Use of community-composition data to predict the fecundity and abundance of species

Conservation Biology

Volumn 22, Issue 6, 2008, Pages 1523-1532

  Elmendorf, Sarah C ^a,b   Moore, Kara A ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

Artificial neural networks; Beals index; Boosted regression trees; Community composition; Fecundity; Species abundance; Species distribution models

Indexed keywords

BIODIVERSITY; COMMUNITY COMPOSITION; FECUNDITY; GRASSLAND; MOISTURE; REGRESSION ANALYSIS; SOLAR RADIATION;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BIODIVERSITY; BIOLOGICAL MODEL; ENVIRONMENT; ENVIRONMENTAL PROTECTION; FERTILITY; METHODOLOGY; PHYSIOLOGY; POACEAE; SPECIES DIFFERENCE; UNITED STATES;

BIODIVERSITY; CALIFORNIA; CONSERVATION OF NATURAL RESOURCES; ENVIRONMENT; FERTILITY; MODELS, BIOLOGICAL; NEURAL NETWORKS (COMPUTER); POACEAE; SPECIES SPECIFICITY;

EID: 57449097637     PISSN: 08888892     EISSN: 15231739     Source Type: Journal    
DOI: 10.1111/j.1523-1739.2008.01051.x     Document Type: Article

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