A protocol to estimate epiphyte biomass in a forest management unit: case of Cameroon

Vascular epiphyte biomass is poorly studied in Congo Basin forest. The aim of this study was to develop a protocol to estimate epiphyte biomass. Epiphytes were collected on 77 phorophytes of diameter 57-169.5 cm, oven-dried for biomass. Allometric equations for epiphyte biomass were developed with d...

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Bibliographic Details
Published in:Journal of sustainable forestry 2018-08, Vol.37 (6), p.619-631
Main Authors: Nfornkah, Barnabas Neba, Zapfack, Louis, Tchamba, Martin, Chimi, Cedric Djomo, Sonke, Bonaventure
Format: Article
Language:English
Subjects:
allometric equations
Allometry
Biodegradation
Biomass
Climate change
Climate change mitigation
Deforestation
Emissions control
Epiphytes
Forest biomass
Forest degradation
Forest management
forest management unit
Forestry
Forests
Mathematical models
phorophyte
Protocol
REDD
Regression analysis
Sustainability
vascular epiphyte biomass
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Summary:Vascular epiphyte biomass is poorly studied in Congo Basin forest. The aim of this study was to develop a protocol to estimate epiphyte biomass. Epiphytes were collected on 77 phorophytes of diameter 57-169.5 cm, oven-dried for biomass. Allometric equations for epiphyte biomass were developed with diameter and phorophyte height as predictor variables using regression analysis. The mean epiphyte biomass was 24.48 kg/phorophyte with a standard deviation of ±49.99. Cylicodiscus gabunensis and Triplochiton scleroxylon hosted the greatest epiphyte biomass with a mean vascular epiphyte biomass of 71.65 and 62.3 kg/phorophyte, respectively. Kruskal-Wallis test (p = 0.005) showed that there was a significant difference between epiphyte biomass with respect to phorophyte species. The relationship found between epiphyte biomass and dendrometric variables of the phorophytes were intermediate (Adj.R 2 < 0.630) meaning epiphyte biomass increased with increasing tree diameter. However, models with diameter input variables had greater prediction than input variables of total height. Based on the Akaike Information Criterion (AIC), the allometry lnY = −21.37 + 5.21 x ln(D) −0.35 x ln(H) with AIC (183) was the best equation for the prediction of epiphyte biomass. These findings shall contribute to REDD+ (Reducing Emissions from Deforestation and Forest Degradation) strategy for climate change mitigation in Congo Basin.
ISSN:1054-9811
1540-756X
DOI:10.1080/10549811.2018.1449122