Dynamic allometric scaling of tree biomass and size

Zhou, Xiaolu; Yang, Mingxia; Liu, Zelin; Li, Peng; Xie, Binggeng; Peng, Changhui

doi:10.1038/s41477-020-00815-8

Cited by 44 publications

(31 citation statements)

References 51 publications

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“…Remarkably, the theory based gMET models outperformed the statistical models of Chave et al 27 using their complied dataset. These results support MET itself, resolving the criticism pertaining to the lack of empirical support to MET scaling for large trees and tropical areas 11,[17][18][19]36 .…”

Section: Discussionsupporting

confidence: 61%

“…small petioles and/or large proportion of vessels within them). This explains the apparent lack of empirical fit observed for the original MET scaling in some cases only 11,[17][18][19]36 . The resulting implication of the gMET modifier in Eqs.…”

Section: Fig | Truncated Cone and Cylinder Approximation Of Tree Volumes This Visualizationmentioning

confidence: 98%

“…Consequently, the geometrically propagated 𝑎𝑔𝑏-𝑑 exponent of 8/3 predicted by MET 2 is consistently higher than adjusted models worldwide [23][24][25][26] . Scholars have therefore taken to using model forms other than power laws that empirically suit their datasets [27][28][29] , thereby preferring statistically optimised model forms, over theory-based models 17,[30][31] . The question is therefore raised as to whether a suitable mechanistic model other than a simple power relationship can be derived from MET, conciliating the current divide between theoretical and statistical plant allometry models.…”

Section: Main Textmentioning

confidence: 99%

“…Hydraulic and mechanical constraints are typically cited as key influences of plant allometry, with their interaction governing ℎ 33 . A trade-off between these two constraints is evident 34 , particularly for large trees 35,36 . Each constraint can be considered through the proportion of tissue with conductive (𝐶𝑇) and supportive (𝑆𝑇) functionality within a crosssection of the stem 37,38 (Fig.…”

Section: Main Textmentioning

confidence: 99%

See 3 more Smart Citations

The Generalized Plant Allometry that Advances Metabolic Ecology Theory

Sopp¹,

Valbuena²

2021

Preprint

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Plant allometry is key for determining the role of forests in global carbon cycles, through the calculation of tree biomass using proxy measurements such as tree diameters or heights. Metabolic ecology theory (MET) considers the general principles that underpin allometry, but MET scaling relationships have been challenged on their lack of fit to empirical data and global applicability. We postulated that MET scaling is applicable only for plant tissues combining conductive and supportive functionality (tracheids), but as plants evolved tissues of specialized conductive functionality (vessels) their allometry progressed into more complex relationships. According to this principle, we deducted generalized MET (gMET) relationships with mechanistically deducted coefficients. Our gMET models proved to have exceptional empirical support against global datasets, achieving unbiased predictions across biomes worldwide. These results prove gMET models to be a crucial improvement to MET-based allometry, providing a universally applicable theoretical framework for worldwide estimations of forest carbon.

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Section: Discussionsupporting

confidence: 61%

Section: Fig | Truncated Cone and Cylinder Approximation Of Tree Volumes This Visualizationmentioning

confidence: 98%

Section: Main Textmentioning

confidence: 99%

Section: Main Textmentioning

confidence: 99%

See 2 more Smart Citations

The Generalized Plant Allometry that Advances Metabolic Ecology Theory

Sopp¹,

Valbuena²

2021

Preprint

View full text Add to dashboard Cite

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“…Movement along linear trajectory in the space of logarithms of the values of some cellular properties means that along the trajectory any two such properties x i , x j are connected through a power law dependence x i = αx β j , α, β = const. Such dependencies are known as allometric in many fields of biology [18][19][20][21][22]. Some approaches in mathematical chemistry and theoretical biology, dealing with systems in stable non-equilibrium, exploit the linear relations between chemical potentials which can be expressed as logarithms of species concentrations [23,24].…”

Section: Introductionmentioning

confidence: 99%

Modeling Progression of Single Cell Populations Through the Cell Cycle as a Sequence of Switches

Zinovyev

Calzone

et al. 2021

Preprint

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Cell cycle is the most fundamental biological process underlying the existence and propagation of life in time and space. It has been an object for mathematical modeling for long, with several alternative mechanistic modeling principles suggested, describing in more or less details the known molecular mechanisms. Recently, cell cycle has been investigated at single cell level in snapshots of unsynchronized cell populations, exploiting the new methods for transcriptomic and proteomic molecular profiling. This raises a need for simplified semi-phenomenological cell cycle models, in order to formalize the processes underlying the cell cycle, at a higher abstracted level. Here we suggest a modeling framework, recapitulating the most important properties of the cell cycle as a limit trajectory of a dynamical process characterized by several internal states with switches between them. In the simplest form, this leads to a limit cycle trajectory, composed by linear segments in logarithmic coordinates describing some extensive (depending on system size) cell properties. We prove a theorem connecting the effective embedding dimensionality of the cell cycle trajectory with the number of its linear segments. We show how the developed formalism can be applied to model the available single cell datasets and simulate certain properties of the cell cycle trajectories.

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Laser scanning reveals potential underestimation of biomass carbon in temperate forest

Calders

Verbeeck

Burt³

et al. 2022

Ecol Sol and Evidence

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Quantifying climate mitigation benefits of biosphere protection or restoration requires accurate assessment of forest above‐ground biomass (AGB). This is usually estimated using tree size‐to‐mass allometric models calibrated with harvested biomass data. Using three‐dimensional laser measurements across the full range of tree size and shape in a typical UK temperate forest, we show that its AGB is 409.9 t ha−1, 1.77 times more than current allometric model estimates. This discrepancy arises partly from the bias towards small trees in allometric model calibration: 50% of AGB in this forest was in less than 7% of the largest trees (stem diameter > 53.1 cm), all larger than the trees used to calibrate the widely used allometric model. We present new empirical evidence that the fundamental assumption of tree size‐to‐mass scale‐invariance is not well‐justified for this kind of forest. This leads to substantial biases in current biomass estimates of broadleaf forests, not just in the UK, but elsewhere where the same or similar allometric models are applied, due to overdependence on non‐representative calibration data, and the departure of observed tree size‐to‐mass from simple size‐invariant relationships. We suggest that testing the underlying assumptions of allometric models more generally is an urgent priority as this has wider implications for climate mitigation through carbon sequestration. Forests currently act as a carbon sink in the UK. However, the anticipated increase in forest disturbances makes the trajectory and magnitude of this terrestrial carbon sink uncertain. We make recommendations for prioritizing measurements with better characterized uncertainty to address this issue.

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Dynamic allometric scaling of tree biomass and size

Cited by 44 publications

References 51 publications

The Generalized Plant Allometry that Advances Metabolic Ecology Theory

The Generalized Plant Allometry that Advances Metabolic Ecology Theory

Modeling Progression of Single Cell Populations Through the Cell Cycle as a Sequence of Switches

Laser scanning reveals potential underestimation of biomass carbon in temperate forest

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