The wooden artifacts from Schöningen's Spear Horizon and their place in human evolution.

Ethnographic records show that wooden tools played a pivotal role in the daily lives of hunter-gatherers including food procurement tools used in hunting (e.g., spears, throwing sticks) and gathering (e.g. digging sticks, bark peelers), as well as, domestic tools (e.g., handles, vessels). However, wood rarely survives in the archeological record, especially in Pleistocene contexts and knowledge of prehistoric hunter-gatherer lifeways is strongly biased by the survivorship of more resilient materials such as lithics and bones. Consequently, very few Paleolithic sites have produced wooden artifacts and among them, the site of Schöningen stands out due to its number and variety of wooden tools. The recovery of complete wooden spears and throwing sticks at this 300,000-y-old site (MIS 9) led to a paradigm shift in the hunter vs. scavenger debate. For the first time and almost 30 y after their discovery, this study introduces the complete wooden assemblage from Schöningen 13 II-4 known as the Spear Horizon. In total, 187 wooden artifacts could be identified from the Spear Horizon demonstrating a broad spectrum of wood-working techniques, including the splitting technique. A minimum of 20 hunting weapons is now recognized and two newly identified artifact types comprise 35 tools made on split woods, which were likely used in domestic activities. Schöningen 13 II-4 represents the largest Pleistocene wooden artifact assemblage worldwide and demonstrates the key role woodworking had in human evolution. Finally, our results considerably change the interpretation of the Pleistocene lakeshore site of Schöningen.

Genome-wide characterization of post-transcriptional processes related to wood formation in Dalbergia odorifera.

BACKGROUND: Alternative polyadenylation (APA), alternative splicing (AS), and long non-coding RNAs (lncRNAs) play regulatory roles in post-transcriptional processes in plants. However, little is known about their involvement in xylem development in Dalbergia odorifera, a valuable rosewood species with medicinal and commercial significance. We addressed this by conducting Isoform Sequencing (Iso-Seq) using PacBio's SMRT technology and combined it with RNA-seq analysis (RNA sequencing on Illumina platform) after collecting xylem samples from the transition zone and the sapwood of D. odorifera. RESULTS: We identified 14,938 full-length transcripts, including 9,830 novel isoforms, which has updated the D. odorifera genome annotation. Our analysis has revealed that 4,164 genes undergo APA, whereas 3,084 genes encounter AS. We have also annotated 118 lncRNAs. Furthermore, RNA-seq analysis identified 170 differential alternative splicing (DAS) events, 344 genes with differential APA site usage (DE-APA), and 6 differentially expressed lncRNAs in the transition zone when compared to the sapwood. AS, APA, and lncRNAs are differentially regulated during xylem development. Differentially expressed APA genes were enriched for terpenoid and flavonoid metabolism, indicating their role in the heartwood formation. Additionally, DE-APA genes were associated with cell wall biosynthesis and terpenoid metabolism, implying an APA's role in wood formation. A DAS gene (involved in chalcone accumulation) with a significantly greater inclusion of the last exon in the transition zone than in the sapwood was identified. We also found that differentially expressed lncRNAs targeted the genes related to terpene synthesis. CONCLUSIONS: This study enhances our understanding of the molecular regulatory mechanisms underlying wood formation in D. odorifera, and provides valuable genetic resources and insights for its molecular-assisted breeding.

Rare wooden artifacts show the smarts of early Neanderthals.

Complex tools from 300,000-year-old deposit at Schöningen in Germany point to a "wood age".

Probing the complexity of wood with computer vision: from pixels to properties.

We use data produced by industrial wood grading machines to train a machine learning model for predicting strength-related properties of wood lamellae from colour images of their surfaces. The focus was on samples of Norway spruce (Picea abies) wood, which display visible fibre pattern formations on their surfaces. We used a pre-trained machine learning model based on the residual network ResNet50 that we trained with over 15 000 high-definition images labelled with the indicating properties measured by the grading machine. With the help of augmentation techniques, we were able to achieve a coefficient of determination (R2) value of just over 0.9. Considering the ever-increasing demand for construction-grade wood, we argue that computer vision should be considered a viable option for the automatic sorting and grading of wood lamellae in the future.

