To support the breeding of superior germplasm of Castanopsis hystrix, this study investigated the genetic variation patterns in leaf functional traits and genotype by environment (G×E) interactions among open-pollinated progeny families from C. hystrix seed orchards, with the aim of identifying key environmental drivers and providing a theoretical basis for precision breeding and effective deployment.

The study used thirty-three 5.5-year-old open-pollinated progeny families (with female parents from five geographical provenances) from three test sites—Yulin, Liuzhou, and Nanning in Guangxi. Leaf functional traits, including morphological and physiological characteristics, were measured. Nested ANOVA, factor analysis, and BLUP-GGE joint analysis were applied to systematically assess genetic variation patterns and G×E effects on leaf functional traits.

1) In single-environment tests, leaf functional traits exhibited significant variation at the family level, showing a pattern of “high variation among families within provenances and low differentiation between provenances.” Family heritability ranged from 0.02-0.85 for morphological traits and 0.12-0.92 for physiological traits, supporting the potential for family selection; 2) Multi-environment tests revealed significant site effects and a notable decrease in across-site heritability—0.03-0.25 for morphological and 0.10-0.14 for physiological traits—indicating a strong G×E influence on leaf development and metabolism, and its role in the coordinated improvement of growth and leaf functional traits; 3) Factor analysis identified site-specific elite families, while BLUP-GGE analysis further discerned widely adapted families with both high performance and stability. Thermal factors were identified as key environmental drivers of spatial variation in leaf functional traits.

In C. hystrix seed orchard progenies, genetic variation in leaf functional traits occurs predominantly at the family level and is significantly shaped by G×E. A family-based breeding strategy guided by G×E patterns is recommended to enhance genetic gain. Deployment of site-specific or broadly adapted genotypes according to target environments will help optimize breeding efficiency and promotion outcomes.

This study aimed to address the inefficiency of manual measurements in current forest resource surveys.

The LiDAR point cloud data of the natural forests of the Greater Khingan mountains were obtained from unmanned aerial vehicle laser scanning (ULS) and handheld laser scanning (HLS). After trajectory solution, filtering, and noise removal, coarse registration of ULS and HLS was performed using the 3D Harris algorithm for key point extraction, followed by fine registration through the Iterative Closest Point (ICP) algorithm. Based on ULS and fused point cloud data (U-HLS), individual trees were segmented using two approaches: the canopy height model (CHM)-based segmentation and a seed-based K-means hierarchical clustering method. Tree height and diameter at breast height (DBH) were extracted from the optimal segmentation results, and a two-variable additive biomass model was applied to estimate biomass and carbon storage at both individual-tree and plot levels, thereby verifying the applicability of multi-platform LiDAR data for refined forest monitoring.

1) Significant differences were observed in individual tree segmentation accuracy among different methods and data sources. The CHM-based method identified 5 790 individual trees from ULS data but exhibited a high false detection rate, with a recall of only 0.61 and an F-score of 0.43. In contrast, the seed-based K-means hierarchical clustering method, constrained by stem position, achieved notably higher completeness and accuracy, with an F-score of 0.87 and recall, precision, and F-score improved by 107.07%, 70.46%, and 87.49%, respectively; 2) Using U-HLS data and K-means hierarchical clustering method, the tree parameters achieved high accuracy with minimal systematic bias. Both DBH and tree height reached R²=0.93, with RMSE values of 1.6 cm and 1.15 m, respectively, and relative RMSEs below 16%. The inclusion of stem position constraints effectively mitigates errors caused by canopy occlusion, improving the reliability of individual-tree parameters extraction; 3) The estimation accuracy of carbon storage based on U–HLS data is high at both the individual-tree and plot levels, with R² values of 0.97. The carbon storage estimation at the individual tree level has small RMSE (7.14 kg) and bias (-0.68 kg), although underestimation and overestimation occur in large (26-36 cm) and small (<12 cm) DBH classes, respectively. At the plot scale, the R² of carbon storage estimation achieves 0.97, and the RMSE and bias were only 3.62 t C·hm^-2 and -1.27 t C·hm^-2, respectively. The rRMSE, in particular, was 6.22%, significantly smaller than that at the individual tree-level (23.32%). This suggests that at the plot level, individual tree estimation errors are further balanced, partially offsetting local overestimations and underestimations, resulting in high consistency between carbon storage estimates and observed values.

Multi-platform LiDAR data effectively enhances the accuracy of individual-tree parameter extraction and carbon storage estimation, maintaining stable and reliable performance under complex forest conditions. It can partially replace traditional field measurements at both individual-tree and plot scales, providing a valuable reference for efficient and refined forest resource surveys and carbon sink monitoring.

To investigate the impact of environmental factors on the canopy hyperspectral characteristics of Camellia oleifera at different growth stages, aiming to provide theoretical support for precise fertilization and scientific management of Camellia oleifera plantations and to promote the sustainable development of the Camellia oleifera industry.

A total of 240 Camellia oleifera plants were divided into 12 sample plots within the study area. Canopy hyperspectral data, topographic factors, and soil factors were measured during three key growth periods: spring shoot stage, fruit expansion stage, and full bloom stage. Climate factor data were obtained from the National Earth System Science Data Center. Thirteen vegetation indices were derived from the hyperspectral bands, and a structural equation model (SEM) was constructed to quantify the impact of different environmental factors on canopy spectral characteristics and to reveal their intrinsic relationships and spatial distribution patterns.

