Dendrochronological study of Cedrus deodar Grown at Kumrat valley Dir Upper KPK, Pakistan: Evaluation of Tree Age and Increment Based on Increment Core

The present research was conducted for tree-rings study in a mixed stand of Himalayan Species Credur deodar in Kumrat valley Dir Upper KPK, Pakistan. Tree-rings analysis was related to the counting of tree ring. Random sampling method was used, and 70 sample trees were selected, tree heights and diameters were measured, and increment cores were collected from each sample-tree diameter at the height at breast point to be analyzed and studied in the laboratory. The objectives of the study were to determine the exact age of tree and to evaluate total and mean annual increment in the basal area and tree volume based on the increment cores. Regression models revealed the impacts of tree age on the basal area and tree-volume increment. Results showed the minimum basal-area increment was 0.0028 m2 at the age of 10 years, the maximum basal-area increment was 2.658 m2 at the age of 60 years, with mean was 0.95±0.677 m2 at the age of 36 years and R2 was 0.9593. The maximum tree-volume increment was 1.42 m3 at the age of 60 years, the minimum tree-volume increment was 0.010 m3 at the age of 10 years, with mean was 1.35±0.96 m3 at the age of 36 years and R2 was 0.9167. The minimum mean annual-basal area increment was 0.0027 m2, the maximum mean annual-basal area increment was 0.048 m2, and the average increment was 0.022±0.010 m2. The maximum mean-annual increment in tree volume was 0.068 m3 at the age of 60 years, the minimum mean-annual increment was 0.0039 m3 at the age of 10 years, with mean was 0.032±0.014 m3 at the age of 36 years and R2 was 0.8903. Results showed a strong positive relationship of tree age with area and volume increment. Keywords: Basal area, increment, tree age, volume

The radial gradient of moisture content of silver birch wood in different seasons

Silver birch ( Roth) is classified in diffuse-porous wood category. In this case structure of wood tissue is quite similar across whole cross-sectional area. The aim of this study was to analyse cross-section variability of moisture content (MC) of growing silver birch wood, significant hardwood species in Polish forests. Investigations were performed on 120 model trees. In the trunk of each model tree, an increment core was collected at breast height. Samples were collected of 30 different trees in four different seasons. The greatest MC was observed during winter, lowest MC in summer. Differences in MC were statistically significant only between winter versus spring, summer, and autumn. Distribution of MC on cross-section was similar in each season. The greatest average value was observed close to pith, then it was decreasing in bark direction. The greatest difference between observed in spring – 19.51% (p < 0.05) and lowest in autumn – 4.66%. Distribution of green density (GD) on cross section was inverse proportional to MC value. Variations in GD and MC are relevant for log transport planning, weight-scaling systems, lumber drying and dynamic assessment of stiffness. Therefore, from an environmental loss perspective, it is important to determine changes in MC and GD across the year.Betula pendula

Effect of number of annual rings and tree ages on genomic predictive ability for solid wood properties of Norway spruce

Background Genomic selection (GS) or genomic prediction is considered as a promising approach to accelerate tree breeding and increase genetic gain by shortening breeding cycle, but the efforts to develop routines for operational breeding are so far limited. We investigated the predictive ability (PA) of GS based on 484 progeny trees from 62 half-sib families in Norway spruce (Picea abies (L.) Karst.) for wood density, modulus of elasticity (MOE) and microfibril angle (MFA) measured with SilviScan, as well as for measurements on standing trees by Pilodyn and Hitman instruments. Results GS predictive abilities were comparable with those based on pedigree-based prediction. Marker-based PAs were generally 25–30% higher for traits density, MFA and MOE measured with SilviScan than for their respective standing tree-based method which measured with Pilodyn and Hitman. Prediction accuracy (PC) of the standing tree-based methods were similar or even higher than increment core-based method. 78–95% of the maximal PAs of density, MFA and MOE obtained from coring to the pith at high age were reached by using data possible to obtain by drilling 3–5 rings towards the pith at tree age 10–12. Conclusions This study indicates standing tree-based measurements is a cost-effective alternative method for GS. PA of GS methods were comparable with those pedigree-based prediction. The highest PAs were reached with at least 80–90% of the dataset used as training set. Selection for trait density could be conducted at an earlier age than for MFA and MOE. Operational breeding can also be optimized by training the model at an earlier age or using 3 to 5 outermost rings at tree age 10 to 12 years, thereby shortening the cycle and reducing the impact on the tree.

