Coastal wetlands are key transitional ecosystems located at the terrestrial-aquatic interface, and influenced by multiple environmental factors such as tidal regimes, salinity gradients, and distribution of halophyte vegetation, thereby forming unique nitrogen (N) cycling patterns. Coastal wetlands play a critical role in alleviating nearshore eutrophication and maintaining ecosystem functions. Although the drivers of soil N removal processes in coastal wetlands have been widely studied, existing research has largely focused on environmental factors or microbial processes separately, whereas the regulating mechanisms of halophytes on microbial denitrification still lacks a systematic review. Halophyte root functional traits are also increasingly considered a key functional attribute in regulating the coupling relationship between vegetation characteristics and soil nitrogen cycling processes. This study systematically reviews current knowledge on the effects of hydrological and salinity gradients, as well as halophytes, on N removal in coastal wetlands, with a particular focus on root traits. We integrate how root chemical, physiological, and morphological traits influence microbial N removal through carbon (C) inputs, radial oxygen loss, and rhizosphere microenvironment regulation. The study further reveals the regulatory mechanisms of root-mediated microbial community restructuring, enrichment of key denitrifying taxa, and the regulation of N removal via coupled elemental cycles, including C–N and iron–N interactions. The aim of this review is to fill the systematic knowledge gap between halophyte root traits to microbial N removal in coastal wetlands, and provide a theoretical basis for advancing future research.

Objective: Long-term acid rain deposition poses a severe threat to the stability of subtropical forest ecosystems. Based on dendroecology and stable isotope techniques, this study investigated the radial growth trends and physiological responses to water and nitrogen variations in Pinus massoniana and Castanopsis fargesii under long-term acid rain stress. The aim of this study is to provide a scientific basis for forest management and species selection in acid rain control zones. Method: This study was conducted in Jinyun Mountain National Nature Reserve, Chongqing, and P. massoniana and C. fargesii were selected as the research objects. The tree-ring width, stable carbon (δ¹³C) and nitrogen (δ¹⁵N) isotopes in P. massoniana and C. fargesii were measured, with which intrinsic water-use efficiency (iWUE) was calculated. Combined with the deposition of major acid rain components (SO₄^2?, NO₃^?, and NH₄⁺) and climatic data, piecewise regression and multiple linear models were employed to quantify the effects of acid rain on tree growth and physiological indicators. Result: 1) Long-term acid rain stress significantly inhibited the growth rates of both species, yet their response patterns diverged. During the period of severe acid rain stress (1981—2010), the radial growth of P. massoniana significantly declined (P < 0.001), while that of C. fargesii stagnated (P > 0.05). However, as acid rain intensity diminished (2011—2020), both species exhibited a significant recovery trend (P < 0.05), with P. massoniana displaying a faster recovery rate. 2) Regarding water-use strategies, the iWUE of P. massoniana significantly decreased during the acid rain alleviation phase (2011—2020) (P < 0.01), whereas C. fargesii showed no significant change (P > 0.05), highlighting distinct strategies between coniferous and broadleaved species. 3) P. massoniana growth was significantly negatively affected only by SO₄^2? (P < 0.001), and its iWUE was significantly negatively correlated with basal area increment (P < 0.001), indicating that a conservative water-use strategy constrained its radial growth. Conversely, C. fargesii growth was inhibited by both SO₄^2? and NO₃^? (P < 0.001), it showed a significant positive correlation with NH₄⁺ deposition (P < 0.001), and its δ¹⁵N remained stable during the recovery period. Conclusion: P. massoniana and C. fargesii employ distinct growth and physiological adaptation strategies under long-term acid rain stress. P. massoniana exhibits high sensitivity to SO₄^2? stress due to conservative water regulation strategy and failure to effectively utilize nitrogen deposition. In contrast, C. fargesii demonstrates stronger growth recovery potential than P. massoniana, attributed to its efficient utilization of NH₄⁺ and synergistic water-carbon regulation. Therefore, management of subtropical forests should adhere to site-species matching, implement mixed-species planting and zonal configuration, and incorporate long-term acid deposition monitoring and soil amelioration measures to enhance community resilience and stress resistance.

Objective: This study aims to screen superior clones of Ginkgo biloba for leaf production with high medicinal components (total flavonoids and ginkgolides) and low ginkgolic acid content. Method: The phenotypic traits (dry weight per leaf, leaf area, specific leaf dry weight) and medicinal component contents (total flavonoids, terpene lactones) of leaves from 46 ginkgo clones, as well as ginkgolic acid content, were systematically measured. Cluster analysis and principal component analysis based on membership functions were employed to comprehensively evaluate the 46 clones. Result: There were significant differences in leaf phenotypic traits, medicinal component contents, and ginkgolic acid content among 46 ginkgo clones, indicating rich genetic diversity, with an average coefficient of variation of 13.8%. Based on the comprehensive evaluation using principal component analysis based on membership functions and combined with cluster analysis, six high-quality clones with high medicinal value and low ginkgolic acid content were selected, namely clones 25, 34, 1, 5, 45, and 3. These clones generally had higher specific leaf dry weight, higher contents of total flavonoids and terpene lactones, and moderate to low levels of ginkgolic acid. Among them, clone 34 had relatively larger leaf area, higher dry weight per leaf, and higher total medicinal component content, while its ginkgolic acid content was relatively low. Conclusion: There are abundant variations in phenotypic traits, main medicinal components and ginkgolic acid content among different ginkgo clones. There is a certain synergistic change between medicinal components and ginkgolic acid, but the correlation between medicinal components is stronger. The results provides the possibility for the breeding of leaf-using ginkgo clones with high medicinal components and low ginkgolic acid.

