Snow disturbances in secondary Norway spruce forests in Central Europe: Regression modeling and its implications for forest management

Forest Ecology and Management

Volumn 262, Issue 12, 2011, Pages 2151-2161

  Hlásny, Tomáš ^a,b   Kristek, Štěpán ^c   Holuša, Jaroslav ^b,d   Trombik, Jiří ^e   Urbaňcová, Naděžda ^c  

^a FOREST RESEARCH INSTITUTE   (Slovakia)

^b CZECH UNIVERSITY OF LIFE SCIENCES PRAGUE   (Czech Republic)

^c Ministerstvo zemedelstvi   (Czech Republic)

^d FORESTRY AND GAME MANAGEMENT RESEARCH INSTITUTE   (Czech Republic)

^e UNIVERSITY OF OSTRAVA   (Czech Republic)

Author keywords

Environmental parameters; Forest management; Neural networks based regression modeling; Norway spruce; Snow damage types; Stand characteristic

Indexed keywords

CENTRAL EUROPE; CZECH REPUBLIC; DAMAGE TYPE; DEVELOPMENTAL STAGE; ECOLOGICAL FACTORS; ENVIRONMENTAL PARAMETER; FOREST HEALTH; HEAVY SNOWFALL; LOCAL CONDITIONS; MOUNTAINOUS REGIONS; NORTHERN LATITUDES; NORWAY SPRUCE; REGRESSION MODELING; SNOW DEPTHS; SNOW LOADS; SPRUCE FOREST; SPRUCE STANDS; STAND CHARACTERISTIC; STAND DENSITIES; STAND VOLUME; STEM BREAKAGE; VEGETATION DISTRIBUTION; WINTER PRECIPITATION;

DAMAGE DETECTION; NETWORK MANAGEMENT; NEURAL NETWORKS; PLANT EXTRACTS; REFORESTATION; REGRESSION ANALYSIS; STRUCTURAL DYNAMICS;

SNOW;

ARTIFICIAL NEURAL NETWORK; CONIFEROUS FOREST; DAMAGE; DISTURBANCE; ENVIRONMENTAL CONDITIONS; FOREST HEALTH; FOREST MANAGEMENT; MOUNTAIN REGION; NUMERICAL MODEL; PRECIPITATION (CLIMATOLOGY); PRODUCTIVITY; REGENERATION; REGRESSION ANALYSIS; SECONDARY FOREST; SNOW;

CENTRAL EUROPE;

PICEA; PICEA ABIES;

EID: 80054980233     PISSN: 03781127     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.foreco.2011.08.005     Document Type: Article

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