Objective: Previous studies have demonstrated that the mixed plantations of Cunninghamia lanceolata and Phoebe bournei can significantly enhance rhizosphere soil phosphorus bioavailability. Specifically, the rhizosphere soil of P. bournei within these mixed plantations serves as a critical hotspot for phosphorus activation, exhibiting notably higher levels of labile phosphorus, greater abundances of phosphorus-solubilizing functional genes, and increased diversity of phosphorus-solubilizing bacterial communities compared to both pure C. lanceolata plantations and the rhizosphere of C. lanceolata within the mixed stands. However, highly effective phosphorus-solubilizing bacterial strains with demonstrated plant growth-promoting capabilities have not yet been systematically isolated. Therefore, this study systematically isolated and screened phosphate-solubilizing and growth-promoting bacterial strains from the rhizosphere soil of P. bournei in mixed C. lanceolata–P. bournei plantation, and verified their growth-promoting effects on the Arabidopsis thaliana and one-year-old clonal seedlings of C. lanceolata, aiming to provide elite germplasm and a theoretical basis for developing tailor-made microbial phosphorus fertilizers suitable for acidic red soils in southern China. Method: Phosphate-solubilizing bacteria (PSB) were isolated from the rhizosphere of P. bournei on PVK (pikovskaya) selective medium and identified by 16S rRNA sequencing. Solubilizing zone diameter (D/d), available-P increment (Mo-Sb colorimetry), IAA (indole-3-acetic acid) production (salkowski method) and biofilm formation (96-well crystal-violet assay) were determined to preliminarily select ten highly efficient strains. These strains were co-cultured with A. thaliana on standard and low-P 1/2 MS plates to identify the most effective strain based on plant biomass. The optimal strain was further evaluated with potted C. lanceolata seedlings. Plant height, ground diameter, biomass, gas-exchange parameters and root architecture were measured to assess the growth promoting effect of phosphate solubilizing bacteria. Result: 1) A total of 18 PSBs were isolated from the rhizosphere of P. bournei in C. lanceolata and P. bournei mixed plantation, belonging to 11 genera, with Paenibacillus and Burkholderia as the dominant groups. 2) There was a significant difference (P<0.05) in the phosphate-solubilizin ability of 18 strains of phosphate solubilizing bacteria, among which the strain P8 released the highest amount of available P (1 176.36 mg·L^?1), but no there was positive correlation existed between the halo size of the phosphorus solubilizing zone and liquid solubilization. 3) All 18 strains of bacteria produced IAA (14.6–22.5 μg·mL^?1) and formed biofilms, with P10 having the highest IAA yield. 4) Under low-P conditions, strain P17 increased A. thaliana root biomass by 398.6%, markedly outperforming the full-P treatment. 5) Further pot experiments on Chinese fir showed that P17 raised the net photosynthetic rate, stomatal conductance and transpiration rate to (7.44±1.49) μmol·m^?2s^?1, (64.68±19.55) μmol·m^?2s^?1and (1.81±0.29) mmol·m^?2s^?1, respectively, which were all significantly higher than those of the control group (P<0.01), and P17 inoculation increased root surface area and root volume by 66.13% and 68.90% (P<0.01), and also enhanced plant height, ground diameter, and total biomass. Conclusion: In this study, 18 phosphate-solubilizing bacterial strains have been isolated from the rhizosphere soil of P. bournei in a mixed C. lanceolata–P. bournei plantation. Among them, a highly efficient phosphate-solubilizing Sphingomonas strain P17 is obtained. It can mobilize sparingly soluble P, secrete IAA to optimize root architecture and form robust biofilms for rhizosphere colonization. P17 establishes a positive “microbial activation–root absorption” feedback under P-limiting conditions, and markedly enhances photosynthetic efficiency and root volume. The P17 strain has excellent characteristics such as phosphorus solubilization, plant growth promotion, and adaptation to acidic red soil. It can be used as a core strain for developing specialized microbial P fertilizers for C. lanceolata, offering a new strategy to alleviate replant obstacles and improve P-cycling efficiency in southern plantation forests.

Objective: This study aims to clarify the compositional structure of medicinal plant resources in the Three-North Shelter Forest Project (TNSP, also known as the Great Green Wall Project) area, characterize species diversity with species richness, and reveal the distribution differences of medicinal plant resources among the three major “battle zones” and three types of regions (core battle zone, coordinated promotion zone, consolidation and expansion zone). Furthermore, this study identified hotspots for conservation and utilization, and selected typical medicinal plant resources suitable for development and utilization in each region, thereby providing a scientific basis and decision-making support for regional ecological management and collaborative promotion of the traditional Chinese medicine industry. Method: In this study, multi-source data was integrated to construct a medicinal plant inventory and its distribution database for the TNSP, and statistically analyze the characteristics of medicinal plant species richness at the levels of county-level administrative regions, the three major “battle zones”, and the three types of regions. The complementary algorithm and species richness ranking methods were employed to identify hotspots of medicinal plants suitable for development and utilization or in need of priority protection. Furthermore, typical medicinal plants were selected based on their distribution breadth and relevant authoritative inventories. Result: 1) There are 7 693 medicinal species in the TNSP (accounting for 45.5% of the total plant species in this region and 50.2% of the national total of medicinal plants). These plants include 1 745 endemic species, 174 national key protected wild medicinal plants, 279 threatened species, 1 820 medicinal plants for ecological engineering construction, 326 original plants of commonly used traditional Chinese medicinal materials, and 100 original plants of Dao-di herbs from their Dao-di producing regions. 2) The average medicinal plant species richness in counties is 431 ± 291. The high species richness areas are primarily concentrated in the Greater Khingan Range, Changbai Mountain, Taihang Mountain, Qilian Mountain, and Tian Mountains, while low medicinal species richness areas are mainly located in the Gashun Gobi, Qaidam Basin, Hexi Corridor, Haihe Plain, and Northeast Plain. 3) There is significant heterogeneity in the distribution of medicinal plant resources. Within three major “battle zones”, the Yellow River “Ji”-shaped bend battle zone has the highest species richness for both total medicinal plants and regionally unique medicinal plants, and Dao-di herbs and commonly used traditional Chinese medicines are concentrated here. In contrast, the Korqin and Hunshandake Sands elimination zone has relatively low species richness. Among three types of regions, the pattern of medicinal plant species richness is roughly as follows: coordinated promotion zone > core battle zone > consolidation and expansion zone. 4) A total of 115 hotspot counties were identified for the development and utilization of medicinal plants, and 143 hotspot counties were identified to be prioritized for protection. There were 70 counties overlapping between the two categories. 5) Based on the needs of ecological engineering construction and the development of the traditional Chinese medicine industry, a total of 28 typical medicinal plants suitable for development and utilization were selected by region, including 15 medicinal plants for ecological engineering construction and 14 original species of commonly used traditional Chinese medicine and Dao-di herbs. Conclusion: The medicinal plant resources in the TNSP are abundant but unevenly distributed. Therefore, it is recommended to implement differential resource protection and utilization strategies based on the identified hotspots of medicinal plants and a list of typical medicinal plants available for development and utilization. In the Yellow River “Ji”-shaped bend battle zone, the development of Dao-di herbs industry should be prioritized; in the Hexi Corridor-Taklamakan Desert perimeter battle zone, medicinal plants that can prevent wind and stabilize sand should be selected to construct ecological barriers; in the Korqin and Hunshandake Sands elimination zone, the application of local medicinal plants in ecological restoration should be strengthened; in the coordinated promotion zone, sustainable utilization under the principle of protection priority should be adhered to; and in theconsolidation and expansion zone, the upgrading of characteristic medicinal materials industry should be promoted. The above strategies may offer a decision-making reference for the high-quality coordinated development of ecology, economy, and society in the TNSP.

