Background: Wood bleaching is used for applications such as the production of uncoated furniture and laminated boards. However, there has been limited research on applying this treatment to Eucalyptus wood, and existing studies often involve reagents that are harmful to both the environment and human health. This study aimed to evaluate the physical and optical properties of Eucalyptus grandis W.Hill veneers following chemical modification with hydrogen peroxide. Methods: Twenty-seven H2O2 bleaching treatments were conducted, varying in time (30, 60, and 90 minutes), temperature (60, 70, and 80°C), and pH (4, 6, and 8), and were compared to a control treatment. Tests comprised measuring density, 24-hour water absorption, wettability, brightness, whiteness, yellowness, and CIELab* colour scale. Results: Bleaching modified the wood’s properties, particularly increasing brightness and whiteness. While density and water absorption did not significantly change with treatment, wettability increased after bleaching, promoting bonding quality for the production of laminated boards. The treatment conducted at 70°C, with an alkaline pH of 8 for 90 minutes, showed the most favourable results. Conclusions: These findings demonstrated the potential of hydrogen peroxide bleaching as a technique for enhancing physical and optical properties of wood veneers.
Background: Phytosanitary treatments are essential in ensuring the safe trade of logs, lumber, or wood-based products by preventing the spread of harmful insects and pathogens across international borders. Methyl bromide and sulfuryl fluoride are effective fumigants which kill both invertebrate pests and plant pathogens which can damage exported logs. Both have adverse effects on the environment; therefore, less damaging alternatives should be investigated. Ethanedinitrile (EDN) has demonstrated efficacy against invertebrate pests in logs and does not damage the ozone layer or act as a greenhouse gas. However, its efficacy against plant pathogens has not been well tested. Methods: This study tested the efficacy of EDN as a fumigant against 20 fungi and oomycetes associated with wood products, such as Pinus radiata D. Don logs. EDN was used as a fumigant in experimental chambers in which Petri plates were inoculated with a 5-mm agar disc from the growing edge of fungal and oomycete cultures. After treatment, mycelial growth was measured every 2-3 days for 14 days, after which EDN-treated discs were transferred to fresh media and growth was observed for an additional 14 days. Results: Mycelial growth of all isolates was almost completely inhibited following EDN treatment at 50 g m(-3) for 24 h, with no resumption of growth observed after transferring treated agar discs onto fresh media. The fungicidal effect of EDN was evident in both mycelium and putative survival structures, including oospores and chlamydospores. Conclusions: These findings align with those of previous studies highlighting the potential of EDN as an alternative fumigant, offering broad-spectrum efficacy without the environmental drawbacks associated with methyl bromide and sulfuryl fluoride. The results suggest that EDN is an effective phytosanitary treatment for fungi and oomycetes that grow in logs, and that it could be used for managing pathogens associated with P. radiata logs or timber traded internationally. This research contributes to ongoing efforts to improve biosecurity measures in international wood trade.
Background: The continuous assessment of new genotypes is essential to boost industries such as that for charcoal production. This is because wood properties can significantly change among different genotypes. The aim of the present study is to assess the wood quality of different Corymbia genotypes to identify those with desirable features and to improve the ability to classify and select the best genotypes for charcoal production. Methods: Different Corymbia genotypes were assessed, including two progenies and nine clones. Trees in the age group 3 and 4 years were collected from two trial crops in Minas Gerais State, Brazil, in collaboration with a company from the steel sector. Genotype assessment demanded several wood analyses focused on physical, chemical, energy and anatomical parameters. The collected data were subjected to multivariate analysis to cluster the genotypes. This procedure allowed classifying the genotypes presenting the most desirable features for charcoal production. Results: The study revealed significant variations in Corymbia genotypes' wood density, bark features, chemical composition, energy and anatomical features. Genotypes were categorised into different groups based on wood and bark density, bark thickness and content, and heartwood content. Notably, genotype influenced parameters such as ash, volatile matter and fixed carbon content. Total extractives, lignin and holocellulose content showed significant variability across genotypes. Genotypes did not significantly affect energy composition, except for energy density. Principal component analysis highlighted key wood properties that contribute to data variability in order to help genotype classification. Conclusions: The study provides understandable insights into the wood quality of Corymbia genotypes, and points out that wood properties work as reliable indicators to classify and select superior Corymbia genotypes for charcoal production. These properties reasonably predict the impact of raw material features on charcoal quality in a quite accurate way. All assessed genotypes emerged as having promising initial potential for charcoal production or for other energy applications, and it also indicates that Corymbia wood properties were comparable to, or even better than, those of genus Eucalyptus.