Objective: Heavy reliance on subjective preferences, combined with substantial uncertainty in management objectives weights, often results in inaccurate decision-making in multi-objective management of plantations. In this study, Larix olgensis plantations were taken as the research object to comprehensively explore the multidimensional weight space, providing a sound basis for multi-objective management of plantations. Method: Stochastic multi-criteria acceptability analysis (SMAA) integrated with stand growth simulations was used to determine the optimal thinning schemes for L. olgensis plantations under different site conditions (SI=16, 18, 20, and 22 m). With the annual mean wood production, net present value (NPV), and the average carbon storage over the rotation as the criteria, this study explored the dynamic effects of 12 alternative thinning schemes (upper or lower thinning, interval periods of 5 and 10 years, thinning intensity of 10%, 20%, and 30%) under different site conditions. By analyzing the overall acceptability index ($ a_{i}^{h} $) and decision-making risk degree ($ \text{DR}{\mathrm{D}}^{r} $) of different thinning schemes, each scheme was comprehensively evaluated and ranked from multiple dimensions (comprehensive performance and risk) to identify the optimal thinning scheme. Result: Under the same thinning scheme, management objectives all increased to different degrees with the increase of site index (every 2 meters increase). The mean annual wood production increased by 10%–52%, NPV increased by 10%–67%, and the average carbon storage increased by 1%–47% during the rotation period for the 12 schemes. The upper thinning resulted in higher mean annual wood production and NPV but lower average carbon storage than lower thinning. For a plantation with a SI of 18 m, the increases were 7%?17% in mean annual wood production and 3%?45% in NPV, while the decrease was 19%?47% in average carbon storage over the rotation. For plantations with site indices of 16 and 18 m, the optimal thinning scheme was Ⅷ (i.e. upper thinning over a 10-year interval with a thinning intensity of 10%) as its overall acceptability index reached up to 79% and 80% and its decision-making risk degree was 1%. For plantations on more productive sites with site indices of 20 or 22 m, thinning scheme X (i.e. upper thinning over a 10-year interval with a thinning intensity of 20%) was optimal, with an overall acceptability index reaching 85% and 83% and the decision-making risk degree were 2% and 1%, respectively. Conclusion: Stochastic multi-criteria acceptability analysis (SMAA) can provide strong support for decision-making in multi-objective forest management through a comprehensive exploration of objective preferences and the multidimensional objective weight space. This study demonstrates its usefulness in determining the optimal thinning schemes for L. olgensis plantations across four site quality classes, providing a sound basis for multi-objective management decision of these plantations in northeast China.

Objective: This study aims to investigate the medium to long term effects of ice storm disturbance on natural evergreen broad-leaved forests, and to clarify the differences in community characteristics, stand spatial structure, and community stability between ice-damaged forests after 13 years of ice storm disturbance and undisturbed in northern Guangdong Province, China. Method: One 1 hm² permanent plot affected by the 2008 ice storm was established in Maozifeng (northern Nanxiong), and a comparable 1 hm² undisturbed control plot was established in Qingzhangshan (southern Nanxiong). All trees with a diameter at breast height (DBH) ≥1 cm were recorded and measured, including species identity, DBH, tree height, and spatial coordinates. Comparative analysis was conducted on the differences in species composition, biodiversity indices, DBH, and height class distributions between the two plots. The neighborhood-based spatial structural unit method was used to analyze the stand spatial structure, including the uniform angle index, neighborhood comparison, and mingling. The Godron method was used to analyze community stability. Result: The two plots affected and unaffected by ice disasters represented typical subtropical evergreen broad-leaved forests dominated by Fagaceae species. In the ice-damaged plot, the three dominant species (by importance value) were Castanopsis fargesii, C. carlesii, and C. faberi, whereas in the undisturbed plot they were C. faberi, Schima superba, and Quercus glauca. The number of small-diameter trees (DBH 1–4 cm) in the ice-damaged plot (2 668 individuals) was much higher than that in the undisturbed plot (681 individuals), while the numbers of medium-diameter trees (DBH 4–30 cm) and large-diameter trees (DBH >30 cm) were similar between the two plots. The mean uniform angle index of trees in the large sample plots affected and unaffected by ice disasters was 0.56 and 0.62, respectively, indicating that random distribution was the predominant spatial pattern in both plots, although some populations in the ice-damaged plot showed a tendency toward aggregated distribution. Mean neighborhood comparison values (0.51 and 0.49, respectively) suggested weak size differentiation and relatively stable stand structures. The mean mingling was higher in the ice-damaged plot (0.79) than in the undisturbed plot (0.62), indicating stronger interspecific mixing following disturbance. Community stability in the ice-damaged plot remained lower than that of an ideal stable forest, whereas the undisturbed plot closely approximated the stability of an ideal forest community. Conclusion: Ice storm disturbance has pronounced and lasting effects on community characteristics, stand spatial structure, and community stability of evergreen broad-leaved forests in northern Guangdong. Even 13 years after the ice storm, the disturbed forest still exhibits a high proportion of small trees, elevated stand density, partial aggregation of tree populations, and reduced community stability. These results indicate that ice storm disturbance exerts long-term influences on subtropical evergreen broad-leaved forests, and that post-disturbance forest recovery is a prolonged and dynamic process.

