Search Results (550)

Climate extremes threaten the resilience of Eucalyptus plantations, yet hybridization with drought-tolerant species may enhance stress tolerance. This study analyzed xylem anatomical and functional drought responses in commercial Eucalyptus grandis (GG) clones and hybrids: E. grandis × camaldulensis (GC), E. grandis × tereticornis (GT), and E. grandis × urophylla (GU1, GU2). We evaluated vessel traits (water transport), fibers (mechanical support), and wood density (D) in stems and branches. Theoretical stem hydraulic conductivity (k_Stheo), vessel lumen fraction (F), vessel composition (S), and associations with previous hydraulic and growth data were assessed. While general drought responses occurred, GC had the most distinct xylem profile. This may explain it having the highest performance in different irrigation conditions. Red gum hybrids (GC, GT) maintained k_Stheo under drought, with stable F and a narrower vessel size, especially in branches. Conversely, GG and GU2 reduced F and S; and stem k_Stheo declined for a similar F in these clones, indicating vascular reconfiguration aligning the stem with the branch xylem. Almost all clones increased D under drought in any organ, with the highest increase in red gum hybrids. These results reveal diverse anatomical adjustments to drought among clones, partially explaining their growth responses. Full article

The ongoing decade of UN restoration matches with the European goal of bringing nature back into our lives, including in urban systems, and Nature Restoration Regulation. Within such a framework, this work is aimed at highlighting the ecological rationale and strategic value of an NRRP measure devoted to forest restoration in Italian Metropolitan Cities, and at assessing respective preliminary results. Therefore, the measure’s overarching goal (not to create urban parks or gardens, but activate forest recovery), geographic extent and scope (over 4000 ha and more than 4 million planted trees and shrubs across the country), plantation model (mandatory use of native species consistent with local potential vegetation, density of 1000 seedlings per ha, use of at least four tree and four shrub species in each project, with a minimum proportion of 70% for trees, certified provenance for reproductive material), and compulsory management activities (maintenance and replacement of any dead plants for at least five years), are herein shown and explained under an ecological perspective. Current implementation outcomes were thus assessed in terms of coherence and expected biodiversity benefits, especially with respect to ecological and biogeographic consistency of planted forests, representativity in relation to national and European plant diversity, biogeographic interest and conservation concern of adopted plants, and potential contribution to the EU Habitats Directive. Compliance with international strategic goals and normative rules, along with recognizable advantages of the measure and limitations to be solved, are finally discussed. In conclusion, the forestation model proposed for the Italian Metropolitan Cities proved to be fully applicable in its ecological rationale, with expected benefits in terms of biodiversity support plainly met, and even exceeded, at the current stage of implementation, especially in terms of the contribution to protected habitats. These promising preliminary results allow the model to be recognized at the international level as a good practice that may help achieve protection targets and sustainable development goals within and beyond urban systems. Full article

Logs supplied in Papua New Guinea and Indonesia are predominantly sourced from fast-growing tree species of plantation forests. The timber primarily consists of sapwood, which is highly susceptible to biodeterioration. At a training center, CCA (chromated copper arsenate) is still used for wood preservation, while in the wood industry, ACQ (alkaline copper quaternary) is commonly applied to enhance the service life of timber. In the future, polystyrene impregnation or other non-biocidal treatments could potentially serve this purpose. This study aimed to determine the discoloration and resistance of polystyrene-impregnated and CCA-preserved woods. Wood samples, Anisoptera thurifera and Octomeles sumatrana from Papua New Guinea, and Anthocephalus cadamba and Falcataria moluccana from Indonesia, were used. The wood samples were treated with polystyrene impregnation, CCA preservation, or left untreated, then exposed at the PNG Forest Research Institute site for four months. After treatment, the color change in polystyrene-impregnated wood was minor, whereas CCA-preserved wood exhibited a noticeably different color compared to untreated wood. The average polymer loading for polystyrene-impregnated wood reached 147%, while the average CCA retention was 8.4 kg/m³. Densities of untreated-, polystyrene-, and CCA-wood were 0.42, 0.64, and 0.45 g/cm³, respectively, and moisture contents were 15.8%, 9.4%, and 13.4%, respectively. CCA preservation proved highly effective in preventing termite attacks; however, CCA is hazardous to living organisms, including humans. Polystyrene impregnation also significantly improved wood resistance to subterranean termites, as indicated by lower weight loss and a higher protection level compared to untreated wood. Additionally, polystyrene treatment is nonhazardous and safe for living organisms, making it a promising option for enhancing wood resistance to termite attacks in the future as an alternative to the biocides currently in use. Full article