The canopy hyperspectral reflectance values of Camellia oleifera during the spring shoot stage, fruit expansion stage, and full bloom stage were 0-0.413, 0-0.532, and 0-0.683, respectively. Significant correlations were found between spectral bands and soil nutrient factors across all periods. The structural equation models (SEMs) constructed with the normalized difference vegetation index (NDVI), photochemical reflectance index (PRI), enhanced vegetation index (EVI), optimized soil-adjusted vegetation index (OSAVI), and plant senescence reflectance index (PSRI) had good fit indices of 0.94, 0.92, 0.83, 0.90, and 0.83, respectively. The results indicated that canopy spectral characteristics of Camellia oleifera are significantly and directly influenced by climate and soil nutrient factors, while topographic factors have an insignificant direct effect but indirectly influence canopy spectra through soil nutrients. Temperature, precipitation, evaporation, nitrogen, and phosphorus were found to have significant impacts on canopy spectral characteristics.

Climate, topography, and soil nutrient factors collectively influence the canopy spectral characteristics of Camellia oleifera, with climate and soil nutrients playing a core role and topography having an indirect effect. This study provides important scientific evidence for large-scale planting and precise management of Camellia oleifera, as well as practical references for improving soil nutrient use efficiency and promoting efficient cultivation techniques.

The growth and nutrient dynamic properties of spring shoot leaves in mature Camellia oleifera forests under various short-cut pruning techniques were examined in this study.

Xiajiang County forest seed farm, Shuibian Town, Xiajiang County, Ji'an City, Jiangxi Province was the location of the experimental site. For Camellia oleifera No.53, a 14-year-old growth forest in this location, five different short-cut pruning treatments were established: [45° no stubble (D-X0), 45° stubble 1 cm (D-X1), 90° no stubble (D-P0), 90° stubble 1 cm (D-P1), control group without pruning (D-CK)]. During the spring shoot growth stage, the effects of various pruning techniques on leaf growth characteristics, nutritional components, and non-structural carbohydrate (NSC) content were investigated.

1) Significant morphological differences were observed in spring shoots and leaves under different short-cutting treatments, with the D-X0 treatment yielding the most pronounced effects. Regarding nutrient patterns, the nitrogen (N) levels significantly increased under D-X0, D-X1, and D-P1 treatments, while the phosphorus (P) and potassium (K) showed varying degrees of increase across all pruning methods. Trace elements exhibited distinct patterns across short-cutting treatments; the NSC showed an accumulative trend under all short-cutting methods; 2) In terms of temporal dynamics, the morphological indexes of spring shoot showed a rapid growth trend from the 10th to the 30th day and then slowed down; the concentrations of macronutrients, magnesiumMg) and iron (Fe) all followed a patern of initially decreasing and then increasing, and the content valley value was at the 30th. The calcium (Ca) content continued to climb, the copper (Cu) content exhibited a declining trend, while the zinc (Zn) content first dropped rapidly before leveling out; and the NSC showed an initial rise followed by a decline, the content peaked on the 30th under each reatment; 3) Structural equation modeling (SEM) indicates that the D-X0 treatment exerts a positive influence on leaf growth traits via the macronutrients and NSC in the leaves.

D-X0 treatment favorably regulated leaf growth through macroelements and NSC, and it had the most stimulating influence on leaf growth features, macroelements, and NSC accumulation. Additionally, there were notable temporal dynamics in the development of spring shoots and nutrients, with the 30th day serving as the critical time node.

Correlation analysis and comprehensive evaluation were conducted on leaf anatomical structure and photosynthetic characteristics of five Camellia oleifera superior lines, and the relationship between leaf anatomical structure and photosynthetic capacity of five Camellia oleifera superior lines was explored, and the superior lines with the best photosynthetic characteristics were screened, so as to provide scientific basis for subsequent breeding, cultivation and popularization.

By artificial cross pollination between ‘Sanhua’ and ‘Xianglin 210’, five superior lines of Camellia oleifera were selected, namely ‘Huashi’ (‘Huashuo’ × ‘Huajin’), ‘Huazeng’ (‘Huajin’ × ‘Xianglin210’), ‘Huatuo’(‘Huajin’ × ‘Xianglin210’), ‘Huafeng’ (‘Huashuo’ × ‘Huaxin’) and ‘Huaping’ (‘Huajin’ × ‘Huaxin’). The chlorophyll content, stomatal characteristics, leaf anatomical structure and photosynthetic characteristics of the five superior lines were determined. Finally, correlation analysis and principal component analysis were used to analyze the five superior lines of Camellia oleifera.

It was found that ‘Huatuo’ had the highest leaf shape index, ‘Huashi’ had the largest leaf area, and the total chlorophyll content (10.06 mg·g^-1) was significantly higher than that of the other four superior lines of Camellia oleifera. ‘Huafeng’ had the best stomatal density (10.80/mm²), and the upper epidermis thickness of ‘Huazeng’ was the largest. However, the leaf thickness (523.23 μm), spongy tissue thickness (288.22 μm), palisade tissue thickness (171.40 μm) and transpiration rate of ‘Huaping’ were higher than those of the other four superior lines of Camellia oleifera. Correlation analysis showed that the net photosynthetic rate of leaves is negatively correlated with the thickness of palisade tissue and the ratio of palisade to leaf, and positively correlated with the thickness of leaves, the thickness of the upper and lower epidermis and TRPS. Principal component analysis showed that the cumulative contribution rate of four principal components extracted from 10 leaf traits reached 85.530%, among which the first, second, third and fourth principal components reflected 29.422%, 27.329%, 18.203% and 10.576% of the original data information, respectively, which could fully reflect the leaf anatomical structure and photosynthetic characteristics of Camellia oleifera superior lines. Based on the principal component analysis method, the comprehensive score of each superior line is calculated, and the order is ‘Huaping’, ‘Huatuo’, ‘Huafeng’, ‘Huazeng’ and ‘Huashi’ according to the comprehensive score from high to low.