Objective: Traditional forest inventory methods are limited in accurately characterizing asymmetric crown growth. This study aims to develop multi-dimensional crown asymmetry indices using UAV-LiDAR point cloud data and to evaluate the effects of neighbor interactions on the degree of crown asymmetry. Method: The study was conducted in a Larix olgensis plantation in Mengjiagang Forest Farm, Jiamusi City, Heilongjiang Province. An UAV-LiDAR platform was used to acquire point cloud data. Following individual tree segmentation, crown parameters were extracted to construct asymmetry indices from three dimensions to quantify crown asymmetry. The one-dimensional crown asymmetry index (CAI1) was defined as the angle between the treetop and the centroid of the 3D convex hull of the crown. The two-dimensional index (CAI2) represented the deviation of the crown projection area from a standard circle. The three-dimensional index (CAI3) quantified the deviation of the actual 3D crown volume from an assumed ideal symmetrical geometry of tree crown. Subsequently, factors related to crown size, spatial structure, and neighbor competition were extracted. Correlation analysis and linear mixed-effects models (LMM) were employed to assess the influence of different neighbor characteristics on multi-dimensional crown asymmetry. Result: The results showed that crown size factors were all significantly negatively correlated with crown asymmetry indices, meaning that the degree of asymmetry decreased as crown size increased. Among the spatial structure indices, uniform angle index (W) and crowding (C) showed no significant effect on asymmetry (P>0.05). However, tree height and crown neighborhood comparison, as well as opening degree, were significantly correlated with all three asymmetry indices (P<0.01), directly driving crown shape development. Neighbor competition indices were very significantly positively correlated with CAI2 and CAI3, indicating that crown asymmetry was intensified with increasing competitive pressure, revealing the critical role of neighbor competition in driving crown asymmetry. Trees tend to expand their canopy preferentially towards more open spaces to avoid lateral competitive pressure from neighbors, leading to asymmetric crown development. Compared to CAI2 and CAI3, CAI1 values were more concentrated ( 0–0.12) and showed generally weaker correlations with tree size, spatial structure, and neighbor competition. LMM showed that crown size, spatial structure, and neighbor competition factors explained up to 65% of the variance in CAI3, substantially higher than the 19% explained for CAI2. Analysis of standardized fixed effect coefficients revealed that variation in crown asymmetry was primarily driven by neighbor competition, with variation in CAI3 resulting from the combined effects of both crown size and neighbor competition. Conclusion: Competition of trees for growing space and light resources is a key factor leading to asymmetric crown development. Neighbor competition plays a dominant role in driving variation in the CAI2 and CAI3 asymmetry indices. Correlation analyses between spatial structure factors and asymmetry indices indicates that, compared to the horizontal distribution pattern of trees, their size dominance relationships and vertical spatial competition have a more direct effect on crown asymmetry. The differential explanatory power of LMM for CAI2 and CAI3 variation confirms that a three-dimensional spatial perspective captures localized crown shape adjustments more effectively, revealing that the essence of tree interactions is competition for spatial niches.

Objective: This study aims to develop a novel method for estimating stand potential productivity based on a process-based model and optimization algorithm, thereby providing a scientific basis for site quality assessment and forest management. Method: The 3-PG_mix model was calibrated using continuous observation data from pure stands of Larix olgensis obtaied from China’s national forest inventory. The model was evaluated by the coefficient of determination (R²), mean absolute error (MAE), root mean square error (RMSE) and relative root mean square error (rRMSE). Two target scenarios were set: maximization of annual volume increment and 5-year periodic mean increment. A particle swarm optimization (PSO) algorithm was applied to estimate the maximum stand volume productivity and corresponding optimal forest density under five different site quality grades. Based on these results, the optimal diameter structure was derived using the scale and shape parameter models of the Weibull distribution. Result: 1) In the calibrated and validated data, the mean diameter at breast height (DBH), stem density, stand volume, and stem biomass of L. olgensis plantations simulated by the 3-PGmix model were consistent with the measured values in the plot, with R² values greater than 0.86 and rRMSE less than 16%. 2) At the base age of 30 years, the potential volume productivity of L. olgensis plantations at the maximum annual and periodic average growth increment for the five site grades ranged from 4.50 to 8.11 m³·hm^?2a^?1 and from 4.53 to 8.18 m³·hm^?2a^?1, respectively. 3) The number of diameter classes, which reached the potential productivity of accumulation, increased monotonically with stand age, and the Shannon index of diameter classes exhibited an increasing trend after a fluctuating pattern at the early growth stage. The two indicators showed higher values under better site quality conditions. Conclusion: The integration of the process-based 3-PG_mix model and the PSO algorithm enables effective estimation of volume potential productivity, compensating for the limitations of traditional methods that do not account for self-thinning and climatic factors, and thereby provides a new approach for potential productivity estimation of forest stands.