Objective: This study aims to investigate the relationship between tree species diversity and aboveground biomass in temperate forests of northeast China with the changes of forest types and developmental stages, and to reveal the underlying mechanisms of niche complementarity and mass ratio effects, providing a scientific basis for improving the quality of secondary forests in northeast China through optimizing tree species composition. Method: Based on data from the National Forest Continuous Inventory plots in Jilin Province, linear mixed-effects models were employed to analyze the effects of multidimensional diversity (species richness, functional diversity, phylogenetic diversity) and the community-weighted mean (CWM) of functional traits on aboveground biomass across different forest types (broad-leaved forests, broad-leaved mixed forests, coniferous broad-leaved mixed forests) and developmental stages, while controlling for climatic, soil, and stand factors. Generalized additive models were used to reveal the dynamic changes in diversity effects with forest development stages, and structural equation modeling was applied to analyze the direct and indirect effects of environmental factors, forest types, developmental stages, and stand density on the relationship between tree species diversity and aboveground biomass. Result: 1) Across the three temperate forest types, species richness, functional diversity, and phylogenetic diversity all had significant positive effects on aboveground biomass. Simultaneously, the CWM, representing tree functional traits, also exhibited significant positive or negative effects. This indicates that both niche complementarity effect and the mass ratio effects operate in tandem during aboveground biomass accumulation in these temperate forests. 2) The influence of tree species diversity on aboveground biomass exhibited significant forest type dependency across different developmental stages. In the three types of forests, diversity effects (including species richness, functional diversity, and phylogenetic diversity) generally showed a decreasing trend from the young forest stage to the mature forest stage. Specifically, the community-weighted mean trait values effect (i.e., the mass ratio effect) of pure broad-leaved forests and coniferous broad-leaved mixed forests was higher in both young forests and mature/over-mature forests. In contrast, there was no significant trend in the community weighted average trait value effect of coniferous broad-leaved mixed forests across different forest developmental stages. Notably, in mature and over-mature forests, the community-weighted mean trait values effect exceeded the functional diversity effect in both broad-leaved forests and coniferous broad-leaved mixed forests. 3) Structural equation modeling indicated that environmental factors (climate, soil), stand characteristics, and forest types/developmental stages jointly regulated forest biodiversity and aboveground biomass. Specifically, forest type and developmental stage were able to indirectly influence aboveground biomass by regulating stand density and biodiversity. Conclusion: In the temperate forests of northeast China, species richness, functional diversity, phylogenetic diversity, and the community-weighted mean of functional traits all significantly influence aboveground biomass, but the strength of their effects varies with forest type and developmental stage. Therefore, forest management and ecological restoration practices should implement precise management strategies tailored to the specific forest type and its developmental stage. In young forests, in addition to increasing tree species diversity, emphasis should be placed on cultivating species with strong resource acquisition abilities. In mature forests, priority should be given to developing and retaining dominant species with long-lived and conservative traits, and attentions should be paid to the target-tree cultivation practices.

Objective: The purpose of this study is to explore the feasibility of establishing models for major stand characteristics based on LiDAR data to estimate the factors of forest patches, providing a demonstration for promoting the application of LiDAR technology in integrated monitoring of the national forest and grassland. Method: Based on the LiDAR point cloud metrics and ground measured data of 1 966 forest plots in Beijing, the error-in-variable simultaneous equations were used to construct 8 forest factor estimation models for 13 forest types, including mean diameter at breast height (DBH), mean height, dominant height, stem number, basal area, stock volume, biomass and carbon storage. Additionally, based on the LiDAR point cloud metrics extracted from the 25 m×25 m grid cells within the forest patches in Beijing, the eight prediction models were used to estimate major stand characteristics of all forest patches. Result: 1) The LiDAR point cloud metrics that contributed the most to the estimation of major stand characteristics were 80% quantile of cumulative height and median point cloud height, followed by leaf area index. 2) The mean prediction errors (MPEs) of eight major stand characteristics models for 13 forest types were less than 15% in either self-validation or cross-validation. 3) Taking the forest as a whole, the determination coefficient (R²) of all eight prediction models were all above 0.7 (excluding the stem number per hectare), the MPEs were less than 3%, and the mean percentage standard errors (MPSEs) were less than 40%, among which the MPSEs of the mean DBH, mean height and dominant height models were about 15%. 4) According to the model inversion, the cumulative value of stock volume in all forest patches estimated by the volume model differed only by ?1.79% from that obtained by the integrated monitoring of the municipality. The differences between the stock volume of forest patches and the integrated monitoring results in the three sub-populations were only 1.04%, ?3.91% and ?5.44%, respectively, which were all within the allowable error range of sampling survey. Conclusion: 1) The LiDAR point cloud metrics that contribute the most to estimating the major stand characteristics are percentile 80 of heights distribution and median height, followed by leaf area index. However, the point cloud intensity and density metrics have no significant effect. 2) The method of error-in-variable simultaneous equations can be applied to construct the simultaneous models of major stand characteristics, which is able to solve both compatibility of different model parameters and error propagation of different stand characteristic estimates. 3) The eight prediction models for 13 forest types can be used to estimate the major stand characteristics of forest patches in Beijing. 4) The prediction accuracy of the major stand characteristics models based on LiDAR point cloud metrics can meet the technical requirements of forest resource inventory and monitoring, and the models can be applied in practice.

