Wood Density Research Articles

Hydraulic and structural traits of trees across light gradients in the Amazon secondary forest.

Amazonian species are generally unable to adapt to long drought periods, indicating a low capacity to adjust their hydraulic traits. Secondary forests account for 20% of forest cover in the Amazon, making natural regeneration species crucial under climate change scenarios. In this study, we compared the hydraulic traits of five species, including non-pioneers (Bertholletia excelsa Bonpl., Carapa guianensis Aubl., Hymenaea courbaril L.) and pioneers (Cedrela fissilis Vell., Tabebuia rosea (Bertol.) Bertero ex A.DC.), across light conditions (understory, intermediate, gap) in a 22-year-old secondary forest in Central Amazon, Brazil. Twenty-five saplings were planted and monitored in 3 plots × 5 blocks. Five years after the plantation, we assessed growth, wood density, leaf water potential at predawn and midday, xylem embolism resistance (P50), and hydraulic safety margins (HSM). Leaf water potential ranged from -2.9 to 0MPa. The non-pioneer species C. guianensis and H. courbaril exhibited the lowest P50 (-4.06MPa), indicating higher embolism resistance, whereas the pioneer T. rosea had the highest P50 (-1.25MPa), indicating lower resistance. HSM varied from -1.60 to 3.26MPa, with lower values in gap conditions during the dry period (-1.60MPa), especially affecting pioneer species. Wood density was influenced by both light and species type, with non-pioneers showing generally higher density, with H. courbaril reached 0.75gcm-3 in the understory while the pioneer T. rosea showed the lowest density (0.27gcm-3). These results highlight that light conditions affect hydraulic traits differently across species strategies, especially during early growth. Non-pioneer, slow-growing native species appear more resilient to light variation, making them suitable for future plantations aimed at climate adaptation in secondary forests.

Analysis of the relationship between cutting forces and local structural properties of Scots pine wood aided by computed tomography

AbstractX-ray computed tomography (CT) is utilised in some sawmills today, primarily for enhancing value yield and for process automation, which includes log sorting and sawing optimisation. Nevertheless, there is a scarcity of recent research utilising CT to assess the local cutting process. As a preliminary study, this paper addresses this gap by using CT to investigate the connections between local cutting force and local wood properties including density, knots, and annual ring width. Workpieces of Scots pine (Pinus sylvestris L.), from Sweden and Poland, were CT-scanned in laboratory conditions. Quasi-linear cutting tests were then performed on both clear and knotty regions of the workpieces using a custom-made laboratory stand with a Stellite-tipped tooth mounted on piezoelectric sensors. It was found that density influences cutting forces for both clear and knotty wood, and this effect increased noticeably with increasing uncut chip thickness. Changes in wood density, such as between sapwood and heartwood or between clear wood and knot, caused dynamic changes in cutting forces and temporary disturbances to the stability of the system. Normalisation of cutting forces by local density allowed the conclusion that density is not the only property affecting cutting forces. Other structural properties, e.g. annual ring width and latewood–earlywood proportion may affect the cutting process as well, which requires deeper analysis in the future research. This preliminary study demonstrates the feasibility and usefulness of coupling CT data with cutting force measurements and suggests further research on the relationship between cutting force and wood properties.

Mistletoes have higher hydraulic safety but lower efficiency in xylem traits than their hosts.

Both mistletoes and their hosts are challenged by increasing drought, highlighting the necessity of understanding their comparative hydraulic properties. The high transpiration of mistletoes requires efficient water transport, while high xylem tensions demand strong embolism resistance, representing a hydraulic paradox. This study, conducted across four environments with different aridity indices in Yunnan, China, examined the xylem traits of 119 mistletoe-host species pairs. Mistletoes showed lower water use efficiency, indicating a more aggressive water use. They also showed lower hydraulic efficiency (lower vessel diameter and theoretical hydraulic conductivity) but higher safety (lower vulnerability index and higher conduit wall reinforcement, vessel grouping index, and wood density) compared with their hosts, supporting the trade-off between efficiency and safety. Environmental variation across sites significantly affected xylem trait comparisons between mistletoes and hosts. Additionally, the xylem traits of mistletoes were strongly influenced by host water supply efficiency. The overall xylem trait relationships in mistletoes and hosts were different. These findings stress the impact of host and site on the hydraulic traits of mistletoes, and suggest that mistletoes may achieve high transpiration by maintaining high stomatal conductance under low water potentials. This study illuminates the distinctive adaptation strategies of mistletoes due to their parasitic lifestyle.