Occupational injury prevalence and predictors among small-scale sawmill workers in the Sokoban Wood Village, Kumasi, Ghana.

BACKGROUND: Sawmill workers are at increased risk of occupational injuries due to their exposure to workplace hazards. However, little is known about the burden of occupational injuries among them in Ghana. Understanding its prevalence and associated factors is necessary to design appropriate interventions to improve workers' health and safety. This study sought to determine the prevalence and factors associated with occupational injuries among small-scale sawmill workers at Sokoban Wood Village, Kumasi. METHODS: A cross-sectional study was conducted among 138 small-scale sawmill workers from December 2020 to January 2021. Data was collected on demographic and work-related characteristics including age, sex, personal protective equipment (PPE), workspace design, and lighting. The primary outcome was the prevalence of occupational injuries in the 12 months preceding the survey. Logistic regression method was used to assess for independent predictors of occupational injuries, and associations were deemed statistically significant at p < 0.05. RESULTS: Approximately 66.7% of the workers experienced occupational injuries within the 12 months preceding the study. Cuts (69.6%) were the most commonly reported injuries. Injuries were mainly caused by machine parts/sharp objects (47.8%) and being hit by logs/objects (46.8%). Only 40.7% of the workers reported always using PPE while legs (38.0%) and hands (37.0%) were the most common body parts injured. The worker's monthly income, poor workspace design and poor lighting had increased odds of occupational injuries while an increase in age was associated with a 5% decreased odds of occupational injuries. CONCLUSION: The prevalence of occupational injuries among the sawmill workers at the Sokoban Wood Village was high, and this calls for prioritization of health and safety at the workplace. Essential measures required include improvements in the safety of machine tools, workspace design and lighting.

Integrated preparation of functional lignin nanoparticles and levulinic acid directly from the pre-hydrolysis liquor of poplar wood.

The pre-hydrolysis liquor (PHL) produced during pulp dissolution and biomass refining is mainly composed of hemicellulose and lignin, and it is a potential source for production of value-added materials and platform chemicals; however, their utilization has been a serious challenge. In this study, we proposed a green and simple strategy to simultaneously prepare size-controlled functional lignin nanoparticles (LNPs) and levulinic acid (LA) from PHL as the raw material. The as-prepared LNPs exhibited remarkable stability thanks to the presence of saccharides with abundant oxygen-containing groups and surface charges, which prevented aggregation and maintained long-term storage stability. Trace amounts of the LNPs (≤ 0.2 wt%) could stabilize various Pickering emulsions, even with oil-to-water ratios as high as 5:5 (v/v). Subsequently, the remaining PHL was directly used to produce LA without adding a catalyst; under optimal conditions (160 °C and 1 h), the yield of LA was 56.3 % based on the dry saccharide content in the raw PHL. More importantly, p-toluenesulfonic acid (p-TsOH), the only reactive reagent used during the entire preparation process, including the two preparation steps of the LNPs and LA, was reusable, and the recovery rate was >70 % after five cycles. Overall, this green and simple strategy effectively and comprehensively utilized the PHL and showed potential for producing biobased nanomaterials and platform chemicals.

Intransitivity in plant-soil feedbacks is rare but is associated with multispecies coexistence.

Although plant-soil feedback (PSF) is being recognized as an important driver of plant recruitment, our understanding of its role in species coexistence in natural communities remains limited by the scarcity of experimental studies on multispecies assemblages. Here, we experimentally estimated PSFs affecting seedling recruitment in 10 co-occurring Mediterranean woody species. We estimated weak but significant species-specific feedback. Pairwise PSFs impose similarly strong fitness differences and stabilizing-destabilizing forces, most often impeding species coexistence. Moreover, a model of community dynamics driven exclusively by PSFs suggests that few species would coexist stably, the largest assemblage with no more than six species. Thus, PSFs alone do not suffice to explain coexistence in the studied community. A topological analysis of all subcommunities in the interaction network shows that full intransitivity (with all species involved in an intransitive loop) would be rare but it would lead to species coexistence through either stable or cyclic dynamics.

