From a tree to a stand in Finnish boreal forests: Biomass estimation and comparison of methods

Liu, Chunjiang

doi:10.14214/df.88

Cited by 4 publications

(3 citation statements)

References 78 publications

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“…These systems of equations for individual trees provide a sound basis for estimating total aboveground stand biomass in commercial logs and residues to complement the existing volume-based stand-level yield information that are most commonly reported and used in resource planning and decision support systems for forest management. When diameter and height measurements of individual trees are available from pre-harvest inventories, aboveground stand biomass in commercial logs and residues can potentially be obtained by scaling up estimates for individual trees, similar to the approach often adopted in forest biomass estimation (Snowdon 1992;Parresol 1999;Liu 2009;Vargas-Larreta et al 2017). This potential can only be fully realised if three additional calculations are made in the scaling up process.…”

Section: Introductionmentioning

confidence: 99%

Additive predictions of aboveground stand biomass in commercial logs and harvest residues for rotation age Pinus radiata plantations in New South Wales, Australia

Qiao

et al. 2021

J. For. Res.

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Two systems of additive equations were developed to predict aboveground stand level biomass in log products and harvest residue from routinely measured or predicted stand variables for Pinus radiata plantations in New South Wales, Australia. These plantations were managed under three thinning regimes or stand types before clear-felling at rotation age by cut-to-length harvesters to produce sawlogs and pulpwood. The residue material following a clear-fell operation mainly consisted of stumps, branches and treetops, short off-cut and waste sections due to stem deformity, defects, damage and breakage. One system of equations did not include dummy variables for stand types in the model specification and was intended for more general use in plantations where stand density management regimes were not the same as the stand types in our study. The other system that incorporated dummy variables was for stand type-specific applications. Both systems of equations were estimated using 61 plot-based estimates of biomass in commercial logs and residue components that were derived from systems of equations developed in situ for predicting the product and residue biomass of individual trees. To cater for all practical applications, two sets of parameters were estimated for each system of equations for predicting component and total aboveground stand biomass in fresh and dry weight respectively. The two sets of parameters for the system of equations without dummy variables were jointly estimated to improve statistical efficiency in parameter estimation. The predictive performances of the two systems of equations were benchmarked through a leave-one-plot-out cross validation procedure. They were generally superior to the performance of an alternative two-stage approach that combined an additive system for major components with an allocative system for sub-components. As using forest harvest residue biomass for bioenergy has increasingly become an integrated part of forestry, reliable estimates of product and residue biomass will assist harvest and management planning for clear-fell operations that integrate cut-to-length log production with residue harvesting.

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Section: Introductionmentioning

confidence: 99%

Additive predictions of aboveground stand biomass in commercial logs and harvest residues for rotation age Pinus radiata plantations in New South Wales, Australia

Qiao

et al. 2021

J. For. Res.

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“…Although process-based and hybrid models that couple conventional estimates of stand volume to a process-based model are sometimes used to derive biomass expansion factors (e.g. Beets et al, 1999;Richards and Evens, 2004;García-Quijano et al, 2007;Simioni et al, 2008), the most common method of forest biomass estimation has been to develop biomass equations and predict forest stand biomass as the sum of predicted biomass of individual trees, i.e., the scaling up approach (Snowdon, 1992;Parresol, 1999;Pattrício et al, 2005;BalboaMurias et al, 2006;Liu, 2009). Biomass equations for individual trees are available for P. radiata in several growing regions (e.g.…”

Section: Introductionmentioning

confidence: 99%

Additive prediction of aboveground biomass for Pinus radiata (D. Don) plantations

Long²,

Turner³

et al. 2010

Forest Ecology and Management

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“…The NPP of a stand, as well as the biomass increment as its main component, is a function of various stand characteristics, such as stand age, density, and site index as a sign of site productivity (Arp and Oja, 1997). Beside, individual tree biomass is affected by age, species and size of object tree and also by site conditions and management practices of the stand where the object tree is located (Liu, 2009). Therefore, stand age, density, and site index are included as independent variables in biomass increment models as individual tree or stand growth (Avery and Burkhart, 2002).…”

Section: Introductionmentioning

confidence: 99%

Allometric relationships between above-ground biomass increment and stand characteristics for crimean pine in Taşköprü, Turkey

Sağlam

Sakıcı

2023

CERNE

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Background: Biomass increment, one of the main components of net primary production (NPP) in forest ecosystems, plays an important role as well as total biomass in the global carbon cycle. In this study, the changes of increments of the above-ground total, stem and branch biomasses depending on stand characteristics (i.e., stand age, stand density, and site index) were investigated, and these relations were modeled for Crimean pine (Pinus nigra J.F.Arnold subsp. pallasiana (Lamb.) Holmboe) stands in Taşköprü region of Türkiye. Data were obtained from 109 sample trees within 74 sample plots representing the wide range of possible stand characteristics. Results:The equations developed for above-ground total, stem and branch biomass increments have quite high coefficients of determination (R 2 =0.784, 0.684 and 0.780, respectively), whereas low root mean square errors (RMSE=0.749, 0.692 and 0.116, respectively). The results indicated that the biomass increment estimates from the allometric equations developed were decreasing with stand age and increasing with stand density and site index and also stand density is the strongest stand characteristic on biomass increment. Conclusion:The estimates are also consistent with the growth patterns, so the equations can be used for biomass increment estimations and also for carbon storage and NPP projections for Crimean pine stands of the region.

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From a tree to a stand in Finnish boreal forests: Biomass estimation and comparison of methods

Cited by 4 publications

References 78 publications

Additive predictions of aboveground stand biomass in commercial logs and harvest residues for rotation age Pinus radiata plantations in New South Wales, Australia

Additive predictions of aboveground stand biomass in commercial logs and harvest residues for rotation age Pinus radiata plantations in New South Wales, Australia

Additive prediction of aboveground biomass for Pinus radiata (D. Don) plantations

Allometric relationships between above-ground biomass increment and stand characteristics for crimean pine in Taşköprü, Turkey

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