Tree traits are a stronger predictor of bee traits and species richness than taxonomic diversity

Abstract Functional traits help to understand biological diversity and the mechanism by which ecological communities are structured and how they respond to the environment. For example, the high tree species diversity within tropical forests can be grouped into a few functional attributes, wood density, size and dependence on animal pollination or seed dispersal. However, little is known about how these traits influence animal taxonomic and functional diversity in the forests. We carried out a vegetation census on six plots (20 × 100 m) within the National Forest of Carajás (Amazon biome) to identify forest canopy species and their functional traits. Within the same plot, we also applied three bee sampling methods (entomological nets, honey traps and scent traps). By characterizing the functional traits of trees and bees, we were able to predict bee functional diversity better than with taxonomic diversity alone via combinations of tree traits like size, wood density, dependence on pollinators and extinction risk. We found that larger trees with low wood density were negatively associated with small, eusocial tree cavity nesting bees. The richness and abundance of trees with high extinction risk was positively associated with the richness of medium‐sized solitary bees. The dominance in the community of pollinator‐dependent trees (average diameter in the basal area) was negatively associated with the richness of above‐ground and cavity nesting bees. Our findings suggest that the composition of the tree community limits the availability of nesting resources for specific groups of bees. Moreover, the presence of trees with higher extinction risk (conservation value) was associated with a greater variety of bee traits and was the only metric associated with overall bee richness. As expected, functional traits shed light on the mechanism that might drive high diversity within tropical forests. In addition, there appears to be complementarity in terms of conservation value and carbon stock potential, as areas that habour tree species with higher extinction risk and higher wood density are also those with overall greater bee and functional diversity. Finally, our study can contribute to the restoration of plant—pollinator community by providing an understanding of the vegetation community that contributes to biodiversity maintenance. Read the free Plain Language Summary for this article on the Journal blog.

MAPPING WOOD DENSITY VARIATION USING QGIS: AN INNOVATIVE APPROACH FOR CHARACTERIZATION OF OCHROMA PYRAMIDALE, ACACIA MANGIUM, EUCALYPTUS GRANDIS, AND PINUS SP.

This study explores the innovative application of QGIS for mapping radial wood density variation across the entire cross-section of selected native and non-native forest species, aiming to enhance wood characterization. Using samples from Ochroma pyramidale, Acacia mangium, Eucalyptus grandis, and Pinus sp., we applied X-ray densitometry to obtain high-resolution images, which were then analyzed with QGIS to create detailed density maps. These maps provided a clear visualization of radial density variation, offering insights into the internal structure of the wood. The integration of QGIS with X-ray densitometry proved to be an effective tool for assessing wood density variation, supporting more precise and sustainable forest management practices.

Non-Destructive Wood Analysis Dataset: Comparing X-Ray and Terahertz Imaging Techniques

Wood density measurement plays a crucial role in assessing wood quality and predicting its mechanical performance. This dataset was collected to compare the accuracy and reliability of two non-destructive techniques, X-rays and terahertz waves, for measuring wood density. While X-rays have been commonly used in the industry due to their effectiveness, they pose health risks due to ionizing radiation. Terahertz waves, on the other hand, are non-ionizing and offer high spatial resolution. This article presents a database of wood samples measurements obtained using both techniques, on the same 110 samples with a fine location of the measuring points, on a wide range of wood species (tropical and temperate ones) and densities, from 111 kg·m−3 to 1086 kg·m−3. The database includes X-ray and terahertz scans, sample dimensions, moisture content, and color photographs.