Objective: With Bayesian network model, a machine learning method based on probabilistic inference, this study aims to analyze the effects of factors such as growth traits, soil nutrients, and understory vegetation diversity on the yield of large-diameter timber of Chinese fir under close-to-nature transformation from Chinese fir to Phoebe bournei, so as to provide theoretical support for the optimal management of Chinese fir stand and the cultivation of large-diameter timber. Method: The Chinese fir plantations planted in 2004 in Xishan State-owned Forest Farm in Linwu County, Hunan Province were targeted, and in 2015, the plantations were thined and, then interplanted with P. bournei. Key variables, including retained density of Chinese fir, DBH, dominant height, crown width, soil nutrients (total nitrogen and total phosphorus), and understory vegetation diversity, were selected. By integrating empirical data with expert knowledge, a mechanism model for the influence of Chinese fir large-diameter timber yield was constructed based on the Bayesian network model, and Expectation–Maximization (EM) algorithm was used to learn model, revealing the effects and interactions of different factors on the large-diameter timber yield. Result: The yield of large-diameter timber of Chinese fir was comprehensively affected by factors such as retained density of Chinese fir, crown width, DBH, dominant height, soil nutrients and understory vegetation diversity. The growth of DBH and the expansion of crown width were the key factors affecting the yield of large-diameter timber of Chinese fir (43.0%), and their influence on the yield was greater than that of the dominant height (2.07%). Suitable retained density of Chinese fir was able to promote the growth of DBH and crown width, so as to improve the yield of large diameter timber. Total phosphorus, as an important nutrient element in soil, had a positive effect on the growth of Chinese fir (1.40%), while the diversity of understory vegetation had little effect on the yield of large-diameter timber, which mainly affected the growth of Chinese fir through indirect ways. The Bayesian network model showed high prediction accuracy (88.9%, AUC=0.916 7) and good interpretability in capturing the complex relationship between multiple factors and predicting the large-diameter timber yield of Chinese fir. Conclusion: Based on the Bayesian network model, this study reveals the influence mechanism of large-diameter timber yield of Chinese fir under close-to-nature transformation, and proposes that Chinese fir plantations management should focus on the growth of DBH and crown width, optimize stand density and soil phosphorus supply, so as to promote the sustainable improvement of large-diameter timber yield. As a machine learning approach, the Bayesian Network model shows high prediction accuracy and interpretability in revealing the complex relationships among multiple factors such as Chinese fir growth conditions, soil nutrients, and understory vegetation diversity, etc. This study provides a scientific basis for the efficient management of Chinese fir plantations and improvement of large-diameter timber yield, and an efficient and interpretable tool for forest management decision-making.

Objective: To address crown overlap, sparse stem points, and noise interference in unmanned aerial vehicle laser scanning (ULS) point clouds for individual tree segmentation (ITS) and parameter estimation in eucalyptus plantations, a semantic-guided method for individual tree segmentation and parameter extraction was developed to improve segmentation accuracy and parameter estimation performance. Method: Gaofeng Forest Farm in Nanning, Guangxi was selected as the study area, and a complete point-cloud processing workflow was established. A deep learning model was used to perform semantic segmentation on point clouds, the point clouds were classified into semantic categories, including stems, leaves, and ground. Subsequently, a hybrid algorithm combining density-based spatial clustering of applications with noise (DBSCAN) and K-nearest neighbors (KNN) was used for individual tree segmentation by incorporating semantic information. To counter the sparsity of ULS point clouds at the stem level, stem curve fitting was adopted for diameter at breast height (DBH) estimation, and a height pseudo-waveform method was employed for tree height estimation. The proposed method was validated across plots with varying structural complexities to assess its applicability and accuracy. Result: Experimental results showed that high ITS accuracy was achieved in the eucalyptus plantations, with an overall recall of 0.92, precision of 0.95, and an average F-score of 0.93. For individual tree parameter estimation, tree height estimation showed a coefficient of determination (R²) of 0.98 with a root mean square error (RMSE) of 1.03 m. DBH estimation yielded an R² of 0.81 and an RMSE of 2.96 cm. Conclusion: The proposed method enables accurate individual tree segmentation and parameter extraction from ULS point clouds in eucalyptus plantations, indicating that semantic guidance can improve the applicability of ULS point clouds for individual-tree-level analysis. This study provides a reference for the efficient use of ULS data in forest resource monitoring.

Objective: This study aims to explore the impacts of rapid urbanization, environmental factors, and cultivated plants on the species composition, spatial distribution patterns, and diversity of spontaneous plants in urban plant communities, providing crucial scientific basis for constructing low artificial maintenance, near-natural vegetation communities in urban green spaces. Method: The distance from the city center and the percentage of impervious surface area were selected as key indicators of urbanization intensity. The cross zone method was used to select 3285 spontaneous plants plots and 657 soil plots within the sixth ring road of Beijing for plant investigation and soil physicochemical property determination. Result: A total of 191 spontaneous plant species were recorded in this study, belonging to 172 genera and 61 families, including 28 trees, 16 shrubs and 147 herbs. The species composition and life form of spontaneous plants showed early regeneration and succession of the spontaneous plant communities. Meanwhile, 337 species of cultivated plants were recorded, belonging to 252 genera and 85 families. It was found that higher urbanization intensity increased spontaneous woody plant diversity, while decreased herbaceous plant diversity. In addition, spontaneous woody plant diversity was significantly positively correlated with the soil water content (P=0.043), total phosphorus (TP) (P<0.05), total nitrogen (TN) (P<0.05), and cultivated woody plants diversity (P<0.001), while not significantly correlated with green space factors. However, spontaneous herbaceous plant diversity was significantly negatively correlated with the soil TP (P<0.05), organic matter (OM) (P<0.01), the cultivated herbaceous plants diversity (P<0.01), and the intensity of disturbance in green space factors (P<0.01). Herbaceous species were able to quickly colonize and became pioneer plants under frequent human disturbance, and reduced the relying on the soil water and nutrition, such as Humulus scandens. Among the influencing factors of green space factors, soil factors and the diversity of cultivated plants, spontaneous species composition was mainly influenced by intensity of disturbance (contribution=32.1%). Conclusion: By altering the environmental factors, soil characteristics and the cultivated plants diversity in urban green spaces, the species composition and diversity of spontaneous plants can be improved in different types of urban green spaces and areas with urbanization intensity, which is conducive to increasing the resilience and sustainability of urban green space landscapes.

