Search Results (305)

Chinese fir [Cunninghamia lanceolata (Lamb.) Hook.] is a fast-growing species widely utilized in construction, industrial raw materials. Owing to its broad application scope, research on Chinese fir is fragmented across multiple disciplines, making it difficult to grasp the overall research context and trends. Following the PRISMA guidelines, we retrieved articles related to Chinese fir published between 1942 and 2024 from Chinese databases (i.e., CNKI, Wanfang Data, and VIP Chinese Journal Database) and the Web of Science Core Collection (WOSCC). After removing duplicate and irrelevant records, a total of 7174 valid records were retained, including 5862 from Chinese databases and 1312 from WOSCC. The PRISMA-screened literature was imported into CiteSpace V.6.2.R4 for bibliometric analysis. Through keyword clustering, burst detection, and timeline mapping, we focused on analyzing the domestic resource distribution, research hotspots, and evolutionary trends of Chinese fir research. The results showed that research publications on Chinese fir have increased year by year, and international research started earlier and is more in-depth, while Chinese research covers a wider scope. Both follow two stages (germination and growth). Chinese research focuses on basic application areas such as seedling cultivation and plantation management; international research emphasizes ecological functions and biomass development. Global research exhibits convergence in the field of eco-environmental interactions; specifically, both domestic and international studies investigate the impacts of climate change (e.g., drought and global warming) and nitrogen deposition on the growth and functional evolution of Chinese fir. This study provides references for researchers, forestry policymakers, and planters. Full article

Accurate biomass and carbon estimation in tropical plantation forests requires species-specific allometric models. Silver Oak (Grevillea robusta A. Cunn. ex R. Br.), cultivar “AVAONE,” is widely planted in northeastern Thailand, yet locally calibrated equations remain limited. This study developed species- and site-specific allometric models using destructive sampling of eight trees (n = 8) aged 2–9 years from a single plantation in Pak Chong District, Nakhon Ratchasima Province, without independent validation. Each tree was separated into stem, branches, leaves, and roots to determine fresh and dry biomass, and carbon concentrations were measured using a LECO CHN628 analyzer in an ISO/IEC 17025-accredited laboratory. Aboveground biomass increased from 17.49 kg at age 2 to 860.42 kg at age 9, with the most rapid gains occurring between ages 6 and 9. Tree height stabilized at approximately 19–20 m after age 7, while diameter continued to increase. Stems accounted for the largest proportion of dry biomass, followed by branches and roots. Carbon concentrations ranged from 45.561% to 48.704%, close to the IPCC default value of 47%. Power-law models based on D²H showed clear relationships with biomass, with R² values ranging from 0.7365 to 0.9372 for individual components and 0.8409 for aboveground biomass. These locally derived equations provide preliminary, site-specific relationships for estimating biomass and carbon stocks in Silver Oak AVAONE plantations and offer a baseline for future studies with expanded sampling and independent validation. Full article

Acacia melanoxylon R.Br. demonstrates strong biological nitrogen–fixation capacity and favourable economic returns, making it a promising candidate for the development of subtropical forestry in South Asia. It is a fast–growing leguminous tree species widely promoted for cultivation in China, and it is also one of the ideal tree species for improving soil fertility in forest lands. What are the synergistic mechanisms between A. melanoxylon-Eucalyptus stands and pure Eucalyptus spp.? Current theories regarding A. melanoxylon–Eucalyptus systems remain relatively fragmented due to the lack of effective silvicultural measures, resistance studies, and comprehensive ecological–economic benefit evaluations. The absence of an integrated analytical framework for holistic research on A. melanoxylon–Eucalyptus systems makes it difficult to summarise and comprehensively analyse their growth and development, thereby limiting the optimisation and widespread application of their models. This study employed CiteSpace bibliometric analysis and qualitative methods to explore ideal tree species combination patterns, elucidate their intrinsic eco–economic synergistic mechanisms, and reasonably reveal their collaborative potential. This study systematically reviewed silvicultural management, stress physiology, ecological security, and economic policy using the Chinese and English literature published from 2010 to 2025. The narrative synthesis results indicated that strip intercropping (7:3) is widely documented as an effective model for creating vertical niche complementarity, whereby canopy light and thermal utilisation by A. melanoxylon species improve subsoil nutrient cycling by enhancing stand structure. A conceptual full–cycle economic assessment framework was proposed to measure carbon sequestration and timber premiums. Correspondingly, this conversion of implicit ecological services into explicit market values acted as a critical tool for decision–making in assessing benefit. A three–dimensional “cultivation strategy–physiological ecology–value assessment” assessment framework was established. This framework demonstrated how to move from wanting to maximise the output of an individual component to maximising the value of the whole system. It theorised and provided guidance on resolving the complementary conflict between “ecology–economy” in the management of sustainable multifunctional plantations. Full article

