLASSIFICATION AND REGRESSION TREE; DRAINAGE AREA; ENDEMIC SPECIES; ENVIRONMENTAL FACTORS; ENVIRONMENTAL VARIABLES; FISH ASSEMBLAGE STRUCTURE; FISH ASSEMBLAGES; FISH DISTRIBUTIONS; HUMAN ACTIVITIES; LAND COVER; LAND-USE CHANGE; LEAVE-ONE-OUT; MIXED MODELS; MODELING APPROACH; MODELING METHOD; PREDICTOR VARIABLES; RANDOM FORESTS; REGIONAL SCALE; RF; SPECIES RICHNESS; SUB-ALPINE; UPPER YANGTZE RIVER; YANGTZE RIVER;

CLASSIFICATION (OF INFORMATION); DECISION TREES; FORESTRY; LAND USE; RIVERS; RUNOFF;

FISH;

ALGORITHM; AQUATIC COMMUNITY; DATA MINING; ENDEMIC SPECIES; ENVIRONMENTAL FACTOR; FISH; MODEL VALIDATION; NUMERICAL MODEL; PREDICTION; SPECIES RICHNESS; VARIANCE ANALYSIS;

ACCURACY; AGRICULTURAL LAND; ALTITUDE; ARTICLE; CHINA; CONTROLLED STUDY; ECOSYSTEM; ENVIRONMENTAL FACTOR; FISH; GRASSLAND; LAND USE; MACHINE LEARNING; NONHUMAN; PREDICTION; PRIORITY JOURNAL; RIVER; SPECIES RICHNESS;

ANIMALS; BIODIVERSITY; CHINA; ENVIRONMENTAL MONITORING; FISHES; FORECASTING; GEOLOGICAL PHENOMENA; MODELS, THEORETICAL; RIVERS;

CLASSIFICATION; DECISION MAKING; FISHES; LAND USE; MATHEMATICAL MODELS; RIVERS; RUNOFF; SPECIES IDENTIFICATION;

CHINA; YANGTZE RIVER;

EID: 77954625327     PISSN: 00489697     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.scitotenv.2010.04.052     Document Type: Article

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