Remotely sensed forest structural complexity predicts multi species occurrence at the landscape scale

Forest Ecology and Management

Volumn 307, Issue , 2013, Pages 303-312

  Zellweger, Florian ^a   Braunisch, Veronika ^b,c   Baltensweiler, Andri ^a   Bollmann, Kurt ^a  

^a SWISS FEDERAL RESEARCH INSTITUTE WSL   (Switzerland)

^b UNIVERSITY OF BERN   (Switzerland)

^c Forest Research Institute of Baden Wurttemberg   (Germany)

Author keywords

Biodiversity; Birds; Habitat; LiDAR; NDVI; Structure

Indexed keywords

BOOSTED REGRESSION TREES; HABITAT; NDVI; PLANT SPECIES COMPOSITION; SPECIES DISTRIBUTION MODELS; STRUCTURAL CHARACTERISTICS; STRUCTURAL HETEROGENEITY; TOPOGRAPHIC POSITIONS;

BIODIVERSITY; BIRDS; ECOSYSTEMS; FORECASTING; INFORMATION MANAGEMENT; OPTICAL RADAR; PLANTS (BOTANY); POPULATION DISTRIBUTION; REMOTE SENSING; SPACE OPTICS; STRUCTURE (COMPOSITION);

FORESTRY;

AVIFAUNA; CONSERVATION PLANNING; FOREST ECOSYSTEM; FOREST EDGE; HABITAT QUALITY; LIDAR; MOUNTAIN REGION; NDVI; PREDICTION; REMOTE SENSING; SNAG; SPECIES DIVERSITY; SPECIES OCCURRENCE; STAND STRUCTURE; SYMPATRY;

BIODIVERSITY; BIRDS; ECOSYSTEMS; FORECASTS; FORESTRY; RADAR; REMOTE SENSING;

SWITZERLAND;

EID: 84881448320     PISSN: 03781127     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.foreco.2013.07.023     Document Type: Article

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