Objective: The “Three-North” region is the main battlefield of China’s ecological restoration efforts. Over the past half century, a series of large-scale ecological projects, represented by the “Three-North” Shelterbelt Program, have been implemented, and remarkable progress has been achieved while new challenges, such as intensified climate change and growing human–environment conflicts, are also confronted. In 2015, the United Nations proposed the sustainable development goals (SDGs) framework toward 2030, and thus it is highly meaningful to evaluate the sustainable development of the “Three-North” region from this perspective. Method: We localized and reconstructed global SDG indicators using remote-sensing-based approaches to develop a computable and comparable sustainable development assessment system tailored to the “Three-North” region. The relative change rates (slope/mean) combined with the Mann–Kendall significance test were used to to unify the quantification of indicator trends, achieving indicator quantification based on spatiotemporal continuous remote sensing data products. The region’s “best achievable performance” method was used to determine the target values and conduct a sustainable development assessment towards the 2030 goal. Result: A localized SDG indicator system was constructed grounded in relevance, feasibility, and observability. A unified method for indicator quantification and integration was established using big earth data. Results showed that the “Three-North” region had an overall composite score of 85, displaying a spatial pattern of “higher in the east and lower in the west”. At the goal level, SDG 15 and SDG 13 performed best, with an average score of around 87 each, reflecting significant progress in ecosystem conservation, restoration, and climate action. SDG 6 had the lowest score, at only 82, indicating that water resource management remained a major bottleneck for sustainable development. Scores at the prefectural and county levels were generally similar, though the finer county-level results highlighted pronounced intra-regional disparities. Conclusion: Overall, the remote-sensing-based sustainable development assessment system developed in this study provides an operational tool for evaluating the sustainability progress of large-scale ecological restoration areas. With capabilities for dynamic updates and cross-scale application, it offers an important reference for systematically tracking how far the “Three-North” region is from achieving the 2030 sustainable development goals.

Objective: To quantify the potential uncertainty of carbon sequestration estimation caused by the neglect of important factors such as site quantity and stand characteristics in previous studies, the present study proposes a simple and effective method for estimating carbon sequestration potential at the management unit scale that is inspired from the theory of forest resource valuation, aiming to provide some insights on the temporal-spatial configuration of various forest management prescription at the management unit scale under the multifunctional forest management concept. Method: Based on the forest resource survey data of Mao’ershan Experimental Forest Farm in 2022, an adjustment coefficient (K) for stand comprehensive condition was constructed based on the site quality, mean diameter at breast height (DBH) and stand density at the sub-compartment scale using a continuous multiplication strategy. The carbon sequestration potential at the management unit scale was accurately estimated by combining the proposed index K with stand growth process tables for various forest types, as well as the datasets of biomass expansion factors and carbon content of different organs for each forest type. Result: 1) The mean DBH adjustment coefficient ($ {k}_{1} $), stand density ($ {k}_{2} $), site quality adjustment coefficient ($ {k}_{3} $) and total adjustment coefficient (K) in the study area were 1.34±0.52, 0.90±0.45, 0.91±0.45 and 0.89±0.48, respectively. Meanwhile, forest types had significant impacts on the adjustment coefficients (P<0.01), with natural coniferous mixed forests having the greatest K values (1.40), and Pinus koraiensis plantation having the smallest (0.51). 2) The determination coefficient between the estimated unit area volume of the adjusted forest stands and the actual survey values significantly increased by 1.23 times on average (from 0.284 to 0.634) compared with that between the estimated unit area volume of the non-adjusted forest stands and the actual survey values, among which Populus davidiana plantation had the largest increase (10.11 times), while the natural P. davidiana-B. platyphylla forest had the smallest increase (83%). 3) During 2022—2050, the average carbon sequestration of arbor forests in the region was 0.38 t·hm^?2a^?1, and gradually decreased with forest age. Among them, the carbon sequestration rates of natural mixed coniferous forest, natural mixed coniferous-broadleaved forest and L. olgensis plantation were relatively high (>1.00 t·hm^?2a^?1), and those of natural soft-hard broadleaf forest and Pinus koraiensis plantation were relatively lower (< 0.30 t·hm^?2a^?1). Conclusion: The adjustment coefficient for stand comprehensive condition proposed in this paper, namely combining the proposed adjustment coefficient, forest resource planning data and the stand growth process tables together, can accurately estimate the carbon sequestration potential at the management unit scale.

Objective: Existing tree counting methods based on unmanned aerial vehicle (UAV) imagery typically require a large amount of annotated data. To address the challenge of tree counting under limited annotation conditions, a tree counting method based on few-shot learning is proposed. Method: The publicly available TreeAI dataset was integrated with orthophotos of trees collected from the southern edge of the Horqin Sandy Land in Inner Mongolia Autonomous Region, Huangfengqiao Forest Farm in Hunan Province, and Camellia oleifera plantations in Jiangxi Province. Point and ellipse annotations were jointly employed for data labeling to construct a UAV-based tree counting dataset (UAV-TC) containing tree species such as Cunninghamia lanceolata, Pinus sylvestris var. mongolica, Camellia oleifera. The tree counting task was subsequently formulated as a few-shot regression problem. A small number of representative samples were used to guide the model in learning structural similarity features of tree objects, thereby reducing its dependence on phenotypic characteristics specific to individual tree species. Accordingly, a few-shot learning-based tree counting model, named FSTC-Net, was developed. The proposed model consists of a species-independent multi-scale feature extraction network and a density map prediction module, enabling robust counting of multiple tree species in complex environments. Specifically, the feature extraction network incorporated MixNet-L with a feature pyramid structure to enhance multi-scale feature representation of tree targets. The density map prediction module replaced conventional direct feature map inputs with correlation maps generated from sample and image features, thereby enabling cross-species feature alignment and similarity matching. In addition, a random scale augmentation strategy and an adaptive loss function were introduced to improve model generalization and counting accuracy under few-shot conditions. Result: Experimental results demonstrated that FSTC-Net achieved accurate counting of Cunninghamia lanceolata, Pinus sylvestris var. mongolica, Camellia oleifera in the test set, with a coefficient of determination (R²) of 0.949 9. The corresponding mean absolute percentage error (MAPE), mean absolute error (MAE), and root mean square error (RMSE) values were 3.54%, 26.71 trees, and 37.60 trees, respectively. Ablation experiments showed that after integrating the MixNet-L and RoI Align modules into the FamNet model, the R² of the model counting increased by 0.0308 and 0.0329, respectively, while the MAPE was reduced by 0.64% and 0.78%, respectively. When both MixNet-L and RoI Align modules were integrated into the FamNet model, the best performance in terms of R² and MAPE was achieved. Further comparisons with mainstream models, including T-Rex, T-Rex2, and FamNet, demonstrated that FSTC-Net outperformed these methods in terms of both error control and result stability. Specifically, the R² values of FSTC-Net were 0.0854, 0.0493, and 0.0413 higher than those of T-Rex, T-Rex2, and FamNet, respectively, whereas the corresponding MAPE values were reduced by 3.12%, 2.35%, and 1.73%, respectively. In addition, analysis under different canopy densities revealed that although the counting error of FSTC-Net increased in high-canopy-density mixed coniferous and broad-leaved forests, the error remained within an acceptable range. Conclusion: The experimental result has verified the effectiveness and superiority of FSTC-Net for tree counting tasks, and it can provide reliable technical support for UAV-assisted forest resource monitoring.