This study revealed the relationship between leaf anatomical structure and photosynthetic characteristics of superior lines of Camellia oleifera, and screened the superior line ‘Huaping’ with the best photosynthetic characteristics, which provided an important reference for the breeding of improved varieties of Camellia oleifera. Future research should further combine multi-trait comprehensive evaluation and consider the influence of environmental conditions to improve the comprehensiveness and reliability of the research.

To investigate the correlations among leaf functional traits and their phylogenetic signals in common woody species of Yuanjiang dry-hot valley, and to provide a scientific basis for regional vegetation conservation.

Leaves from 32 woody species representing different life forms were collected, and eight leaf functional traits were measured, including leaf area (LA), leaf dry matter content (LDMC), and specific leaf area (SLA). Trait differences were analyzed using t-tests, Pearson correlation was employed to assess trait relationships, and phylogenetic signals were quantified using Blomberg's K.

Significant interspecific trait variations were observed across life forms. Evergreen species exhibited lower LA, leaf carbon content (LCC), and leaf phosphorus content (LPC) but higher LDMC and N∶P ratios compared to deciduous species (P<0.05). Trees showed higher LA, leaf thickness (LT), LCC, and LPC, but lower LDMC, SLA, and N∶P than shrubs (P<0.05). Trait correlations varied by life form: In evergreens, LNC and LPC, as well as LDMC and SLA, were positively correlated (P<0.05), while LT and LNC, and N∶P were negatively correlated (P<0.05). In deciduous species, LT and LA, and LNC and N∶P showed positive correlations (P<0.05), whereas LT and LDMC, and SLA were negatively correlated (P<0.05). Trees displayed positive correlations between LCC and LNC, and N∶P (P<0.05), while shrubs showed positive correlations between LT and LDMC, and LNC and LCC (P<0.05). Principal component analysis (PCA) identified LA, LT, and LCC as key trait indicators, classifying the 32 species into four functional groups: high LNC, N∶P, SLA; high LA, LCC, LPC; high LT, and high LDMC. All traits exhibited detectable but weak phylogenetic signals (0<K<1, P=0.01), suggesting environmental selection outweighs phylogenetic constraints in trait evolution.

Evergreen and shrub species adapt to the dry-hot environment through high LDMC and LT, reflecting conservative resource-use strategies, while deciduous and tree species employ large LA, high C, N, P, and SLA for rapid resource acquisition. LA, LT, and LCC serve as diagnostic traits for these adaptive strategies. Phylogenetic history weakly influences trait variation, these findings provide functional evidence for understanding plant adaptation mechanisms in dry-hot valleys.

This study screened superior variant types through phenotypic trait analysis and measurement of nutritionally valuable components in the fruits of Docynia delavayi, providing a theoretical basis for the breeding of high-quality Docynia delavayi cultivars.

Taking the fruits of Docynia delavayi from Lancang County as the subject of study, twelve variant types were classified based on fruit size, shape, and color. Seven nutritional components—total acidity, total sugars, tannins, flavonoids, crude protein, vitamin C, and crude fiber—were measured. Comprehensive evaluation of the twelve types was conducted using principal component analysis, correlation analysis, score assignment method, and integrated scoring method.

Based on the variation characteristics of fruit phenotypic traits (fruit size, fruit shape, fruit color), these are categorized into 12 variation types: small globular yellow type, small globular red-yellow type, small oval yellow type, small oval red-yellow type, medium globular yellow type, medium globular red-yellow type, medium oval yellow type, medium oval red-yellow type, large globular yellow type, large red-yellow type, large oval yellow type, large oval red-yellow type). Analysis of fruit constituents (total acidity, total sugars, tannins, flavonoids, crude protein, vitamin C, crude fiber) revealed significant variation across all traits. The coefficients of variation were as follows: flavonoids (39.92%)>total sugars (27.25%)>crude fiber (20.83%)>vitamin C (18.42%)>crude protein (12.50%)>total acidity (10.39%)>tannin (2.31%). Correlation analysis revealed extremely significant positive correlations between flavonoid, vitamin C, and total sugar content with fruit transverse diameter, longitudinal diameter, individual fruit weight, and fruit shape index. Principal component analysis further indicated that individual fruit weight, transverse diameter, longitudinal diameter, total sugar, and flavonoids were the primary indicators influencing fruit morphological variation, cumulatively accounting for 70.795% of the variance. Principal component-based ranking revealed that PC1 and PC2 clearly distinguished the ‘large, medium, and small’ fruit size categories, with high internal clustering and distinct classification boundaries within each category. The quality ranking obtained using the score assignment method—‘large fruit>medium fruit>small fruit’—was consistent with the PCA analysis conclusions.

The fruits of Docynia delavayi exhibit rich phenotypic variation and nutritional bioactive compounds. Twelve types were identified and screened, yielding four superior types. This provides a scientific basis for the breeding of high-quality Docynia delavayi cultivars and the development and utilization of its resources.

The aim of this experiment was to explore the effects of root sprouting rejuvenation on the growth of Robinia pseudoacacia cutting seedlings, and provide a theoretical basis for the establishment of Robinia pseudoacacia rejuvenation system in the future production practice.

The cuttings of Robinia pseudoacacia root sprouts and semi-lignified branches of the mother tree were used as propagation materials, and the 1-year-old seedlings of Robinia pseudoacacia were set as the control. The differences in leaf morphology and anatomical structure, dry and fresh weight, gas exchange parameters, chlorophyll fluorescence parameters, photosynthetic enzyme activity and nutrient physiology of seedlings cultivated with different propagation materials were determined.