Traditional rainfed fig orchards intended for fresh consumption tend to have low yields and cultural practices difficulties due to wide plant spacing and large canopies. This study investigates whether the espalier training system, commonly employed in other fruit species, can be applied to fig cultivation to improve productivity and fruit quality under high-density irrigated plantations. For the first time, four fig varieties (‘San Antonio’, ‘Dalmatie’, ‘Albacor’, and ‘De Rey’) were evaluated in a high-density system (625 trees/ha) using espalier training over four consecutive years (2018–2021) in southwestern Spain. Among the varieties, ‘Dalmatie’ demonstrated the highest suitability to the system, combining low vegetative vigour with superior yield performance, reaching a cumulative yield of 103.15 kg/tree and yield efficiency of 1.94 kg/cm². ‘San Antonio’ was the earliest to ripen and exhibited the longest harvest duration (81 days), enabling early and extended market availability. In terms of fruit quality, ‘Albacor’ stood out for its high total soluble solids content (24.97 °Brix), while ‘De Rey’ exhibited the best sugar–acid balance, with a maturity index of 384.58. The present work demonstrates that intensive fig cultivation on espalier structures offers an innovative alternative to traditional systems, thereby enhancing orchard efficiency, management, and fruit quality. Full article

In the context of accelerating global climate change, the accurate quantification of forest carbon sequestration at the regional scale is of critical importance to estimate carbon budgets and formulate targeted ecological policies. This study systematically investigated the spatiotemporal dynamics and driving mechanisms of arbor forest carbon stocks between 2016 and 2020 in Yunnan Province, China. Based on the “One Map” forest resource inventory, the continuous biomass expansion factor (CBEF) method, standard deviational ellipse (SDE) analysis, and multiple linear regression (MLR) modeling, the results showed the following. (1) Arbor forest carbon stocks steadily increased from 832.13 Mt to 938.84 Mt, and carbon density increased from 41.92 to 42.32 t C·hm⁻². Carbon stocks displayed a dual high pattern in the northwest and southwest, with lower values in the central and eastern regions. (2) The spatial centroid of carbon stocks shifted 4.8 km eastward, driven primarily by afforestation efforts in central and eastern Yunnan. (3) The MLR results revealed that precipitation and economic development were significant positive drivers, whereas temperature, elevation, and anthropogenic disturbances were major limiting factors. A negative correlation to afforestation area indicated a diminished need for new plantations as forest quality and quantity improved. These results provided a theoretical foundation for spatially differentiated carbon sequestration strategies in Yunnan, providing key insights for reinforcing ecological security in Southwest China and enhancing national carbon neutrality objectives. Full article

