Reducing the error in biomass estimates strongly depends on model selection

Annals of Forest Science

Volumn 72, Issue 6, 2015, Pages 811-823

  Picard, Nicolas ^a   Boyemba Bosela, Faustin ^b   Rossi, Vivien ^c,d  

^a Central African Forests Commission   (Cameroon)

^b UNIVERSITY OF KISANGANI   (Congo)

^c CIRAD   (France)

^d UNIVERSITY OF YAOUNDÉ I   (Cameroon)

Author keywords

Aboveground biomass; African moist forest; Allometric equation; Bayesian model averaging; Error propagation; Prediction error

Indexed keywords

ABOVEGROUND BIOMASS; ALLOMETRY; BAYESIAN ANALYSIS; DATA SET; ERROR ANALYSIS; ESTIMATION METHOD; FOREST INVENTORY; FOREST MANAGEMENT; FORESTRY MODELING; LANDSCAPE ECOLOGY; PREDICTION; TROPICAL FOREST;

CENTRAL AFRICA; DEMOCRATIC REPUBLIC CONGO; KISANGANI; ORIENTALE;

EID: 84938634400     PISSN: 12864560     EISSN: 1297966X     Source Type: Journal    
DOI: 10.1007/s13595-014-0434-9     Document Type: Article

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