Important Timber Species Research Articles

Sustainable Management of Central Appalachian Red Spruce

Red spruce (Picea rubens) was historically an important and dominant timber species in the central Appalachian mountain range. The tree species is now found in a small fraction of its original home range. Threatened and endangered organisms such as the Cheat Mountain Salamander (Plethodon nettingi) rely on red spruce associated forests for survival. This review provides a background on the history of forest management of red spruce in the central Appalachian region. A meta-analysis was conducted on recent literature (published 2000 or later) of red spruce in the central Appalachian region to highlight key management and conservation concerns. In particular, forest health concerns related to air pollution and climatic stress also are addressed. Approaches to examine the impact of environmental factors on red spruce site productivity are covered. This review also provides sustainable management options for restoration of red spruce in the central Appalachian mountain range.

Ray Traits of Juvenile Wood and Mature Wood: Pinus massonia and Cunninghamia lanceolata

Ray traits affect secondary xylem development and wood properties. Pinus massonia and Cunninghamia lanceolata, commercially important timber species, were chosen to study the differences in wood ray traits of juvenile versus mature wood. Seven ray traits, i.e., percentage of rays, ray spacing, ray number, uniseriate ray height, fusiform ray height, ray parenchyma cell length and ray tracheid length, as well as eight wood axial tissue traits, were investigated quantitatively. Intraspecific variations in ray traits and axial tissue traits between juvenile wood and mature wood were displayed in violin plots. The results showed that anatomical differences between juvenile wood and mature wood were significant for both ray traits and axial tissue traits. Juvenile wood generally possessed the larger percentage of rays, higher ray spacing and ray number, smaller ray height and shorter ray cells than mature wood. A positive correlation was present between the ray parenchyma cell length and ray tracheid length. Negative correlations of the ray number and ray spacing with uniseriate ray height were found. Additionally, the axial tracheid cell wall thickness all had Pearson’s correlations with ray spacing, ray number and ray parenchyma cell length.

Hyperspectral Imaging Combined with Machine Learning for the Detection of Fusiform Rust Disease Incidence in Loblolly Pine Seedlings

Loblolly pine is an economically important timber species in the United States, with almost 1 billion seedlings produced annually. The most significant disease affecting this species is fusiform rust, caused by Cronartium quercuum f. sp. fusiforme. Testing for disease resistance in the greenhouse involves artificial inoculation of seedlings followed by visual inspection for disease incidence. An automated, high-throughput phenotyping method could improve both the efficiency and accuracy of the disease screening process. This study investigates the use of hyperspectral imaging for the detection of diseased seedlings. A nursery trial comprising families with known in-field rust resistance data was conducted, and the seedlings were artificially inoculated with fungal spores. Hyperspectral images in the visible and near-infrared region (400–1000 nm) were collected six months after inoculation. The disease incidence was scored with traditional methods based on the presence or absence of visible stem galls. The seedlings were segmented from the background by thresholding normalized difference vegetation index (NDVI) images, and the delineation of individual seedlings was achieved through object detection using the Faster RCNN model. Plant parts were subsequently segmented using the DeepLabv3+ model. The trained DeepLabv3+ model for semantic segmentation achieved a pixel accuracy of 0.76 and a mean Intersection over Union (mIoU) of 0.62. Crown pixels were segmented using geometric features. Support vector machine discrimination models were built for classifying the plants into diseased and non-diseased classes based on spectral data, and balanced accuracy values were calculated for the comparison of model performance. Averaged spectra from the whole plant (balanced accuracy = 61%), the crown (61%), the top half of the stem (77%), and the bottom half of the stem (62%) were used. A classification model built using the spectral data from the top half of the stem was found to be the most accurate, and resulted in an area under the receiver operating characteristic curve (AUC) of 0.83.

Variations in Rainfall Affect the Responses of Foliar Chemical Properties of Cunninghamia lanceolata Seedlings to Soil Warming.