Background: Eucalyptus urophylla S.T.Blake is a major plantation species in tropical and subtropical regions, mainly grown for pulpwood. Increasing interest in solid wood applications has highlighted the need to improve wood properties through genetic selection. Methods: A subset of 200 trees representing 50 open-pollinated families from three seed sources in an eight-year-old progeny trial in northern Vietnam was sampled. Wood basic density, tangential, radial and longitudinal shrinkage, coefficient of anisotropy, and log end-splitting index (LESI) were assessed. Results: Wood basic density showed high heritability (h2 = 0.90 +/- 0.24). Tangential and radial shrinkage exhibited moderate heritability estimates (0.43 +/- 0.22 and 0.34 +/- 0.21, respectively), while longitudinal shrinkage showed no genetic variation. The coefficient of anisotropy and LESI also showed moderate heritability estimates (0.32 +/- 0.21 and 0.31 +/- 0.21). Genetic correlations between growth and wood traits were weak and non-significant, but a strong negative genetic correlation was observed between wood density and coefficient of anisotropy (-0.89 +/- 0.37). Conclusions: Substantial additive genetic variation exists for key wood properties in E. urophylla, indicating good potential for genetic improvement. Selection for higher wood density is expected to reduce anisotropy without compromising growth. These results support the integration of wood quality traits into breeding objectives to enhance solid wood recovery from plantation-grown E. urophylla.
Background: This study compares two remote sensing methods to a field-based line intersect sampling (LIS) method for measuring Large Woody Debris (LWD) on 27 ha of recently clear-felled plantation cutover in North Canterbury, New Zealand. The remote sensing methods tested were: 1) machine learning-based LWD detection on high-resolution orthophotography; and, 2) virtual line intersect sampling via photogrammetric point clouds. Methods: The site was flown at 40 m above ground level with a 20 megapixel RGB camera, and 80% image overlap, achieving a ground sampling distance of 1.1 cm. The resulting point cloud and orthophoto were used for remote sensing measures, compared to the ground-based volume measure. The ground-based line intersect sampling used 28 x 50 m, slope-corrected L-shaped transects arranged in a grid pattern across the site. LWD diameter was measured at the transect intersection and used to derive volume using Van Wagner's (1968) LIS formula. Results: The ground-based method measured a mean LWD volume of 31.0 +/- 10.2 m3/ha. The photogrammetry-based method measured a lower mean volume of 13.6 +/- 3.8 m3/ha, with an r2 value of 0.61, indicating moderate correlation with the ground-based method. The machine learning method measured a mean LWD volume of 14 m3/ha and had a moderately weak r2 value of 0.39, in line with other published models. The machine learning method positively correlated with both ground-based and photogrammetric LWD volume, making it most useful for identifying high-density areas. The ground-based method consistently returned higher volume measures. Occluded residues could not be captured by the remote sensing methods, but were positively observed in the field. Accuracy in establishing and measuring to the in-field transect remains critical also, regardless of topography challenges. Plot-wise interpretation of the orthophoto revealed 11% of field-measured pieces fell outside the transect. While challenging in steep topographies, field measures remain the only way to capture occluded volume in high-density areas. Conclusions: Remote sensing techniques based on RGB photography offer a safer, more efficient alternative that can reliably identify high-density areas, even if the estimate is likely low. Strategic application of these methods, considering costs, benefits, and limitations, will enhance plantation owners' ability to ensure alignment with new cutover standards.