Objective: This study aims to reveal the variation of growth and wood properties traits in Populus deltoides, and screen high-yielding superior clones, providing a scientific basis for the genetic improvement and efficient utilization of P. deltoides. Method: Four full-sib families and varieties of 10-year-old P. deltoides from a comparison plantation in the Daxing Forest Farm of Beijing were used as experimental materials, and selection of elite clones was conducted based on growth traits such as tree height and diameter at breast height (DBH). Twenty-seven elite clones and new varieties were selected, and the wood properties were measured across different annual rings, including ring width (RW), basic density (BD), microfibril angle (MA), fiber length (FL), and fiber width (FW). Principal component analysis (PCA) was employed for comprehensive evaluation of 27 elite clones. On this basis, the radial variation patterns of wood properties in P. deltoides were further analyzed using annual ring data. The correlation analysis, stepwise regression, and path analysis were comprehensively used to reveal the variation patterns underlying growth and wood property formation. Result: Statistical analysis of growth traits among 242 hybrid progenies showed that there were no significant differences in growth traits among the four full-sib families, whereas there were significant differences in growth traits among elite progenies within each family. Among them, the family P. deltoides ‘Danhong’ × P. deltoides ‘Beiyang’ exhibited the highest genetic gain, with tree height and diameter at breast height (DBH) gain rates reaching 15.27% and 43.61%, respectively. Based on clustering analysis of growth and wood property data, the 27 elite clones were divided into three clusters, which differed markedly in FL, fiber length-to-width ratio (FLR), BD, and growth performance. PCA showed that the first three principal components explained the majority of genetic variation in wood properties. Through PCA-based comprehensive evaluation, five clones with superior wood properties, including P. deltoides ‘Zhonghuai 1’, P. deltoides ‘Zhongcheng 4’, P. deltoides ‘Zhongcheng 2’, P. deltoides ‘Zhonghe 1’, and P. deltoides ‘K25’, were identified. Analysis of annual ring data indicated abundant genetic variation among clones, with relatively high coefficients of variation for RW, MA, and DBH, and relatively low variation for BD and FW. Radial variation analysis indicated that the 4th to 5th year represented the rapid growth stage of P. deltoides, after which wood properties tended to stabilize in maturity. FL, FW, FLR, and BD generally increased from pith to the bark. Correlation analysis showed that there were weak relationships between growth and wood properties in the 9th year, while annual ring-based correlations were relatively complex, and MA exhibited distinct sex-related differences. Further stepwise regression and path analyses indicated that BD and MA exerted the strongest explanatory power on growth, while other traits contributed less. Conclusion: P. deltoides hybrids have substantial variation in growth and wood property traits. Among them, five clones (P. deltoides ‘Zhonghuai 1’, P. deltoides ‘Zhongcheng 4’, P. deltoides ‘Zhongcheng 2’, P. deltoides ‘Zhonghe 1’, and P. deltoides ‘K25’) show superior wood quality. In addition, MA displays a significant sex effect, with female trees showing markedly higher values than males. Wood properties traits are dynamically regulated across developmental stages, with the 4th to 5th year identified as the rapid growth phase. Most wood traits display a radial pattern of gradual increase from pith to bark and stabilize at maturity. BD and MA show consistently high correlations among annual rings and are less affected by tree age, indicating strong potential for early prediction. Collectively, this study provides novel insights into the radial genetic variation of wood properties in P. deltoides hybrids and offers important theoretical and practical guidance for the selection and genetic improvement of elite clones.