The long-term monoculture of Eucalyptus plantations in southern China has raised ecological concerns, prompting a shift towards mixed-species plantations as a sustainable alternative. This study investigates the mechanisms by which companion tree species enhance soil functionality in subtropical red soil regions. A field experiment compared a pure Eucalyptus (CK) plantation with three mixed-species plantations: Eucalyptus × Mytilaria laosensis (A × M), Eucalyptus × Magnolia hypolampra (A × H), and Eucalyptus × Michelia gioii (A × X). Comprehensive soil analyses were conducted at three soil depths (0–20 cm, 20–40 cm, and 40–60 cm) to assess chemical properties, enzyme activities, and humus components, and soil organic carbon (SOC) molecular structure was characterized by Fourier-Transform Infrared Spectroscopy (FTIR), with the relationships quantified using structural equation modeling (SEM) to test predefined causal hypotheses. The results showed that A × H significantly boosted topsoil fertility (e.g., OM: 46.61 g/kg), while A × M enhanced the recalcitrant organic carbon (ROC: 35.29 g/kg), indicating superior carbon sequestration potential. The FTIR analysis revealed species-specific alterations in SOC chemistry, such as increased aromatic compounds in A × H/A × X. The SEM analysis demonstrated that the latent variable “Humus” (reflected by LOC and ROC) directly and positively influenced the latent variable “Soil Fertility” (reflected by pH, OM, and AP; path coefficient: 0.62). In contrast, the latent variable “Organic Components” (reflected by specific FTIR functional groups) exhibited a significant direct negative effect on “Soil Fertility” (−0.41). The significant pathway from “Organic Components” to “Enzymatic Activity” (0.55*) underscored the role of microbial mediation. The study concludes that mixed plantations, particularly with Mytilaria laosensis (A × M), improve soil health through an “organic input–microbial enzyme response–humus formation” pathway, offering a scientific basis for sustainable forestry practices that balance productivity and ecological resilience. Full article

Eucalypt plantations form the basis of Brazilian forestry; however, successive rotations under coppice systems often experience productivity declines. This study presents an original long-term investigation over a 13-year cultivation cycle (2005–2018) with Eucalyptus grandis W. Hill ex Maiden × E. urophylla S. T. Blake, assessing whether the full maintenance of nine phosphate fertilization packages could sustain productivity from the first to the second rotation in a commercial plantation in Itamarandiba, Minas Gerais. Continuous forest inventories and rotation-specific growth modeling were used. Productivity in the second rotation declined by 33%–46% in packages TP1 to TP6, which included various phosphorus sources, highlighting the recurring challenges of coppice systems. Conversely, the highest and most consistent yields (~305 m³ ha⁻¹ rotation⁻¹) were obtained with package TP9, which consisted of 280 kg ha⁻¹ of triple superphosphate (TSP) applied at the beginning of each rotation and 600 kg ha⁻¹ of ammonium sulfate (SA) in split topdressing applications. These findings demonstrate that the full maintenance of fertilization, specifically with highly soluble phosphorus sources combined with balanced nitrogen and sulfur supplementation, is an effective strategy to secure productivity and ensure the economic viability of coppice systems. This offers a new paradigm for managing successive rotations, where nutritional synergy, rather than single-nutrient fertilization, is key to enhancing the resilience of clonal eucalypt plantations. Full article