Aridity and forest age mediate landscape scale patterns of tropical forest resistance to cyclonic storms

Abstract Cyclonic storms, or hurricanes, are expected to intensify as ocean heat energy rises due to climate change. Ecological theory suggests that tropical forest resistance to hurricanes should increase with forest age and wood density. However, most data on hurricane effects on tropical forests come from a limited number of well‐studied long‐term monitoring sites, restricting our capacity to evaluate the resistance of tropical forests to hurricanes across broad environmental gradients. In this study, we assessed whether forest age and aridity mediate the effects of hurricanes Irma and Maria in Puerto Rico, Vieques and Culebra islands. We leveraged functional trait data for 410 tree species, remotely sensed measurements of canopy height and cover, along with data on forest stand characteristics of 180 of 338 forest monitoring plots, each covering an area of 0.067 ha. The plots represent a broad mean annual precipitation (MAP) gradient from 701 to 4598 mm and a complex mosaic of forest age from 5 to around 85 years since deforestation. Hurricanes resulted in a 25% increase in basal area mortality rates, a 45% decrease in canopy height and a 21% reduction in canopy cover. These effects intensified with forest age, even after considering proximity to the hurricane path. The links between forest age and hurricane disturbances were likely due the prevalence of tall canopies. Tall forest canopies were strongly linked with low community‐weighted wood density (WD). These characteristics were on average more common in moist and wet forests (MAP >1250 mm). Conversely, dry forests were dominated by short species with high wood density (WD > 0.6 g cm−3) and did not show significant increases in basal area mortality rates after the hurricanes. Synthesis. Our findings show that selection towards drought‐tolerant traits across aridity gradients, such as short stature and dense wood, enhances resistance to hurricanes. However, forest age modulated responses to hurricanes, with older forests being less resistant across the islands. This evidence highlights the importance of considering the intricate links between ecological succession and plant function when forecasting tropical forests’ responses to increasingly strong hurricanes.

The Impact of Salvage Logging on Deadwood Decomposition and Forest Regeneration: A Case Study in Tatra National Park, Slovakia

In November 2004, a severe windstorm destroyed large portions of the spruce-dominated forests in the Tatra National Park (northern Slovakia). This study focused on the status of deadwood and its influence on post-disturbance forest regeneration 18 years after the destruction. Since some disturbed areas were salvaged and others were not, we could compare the situations between these two management approaches. Therefore, 40 research sites (20 salvaged and 20 unsalvaged) were analyzed; each contained four satellite plots, i.e., circle-like areas with a radius of 3 m. We measured the diameter of deadwood and its decay status (classes 1–5) and recorded the sizes (stem base diameter and height) as well as species of young trees. Our results showed that while salvage conditions and contact with soil stimulated deadwood decomposition, the diameter of logs was not a significant factor. The highest decay class (3.83) was found in deadwood in salvaged areas and touching the soil, while the lowest decay class (3.10) was found in deadwood in unsalvaged areas and in the case of logs not touching the soil. Although carbon content (based on the percentage of wood mass) did not change with the decay class, wood density decreased sharply with decay, and deadwood moisture increased. We also found that the different post-disturbance management strategies influenced forest regeneration. Significantly higher tree diversity was observed in salvaged sites (5.40 species per plot) compared to unsalvaged sites (3.85 species per plot). At the same time, while sites with logging were predominantly covered by broadleaved species, those without logging were typically dominated by Norway spruce (Picea abies L. Karst). Our findings suggest that although salvage logging reduced the carbon and total water content in deadwood, it can promote tree species diversity. Therefore, the currently prevailing opinion about the exclusively negative effects of salvage logging on the forest environment should be accepted with caution, and local conditions must be considered before making broad judgments.

Flame spread characteristics of densified wood with various sample widths and densities

Densified wood (DW) is a novel functional material with great mechanical properties, its structural characteristics make it attractive as an ideal building material for mid-to-high-rise timber constructions. However, its flame spread characteristics is not yet fully understood, which threatens its further developments and applications. This study experimentally and analytically investigates the impact of density and width on the flame spread behaviors and heat transfer characteristics of DW. Flame spread rate, mass loss rate (MLR), and flame height decrease with increasing wood density. Both MLR and flame height increase with the increasing width, while flame spread rate increases first and then decreases. Dimensionless power-law relationships among them were established, which well predict the measurements. The dominant gaseous heat transfer transits from radiation to convection with the increase of density. The critical density for this transition is increased with width. Both width and density impact the preheating length and total heat flux, which are combined to influence the flame spread rate. A dimensionless correlation among them was established with an R2 of 0.915 to the experiments of current and previous publications. This work helps to understand flame spread of DW and benefits the fire safety in timber construction.