Objective: In this study, SSR markers were used to identify the paternal origin of the open-pollinated progeny population of 5 high-yielding Xanthoceras sorbifolium (yellowhorn) varieties, and to explore suitable pollinator trees or pollinator varieties that can enhance the yield of specific yellowhorn varieties, thereby providing references for yellowhorn variety selection and high-yield cultivation. Method: A total of 395 progeny plants derived from the free pollination of 5 high-yielding yellowhorn varieties and 288 candidate male parents were used as materials. Based on the SSR markers developed by the team in the previous stage, a total of 17 SSR markers were screened out. Paternity identification was conducted through Cervus software, and genetic diversity analysis was carried out on the offspring population. Result: At a 95% confidence level, the paternal parent of 121 offspring was successfully identified. Both ‘Qiaoranboke’ and ‘Zhongshi No.4’ provided pollen for the mother trees. The paternal parent ‘Qiaoranboke’ and maternal parent ‘Zhongshi No.4’ had the most offspring, totaling 6 offspring. Among the 68 seedling-originated yellowhorn plants, 3 paternal origins produced the most offspring, totaling 15 offspring. The four yellowhorn trees with the numbers 12-150, 12-193, 6-144, and 6-107 had a high overall reproductive contribution rate and some of their pollen travelled a relatively long distance. The reproductive contribution rates of the yellowhorn with the numbers 12-141 and 6-161 to the maternal parent ‘Zhongshi No.9’ were 4.13% and 3.31%, respectively, and the reproductive contribution rate of the yellowhorn with the number 6-107 to the maternal parent ‘Qiaoranboke’ was 2.48%. Through paternal analysis, no self-pollinated offspring was detected, indicating that self-pollination in yellowhorn is extremely weak. The effective pollen dispersal distance of yellowhorn was 6?154.1 m, with an average distance of 54.67 m. Proximal pollen (<60 m) accounted for 62.28% of the total pollen sources. The average number of alleles, average effective number of alleles, average Shannon’s information index (I), average observed heterozygosity, and average expected heterozygosity were 8.706, 3.152, 1.308, 0.619, and 0.644, respectively. The polymorphic information content (PIC) ranged from 0.369 to 0.834, with an average of 0.588. Both population genetic structure and clustering analysis results indicated that the 395 yellowhorn germplasm samples were able to be divided into two major groups. Conclusion: The pollen sources of yellowhorn are relatively dispersed, and distance significantly affects the pollination rate of yellowhorn. The ‘Qiaoranboke’ cultivar is suitable as a pollinator for the ‘Zhongshi No.4’ cultivar. The yellowhorn trees numbered 12-150 and 12-193 are suitable as pollinators for the ‘Zhongshi No.1’ cultivar. The yellowhorn trees numbered 6-144, 9-200, and 6-107 are suitable as pollinators for ‘Zhongshi No.4’, ‘Zhongshi No.4’, and ‘Qiaoranboke’, respectively. The ‘Zhongshi No.4’ half-sib family exhibits the highest genetic diversity, while the ‘Yuandashuozhong’ half-sib family shows the lowest genetic diversity.

Objective: Based on the burn probability model, this study aims to uncover the spatial patterns of seasonal forest fire risks, and optimize the allocation of forest fire suppression resources, so as to provide theoretical support and practical guidance for improving the firefighting resource management in northern forests and enhancing forest fire prevention and control capabilities. Method: The Daxing’anling Mountains, an important forest area in China, was targeted. An enhanced burn probability model was employed to simulate the spatiotemporal dynamics of burn probabilities across the three distinct fire-risk seasons: spring, summer, and autumn for Daxing’anling forest region. Extensive iterative simulations were used to quantify seasonal variations in burn probabilities (BP), fire spread rates (ROS), and fire intensities (FI), and thereby assess the initial attack success rate. Two simulation scenarios were developed for comparative analysis: a baseline scenario reflecting current firefighting resource allocations and an optimized scenario that adjusted the placement and amount of temporary ground firefighting bases according to BP distribution. Resource reallocation strategies were designed to relocate temporary firefighting bases from areas of low BP areas to high BP areas. The resource allocation was strengthened in deciduous coniferous forests in the eastern and southern regions during spring, and the resource allocation was strengthened in mixed forest zones in autumn. One-way repeated measures ANOVA was used to examine seasonal differences in BP, ROS, and FI, and paired-sample t-tests was used to validate the efficacy of pre- and post-adjustment outcomes. Key evaluation metrics encompassed response time, initial attack success rate, and burn probability, providing a comprehensive framework for assessing the impact of resource optimization on fire management effectiveness. Result: There were significant seasonal variations in forest fire risks in Daxing’anling region, with the burnt area in spring accounting for over 80% of the annual burnt area. The combination of dry fuel conditions (fine fuel moisture code, FFMC > 85) and elevated fire weather index (FWI) during spring significantly amplified fire spread, whereas precipitation in summer and autumn exerted a strong suppressive effect on fire risks. The model simulations revealed that the average BP in spring was 0.002 6, with 94.6% of the area exhibiting potential for combustion. During this period, the ROS peaked at 6.3 m·min^?1, and FI reached its highest annual value of 4 504.6 kW·m^?1. In contrast, summer showed a substantial decline in BP to an average of 0.000 9, which is 73.6% lower than that in spring, accompanied by decreases in ROS to 2.6 m·min^?1 and FI to 1864.1 kW·m^?1. Autumn experienced the lowest fire risk, with only 20.3% of the area at risk of burning, with an average BP of 0.000 1, and further reductions in ROS to 2.4 m·min^?1 and FI to 1 512.7 kW·m^?1. Following the dynamic reallocation of temporary ground firefighting bases informed by BP simulation outcomes, the number of temporary firefighting bases in spring, summer, and autumn was reduced by 14.4%, 27.1%, and 33.3%, respectively. Despite these reductions, the response times continued to meet the critical threshold of <1.5 hours, while the initial attack success rate was sustained within the range of 77.2%?93.5%. The optimization of temporary ground firefighting resource allocation resulted in no statistically significant changes in burn probability (P = 0.84) or fire behavior (P = 0.91), underscoring the efficacy of the adaptive management strategy. Conclusion: This study can quantify the spatial differentiation patterns of seasonal forest fire risks in Daxing’anling and proposes a dynamic adjustment approach for optimizing the allocation of limited ground firefighting resources based on the BP simulations. The approach has successfully achieved the dual objective of reducing the number of temporary firefighting bases by 14%?33% while maintaining established firefighting goals.

