Height-diameter allometry and above ground biomass in tropical montane forests: Insights from the Albertine Rift in Africa

Abstract

Tropical montane forests provide an important natural laboratory to test ecological theory. While it is well-known that some aspects of forest structure change with altitude, little is known on the effects of altitude on above ground biomass (AGB), particularly with regard to changing height-diameter allometry. To address this we investigate (1) the effects of altitude on height-diameter allometry, (2) how different height-diameter allometric models affect above ground biomass estimates; and (3) how other forest structural, taxonomic and environmental attributes affect above ground biomass using 30 permanent sample plots (1-ha; all trees ≥ 10 cm diameter measured) established between 1250 and 2600 m asl in Kahuzi Biega National Park in eastern Democratic Republic of Congo. Forest structure and species composition differed with increasing altitude, with four forest types identified. Different height-diameter allometric models performed better with the different forest types, as trees got smaller with increasing altitude. Above ground biomass ranged from 168 to 290 Mg ha-1, but there were no significant differences in AGB between forests types, as tree size decreased but stem density increased with increasing altitude. Forest structure had greater effects on above ground biomass than forest diversity. Soil attributes (K and acidity, pH) also significantly affected above ground biomass. Results show how forest structural, taxonomic and environmental attributes affect above ground biomass in African tropical montane forests. They particularly highlight that the use of regional height-diameter models introduces significant biases in above ground biomass estimates, and that different height-diameter models might be preferred for different forest types, and these should be considered in future studies.

Landscape‐level validation of allometric relationships for carbon stock estimation reveals bias driven by soil type

“…The observed spatial structure reinforces the dangers of applying allometric relationships validated in different locations, in a limited number of sampling locations or at different spatial scales than the area of interest (e.g., models N1 and N2 were validated from a single site in northeastern Gabon). Of the covariates applied to explain the variation in D:H model bias, soil type was by far the most informative, which is consistent with several previous studies linking soil parameters to AGB estimates (e.g., Cleveland et al 2011, Ledo et al 2016b, Imani et al 2017. The published models typically performed adequately on the two most common soil types (ferralitic and coastal sedimentary), presumably because previously published allometric equations were based on data from these habitat types.…”

“…, Imani et al. ). The published models typically performed adequately on the two most common soil types (ferralitic and coastal sedimentary), presumably because previously published allometric equations were based on data from these habitat types.…”

“… , b, Imani et al. , Kearsley et al. ), it is the first robust, systematic‐random, landscape scale assessment of the implications of D : H model selection.…”

“…Regression models are then fit to the field data to model the relationship between tree diameter and height, from which heights are predicted for all unmeasured trees, and then used in allometric equations to estimate AGB and carbon (e.g., Huang et al 2000, Chave et al 2014, Ngomanda et al 2014. Recently, several studies have compared locally derived models to generic models, finding that variation in tree D:H allometry causes local models to outperform regional models (Kearsley et al 2013, Rutishauser et al 2013, Thomas et al 2015, Ledo et al 2016a,b, Imani et al 2017, Sullivan et al 2018, but see Duque et al 2017, Kearsley et al 2017). However, the causes of variation in model fit and the landscapelevel implications of allometric model selection remain elusive.…”

Carbon Stock Estimation of Mangrove Vegetation Using Remote Sensing in Perancak Estuary, Jembrana District, Bali

“…Biomass in each part of the plant increases proportionately with the larger diameter of the tree. The high ability of trees to store carbon free from air depends on the diameter of trees (Imani et al 2017) and tree height (Fu and Wu 2011). The estimated of total carbon stock value in the Perancak Estuary is 22.18±11.76 tonC ha -1 and the amount of CO2 sequestration estimation is 81.41±43.18 tonC ha -1 .…”