Carbon sequestration by vegetation and soil conservation are vital components in balancing greenhouse gas emissions and enhancing terrestrial ecosystem carbon sinks. They also represent an efficient pathway towards achieving carbon neutrality objectives and addressing numerous environmental challenges arising from global warming. Soil and water conservation, as crucial elements of ecological civilisation development, constitute a key link in realising carbon neutrality. This study systematically quantifies and forecasts the spatiotemporal characteristics of carbon sink capacity in soil and water conservation within the study area of Puding County, a typical karst region in Guizhou Province, China. Following a research approach of “mechanism elucidation–model construction–categorised estimation”, we established a carbon sink calculation system based on the dual mechanisms of vertical biomass carbon fixation via vegetative measures and horizontal soil organic carbon (SOC) retention using engineering measures. This system combines forestry, grassland, and engineering, with the aim of quantifying regional carbon sinks. Machine learning regression algorithms such as Random Forest, ExtraTrees, CatBoost, and XGBoost are used for backtracking estimation and optimisation modelling of soil and water conservation as carbon sinks from 2010 to 2022. The results show that the total carbon sink capacity of soil and water conservation in Puding County in 2017 was 34.53 × 10⁴ t, while the contribution of engineering measures was 22.37 × 10⁴ t. The spatial distribution shows a pattern of “higher in the north and lower in the south”. There are concentration hotspots in the central and western regions. Model comparison demonstrates that the Random Forest and extreme gradient boosting regression models are the best models for plantations/grasslands and engineering measures, respectively. The LSTM model was applied to predict carbon sink variables over the next ten years (2025–2034), showing that the overall situation is relatively stable, with only slight local fluctuations. This study solves the problem of the lack of quantitative data on soil and water conservation as carbon sinks in karst areas and provides a scientific basis for regional ecological governance and carbon sink management. Our findings demonstrate the practical significance of promoting the realisation of the “double carbon” goal. Full article

The nitrogen (N) uptake preferences of mature tropical trees remain poorly understood, largely because traditional hydroponic methods fail to adequately simulate field conditions. To address this, we applied an in situ whole-tree paired ¹⁵N labeling experiment to quantify N acquisition strategies in three common species of tropical plantations in southern China: Hevea brasiliensis, Pinus caribaea, and Acacia mangium. The in situ whole-tree paired ¹⁵N labeling experiment revealed distinct species-specific nitrogen uptake strategies: Hevea brasiliensis preferentially absorbed nitrate (contributing 76% to total N uptake), Pinus caribaea relied more heavily on ammonium (61%), while Acacia mangium exhibited no strong preference for either N form but demonstrated the highest N uptake rate. These findings indicate the significant role of mycorrhizal type and biological nitrogen fixation in shaping N uptake patterns. Importantly, even when accounting for the dilution by the soil nitrogen pool, nitrate still contributed 42–99% of the total nitrogen uptake across the three tree species. All three species showed a substantial capacity for nitrate assimilation, challenging the conventional view of ammonium dominance in tropical trees and providing a mechanistic basis for refining nitrogen management practices in plantation forestry. Full article

Eucalyptus plantations have suffered severe damage from scarab grubs in recent years. To investigate the actual scarab species that damage Eucalyptus trees, continuous closed-net monitoring and monthly soil-digging surveys were conducted in Eucalyptus plantations in Lancang County, China, from 2024 to 2025. The primarily affected roots were covered with nylon mesh bags until the insects reached adulthood. A few adults were successfully collected from the damaged roots. The scarab species that infests Eucalyptus trees has been identified as Megistophylla grandicornis (Fairmaire, 1891). It exhibited a single generation annually in local Eucalyptus plantations. Adults emerge from late April to June, and larvae cause damage from July to November. Eucalyptus trees with severely damaged roots exhibit reduced growth vigor and are highly prone to windthrow and death, leading to substantial losses in forestry production. These preliminary results provide foundational data for recognizing Megistophylla grandicornis as a new root pest of Eucalyptus and establishing targeted larval-monitoring protocols in Eucalyptus plantations. Full article