Background: Relationship between height (H) and diameter (D) highly depends on site conditions and stand structures. In this regard, this study aimed to build a new site-specific model based on the Chapman-Richards function, for the Crimean pine stands in the Black Sea Backward Region of Turkiye. Methods: The model was developed using the mixed-effects framework and its accuracy and performance were assessed using a validation data set. The model was then compared to two highly predictive models derived from the Chapman-Richards function through fit statistics, curvature and bias measures of nonlinearity, and biological principles. Results: The new model resulted in the most favourable fit statistics and nonlinearity measures, and also exhibited a suitable H-D curve that was compatible with the ecological conditions of the study area. While the alternative models in the current literature showed good fit statistics, they resulted in biased parameter estimates and produced inappropriate H-D curves. The proposed model, however, demonstrated a satisfactory accuracy when validated using the validation data set. Conclusions: (1) It is essential to assess H-D models by considering both fit statistics and curvature and bias measures of nonlinearity; and (2) it is crucial to examine whether H-D models are appropriate for the specific ecological conditions of a particular region.
Background: Biological populations were studied to understand their ecology and to evaluate the relationships between living beings that comprise them. Mathematical functions used in probabilistic models should present multifunctionality, sensitivity, and flexibility to appropriately describe a natural phenomenon. The objective of this study was to develop a new probabilistic distribution with five parameters to maximize its flexibility and ensure a better goodness of fit when compared to other important distributions, such as Beta, Burr, Silva and Pareto. Methods: New distribution estimators were derived usingthe mathematical expectation of central and dispersion moments. Estimated values of the parameters were obtained using an optimization process developed by Abel Soares Siqueira, research software engineer at the Netherlands eScience Center in Amsterdam. Data for the application of the developed distribution method were collected at different sites in Brazil, where asymmetry and kurtosis were detected. Results: The Pellico-Behling Probability Distribution (5P) was applied to fit the datasets for Cariniana legalis, Acacia mearnsii, and Eucalyptus saligna. For the average mortality of 124 species, it was used with (4P). The distribution fitted to sampled datasets was compared with the fitted Beta and Burr (4P) distributions, except for Silva's polynomial distribution that was fitted to the heights of the species Eucalyptus saligna and the Pareto distribution to mortality of 124 tropical species from a fragment of a semideciduous seasonal forest, to evaluate and verify its potential and robustness. Conclusions: The new distribution with five parameters is flexible and produced better goodness of fit than those obtained from the other distributions used for comparative purposes.
Background: Estimation of forest biomass has become critical as afforestation has been proposed to sequester carbon from the atmosphere in order to mitigate climate change. New Zealand Dryland Forestry Innovation (NZDFI), in collaboration with the University of Canterbury's School of Forestry and the Marlborough Research Centre, has initiated a research and development programme to gather seed, breed, propagate, identify site limitations, model growth, investigate silviculture, and develop wood products from a suite of eucalypts that grow durable heartwood. The aim is to supply naturally durable wood for uses that formerly required either imports of durable wood or copper-chrome-arsenate treated pine. Methods: As part of a project examining land-use and greenhouse gas budget case studies in Marlborough, New Zealand, we collected and summarised data describing above-ground biomass (AGB) of Eucalyptus bosistoana F.Meull., and Eucalyptus globoidea Blakely trees across a wide range of combinations of height (h) and diameter at breast height (dbh). One hundred and eleven trees were felled, separated into stems, branches and foliage, and the components were weighed in the field. Subsamples of these tree parts were collected and weighed in the field after separating bark from stem discs. The subsamples were dried in an oven at 105 degrees C, and then weighed. Ratios of dry to wet weights for samples were applied to total green weights from the field in order to calculate AGBs of tree components. Systems of non-linear equations were simultaneously fitted to the data to ensure additivity; that sums of estimates oftree part AGBs versus dhb, hand slenderness (h/dbh) equalled estimates from a model of total tree AGB versus the same independent variables. The study also included the development of a plot-level estimation model of above-ground CO2-e/ha for E. globoidea and its incorporation in an on-line growth and yield simulator. Moreover, a comparison of two pathways to estimating AGB by aerial LiDAR was made: One including estimates of dbh and h from LiDAR and applying the tree-level equations developed in this study, and one going directly from LiDAR metrics to estimates of AGB. Results: A system of models created for both species with a dummy variable denoting species yielded the least biased residuals, with 22 coefficients estimated in one simultaneous fit. Standard errors varied with plant part and with the size of the prediction, requiring transformations prior to fitting. R2 values also varied with part, but were typically between 0.96 and 0.98. An exception was foliage and seeds which were influenced by one tree with an unusually high loading of seeds. The standard error for plot level estimates of CO2-e was 1.9 tonnes CO2-e /ha and residuals were relatively unbiased. Directly predicting individual tree AGB from LiDAR metrics yielded less biased estimates than predicting dbh and h and then using those estimates to predict AGB. Conclusions: A system of related, additive equations with a dummy variable denoting species represented the aboveground biomass of Eucalyptus globoidea and Eucalyptus bosistoana with precision adequate for prediction of biomass for fuel and carbon storage to mitigate climate change. Direct predictions of biomass from LiDAR metrics were less biased than predictions of biomass from tree height and diameter at breast height that were in turn predicted from LiDAR metrics.