The results showed that, compared with the seedlings and mother tree branch cuttings, the root sprouting and rejuvenation treatment significantly increased the leaf length, leaf width, leaf perimeter, leaf area, dry and fresh weight, and leaf axis length of Robinia pseudoacacia cuttings, and significantly reduced the thickness of the upper epidermis, palisade tissue, and leaf thickness. Compared with seeded seedlings, the thickness of spongy tissue, leaf compactness, leaf porosity and the P/S ratio had no significant changes. The content of photosynthetic pigment, net photosynthetic rate, transpiration rate, F_v/F_m, F_v/F_o, NPQ and other gas exchange parameters, chlorophyll fluorescence parameters of Robinia pseudoacacia seedlings were significantly increased by root sprouting and rejuvenation treatment, and the rooting sprouts in one year were the highest. The activities of fructose 1,6-bisphosphate aldolase (FBA) and ribulose-1,5-diphosphate carboxylase/oxygenase (Rubisco) in the seedlings after root sprouting and rejuvenation were significantly higher than those in the mother branch cuttings, but there were still significant differences between the seedlings and the seedlings; However, the C/N, N/P, NSC and starch contents as well as the dry and fresh weight of leaves increased. The seedlings after root sprouting and rejuvenation had higher nutrient utilization efficiency and dry matter accumulation, and the one-year-old rooting shoots was the highest.

The cuttings of Robinia pseudoacacia, which have been rejuvenated by root sprouting, have stronger growth potential and juvenility, which provides theoretical support for the breeding of improved varieties and strong seedlings of Robinia pseudoacacia.

To investigate the physiological impacts of different waterlogging depths on Phyllostachys heteroclada f. solida during specific waterlogging periods, and to explore the mechanisms underlying its effects on leaf photosynthesis, chlorophyll fluorescence characteristics, and the antioxidant system, thereby revealing its waterlogging tolerance and response strategies at the physiological and ecological levels.

Two-year-old P. heteroclada f. solida seedlings were subjected to simulated waterlogging treatments, including a control group under normal moisture CK, GY and SY. Measurements of photosynthetic pigment content, gas exchange parameters, chlorophyll fluorescence parameters, osmoregulatory substance levels, and antioxidant enzyme activities were conducted at five time points (Day 0, Day 10, Day 20, Day 30, and Day 40).

1) The content of photosynthetic pigments in P. heteroclada f. solida initially declines and then rises, though remaining lower than that in the CK group. In the GY group, chlorophyll a (Chl a) reaches its nadir on Day 30, decreasing by 48.97% compared to CK. Chlorophyll b (Chl b) in both waterlogging groups shows the lowest levels on Day 30, with reductions of 48.09% (GY) and 62.15% (SY) relative to CK; 2) Waterlogging intensity significantly affects photosynthetic gas exchange parameters (P<0.05). Over time, net photosynthetic rate (P_n), stomatal conductance (G_s), and transpiration rate (T_r) decline in all treatment groups, with SY showing reductions of 86.87%, 78.02% and 60.00%, respectively, compared to CK by the end of the stress period. Intercellular CO₂ concentration (C_i) increases continuously. Chlorophyll fluorescence parameters differ markedly among treatments, though GY and SY exhibit similar trends: initial fluorescence (F_o) and non-photochemical quenching (NPQ) rise, while maximum fluorescence (F_m) and photochemical quenching (qP) decline; 3) Waterlogging duration differentially influences malondialdehyde (MDA) content: GY follows a “rise-decline-rise” pattern, whereas SY peaks on Day 30 (56.92% higher than CK) before declining. Proline (PRO) content increases steadily in both treatment groups; 4) SOD, POD, and CAT activities generally increased rapidly initially and then declined slowly.

P. heteroclada f. solida responds to early waterlogging stress by rapidly elevating SOD, POD, and CAT activities. In the mid-stage, black spots appear on submerged leaves, which subsequently fall off, accompanied by reduced photosynthetic pigment content and photosynthesis. Despite the weakening of photosynthetic parameters over time, antioxidant enzyme activities remain higher than those in CK, and chlorophyll content gradually recovers, indicating that the plant is still in a phase of self-metabolic regulation. In summary, P. heteroclada f. solida demonstrates certain waterlogging tolerance, enabling it to sustain basic growth and metabolism under prolonged waterlogging. Based on this trait, it holds potential as a landscape plant for urban-rural sponge city and waterfront greening projects.

To investigate the genetic variation in growth rhythm of Dalbergia odorifera seedlings from different provenances, so as to provide a theoretical basis for superior provenance selection and efficient seedling cultivation.

One-year-old seedlings from nine provenances in Hainan were regularly measured for height and ground diameter. The annual growth process was fitted using the Logistic growth curve, and key growth parameters including maximum growth rate (MGR), rapid growth rate (RGR), growth increment during the rapid growth period (RIG), and the proportion of rapid growth period (PRT) were calculated. Correlation and cluster analyses were conducted in combination with geographical and climatic factors. The genetic parameters such as heritability were estimated by the ASReml-R 3.0.

The Logistic model showed a good fit for both height and ground diameter growth (R²>0.98), with seedling growth following a typical “S”-shaped curve, which could be divided into initial, rapid, and late growth phases. Significant differences were observed among provenances in both phenological and growth parameters. The rapid growth period of ground diameter occurred earlier than that of height, with average starting times of day 47 and day 117, respectively. MGR, RGR, and RIG were significantly positively correlated with annual precipitation of the provenances, indicating that moisture is an important environmental factor affecting growth rate. Cluster analysis grouped the nine provenances into two categories based on geographical structure. With the exception of PRT, significant differences in growth rhythm parameters were observed between groups. Genetic analysis revealed that heritability was generally higher for ground diameter than for height, and growth rhythm traits exhibited moderate heritability with low coefficients of genetic variation, indicating that these traits are mainly under genetic control and have high potential for genetic improvement.

