Journal of Forestry Research最新文献

The spatial pattern of trees is an important feature of forests, and different spatial patterns of trees exhibit different ecological stability. Research has confirmed that natural forests with random patterns have higher biodiversity and stronger resistance to unstable factors such as pests and diseases. Even if they are disturbed or destroyed by unstable factors such as pests and diseases, they can still recover and rescue themselves; while artificial forests with uniform and clustered patterns have lower biodiversity and are susceptible to unstable factors such as pests and diseases. And once pests and diseases occur, it’s more difficult for them to recover. In order to promote the healthy and stable development of the forestry industry and protect the diversity of the biological environment, it is necessary to protect the random pattern of natural forests from being destroyed in the process of forest management, while effectively transforming the spatial pattern of artificial forests into a random pattern. Therefore, in order to ensure the convenient and accurate determination of the type of forest spatial pattern, research on methods for determining forest spatial pattern has become particularly important. Based on the theory of uniformity, this study proposes definitions and related theories of included exclusive sphere, included exclusive body, included random pattern, and included uniformity. Under the guidance of the definition of inclusion uniformity and related theories, and by using mathematical method, it is proved that the uniformity of inclusion (CL) is asymptotically subject to the Eq. 18, Therefore, the relationship between the included uniformity (CL) and the number of trees in the sample plot was established, and the corresponding relationship formula was obtained, and then the determination of the spatial pattern type of trees was completed by using the corresponding relationship formula. Through rigorous reasoning and case verification, the determination method of forest spatial pattern is effective.

A decline in tree growth has occurred in numerous regions over recent decades and is associated with enhanced water deficits driven by climate warming. This phenomenon may be more noticeable at lower latitudes with higher temperatures. However, the process by which these elevated temperatures alter growth performance is not well understood. In this study, by combining tree-ring data (including 340 increment cores) and remotely sensed vegetation index data, we investigated the long-term growth performance of Pinus sylvestris var. mongolica Litv. (Mongolian pine), an important species for afforestation in northern China, in response to environmental factors in an area of introduction (lower latitude) and its native range (higher latitude). More notable decreases in both tree-ring width index (RWI) and basal area increment at breast height coincided with lower values and larger variations in the satellite-derived vegetation index in the area of introduction. The RWI showed stronger negative correlations with temperature and positive correlations with the self-calibrating Palmer drought severity index during most months in the introduction area. These results indicate that enhanced drought stress caused by elevated temperatures in lower latitudes might be a key factor for the growth decline in Mongolian pine plantations. The negative impact of increased temperatures on tree growth through exacerbating drought stress at lower latitudes with water deficit highlights the need to reduce water stress in forest management in such areas under climate warming-driven aridification.

Glutathione-S-transferase (GST, EC2.5.1.18) multifunctional protease is important for detoxification, defense against biotic and abiotic stresses, and secondary metabolic material transport for plant growth and development. In this study, 71 members of the BpGST family were identified from the entire Betula platyphylla Suk. genome. Most of the members encode proteins with amino acid lengths ranging from 101 to 875 and were localized to the cytoplasm by a prediction. BpGSTs can be divided into seven subfamilies, with a majority of birch U and F subfamily members according to gene structure, conserved motifs and evolutionary analysis. GST family genes showed collinearity with 22 genes in Oryza sativa L., and three genes in Arabidopsis thaliana; promoter cis-acting elements predicted that the GST gene family is functional in growth, hormone regulation, and abiotic stress response. Most members of the F subfamily of GST (BpGSTFs) were expressed in roots, stems, leaves, and petioles, with the most expression observed in leaves. On the basis of the expression profiles of F subfamily genes (BpGSTF1 to BpGSTF13) during salt, mannitol and ABA stress, BpGSTF proteins seem to have multiple functions depending on the type of abiotic stress; for instance, BpGSTs may function at different times during abiotic stress. This study enhances understanding of the GST gene family and provides a basis for further exploration of their function in birch.