Objective: This study aims to reveal the responses of dominant afforestation tree species in the semi-arid northern region of China to the northward shift of the 400 mm isoline by constructing an afforestation optimization framework that integrates temperature thresholds, root stratification, and risk zoning, thereby providing scientific support for ecological restoration projects under the influence of climate change. Method: A kernel normalized difference vegetation index (kNDVI) time series was constructed based on MOD13Q1 v6.1 data (2000–2024). The Theil-Sen slope was combined with Mann-Kendall (MK) test to quantify the northward migration characteristics of the 400 mm isoline. Random forest and partial dependence plot analyses were employed to extract the optimal photosynthetic temperature windows (21.2–22.3 ℃) of the dominant afforestation tree species of Pinus tabuliformis, Pinus sylvestris var. mongolica, and Caragana korshinskii in semi-arid northern China. The attribution of layered soil moisture content and cross-correlation function were used to calculate the lag response time of the dominant tree species to precipitation and their temperature sensitivity, which were then integrated with the precipitation-belt migration rates to construct the forestry risk index (RFI). Result: 1) The centroid of the 400 mm isoline significantly shifted northward at a rate of 3.89 km·a^–1, resulting in a 119.7% expansion of candidate suitable areas for P. tabuliformis, a 27.5% expansion for P. sylvestris var. mongolica, and an 8.1% contraction for C. korshinskii. 2) The optimal temperature zones for the kNDVI index of the dominant tree species were 23.1–23.8 ℃ for P. tabuliformis, 19.4–19.5 ℃ for P. sylvestris var. mongolica, and 23.0–23.6 ℃ for C. korshinskii. Combined with partial dependence curve analysis, it was found that when temperatures exceeded 25 ℃, the kNDVI index declined by ?11.03%, ?10.54%, and ?13.55%, respectively. 3) The spatial partitioning accuracy of RFI reached 89%, identifying high-risk areas, moderate-risk areas, and low-risk areas accounting for 12.3%, 27.5%, and 60.2% of the total study area, respectively. Subsequently, differentiated afforestation strategies and recommendations were proposed for different risk zones. Conclusion: This study has clarified the sensitivity of P. tabuliformis and P. sylvestris var. mongolica to high temperatures and soil moisture in 0–1 m layer, as well as the drought-resistance characteristics of C. korshinskii conferred by its deep root system. A differentiated regional afforestation strategy is constructed based on the “temperature threshold-root stratification-risk zoning” framework, providing scientific basis and practical pathways for ecological restoration project construction and forest regeneration in the semi-arid northern region of China.

Objective: This study aims to explore functional endophytic bacteria resources from Vernicia fordii (tung tree), screen efficient phosphate-solubilizing strains, so as to provide a scientific basis for developing growth-promoting bacterial agents for plants in rocky desertification regions. Method: Endophytic bacteria were isolated from roots, stems and leaves of healthy tung trees. Phosphate-solubilizing strains were obtained through primary screening by phosphate-solubilizing halo and rescreening by molybdenum-antimony anti-colorimetric method. Strains were identified by 16S rRNA gene sequencing. Their nitrogen-fixation, IAA production, and antagonism against Fusarium oxysporum were analyzed. Pot experiments were conducted to verify their effects on growth and nutrient accumulation in V. fordii/V. montana seedlings treated with phosphate solubilizing bacteria. Result: A total of 31 species of fungi and bacteria were isolated. Burkholderia cepacia (RP2) showed the strongest phosphate-solubilizing capacity (459.64 mg·L^–1), with high nitrogen-fixation (53.12 mg·g^–1) and IAA production (97.54 μg·mL^–1). Inoculation with RP2 increased plant height and shoot fresh weight of tung tree by 68.5% and 98.2%, respectively, and root phosphorus content by 88.6%. Serratia marcescens (RP3) exhibited both phosphate-solubilization (399.10 mg·L^–1). RP2 and Bacillus subtilis (SP4) had both phosphate solubilizing and antagonistic abilities against Fusarium oxysporum. Conclusion: Two multifunctional growth-promoting strains, RP2 and RP3, have been identified from tung tree for the first time. They significantly promote the growth of Vernicia species. This study provides core resources for developing green and environmentally friendly growth promoting agents.

Objective: This study aims to elucidate the physiological and molecular regulatory effects of prolonged subculture on Picea abies embryogenic callus, and reveal the underlying mechanisms of its declining somatic embryogenic potential, so as to provide a theoretical basis for optimizing the somatic embryogenesis system and facilitating large-scale clonal propagation of conifers. Method: In this study, embryogenic callus from different P. abies cell lines with varying subculture generations was subjected to long-term subculture. Histocytological observations were performed, and the correlations between endogenous hormone content, gene expression patterns, and differentiation capacity were comprehensively analyzed. Result: 1) Analyses of histocytology and differentiation capacity indicated that as the number of subculture generations increased, the embryogenic callus of P. abies exhibited structural compaction and browning, accompanied by a progressive loss of embryogenicity. There were significant differences in the decline of differentiation capacity among the four cell lines, while the differentiation capacity of all four cell lines exhibited a unimodal pattern of first increasing and then decreasing. Among them, cell line 32-29 retained the highest potential for sustained differentiation. 2) Endogenous hormone analysis revealed that the dynamic changes of cytokinin (CTK) and gibberellin (GA₃) were consistent with the changes in differentiation rates of embryogenic callus, initially rising before falling. There was a significant positive correlation between the two, indicating that these hormones might play an important role in sustaining embryogenic potential. The content of indole-3-acetic acid (IAA) remained at a relatively low level with a transient increase followed by a slow decline, while the content of abscisic acid (ABA) exhibited a general decreasing trend. 3) An integrative analysis of gene expression level, somatic embryo number, and endogenous hormone content revealed that the expression levels of genes ARF6, BLH1, GH3.6, and SCL1 were significantly downregulated with increasing number of subcultures, and were significantly positively correlated with the number of differentiated somatic embryos, indicating positive regulators of somatic embryogenesis. On the other hand, the expression levels of genes ZAT9, WHY1, ZHD1, SCR, and AP2L2 were significantly upregulated with increasing number of subcultures, indicating potential negative regulatory factors. Furthermore, the expression levels of these key genes were closely related to the cytokinin (CTK) and gibberellin (GA₃) hormone signaling pathways. There was a significant positive correlation between ABA levels and WHY1, BLH1, SCR, SCL1, and ZHD1 expression, suggesting a co-regulatory network governing callus differentiation and development. Conclusion: In summary, the decline in somatic embryogenic potential of P. abies embryogenic callus is a biological process co-regulated by weakened cell division, an imbalance of endogenous hormone homeostasis, and the aberrant expression of key genes in somatic embryogenesis.