Background: Geospatial technologies have emerged as powerful tools for optimising forest management, improving operational precision, and supporting data-driven decision-making. This study aims to understand the technologies adopted by the New Zealand plantation forest industry and identify any barriers to the uptake of geospatial tools. This is the third such study, following comparable surveys in 2013 and 2018. Methods: An online survey was sent to 29 organisations in New Zealand's forestry sector. Topics included organisation demographics, data acquisition, positioning technology, remote sensing technologies, software, and Artificial Intelligence (AI). Specifically, the survey focused on five remote sensing technologies: aerial photography, aerial videography, multispectral imagery, hyperspectral imagery, and LiDAR. Each section contained questions relating to the acquisition and application of the remote sensing technology and the software used for data processing. Questions were included to ascertain barriers to adoption. To identify changes in technology usage and uptake, results were compared to the 2013 and 2018 studies. Results: Twenty-seven of the 29 queried organisations responded, resulting in a 93% response rate. Responding organisations managed 1,283,000 hectares (74% of New Zealand's plantation forest estate), with estate sizes ranging from about 7,000 to 200,000 hectares. Data acquisition from online portals included aerial imagery (100%), property ownership data (96%), and elevation data (89%), primarily from the Land Information New Zealand (LINZ) Data Service. Global Navigation Satellite Systems (GNSS) technology was universally employed. All respondents acquired aerial photography. In addition, 67% acquired multispectral imagery, 4% acquired hyperspectral imagery, and 93% acquired LiDAR data. The AI topic was surveyed for the first time and the technology was used by 30% of respondents when working with geospatial data. The main barrier to using remotely sensed data was the lack of perceived benefits, while the primary barrier to AI adoption was a lack of staff knowledge and training. Except for hyperspectral imagery, all remote sensing technologies saw increased uptake since 2013. LiDAR experienced the largest growth, with uptake increasing from 17% in 2013 to 93% in 2023. ArcGIS remains the primary tool for geospatial analysis, used by 96% of respondents. Notably, the use of open-source software such as QGIS increased by 31% over the past decade. Conclusions: This study demonstrated an overall increase in the usage of geospatial technology in the forestry sector. To promote further uptake, it is important not only to increase exposure to available tools and provide training, particularly on emerging technologies such as AI, but also to demonstrate the practical and economic value these technologies can offer.
Background: Thermal modification of nondurable Eucalyptus nitens timber was reported to result in excessive checking and only marginally improved durability when heat treating in steam or atmospheric environments. This study investigated if oil heat-treatment of E. nitens above 210 degrees C was able to overcome previously reported difficulties. Methods: Eucalyptus nitens clears were oil heat-treated to 210 degrees C, 220 degrees C and 230 degrees C and assessed for density, stiffness, strength, colour and decay resistance. Results: Oil heat-treated E. nitens samples showed mass loss matching the highest durability class when tested against the brown-rot Rhodonia placenta (Fr.) Niemel & auml;, K.H.Larss. & Schigel and the white-rot Trametes versicolor (L.) Lloyd, matching Durability Class-2 rated Eucalyptus muelleriana A.W.Howitt heartwood. Oil heat-treated E. nitens samples outperformed Pinus radiata treated with chromated copper arsenate (CCA) to Hazard Class (H3) grade when tested for the brown-rot R. placenta. While oil heat-treatment reduced mean stiffness (MoE) and strength (MoR), the resulting material exceeded characteristic SG8 grade values. No checking was observed in the oil heat-treated E. nitens boards. Letting samples cool outside the oil bath limited uptake of oil to less than 4 mm in depth. The planed product became darker the higher the oil heat-treatment temperature. Conclusions: Oil heat-treatment above 210 degrees C has the potential to refine E. nitens timber, avoiding excessive degrade and providing decay resistance.
