Site-effects on biomass allometric models for early growth plantations of Norway spruce (Picea abies (L.) Karst.)

Dutcă, Ioan; Mather, Richard C.; Blujdea, Viorel; Ioraş, Florin; Olari, Mănăilă; Abrudan, I. V.

doi:10.1016/j.biombioe.2018.05.013

Cited by 33 publications

(25 citation statements)

References 57 publications

(74 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…There has considerable divergence in the previous research on the effect of adding H to the biomass models to predict tree biomass: while some studies reported no improvement-or even deterioration [12,22,27]-other studies reported improvement [32,36]. Many workers suggest that including height in models will offset the site effect [37,38], but Dutcă et al reported that height inclusion reduces model site specificity only for stem biomass and increases site specificity for total trees and total aboveground biomass [39]. Our results show that the use of DBH as a predictor variable provided a highly significant fit (p < 0.001), which indicated that DBH was a strong predictor of tree biomass.…”

Section: Effect Of Adding Tree Height On Biomass Estimationmentioning

confidence: 99%

“…When highly correlated, DBH and H will inevitably exceed or repeat a certain proportion of biomass variation. Dutcă (2018) pointed out that in the biomass allometric models, collinearity increases the standard error of regression coefficients, extending the range of confidence intervals, and increases the uncertainty of model [39]. Furthermore, collinearity makes the regression coefficients sensitive to small changes in the dataset, such that the changes alter the coefficients and profoundly affect biomass prediction.…”

Section: Effect Of Adding Tree Height On Biomass Estimationmentioning

confidence: 99%

See 1 more Smart Citation

Site-Specific Allometric Models for Prediction of Above-and Belowground Biomass of Subtropical Forests in Guangzhou, Southern China

Halin

Zhou

et al. 2019

Forests

View full text Add to dashboard Cite

Tree allometric models that are used to predict the biomass of individual tree are critical to forest carbon accounting and ecosystem service modeling. To enhance the accuracy of such predictions, the development of site-specific, rather than generalized, allometric models is advised whenever possible. Subtropical forests are important carbon sinks and have a huge potential for mitigating climate change. However, few biomass models compared to the diversity of forest ecosystems are currently available for the subtropical forests of China. This study developed site-specific allometric models to estimate the aboveground and the belowground biomass for south subtropical humid forest in Guangzhou, Southern China. Destructive methods were used to measure the aboveground biomass with a sample of 144 trees from 26 species, and the belowground biomass was measured with a subsample of 116 of them. Linear regression with logarithmic transformation was used to model biomass according to dendrometric parameters. The mixed-species regressions with diameter at breast height (DBH) as a single predictor were able to adequately estimate aboveground, belowground and total biomass. The coefficients of determination (R2) were 0.955, 0.914 and 0.954, respectively, and the mean prediction errors were −1.96, −5.84 and 2.26%, respectively. Adding tree height (H) compounded with DBH as one variable (DBH2H) did not improve model performance. Using H as a second variable in the equation can improve the model fitness in estimation of belowground biomass, but there are collinearity effects, resulting in an increased standard error of regression coefficients. Therefore, it is not recommended to add H in the allometric models. Adding wood density (WD) compounded with DBH as one variable (DBH2WD) slightly improved model fitness for prediction of belowground biomass, but there was no positive effect on the prediction of aboveground and total biomass. Using WD as a second variable in the equation, the best-fitting allometric relationship for biomass estimation of the aboveground, belowground, and total biomass was given, indicating that WD is a crucial factor in biomass models of subtropical forest. Root-shoot ratio of subtropical forest in this study varies with species and tree size, and it is not suitable to apply it to estimate belowground biomass. These findings are of great significance for accurately measuring regional forest carbon sinks, and having reference value for forest management.

show abstract

Section: Effect Of Adding Tree Height On Biomass Estimationmentioning

confidence: 99%

Section: Effect Of Adding Tree Height On Biomass Estimationmentioning

confidence: 99%

Site-Specific Allometric Models for Prediction of Above-and Belowground Biomass of Subtropical Forests in Guangzhou, Southern China

Halin

Zhou

et al. 2019

Forests

View full text Add to dashboard Cite

show abstract

“…Although D and H are always correlated to some degree, their relationship varies greatly (Feldpausch et al, 2010), being influenced by genotype, competition and environmental conditions (Egbäck et al, 2015;Hulshof et al, 2015;Dutcă et al, 2018b). As a result, including H in allometric models has been shown to improve biomass prediction accuracy (Chave et al, 2005(Chave et al, , 2014Feldpausch et al, 2012;Fayolle et al, 2013;Rutishauser et al, 2013;Dutcă et al, 2018a). Because D and H are correlated, the unique effect of each predictor (i.e., the main effect) is based on its unique information (i.e., disregarding shared information).…”