A Spatial Signal of Niche Differentiation in Tropical Forests.

AbstractExplaining diversity in tropical forests remains a challenge in community ecology. Theory tells us that species differences can stabilize communities by reducing competition, while species similarities can promote diversity by reducing fitness differences and thus prolonging the time to competitive exclusion. Combined, these processes may lead to clustering of species such that species are niche differentiated across clusters and share a niche within each cluster. Here, we characterize this partial niche differentiation in a tropical forest in Panama by measuring spatial clustering of woody plants and relating these clusters to local soil conditions. We find that species were spatially clustered and the clusters were associated with specific concentrations of soil nutrients, reflecting the existence of nutrient niches. Species were almost twice as likely to recruit in their own nutrient niche. A decision tree algorithm showed that local soil conditions correctly predicted the niche of the trees with up to 85% accuracy. Iron, zinc, phosphorus, manganese, and soil pH were among the best predictors of species clusters.

Exploring research trends and priorities of genus Melia.

The genus Melia is known for its secondary metabolites and recently, this genus is being explored for its timber. There are vast differences among its species. For instance, Melia azedarach is reported to be invasive and while another species, M. dubia, has diverse utility with complex germination and regeneration characteristics. Researchers globally have been working on various aspects of this genus; In this study, using topic modelling and science mapping approach, we attempted to understand research facets on this genus. The literature corpus of the Web of Science database was explored using a single keyword-"Melia" which yielded 1523 publications (1946-2022) and after scrutiny metadata of 1263 publications were used in the study. Although nine individual species were cited in the publications, only three species are accepted viz., M. dubia, M. azedarach, and M. volkensii. This implies taxonomic uncertainty, with potential confusion in assigning scientific findings to particular species. Thus, a taxonomic relook on this genus is warranted for a better assessment of the economic utility in many countries. More importantly, our results indicate that the research interests have recently shifted from the secondary metabolite constituents towards growth, biomass, wood properties, germination, plantation, and green synthesis. The shift in research focus toward wood properties of Melia sp. can impact the wood demand-supply at a global scale owing to its fast growth and the possibility of cultivation over a wider geographical range.

Comparison of classification methods performance for defining the best reuse of waste wood material using NIR spectroscopy.

Recycling of post-consumer waste wood material is becoming an increasingly appealing alternative to disposal. However, its huge heterogeneity is calling for an assessment of the material characteristics in order to define the best recycling option and intended reuse. In fact, waste wood comes into a variety of uses/types of wood, along with several levels of contamination, and it can be divided into different categories based on its composition and quality grade. This study provides the measurement of more than a hundred waste wood samples and their characterisation using a hand-held NIR spectrophotometer. Three classification methods, i.e. K-nearest Neighbours (KNN), Principal Component Analysis - Linear Discriminant Analysis (PCA-LDA) and PCA-KNN, have been compared to develop models for the sorting of waste wood in quality categories according to the best-suited reuse. In addition, the classification performance has been investigated as a function of the number of the spectral measurements of the sample and as the average of the spectral measurements. The results showed that PCA-KNN performs better than the other classification methods, especially when the material is ground to 5 cm of particle size and the spectral measurements are averaged across replicates (classification accuracy: 90.9 %). NIR spectroscopy, coupled with chemometrics, turned out to be a promising tool for the real-time sorting of waste wood material, ensuring a more accurate and sustainable waste wood management. Obtaining real-time information about the quality and characteristics of waste wood material translates into a decision of the best recycling option, increasing its recycling potential.

An historical "wreck": A transcriptome assembly of the naval shipworm, Teredo navalis Linnaeus, 1978.