Background: The ecological science associated with transitioning exotic forest to native dominance (hereafter transitional forestry, transition forests) is currently limited, yet this form of forest has expanded rapidly. In part, this is related to forest-based carbon credit schemes which have driven large-scale afforestation in exotic trees. In other circumstances (e.g., for soil conservation or values-based reasons such as biodiversity conservation), forest owners wish to transition their exotic forest to native forest without harvest. Knowledge is required to inform management of realistic expectations for regeneration and succession both spatially and temporally. Methods: Mature (>20-year-old) Pinus radiata plantations were surveyed along three elevation-climate gradients in the Waikato region of New Zealand to explore the composition and structure (including native carbon stocks) of plantation understories and whether these parameters vary spatially over several decades. Mammalian browsing was also recorded. Results: Native woody stem densities were variable. Factors indicated as driving variability were stand age, elevation, topographic shelter, soil hydrology, solar radiation, and air temperature. On average, understories comprised five native woody species in the seedling tier, a single native species in the sapling tier, and a single native species in the tree tier. The most common species were the sub-canopy tree species Melicytus ramiflorus, Geniostoma ligustrifolium, and Aristotelia serrata. Tall old-growth species, such as Beilschmiedia tawa, Podocarpus totara, Pectinopitys ferruginea, and Prumnopitys taxifolia, occurred in only particular circumstances and on average at densities too low to form a meaningful part of a future forest canopy. Average species richness was low, although some diversity hotspots occurred. Carbon stocks in native trees and tree ferns in the understories were on average 1.55 +/- 0.38 tCha(-1). Heavy browsing by mammalian herbivores was recorded at 60% of plots. Conclusions: These data indicate typical understorey conditions in mature P. radiata plantations for this area of New Zealand in the absence of management to promote a native transition. These data also highlight the importance of browser control, enrichment planting of tall old-growth species, and canopy manipulations to accelerate regeneration and succession in non-harvest P. radiata plantations. The data suggest transitional forestry should only be attempted at scales that can be reasonably managed, and there is a need for caution against large-scale establishment of P. radiata for transitional forestry as at large scales, achieving adequate levels of management are uncertain.
Background: Red needle cast (RNC), caused by Phytophthora pluvialis Reeser, W.L. Sutton & E.M. Hansen, is a significant foliar disease impacting Pinus radiata D.Don in New Zealand. First detected in 2005, the disease has now been observed in all regions of the country. In the most severe cases, defoliation of entire tree crowns can occur at a landscape scale. While some evidence of growth loss and productivity reduction has been reported, quantitative estimates of the effect of RNC on productivity are needed to inform disease management and mitigation decisions. This study aims to assess both short-and long-term losses in radial growth due to RNC. Methods: We used tree cores to quantifyyearly basal area increments attwo plantations: a 32-year-old stand in Wharerata Forest, with documented history of outbreaks both severe and cyclic in nature, and a 26-year-old stand in Kinleith Forest, where 8 years of continuous disease severity monitoring has been conducted at the tree level. A Bayesian multilevel modelling framework was used to predict growth losses due to RNC at each site separately, accounting for yearly weather and outbreak severity. Results: We predicted a 31% to 51.5% radial growth loss in the year following an RNC outbreak, with reduced growth detectable for 3 to 4 years after disease, amounting to up to 30.6% growth loss over the course of a single event. Recurring disease events everythreeto four years can lead to a 20% reduction in total radial area growth over the period encompassing the presence of the disease, with no evidence that each additional RNC event aggravates growth loss. Conclusions: RNC causes significant growth loss in P. radiata, with the potential to severely reduce stand productivity over a rotation period. These results contribute valuable insights for forest managers in RNC-prone regions. The enablement of more accurate productivity forecasts and targeted mitigation efforts will also benefit from further research on the impact of RNC on other important tree characteristics such as wood density, and the interaction of disease presence and impact with climate.