Climate warming is becoming an increasingly serious threat. Understanding plant stoichiometry changes under climate warming is crucial for predicting the effects of future warming on terrestrial ecosystem productivity. Nevertheless, how plant stoichiometry responds to warming when interannual rainfall variation is considered, remains poorly understood. We performed a field soil warming experiment (+5°C) using buried heating cables in subtropical areas of China from 2015 to 2018. Stoichiometric patterns of foliar C:N:P:K:Ca:Mg, non-structural carbohydrate, and stable isotope of Cunninghamia lanceolata seedlings were studied. Our results showed that soil warming decreased foliar P and K concentrations, C:Ca, P:Ca, and P:Mg ratios. However, soil warming increased foliar Ca concentration, δ15N value, C:P and N:P ratios. The response ratios of foliar N, C:N, and δ15N to soil warming were correlated with rainfall. Our findings indicate that there was non-homeostasis of N and C:N under warming conditions. Three possible reasons for this result are considered and include interannual variations in rainfall, increased loss of N, and N limitation in leaves. Piecewise structural equation models showed that stoichiometric non-homeostasis indirectly affected the growth of C. lanceolata seedlings in response to soil warming. Consequently, the growth of C. lanceolata seedlings remained unchanged under the warming treatment. Taken together, our results advance the understanding of how altered foliar stoichiometry relates to changes in plant growth in response to climate warming. Our results emphasize the importance of rainfall variations for modulating the responses of plant chemical properties to warming. This study provides a useful method for predicting the effects of climate warming on economically important timber species.

Indian Timbers for Veneering - A Review

Conservation oriented forest management policies and total ban on commercial logging from natural forest has led the plywood industry in India to a situation of shortage of traditional timber raw material which is used for manufacturing wood based panels. The shortage of raw materials has forced many wood based product mills to operate below their installed production capacities. The wood based industries in India are managing to survive on the availability of timber outside forest, secondary species and other lesser known Indian hardwoods. The industry is dependent on imported timber species to some extent as a source of raw material. Under this circumstance, the study on lesser known Indian hardwoods which can be grown in agro forestry and farm forestry plantation will help in making use of these species for plywood manufacturing and thereby ensuring uninterrupted supply of raw materials for production of plywood and other wood based panels. Keeping this in view, a series of studies has been carried out at Indian Plywood Industries Research and Training Institute (IPIRTI) to investigate the suitability of secondary species of timbers or lesser known Indian hardwoods especially the short rotation plantation grown timbers for the manufacture of plywood. This is a compilation of the outcome of such studies carried out at IPIRTI.

Strigolactone regulates plant architecture by inhibiting lateral branch growth in Quercus mongolica seedlings

ABSTRACT Mongolian oak (Quercus mongolica) is an important timber species in northeast China, but overdeveloped lateral branches during the seedling stage often result in poor plant architecture and reduce the growth potential. Strigolactones (SLs) were proposed to play an important role in plant architecture by inhibiting the growth of lateral branches; however, there is no knowledge on the strigolactone effects in Mongolian oak. In this study, 0.3, 3, 10, and 30 mg/L of GR24 (analogue of SLs) and 1 mg/L Thidiazuron (TDZ) were applied to Mongolian oak seedlings by the lanolin method. All GR24 treatments significantly reduced the number and biomass of lateral branches; in addition, the length increment of lateral branches was decreased by 3, 10 and 30 mg/L GR24. In addition, the auxin content in lateral branches was significantly increased by the 10 mg/L GR24 treatment, which might be one of the main reasons for the inhibition of lateral branch growth. Increased sucrose content in apex, combined with a decrease of sucrose content in lateral branches, further demonstrated the important role of GR24 in inhibiting lateral branch growth.

Extending coverage and thematic resolution of compositional land cover maps in a hierarchical Bayesian framework.

Ecological models are constrained by the availability of high-quality data at biologically appropriate resolutions and extents. Modeling a species' affinity or aversion with a particular land cover class requires data detailing that class across the full study area. Data sets with detailed legends (i.e., high thematic resolution) and/or high accuracy often sacrifice geographic extent, while large-area data sets often compromise on the number of classes and local accuracy. Consequently, ecologists must often restrict their study extent to match that of the more precise data set, or ignore potentially key land cover associations to study a larger area. We introduce a hierarchical Bayesian model to capitalize on the thematic resolution and accuracy of a regional land cover data set, and on the geographic breadth of a large area land cover data set. For the full extent (i.e., beyond the regional data set), the model predicts systematic discrepancies of the large-area data set with the regional data set, and divides an aggregated class into two more specific classes detailed by the regional data set. We illustrate the application of our model for mapping eastern white pine (Pinus strobus) forests, an important timber species that also provides habitat for an invasive shrub in the northeastern United States. We use the National Land Cover Database (NLCD), which covers the full study area but includes only generalized forest classes, and the NH GRANIT land cover data set, which maps White Pine Forest and has high accuracy, but only exists within New Hampshire. We evaluate the model at coarse (20km2 ) and fine (2km2 ) resolutions, with and without spatial random effects. The hierarchical model produced improved maps of compositional land cover for the full extent, reducing inaccuracy relative to NLCD while partitioning a White Pine Forest class out of the Evergreen Forest class. Accuracy was higher with spatial random effects and at the coarse resolution. All models improved upon simply partitioning Evergreen Forest in NLCD based on the predicted distribution of white pine. This flexible statistical method helps ecologists leverage localized mapping efforts to expand models of species distributions, population dynamics, and management strategies beyond the political boundaries that frequently delineate land cover data sets.

