Search Results (41)

There is growing interest in the use of herbicide for the silvicultural practice of tree thinning (i.e., chemical thinning or e-thinning) in New Zealand. Potential benefits of this approach include improved stability of the standing crop in high winds, and safer and lower-cost operations, particularly in steep or remote terrain. As uptake grows, tools for monitoring treatment effectiveness, particularly during the early stages of stress, will become increasingly important. This study evaluated the use of UAV-based multispectral and hyperspectral imagery to detect early herbicide-induced stress in a nine-year-old radiata pine (Pinus radiata D. Don) plantation, based on temporal changes in crown spectral signatures following treatment with metsulfuron-methyl. A staggered-treatment design was used, in which herbicide was applied to a subset of trees in six blocks over several weeks. This staggered design allowed a single UAV acquisition to capture imagery of trees at varying stages of herbicide response, with treated trees ranging from 13 to 47 days after treatment (DAT). Visual canopy assessments were carried out to validate the onset of visible symptoms. Spectral changes either preceded or coincided with the development of significant visible canopy symptoms, which started at 25 DAT. Classification models developed using narrow band hyperspectral indices (NBHI) allowed robust discrimination of treated and non-treated trees as early as 13 DAT (F1 score = 0.73), with stronger results observed at 18 DAT (F1 score = 0.78). Models that used multispectral indices were able to classify treatments with a similar accuracy from 18 DAT (F1 score = 0.78). Across both sensors, pigment-sensitive indices, particularly variants of the Photochemical Reflectance Index, consistently featured among the top predictors at all time points. These findings address a key knowledge gap by demonstrating practical, remote sensing-based solutions for monitoring and characterising herbicide-induced stress in field-grown radiata pine. The 13-to-18 DAT early detection window provides an operational baseline and a target for future research seeking to refine UAV-based detection of chemical thinning. Full article

Forests are a key terrestrial carbon sink, storing carbon in biomass, the forest floor, and the mineral soil (SOC). Since Pinus radiata D. Don is the most widely planted forest species in Chile, it is important to understand how environmental and soil factors influence these carbon pools. Our objective was to evaluate the effects of climate and site variables on carbon stocks in adult radiata pine plantations across contrasting water and nutrient conditions. Three 1000 m² plots were installed at 20 sites with sandy, granitic, recent ash, and metamorphic soils, which were selected along a productivity gradient. Biomass carbon stocks were estimated using allometric equations, and carbon stocks in the forest floor and mineral soil (up to 1 m deep) were assessed. SOC varied significantly, from 139.9 Mg ha⁻¹ in sandy soils to 382.4 Mg ha⁻¹ in metamorphic soils. Total carbon stocks (TCS) per site ranged from 331.0 Mg ha⁻¹ in sandy soils to 552.9 Mg ha⁻¹ in metamorphic soils. Across all soil types, the forest floor held the lowest carbon stock. Correlation analyses and linear models revealed that variables related to soil water availability, nitrogen content, precipitation, and stand productivity positively increased SOC and TCS stocks. In contrast, temperature, evapotranspiration, and sand content had a negative effect. The developed models will allow more accurate estimation estimates of C stocks at SOC and in the total stand. Full article

As the frequency of strong storms and cyclones increases, understanding wind risk in both existing and newly established plantation forests is becoming increasingly important. Recent advances in the quality and availability of remotely sensed data have significantly improved our capability to make large-scale wind risk predictions. This study models the loss of radiata pine (Pinus radiata D.Don) plantations following a severe cyclone within the Gisborne Region of New Zealand through leveraging repeat regional LiDAR acquisitions, optical imagery, and various surfaces describing key climatic, topographic, and storm-specific conditions. A random forest model was trained on 9713 plots classified as windthrow or no-windthrow. Model validation using 50 iterations of 80/20 train/test splits achieved robust accuracy (accuracy = 0.835; F1 score = 0.841; AUC = 0.913). In comparison to most European empirical models (AUC = 0.51–0.90), our framework demonstrated superior discrimination, underscoring its value for regions prone to cyclones. Among the 14 predictor variables, the most influential were mean windspeed during February, the wind exposition index, site drainage, and stand age. Model predictions closely aligned with the estimated 3705 hectares of cyclone-induced forest damage and indicated that 20.9% of unplanted areas in the region would be at risk of windthrow at age 30 if established in radiata pine. The resulting wind risk surface serves as a valuable decision-support tool for forest managers, helping to mitigate wind risk in existing forests and guide adaptive afforestation strategies. Although developed for radiata pine plantations in New Zealand, the approach and findings have broader relevance for forest management in cyclone-prone regions worldwide, particularly where plantation forestry is widely practised. Full article