Background: Global canopy height models are becoming prolific yet require evaluation across New Zealand's diverse vegetation types to assess their accuracy and applicability. Accurate measurement of canopy height is crucial for estimating above-ground woody biomass, which is essential for modelling carbon emissions and sequestration in the context of climate change. These models generally rely on remote sensing data and machine learning techniques, with Light Detection and Ranging (LiDAR) technology commonly employed for precise measurement. Methods: This study validated the three latest global canopy height models, each provided at a different resolution: 30-metre, 10-metre, and 1-metre. We assessed the accuracy of the selected models by comparing them against canopy height estimates derived from local Airborne Laser Scanning (ALS) datasets, which served as our reference data. Eleven regions across New Zealand were selected based on ALS data availability, encompassing five vegetation and land cover types. Our methodology involved utilising and automating the processing of large New Zealand ALS datasets. To align resolutions for comparison, the reference canopy height was calculated by aggregating average or maximum heights at 10 and 30 m spatial resolution. Model performances were assessed using statistical metrics, including root-mean-square error (RMSE), bias, and R2. Results: Overall, all models exhibited relatively low R2 values, indicating limited capture of canopy height variability. The Potapov 30-metre model performed best with average aggregation in shorter vegetation. In contrast, the Lang 10-metre model showed improved accuracy with maximum aggregation, particularly in taller vegetation, but visual boundaries between different vegetation types were not as distinct. The Tolan 1-metre model provided a balanced approach, minimising biases in lower heights but underestimating taller canopies. Results highlight model-specific strengths for varying vegetation structures and the sensitivity of performances to aggregation methods applied to high-resolution reference ALS data. Conclusions: All three global canopy height models exhibit varied performance across New Zealand's vegetation types. The findings highlight the importance of vegetation-specific applications to optimise each global model's accuracy. Currently, these models are suitable for carbon accounting efforts as supplementary tools rather than replacements for existing methodologies.
Background: Red needle cast (RNC) is a foliar disease of radiata pine (Pinus radiata D.Don) in New Zealand caused by Phytophthora pluvialis Reeser, W.L.Sutton & E.M.Hansen and, to a lesser extent, Phytophthora kernoviae Brasier, Beales & S.A.Kirk. Incidence and severity of RNC vary substantially between years. To investigate the impact of seasonal weather variables on this variation, RNC was assessed annually for ten years at radiata pine transects. Methods: Fifty-three transects were established in 2015 in the Central North Island and Gisborne Region (east coast North Island) of New Zealand, with twenty-three monitored until 2024 (surviving harvest). The relationship between seasonal weather variables and RNC severity was analysed using two non-parametric statistical approaches: (1) correlation analyses (Spearman correlations, rs,where positive values indicate an increase in RNC severity with an increase in the explanatory variable); and (2) binary recursive partitioning (with models trained on 85% of observations and tested on the remaining 15%). Results: Disease expressed more consistently, and severity was generally greater, at Gisborne sites. Disease severity peaked in 2017 and 2023 in both regions. Autumn (March-May) variables tended to be prevalent amongst predictors of RNC severity. Autumn soil moisture index (calculated from cumulative rainfall and evapotranspiration) was the most strongly correlated variable for the Gisborne dataset (rs = 0.70) and, along with vapour pressure, were the key partitioning variables in the recursive partitioning model. The strongest correlating variable for the Central North Island dataset was autumn potential evapotranspiration (rs =-0.46) while the most important variable and first data partition was autumn vapour pressure. Model evaluation metrics indicated good performance: R2 values were 0.63 and 0.68 for the Gisborne and Central North Island test datasets respectively, and mean absolute errors were 18.1 % and 7.8 % for the respective datasets. Conclusions: The importance of autumn more than summer weather variables in determining disease expression differs from the findings of previous studies and indicates that conditions during periods of exponential epidemic growth may be as, or more, important than initial inoculum level in determining RNC severity. Proactive control activities may require long-term weather forecasting or frequent monitoring during this season.