Objective: Under laboratory conditions simulating roadside NO₂ exposure, this study investigated the leaf morphological, physiological, biochemical, and metabolomic responses of the urban roadside greening plant Bougainvillea × buttiana ‘Miss Manila’ to long-term NO₂ exposure, aiming to clarify the mechanisms underlying plant responses to NO₂ and to provide a theoretical basis for the precise selection and management of urban greening plants. Method: The common ornamental cultivar B. × buttiana ‘Miss Manila’ was used as the experimental material. In a fully automated closed fumigation system, plants were exposed to three treatments: clean air as the control (CK), class I NO₂ concentration (T1, 0.02 μL·L^?1), and class II NO₂ concentration (T2, 0.04 μL·L^?1). During the treatment period, plant phenotype, photosynthetic parameters, and metabolic regulation related indicators were dynamically monitored. After exposure, leaf nitrogen metabolism, microstructure, and metabolomic profiles were comparatively analyzed. Result: 1) With prolongation of fumigation time, NO₂ significantly inhibited the growth and photosynthetic rate of B. × buttiana ‘Miss Manila’ and altered the contents of physiological regulatory substances. Under the class II concentration, the leaf integrity index and the activities of superoxide dismutase and catalase decreased by 50.14%, 31.58%, and 46.81%, respectively, whereas the contents of malondialdehyde, proline, and soluble protein increased by 43.50%, 149.02%, and 22.72%, respectively. 2) Compared with the control, T2 treatment significantly reduced leaf chlorophyll content, net photosynthetic rate, and photochemical efficiency, damaged the leaf cuticular structure, disrupted epidermal cells and chloroplast structure, significantly enhanced the activities of nitrogen metabolism-related enzymes, and increased oxidized nitrogen content by 158.43%. 3) After conducting correlation analysis and cluster analysis on the 22 selected indicators, two major groups were divided on their basic response patterns: the first group comprised chlorophyll fluorescence parameters and antioxidant enzyme indicators, and the second group comprised nitrogen forms and nitrogen metabolism-related enzyme indicators. Compared with the control, the overall response trend of B. × buttiana ‘Miss Manila’ under T1 and T2 treatments was similar, but their temporal trajectories were non-linear. 4) NO₂ stress induced systemic metabolic responses, with significant changes in the contents of multiple metabolites, including L-leucine and α-linolenic acid. These changes mainly involved metabolic pathways of amino acids, α-linolenic acid, and betalain. KEGG enrichment analysis showed that metabolic pathways such as betalain biosynthesis and glutathione metabolism had relatively high enrichment factors, and the substrate content in the corresponding pathways significantly decreased, showing dose-dependent responses. Conclusion: Inhibition of key metabolite synthesis and disruption of cellular structure may be important causes of the reduced resistance in B. × buttiana ‘Miss Manila’ under NO₂ stress, and NO₂ exposure markedly alters its metabolic profile. Overall, high-concentration and long-term NO₂ exposure have stronger negative effects, whereas short-term exposure to low-concentration NO₂ shows a certain low-dose stimulatory effect. Therefore, in roadside environments with long-term high NO₂ concentrations, B. × buttiana ‘Miss Manila’ should be planted in combination with other plant species rather than as a single dominant species.

Objective: This study aims to systematically analyze the emission patterns of volatile aroma components in Paeonia suffruticosa ‘Luoyang Hong’ during different flowering developmental stages and diurnal variations, and investigate the expression levels of scent-related genes, so as to provide theoretical support for improving the ornamental quality and industrial application of P. suffruticosa ‘Luoyang Hong’ as a New Year flower. Method: In this study, potted and field-grown P. suffruticosa ‘Luoyang Hong’ plants were used as materials. Dynamic headspace adsorption combined with gas chromatography-mass spectrometry (GC-MS) was employed to analyze the aroma components at seven different flower developmental stages (color exposure stage, blooming stage, initial flowering stage, half opening stage, full blooming stage, initial decay stage, decay stage), as well as the diurnal variation patterns (from 06:00 to 18:00) at the full blooming stage, respectively. Result: 1） The results showed that 43 volatile components (in potted plants) and 30 volatile components (in field-grown plants) were identified in P. suffruticosa ‘Luoyang Hong’, including 8 benzenes, 5 alcohols, 1 phenol, 3 aldehydes, 2 terpenes, 6 esters, and 27 hydrocarbons. 2） The total emission of floral aroma exhibited a unimodal pattern of first increasing and then decreasing during the flowering process. The total emission reached the peak at the half-opening stage in potted plants, while it peaked at the full blooming stage in field-grown plants. During different time of periods in a day, the volatile emission of potted plants gradually increased over time, reaching the peak between 15:00 and 18:00. In contrast, that of field-grown plants showed a trend of first increasing and then decreasing, peaking between 09:00 and 12:00. 3） The expression patterns of PsTPS and PsPAL genes in the floral scent biosynthesis pathway were detected using qRT-PCR technology. It was found that during different flowering stages, the expression level of PsTPS in potted plants showed a similar trend to that of linalool content, while its expression level in field-grown plants exhibited a similar trend to that of α-farnesene content. The expression level of PsPAL in potted and field-grown plants was consistent with the content variation trends of m-xylene and phenylethyl alcohol, respectively. Additionally, at different time of periods in a day, the expression levels of PsTPS and PsPAL were similar to the content variation trends of α-farnesene and m-xylene, respectively. Conclusion: This study reveals the emission pattern of the floral scent of P. suffruticosa ‘Luoyang Hong’ from two perspectives: volatile aroma components and gene expression, which has significant application value for the development of the forcing-flowering industry of P. suffruticosa ‘Luoyang Hong’.