Stand age is an important indicator of tree growth and life cycle, and has implications for ecological and biological processes. This study examined changes in soil microbial biomass (SMB) as well as enzyme activities of different aged plantations and revealed their relationship to soil properties. SMB, microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), microbial biomass phosphorous (MBP) and enzyme activities (β-1,4-glucosidase (β-G), β-1,4-xylosidase (β-X), cellobiohydrolase (CBH), leucine aminopeptidase (LAP), β-1,4-n-acetylglucosamine (NAG) and acid phosphatase (ACP)) were measured in Oromosia hosiei plantations of different ages. The soil quality index (SQI) model assessed soil quality. SMB contents significantly decreased in young (7-year-old) and mature plantations (45-year-old) compared to middle-aged (20-year-old) plantations. Activity of soil β-G, β-X, CBH and NAG in the 20-year-old plantations was markedly higher than in the other plantations except for β-G, CBH and NAG in the 45-year-old plantations. Soil organic carbon (SOC), total potassium (TK), total porosity, dissolved organic carbon, nitrate nitrogen (NO₃⁻-N) and non-capillary porosity were key factors affecting SMB, while soil bulk density, pH, SOC, NO₃⁻-N, TK and forest litter (FL) were the main factors affecting soil enzyme activities. SQI decreased in the order: middle-aged > mature > young. The efficiency of soil organic matter conversion, the effect of nitrogen mineralization and fixation by microorganisms, and the better efficiency of phosphorus utilization in mid-age plantations, which improves soil physical properties, better facilitates tree growth, and further improves the buffering of the soil against acidity and alkalinity. FL quality was the only soil biological factor affecting soil enzyme activity. Our findings demonstrate that different aged plantations affect soil microbial biomass, enzyme activity, and soil quality.

Available water for communities is insufficient in the central part of Myanmar due to limited rainfall and surface water resources. Over the last two decades, afforestation and reforestation projects have been implemented in this region to provide sufficient water to local communities, expecting forested areas to store more rainwater than other land uses. However, there has been no research and very limited information on rainfall partitioning into throughfall (TF) and stemflow (SF), particularly concerning tree characters. Gross rainfall, TF under different canopy types, and SF of different tree types were measured in 2019. TF and SF were frequently observed even without rain but under foggy conditions. Therefore, both were partitioned into TF and SF from rainfall and fog individually. Sparser canopies resulted in larger TF from rainfall than denser canopies. However, a denser canopy delivered larger TF from fog than a sparser one. TF rates from rainfall in sparser and denser canopies were 54.5% and 51.5%, respectively, while those from fog were 15.2% and 27.2%, respectively. As a result, total TF rate in the denser canopy (70.7%) was significantly larger than that from the sparser one (64.3%). Short trees with small crown projection area and smooth bark (Type I) resulted in larger SF from rainfall than taller trees with large crown projection area and rough bark (Type II). However, Type II trees resulted in larger SF from fog. SF rates by rainfall from Type I and II trees were 17.5% and 12.2%, respectively, while those by fog were 22.2% and 39.5%, respectively. No significant total SF rates were found for Type I (22.5%) and II trees (20.1%). A denser canopy results in larger TF, and Type I trees result in larger SF. In an area where foggy conditions occur frequently and for a lengthy period, however, Type II trees will result in larger SF. These three tree characters (dense canopies, short trees with small crown projection area and smooth bark, and tall trees with large crown projection area and rough bark) should be considered for afforestation and reforestation projects in the Popa Mountain Park to enhance net water input by forests.

Urban and community forestry is a specialized discipline focused on the meticulous management of trees and forests within urban, suburban, and town environments. This field often entails extensive civic involvement and collaborative partnerships with institutions. Its overarching objectives span a spectrum from preserving water quality, habitat, and biodiversity to mitigating the Urban Heat Island (UHI) effect. The UHI phenomenon, characterized by notably higher temperatures in urban areas compared to rural counterparts due to heat absorption by urban infrastructure and limited urban forest coverage, serves as a focal point in this study. The study focuses on developing a methodological framework that integrates Geographically Weighted Regression (GWR), Random Forest (RF), and Suitability Analysis to assess the Urban Heat Island (UHI) effect across different urban zones, aiming to identify areas with varying levels of UHI impact. The framework is designed to assist urban planners and designers in understanding the spatial distribution of UHI and identifying areas where urban forestry initiatives can be strategically implemented to mitigate its effect. Conducted in various London areas, the research provides a comprehensive analysis of the intricate relationship between urban and community forestry and UHI. By mapping the spatial variability of UHI, the framework offers a novel approach to enhancing urban environmental design and advancing urban forestry studies. The study’s findings are expected to provide valuable insights for urban planners and policymakers, aiding in creating healthier and more livable urban environments through informed decision-making in urban forestry management.