Objective: To address the ecological and economic threats posed by frequent forest fires in the Sino-Mongolian border region, this study focuses on Larix gmelinii biological firebreaks. The aims are to investigate the differences in fire behavior characteristics of biological firebreaks under various environmental configurations and their influencing factors, and to identify the optimal forest belt density for constructing L. gmelinii biological firebreaks in this region. The study intends to provide a theoretical basis for the scientific establishment and fire control efficacy assessment of biological firebreaks in the Sino-Mongolian border region and to offer technical support for enhancing fire prevention capabilities within the “Three-North” shelterbelt system. Method: In this study, L. gmelinii biological firebreaks in the Bailang area of the northeastern Sino-Mongolian border was targeted. The fuel characteristic classification system (FCCS) was used to simulate the potential fire behavior of biological firebreaks at different forest belt densities under varying fuel moisture contents, wind speeds, and slope scenarios. Finally, the entropy-weight TOPSIS method was employed to comprehensively evaluate the fire control effectiveness of different forest belt densities across multiple scenarios. Result: 1) Under different wind speed and slope conditions, higher forest belt densities (≥ 8 000 individual·hm^?2) in biological firebreaks significantly suppressed potential surface fire behavior compared to the control plot (CK). The maximum reduction in fire spread rate reached 93.94%, and the maximum reduction in flame height reached 87.60%. 2) Forest belt density indirectly suppressed flame height by reducing fire spread rate. Wind speed and slope also affected the potential fire behavior of biological firebreaks, indicating that optimization of forest belt structure in combination with terrain configuration is essential to enhance fire control effectiveness. 3) Based on the entropy-weight TOPSIS method, the comprehensive evaluation of fire control effectiveness across multiple scenarios showed that the fire resistance effect was as follows: 8 000 individual·hm^?2> 9 000 individual·hm^?2> 7 000 individual·hm^?2> 6 000 individual·hm^?2. Conclusion: Rationally increasing the forest belt density of biological firebreaks can effectively regulate forest flammability and reduce potential fire risk. Therefore, it is recommended to prioritize the use of high-density (≥ 8 000 individual·hm^?2) biological firebreaks in high-fire-risk areas along the Sino-Mongolian border, and optimize forest and understory structure in conjunction with terrain, wind direction, and other environmental factors to balance fire prevention and ecological benefits. Future studies should also consider potential ecological effects of high-density biological firebreaks, such as reduced understory biodiversity and slower nutrient cycling. Further exploration should be conducted on the comprehensive impacts of forest belt density regulation on ecosystem structure and function, in order to provide a theoretical basis for optimizing the configuration of biological firebreaks in the Sino-Mongolian border region and other high-fire-risk northern forest areas.

Objective: This study aims to investigate the expression characteristics and biological functions of the PdbpetA gene in Populus davidiana × P. bolleana, and elucidate the molecular mechanism by which this gene is activated and regulates plant defense responses upon induction by the Lymantria dispar oral effector Armet. Method: The open reading frame (ORF) sequence of the PdbpetA gene from P. davidiana × P. bolleana was obtained by PCR cloning. Using techniques such as restriction enzyme digestion and homologous recombination, the PdbpetA gene sequence was constructed into plant transient expression, subcellular localization, and bimolecular fluorescence complementation (BiFC) vectors. The transient transformation system was used to analyze the subcellular localization of PdbpetA protein in tobacco cells. Transient expression of the PdbpetA gene in transgenic P. davidiana × P. bolleana was achieved through Agrobacterium-mediated transient transformation. The quantitative real-time RT-PCR was employed to examine the tissue-specific expression patterns of the PdbpetA gene in P. davidiana × P. bolleana. The relative expression levels of jasmonic acid biosynthesis-related genes PdbJAR1, PdbAOC, and PdbLOX2 were compared between control and transgenic plants. Additionally, proteins interacting with PdbpetA were screened using a yeast two-hybrid (Y2H) system. Result: The ORF of the PdbpetA gene is 696 bp in length and encodes 231 amino acids. The gene exhibited the highest expression level in mature leaves and the protein was localized to both the nucleus and cell membrane. Transient overexpression of PdbpetA in P. davidiana × P. bolleana reached its peak at 48 hours after transformation, whereas transient suppression led to significantly reduced expression at 36 hours. After L. dispar larvae feeding on PdbpetA-overexpressing plants, the relative expression levels of jasmonic acid biosynthesis-related genes PdbJAR1, PdbAOC, and PdbLOX2 were significantly up-regulated. However, these JA synthesis genes were markedly down-regulated in plants with transiently suppressed PdbpetA. Protein interaction analysis revealed that PdbpetA interacted with PdbKunitz and PdbrDNA. Conclusion: The PdbpetA gene of P. davidiana × P. bolleana not only participates in plant jasmonic acid synthesis, but also likely participates in plant defense responses through interactions with PdbKunitz and PdbrDNA.

Objective: Monellia carylella is one of the critical pests that seriously threatens pecan industry in China. This study aims to provide a vital basis for the prediction and scientific control the pest by investigating its morphological and biological characteristics. Method: In the Hefei area of Anhui Province, a detailed field investigation and indoor feeding observation of M. carylella were carried out to describe its morphological characteristics, biological characteristics, and annual life history. Result: Both the gynoparae and sexual generation of M. carylella are winged. The nymph has four instars all of which are wingless. Under 25°C and 75% humidity, the average duration of nymph was (7.12±0.96) days, the average pre-reproductive period was (1.91±0.54) days, the average lifespan of adults was (22.88±12.87) days, and the average reproductive yield of gynoparae was (73±45.72). In Hefei area, this aphid was able to produce 20–25 generations per year. Overwintering fertilized eggs started to hatch in early April of the following year, and then the gynoparae continued until early October. Male aphids gradually appeared in mid-October. After mating, female aphids always laid their eggs on the surface of the branches for overwintering. Approximately 77% of the fertilized eggs were distributed on the surface of branches, 18% on the leaf scars, and only 5% of the fertilized eggs were laid on the leaf buds. Conclusion: M. carylella is autoecious holocyclic life type with long parthenogenesis period. The gynoparae and sexual generation aphids are all winged. There is no oversummering phenomenon, and the damage lasts long. They overwinter with eggs, and are the key prevention and control target in pecan planting areas of Hefei.