CTRing: An R package to extract wood density profiles from computed tomography images of discs and logs

Accurately determining the position of pith and accessing tree-ring density profiles, including intra-ring variations, is important for both the forest industry and dendroclimatology. Although several available methods exist for acquiring this information, such as X-ray computed tomography (CT), micro-CT, and X-ray films, the availability of open-source programs for extracting data remains limited. The CTRing package in the R environment integrates a series of functions to detect precisely the pith and tree-ring boundaries and generate tree-ring density profiles using CT images of tree cross sections. Before processing, grey values are transformed into density using a calibration function. Pith position is then detected by combining an adapted Hough Transform method and a one-dimensional edge detector. Tree-ring profiles along the pith-to-bark path of interest are inspected visually, and tree-ring boundaries can be easily added or removed manually via a graphical user interface. After correcting for tree-ring boundaries, the inflection points of a 3rd-degree polynomial obtained from density profiles are used to delimit the earlywood–latewood transition. We tested this package using 60 CT-scanned images of white spruce (Picea glauca (Moench) Voss) discs collected at various tree heights (0%, 25%, 50% and 75% of the total tree height as well as at 1.3m). The pith detection function had an average mean error of 0.72mm with 95% of the automatically detected pith locations that differed by less than 2mm from their manually located positions. Error decreased toward the apex of the tree. The functions of the CTRing package are flexible and can be easily implemented or adapted. The package could also be used with simple images of discs to obtain ring-width time series; however, this use must be evaluated further. Future work with this package involves assessing the use of low-quality images and ring-porous species.

GROWTH AND WOOD TRAITS EVALUATION OF 15-YEAR-OLD TENGKAWANG (Shorea spp.) TREE STANDS IN GUNUNG WALAT UNIVERSITY FOREST, WEST JAVA, INDONESIA

Gunung Walat University Forest (GWUF) in Sukabumi Regency, Indonesia, plays a crucial role in providing various ecosystem services. Five important Shorea trees, i.e., S. stenoptera, S. mecisopteryx, S. pinanga, S. palembanica, and Shorea leprosula have been planted in GWUF as an effort for its conservation and object of research. An evaluation of the adaptability and suitability of these species to the GWUF ecosystem, as well as their wood characteristics, needs to be carried out regularly. Therefore, the study aimed to examine the growth performances and physical wood properties of five Shorea species, i.e., Shorea stenoptera, S. mecisopteryx, S. pinanga, S. palembanica, and S. leprosula at the age of 15-year-old planted in GWUF. The results indicated that S. leprosula exhibited the best growth performance in terms of average diameter (19.64 cm), volume (0.27 m3), slenderness (126.58), and wood density (0.94 g/cm3), and S. stenoptera showed the best performance in average height (23.35 m). While the poor performance was shown by S. palembanica in terms of average diameter (6.73 cm), height (11.15 m), volume (0.02 m3), wood density (0.87 g/cm3), and specific gravity (0.45), and S. stenoptera in terms of average slenderness (202.73). In addition, significant differences in tree height, diameter, volume, wood density, specific gravity, and moisture content were found in S. palembanica compared with other species. The relationship between the growth and physical wood properties parameters varied between species. The study revealed that planting the five Shorea species in GWUF is suitable for increasing vegetation cover and conserving the species.

Stem Longitudinal Gradient for Basic Density, Carbon, Nitrogen, and CN Ratio in Khaya spp.: Improved Correlation Using Diameter Instead of Commercial Height

The basic wood density influences the carbon stock, playing a crucial role in climate-changing global mitigation through carbon sequestration. Understanding wood carbon release depends on the Nitrogen assessment and CN ratio. Therefore, our research aimed to: (i) Compare basic density, organic carbon, nitrogen, and C/N ratio among the Khaya grandifoliola, K. ivorensis, and K. senegalensis; (2) Analyze the gradient along positions and diameter of the commercial stem; (3) Recommend the most representative sampling position for each species based on the diameter. The experimental area is located in Southeastern Brazil. Twelve average-diameter trees per species were cut down, and wood disc samples were collected at 0, 25, 50, 75, and 100% commercial height. Our results show statistical differences in wood basic density among the species, and K. senegalensis has the highest basic density, 592 kg m3. There was no statistical difference in organic carbon between species and along the stem. Stem diameter instead of commercial height improved the variable studied, confirming the research hypothesis. Sampling at 17% of the commercial height, ranging to 18–22 cm stem diameters, is recommended for greater representativeness.