Mycoforestry, a farming system that produces edible fungi crops in forest plantations through controlled mycorrhizal symbiosis, has the potential to enhance biodiversity in forestry plantations and mitigate some of the negative impacts associated with modern agriculture, such as soil erosion, habitat degradation, and carbon emissions. Mycoforestry systems typically exploit a range of native fungi that can be inoculated into planting stock of commercial tree species, with biodiversity benefits delivered through expanded habitat provision for the fungi and a range of other organisms through alterations to stand structure. One mycoforestry system showing strong potential for commercial viability involves the cultivation of Lactarius deliciosus (L.:Fr.) S.F. Gray in Pinaceae plantations. This review aims to evaluate the benefits of mycoforestry systems with a focus on Lactarius deliciosus (L.:Fr.) as a case study. It will review the state of the art and discuss technical developments necessary for the successful large-scale application of mycoforestry systems. Full article

Accurate estimation of forest stand carbon storage is critical for assessing ecosystem functions and informing sustainable forest management. Most existing models depend heavily on stand age, a strategy that is often unreliable in natural forests, and they typically ignore species interactions, limiting their applicability across forest types. To overcome these issues, we developed a dynamic carbon storage model based on the Richards equation that replaces stand age with a growth interval period (defined as the time difference between two successive growth stages, T_n = T₂ − T₁) and explicitly incorporates site quality and species composition. This approach enables consistent estimation for both natural and plantation forests. Using field data from six dominant tree species in Wuyishan City, Fujian Province, we calibrated and validated the model through five-fold cross-validation. It achieved high accuracy, with an efficiency coefficient (EA) above 99% and a relative mean absolute error (RMA) under 7%, effectively reflecting how site conditions and mixed-species structures influence carbon dynamics. Total forest carbon storage in the study area was estimated at 7.32 million tons. Simulations show a gradual decline in carbon accumulation over time, consistent with natural growth saturation in aging stands. Scenario analyses further identified practical zones for sustainable harvesting in major plantation types, underscoring the model’s management relevance. The model does not yet include climate variability, disturbances, or below-ground carbon pools. Adding these components in future work would strengthen its utility for regional carbon assessment and support more robust carbon-neutral forestry planning. Full article

In Portugal, increasing wildfire frequency and severe storm events have intensified the need for advanced monitoring tools to assess forest damage and recovery efficiently. This study explores the application of deep learning neural network techniques, specifically the Mask R-CNN architecture, for the automatic detection of trees in Pinus pinaster stands using RGB and multispectral imagery captured by a drone. The research addresses two distinct forest scenarios, resulting from disturbances intensified by climate change. The first concerns the detection of fallen trees following an extreme weather event to support damage assessment and inform post-disturbance forest management. The second focuses on segmenting individual trees in a newly established plantation after wildfire to evaluate the effectiveness of ecological restoration efforts. The collected images were processed to generate high-resolution orthophotos and orthomosaics, which were used as input for tree detection using Mask R-CNN. Results showed that integrating drone-based imagery with deep learning models can significantly enhance the efficiency of forest assessments, reducing the need for fieldwork effort and increasing the reliability of the collected data. Results demonstrated high performance, with average precision scores of 90% for fallen trees and 75% for recently planted trees, while also enabling the extraction of spatial metrics relevant to forest monitoring. Overall, the proposed methodology shows strong potential for rapid response in post-disturbance environments and for monitoring the early development of forest plantations. Full article