Effect of number of annual rings and tree ages on genomic predictive ability for solid wood properties of Norway spruce

BACKGROUND: Genomic selection (GS) or genomic prediction is considered as a promising approach to accelerate tree breeding and increase genetic gain by shortening breeding cycle, but the efforts to develop routines for operational breeding are so far limited. We investigated the predictive ability (PA) of GS based on 484 progeny trees from 62 half-sib families in Norway spruce (Picea abies (L.) Karst.) for wood density, modulus of elasticity (MOE) and microfibril angle (MFA) measured with SilviScan, as well as for measurements on standing trees by Pilodyn and Hitman instruments. RESULTS: GS predictive abilities were comparable with those based on pedigree-based prediction. Marker-based PAs were generally 25-30% higher for traits density, MFA and MOE measured with SilviScan than for their respective standing tree-based method which measured with Pilodyn and Hitman. Prediction accuracy (PC) of the standing tree-based methods were similar or even higher than increment core-based method. 78-95% of the maximal PAs of density, MFA and MOE obtained from coring to the pith at high age were reached by using data possible to obtain by drilling 3-5 rings towards the pith at tree age 10-12. CONCLUSIONS: This study indicates standing tree-based measurements is a cost-effective alternative method for GS. PA of GS methods were comparable with those pedigree-based prediction. The highest PAs were reached with at least 80-90% of the dataset used as training set. Density could be conducted at an earlier age than for MFA and MOE. Operational breeding can also be optimized by training the model at an earlier age or using 3 to 5 outermost rings at tree age 10 to 12 years, thereby shortening the cycle and reducing the impact on the tree.

Understanding and predicting species- and elevation-dependent dynamics in East Asian temperate forests

&lt;p&gt;The velocity and impact of climate change on forest appear to be site, environment, and tree species-specific. The primary objective of this research is to assess the changes in productivity of major temperate tree species in South Korea using terrestrial inventory and satellite remote sensing data. The area covered by each tree species was further categorized into either lowland forest (LLF) or high mountain forest (HMF) and investigated. We used the repeated Korean national forest inventory (NFI) data to calculate a stand-level annual increment (SAI). We then compared the SAI, a ground-based productivity measure, to MODIS net primary productivity (NPP) as a measure of productivity based on satellite imagery. In addition, the growth index of each increment core, which eliminated the effect of tree age on radial growth, was derived as an indicator of the variation of productivity by tree species over the past four decades. Based on these steps, we understand the species- and elevation-dependent dynamics. The secondary objective is to predict the forest dynamics under climate change using the Perfect Plasticity Approximation with Simple Biogeochemistry (PPA-SiBGC) model. The PPA-SiBGC is an analytically tractable model of forest dynamics, defined in terms of parameters for individual trees, including allometry, growth, and mortality. We estimated these parameters for the major species by using NFI and increment core data. We predicted forest dynamics using the following time-series metrics: Net ecosystem exchange, aboveground biomass, belowground biomass, C, N, soil respiration, and relative abundance. We then focus on comparing the impact of climate change on LLF and HMF. The results of our study can be used to develop climate-smart forest management strategies to ensure that both LLF and HMF continue to be resilient and continue to provide a wide range of ecosystem services in the Eastern Asian region.&lt;/p&gt;

Impact of air pollution on forest stands in the vicinity of Wodzisław Śląski and Rybnik, Poland