The effect of seasonal temperature difference on estimated wood density in Populus ussuriensis Kom. trees by the resistance drilling method

ABSTRACT Wood density is a main determinant of wood quality assessment for wood end-use and plantation trees. The resistance drilling method (RST) is one of the rapid assessment methods of wood density for standing trees. As the season changes, the water within trees occurs to freeze and is expected to indirectly affect RST results. However, the impact of ambient temperature is unknown. To investigate the effect of seasonal temperature difference on estimated wood density, the RST of Populus ussuriensis Kom. trees was examined across different seasons. A good linear regression model between average wood density and RST was established at normal temperature during summer, with a coefficient of determination of 0.708. The average RST of sapwood and heartwood increased by 6% to 22% from autumn (−5–0°C) to winter (−20–−10°C) compared to normal temperature in summer. Correspondingly, the average wood density estimated by RST increased by 4% to 16% from autumn to winter relative to normal temperature. The quadratic polynomial functions described the relationship between relative RST, relative wood density and seasonal temperature, with coefficients of determination over 0.922. Seasonal temperature had a significant effect on wood density, which was overestimated by RST in winter. This overestimation should be considered in the RST application.

Stiffness and hardness of thermally modified timber assessed with explainable machine learning

Thermal modification is an environmentally friendly practice to enhance the durability of wood. Despite the method's effectiveness in improving wood durability and dimensional stability, the mechanical properties of wood could be compromised following the heat treatment process. While most of the literature has focused on studying the impact of wood modification on stiffness or strength, less attention was given to characterization and nondestructive prediction of wood hardness following thermal treatment. Hardness, an important quality indicator of wood, has been a subject of limited research in the context of developing predictive models for assessing the hardness of thermally modified wood. The existing research in this area has either been scarce or unsuccessful, with poor predictive performance being a common issue. This research studies the impact of thermal modification on the longitudinal and transverse hardness of some common North American softwoods (Douglas-fir, Western hemlock, red cedar) and hardwoods (red alder, paper birch). It also aims to develop an explainable machine-learning (TreeNet gradient boosting machine) predictive model for hardness prediction using stress wave data combined with wood density and information about the type of wood species and heat treatment level. The impact of heat treatment on the stress wave velocity, density, and hardness was studied, and the dependency of the variables was assessed using correlation and clustering analysis. Machine learning modeling showed that the longitudinal and transverse hardness could be predicted by having a maximum R2 (test data) of 70.62 and 72.78, respectively, with a relative importance of the predictors in descending order as wood species > density > wave velocity >MOEdyn> heat treatment. Using the top 3 critical parameters yielded an R2 (test data) of ∼69 % for both models. The developed model could predict the hardness of various wood species treated at different temperatures, having only the type of wood species and its density followed by the stress wave velocity, which can be measured at an industrial scale.

Genomic selection in forest trees comes to life: unraveling its potential in an advanced four-generation Eucalyptus grandis population.