Background: Do tree species that have wood of high commercial value which are being extracted in the Saraca-Taquera National Forest have diameter and spatial distribution patterns that enable continuous production of timber to meet the criteria of ecological conservation and sustainable management of their populations? To answer this question, we evaluated diameter and spatial distributions of 15 commercial tree species of ecological and economic importance, in a concession area in the Saraca-Taquera National Forest, Eastern Amazon. Methods: The data were obtained from a forest inventory carried out in 24 50 m x 50 m plots, considering a minimum diameter of 30 cm. The 15 species were selected based on three criteria: importance value index; volume stock; and commercial value of the wood. The trees were distributed into diameter classes with an interval of 10 cm between them to analyse the diameter distribution. The spatial distribution patterns of the species were analysed using the univariate Ripley's Kfunction. Results: The results showed that the presence of large trees and the aggregated spatial distribution in most of the tree species studied may determine the feasibility of continuous timber production to meet conservation and sustainable management criteria. The spatial distributions of stocks should guide planning of forest management activities, including pre-logging, logging and post-logging activities. However, the low population density of most species suggests that logging must be well planned to avoid population declines. Although forest management on a sustainable basis has advanced substantially in recent years in the Amazon, the factors that promote different diameter and spatial distributions of species are still considered complex and little studied. Conclusions: The results pointto a need to expand research on this topic in managed areas, includingthe same technological approach as the work described here. This type of analysis can constitute an important tool for defining population management strategies for each species, considering their ecological characteristics and environmental adaptation at a local level.
Background: Robust species-specific height-diameter (H-D) equations are necessary for the estimation and prediction of tree volume, yield, biomass or carbon stocks. In addition, information about height growth characteristics allows for the analysis of stand growth dynamics. But there is a general lack of species-specific growth models for most New Zealand native tree species considered for plantation and wood production. Therefore, the aim of this study was to develop a species- and site-specific H-D model for planted lowland tōtara (Podocarpus totara G. Benn. ex D. Don). Methods: The models were developed using data from 719 individually measured trees aged 11 to 110 years from eight different sites in the North Island of New Zealand. Two different modelling approaches, traditional non-linear and linear mixed effect, were used. The process included selecting, testing, conditioning, and extending a total of 18 different equations by incorporating site-specific tree variables. Results: The most precise model predicting the H-D relationship was reported by linear mixed-effect models that include diameter at breast height (DBH at 1.4 m, cm) and age (years). The final model had a low root mean square error (RMSE, 0.21, m), mean absolute error (MAE, 0.16, m) and high R2 (0.94), which slightly increased during validation. Conclusions: The study demonstrated a robust process and reported the most plausible and parsimonious model to predict P. totara’s H-D relationship, which serves as the basis for species-specific growth dynamics. The reported models provide for the first time the opportunity to predict the H-D relationship of planted P. totara in New Zealand. This fills a long existing knowledge gap and provides forest growers and managers important decision-making information.
Background: Handroanthus impetiginosus (lavender trumpet tree) is valued for its construction, medicinal, and ecological uses. However, its slow initial growth and weak root system hinder seedling production. Rhizobacteria from the genera Bacillus and Azospirillum enhance plant growth and resilience. This study evaluated their effects on H. impetiginosus seedling development. Methods: The experiment was conducted in a greenhouse at the Experimental Nursery of Ornamental and Forestry Plants - College of Agricultural and Veterinary Sciences (UNESP/FCAV), Jaboticabal, Brazil, during the summer 2022/23. A completely randomised design included five treatments: Bacillus subtilis, B. megaterium, B. amyloliquefaciens, Azospirillum brasilense, and a control (no inoculation). Each treatment had four replicates of 20 plants. Seeds were sown in 280 cm³ tubes with a commercial substrate, composed of peat, vermiculite, roasted rice husk, calcined dolomitic limestone, NPK 14-16-18, and micronutrients. The rhizobacteria were inoculated at 30 and 60 days after sowing. Growth parameters (shoot height, stem diameter, root length, and biomass) were assessed at 107 days. Photosynthetic performance and microbiological colonisation were also evaluated. Data were analysed using ANOVA, Tukey’s test and Pearson correlation. Results: Azospirillum brasilense significantly enhanced growth, with the highest averages for shoot height (13.9 cm), stem diameter (1.72 mm), shoot dry mass (0.172 g), and total dry mass (0.686 g). It also improved seedling quality indices, including the Dickson Quality Index and shoot height-to-stem diameter ratio. Photosynthetic efficiency increased when inoculated with Azospirillum brasilense, as indicated by greater leaf area and chlorophyll content. Colony Forming Units (CFU) analysis showed higher bacterial colonisation in the substrate, roots, and aerial parts of A. brasilense-treated plants, with strong correlations between colonisation and plant growth. Conclusions: Azospirillum brasilense was the most effective rhizobacterium promoting H. impetiginosus seedling growth and quality. Its use could enhance reforestation and nursery production efficiency, accelerating seedling establishment. These findings highlight the potential of rhizobacteria to improve seedling vigour and adaptation in early growth stages.