Historically famous for their negative impact on human-built marine wood structures, mollusc shipworms play a central ecological role in marine ecosystems. Their association with bacterial symbionts, providing cellulolytic and nitrogen-fixing activities, underscores their exceptional wood-eating and wood-boring behaviours, improving energy transfer and the recycling of essential nutrients locked in the wood cellulose. Importantly, from a molecular standpoint, a minute of omic resources are available from this lineage of Bivalvia. Here, we produced and assembled a transcriptome from the globally distributed naval shipworm, Teredo navalis (family Teredinidae). The transcriptome was obtained by sequencing the total RNA from five equidistant segments of the whole body of a T. navalis specimen. The quality of the produced assembly was accessed with several statistics, revealing a highly contiguous (1194 N50) and complete (over 90% BUSCO scores for Eukaryote and Metazoan databases) transcriptome, with nearly 38,000 predicted ORF, more than half being functionally annotated. Our findings pave the way to investigate the unique evolutionary biology of these highly modified bivalves and lay the foundation for an adequate gene annotation of a full genome sequence of the species.

Wood identification based on macroscopic images using deep and transfer learning approaches.

Identifying forest types is vital for evaluating the ecological, economic, and social benefits provided by forests, and for protecting, managing, and sustaining them. Although traditionally based on expert observation, recent developments have increased the use of technologies such as artificial intelligence (AI). The use of advanced methods such as deep learning will make forest species recognition faster and easier. In this study, the deep network models RestNet18, GoogLeNet, VGG19, Inceptionv3, MobileNetv2, DenseNet201, InceptionResNetv2, EfficientNet and ShuffleNet, which were pre-trained with ImageNet dataset, were adapted to a new dataset. In this adaptation, transfer learning method is used. These models have different architectures that allow a wide range of performance evaluation. The performance of the model was evaluated by accuracy, recall, precision, F1-score, specificity and Matthews correlation coefficient. ShuffleNet was proposed as a lightweight network model that achieves high performance with low computational power and resource requirements. This model was an efficient model with an accuracy close to other models with customisation. This study reveals that deep network models are an effective tool in the field of forest species recognition. This study makes an important contribution to the conservation and management of forests.

Disentangling the effect of growth from development in size-related trait scaling relationships.

In plant ecology, the terms growth and development are often used interchangeably. Yet these constitute two distinct processes. Plant architectural traits (e.g. number of successive forks) can estimate development stages. Here, we show the importance of including the effect of development stages to better understand size-related trait scaling relationships (i.e. between height and stem diameter). We focused on one common savanna woody species (Senegalia nigrescens) from the Greater Kruger Area, South Africa. We sampled 406 individuals that experience different exposure to herbivory, from which we collected four traits: plant height, basal stem diameter, number of successive forks (proxy for development stage), and resprouting. We analysed trait relationships (using standardized major axis regression) between height and stem diameter, accounting for the effect of ontogeny, exposure to herbivory, and resprouting. The number of successive forks affects the scaling relationship between height and stem diameter, with the slope and strength of the relationship declining in more developed individuals. Herbivory exposure and resprouting do not affect the overall height-diameter relationship. However, when height and stem diameter were regressed separately against number of successive forks, herbivory exposure and resprouting had an effect. For example, resprouting individuals allocate more biomass to both primary and secondary growth than non-resprouting plants in more disturbed conditions. We stress the need to include traits related to ontogeny so as to disentangle the effect of biomass allocation to primary and secondary growth from that of development in plant functional relationships.

Tree parameter extraction in Fokienia hodginsii plantation based on airborne LiDAR data.