Genomic Selection (GS) in tree breeding optimizes genetic gains by leveraging genomic data to enable early selection of seedlings without phenotypic data reducing breeding cycle and increasing selection intensity. Traditional assessments of the potential of GS in forest trees have typically focused on model performance using cross-validation within the same generation but evaluating effectively realized predictive ability (RPA) across generations is crucial. This study estimated RPAs for volume growth (VOL), wood density (WD), and pulp yield (PY) across four generations breeding of Eucalyptus grandis. The training set spanned three generations, including 34,461 trees with three-year growth data, 6,014 trees with wood quality trait data, and 1,918 trees with 12,695 SNPs (single nucleotide polymorphisms) data. Employing single-step genomic BLUP, we compared the genomic predictions of breeding values (GEBVs) for 1,153 fourth-generation full-sib seedlings in the greenhouse with their later-collected phenotypic estimated breeding values (EBVs) at age three years. RPAs were estimated using three GS targets (individual trees, trees within families, and families), two selection criteria (single- and multiple-trait), and training populations of either all 1,918 genotyped trees or the 67 direct ancestors of the selection candidates. RPAs were higher for wood quality traits (0.33 to 0.59) compared to VOL (0.14 to 0.19) and improved for wood traits (0.42 to 0.75) but not for VOL when trained only with direct ancestors, highlighting the challenges in accurately predicting growth traits. GS was more effective at excluding bottom-ranked candidates than selecting top-ranked ones. The between-family GS approach outperformed individual-tree selection for VOL (0.11 to 0.16) and PY (0.72 to 0.75), but not for WD (0.43 vs. 0.42). Furthermore, higher levels of relatedness and lower genotype by environment (G × E) interaction between training and testing populations enhanced RPAs for VOL (0.39). In summary, despite limited effectiveness in ranking top VOL individuals, GS effectively identified low-performing individuals and families. These multi-generational findings underscore GS's potential in tree breeding, stressing the importance of considering relatedness and G × E interaction for optimal performance.

Linking seedling wood anatomical trade-offs with drought and seedling growth and survival in tropical dry forests.

Wood anatomy plays a key role in plants' ability to persist under drought and should therefore predict demography. Plants balance their resource allocation among wood cell types responsible for different functions. However, it remains unclear how these anatomical trade-offs vary with water availability, and the extent to which they influence demographic rates. We investigated how wood anatomical trade-offs were related to drought and demographic rates, for seedling communities in four tropical dry forests differing in their aridity indexes (AIs). We measured wood density, as well as vessel, fiber and parenchyma traits of 65 species, and we monitored growth and survival for a 1-yr period. Two axes defined wood anatomical structure: a fiber-parenchyma axis and a vessel-wood density axis. Seedlings in drier sites had larger fiber but lower parenchyma fractions, while in less dry forests, seedlings had the opposite allocation pattern. The fiber-parenchyma trade-off was unrelated to growth but was positively related to survival, and this later relationship was mediated by the AI. These findings expand our knowledge about the wood anatomical trade-offs that mediate responses to drought conditions and influence demographic rates, in the seedling layer. This information is needed to anticipate future responses of forests to changing drought conditions.

Intraspecific Variability of Xylem Hydraulic Traits of Calligonum mongolicum Growing in the Desert of Northern Xinjiang, China.

Plant hydraulic traits are essential for understanding and predicting plant drought resistance. Investigations into the mechanisms of the xylem anatomical traits of desert shrubs in response to climate can help us to understand plant survival strategies in extreme environments. This study examined the xylem anatomical traits and related functional traits of the branches of seven Calligonum mongolicum populations along a precipitation gradient, to explore their adaptive responses to climatic factors. We found that (1) the vessel diameter (D), vessel diameter contributing to 95% of hydraulic conductivity (D95), hydraulic weighted vessel diameter (Dh), vessel density (VD), percentage of conductive area (CA), thickness-to-span ratio of vessels ((t/b)2), and theoretical hydraulic conductivity (Kth) varied significantly across sites, while the vessel group index (Vg), wood density (WD), and vulnerability index (VI) showed no significant differences. (2) Principal component analysis revealed that efficiency-related traits (Kth, Dh, D95) and safety-related traits (VI, VD, inter-wall thickness of the vessel (t)) were the primary factors driving trait variation. (3) Precipitation during the wettest month (PWM) had the strongest influence, positively correlating with (t/b)2 and negatively with D, D95, Dh, CA, and Kth. (4) Structural equation modeling confirmed PWM as the main driver of Kth, with indirect effects through CA. These findings indicate that C. mongolicum displays high plasticity in xylem traits, enabling adaptation to changing environments, and providing insight into the hydraulic strategies of desert shrubs under climate change.

