The Variation Driven by Differences between Species and between Sites in Allometric Biomass Models

In mountainous or hilly areas, the slope aspect affects the amount of solar radiation, with direct consequences on species distribution and tree growth. However, little is known on how the tree shape and volume allometry may be affected by contrasting environmental conditions driven by the slope aspect. This study aims to investigate whether the slope aspect affects the aboveground tree shape and volume allometry of European beech (Fagus sylvatica L.) trees. We used the data of scanned trees from two plots located on south- and respectively north-facing slopes and, additionally, an inventory dataset containing measurements of diameter at breast height (D) and tree height (H). To investigate the differences in tree shape, we used analysis of covariance. However, to assess the differences in volume allometry, we first predicted the volume of each individual tree within the inventory dataset using either the south- or the north-facing slope volume model, and then performed a paired t-test on the plot estimates based on the two volume models. Since the uncertainty originating from allometric volume model predictions was likely to affect the results of the paired t-test, we performed a Monte-Carlo simulation to assess the rate of null hypothesis acceptance with the paired t-test. The results showed that trees growing on the north-facing slope were significantly thinner (p < 0.001), with a significantly longer branching system (p < 0.001) compared to those on the south-facing slope. Correspondingly, the volume estimates per unit of forest area based on the south- vs. north-facing slope allometric volume models were significantly different (p < 0.001). The estimates of total aboveground volume per unit of forest area based on the north-facing slope allometric models were significantly larger compared to those based on the south-facing slope volume models, a difference driven by the significantly larger branch and stem volume for the north-facing slope. These differences in estimates per unit of forest area were larger when based on allometric models that only used D as a predictor of aboveground tree volume. The rates of null hypothesis acceptance within the paired t-test were generally low. For total aboveground volume estimated by D and H, the acceptance rate was 1.79%. Nevertheless, only using D to predict tree volume, the rates of null hypothesis acceptance were lower (i.e., 0.1%), suggesting that addition of H as a predictor of tree volume partly explains the differences caused by the slope aspect on volume allometry, but not enough to offset the differences entirely. In conclusion, slope aspect has significantly affected the tree shape and volume allometry of European beech trees.

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Does Slope Aspect Affect the Aboveground Tree Shape and Volume Allometry of European Beech (Fagus sylvatica L.) Trees?

Dutcă

Cernat

Stăncioiu

et al. 2022

“…The addition of H as a predictor variable in allometric biomass models was shown to improve the biomass prediction [11,12] and reduce the dependence of allometric models on sites [13]. However, the dependence on tree species was only marginally reduced when including H [13], although 'wood density' as an additional predictor of D and H was shown to significantly reduce dependence on species [14]. Correlation of D and H, although strong, is never perfect; the relationship between D and H is affected by genotype, age, tree competition, and environmental conditions [15,16].…”

Section: Introductionmentioning

confidence: 99%

The Effects of Combining the Variables in Allometric Biomass Models on Biomass Estimates over Large Forest Areas: A European Beech Case Study

Osewe

Dutcă

2021

Effective initiatives for forest-based mitigation of climate change rely on continuous efforts to improve the estimation of forest biomass. Allometric biomass models, which are nonlinear models that predict aboveground biomass (AGB) as a function of diameter at breast height (D) and tree height (H), are typically used in forest biomass estimations. A combined variable D2H may be used instead of two separate predictors. The Q-ratio (i.e., the ratio between the parameter estimates of D and parameter estimates of H, in a separate variable model) was proposed recently as a measure to guide the decision on whether D and H can be safely combined into D2H, being shown that the two model forms are similar when Q = 2.0. Here, using five European beech (Fagus sylvatica L.) biomass datasets (of different Q-ratios ranging from 1.50 to 5.05) and an inventory dataset for the same species, we investigated the effects of combining the variables in allometric models on biomass estimation over large forest areas. The results showed that using a combined variable model instead of a separate variable model to predict biomass of European beech trees resulted in overestimation of mean AGB per hectare for Q > 2.0 (i.e., by 6.3% for Q = 5.05), underestimation for Q < 2.0 (i.e., by –3.9% for Q = 1.50), whereas for Q = 2.03, the differences were minimum (0.1%). The standard errors of mean AGB per hectare were similar for Q = 2.03 (differences up to 0.2%), and the differences increased with the Q-ratio, by up 10.2% for Q = 5.05. Therefore, we demonstrated for European beech that combining the variables in allometric biomass models when Q ≠ 2.0 resulted in biased estimates of mean AGB per hectare and of uncertainty.

“…In this context, the development of prediction models capable of precise biomass estimations is required. Allometric biomass models are regression models that use tree dimensions, such as diameter at breast height and/or tree height to predict aboveground biomass [4]. To estimate forest biomass, there is significant literature on the development and use of allometric models [5].…”

Section: Introductionmentioning

confidence: 99%

Allometric Models for Estimating Aboveground Biomass in Short Rotation Crops of Acacia Species in Two Different Sites in Chile

Cabrera-Ariza

Valdés

Gilabert

et al. 2021

We evaluated the ability of different allometric models to estimate the biomass production of short-rotation woody crops of Acacia dealbata, A. mearnsii and A. melanoxylon. Models considered the adjustment and validation of biomass functions and biological restrictions, such as the use of additive components of the biomass (stem, branches, and leaves). Adjustments of linear and nonlinear models of the three acacia species—established in two locations and of three densities in southern Chile—were utilized. Systems of equations were adjusted to guarantee the addition of the biomass components and the trees’ total biomass. The selection of models was performed based on their goodness of fit and predictive quality. Methods that accounted for the correlation between biomass components granted an additively consistent equations system with efficient estimates and reliable prediction intervals.