Section: Introductionmentioning

confidence: 99%

A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models

Dutcă

McRoberts

Næsset

et al. 2019

Forestry: An International Journal of Forest Research

Self Cite

View full text Add to dashboard Cite

Tree diameter at breast height (D) and tree height (H) are often used as predictors of individual tree biomass. Because D and H are correlated, the combined variable D2H is frequently used in regression models instead of two separate independent variables, to avoid collinearity related issues. The justification for D2H is that aboveground biomass is proportional to the volume of a cylinder of diameter, D, and height, H. However, the D2H predictor constrains the model to produce parameter estimates for D and H that have a fixed ratio, in this case, 2.0. In this paper we investigate the degree to which the D2H predictor reduces prediction accuracy relative to D and H separately and propose a practical measure, Q-ratio, to guide the decision as to whether D and H should or should not be combined into D2H. Using five training biomass datasets and two fitting approaches, weighted nonlinear regression and linear regression following logarithmic transformations, we showed that the D2H predictor becomes less efficient in predicting aboveground biomass as the Q-ratio deviates from 2.0. Because of the model constraint, the D2H-based model performed less well than the separate variable model by as much as 12 per cent with regard to mean absolute percentage residual and as much as 18 per cent with regard to sum of squares of log accuracy ratios. For the analysed datasets, we observed a wide variation in Q-ratios, ranging from 2.5 to 5.1, and a large decrease in efficiency for the combined variable model. Therefore, we recommend using the Q-ratio as a measure to guide the decision as to whether D and H may be combined further into D2H without the adverse effects of loss in biomass prediction accuracy.

show abstract

“…Compared with the differences in leaf trait among the major floristic regions, the results suggest that the allometric scaling of leaf traits varied among these global floras (Heberling & Fridley, ). However, previous research on plant adaptation strategies has mostly focused on the adult stage and has neglected to note that seedlings are more sensitive to the environment and that the growth of seedlings determines the strategy of subsequent stages (An & Shangguan, ; Dutcă et al, ; Ishida, Yazaki, & Hoe, ). Meanwhile, allometric growth patterns in different life stages of a species can accurately reflect specific changes in leaf N:P stoichiometry (Bloomfield et al, ).…”

Section: Introductionmentioning

confidence: 99%

N‐P utilization ofAcer monoleaves at different life history stages across altitudinal gradients

Song

Liu

et al. 2019

Ecology and Evolution

View full text Add to dashboard Cite

The relationship between plants and the environment is a core area of research in ecology. Owing to differences in plant sensitivity to the environment at different life history stages, the adaptive strategies of plants are a cumulative result of both their life history and environment. Previous research on plant adaptation strategies has focused on adult plants, neglecting saplings or seedlings, which are more sensitive to the environment and largely affect the growth strategy of subsequent life stages. We compared leaf N and P stoichiometric traits of the seedlings, saplings, and adult trees of Acer mono Maxim and different altitudes and found significant linear trends for both life history stages and altitude. Leaf N and P content by unit mass were greatly affected by environmental change, and the leaf N and P content by unit area varied greatly by life history stage. Acer mono leaf N‐P utilization showed a significant allometric growth trend in all life history stages and at low altitudes. The adult stage had higher N‐use efficiency than the seedling stage and exhibited an isometric growth trend at high altitudes. The N‐P utilization strategies of A. mono leaves are affected by changing environmental conditions, but their response is further dependent upon the life history stage of the plant. Thus, this study provides novel insights into the nutrient use strategies of A. mono and how they respond to the environmental temperature, soil moisture content along altitude and how these changes differ among different life history stages, which further provide the scientific basis for the study of plant nutrient utilization strategy on regional scale.

show abstract

Site-effects on biomass allometric models for early growth plantations of Norway spruce (Picea abies (L.) Karst.)

Cited by 33 publications

References 57 publications

Site-Specific Allometric Models for Prediction of Above-and Belowground Biomass of Subtropical Forests in Guangzhou, Southern China

Site-Specific Allometric Models for Prediction of Above-and Belowground Biomass of Subtropical Forests in Guangzhou, Southern China

A practical measure for determining if diameter (D) and height (H) should be combined into D2H in allometric biomass models

N‐P utilization ofAcer monoleaves at different life history stages across altitudinal gradients

Contact Info

Product

Resources

About