Unraveling key environmental drivers of spatial variation in plant functional traits: Insights from Dacrydium pectinatum de Laub. in natural communities on Hainan Island, China

Accurate predictions of species distribution and coexistence in response to environmental changes depend on a thorough understanding of how functional traits relate to environmental conditions. However, there is still limited evidence regarding the sources of functional trait variation and the environmental mechanisms that regulate these traits in tropical forests. This study focuses on Dacrydium pectinatum de Laub., a crucial and endangered species native to the tropical mountain forests of Hainan Island, China. We gathered functional trait data from 68 permanent plots of D. pectinatum situated in three regions: Bawangling (163 tree species), Diaoluoshan (127 tree species), and Jianfengling (175 tree species). Nine functional traits were measured at the species level, and their variation patterns and sources were analyzed using linear mixed-effects models and variance decomposition methods. Our findings reveal that environmental pressures cause variations in trait relationships across different site conditions at the species level. Typically, inter-specific trait variation exceeds intra-specific variation, particularly for leaf area (LA) and specific leaf area (SLA). This indicates that trait variability is influenced by how species adapt to and balance specific environmental conditions. Site conditions significantly impact trait variation, especially for SLA, leaf dry matter content (LDMC), and wood density (WD). Additionally, intraspecific variation is notable for certain traits, reflecting individual responses to environmental heterogeneity. At the community level, eight out of nine traits exhibit significant changes in community-weighted mean (CWM) across various site conditions and environmental gradients. For instance, LA's CWM increases with soil fertility, whereas SLA, leaf nitrogen content (LNC), and leaf phosphorus content (LPC) show differences between site conditions. LDMC and WD decrease significantly in high-fertility environments, suggesting a transition from resource conservation to resource acquisition strategies within communities as soil fertility rises. Geographic variables play a crucial role in trait distributions across different community levels, with elevation and soil factors also contributing significantly to trait variation. Overall, our study provides direct evidence of how environmental filtering influences plant functional trait distributions and community assembly. Future research should explore the mechanisms driving these trait-environment relationships and their responses across various ecological contexts.

Clustering of tropical species through multivariate analysis of the bonding properties of edge-glued panels (EGP)

Tropical woods have high added value, and the use of waste for panel production is an initiative to add more value to this material, typically consisting of various species. The use of raw materials from tropical solid wood waste in the Amazon region contributes to the reduction of carbon emissions associated with the burning of this material. In this context, this study aimed to cluster species based on the bonding properties of Amazonian woods by applying multivariate analysis. The apparent density 12% and strength of finger joint and edge-glued joints of Cedrela odorata, Enterolobium schomburgkii, Erisma uncinatum and Qualea paraensis was evaluated which were joined in homogeneous and hybrid configurations with the adhesives PVA and EPI, as spreading rate of 180 g/m2. The treatments were compared by multivariate analysis of variance and discriminant analysis. The discrimination of species and combinations based on wood density (low, medium, and high) revealed that this is the most important characteristic for grouping different species that make up tropical hardwood waste for the production of EGP panels. In practice, the separation of species into groups according to wood densities can contribute to a better definition of the indications for use of edge glued panels of each density class, and assertive targeting for applications according to the strength ranges required. In the static bending, parallel tensile and shear tests all species and their combinations met the minimum requirements normative, indicating the approval of species and combinations studied for the production of EGP panels.

The need for carbon finance schemes to tackle overexploitation of tropical forest wildlife.

Defaunation of tropical forests, particularly from unsustainable hunting, has diminished populations of key seed dispersers for many tree species, driving shifts in forest community composition toward small-fruited or wind-dispersed trees with low wood density. Such shifts can reduce aboveground biomass, prompting calls for overexploitation to be included in bioeconomic policy, but a synthesis of existing literature for wildlife impacts on carbon stores is lacking. We evaluated the role of wildlife in tropical forest tree recruitment and found that it was critical to tropical forest carbon dynamics. The emerging financial value of ecosystem services provided by tropical forest fauna highlights the need for carbon-based payments for ecosystem services schemes to include wildlife protection. We argue for three cost-effective actions within carbon finance schemes that can facilitate wildlife protection: support land security opportunities for Indigenous peoples and local communities; provide support for local people to protect forest fauna from overexploitation; and focus on natural regeneration in restoration projects. Incorporating defaunation in carbon-financing schemes more broadly requires an increased duration of carbon projects and an improved understanding of defaunation impacts on carbon stores and ecosystem-level models. Without urgent action to halt wildlife losses and prevent empty forest syndrome, the crucial role of tropical forests in tackling climate change may be in jeopardy.