Objective: This study aims to reveal the spatiotemporal distribution relationships between forest and grassland fires and meteorological factors in Sichuan Province. It identifies the key meteorological factor combinations driving fire distribution, defines Foehn-prone periods, and analyzes the underlying atmospheric circulation mechanisms, providing a theoretical reference for developing scientific fire prevention strategies. Method: Based on MODIS active fire data and ERA5 meteorological data from 2005 to 2024, combined with land use and topographical data, the tools such as ArcGIS 10.8.2, Origin 2024, Excel 2021, and SPSS 27 were employed. First, the forest and grassland were distinguished from non-forest and non-grassland areas via land use data and fire points were extracted. Then, statistical analyses are conducted to characterize the distribution of fire occurrence counts at the monthly and spatial scales, respectively. Subsequently, the monthly spatial distributions of wind direction, average wind speed, average precipitation, average relative humidity, average temperature, and temperature differences between adjacent months were analyzed. Finally, the correlation between meteorological factors and fires was comprehensively explored, and thereby its accuracy was verified. The Foehn-prone seasons in Sichuan Province were clarified by generalizing judgment criteria and coarsening the time scale, and determining monthly-scale Foehn in Sichuan Province. Result: 1) Approximately 86.9% of forest and grassland fires in Sichuan Province occurred from January to May and in December (winter and spring). Spatially, about 97.66% of the Province’s total fires were concentrated in southwest Sichuan (Panzhihua City, Liangshan Yi Autonomous Prefecture) and northwest Sichuan (Ganzi Tibetan Autonomous Prefecture, Aba Tibetan and Qiang Autonomous Prefecture), with a higher frequency in southwest Sichuan than in northwest Sichuan. 2) Comparative analysis showed that across different regional and temporal combinations in Sichuan Province, only the winter and spring seasons in southwest and northwest Sichuan exhibit a distinct meteorological pattern characterized by high average wind speed, low precipitation, low relative humidity, significant temperature rise, and the dominance of southwesterly and southerly winds. 3) The number of fires was positively correlated with average wind speed, the monthly count of southwesterly winds, and the monthly count of southerly winds (ρ=0.923^**, P<0.001; ρ=0.930^**, P<0.001; ρ=0.804^**, P=0.002). Conversely, it was negatively correlated with average temperature, average precipitation, and average relative humidity (ρ=?0.643^*, P=0.024; ρ=?0.809^**, P=0.001; ρ=?0.979^**, P<0.001). 4) The winter and spring seasons in southwest and northwest Sichuan satisfy the criteria for “Foehn seasons”. Conclusion: This study reveals the spatiotemporal pattern of forest and grassland fires in Sichuan. They are temporally concentrated in winter and spring and spatially focused in the southwest and northwest regions (with higher frequency in the southwest). The winter and spring periods of southwestern and northwestern Sichuan have be defined as “Foehn seasons”. The study concludes that the specific meteorological combination—dominated by southwesterly and southerly winds, high wind speed, low precipitation, low humidity, and significant warming, coupled with frequent Foehn events, constitutes the key driver for the concentration of fires.

Objective: The moisture sorption isotherms and dimensional change ratio in sectional area and the longitudinal, radical and tangential directions of tracheid and fusiform wood ray in earlywood (EW) and latewood (LW) in the same growth ring of Pinus massoniana (masson pine) were real-timely and synchronously investigated. This study aims to reveal the wet swelling-dry shrinkage behavior of EW and LW, providing an important theoretical basis for guiding the efficient processing and utilization of resin-containing pine wood. Method: The same growth ring of masson pine was used as the research object. The experiment was conducted in the range of 0–98% relative humidity by using Dynamic Vapor Sorption Resolution combined with a video Dino X Lite Digital Microscope. During the adsorption-desorption period, the moisture sorption isotherm and dimensional change ratio in sectional area and the longitudinal, radical and tangential directions of tracheid and fusiform wood ray were synchronously measured. During the period of constant equilibrium moisture content (EMC), whether there was hysteresis between dimensional change ratio and EMC or not was investigated. In addition, the resin content, chemical components, microfibril angle, and porosity of EW and LW were tested using anhydrous ethanol extraction method, National Renewable Energy Laboratory method, X-ray diffractometer, and automatic mercury porosimeter, respectively. Result: 1) Compared to EW, LW had a higher resin content, cellulose and hemicellulose content, as well as lower microfibril angle, porosity and lignin content. 2) Under any RH condition, the EMC of EW was greater than that of LW. At 98% RH, the EMC of EW and LW was 17.65% and 16.36%, respectively. 3) The absolute hysteresis of EW and LW increased first and then decreased with the increase of RH, with 60% RH as the inflection point. Compared with EW, LW had a more obvious absorption hysteresis phenomenon. 4) The dimensional change ratio of tracheid and fusiform wood ray in EW and LW increased/decreased with the increase/decrease of RH. The area change ratio of tracheid was the largest. At 98% RH, the area change ratio of tracheid in EW and LW were 1.117 and 1.181, respectively. Regardless of the tangential or longitudinal direction, the relationship of the dimensional change ratio of fusiform wood ray between EW and LW was opposite to that of tracheid. 5) The wet swelling hysteresis of tracheid and fusiform wood ray in EW and LW first increased and then decreased with the increase of RH, with 60% RH as the inflection point, which was consistent with the change pattern of the absolute hysteresis. Compared with EW, LW tracheid and fusiform wood ray exhibited more pronounced hysteresis in wet swelling. 6) The dimensional change ratio of tracheid and fusiform wood ray in EW and LW during the EMC constant period was four orders of magnitude lower than that in the moisture adsorption-desorption period. Conclusion: Compared to EW, the resin content has a greater effect on the water vapor isothermal sorption behavior of LW. The effect of hemicellulose on absolute hysteresis is greater than that of lignin. The dry shrinking/wet swelling behavior of fusiform wood ray is inhibited by the surrounding tracheid. Compared with EMC, the porosity has a more significant effect on the wet swelling hysteresis. The time point at which the parameters of tracheid and fusiform wood ray in EW and LW reach the equilibrium content is consistent with the time point at which the dimensional change ratio is constant, that is, there is no time hysteresis.

Objective: To address critical bottlenecks of timber wall systems in severe cold regions, including inadequate thermal performance (e.g., heat transfer coefficient K=0.692 W·m^?2 K^?1 in light wood frame walls) and significant sound/thermal bridging effects, combined with practical requirements of current energy efficiency and fire safety codes for wall thickness, this study aims to elucidate thermal transfer failure mechanisms in light wood frame and cross-laminated timber (CLT) walls and proposes synergistic optimization strategies for integrated thermal and acoustic performance, thereby advancing high-performance wall solutions for prefabricated buildings in harsh climates. Method: The calibrated hot box method was used to examine thermal resistance (R) on 11 full-scale wall specimens (1.5 m × 1.5 m), and conduct theoretical calculations of thermal performance. Based on the prior airborne sound insulation research data, this study compared and analyzed the impact of staggered design of wood/light steel studs, innovative sound insulation cushion layer [adding rubber pads between wood frames and oriented strand boards (OSB), and adding compressed glass wool strips between light steel frames and gypsum boards (GB)], and composite configurations (CLT walls sheathed with wood frames and filled with glass wool) on the thermal performance of the wall and improves efficiency. Result: The thermal and acoustic performance was synergistically improved. Light wood frame walls with staggered wood studs reduced K to 0.251 W·m^?2K^?1, which is 63.7% lower than that of conventional light wood frame walls. The heat transfer coefficient of light steel frame walls with staggered steel studs was reduced to 0.524 W·m^?2K^?1, which is 47.7% lower than that of the light steel keel composite wall. The heat transfer coefficient of the CLT composite walls (wood frame-sheathed + glass wool) attained K=0.587 W·m^?2K^?1, which is 40.2% lower than that of single-layer CLT walls. Compared with the CLT single-layer wall with only an increase in the number of layers, the CLT composite wall achieved comprehensive breakthroughs in increasing the wall thickness (155 mm vs. 175 mm) and surface density (70.0 kg·m^?2 vs. 91.0 kg·m^?2), and improved the weighted sound insulation (40 dB vs. 37 dB) and heat transfer coefficient (0.587 W·m^?2K^?1 vs. 0.623 W·m^?2K^?1), meeting the dual requirements of thermal and sound insulation performance for building walls. Except for light steel frame walls due to the high heat loss caused by the nail node thermal bridge (penetrating the cladding panel), the theoretical K calculations showed <15% error for other walls, which has high calculation efficiency and accuracy. Conclusion: Sound/thermal bridging in studs critically constrains wood frame wall performance. Staggered framing disrupts vibration transmission paths and elongates thermal conduction channels, mitigating bridging effects. The optimized light wood frame walls with staggered wood studs (208 mm thick, 39.1 kg·m^?2) overcome the insulation-soundproofing trade-off, meeting severe cold region requirements. For single-layer CLT walls, the technical measures of sheathing with light wood frame filled with glass wool proves more efficient than increasing lamina layers.