Objective: In response of the problem of low recognition rate of unknown categories in infrared camera monitoring images of wildlife in open environments, a method for unknown category detection is proposed that does not rely on explicit environmental descriptions or habitat metadata, but only relies on known species labels. This method is designed for adapting to the common scenario of limited information in real monitoring dataset. Method: An envisioning unknown animal (EUA) method was proposed based on visual language feature matching, and the method integrated the ecological reasoning capability of large language model (LLM) with the cross-modal alignment of vision-language models to construct a monitoring framework for open environments. First, an ecologically-informed prompt was designed to guide the LLM to infer the regional ecological context solely from the set of known species sets and generate a list of potential species with ecological plausibility. Second, the text descriptions of these potential species were combined with known categories to construct an expanded vision-language semantic space. Finally, an outlier detection score (ODS) mechanism was introduced to robustly detect unknown categories by calculating the deviation in matching distribution of images between known categories and potential species. Result: Experiments on two public datasets, Dataset3 (D3) and North American Camera Trap Images (NACTI), demonstrated that EUA significantly outperformed existing methods. In the most challenging scenario with 5 unknown categories, the average false positive rate at 95% true positive rate (FPR@95TPR) of EUA was 57.86%, which was 16.19 percentage points lower than the suboptimal method. The area under the receiver operating characteristic curve (AUC) reached 84.31%, representing a 4.64 percentage point improvement. Ablation experiment confirmed that the ecologically-guided potential species generation and the scoring ODS mechanism were the core drivers of this performance gain. Visualization analysis further showed that EUA effectively separated the distributions of known and unknown samples, validating the effectiveness of the design. Conclusion: This study achieves a paradigm shift from “passive classification” to “proactive prediction”, providing an effective solution to the problem of unknown category detection in real-world monitoring scenarios lacking environmental priors. The EUA method not only achieves a breakthrough in performance, but also explores a feasible path for embedding ecological knowledge into AI reasoning processes, offering a new direction for building the next generation of ecologically-aware intelligent wildlife monitoring systems.

Objective: This study aims to clarify whether the effect of embodied carbon in exports associated with upgrading global value chain (GVC) status is a booster or a drag, providing a scientific basis for balancing industrial upgrading and carbon neutrality goals, and helping China in taking strategic initiative in the global green value chain reconstruction. Method: Based on panel data from 30 trading partner countries of China from 2007 to 2021, multidimensional indicators were constructed to assess GVC status and embodied carbon intensity in trade. Fixed-effects models and mechanism testing models were employed to empirically examine the relationship between the GVC status of the timber industry and embodied carbon emissions in export trade, and the underlying mechanisms. Result: The upgrading of China’s timber industry’s in GVC status significantly inhibits the intensity of embodied carbon emissions in export trade. Scale, structure, and technological level are key pathways for emission reduction. After a series of robustness tests and endogeneity treatments, this conclusion remains valid, with significant regional heterogeneity observed. The inhibitory effect is stronger in developed nations and smaller trading partners. Conclusion: The upgrading of China’s timber industry in the GVC status can effectively inhibit the embodied carbon emission intensity of export trade. Therefore, efforts should be made to enhance the GVC status of China’s timber industry and vigorously exert the synergistic role of scale effect, structural optimization, and technological upgrading.

: Ginkgo biloba is a national first-class protected relict plant belonging to the genus Ginkgo in the family Ginkgoaceae, boasting high ornamental, economic, and medicinal values. Terpene trilactones, as one of the most significant bioactive components in G. biloba leaves, exhibit anti-dengue, anti-inflammatory, anti-cancer, and antioxidant properties. Specifically, they demonstrate a potent and specific inhibitory effect on platelet-activating factor receptors and serve as effective agents for the treatment of Alzheimer's disease. Consequently, the content of terpene trilactone is considered a crucial selection index in the breeding of superior G. biloba varieties. This paper provides a comprehensive review of the regulatory network underlying the biosynthesis of terpene trilactones. Based on the Methylerythritol 4-phosphate (MEP) and Mevalonate (MVA) pathways, the positive and negative regulatory roles of 20 identified structural genes, five categories of key transcription factors (including MYB, WRKY, bZIP, bHLH, and AP2/ERF), and two types of non-coding RNAs (miRNA and lncRNA) are thoroughly discussed. Furthermore, the indirect effects of environmental factors (such as light, temperature, water, and nutrients) and plant hormones (including ABA, SA, MeJA, IAA, ETH, GA₃, and CCC) on the biosynthesis of terpene trilactones are systematically analyzed. It is clarified that external environmental stimuli, such as ultraviolet radiation and moderate drought, as well as the exogenous application of hormones, such as MeJA, SA, and CCC, can significantly enhance the accumulation of terpene trilactones in G. biloba leaves. Additionally, the factors such as soil fertility, planting density, and the occurrence of pests and diseases also influence their accumulation. Finally, a synergistic strategy integrating “endogenous gene regulation” and “exogenous environmental optimization” is proposed to promote the content of terpene trilactones. This review aims to provide theoretical guidance with significant reference value for future production practices and scientific research, thereby maximizing the medicinal and commercial potential of G. biloba.