Factors Affecting the Number of Pollen Grains per Male Strobilus in Japanese Cedar (Cryptomeria japonica).

Japanese cedar (Cryptomeria japonica) is the most important timber species in Japan; however, its pollen is the primary cause of pollinosis in Japan. The total number of pollen grains produced by a single tree is determined by the number of male strobili (male flowers) and the number of pollen grains per male strobilus. While the number of male strobili is a visible and well-investigated trait, little is known about the number of pollen grains per male strobilus. We hypothesized that genetic and environmental factors affect the pollen number per male strobilus and explored the factors that affect pollen production and genetic variation among clones. We counted pollen numbers of 523 male strobili from 26 clones using a cell counter method that we recently developed. Piecewise Structural Equation Modeling (pSEM) revealed that the pollen number is mostly affected by genetic variation, male strobilus weight, and pollen size. Although we collected samples from locations with different environmental conditions, statistical modeling succeeded in predicting pollen numbers for different clones sampled from branches facing different directions. Comparison of predicted pollen numbers revealed that they varied >3-fold among the 26 clones. The determination of the factors affecting pollen number and a precise evaluation of genetic variation will contribute to breeding strategies to counter pollinosis. Furthermore, the combination of our efficient counting method and statistical modeling will provide a powerful tool not only for Japanese cedar but also for other plant species.

The yield of edible caterpillars Imbrasia oyemensis and Cirina forda from timber trees logged on concessions in the Democratic Republic of the Congo: A contribution to managing tropical forests for multiple resources

Local people in rural areas of the tropics depend on forests for a range of food resources, including protein-rich edible caterpillars, among them Imbrasia oyemensis and Cirina forda, which are important for nutrition and income. Sapelli (Entandrophragma cylindricum), the African mahogany, and Tali (Erythrophleum suaveolens) are food sources for these caterpillars; they are also among the most important timber species harvested from Congo Basin forests. This study quantified the yield of caterpillars from harvestable and precommercial sizes of trees of these two timber species to better understand the impact of logging on the availability of edible caterpillars to local people, and the implications for managing both timber and non-timber resources in industrial timber concessions. Caterpillars were collected and weighed beneath 50 Sapelli trees 23–190 cm DBH and 170 Tali trees 22–174 cm DBH on two timber concessions, from mid-August to mid-September, over two years. Caterpillars were found to descend from the trees during 5 days each year, and quantities varied between years. In both sample years, yields were significantly higher from harvestable trees larger than the minimum cutting diameter than from precommercial trees. Each harvestable Sapelli tree (≥ 80 cm DBH), yielded an average of 11.3 kg fresh weight of I. oyemensis year-1; smaller, precommercial trees yielded 5.4 kg tree−1year−1. Each harvestable Tali tree (≥ 60 cm DBH) yielded an average of 9.1 kg of C. forda year−1, as compared to 5.7 kg tree−1year−1 from precommercial trees. This means that industrial timber harvesting, which removes trees larger than the minimum cutting diameter, has a disproportionate effect on the availability of caterpillars. However, trees below the minimum cutting diameter also yield caterpillars, and may occur at higher densities. Guidelines that limit harvesting on steep slopes or near watercourses, or that call for retaining large trees as seed sources, also safeguard caterpillar yields. However, multiple resource management should consider proactive measures, which could include zoning areas near villages as sources of edible caterpillars, and protecting those trees from logging.

