Aboveground Biomass and Carbon in a South African Mistbelt Forest and the Relationships with Tree Species Diversity and Forest Structures

Abstract

Biomass and carbon stocks are key information criteria to understand the role of forests in regulating global climate. However, for a bio-rich continent like Africa, ground-based measurements for accurate estimation of carbon are scarce, and the variables affecting the forest carbon are not well understood. Here, we present the first biomass study conducted in South Africa Mistbelt forests. Using data from a non-destructive sampling of 59 trees of four species, we (1) evaluated the accuracy of multispecies aboveground biomass (AGB) models, using predictors such as diameter at breast height (DBH), total height (H) and wood density; (2) estimated the amount of biomass and carbon stored in the aboveground compartment of Mistbelt forests and (3) explored the variation of aboveground carbon (AGC) in relation to tree species diversity and structural variables. We found significant effects of species on wood density and AGB. Among the candidate models, the model that incorporated DBH and H as a compound variable (DBH 2ˆH ) was the best fitting. AGB and AGC values were highly variable across all plots, with average values of 358.1 Mg¨ha´1 and 179.0 Mg¨C¨ha´1, respectively. Few species contributed 80% of AGC stock, probably as a result of selection effect. Stand basal area, basal area of the ten most important species and basal area of the largest trees were the most influencing variables. Tree species richness was also positively correlated with AGC, but the basal area of smaller trees was not. These results enable insights into the role of biodiversity in maintaining carbon storage and the possibilities for sustainable strategies for timber harvesting without risk of significant biomass decline.

Tree species diversity promotes aboveground carbon storage through functional diversity and functional dominance

“…In tropical natural forests, where several species cohabit and fulfill the major ecosystem functions, it is common to observe the abundance and dominance of highly productive tree species, thus increasing the chances that diversity–carbon relationships are mediated by selection effects. This was partly confirmed by our previous observations in South African mistbelt forests, especially the greater influence of the most dominant species on biomass stocks (Mensah, Veldtman, du Toit, Glèlè Kakaï, & Seifert, ). More and more, research tends to show how functional diversity and/or functional dominance play a major role in ecosystem functioning (Baraloto et al., ; Clark, Flynn, Butterfield, & Reich, ; Ruiz‐Jaen & Potvin, ; Song et al., ).…”

“…This fact is even often used to support the reason why mixed species communities of plantations are far more productive than monospecific stands. But it might also be well possible that increasing species richness increases the chances of inclusion of highly productive and naturally favored dominant species (Ruiz‐Benito et al., ), as shown by our previous results on the influence of most dominant species on carbon stocks in mistbelt forests (Mensah, Veldtman, du Toit, Glèlè Kakaï, & Seifert, ).…”

“…We used the multispecies allometric biomass equation developed for the northern mistbelt forests (Mensah, Veldtman, du Toit, Glèlè Kakaï, & Seifert, ) to calculate the aboveground biomass (AGB) for all individual trees present in the plots. The allometric equation provided more accurate estimated biomass values, compared with the existing pantropical biomass equation (Chave et al., ; Mensah, Veldtman, & Seifert, ).…”

Functions of farmers’ preferred tree species and their potential carbon stocks in southern Burkina Faso: implications for biocarbon initiatives

“…The AGB (Mg ha −1 ) was further upscaled to the study site level (10,000 ha) by applying the surface expansion factor (100). For carbon stock determination, the AGB (Mg ha− 1 ) was converted by applying a carbon conversion factor of 0.5 [43-44].…”

Prediction of stem diameter and biomass at individual tree crown level with advanced machine learning techniques

“…In forest inventories in general, DBH and height (H) are measured and registered in the field in order to predict the AGB using allometric models. AGB is then converted to carbon density for each field-reference tree (Chave et al 2014, Mensah et al 2016, Zhang et al 2016, Peng et al 2017. With ALS, it became possible to measure the heights of trees in large forests in a short time, which makes it more practical compared to filed-measured methods.…”