Allometric patterns in Acer platanoides (Aceraceae) branches

Dahle, Gregory A.; Grabosky, Jason

doi:10.1007/s00468-009-0401-5

Cited by 27 publications

(28 citation statements)

References 22 publications

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“…In this study the results indicated that the large branches of crape myrtle did not necessary have more branches at next lower orders. But for another species, Norway maple, a significant quadratic regression existed between the number of 2nd order and the 1st order branch length (Dahle & Grabosky, 2010). This indicates that when primary branch length slows, investment of photosynthetic product in elongation would likely turn towards the lateral branches.…”

Section: Discussionmentioning

confidence: 99%

“…These numbers may be unique to crape myrtle, because other tree species could reach a slenderness around 260 (Bertram, 1989). Dahle & Grabosky (2010) found that slenderness of Acer platanoides L. (Norway maple) peaked near 300 and appeared to shift at the branch length of 300 cm. These thresholds might mean that branches approach potential instability when they were transitioning from a primary role of flexible branch to a stiffer structural branch.…”

Section: Discussionmentioning

confidence: 99%

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Allometric Dynamics in Branch Growth of Crape Myrtle

Chen¹

2017

JPS

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Tree branches provide multiple functions in tree growth. It is necessary to study the allometric patterns of branches in order to understand some quantitative perspectives in tree growth. In this study, branches of seven crape myrtle trees (Lagerstroemia indica) were studied to examine allometric relationships in different times. The results indicated that the total basal area of branches at one order was far more than it at the next lower order (branches far from trunks). The scaling exponents of frequency distribution in both branch length and diameter decreased from above 1.0 in May to 0.1 in November as branches grew. The entropy of branch length and diameter both decreased at the beginning and then increased for all trees during the growing season. The observed entropy was always less than the maximum entropy. The average slenderness of branches was close to 20 for all trees. There were higher fluctuations in the slenderness within small or short branches (diameter less than 10 mm or length less than 100 cm). The scaling exponents between branch radius and length were concentrated at 1.0 for most trees. The correlation between the branch diameters of 1 st order and the number of branches at 2 nd order was not significant. The general trend and deviations in allometric relationships may help to understand the complexity in tree branch development.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Allometric Dynamics in Branch Growth of Crape Myrtle

Chen¹

2017

JPS

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“…1 The sketch map of tree and branch variables. HT tree height; CL the length of crown; HCB the height of crown base; DINC absolute depth of branch into the crown; CR the crown radius; CW the crown width; BA the branch angle; BCL the branch chord length; BAL the branch arc length; BL branch length; RDINC the relative depth of branch into crown, which can be calculated as: RDINC = DINC/CL Trees 2001; Calama and Montero 2005;Yang and Huang 2011;Corral-Rivas et al 2014), as well as branch attributes models (e.g., Meredieu et al 1998;Hein et al 2008;Dahle and Grabosky 2010). However, most of the NLME models in forestry were often simplified or assumed the withinsubject heterogeneous and autocorrelation to be negligible in the presence of random subject effects (e.g., Garber and Maguire 2003;Corral-Rivas et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Nonlinear mixed-effects branch diameter and length models for natural Dahurian larch (Larix gmelini) forest in northeast China

Dong

Liu

Bettinger

2016

Trees

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Key message We developed the generalized branch diameter and length models using the multi-level nonlinear mixed-effects techniques for the natural Dahurian larch (Larix gmelini) forest in northeast China. Abstract Dahurian larch (Larix gmelini) is the most commercially cultivated timber species in northeastern China due to its ecological prevalence and its superior wood attribute. However, its timber quality was largely driven by the crown architecture, i.e., the number, size and distribution of branches. The majority of branch-level models in the literature are focused on planted forests, which have substantially different crown architecture than that grown in natural mixed forests. Therefore, the goal of this investigation was to develop branch diameter and length models for Dahurian larch that are grown in natural mixed forests. A multi-level nonlinear mixed-effects model technique, including the fixed-effects, random-effects, variance functions and correlation structures, was employed to develop the branch growth models. The results suggested that the cumulative branch diameter and length were both increased with the increases of branch depth into the crown. Diameter at breast height (DBH) had significant positive influences on the branch size; however, tree height (HT) produced negative influences on the branch size, i.e., larger DBH and smaller HT could lead to larger branch size. Model fitting and validation results confirmed that we should avoid developing over-complex models from the perspective of application. As for the branch diameter and length models in our study, addressing the stand and tree level effects as random component were quite reliable and accurate for predicting the branch growth process of Dahurian larch in northeastern China.

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“…There is increasing evidence challenging the assumption that intraspecific variability is much lower than interspecific variability [20,21]. Moreover, the variability of plant allometric equations (scale laws) for relationships such as metabolic rate-biomass [22], tree height-diameter [23][24][25][26], tree productivity-biomass [27], biomass-diameter [28,29], branch radius-branch length [24,30], and foliage and woody mass in crowns [31] has been extensively examined.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Variability of Internode Allometry within and between Trees for Pinus tabulaeformis Carr. Using a Multilevel Nonlinear Mixed-Effect Model

Jun

Lei

Wang

et al. 2014

Forests

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Allometric models of internodes are an important component of Functional-Structural Plant Models (FSPMs), which represent the shape of internodes in tree architecture and help our understanding of resource allocation in organisms. Constant allometry is always assumed in these models. In this paper, multilevel nonlinear mixed-effect models were used to characterize the variability of internode allometry, describing the relationship between the last internode length and biomass of Pinus tabulaeformis Carr. trees within the GreenLab framework. We demonstrated that there is significant variability in allometric relationships at the tree and different-order branch levels, and the variability decreases among levels from trees to first-order branches and, subsequently, to second-order branches. The variability was partially explained by the random effects of site characteristics, stand age, density, and topological position of the internode. Tree-and branch-level-specific allometric models are recommended because they produce unbiased and accurate internode length estimates. The model and method developed in this study are useful for understanding and describing the structure and functioning of trees. OPEN ACCESSForests 2014, 5 2826 Keywords: internode allometry; mixed-effect models; Pinus tabulaeformis Carr.; variance of random effects

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Allometric patterns in Acer platanoides (Aceraceae) branches

Cited by 27 publications

References 22 publications

Allometric Dynamics in Branch Growth of Crape Myrtle

Allometric Dynamics in Branch Growth of Crape Myrtle

Nonlinear mixed-effects branch diameter and length models for natural Dahurian larch (Larix gmelini) forest in northeast China

Quantifying the Variability of Internode Allometry within and between Trees for Pinus tabulaeformis Carr. Using a Multilevel Nonlinear Mixed-Effect Model

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