This study investigated the effects of planting density and site index on stand attributes and soil nutrients in mature Chinese fir [Cunninghamia lanceolata (Lamb.) Hook.] plantations across Fujian and Sichuan Provinces, elucidating the pathways through which these factors influence standing volume (SV). The results showed that (1) planting density significantly affected stand variables, with average diameter at breast height (ADBH) decreasing and SV initially increasing and then declining with higher density. The number of mortality plants (NMP) and actual stand density (ASD) both increased significantly with higher density. Average tree height (ATH) and dominant height (DH) responses varied by region, with ATH decreasing in Sichuan and DH decreasing in Fujian with higher density. (2) Planting density affected soil nutrients differently in the two provinces, with soil total potassium (TK) increasing in Fujian and phosphorus decreasing in Sichuan. (3) Site index was positively correlated with ATH and ADBH but negatively correlated with ASD and NMP. Its relationship with soil nutrients was province-specific: in Fujian, site index was negatively correlated with total phosphorus (TP) and positively correlated with TK and soil pH, while in Sichuan it was only positively correlated with TK. (4) Structural equation modeling revealed different regulatory pathways: in Fujian, planting density influenced SV through both ASD and soil nutrients, while in Sichuan it affected only through ASD. This study highlights the region-specific interactions between planting density, site index, stand structure, and soil nutrients, providing a foundation for optimized plantation management. Full article

Acacia hybrid is an important plantation species in Malaysia, but its use in structural applications is still limited due to the lack of comprehensive data on its engineering properties. This study evaluated the physical and mechanical properties of laminated or glulam Acacia hybrid timber in an air-dried condition for three age group combinations (7//10, 10//13, and 7//13 years old) to determine the optimal combination for structural applications. The results showed that the 10//13-year-old combination had the best mechanical performance, along with the highest basis density (0.7099 g/cm³), highest modulus of elasticity (MOE) (16,335.6 N/mm²), and highest parallel compressive strength (56.998 N/mm²), while the 7//10-year-old combination showed the highest moisture content (14.94%) and highest perpendicular compressive strength (8.9256 N/mm²). This study demonstrated that the combination of juvenile wood (7 years old) with mature wood (10 or 13 years old) increased strength by up to 43.06%, thus optimising the potential of Acacia hybrid in the construction industry. All combinations meet SG5 standards, with the 10//13-year-old combination recommended as the best choice for high-performance applications of glulam products. Full article

Pellets can be produced not only from forest dendromass but also from agricultural dendromass derived from short rotation coppice (SRC) plantations, as well as surplus straw from cereal and oilseed crops. This study aimed to determine the thermophysical properties and elemental composition of 16 types of pellets produced from four types of forest biomass (Scots pine I, alder, beech, and Scots pine II), four types of agricultural biomass (SRC willow, SRC poplar, wheat straw, and rapeseed straw), and eight types of pellets from mixtures of wood biomass and straw. Another aim of the study was to demonstrate which pellet types met the parameters specified in three standards, categorizing pellets into thirteen different classes. As expected, pellets produced from pure Scots pine sawdust exhibited the best quality. The quality of the pellets obtained from mixtures of dendromass and straw deteriorated with an increase in the proportion of cereal straw or rapeseed straw in relation to pure Scots pine sawdust and SRC dendromass. The bulk density of the pellets ranged from 607.9 to 797.5 kg m⁻³, indicating that all 16 pellet types met the requirements of all six classes of the ISO standard. However, it was determined that four types of pellets (rapeseed, wheat, and two others from biomass mixtures) did not meet the necessary requirements of the Premium and Grade 1 classes. The ash content ranged from 0.44% DM in pellets from pure Scots pine sawdust to 5.00% DM in rapeseed straw pellets. Regarding ash content, only the pellets made from pure Scots pine sawdust met the stringent requirements of the highest classes, A1, Premium, and Grade 1. In contrast, all 16 types of pellets fulfilled the criteria for the lower classes, i.e., Utility and Grade 4. Concerning the nitrogen (N) content, seven types of pellets met the strict standards of classes A1 and Grade 1, while all the pellets satisfied the less rigorous requirements of classes B and Grade 4. Full article