Objective: The existing bamboo strip surface defect detection methods on bamboo strips have problems such as large model parameters and poor performance in detecting small-scale defects, making it difficult to balance the dual requirements of high-precision and high real-time requirements in industrial scenarios. To address the problems, this paper proposes FCHM-DETR, a lightweight end-to-end detection model, for improving the comprehensive performance of bamboo strip surface defect detection. Method: Based on the RT-DETR network, a lightweight backbone Faster-CGLU was designed by integrating part convolutional and gated linear units (CGLU) to enhance the fusion capability of local and global features while reducing computational complexity. A spatial feature reconstruction pyramid network CGRFPN was constructed, which was combined with rectangular a self calibration module (RCM) and a dynamic interpolation fusion (DIF) mechanism to optimize the multi-scale feature fusion effect and improve the model's spatial perception ability for defects. A Haar Wavelet Downsampler was introduced to achieve efficient compression of feature maps through frequency-domain feature recombination, while fully retaining high-frequency detail information such as defect edges and texture mutations. In addition, we proposed an MPDIoU loss function, which improved the regression accuracy of defect bounding boxes and the convergence efficiency of the model by explicitly optimizing the distance constraints of bounding box diagonal corner points. Ablation experiments and comparative experiments with mainstream models were carried out on a dataset covering six common types of bamboo strip surface defects, including black knot, wormhole, mildew, crack, residual bamboo yellow and residual bamboo green, to verify the effectiveness of each module and the comprehensive performance of the proposed model. Result: The FCHM-DETR model achieved a mAP50 of 94.7%, which was 3.7% points higher than that of the baseline model RT-DETR-r18, with a significant performance improvement in detecting small-scale, low-contrast defects such as wormholes and cracks. Meanwhile, the parameter count and FLOPs of the model were reduced by 30.6% and 35.6% respectively compared with the baseline, and its inference speed reached 355 FPS, which can fully meet the frame rate requirements of real-time detection in industrial scenarios. Compared with mainstream defect detection models including YOLOv10m and Faster R-CNN, FCHM-DETR achieved a superior balance among three core dimensions of detection accuracy, lightweight level and inference speed, with outstanding comprehensive performance advantages. Conclusion: FCHM-DETR effectively breaks through the core technical bottlenecks of existing bamboo strip defect detection methods, and realizes the synergistic improvement of detection accuracy and industrial deployment adaptability. It can provide an end-to-end automated defect detection solution for the bamboo processing industry.

Objective: This study aims to address the issues of excessive reliance on complex and time-consuming outdoor experiments in the design and improvement of Camellia oleifera vibration harvesters, as well as the low simulation accuracy of traditional simulation models due to ignoring the mass of fruit-bud-leaf. A distributed mass based method for constructing a vibration model of C. oleifera trees was proposed-bud-leaf under vibration excitation, and to provide a theoretical basis for optimizing the harvester operational parameters. Method: First, statistical analysis was used to determine the distribution patterns of the number and mass of fruit-bud-leaf on the fruiting branches, and their total mass was applied as distributed mass to the fruit-bearing branches, thereby constructing a vibration model with fruit-bud-leaf. Next, hammer impact tests were conducted to obtain the natural frequencies of the trees, and vibration response tests were carried out to measure the acceleration at different positions of the trees. The test results were compared with simulation results under corresponding conditions to validate the accuracy of the model. Finally, based on the validated model, harmonic response analysis and field picking tests were conducted. By simulating the harmonic excitation response of trees under different excitation positions, the difficulty of fruit detachment was analyzed; through spectrum analysis, the optimal excitation frequency range for the harvesting device was determined. The best picking method was verified through field picking tests. Result: 1) Modal analysis and impact hammer test results showed that the first 15 natural frequencies simulated for by the C. oleifera tree model with fruit-bud-leaf were basically consistent with the impact hammer test results, with an average error of 6.64%. Compared with the tree model without fruit-bud-leaf, the average simulation error was reduced by 78.94%. 2) Transient analysis and vibration response test results indicated that the simulated acceleration values at 16 measurement points were in good agreement with the test acceleration values. The average values of the error, correlation coefficient, and acceleration ratio between the two were 24.06%, 0.85, and 1.03, respectively. Additionally, the amplitude of acceleration increased gradually along the branches from the bottom to the top with frequency. 3) Harmonic response analysis and field picking test results indicated fruits were more easily detached when the excitation force was applied to lateral branches and the excitation frequency ranged from 11.83 to 13.97 Hz. Conclusion: This paper establishes a vibration model for C. oleifera trees based on the mass distribution patterns of fruit-bud-leaf, effectively addressing the issue of low simulation accuracy in traditional models caused by neglecting the mass of fruit-bud-leaf. This model significantly improves the simulation accuracy. Furthermore, through harmonic response analysis and field picking tests, the excitation method for lateral branch harvesting of C. oleifera and the optimal excitation frequency range are determined. The research findings not only provide important theoretical guidance for the design and parameter optimization of C. oleifera harvesters but also offer a new method for constructing dynamics models for other forest fruit.