Genetic stability of Larix olgensis provenances planted in different sites in northeast China

Larix olgensis, also known locally as Changbai larch, is one of the most important timber species in northeast China. In order to widely expand the plantation of this species, the genetic stability and adaptability of the provenances must be analyzed through provenance tests. In this study, growth traits and survival rate (SR) of 10 L. olgensis provenances planted in four representative sites were investigated and analyzed. The results of ANOVA and AMMI analyses showed that the environment effect was a predominant source of variation. The average diameter at breast height (DBH) of different provenances at the four sites ranged from 14.65 to 28.51 cm. The stand volume also varied among provenances planted at different sites mainly due to variation in SR and DBH. The phenotypic coefficient of variation (PCV), genotypic coefficient of variation (GCV) and repeatability (hP2) for DBH in different sites ranged from 12.47% to 17.79%, from 2.94% to 3.83% and from 0.49 to 0.63, respectively. The correlation analysis showed that there were highly significant positive correlations among DBH, survival rate, and stand volume, and they all not correlated with geoclimatic factors of provenances original sites. However, they were significantly positively correlated with longitude and precipitation of the trial sites. Significant negative correlations were observed between SR and latitude and with equivalent latitude. According to AMMI biplots, four provenances were regarded as the most stable and relatively high-yielding provenances across environments. These provenances could be used as the preferred materials for the establishment of large-scale plantations in the future.

Hyperspectral Imaging with Cost-Sensitive Learning for High-Throughput Screening of Loblolly Pine (Pinus taeda L.) Seedlings for Freeze Tolerance

HighlightsA hyperspectral imaging approach was developed for freeze-tolerance phenotyping of loblolly pine seedlings.Image acquisition was conducted before and periodically after artificial freezing of the seedlings.A hyperspectral data processing pipeline was developed to extract the spectra from seedling segments.Cost-sensitive support vector machine (SVM) was used for classifying stressed and healthy seedlings.Post-freeze scanning of seedlings on day 41 achieved the highest screening accuracy of 97%.Abstract. Loblolly pine (Pinus taeda L.) is a commercially important timber species planted across a wide temperature gradient in the southeastern U.S. It is critical to ensure that the planting stock is suitably adapted to the growing environment to achieve high productivity and survival. Long-term field studies, although considered the most reliable method for assessing cold hardiness of loblolly pine, are extremely resource-intensive and time-consuming. The development of a high-throughput screening tool to characterize and classify freeze tolerance among different genetic entries of seedlings will facilitate accurate deployment of highly productive and well-adapted families across the landscape. This study presents a novel approach using hyperspectral imaging to screen loblolly pine seedlings for freeze tolerance. A diverse population of 1549 seedlings raised in a nursery were subjected to an artificial mid-winter freeze using a freeze chamber. A custom-assembled hyperspectral imaging system was used for in-situ scanning of the seedlings before and periodically after the freeze event, followed by visual scoring of the frozen seedlings. A hyperspectral data processing pipeline was developed to segment individual seedlings and extract the spectral data. Examination of the spectral features of the seedlings revealed reductions in chlorophylls and water concentrations in the freeze-susceptible plants. Because the majority of seedlings were freeze-stressed, leading to severe class imbalance in the hyperspectral data, a cost-sensitive learning technique that aims to optimize a class-specific cost matrix in classification schemes was proposed for modeling the imbalanced hyperspectral data, classifying the seedlings into healthy and freeze-stressed phenotypes. Cost optimization was effective for boosting the classification accuracy compared to regular modeling that assigns equal costs to individual classes. Full-spectrum, cost-optimized support vector machine (SVM) models achieved geometric classification accuracies of 75% to 78% before and within 10 days after the freeze event, and up to 96% for seedlings 41 days after the freeze event. The top portions of seedlings were more indicative of freeze events than the middle and bottom portions, leading to better classification accuracies. Further, variable selection enabled significant reductions in wavelengths while achieving even better accuracies of up to 97% than full-spectrum SVM modeling. This study demonstrates that hyperspectral imaging can provide tree breeders with a valuable tool for improved efficiency and objectivity in the characterization and screening of freeze tolerance for loblolly pine. Keywords: Cost-sensitive learning, Freeze tolerance, Hyperspectral imaging, Plant phenotyping, Support vector machine.