Recent advances in spectral sensing techniques and machine learning (ML) methods have enabled the estimation of plant physiochemical traits. Nitrogen (N) is a primary limiting factor for terrestrial forest growth, but traditional methods for N determination are labor-intensive, time-consuming, and destructive. In this study, we present a rapid, non-destructive method to predict leaf N concentration (LNC) in Metasequoia glyptostroboides plantations under N and phosphorus (P) fertilization using ML techniques and unmanned aerial vehicle (UAV)- based RGB (red, green, blue) images. Nine spectral vegetation indices (VIs) were extracted from the RGB images. The spectral reflectance and VIs were used as input features to construct models for estimating LNC based on support vector machine, random forest (RF), and multiple linear regression, gradient boosting regression and classification and regression trees (CART). The results show that RF is the best fitting model for estimating LNC with a coefficient of determination (R²) of 0.73. Using this model, we evaluated the effects of N and P treatments on LNC and found a significant increase with N and a decrease with P. Height, diameter at breast height (DBH), and crown width of all M. glyptostroboides were analyzed by Pearson correlation with the predicted LNC. DBH was significantly correlated with LNC under N treatment. Our results highlight the potential of combining UAV RGB images with an ML algorithm as an efficient, scalable, and cost-effective method for LNC quantification. Future research can extend this approach to different tree species and different plant traits, paving the way for large-scale, time-efficient plant growth monitoring.

To study the effect of thinning intensity on the carbon sequestration by natural mixed coniferous and broadleaf forests in Xiaoxing’an Mountains, China, we established six 100 m × 100 m experimental plots in Dongfanghong Forest that varied in thinning intensity: plot A (10%), B (15%), C (20%), D (25%), E (30%), F (35%), and the control sample area (0%). A principal component analysis was performed using 50 different variables, including species diversity, soil fertility, litter characteristics, canopy structure parameters, and seedling regeneration parameters. The effects of thinning intensity on carbon sequestration were strongest in plot E (0.75), followed by D (0.63), F (0.50), C (0.48), B (0.22), A (0.11), and the control (0.06). The composite score of plot E was the highest, indicating that the carbon sequestration effect was strongest at a thinning intensity of 30%. These findings provide useful insights that could aid the management of natural mixed coniferous and broadleaf forests in Xiaoxing’an Mountains, China. This information has implications for future studies of these forests, and the methods used could aid future ecological assessments of the natural forests in Xiaoxing’an Mountains, China.

Cold stress severely limits the distribution of mangrove species worldwide and it remains unclear how mangroves respond and adapt to cold temperatures. In this study, we investigated the effects of cold acclimation and/or inhibition of serotonin levels on reactive oxygen species (ROS), reactive nitrogen species (RNS), melatonin (MEL) and serotonin (SER) accumulation during cold stress in Kandelia obovata. Morphologic observation and parameter analysis revealed that cold acclimation mitigated the photoinhibition of photosystem I (PSI) and photosystem II (PSII), maintained optimal ROS and RNS redox homeostasis, and increased the contents of SER and MEL in leaves. This suggests that cold acclimation reshapes the MEL/ROS/RNS redox network. In particular, the tryptophan/tryptamine/Ser/N-acetylserotonin/MER pathway was identified as a branch of the MEL synthesis pathway. Inhibition of endogenous SER exacerbated damage caused by cold stress, indicating the crosstalk of SER synthesis and cold acclimation. In this study, we report a coordinated regulation of cold stress by a complex defense network in K. obovata.