Forest plantations in the Neotropics aim to alleviate pressure on primary forests. This study synthesizes knowledge on pine species used in these plantations, emphasizing the challenges and potential of ectomycorrhizal fungi and bacteria as inoculants. An analysis of 98 articles identifies 23 pine species in Mexico and Central America and about 16 fast-growing species in South America. While pine plantations provide a habitat for generalist species, they reduce the richness of specialist species. Ectomycorrhizal fungi and bacterial diversity in plantations with introduced pines is up to 20% lower compared to native ecosystems. Suillus and Hebeloma are commonly used as mycorrhizal inoculants for Neotropical and introduced species, including Pinus ponderosa and Pinus radiata in South America. Commercial inoculants predominantly feature the fungal species Pisolithus tinctorius, alongside bacterial genera such as Bacillus, Cohnella, and Pseudomonas. This study emphasizes the importance of leveraging native microbial communities and their synergistic interactions with ECM fungi and bacteria to enhance seedling growth and quality. Such a combined approach can improve plantation survival, boost resilience to environmental stressors, and promote long-term productivity. These findings underscore the need to incorporate native fungi and bacteria into inoculant strategies, advancing sustainable forestry practices and ecosystem adaptation in the Neotropics. Full article

The rapid development of UAV-LiDAR and data processing capabilities is likely to enable accurate individual-tree inventories in the near future, requiring few on-ground calibration measurements. Using data collected from 20 radiata pine trials dispersed across New Zealand, the objective of this study was to determine the accuracy of high-density UAV-LiDAR for the prediction of tree diameter and volume, under a range of data calibration scenarios. Using all measurements for the calibration (a range of 335–4703 tree measurements across the 20 sites), accurate random forest models for each of the 20 sites were created from a diverse range of LiDAR metrics that characterised the horizontal and vertical structures of the canopy. Averaged across the 20 sites, predictions had a mean R² and relative RMSE (rRMSE) of, respectively, 0.713 and 9.699% for the tree diameter and 0.746 and 19.57% for the tree volume. Reductions in the numbers of calibration trees per trial had little effect on model accuracy until only 300 trees/site were used; however, accurate, unbiased predictions were still possible using as few as 100 trees/site. More generally, applicable random forest models for both tree dimensions were constructed by collating all of the data and tested using leave-one-site-out cross-validation to determine the accuracy of the model predictions when calibration measurements were not available. The predictions using this approach were reasonable but less accurate and more biased than with the use of calibration data, with a mean R² and rRMSE of, respectively, 0.631 and 15.12% for the tree diameter and 0.631 and 35.6% for the volume. Our research aims to facilitate the transition from a plot-based to tree-level inventory in plantation forests and contribute to the future development of a generalised model that could accurately predict tree dimensions from UAV-LiDAR, relying on minimal field measurements. Full article

Accurate characterization of tree stems is critical for assessing commercial forest health, estimating merchantable timber volume, and informing sustainable value management strategies. Conventional ground-based manual measurements, although precise, are labor-intensive and impractical at large scales, while remote sensing approaches using satellite or UAV imagery often lack the spatial resolution needed to capture individual tree attributes in complex forest environments. To address these challenges, this study provides a significant contribution by introducing a large-scale dataset encompassing 40 plots in Western Australia (WA) with varying tree densities, derived from Hovermap LiDAR acquisitions and destructive sampling. The dataset includes parameters such as plot and tree identifiers, DBH, tree height, stem length, section lengths, and detailed diameter measurements (e.g., DiaMin, DiaMax, DiaMean) across various heights, enabling precise ground-truth calibration and validation. Based on this dataset, we present the Forest Stem Extraction and Modeling (FoSEM) framework, a LiDAR-driven methodology that efficiently and reliably models individual tree stems from dense 3D point clouds. FoSEM integrates ground segmentation, height normalization, and K-means clustering at a predefined elevation to isolate stem cores. It then applies circle fitting to capture cross-sectional geometry and employs MLESAC-based cylinder fitting for robust stem delineation. Experimental evaluations conducted across various radiata pine plots of varying complexity demonstrate that FoSEM consistently achieves high accuracy, with a DBH RMSE of 1.19 cm (rRMSE = 4.67%) and a height RMSE of 1.00 m (rRMSE = 4.24%). These results surpass those of existing methods and highlight FoSEM’s adaptability to heterogeneous stand conditions. By providing both a robust method and an extensive dataset, this work advances the state of the art in LiDAR-based forest inventory, enabling more efficient and accurate tree-level assessments in support of sustainable forest management. Full article

