Radial trends in black spruce wood density can show an age- and growth-related decline

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Abstract:The number of planted trees per hectare influences individual volume growth, which in turn can affect wood properties. The objective of this study was to assess the effect of six different plantation spacings of jack pine (Pinus banksiana Lamb.) 25 years following planting on tree growth, morphology, and wood properties. Stem analyses were performed to calculate annual and cumulative diameter, height, and volume growth. For morphological and wood property measurements several parameters were analyzed: diameter of the largest branch, live crown ratio, wood density, and the moduli of elasticity and rupture on small clear samples. The highest volume growth for individual trees was obtained in the 1111 trees/ha plantation, while the lowest was in the 4444 trees/ha plantation. Wood density and the moduli of elasticity and rupture did not change significantly between the six plantation spacings, but the largest branch diameter was significantly higher in the 1111 trees/ha (3.26 cm mean diameter) compared with the 4444 trees/ha spacing (2.03 cm mean diameter). Based on this study, a wide range of spacing induced little negative effect on the measured wood properties, except for the size of knots. Increasing the initial spacing of jack pine plantations appears to be a good choice if producing large, fast-growing stems is the primary goal, but lumber mechanical and visual properties could be decreased due to the larger branch diameter.

Section: Wood Densitymentioning

confidence: 99%

Effect of Tree Spacing on Tree Level Volume Growth, Morphology, and Wood Properties in a 25-Year-Old Pinus banksiana Plantation in the Boreal Forest of Quebec

Hébert

Krause

Plourde

et al. 2016

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“…• X-ray densitometry to measure specific gravity [18][19][20] • X-ray diffraction to measure the microfibril angle [21][22][23] • Automated image analysis to measure fiber dimensions on macerated fibers [24,25] or on solid wood samples [26][27][28] • Near-infrared spectroscopy to predict a variety of properties [29][30][31] • Acoustics in combination with density to measure stiffness [32,33], or to correlate acoustic velocity values to MFA or tracheid length [34,35] • Light transmission to measure spiral grain [36,37] Of the aforementioned tools, X-ray densitometry has arguably been the most widely used to investigate radial patterns of variation. This is undoubtedly due to the overall importance of wood density, the ease of measurement, and the variety of X-ray densitometry instruments/techniques that are available [20].…”

Section: Introductionmentioning

confidence: 99%

“…), and black spruce (Picea mariana (Mill.) B.S.P) all exhibit SG radial trends where SG is high near the pith, decreases in the transition wood, and then increases in the outerwood [19,40,41]. For loblolly pine, the reason for the low SG near the pith is due to the low proportion of latewood to earlywood tracheids and reduced cell wall thicknesses, as well as lower latewood SG [13,42].…”

Section: Introductionmentioning

confidence: 99%

Models for Predicting Specific Gravity and Ring Width for Loblolly Pine from Intensively Managed Plantations, and Implications for Wood Utilization

Dahlen

Auty

Eberhardt

2018

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Abstract:Loblolly pine (Pinus taeda L.) is increasingly grown on intensively managed plantations that yield high growth rates. Wood properties, including specific gravity (SG), change with cambial age, and thus intensively managed trees contain a high proportion of low density corewood when harvested because of reduced rotation lengths. This study was undertaken to develop models of ring-level properties (SG and width) in intensively managed loblolly pine plantations. Ninety-three trees from five stands aged from 24 to 33 years were harvested, and 490 disks were obtained from in between the 5.2-m logs that were cut, and at the merchantable top. The disks were cut into pith-to-bark radial strips that were scanned on an X-ray densitometer, and the resultant data analyzed using non-linear mixed-effects models. The fixed effects of the models, which included cambial age and for some models disk height and ring width, were able to explain 56, 46, 54, 16, and 46 percent of the within-tree variation for ring SG, ring width, latewood SG, earlywood SG, and latewood percent, respectively. To assess implications for wood utilization, a modeled tree was built by using height, diameter, and taper equations and these models were linked with the developed ring SG model to produce a tree properties map. The linked information was also used to generate tree and log SG and proportion of corewood values for different rotation ages. The results from this study are a step towards integrating wood quality models into growth-and-yield modeling systems that are important for loblolly pine plantation management.

“…Pith-to-bark density profiles were obtained using a QTRS-01X Tree Ring Analyzer (Quintek Measurement Systems Inc., Knoxville, TN, USA). The samples were scanned in the longitudinal direction with an X-ray beam at a resolution of 40 μm (For details, see [38]). From these measurements, minimum ring density (MnD), maximum ring density (MxD) and mean ring density (RD) were calculated.…”

Section: Annual Ring Width and Wood Density Measurementsmentioning

confidence: 99%

“…Ring density was highly variable in the juvenile zone [38], but remained relatively constant after a cambial age (CA) of around 25 years. In addition, a density decline close to the bark was detected in some rings older than 60 years.…”

Section: Annual Ring Width and Wood Density Measurementsmentioning

confidence: 99%

Wood Density-Climate Relationships Are Mediated by Dominance Class in Black Spruce (Picea mariana (Mill.) B.S.P.)

Xiang

Auty

Franceschini

et al. 2014

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Abstract:The relationships between climate and wood density components, i.e., minimum ring density, maximum ring density and mean ring density have been studied mainly in dominant trees. However, the applicability of the findings to trees of other dominance classes is unclear. The aim of this study was to address whether climate differentially influences wood density components among dominance classes. X-ray densitometry data was obtained from 72 black spruce (Picea mariana (Mill.) B.S.P.) trees harvested in Northwestern Ontario, Canada. Dominant, co-dominant and intermediate trees were sampled and the data analysed using mixed-effect modelling techniques. For each density component, models were first fitted to the pooled data using ring width and cambial age as predictors, before monthly climatic variables were integrated into the models. Then, separate models were fitted to the data from each dominance class. In general, the addition of climatic factors led to a small but significant improvement in model performance. The predicted historical trends were well synchronized with the observed data. Our results indicate that trees from all dominance classes in a stand should be sampled in order to fully characterize wood density-climate relationships. OPEN ACCESSForests 2014, 5 1164