Impact of Anthropogenic Activities on Genetic Diversity of <i>Celtis zenkeri </i>Engl in South-West Nigeria

Celtis zenkeri is a valuable tropical tree species for industrial and domestic purposes. For several years, exploitation of this species has not been sustainable and no reforestation or cultivation effort has been put in place both by governmental and non-governmental agencies. Anthropogenic activities have resulted in deforestation and subsequent reduction in the population size of important timber species. The research aim was to determine the impact of anthropogenic activities on genetic diversity of Celtis zenkeri in South-West Nigeria. Extensive sampling of Celtis zenkeri was carried out in four natural forest ecosystems. Two pristine forests (SNR, Akure forest and Osun Osogbo sacred grove) and two degraded forests (OA3 and Eda forest reserve). Young leaves were collected from each tree found in each site and preserved with silica gel for molecular analysis. In all, 130 accessions were sampled and were analyzed with five chloroplast microsatellite markers. In the result, allelic richness, which is a measure of genetic diversity and an indicator of a population's long-term potential for adaptability and persistence, was significantly higher in the two pristine forests than the two degraded forests. Statistically, a significant difference was not recorded for the observed heterozygosities (Ho) in the population of Celtis zenkeri in the pristine forests (Queen’s plot and Osun-Osogbo Sacred Grove) and a degraded forest (OA3). The formal indicates the possibility of conserving genetic diversity using traditional conservation approaches such as taboos and restrictions. Though OA3 is a degraded forest, the impact of the anthropogenic activities may not have been severe when compared with Eda forest reserve. At present, the scale of human activities in Eda forest reserve and OA3 could pose a serious threat to the future viability of the species if unchecked. Therefore, ex-situ conservation and sustainable harvesting of Celtis zenkeri are recommended.

Identification Method of Imported Timber Species by Mid-Infrared Spectrum

Identification Method of Imported Timber Species by Mid-Infrared Spectrum

Wood Properties Characterisation of Thermo-Hydro Mechanical Treated Plantation and Native Tasmanian Timber Species

Thermo-hydro mechanical (THM) treatments and thermo-treatments are used to improve the properties of wood species and enhance their uses without the application of chemicals. This work investigates and compares the effects of THM treatments on three timber species from Tasmania, Australia; plantation fibre-grown shining gum (Eucalyptus nitens H. Deane and Maiden), plantation saw-log radiata pine (Pinus radiata D. Don) and native-grown saw-log timber of the common name Tasmanian oak (which can be any of E. regnans F. Muell, E. obliqua L’Hér and E. delegatensis L’Hér). Thin lamellae were compressed by means of THM treatment from 8 mm to a target final thickness of 5 mm to investigate the suitability for using THM-treated lamellas in engineered wood products. The springback, mass loss, set-recovery after soaking, dimensional changes, mechanical properties, and Brinell hardness were used to evaluate the effects of the treatment on the properties of the species. The results show a marked increase in density for all three species, with the largest increase presented by E. nitens (+53%) and the smallest by Tasmanian oak (+41%). E. nitens displayed improvements both in stiffness and strength, while stiffness decreased in P. radiata samples and strength in Tasmanian oak samples. E. nitens also displayed the largest improvement in hardness (+94%) with respect to untreated samples. P. radiata presented the largest springback whilst having the least mass loss. E. nitens and Tasmanian oak showed similar dimensional changes, whilst P. radiata timber had the largest thickness swelling and set-recovery due to the high water absorption (99%). This study reported the effects of THM treatments in less-known and commercially important timber species, demonstrating that the wood properties of a fibre-grown timber can be improved through the treatments, potentially increasing the utilisation of E. nitens for structural and higher quality timber applications.

Drought response of European beech (Fagus sylvatica L.)—A review

European beech (Fagus sylvatica) is the dominant tree species of Central Europe’s natural forests and one of the continent’s most important timber species. This highly competitive species is known to be drought-sensitive and thus may increasingly be threatened by climate change-related heat waves and drought in part of its distribution range. Tree responses and tolerance to drought are complex processes that are best understood by adopting a multi-level analysis spanning from the molecular physiological to the tree and stand levels. Here I review recent progress in our understanding of beech drought responses in all relevant fields of research, notably adjustments in cellular biochemistry, responses of photosynthesis, stomatal regulation and leaf water status, the vulnerability of the hydraulic and phloem systems, adaptive responses of the fine root system, leaf area adjustments, long-term declines in radial growth, and drought-induced tree mortality. A special focus is on population differences in drought tolerance as the basis for the selection of drought-hardier provenances. The evidence from the different research fields is brought together with the aim to develop a multi-disciplinary perception of beech drought response, to identify weak components in the species’ drought response strategy, and to suggest future research efforts to close knowledge gaps.