Tree-ring analysis was used to investigate the impact of air pollution on forest stands in the southern part of the Upper Silesia region of southern Poland. Four about 120 years old Scots pine stands located near Wodzisław Śląski and Rybnik were selected for study and 20 increment core samples from each stand were taken. All study stands were selected based upon their considerable exposure to air and dust pollution.The results of dendrochronological analysis showed strong and significant reductions in tree ring growth especially during the period from 1960 to 1990. A significant number of trees with reductions (85%) was observed in two Scots pine stands both of which are directly exposed to air pollution from mine-owned coking plant and power and heating plants. Since 1990s the improved growth of these pines was clearly noted. A comparison for the period 1970 to 1990 for stands located west from the main emitters’ versus stands east and directly exposed found fewer trees with growth reductions (ca. 40%). At the beginning of the 21st century, a large number of trees in these western stands were observed with growth reductions between 50 and 60%. Probably, these trees were affected by air pollution from a nearby power plant located immediately across the border in the Czech Republic. Relationships between periods of severe reductions in ring width growth or missing rings were noted in a large percentage of pine trees in all four stands; these cross-stand relationships suggested common weather-related impacts. Missing rings were noted in 1956, 1963, 1968, 1970, 1971, 1973, 1976 and 1979.

Prediction of Stilbene Content from Heartwood Increment Cores of Scots Pine Using near Infrared Spectroscopy Methodology

High-throughput and non-destructive methods for quantifying the content of the stilbene compounds of Scots pine ( Pinus sylvestris L.) heartwood are needed in the breeding for decay resistance of heartwood timber. In this study, near infrared (NIR) spectroscopy calibrations were developed for a large collection of solid heartwood increment core samples in order to predict the amount of the stilbene pinosylvin (PS), its monomethyl ether (PSM) and their sum (STB). The resulting models presented quite accurate predictions in an independent validation set with R2V values ranging between 0.79 and 0.91. The accuracy of the models strongly depended on the chemical being calibrated, with the lowest accuracy for PS, intermediate accuracy for PSM and highest accuracy for STB. The effect of collecting one, two or more (up to five) spectra per sample on the calibration models was studied and it was found that averaging multiple spectra yielded better accuracy as it may account for the heterogeneity of wood along the increment core within and between rings. Several statistical pretreatments of the spectra were tested and an automatic selection of wavenumbers prior to calibration. Without the automatic selection of wavenumbers, a first derivative of normalised spectra yielded the best accuracies, whereas after the automatic selection of wavenumbers, no particular statistical pretreatment appeared to yield better results than any other. Finally, the automatic selection of wavenumbers slightly improved the accuracy of the models for all traits. These results demonstrate the potential of NIR spectroscopy as a high-throughput and non-destructive phenotyping technique in tree breeding for the improvement of decay resistance in heartwood timber.

Voronoi polygons quantify bias when sampling the nearest plant

The design bias in the sample mean obtained from sampling the trees nearest to points randomly and uniformly distributed over a forested area can be exactly quantified in terms of the Voronoi polygons (V polygons) surrounding each tree in the forest of interest. For this sampling method, the V polygon for a prospective sample tree is its inclusion zone. The sides of such polygons are perpendicular to a line joining adjacent trees and equidistant from these trees. For any individual tree attribute Y, the design bias in such a sample mean for estimating the population mean of Y will be equal to the covariance between Y and V-polygon area V divided by the mean V-polygon area. The bias as a percent of the population mean of Y is the product of the correlation coefficient between Y and V and the coefficients of variation for Y and V multiplied by 100. This implies that attempts to estimate the means of commonly measured individual tree variables such as DBH, basal area, and crown diameter or the area from sampling trees nearest to randomly located points will likely be positively biased, and the magnitude of that bias will depend on the strength of the linear relationship to the V-polygon area, as well as the variability among the V-polygon areas and the variable of interest. It is not obvious whether increment core data will be positively or negatively biased, because this depends on the characteristics of the forest of interest. The main conclusion of the study is that the bias formula derived for unweighted estimation from sampling the tree nearest to a point indicates that bias in the range of 5%–10% or greater can occur in many forest populations.