Remote sensing data can improve predictions of species richness by stacked species distribution models: A case study for Mexican pines

Journal of Biogeography

Volumn 41, Issue 4, 2014, Pages 736-748

  Cord, Anna F ^a,b,c   Klein, Doris ^b   Gernandt, David S ^d   de la Rosa, Jorge A Pérez ^e   Dech, Stefan ^b,c  

^a HELMHOLTZ CENTRE FOR ENVIRONMENTAL RESEARCH UFZ   (Germany)

^b GERMAN AEROSPACE CENTER DLR   (Germany)

^c UNIVERSITY OF WÜRZBURG   (Germany)

^d UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO   (Mexico)

^e UNIVERSITY OF GUADALAJARA   (Mexico)

Author keywords

Biodiversity; Enhanced vegetation index; Herbarium presence records; Land surface temperature; Maximum entropy; MODIS; Time series; Vegetation phenology

Indexed keywords

ALGORITHM; CONIFEROUS TREE; ECOLOGICAL MODELING; FOREST INVENTORY; HABITAT AVAILABILITY; MAXIMUM ENTROPY ANALYSIS; MODIS; PHENOLOGY; POPULATION DISTRIBUTION; REMOTE SENSING; SPECIES RICHNESS; SURFACE TEMPERATURE; TERRA (SATELLITE); TIME SERIES ANALYSIS; VEGETATION INDEX;

MEXICO [NORTH AMERICA];

PINACEAE;

EID: 84896110415     PISSN: 03050270     EISSN: 13652699     Source Type: Journal    
DOI: 10.1111/jbi.12225     Document Type: Article

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