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.