The growth rhythm of D. odorifera seedlings exhibits clear differences among provenances and geographic variations. Annual precipitation is an important environmental factor influencing growth rate. The Logistic model can accurately predict growth processes, providing a reliable basis for scientific seedling cultivation, provenance selection and genetic improvement, the results of this study offer important theoretical and technical support for superior breeding and efficient cultivation of D. odorifera.

This study aims to investigate the long-term and effective protection mechanisms for ecological protection redline areas, which are crucial for maintaining ecological security patterns, ensuring ecosystem functionality, and supporting sustainable socioeconomic development.

The research took the ecological protection redline areas in the Poyang lake basin as its study object. It constructed a dynamic ecological quality monitoring system based on the "matrix-stress-wildness" framework by integrating multi-source remote sensing data and ground monitoring data. The study introduced the XGBoost machine learning algorithm to adaptively adjust weight thresholds and establish a modified ecological quality index. Furthermore, it employed Theil-Sen trend analysis, Mann-Kendall test, and long short-term memory (LSTM) neural network to systematically reveal and predict the spatiotemporal evolution patterns and future development trends of ecological quality within the ecological protection redline areas of the Poyang lake basin.

The ecological quality within the ecological protection redline areas of the Poyang lake basin showed distinct phased characteristics temporally. During the rapid change period, spatial heterogeneity of ecological quality significantly intensified, with widening disparities among different land use types. In the stable adjustment period, the overall fluctuation range of ecological quality tended to moderate, with restorative improvements observed in some areas, reflecting the positive effects of ecological protection policies. Spatially, regions with lower ecological quality are mainly concentrated in the northwestern mountainous and hilly areas, the central basins characterized by concentrated agriculture and urbanization, and the northern lake areas affected by significant human activities. In contrast, areas with higher ecological quality are primarily distributed in the southern part of the basin, which features high natural vegetation coverage and minimal human disturbance. LSTM model predictions indicated that future ecological quality is primarily classified as "poor" and "medium," with "good" quality areas covering only 10 600 km² and concentrated in the Ganjiang river source reserve. Typical ecologically vulnerable areas continue to face multiple anthropogenic and natural pressures.

The monitoring and assessment system established in this study effectively identifies the spatiotemporal evolution characteristics of ecological quality, providing data support and theoretical references for precise management and policy formulation in ecological protection redline areas.

Nutrient resorption from senescing tissues is recognized as a strategy for plants to adapt to nutrient deficiency. However, how nutrient resorption regulates the balance of nutrient elements within plants remains unclear, particularly under conditions of increased soil nitrogen availability.

This study investigated the changes in nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) content in green and senescent leaves, as well as soil nutrient contents, in a subtropical Castanopsis hystrix plantation under different N addition treatments (Control, CK: 0 kg·hm^-2·a^-1; Low N, LN: 50 kg·hm^-2·a^-1; Medium N, MN: 100 kg·hm^-2·a^-1; High N, HN: 150 kg·hm^-2·a^-1). The overall patterns and main drivers of nutrient resorption efficiency and its stoichiometric ratios were also examined.

The results showed that the HN treatment significantly increased soil dissolved inorganic N (DIN) content, leading to a significant decrease in soil DOC∶DIN and a significant increase in soil DIN∶AP (P<0.05), indicating that long-term high N input exacerbates soil P limitation. Under N addition, the concentrations of N, P, Ca, and Mg in both green and senescent leaves showed an increasing trend. MN and HN significantly increased green leaf total N (TN) content; MN significantly increased green leaf total P (TP) content; LN and HN significantly increased green leaf Ca content. LN, MN, and HN significantly increased senescent leaf TN content; HN significantly increased senescent leaf Ca content. LN, MN, and HN significantly decreased nitrogen resorption efficiency (NRE); phosphorus resorption efficiency (PRE) was significantly reduced only under the LN treatment. N addition had no significant effect on potassium, calcium, or magnesium resorption efficiency (KRE, CaRE, MgRE). Furthermore, senescent leaf nutrient content was significantly negatively correlated with resorption efficiency, indicating that nutrient resorption in C. hystrix is primarily regulated by senescent leaf nutrient status.

Our findings provide a theoretical basis for nutrient management in subtropical C. hystrix plantations and for understanding ecological adaptation strategies under nitrogen deposition.

To explore the effects of stand types on plant diversity and soil stoichiometric characteristics, and to provide theoretical references for afforestation and vegetation restoration and reconstruction in arid and semi-arid regions.

In this study, Pinus tabuliformis×Cotinus coggygria (Pt×Cc), Pinus tabuliformis×Quercus mongolica (Pt×Qm), Pinus tabuliformis×Caragana korshinskii (Pt×Ck), Pinus tabuliformis×Prunus sibirica (Pt×Ps), Pinus tabuliformis×Acer mono (Pt×Am) and Pinus tabuliformis (Pt) were selected as the research objects. Based on the investigation of typical plots and the results of indoor experiments, the understory diversity and contents, stocks and stoichiometric ratios of soil organic carbon (SOC), total nitrogen (TN) and total phosphorus (TP) in the soil were calculated.