Changes in leaf chemistry and anatomy of Corymbia citriodora subsp. variegata (Myrtaceae) in response to native and exotic pathogens

Corymbia citriodora subsp. variegata (CCV) is an economically and ecologically important timber species, native to eastern Australia. It is highly susceptible to Quambalaria pitereka, a coevolved endemic pathogen, and Austropuccinia psidii, an exotic invasive pathogen. Genes associated with resistance to Q. pitereka are specific and uncorrelated with the genes associated with resistance to A. psidii, suggesting different resistance mechanisms to each pathogen, possibly associated with leaf phenotypic traits. This study examined leaf chemical and anatomical differences in CCV between uninoculated plants and those inoculated with Q. pitereka and A. psidii. The results demonstrate that the pathogens induce different responses in CCV. Plants inoculated with A. psidii exhibited chemical and anatomical changes that were not observed in uninoculated controls and Q. pitereka-inoculated plants, such as deposition of polyphenols and tannins in upper/lower epidermis, variation in the proportion of monoterpenes, steroids, monounsaturated hydrocarbons and long chain hydrocarbons and higher leaf toughness. In contrast, CCV response to Q. pitereka altered the distribution of polyphenols and tannins in the leaves and possible accumulation of these compounds and lignin in necrotic areas. These findings provide a better understanding of factors underlying CCV responses to coevolved and exotic pathogens and add insights into plant-pathogen interactions.

Variability Assessment for Volume, Biomass and Carbon Stock in Cedrus deodara (Roxb) G.Don. Forests of Garhwal Himalaya

Deodar is typically gregarious and is usually found in pure stands. It is one of the most important timber species in the forests of North Indian Himalayas. The objective of the present study was the assessment of variation in volume and biomass along with the carbon holding capacity of different deodar forests. The present study was undertaken in ten different forests sites, assessed by laying out three 0.1 ha sample plots randomly on each location. Total enumeration of trees within the sample plot was done by measuring girth and height of all the trees. Further, data collected from stand were computed for dbh, basal area, volume, stand density and canopy cover. The above ground biomass densities (AGBD), below ground biomass density (BGBD), total biomass density (TBD), total carbon density (TCD) were examined for variation of biomass and carbon stock. The results derived from field data during the study revealed that the values range from 42.10 to 57.07 cm (diameter at breast height), 1.37 to 2.84 m2 trees-1 (basal area), 19.68 to 37.64 m (height), 1.44 m3 tree-1 to 4.27 m3 tree-1 (volume), 227 to 407 individual ha-1 (stand density) and 57.91% to 80.60% (canopy cover) respectively. The values of AGBD (428.57 to 1279.51 Mg ha-1), BGBD (97.41 to 256.14 Mg ha-1), TBD (525.98 to 1535.65 Mg ha-1), and TCD (767.83 to 262.99 Mg ha-1) were recorded in different study sites and highest values was observed in Kanasar-I site. On the basis of above results it can be concluded that the healthy stand growth means presence of trees in all diameter classes. The Kanasar-I has more prominent capacity to storage biomass and carbon stock. Deodar being a slow growing conifer will provide a long term and high carbon storage than broadleaf species forest. Therefore, protecting deodar forest would have the largest impact, per unit area, on reducing carbon emission from deforestation.

An Assessment of Stumpage Price and the Price Index of Chinese Fir Timber Forests in Southern China Using a Hedonic Price Model