Pinus radiata D. Don is the most widely planted forest species in Chile, making it crucial to understand carbon pools in adult plantations. This study aimed to evaluate the effect of soil type and site productivity on the total carbon stock in adult radiata pine plantations, considering sites with contrasting water and nutrient availability. We selected 10 sites with sandy and recent volcanic ash soils, representing a productivity gradient. At each site, three 1000 m² plots were established to quantify the carbon stock of total biomass using allometric equations and in situ carbon assessments of the forest floor and mineral soil (up to 1 m deep). The results indicated significantly higher carbon stocks in the mineral soil of recent ash sites (281.4 Mg ha⁻¹) compared to sandy soils (139.9 Mg ha⁻¹). The total site carbon was also higher in recent ash (473.2 Mg ha⁻¹) than in sandy sites (330.9 Mg ha⁻¹). A significant relationship was found between stand productivity and soil organic carbon (r² = 0.88), as well as total carbon stock (r² = 0.91) when considering soil type. These findings highlight the importance of including assessments up to 1 m depth and developing soil type and productivity models to improve site carbon stock estimates. Full article

The management of plantation forests using precision forestry requires advanced inventory methods. Unmanned aerial vehicle laser scanning (ULS) offers a cost-effective approach to accurately estimate forest structural attributes at both plot and individual tree levels. We examined the utility of ULS data collected from a radiata pine stand for tree detection and prediction of diameter at breast height (DBH) and stem volume, using data thinned to 13-point densities (ranging from 10–12,200 points/m²). These datasets were created using a DTM with the highest pulse density and DTMs that used the native decimated point clouds. Models of DBH were constructed using partial least squares (PLS) and random forest (RF) from seven classes of metrics that characterized the horizontal and vertical structure of the canopy. Individual tree segmentation was consistently accurate across the 13-point densities and was insensitive to DTM type (F1 scores > 0.96). Predictions of DBH using PLS models were consistently more accurate than RF models and accuracy was insensitive to the DTM type. Using data from the native DTMs, DBH estimation using PLS had the lowest RMSE of 1.624 cm (R² of 0.756) at a point density of 12,200 points/m². Stem volume predictions made using PLS predictions of DBH and height from the ULS had the lowest RMSE of 0.0418 m³ (R² of 0.792) at 12,200 points/m². The RMSE values for DBH and volume remained relatively stable from 12,200 to between 750 and 400 points/m², with reductions in accuracy occurring as point density declined below this threshold. Overall, these findings have significant implications, particularly for the precise estimation of DBH and stem volume at the individual tree level. They demonstrate the potential of cost-effective ULS sensors for rapid and frequent plantation forest assessment, thereby enhancing the application of light detection and ranging (LiDAR) technology in plantation forest management. Full article

This study demonstrates a framework for using high-resolution satellite imagery to automatically map and monitor outbreaks of red needle cast (Phytophthora pluvialis) in planted pine forests. This methodology was tested on five WorldView satellite scenes collected over two sites in the Gisborne Region of New Zealand’s North Island. All scenes were acquired in September: four scenes were acquired yearly (2018–2020 and 2022) for Wharerata, while one more was obtained in 2019 for Tauwhareparae. Training areas were selected for each scene using manual delineation combined with pixel-level thresholding rules based on band reflectance values and vegetation indices (selected empirically) to produce ‘pure’ training pixels for the different classes. A leave-one-scene-out, pixel-based random forest classification approach was then used to classify all images into (i) healthy pine forest, (ii) unhealthy pine forest or (iii) background. The overall accuracy of the models on the internal validation dataset ranged between 92.1% and 93.6%. Overall accuracies calculated for the left-out scenes ranged between 76.3% and 91.1% (mean overall accuracy of 83.8%), while user’s and producer’s accuracies across the three classes were 60.2–99.0% (71.4–91.8% for unhealthy pine forest) and 54.4–100% (71.9–97.2% for unhealthy pine forest), respectively. This work demonstrates the possibility of using a random forest classifier trained on a set of satellite scenes for the classification of healthy and unhealthy pine forest in new and completely independent scenes. This paves the way for a scalable and largely autonomous forest health monitoring system based on annual acquisitions of high-resolution satellite imagery at the time of peak disease expression, while greatly reducing the need for manual interpretation and delineation. Full article