Accurate and efficient extraction of tree parameters from plantations lay foundation for estimating individual wood volume and stand stocking. In this study, we proposed a method of extracting high-precision tree parameters based on airborne LiDAR data. The main process included data pre-processing, ground filtering, individual tree segmentation, and parameter extraction. We collected high-density airborne point cloud data from the large-diameter timber of Fokienia hodginsii plantation in Guanzhuang State Forestry Farm, Shaxian County, Fujian Province, and pre-processed the point cloud data by denoising, resampling and normalization. The vegetation point clouds and ground point clouds were separated by the Cloth Simulation Filter (CSF). The former data were interpolated using the Delaunay triangulation mesh method to generate a digital surface model (DSM), while the latter data were interpolated using the Inverse Distance Weighted to generate a digital elevation model (DEM). After that, we obtained the canopy height model (CHM) through the difference operation between the two, and analyzed the CHM with varying resolutions by the watershed algorithm on the accuracy of individual tree segmentation and parameter extraction. We used the point cloud distance clustering algorithm to segment the normalized vegetation point cloud into individual trees, and analyzed the effects of different distance thresholds on the accuracy of indivi-dual tree segmentation and parameter extraction. The results showed that the watershed algorithm for extracting tree height of 0.3 m resolution CHM had highest comprehensive evaluation index of 91.1% for individual tree segmentation and superior accuracy with R2 of 0.967 and RMSE of 0.890 m. When the spacing threshold of the point cloud segmentation algorithm was the average crown diameter, the highest comprehensive evaluation index of 91.3% for individual tree segmentation, the extraction accuracy of the crown diameter was superior, with R2 of 0.937 and RMSE of 0.418 m. Tree height, crown diameter, tree density, and spatial distribution of trees were estimated. There were 5994 F. hodginsii, with an average tree height of 16.63 m and crown diameter of 3.98 m. Trees with height of 15-20 m were the most numerous (a total of 2661), followed by those between 10-15 m. This method of forest parameter extraction was useful for monitoring and managing plantations.

The potential use of mass timber in mid-to high-rise construction and the associated carbon benefits in the United States.

Nonresidential and mid- to high-rise multifamily residential structures in the United States currently use little wood per unit floor area installed, because earlier building codes lacked provisions for structural wood use in those types of buildings. However, revisions to the International Building Code allow for increased wood use in the form of mass timber, as structural and fire safety concerns have been addressed through new science-based design standards and through newly specified construction materials and measures. This study used multiple models to describe alternative futures for new construction, mass timber adoption rates, and the associated carbon benefits in higher than three-story buildings in the United States. The use of mass timber, in place of traditional constructions (i.e., structures dominated by concrete and steel), in projected new higher than three-story buildings was shown to provide combined carbon benefits (i.e., global warming mitigation benefits), including avoided embodied carbon emissions due to the substitution of non-wood alternatives and additional biogenic carbon storage in mass timber materials, of between 9.9 and 16.5 million t CO2e/yr spanning 50 years, 2020 to 2070. These carbon benefits equate to 12% to 20% of the total U.S. harvested wood products carbon storage for 2020. Future research is needed to understand how greater mass timber adoption leads to changes in forest product markets, land use, and total forest sector carbon.

Development of methodology for identification and assessment of ecosystems with an underground source of tritium.

The article considers the issues of working out the suitable approaches for identifying zones with the presence of underground near-surface waters with increased concentrations of tritium discharged into a surface reservoir. The following methods were used as possible methods: determination of tritium content in snow cover, determination of tritium content in vegetation in the form of tritium of free water and organically bound tritium, determination of tritium content in river water and coastal vegetation. The studies were carried out at a previously identified site where groundwater with a tritium concentration of up to 6000 Bq/l is present, located in the vicinity of the city of Obninsk (Kaluga region, Russia). As a result of the conducted research, it was concluded that the analysis of the distribution of tritium in vegetation is an excellent methodological technique for identifying areas of location of near-surface underground waters contaminated with tritium. As a control parameter, both the concentration of tritium in the free water of plants and the content of organically bound tritium can be used. To detect underground tritium contamination the most promising use is the following indicator - the content of OBT in the shoots of woody plants. This parameter is very informative, and the sampling procedure for its determination has no seasonal restrictions, unlike such parameters as the content of tritium in grass and leaves, the content of tritium in snow cover, surface waters, which are preferably collected only in summer or winter. It should be noted that the control of surface waters of the groundwater discharge zone may not be a sufficiently informative indicator for identifying areas of polluted water inflow, since it depends on the ratio of the volumes of leaking polluted groundwater and the annual flow of the watercourse.

