Analysis of wood density profiles of tree stems: incorporating vertical variations to optimize wood sampling strategies for density and biomass estimations

To better understand the phenomenon of growth "stagnation" in high-density lodgepole pine (Pinuscontorta Dougl. ex Loud.), leaf area and its relationship with sapwood cross-sectional area were examined on both an individual tree and stand basis. Leaf areas of individual trees in a 22-year-old stand varied from 30.8 m2 (dominants in stands of low stocking) to 0.05 m2 (suppressed trees in stands of high stocking). Leaf area indices ranged from 13.4 to 2.3 m2 m−2 between low and high stocking levels, respectively. Over the same stocking range, the ratio of leaf area to sapwood cross-sectional area was reduced from 0.3 to 0.15 m2 cm−2. Intraring wood density profiles showed that ovendry density increased from 0.52 to 0.7 g cm−3 and the proportion of early wood decreased over a stocking level range of 6500–109 000 trees/ha. A reduction in hydraulic conductivity in the stems of stagnant trees, suggested by the greater proportion of narrow-diameter tracheids present, may lead to a greater resistance to water transport within the boles of trees from stagnant stands, leading to low leaf areas.

Download Full-text

Integrated system of equations for estimating stem volume, density, and biomass for Australian redcedar (Toona ciliata) plantations

Canadian Journal of Forest Research ◽

10.1139/cjfr-2016-0135 ◽

2017 ◽

Vol 47 (5) ◽

pp. 681-689 ◽

Cited By ~ 1

Author(s):

Natalino Calegario ◽

Timothy G. Gregoire ◽

Tatiane Antunes da Silva ◽

Mario Tomazello Filho ◽

Joyce A. Alves

Keyword(s):

Wood Density ◽

Nonlinear Function ◽

Volume Density ◽

Density Variation ◽

Integrated System ◽

Stem Volume ◽

System Of Equations ◽

Stem Wood ◽

Toona Ciliata ◽

Density And Biomass

A system of equations is proposed to assess the stem wood density variation of Toona ciliata M. Roem. growing in Brazilian plantations. As a taper function, a third-degree polynomial was fitted and the stem radius squared (r2), the dependent variable, was estimated as a function of diameter at breast height (dbh), total height (ht), and radius (r) at height (h). A nonlinear function was fitted to estimate wood density variation, having as the independent variable the ratio of r to h. The stem mass was estimated by integrating the product of stem volume and wood density. Stem measurements from a group of 72 trees of T. ciliata were used to fit the taper equation. A group of six trees was selected and a wood density database was created using X-ray technology. Both the taper and the nonlinear functions performed well in estimating the radius and the wood density. The within-tree wood density systematically increased from pith to bark and from the base to the top of the tree. With the density varying from base to top, the estimated mass of the stem, compared with the mass estimated using wood density value at dbh, had a bias of 4.2%. When the density variations from base to top and from pith to bark of the tree were considered, the estimated mass had a bias of 1.5%.

Download Full-text

Evaluation of intra-ring wood density profiles using NIRS: comparison with the X-ray method

Annals of Forest Science ◽

10.1007/s13595-016-0597-7 ◽

2017 ◽

Vol 74 (1) ◽

Cited By ~ 2

Author(s):

Ricardo Baettig ◽

Jorge Cornejo ◽

Jorge Guajardo

Keyword(s):

Wood Density ◽

Ray Method ◽

Density Profiles ◽

X Ray

Download Full-text

Wood Density Profiles and Their Corresponding Tissue Fractions in Tropical Angiosperm Trees

Forests ◽

10.3390/f9120763 ◽

2018 ◽

Vol 9 (12) ◽

pp. 763 ◽

Cited By ~ 8

Author(s):

Tom De Mil ◽

Yegor Tarelkin ◽

Stephan Hahn ◽

Wannes Hubau ◽

Victor Deklerck ◽

...

Keyword(s):

Wood Density ◽

Density Profile ◽

Growth Ring ◽

Random Effect ◽

Average Density ◽

Congo Basin ◽

Life Strategy ◽

Density Profiles ◽

Automated Method ◽

Profile Variation

Wood density profiles reveal a tree’s life strategy and growth. Density profiles are, however, rarely defined in terms of tissue fractions for wood of tropical angiosperm trees. Here, we aim at linking these fractions to corresponding density profiles of tropical trees from the Congo Basin. Cores of 8 tree species were scanned with X-ray Computed Tomography to calculate density profiles. Then, cores were sanded and the outermost 3 cm were used to semi-automatically measure vessel lumen, parenchyma and fibre fractions using the Weka segmentation tool in ImageJ. Fibre wall and lumen widths were measured using a newly developed semi-automated method. An assessment of density variation in function of growth ring boundary detection is done. A mixed regression model estimated the relative contribution of each trait to the density, with a species effect on slope and intercept of the regression. Position-dependent correlations were made between the fractions and the corresponding wood density profile. On average, density profile variation mostly reflects variations in fibre lumen and wall fractions, but these are species- and position-dependent: on some positions, parenchyma and vessels have a more pronounced effect on density. The model linking density to traits explains 92% of the variation, with 65% of the density profile variation attributed to the three measured traits. The remaining 27% is explained by species as a random effect. There is a clear variation between trees and within trees that have implications for interpreting density profiles in angiosperm trees: the exact driving anatomical fraction behind every density value will depend on the position within the core. The underlying function of density will thus vary accordingly.

Download Full-text