Forest damage has been increasingly recorded over the past decade in both Europe and Hungary, primarily due to prolonged droughts, causing a decline in forest health. In the framework of ICP Forests, the forest damage has been monitored for decades; however, it is labour-intensive and time-consuming. Satellite-based remote sensing offers a rapid and efficient method for assessing large-scale damage events, combining the ground-based ICP Forests datasets. This study utilised cloud computing and Sentinel-2 satellite imagery to monitor forest health and detect anomalies. Standardised NDVI (Z NDVI) maps were produced for the period from 2017 to 2023 to identify disturbances in the forest. The research focused on seven active ICP Forests Level II and 78 Level I plots in Hungary. Z NDVI values were divided into five categories based on damage severity, and there was agreement between Level II field data and satellite imagery. In 2017, severe damage was caused by late frost and wind; however, the forest recovered by 2018. Another decline was observed in 2021 due to wind and in 2022 due to drought. Data from the ICP Forests Level I plots, which represent forest condition in Hungary, indicated that 80% of the monitored stands were damaged, with 30% suffering moderate damage and 15% experiencing severe damage. Z NDVI classifications aligned with the field data, showing widespread forest damage across the country. Full article

This study explores the impact of shelterbelt forest plantations on agricultural productivity in Ukraine. The purpose of this article is to investigate how forest belts and land use patterns affect crop yields and agricultural land use in Ukraine, and to compare these patterns with factors contributing to forest cover loss in EU countries in order to develop practical management recommendations. Using geoinformation modeling and correlation analysis, we examined the relationship between shelterbelt coverage and agricultural indicators, including land leasing, crop yields and the planted area under annual and biennial crops. The total area of agricultural land protected by these plantations amounted to 51.66 thousand hectares, generating an additional 206.64 thousand centners of grain annually. Given the average price of 12.23 euros per centner for cereals and legumes, the total economic effect was estimated at approximately 2.53 million euros per year. The study also presents theoretical and methodological approaches for mathematically modeling economic indicators of forestry land use, drawing on successful practices from the European Union regarding sustainable development under significant anthropogenic, economic, and climatic pressures. The results highlight that shelterbelt plantations, once established, are among the most cost-effective agronomic practices, offering long-term environmental and economic benefits for sustainable agricultural development. Full article

Tectona grandis L.f. (teak) is a timber species of exceptional commercial value, widely cultivated in Ecuador for export to international markets. This study aimed to ecogeographically characterise current production and identify zones with high potential for exploitation, using tools from CAPFITOGEN v3.0 and the MaxEnt maximum entropy algorithm, based on data from 1023 plantations. The territory was classified into 26 ecogeographic categories, of which teak is present in 13. Categories 17, 19, and 21 were predominant, collectively accounting for 88.27% of the analysed plantations. Sixteen relevant variables (comprising four climatic, four edaphic, and eight geophysical factors) served as predictors in MaxEnt, with model validation demonstrating strong accuracy (AUC = 0.924). The most influential factors for teak suitability were precipitation seasonality, altitude, annual precipitation and September wind speed. Areas with elevated and high probabilities for teak exploitation were quantified at 6737.83 km² and 10,154.70 km², respectively, with Guayas, Los Ríos, and Manabí provinces showing the most favourable conditions. This integrative framework provides an evidence-based basis for land-use planning and resource management, supporting more sustainable and efficient development of Ecuador’s teak forestry sector. Full article

Camellia oleifera is an important economic tree species in China. Accurate estimation of canopy structural parameters of C. oleifera is essential for yield prediction and plantation management. However, this remains challenging in mountainous plantations due to canopy occlusion and background interference. This study developed a multi-level object-oriented segmentation method integrating UAV-based LiDAR and visible-light data to address this issue. The proposed approach progressively eliminates background objects (bare soil, weeds, and forest gaps) through hierarchical segmentation and classification in eCognition, ultimately enabling precise canopy delineation. The method was validated in a high-canopy-closure plantation characterized by a mountainous area. The results demonstrated exceptional performance; canopy area extraction and individual plant extraction achieved average F-scores of 97.54% and 91.69%, respectively. The estimated tree height and mean crown diameter were strongly correlated with field measurements (both R² = 0.75). This study provides a method for extracting the parameters of C. oleifera canopies that is suitable for mountainous regions with high canopy closure, demonstrating significant potential for supporting digital management and precision forestry optimization in such wooded areas. Full article