Despite the utility of thermal imagery for characterising the impacts of water stress on plant physiology, few studies have been undertaken on plantation-grown conifers, including the most widely planted exotic species, radiata pine. Using data collected from a pot trial, where water was withheld from radiata pine over a nine-day period, the objectives of this study were to (i) determine how rapidly key physiological traits change in response to water stress and (ii) assess the utility of normalised canopy temperature, defined as canopy temperature–air temperature (Tc–Ta), for detecting these physiological changes. Volumetric water content remained high in the well-watered control treatment over the course of the experiment (0.47–0.48 m³ m⁻³) but declined rapidly in the water stress treatment from 0.47 m³ m⁻³ at 0 days after treatment (DAT) to 0.04 m³ m⁻³ at 9 DAT. There were no significant treatment differences in measurements taken at 0 DAT for Tc–Ta, stomatal conductance (gs), transpiration rate (E) or assimilation rate (A). However, by 1 DAT, differences between treatments in tree physiological traits were highly significant, and these differences continued diverging with values in the control treatment exceeding those of trees in the water stress treatment at 9 DAT by 42, 43 and 61%, respectively, for gs, E and A. The relationships between Tc–Ta and the three physiological traits were not significant at 0 DAT, but all three relationships were highly significant from as early as 1 DAT onwards. The strength of the relationships between Tc–Ta and the three physiological traits increased markedly over the duration of the water stress treatment, reaching a maximum coefficient of determination (R²) at 7 DAT when values were, respectively, 0.87, 0.86 and 0.67 for gs, E and A. The early detection of changes in tree physiology from 1 DAT onwards suggests that thermal imagery may be useful for a range of applications in field-grown radiata pine. Full article

Carbon sequestration has become an important source of supplementary revenue from forest plantations. Although there are many financial comparisons of species based on timber revenue, there have been few regional comparisons that integrate revenue from carbon. Within New Zealand, radiata pine is the most widely planted species, but there has been a recent upsurge in planting rates for coast redwood. Under New Zealand’s Emissions Trading Scheme, areas that are newly afforested under clear-fell rotational forestry receive carbon payments up to a set age, intended to represent the long-term average under successive rotations. Using growth models for both species, the objectives of this research were to regionally quantify (i) how the rotation length and the carbon averaging age influenced the profitability of growing redwood and (ii) compare carbon, timber yields, and profitability between radiata pine and redwood. The results showed the legislated carbon averaging age of 22 years for redwood underestimated the actual mid-points of carbon accumulation, which averaged 26, 28, and 31 years across rotation lengths of 40, 45, and 50 years, respectively. The optimal rotation length for redwood varied markedly by region and carbon price but was most often 40 years, increasing to 50 years at higher carbon prices, particularly for southern regions. Under regimes where revenue was only derived from timber, the redwood internal rate of return (IRR) exceeded that of radiata pine for eight of the nine New Zealand regions. When revenue was received from carbon and timber, redwood had a higher IRR than radiata pine up to carbon prices ranging from 29 to 50 NZD/tonne CO₂ for the North Island and 23 to 34 NZD/tonne CO₂ in all South Island regions apart from Otago. The IRR of radiata pine exceeded that of redwood at carbon prices above these values for the eight regions and at all carbon prices within the cold, dry Otago region. Full article

This work was aimed at the characterization of residual generated biomass from pruned tree species present in the Andean areas of Ecuador as a source of energy, both in plantations and in urban areas, as a response to the change in the energy matrix proposed by the Ecuadorian government. From the proximate analysis (volatiles, ashes, and fixed carbon content), elemental analysis (C, H, N, S, O, and Cl), structural analysis (cellulose, lignin, and hemicellulose content), and higher heating value, the studied species were pine (Pinus radiata), cypress (Cupressus macrocarpa), eucalyptus (Eucalyptus globulus), poplar (Populus sp.), arupo (Chionanthus pubescens), alder (Alnus Acuminata), caper spurge (Euphorbia laurifolia), and lime (Sambucus nigra L.) trees. We evaluated the influence of the presence of leaves in the biomass. From this characterization, we developed a method based on obtaining the main components for the identification of the biomass’s species. If the origin of the biomass was unknown, this method enabled us to identify the species, with all its characteristics. If the origin of the biomass was unknown, this innovative method enabled the identification of the species from the lignocellulosic biomass, with all of its characteristics. Finally, we developed regression models that relate the higher heating value to the elemental, proximate, and structural composition. Full article