Life cycle assessment and techno-economic analysis of wood-based biorefineries for cellulosic ethanol production.

Poplar is widely used in the paper industry and accompanied by abundant branches waste, which is potential feedstock for bioethanol production. Acid-chlorite pretreatment can selectively remove lignin, thereby significantly increasing enzymatic efficiency. Moreover, lignin residues valorization via gasification-syngas fermentation can achieve higher fuel yield. Herein, environmental and economic aspects were conducted to assess technological routes, which guides further process optimization. Life cycle assessment results show that wood-based biorefineries especially coupling scenarios have significant advantages in reducing global warming potential in contrast to fossil-based automotive fuels. Normalization results indicate that acidification potential surpasses other indicators as the primary impact category. In terms of economic feasibility, coupling scenarios present better investment prospects. Bioethanol yield is the most critical factor affecting market competitiveness. Minimum ethanol selling price below ethanol international market price is promising with higher-levels technology. Further work should be focused on technological breakthrough, consumable reduction or replacement.

Dendrochronology: Large datasets help explain when and how trees grow but not why.

A meta-analysis of a large dataset of wood cell formation observations from several tree species in the Northern Hemisphere suggests that the 5th of June is favorable for cell division and enlargement, while the summer solstice promotes cell wall thickening.

Revealing the structural changes of lignin in Chinese quince (Chaenomeles sinensis) fruit as it matures.

Chinese quince fruits (Chaenomeles sinensis) contain substantial amounts of lignin; however, the exact structure of lignin remains to be investigated. In this study, milled wood lignins (Milled wood lignin (MWL)-1, MWL-2, MWL-3, MWL-4, MWL-5, and MWL-6) were extracted from fruits harvested once a month from May to October 2019 to investigate their structural evolution during fruit growth. The samples were characterized via High-performance anion exchange chromatography (HPAEC), Fourier transform-infrared spectroscopy (FT-IR), gel permeation chromatography (GPC), thermogravimetric (TGA), pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) and NMR (2D-heteronuclear single quantum coherence (HSQC) and 31P). The MWL samples in all fruit growth stages were GS-type lignin and lignin core undergoing minimal alterations during fruit development. The predominant linkage in the lignin structure was ß-O-4', followed by ß-ß' and ß-5'. Galactose and glucose were the main monosaccharides associated with MWL. In MWL-6, the lignin exhibited the highest homogeneity and thermal stability. As the fruit matured, a gradual increase in the ß-O-4' proportion and the ratio of S/G was observed. The results provide comprehensive characterization of the cell wall lignin of quince fruit as it matures. This study could inspire innovative applications of quince fruit lignin and provide the optimal harvest time for lignin utilization.

Preparation of tannic acid-reinforced cellulose nanofiber composites for all-water-based high-performance wood adhesives.

Traditional adhesives easily release toxic gases during the preparation process or apply to wood composite products, which have adverse effects on the human body and the environment. Herein, an all-water-based high-performance wood adhesive is prepared using TEMPO-oxidized cellulose nanofiber (TOCNF), acrylamide (AM), and tannic acid (TA) through free radical polymerization. Different characteristics of the prepared composites, including morphology, injectability, and adhesion properties, have been investigated. Results showed that the TA/TOCNF/PAM composite has excellent injectability. The addition of TA can enhance the lap shear strength of the TA/TOCNF/PAM composites and with the increment of TA content, the lap shear strength gradually decreases. The formation of effective hydrogen bonds and Van der Waals interaction among the rich functional groups in the composite, lead to strong lap shear strength on different substrates. The composite with 5.0 g of AM, 5.0 g of the TOCNF suspension and 0.1 g TA possesses a high lap shear strength of 10.5 MPa on wood and 1.5 MPa on aluminium. Based on strong adhesion properties and excellent injectability, the TA/TOCNF/PAM composites have great potential in the furniture construction and building industries.