Clarifying spatiotemporal variations in transpiration and their influencing mechanisms is highly valuable for the accurate assessment of hillslope-scale transpiration and for the effective management of forest–water coordination. Here, the sap flow density, meteorological conditions, and soil moisture downslope and upslope of a Larix gmelinii var. principis-rupprechtii plantation hillslope were observed during the growing season (June to September) in 2023, China. The results revealed that transpiration per unit leaf area (T_L) was significantly lower at the upslope position than at the downslope position, with mean values of 0.21 and 0.31 mm·d⁻¹, respectively; these data were associated with the lower canopy conductance per unit leaf area induced by the higher vapor pressure deficit (VPD) and lower soil water content at the 40–60 cm soil depth at the upslope position. The temporal variations in the T_L were controlled by solar radiation, VPD, air temperature, and soil moisture at both slope positions, and the quantitative relationships established from these factors explained 89% of the variation in the T_L. The slope position did not affect the response functions between the T_L and the controlling factors but changed the contribution to the T_L. Compared with those at the downslope position, the contributions from solar radiation and VPD (air temperature) decreased (increased) at the upslope position, and the contribution of soil moisture was essentially similar at both slope positions. Transpiration mainly utilized water from the 20–60 cm soil depth; these results indicated that the soil water content at the 20–40 and 40–60 cm soil depths contributed more to the T_L than did that at the 0–20 cm soil depth. Based on our findings, changes in the environmental conditions caused by slope position have a critical impact on transpiration and can contribute to the development of hillslope-scale transpiration estimates and precise integrated forest and water management. Full article

Plant roots and soil properties play crucial roles in regulating soil hydrological processes, particularly in determining soil water infiltration capacity. However, the infiltration patterns and underlying mechanisms across different forest types in subtropical regions remain poorly understood. In this study, we measured the infiltration characteristics of three typical stands (pure Phyllostachys edulis forest, mixed Phyllostachys edulis-Cunninghamia lanceolata forest, and pure Cunninghamia lanceolata forest) using a double-ring infiltrometer. Stepwise multiple regression and structural equation modeling (SEM) were employed to analyze the effects of root traits and soil physicochemical properties on soil infiltration capacity. The results revealed the following: (1) The initial infiltration rate (IIR), stable infiltration rate (SIR), and average infiltration rate (AIR) followed the order pure Phyllostachys edulis stand > mixed stand > pure Cunninghamia lanceolata stand. (2) Compared to the pure Cunninghamia lanceolata stand, the IIR, SIR, and AIR in the pure Phyllostachys edulis stand increased by 6.66%, 35.63%, and 28.51%, respectively, while those in the mixed stand increased by 28.79%, 28.82%, and 33.51%. (3) Fine root biomass, root length density, non-capillary porosity, and soil bulk density were identified as key factors influencing soil infiltration capacity. (4) Root biomass and root length density affected infiltration capacity through both direct pathways and indirect pathways mediated by alterations in non-capillary porosity and soil bulk density. These findings provide theoretical insights into soil responses to forest types and inform sustainable water–soil management practices in Phyllostachys edulis plantations. Full article

Michelia macclurei, a valuable native broad-leaved species with good ecological and economic benefits and a key afforestation tree in South China, is facing progressive stand degradation and soil fertility decline with age. To investigate age-dependent dynamics of stand structure and soil properties, this study examined five stands (5, 10, 15, 20, and 42 a) in Yunfu City, Guangdong Province. The results revealed that (1) spatial distribution shifted from aggregated in young stands (5–10 a) to random in mature stands (42 a), with diameter and height class distributions becoming more diverse with age. Notably, topsoil (0–20 cm) in near-mature stands (15–20 a) exhibited not only significantly higher capillary porosity, non-capillary porosity, and water-holding capacity compared to young stands but also increased bulk density, indicating soil physical degradation. (2) Soil nutrient decline was observed in over-mature stands (42 a), characterized by a reduction in soil total nitrogen to 1.08 ± 0.06 g·kg⁻¹ and total phosphorus to 0.16 ± 0.02 g·kg⁻¹ in the topsoil (0–20 cm layer), suggesting age-related soil nutrient degradation. (3) Correlation analysis revealed a significant negative correlation between total potassium content and crown uniformity indices (p < 0.01), while available phosphorus was significantly positively correlated with crown and tree growth (p < 0.05). These findings provide critical insights for developing stage-specific management strategies in Michelia macclurei plantations. Full article