Stand types significantly influence the composition and diversity characteristics of understory shrubs and herbs. The understory plant species are as follows: Pt×Qm (39 species), Pt×Ck (38 species), Pt×Cc (27 species), Pt×Ps (27 species), Pt (21 species), and Pt×Am (20 species). The dominant species in the shrub layer consist primarily of regenerating saplings from the mixed tree species, while the herb layer is co-dominated by Lespedeza bicolor and Carex lanceolata. In the shrub layer, the plant diversity index of the Pt×Qm was significantly higher than that of other stands. The plant richness of Pt is the lowest, but the evenness index is relatively high. In the herb layer, the Pt×Ck exhibited the highest plant diversity index, while the Pt showed a relatively high plant diversity index with no significant difference compared to most other forest stands. The content and stocks of SOC and TN in mixed forests were significantly higher than those in pure forests, and there was no significant difference in TP content and stocks. The soil C∶N of Pt×Qm and Pt×Cc showed no significant differences compared to Pt, while their soil C∶P and N∶P were significantly higher than that of Pt. The comprehensive scores of the six stand types were ranked as follows: Pt×Qm>Pt×Cc>Pt×Ck>Pt×Ps>Pt×Am>Pt.

Introducing broadleaf tree species into Pt can enhance understory plant diversity and promote soil nutrient retention. The Pt×Qm demonstrates optimal performance in terms of species diversity and soil nutrient content, making it an ideal configuration for ecological restoration efforts.

This study aimed to characterize the woody species composition and community structure of a typical southern subtropical evergreen broad-leaved forest in China, elucidate its succession pattern, species diversity, and development trend, and to provide a scientific basis for the refined management and biodiversity conservation of forest ecosystems in this region.

Sixteen permanent plots, each covering an area of 1 200 m², were established in a secondary forest in Conghua, Guangzhou, which had naturally regenerated after logging in the 1990s. All woody plants with a diameter at breast height (DBH)≥5 cm were surveyed within each plot. The species composition, species diversity, diameter-class structure, and vertical stratification of the community were systematically analyzed.

1) A total of 4 095 woody individuals (DBH≥5 cm) were recorded in the plots, belonging to 58 species, 46 genera and 34 families; and the families Lauraceae, Ebenaceae and Fagaceae were predominant; 2) Eight family and 11 genus distribution area types were identified, with tropical elements predominantly accounting for 64.71% of families and 65.22% of genera; 3) Twenty-three species had an importance value above 1%; the top six dominant tree species were Machilus chinensis, Diospyros morrisiana, Schima superba, Castanopsis faberi, Triadica cochinchinensis and Camphora parthenoxylon; and M. chinensis was absolutely dominant (importance value: 22.36%); 4) The diameter-class structure showed a typical reverse “J”-shaped distribution, indicating favorable community regeneration; 5) The vertical structure was stratified into four layers: sapling (2.5-9.3 m), sub-canopy (9.4-12.9 m), mid-canopy (13.0-16.5 m), and upper-canopy layers (16.6-25.8 m), trees in the sub- and mid-canopy layers together accounted for 64.96%, and species diversity decreased significantly with increasing canopy height; 6) The overall species diversity of the community was moderately high, but individual abundance was unevenly distributed among species, concentrated in a few dominant tree species.

This community represents a typical warm subtropical evergreen broad-leaved forest in the Pearl River Delta region. Currently in a mid-succession stage, it is characterized by generally small tree diameters, a stable structure, and a growing trend. Forest quality can be rapidly improved through target-tree management and enrichment planting with valuable tree species characteristic of middle and late succession stages.

This study aimed to explore the variation characteristics of net ecosystem productivity (NEP) and its environmental regulation in a typical artificial mixed coniferous and broad-leaved forest ecosystem in Beijing, clarify its carbon sequestration function, and to support the goals of carbon peaking and carbon neutrality.

An artificial mixed coniferous and broad-leaved forest ecosystem located in Beijing was selected as the study site. Continuous in-situ observations of NEP were conducted throughout 2023 using the eddy covariance (EC) technique. Simultaneously, environmental factors, including photosynthetically active radiation (PAR), vapor pressure deficit (VPD), air temperature (T_a), and soil water content (SWC), were monitored. The random forest model was used to calculate the importance scores of these environmental factors and to quantify their impacts on NEP and carbon sequestration.

The energy closure of the measurements was 0.72, The average daily and seasonal variations of NEP exhibited unimodal trends, with NEP peaking at 11.95 μmol·m^-2·s^-1 in July during the growing season (March–November). The ecosystem acted as a carbon sink during the growing season, with a net carbon sequestration of 384.83 g·m^-2, whereas it functioned as a carbon source in the non-growing season, releasing 1.18 g·m^-2. The total annual net carbon sequestration was 383.65 g·m^-2. Seasonal variations in NEP showed an initial increasing trend followed by a decrease, significantly influenced by PAR, SWC, VPD and T_a (P<0.01). Among these factors, PAR was the dominant environmental factor controlling NEP and carbon sequestration, with an importance score of 56.42 determined by the random forest model. The thresholds of environmental factors influencing NEP were 400 μmol·m^-2·s^-1 (PAR), 0.17 m³/m³ (SWC), 1.5 kPa (VPD), and 28 ℃ (T_a). Additionally, when SWC was below 0.1 m³/m³, it initially increased with rising T_a, but after exceeding 10 ℃, SWC decreased. The indirect regulatory threshold of T_a on NEP was thus identified as 10 ℃.

The studied artificial mixed coniferous and broad-leaved forest exhibited moderate carbon sequestration capacity. PAR was the primary factor controlling seasonal variations in carbon sequestration. The findings provide scientific support for managing carbon sink enhancement in artificial mixed coniferous and broad-leaved forest ecosystems in Beijing. Additionally, the observational dataset constitutes an important supplement for validating models used in forest carbon estimation.