Background: Studies show that forest uniformity has a direct correlation with productivity, and uniformity measures can serve as indicators of the silvicultural quality of plantations. In this context, this work aimed to determine uniformity and survival in young Eucalyptus sp. plantations using attributes obtained from passive sensors boarded on Unmanned Aerial Vehicles (UAV). Methods: Tree height was underestimated by the UAV compared to those measured in the Quality Forest Inventory (QFI). Thus, a correction factor applied to size classes was proposed to estimate these heights. The plantations’ uniformity was obtained through the uniformity indices (UI). The UIs were spatialised and integrated, resulting in two uniform surfaces, with and without planting failures. Results: The UAV survival estimates did not show significant differences compared to the inventory estimates at the 1% or the 5% significance levels. The classification of uniformity surfaces showed that the Eucalyptus saligna Sm plantation was the least uniform compared to the E. grandis W. Hill × E. urophylla S. T. Blake plantations. Conclusions: Measures of survival and uniformity by the UAV can be jointly employed to generate uniformity surfaces and to determine the areas that need more attention from silvicultural management.
Background: Many tree species with potential for wood production present high intra-specific variations in the extent of trunk differentiation (i.e. hierarchical architecture). The identification of multiple-scale traits related to hierarchical architecture could improve selection criteria for domestication. Methods: We investigated the hierarchical architecture of Nothofagus obliqua, a valuable species for timber production, but with high structural variability. Young trees in even-aged natural regeneration gaps, and seedlings derived from controlled crosses and open pollination were studied. For the second approach, trees with contrasting degree of hierarchical architecture were manually crossed. In both, juvenile plants and seedlings, we analyzed trunk growth unit traits and hierarchical architecture indices based on the relative size and branching angle of main branches. Results: In regeneration gaps, hierarchical architecture was positively related to height and diameter. Apex persistence, the number of sylleptic branches and mean internode length were indicative of larger and more hierarchical trees. Some support is provided to the idea that adult trees with a notably hierarchical architecture could produce young trees with early signs of a hierarchical architecture. In seedlings, hierarchical architecture was negatively related to basal diameter. Conclusions: Some growth unit traits that differed among progenies and were related to hierarchical architecture could be considered for the development of selection criteria for young trees.
Background: Do tree species that have wood of high commercial value which are being extracted in the Saracá-Taquera National Forest have diameter and spatial distribution patterns that enable continuous production of timber to meet the criteria of ecological conservation and sustainable management of their populations? To answer this question, we evaluated diameter and spatial distributions of 15 commercial tree species of ecological and economic importance, in a concession area in the Saracá-Taquera National Forest, Eastern Amazon. Methods: The data were obtained from a forest inventory carried out in 24 50 m × 50 m plots, considering a minimum diameter of 30 cm. The 15 species were selected based on three criteria: importance value index; volume stock; and commercial value of the wood. The trees were distributed into diameter classes with an interval of 10 cm between them to analyse the diameter distribution. The spatial distribution patterns of the species were analysed using the univariate Ripley’s K function. Results: The results showed that the presence of large trees and the aggregated spatial distribution in most of the tree species studied may determine the feasibility of continuous timber production to meet conservation and sustainable management criteria. The spatial distributions of stocks should guide planning of forest management activities, including pre-logging, logging and post-logging activities. However, the low population density of most species suggests that logging must be well planned to avoid population declines. Although forest management on a sustainable basis has advanced substantially in recent years in the Amazon, the factors that promote different diameter and spatial distributions of species are still considered complex and little studied. Conclusions: The results point to a need to expand research on this topic in managed areas, including the same technological approach as the work described here. This type of analysis can constitute an important tool for defining population management strategies for each species, considering their ecological characteristics and environmental adaptation at a local level.
