Allometric relationship and biomass expansion factors (BEFs) for above- and below-ground biomass prediction and stem volume estimation for ash (Fraxinus excelsior L.) and oak (Quercus robur L.)

Krejza, Jan; Světlík, Jan; Bednář, Pavel

doi:10.1007/s00468-017-1549-z

Cited by 30 publications

(22 citation statements)

References 42 publications

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“…The allometric relationship equations are usually based on a limited number of sampled trees (Zianis et al 2005). The number of sampled trees varies from several to thousands of individuals, but the most common number of sampled trees belongs to the interval from 6 to 40 for the sitespecific allometric relationship (Krejza et al 2017). A lower number of sampled trees can be used when the sampled trees are selected from tree diameter distribution in the forest stand (Roxburgh et al 2015).…”

Section: Inventory and Sample Treesmentioning

confidence: 99%

Biomass production of Betula pendula stands regenerated in the region of allochthonous Picea abies dieback

Martiník¹,

Knott²,

Krejza³

et al. 2018

Silva Fenn.

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The paper deals with production of above-ground biomass of silver birch ( Roth) stands in the Czech Republic. One-year biomass dynamics was studied within chronosequence of birch stands at the age of 4â5, 8â9, 17â18 and 22â23 years. With the exception of the youngest stand, which was established by seeding, all experimental birch stands were regenerated naturally after the allochthonous spruce stands. Above-ground biomass (AB) was calculated from plot inventory data and biomass equations were parameterized from destructive sampling of biomass component of sampled trees. Results reveal that the peak of the mean annual increment (MAI) of birch stands can be expected at the age from 15 to 20 years. Additionally, the stand age, the value of basal area (BA) should be considered as a predictor of stand productivity. If the value of BA varied from 25 to 35 m ha, the MAI of the birch stands reached the range from 5.0 to 6.5 t of dry biomass per ha y at the age ranging between 15 and 25 years. The stem/branch proportion increased with stand age, the stem relative proportion ranging from 75 to 90% of total above-ground biomass. According to the results of this study, birch stand biomass production and utilization is one of the approaches in terms of forest recovery management in large disturbed areas. Although, no silvicultural treatments were occurred in all analysed stands, the pre-commercial thinning method could increase stand productivity and stability as well.Betula pendulaABtotal2â1â1

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Section: Inventory and Sample Treesmentioning

confidence: 99%

Biomass production of Betula pendula stands regenerated in the region of allochthonous Picea abies dieback

Martiník¹,

Knott²,

Krejza³

et al. 2018

Silva Fenn.

Self Cite

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“…The predictive ability is expressed by the mean quadratic error of prediction (MEP) [[13], [14]], and model prediction error (MPE) [15]. MEP is defined by Eq.…”

Section: Analysesmentioning

confidence: 99%

“…MEP is defined by Eq. (2) [[13], [14]]. MEP=1n∑i=1nei2(1−Hii)2where e i 2 is the square of model residual and H ii is the diagonal element of the projection matrix H.…”

Section: Analysesmentioning

confidence: 99%

Least squares-based biomass conversion and expansion factors best estimate biomass than ratio-based ones: Statistical evidences based on tropical timber species

Magalhães

Mate

2018

MethodsX

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“…As it has been known, directly measuring the stem volume and weights of the tree components are undeniably the most precise approach for estimating individual tree biomass [19,20]. Thus, biomass is often estimated by utilizing the biomass allometric equations or merely by multiplying the stem volume approximations with biomass conversion and expansion factors (BCEF s ) or basic wood density [13,[21][22][23][24][25]. The BCEF s would be more favorable in case the tree volume is the only existing data; thus, it is possible to convert the stem volume data into the tree components' (i.e., root, stem, branch, and foliage) dry biomass [26,27].…”

Section: Introductionmentioning

confidence: 99%

Biomass and Volume Modeling along with Carbon Concentration Variations of Short-Rotation Poplar Plantations

Dong

Widagdo

Xie

et al. 2020

Forests

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Short-rotation forestry is of interest to provide biomass for bioenergy and act as a carbon sink to mitigate global warming. The Poplar tree (Populus × xiaohei) is a fast-growing and high-yielding tree species in Northeast China. In this study, a total of 128 Populus × xiaohei trees from the Songnen Plain, Heilongjiang Province, Northeastern China, were harvested. Several available independent variables, such as tree diameter at breast height (D), tree’s total height (H), crown width (CW), and crown length (CL), were differently combined to develop three additive biomass model systems and eight stem volume models for Populus × xiaohei tree. Variance explained within the three additive biomass model systems ranged from 83% to 98%, which was lowest for the foliage models, and highest for the stem biomass models. Similar findings were found in the stem volume models, in which the models explained more than 94% of the variance. The additional predictors, such as H, CL, or CW, evidently enhanced the model fitting and performance for the total and components biomass along with the stem volume models. Furthermore, the biomass conversion and expansion factors (BCEFs) of the root (118.2 kg/m3), stem (380.2 kg/m3), branch (90.7 kg/m3), and foliage (31.2 kg/m3) were also calculated. The carbon concentrations of Populus × xiaohei in root, stem, branch, and foliage components were 45.98%, 47.74%, 48.32%, and 48.46%, respectively. Overall, the newly established models in this study provided complete and comprehensive tools for quantifying the biomass and stem volume of Populus × xiaohei, which might be essential to be specifically utilized in the Chinese National Forest Inventory.

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Allometric relationship and biomass expansion factors (BEFs) for above- and below-ground biomass prediction and stem volume estimation for ash (Fraxinus excelsior L.) and oak (Quercus robur L.)

Cited by 30 publications

References 42 publications

Biomass production of <i>Betula pendula</i> stands regenerated in the region of allochthonous <i>Picea abies</i> dieback

Biomass production of <i>Betula pendula</i> stands regenerated in the region of allochthonous <i>Picea abies</i> dieback

Least squares-based biomass conversion and expansion factors best estimate biomass than ratio-based ones: Statistical evidences based on tropical timber species

Biomass and Volume Modeling along with Carbon Concentration Variations of Short-Rotation Poplar Plantations

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