To reveal the altitudinal distribution pattern and driving factors of soil fungal communities in Sabina przewalskii natural forests, thereby providing a theoretical basis and scientific support in the field of soil microbiology for the ecological protection of the Qilian mountains.

Focusing on the Sabina przewalskii natural forests soil at different altitudes in Qilian mountains, the high-throughput sequencing technology was used to analyze the diversity and community composition of soil fungi and explore the main factors influencing the soil fungal community structure.

A total of 6 phyla, 27 classes, 81 orders, 170 families, 295 genera and 355 species of soil fungi were discovered across different altitudes at the phylum level, Basidiomycota and Ascomycota dominated the fungal communities, with relative abundances of 0.22-0.66 and 0.11-0.39. Hygrocybe and Mortierella were the dominant genera. There were significant differences in soil fungal among different altitudes (P<0.05), with the richness and diversity of soil fungal communities at low and medium altitudes being significantly higher than those at high altitudes. Overall, the soil fungal diversity first increased and then decreased with increasing altitude. Redundancy analysis (RDA) and Spearman correlation analysis showed that altitude, soil pH, SOM, TP, AK and AP were the key environmental factors affecting the community structure and diversity distribution pattern of soil fungal.

The soil fungal community in Sabina przewalskii natural forests of the Qilian mountains is rich in composition, with Basidiomycota and Ascomycota as the dominant phyla. Soil pH, AP and TP are the core variables driving the soil fungal community structure. In addition, fungal diversity is negatively correlated with altitude and HN, while positively correlated with AK and SOM.

By cloning the BpbZIP36 gene, constructing a plant expression vector, and obtaining stable transgenic birch plants, this study aimed to investigate the drought resistance function of the BpbZIP36 gene.

Using birch as the experimental material, the BpbZIP36 gene was cloned from birch cDNA as the template. Bioinformatics analysis was performed on the gene, and the pROK2-BpbZIP36 plant expression vector was constructed and introduced into birch seedlings to obtain transgenic birch overexpressing BpbZIP36. The transgenic birch plants and wild-type were subjected to drought stress to study the drought resistance function of the BpbZIP36 gene.

A bZIP gene was obtained from the birch genome database, with an open reading frame (ORF) of 1 269 bp encoding 422 amino acids. The results of multiple sequence alignment showed that the BpbZIP36 protein was similar to the bZIP protein of other plants and a conserved bZIP structural domain. qRT-PCR results showed that the BpbZIP36 gene was expressed in roots, stems, and leaves. In stems and leaves, the expression level of BpbZIP36 peaked at 72 h, while in roots, the highest expression was observed at 24 h of stress treatment, indicating that the BpbZIP36 gene could be induced by drought stress. Physiological index and histochemical staining analyses revealed that under drought stress, the transgenic birch overexpressing BpbZIP36 exhibited lower MDA, H₂O₂ content, and relative electrical conductivity compared to wild-type plants, indicating better cell membrane integrity. The SOD, POD and CAT activities, as well as relative water content, were higher in the transgenic birch. DAB staining showed the lightest coloration in the three overexpression lines, suggesting lower H₂O₂ accumulation and reduced cellular damage. These results demonstrated that the drought resistance capacity of the transgenic birch overexpressing BpbZIP36 was stronger than that of wild-type.

Overexpression of the BpbZIP36 gene enhances the drought resistance capability of transgenic birch.

Ormosia microphylla is a rare and endangered tree species endemic to China and is listed as a Class I nationally protected wild plant. It possesses high economic and ecological value. Due to limited seed sources, traditional seed propagation methods have a low propagation coefficient; therefore, tissue culture technology has become an important approach for the rapid propagation of O. microphylla. This study aimed to establish an in vitro rapid propagation system for O. microphylla.

Mature seeds of O. microphylla were used to establish an aseptic seedling culture system, and the optimal seed sterilization protocol was screened. Bud-bearing stem segments from germinated aseptic seedlings were used as explants, and an L₉(3³) orthogonal experimental design was employed to determine the optimal medium for shoot induction and proliferation. The effects of different subculture cycles on proliferation were analyzed during the subculture stage. Finally, rooting and transplanting experiments were conducted to screen for the optimal rooting medium and the most suitable transplanting substrate.

The optimal sterilization protocol was to retain the seed coat and disinfect the seeds with 2% NaClO for 12 min, under which no contamination occurred, with an aseptic seedling rate of 70.37% and a browning rate of 23.23%. The optimal proliferation medium was MS supplemented with 1.5 mg·L^-1 6-BA and 0.15 mg·L^-1 IAA, yielding a proliferation coefficient of 5.23 and an average shoot height of 3.59 cm. The third subculture cycle showed the best proliferation performance, with a proliferation coefficient of 5.33. The optimal rooting medium was 1/2 MS supplemented with 0.3 mg·L^-1 NAA, resulting in a rooting rate of 93.33%, an average of 3.95 roots per shoot, and an average root length of 3.63 cm. The highest survival rate (95.56%) was achieved when vermiculite∶perlite (1∶1) was used as the substrate.

This study established a relatively stable and efficient in vitro rapid propagation system for O. microphylla. Based on experimental investigations of key procedures including explant sterilization, bud induction and proliferation, subculture, rooting and acclimatization, this work provides a theoretical basis and technical support for the germplasm conservation and large-scale propagation of this species.

To investigate the out-of-plane compressive performance of laminated bamboo grid sandwich panels under different loading conditions, and to provide both theoretical foundations and experimental support for their lightweight applications in modern green prefabricated buildings.