Commercial forest plantations in Chile are dominated by pine (Pinus radiata) and eucalyptus (Eucalyptus globulus). Tree bark is the main by-product of the forestry industry and has low value, but great potential for use as an agricultural substrate. However, the direct use of bark fibers may cause plant phytotoxicity due to the presence of polyphenolic and other compounds. This study aims to evaluate the physicochemical properties of E. globulus and P. radiata bark after water extraction treatments. The phytotoxicity of the resulting extracted bark alone and that mixed with commercial substrates (coconut fiber, moss, peat, and composted pine) at different ratios (25 to 75 wt%) were assessed using the Munoo-Liisa vitality index (MLVI) test. For all treatments, the seed germination and growth of radish (Raphanus sativus) and Chinese cabbage (Brassica rapa) species were evaluated and compared to a commercial growing medium (peat) as a control. The optimal mixture for seed growth was determined to be 75% extracted E. globulus bark fiber and 25% commercial substrates such as peat (P), coconut fiber (C), moss (M), and composted pine (CP), as indicated by the MLVI and germination results. Two phytostimulant products, chitosan and alginate-encapsulated fulvic acid, were added to the best substrate mixture, with the purpose of improving their performance. Encapsulated fulvic acid at 0.1% w/v was effective in promoting plant growth, while chitosan at all of the concentrations studied was effective only for mixture 75E-25CP. The mixture of E. globulus fiber and commercial substrates, containing a high proportion of water-extracted fiber (75%), shows the potential to be used in the growth of horticultural crops and in the plant nursery industry. Full article

Increasing concerns regarding carbon emissions and climate change are prompting a shift toward the use of sustainable materials in the construction industry. Engineered timber products are gaining attention in the construction industry due to advancements in lamination techniques and adhesives as well as the renewable characteristics of wood. Bond properties play a significant role in engineered timber products. In Australia, Radiata Pine (RP, softwood) and Shining Gum (SG, hardwood) share a large proportion of local and native plantation forest resources. The present paper investigates the bond behaviours of Australian softwoods (RP–RP), hardwoods (SG–SG) and hybrid-wood (RP–SG) combinations in both parallel (PAL) and perpendicular (PER) bonding directions using one-component polyurethane adhesives. The results indicate that most of the softwood samples were subjected to wood-side (timber) failure, whereas hardwood samples failed due to delamination but exhibited higher strength and stiffness regardless of bond direction. In contrast, bond direction had a significant effect on the bond characteristics of hybrid configurations. Improved bond properties were observed when bonded in PAL directions; however, negative effects were seen when bonded in PER directions. Obtained characteristic (5th percentile) shear bond strengths for RP–RP–PAL, RP–SG–PAL and SG–SG–PAL samples were 3.88 MPa, 6.19 MPa and 8.34 MPa, whilst those for RP–RP–PER, RP–SG–PER and SG–SG–PER samples were 3.45 MPa, 2.96 MPa and 7.83 MPa, respectively. Full article

Sediment production and transport in a basin are generally a function of the degree of soil protection, normally represented by plant cover. In this study, two basins located at similar latitudes but with different hydrological regimens and plant covers were studied, one with a pluvial regimen and forest plantations (Purapel) and another one with the pluvio-nival regimen and native forest (Ñuble). For this purpose, sediment yield was analyzed in both drainage areas using the Mann-Kendall statistical test. Both basins showed larger amounts of sediment production during winter months. In addition, sediment yield trends did not show significant variation in the case of the Ñuble, most likely due to non-relevant changes in plant cover over time. However, there is a sustained decrease in annual sediment release at Purapel, coinciding with the afforestation in the basin, so it is logical to attribute the referred reduction to this process. For the first time, the behavior of two watersheds is contrasted, one covered with native forest and the other one with forest plantations, appreciating that the basin covered with plantations presents a reduction in sediment production over time, which means that forest plantations are efficient in sediment retention, even in contrast to native forest. However, both basins have different types of soil, topography, etc., meaning that more studies are needed to support this theory. Full article