Accurate individual tree segmentation (ITS) in dense rubber plantations is a challenging task due to overlapping canopies, indistinct tree apexes, and intricate branch structures. To address these challenges, we propose a bottom-up, multi-feature fusion method for segmenting rubber trees using UAV-LiDAR point clouds. Our approach first involves performing a trunk extraction based on branch-point density variations and neighborhood directional features, which allows for the precise separation of trunks from overlapping canopies. Next, we introduce a multi-feature fusion strategy that replaces single-threshold constraints, integrating geometric, directional, and density attributes to classify core canopy points, boundary points, and overlapping regions. Disputed points are then iteratively assigned to adjacent trees based on neighborhood growth angle consistency, enhancing the robustness of the segmentation. Experiments conducted in rubber plantations with varying canopy closure (low, medium, and high) show accuracies of 0.97, 0.98, and 0.95. Additionally, the crown width and canopy projection area derived from the segmented individual tree point clouds are highly consistent with ground truth data, with R² values exceeding 0.98 and 0.97, respectively. The proposed method provides a reliable foundation for 3D tree modeling and biomass estimation in structurally complex plantations, advancing precision forestry and ecosystem assessment by overcoming the critical limitations of existing ITS approaches in high-closure tropical agroforests. Full article

Camellia oleifera harvester is a compact agricultural vehicle utilized in plantations located in China’s red soil hilly regions. To enhance its functionality and off-road performance, additional electronic devices and a more powerful powertrain system have been integrated within the engine compartment. However, the increased component density has resulted in constrained heat dissipation space, leading to critical issues including insufficient engine power, delayed control response, and reduced vibration frequency of the harvesting device. These thermal problems significantly compromise operational efficiency and pose safety hazards to operators. To address these heat dissipation challenges, this study proposes a collaborative optimization approach integrating computational fluid dynamics (CFD) simulation with an Adaptive Particle Swarm Optimization (APSO) algorithm. Initially, preliminary experiments, coupled with CFD simulations, were conducted to analyze the airflow distribution and temperature field within the engine compartment. Based on these findings, the component arrangement was reconfigured to improve thermal performance. Subsequently, an “engine compartment cover parameters–temperature” correlation model was established, and the dimensional parameters of the engine compartment cover were optimized using the APSO algorithm. Experimental results demonstrate that the optimized configuration achieves an average surface temperature reduction of approximately 17.82% for critical components, enabling prolonged stable operation and significantly enhanced operational reliability of the harvester. 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

Accurate estimation of green canopy cover (GCC) in rubber plantations is crucial for monitoring vegetation health and assessing stress impacts. This study validates satellite-derived GCC estimates using unmanned aerial vehicle (UAV)-based remote sensing, ground observations, spaceborne remote sensing (satellite imagery), and supervised machine learning regression approaches. Sentinel-2 and Landsat imagery were utilized to derive spectral vegetation indices (SVIs) under varying stress conditions, while UAV-based GCC assessments provided high-resolution reference data for validation. The findings revealed that while certain SVIs exhibited strong correlations with canopy density under stable conditions, their predictive accuracy declined significantly during extreme stress events, such as Pestalotiopsis outbreaks and seasonal leaf fall periods. To improve estimation accuracy, supervised machine learning regression models were developed, with Random Forest (RF) outperforming Support Vector Machines (SVMs), Classification and Regression Trees (CARTs), and Linear Regression (LR). RF achieved the highest predictive accuracy (R² = 0.82, RMSE = 6.48, MAE = 4.97), demonstrating its reliability in capturing non-linear interactions between canopy heterogeneity and environmental stressors. These results highlight the limitations of traditional vegetation indices and emphasize the importance of multi-sensor integration and advanced modeling techniques for more precise GCC monitoring. Full article