This study focused on flat-pressed laminated bamboo grid sandwich panels fabricated from Phyllostachys edulis sourced from Taojiang County, Hunan Province. Two core configurations were designed: axial parallel-to-grain and axial perpendicular-to-grain. A total of 18 specimens were prepared (3 parallel specimens for each of the 2 core types under 3 loading conditions). Out-of-plane compression tests were conducted under concentrated, linear, and planar loads to systematically investigate their failure mechanism and mechanical properties.

The laminated bamboo grid sandwich panels exhibited significantly distinct failure modes under different loading conditions. Under concentrated load, failure primarily manifested as localized face-sheet fracture; under linear load, face-sheet fracture dominated; while under planar load, the predominant failure modes were web buckling and fracture. Axial parallel-to-grain core specimens demonstrated superior mechanical performance across all three loading conditions compared to axial perpendicular-to-grain specimens, with compressive strength increasing by 33.3%, 130.3% and 178.0%, compressive modulus increasing by 36.4%, 16.6%, and 25.2%, and energy absorption capacity increasing by 14.3%, 72.5% and 186.6%, respectively. As shown in the results, the load-displacement curves exhibited typical nonlinear characteristics, with axial parallel-to-grain specimens showing higher stiffness but lower ductility, while axial perpendicular-to-grain specimens displayed the opposite behavior.

The failure modes of specimens showed significant differences under different loading conditions (concentrated load, linear load, planar load). Meanwhile, the core type significantly affected the out-of-plane compressive performance of specimens, specifically showing that axial parallel-to-grain core specimens exhibited notably higher compressive strength, compressive modulus and energy absorption capacity than axial perpendicular-to-grain core specimens.

Wood density, as a key parameter for evaluating wood quality, is a focal point in both wood trading and processing. The development of efficient, non-destructive, and cross-species detection technologies for wood density is of great importance for the exploitation of forestry resources and the efficient utilization of wood.

This study selected two typical hardwood species from northeast China, specifically Manchurian walnut (Juglans mandshurica) and Manchurian ash (Fraxinus mandshurica), as research subjects to establish a near-infrared (NIR) spectral transfer model for cross-species wood density prediction. A stable predictive feature selection (SPFS) algorithm was designed to score and rank spectral bands. The elbow method was applied to determine the optimal number of bands and to select common feature bands. A stacked autoencoder (SAE) was introduced as a feature transformation mechanism. Combined with an artificial backpropagation (BP) neural network prediction model, a new cross-species spectral model transfer method was constructed.

Following the transfer of the Juglans mandshurica model based on SAE, the coefficient of determination (R²) for the Fraxinus mandshurica prediction set rose from 0.172 7 to 0.827 1, and its root mean square error of prediction (RMSEP) fell from 0.180 1 to 0.049 3 g/cm³. In the opposite transfer direction, applying SAE to the Fraxinus mandshurica model improved the R² for the Juglans mandshurica prediction set from 0.000 9 to 0.884 9, and reduced the RMSEP from 0.187 8 to 0.032 9 g/cm³. These results indicate that the SAE-based method achieves substantial improvements in both R² and RMSEP metrics when compared to traditional techniques such as piecewise direct standardization and slope/bias correction algorithms.

The findings of this study demonstrate that the SAE-based NIR transfer model is effective for cross-species applications, allowing for the rapid and efficient prediction of wood density in different tree species. This approach promotes model sharing across species and offers both a theoretical basis and technical support for improving the universality of NIR models.

Under the global context of climate change and the pursuit of carbon peaking and neutrality goals, scientifically assessing the dynamic evolution, driving mechanisms, and future evolution pathways of tourism-related carbon emissions at the provincial scale is critical for formulating differentiated emission reduction strategies.

Taking Hunan Province as a case study, this paper develops a hybrid accounting framework that integrates top-down and bottom-up approaches to systematically measure the magnitude and structure of tourism carbon emissions from 2006 to 2025. An extended STIRPAT model combined with ridge regression is employed to identify key driving factors, while the Tapio decoupling model and multi-scenario simulation are coupled to project peak emission pathways.

1) In terms of emission scale, tourism carbon emissions in Hunan reached a staged historical peak of 17.814 3 million tons in 2019, rebounding strongly to 16.889 7 million tons from 2023 to 2025, with transportation and sightseeing activities accounting for 74%-84% of total emissions; 2) Regarding driving factors, tourist volume is the primary positive driving factor (elasticity coefficient 0.648 7), while energy intensity shows a relatively marginal contribution (elasticity coefficient 0.106 6), indicating that current growth remains dominated by scale expansion, with technological mitigation effects not yet fully materialized; 3) In terms of decoupling trends, the dominant decoupling state from 2006 to 2025 is weak decoupling (9 occurrences), with strong decoupling occurring only once in 2008 due to external shocks; the abnormally high decoupling index in 2022 reflects exceptional circumstances, suggesting that low-carbon transition stability still requires consolidation; 4) Multi-scenario prediction indicate that under the stringent low-carbon scenario with enhanced policy constraints, emissions will peak at 19.849 million tons in 2030 and then decline gradually, contrasting with the persistent growth trajectories under the baseline and moderate low-carbon scenarios.

The relative rate of change between tourist volume and energy intensity is the decisive factor for achieving the peak; only by simultaneously curbing tourist growth and reducing energy intensity can a trend reversal be realized. This study establishes a systematic analytical framework encompassing aggregate accounting, driver decomposition, and scenario simulation, providing quantitative decision-making references for the formulation of low-carbon tourism development policies at the provincial level.