Research Highlights: Stumpage price is the most important factor affecting the value of forests. Therefore, an understanding of the factors affecting stumpage prices and trends is critical for effective forest management. Background and Objectives: Chinese fir is the most important fast-growing timber species in China, it is also the tree species with the largest trading volume in the stumpage markets of Southern China. The aim of this study was to analyze the determinants and trends of stumpage prices for Chinese fir timber forests. Materials and Methods: Data on 928 sales of Chinese fir timber forests transacted between 2007 and 2016 were gathered from the stumpage markets in Southern China. We analyzed the relationship between stumpage prices and sales characteristics using the hedonic price method (HPM) and measured the stumpage price index with a dummy time hedonic index. Results: (1) The double logarithmic form of the HPM yielded a more accurate estimate than the semi logarithmic form. The R2ad values in the nine annual prediction models were all above 80%. Stock volume made the greatest contribution to stumpage price, followed by stand age. Stand area had no significant impact on the stumpage price. (2) Stumpage prices of Chinese fir timber forests fluctuated greatly, especially in 2010 and 2015 when the sequential price indexes were 180.01% and 74.95%, respectively. Taking 2007 as the baseline, we calculated the base price index in 2016 to be 197%, with an average annual growth rate of 7.82%. (3) The stumpage market was associated with a higher degree of risk than the timber market. Conclusions: Our findings provide valuable inputs that can guide and facilitate the Chinese government’s efforts to optimize resource allocation and standardize the stumpage market.

Progeny performance and selection of superior trees within families in Larix olgensis

Larix olgensis is one of the most important timber species in Northeast China. Although L. olgensis seed orchards have been established for many years and some progeny tests have been conducted, studies of progeny performance and the selection of superior families are still lacking. These tests are important for upgrading and improvement of seed orchards. Here, we estimate the genetic variation for major economic traits between families to provide selection materials for the establishment of a second-generation seed orchard. This study examined 71 half-sib families and 2 control families of L. olgensis in the Xiyang forest seed orchard in Yongji County, Northeast China. We measured tree height, diameter at breast height, volume, branch angle, stem straightness degree and crown width of 4-year-old progeny. Genetic parameters for the studied traits were determined, and comprehensive analyses of multiple traits and breeding values were used for selection of superior families and individual trees within families. The results show that all these traits are significantly different (P < 0.01) among families where family variance was greater than environmental variance. The phenotypic and genotypic coefficients of variation ranged from 9.01% to 78.22% and from 1.81% to 39.20%, respectively. The heritability values of families and individual trees ranged from 0.663 to 0.959 and 0.034 to 0.983, respectively. There was a significant positive correlation between investigated traits. Using the multiple-traits comprehensive evaluation method, seven families and 56 superior individual trees were selected. Selection of superior parents using breeding values for timber yield, stem quality and crown width as a proxy for planting density again resulted in the selection of seven superior families. We determined that the comprehensive multiple-traits evaluation approach is effective for selecting superior families and individual trees for the establishment of advanced second generation seed orchards. Families selected based on breeding value may be used as preferred parents for future hybridization breeding.

Population genomics of the widespread African savannah trees Afzelia africana and Afzelia quanzensis reveals no significant past fragmentation of their distribution ranges.

Few studies have addressed the evolutionary history of tree species from African savannahs. Afzelia contains economically important timber species, including two species widely distributed in African savannahs: A. africana in the Sudanian region and A. quanzensis in the Zambezian region. We aimed to infer whether these species underwent range fragmentation and/or demographic changes, possibly reflecting how savannahs responded to Quaternary climate changes. We characterized the genetic diversity and structure of these species across their distribution ranges using nuclear microsatellites (SSRs) and genotyping-by-sequencing (GBS) markers. Six SSR loci were genotyped in 241 A. africana and 113 A. quanzensis individuals, while 2800 high-quality single nucleotide polymorphisms (SNPs) were identified in 30 A. africana individuals. Both species appeared to be mainly outcrossing. The kinship between individuals decayed with the logarithm of the distance at similar rates across species and markers, leading to relatively small Sp statistics (0.0056 for SSR and 0.0054 for SNP in A. africana, 0.0075 for SSR in A. quanzensis). The patterns were consistent with isolation by distance expectations in the absence of large-scale geographic gradients. Bayesian clustering of SSR genotypes did not detect genetic clusters within species. In contrast, SNP data resolved intraspecific genetic clusters in A. africana, illustrating the higher resolving power of GBS. However, these clusters revealed low levels of differentiation and no clear geographical entities, so that they were interpreted as resulting from the isolation by distance pattern rather than from past population fragmentation. These results suggest that populations have remained connected throughout the large, continuous savannah landscapes. The absence of clear phylogeographic discontinuities, also found in a few other African savannah trees, indicates that their distribution ranges have not been significantly fragmented during the climatic oscillations of the Pleistocene, in contrast to patterns commonly found in African rainforest trees.