A review of the challenges and opportunities in estimating above ground forest biomass using tree-level models

Self Cite

There are few allometric equations available for dipterocarp forests, despite the fact that this forest type covers extensive areas in tropical Southeast Asia. This study aims to develop a set of equations to estimate tree aboveground biomass (AGB) in dipterocarp forests in Vietnam and to validate and compare their predictive performance with allometric equations used for dipterocarps in Indonesia and pantropical areas. Diameter at breast height (DBH), total tree height (H), and wood density (WD) were used as input variables of the nonlinear weighted least square models. Akaike information criterion (AIC) and residual plots were used to select the best models; while percent bias, root mean square percentage error, and mean absolute percent error were used to compare their performance to published models. For mixed-species, the best equation was AGB = 0.06203 × DBH 2.26430 × H 0.51415 × WD 0.79456 . When applied to a random independent validation dataset, the predicted values from the generic equations and the dipterocarp equations in Indonesia overestimated the AGB for different sites, indicating the need for region-specific equations. At the genus level, the selected equations were AGB = 0.03713 × DBH 2.73813 and AGB = 0.07483 × DBH 2.54496 for two genera, Dipterocarpus and Shorea, respectively, in Vietnam.Compared to the mixed-species equations, the genus-specific equations improved the accuracy of the AGB estimates. Additionally, the genus-specific equations showed no significant differences in predictive performance in different regions (e.g., Indonesia, Vietnam) of Southeast Asia.

Section: Equations At the Mixed-species Level In The Dipterocarp Foresupporting

confidence: 77%

Allometric Equations for Estimating Tree Aboveground Biomass in Tropical Dipterocarp Forests of Vietnam

Huy

Poudel

Kralicek

et al. 2016

Self Cite

“…For P. massoniana both approaches resulted in a high CCC (Raumonen et al [49] = 0.99 and SimpleTree = 0.98), the Raumonen et al [49] results are slightly better. We consider the TLS reconstructed results for both approaches as highly accurate and the minor prediction errors for this species are already in the range of ground truth errors which have to be expected [94].…”

Section: Discussionmentioning

confidence: 99%

SimpleTree —An Efficient Open Source Tool to Build Tree Models from TLS Clouds

Hackenberg

Spiecker

Calders

et al. 2015

280

260

An open source tool named SimpleTree, capable of modelling highly accurate cylindrical tree models from terrestrial laser scan point clouds, is presented and evaluated. All important functionalities, accessible in the software via buttons and dialogues, are described including the explanation of all necessary input parameters. The method is validated utilizing 101 point clouds of six different tree species, in the main evergreen and coniferous trees. All scanned trees have been destructively harvested to get accurate estimates of above ground biomass with which we assess the accuracy of the SimpleTree-reconstructed cylinder models. The trees were grouped into four data sets and for each one a Concordance Correlation Coefficient of at least 0. 92 (0.92, 0.97, 0.92, 0.94) and an total relative error at most ∼ 8 % (2.42%, 3.59%, -4.59%, 8.27%) was achieved in the comparison of the model results to the ground truth data. A global statistical improvement of derived cylinder radii is presented as well as an efficient optimization approach to Forests 2015, 6 4246 automatically improve user given input parameters. An additional check of the SimpleTree results is presented via comparison to the results of trees reconstructed using an alternative, published method.

“…Even so, regarding the species-specific differences in DBH-height allometry, tree height is an important factor for biomass estimation [24,56]. The inclusion of height as an additional variable helps accounting for variation in AGB among trees with the same value of DBH [24], thus reducing the estimate errors [11].…”

Section: Predictors For Multispecies Agb Equationsmentioning

confidence: 99%

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

Mensah

Veldtman

Toit

et al. 2016

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.