Objective: This paper aims to explore the relationship between structural parameters and the stability, safety, and operational performance of traditional transplanting machines by combining finite element simulation and multibody dynamics analysis, so as to further enhance the performance of traditional tree transplanting machines in southern hilly and mountainous environments. Method: The RecurDyn multibody dynamics simulation software was used to dynamically analyze the tracked walking chassis, determine the adjustable track width range, and ensure the stability of the transplanting machine when operating in hilly and mountainous areas. In terms of the lifting device, the ADAMS dynamics software was employed to analyze the forces at various hinge points of the lifting boom, providing parameters for static analysis. The ANSYS static software was used to determine the optimal design parameters for the lifting boom under maximum stress conditions, ensuring the reliability and lifting capacity of the transplanting machine during lifting operations. For the torsional vibration excavation device, the ABAQUS simulation software was used to analyze the cutting soil dynamics of the shovel. The three optimal working parameters of the seedling torsional vibration digging device were determined, namely a vibration frequency (d₁) of 30 Hz, a vibration amplitude (d₂) of 7 mm, and a cutting speed (d₃) of 0.3 rad·s^-1. Result: Simulation results showed that the transplanting machine with an adjustable track width increased the maximum overturning angle of 16.7% compared to the original prototype, improving the lateral stability and flexibility of the transplanting machine in forest environments. After adopting the optimal cutting parameters for the excavation device, the cutting resistance was reduced by 24.41% compared to the initial parameters. The maximum equivalent stress of the lifting boom after structural parameter optimization decreased by 9.2%, improving the structural strength and reducing design redundancy. Field tests on driving performance showed that the transplanting machine exhibited good stability on slopes with θ ≤ 20° without tipping or slipping, and with the adjustable track width, no tipping occurred on a slope of θ = 30°, which was consistent with the simulation results. Field operation performance tests using the optimal parameters obtained from simulations showed that the transplanting machine took 64.1 seconds to dig up trees with a diameter at breast height (DBH) of 5–10 cm and 126.4 seconds for trees with a DBH of 10–20 cm. Additionally, the soil balls of the seedlings, after being lifted and bundled by the transplanting machine, were suitable for short-distance transportation. Conclusion: The experimental results confirm that the transplanter meets all performance requirements and is capable of fulfilling tree transplantation needs in hilly and mountainous terrain, providing a practical reference for tree-digging operations in southern hilly and mountainous areas.

Objective: This study aims to design and validate a novel DBH measurement device based on high-performance flexible strain sensors, which can be used for rapid, convenient, high-precision, non-invasive tree DBH measurement suitable for long-term in-situ monitoring. Method: The device mainly consists of three components: the core sensing unit is a flexible strain sensor whose conductive channel is constructed via a specific composite process using multi-walled carbon nanotubes (MWCNTs) and Ecoflex elastomer, operating on the principle of regular resistance change in response to applied strain (stretching caused by trunk circumference variation); a flexible connector, designed with compatible materials, is used to stably, tightly, and non-destructively wrap and fix the sensor around the trunk surface, ensuring good conformity and accommodating irregular surfaces and growth changes; peripheral acquisition circuitry is responsible for real-time acquisition, conditioning, and digitization of the sensor's resistance change signal. Result: To evaluate the performance of the device, a systematic test was conducted, and the experimental results demonstrated that the MWCNTs/Ecoflex-based flexible strain sensor exhibited a highly linear resistance-strain response within the 0–20% strain range, with a high sensitivity (Gauge Factor, GF) of 3.464, and an ultra-low Young's modulus (0.23 MPa), enabling it to conform tightly and seamlessly to the trunk surface, effectively preventing damage and ensuring non-invasiveness. The static stability tests confirmed the device's ability to maintain relative stability in resistance signal with minimal fluctuation and high reliability during long-term monitoring. The standard cylinder simulation experiments proved its high repeatability in measurement capability with good result consistency, and reliable measurement of simulated trunk diameters (within the 10.00–11.00 cm range). The results of live tree testing demonstrated that the device maintained excellent anti-interference performance under complex environmental conditions (including disturbances such as varying temperature, humidity, and cloudy or rainy weather), accurately capturing the diurnal dynamic changes in the DBH of Koelreuteria paniculata (131.9–132.5 mm), fully validating its practicality and reliability in real forest environments. Conclusion: This study has successfully developed a novel tree DBH measurement device based on a high-performance MWCNTs/Ecoflex flexible strain sensor, which achieves high sensitive detection of trunk circumference changes through innovative flexible sensing technology. Its ultra-low Young's modulus ensures non-destructive, tight conformity, guaranteeing tree-friendliness. The device possesses high measurement accuracy, excellent repeatability, stable resistance during long-term monitoring, and good adaptability to complex environments. The structural design emphasizes rapid and convenient installation to significantly improve efficiency. The device provides an innovative solution meeting the demands for rapidity, convenience, high accuracy, non-destructiveness, and long-term in-situ monitoring, holding broad application prospects in precision forestry, ecological research, and intelligent urban greening management.

Forest ecosystems constitute the foundation of terrestrial carbon (C) sinks. Precise quantification of their sequestration capacity is an essential prerequisite for enhancing C storage in terrestrial ecosystems and mitigating climate change. Especially, it is of great value in predicting long-term C dynamics for optimizing forest management strategies and achieving China’s dual C strategic objectives. The currently widely used process models are mainly based on the prediction frameworks of forest ecosystem productivity, utilizing “light quantum transfer-large leaf model” to characterize C sink formation mechanisms. These models evaluate short-term ecological dynamics through key biometric indicators including gross primary production (GPP) and net primary production (NPP), thereby overcoming inherent limitations in traditional methods for predicting ecosystem C sequestration potential. Theoretically, community attributes significantly influence the variation in forest carbon sink functions. Under the dual regulation of climatic effects and interspecific competition, the dynamics of forest carbon sinks are primarily dictated by stand age and vegetation growth processes. Therefore, assessments of forest carbon sink dynamics should incorporate a full consideration of these regulatory mechanisms. However, current research on the formation mechanism of forest ecosystem carbon sinks is difficult to scientifically explain the forest community growth trajectories. Productivity-based predictive approaches demonstrate limited capacity to support process models in evaluating long-term growth trends and spatiotemporal heterogeneity of C sequestration, consequently constraining the effectiveness of scientific evidence available for policy formulation. To address these methodological constraints, this study systematically elaborates on a research framework for predicting the long-term forest C sequestration based on tree growth processes. This framework, based on growth equations, characterizes the long-term expansion of biomass C pools driven by stand age dynamics, integrates the response mechanisms of C sink to climatic and soil variables into the traditional vegetation growth hypotheses, and thus, achieves a process-based prediction model for forest C dynamics that incorporates both ecological and environmental determinants. The forest C sequestration model (FCS model) was developed using the logistic growth equation and key parameters to characterize long-term dynamic patterns of forest vegetation C sinks. This model builds upon a process-based C turnover approach to create a predictive framework for forest ecosystem C sequestration, wherein the dynamics of forest vegetation drive the stock growth of other major C pools, such as the dead organic matter C pool and soil organic C pool. The model was parameterized using systematic survey data from typical forest ecosystems in China. Studies have shown that the FCS model effectively quantifies the spatiotemporal covariation patterns of forest ecosystem C sinks. This predictive framework, grounded in tree growth processes, offers a novel theoretical paradigm for C sink projections. It significantly improves the simulation capability of long-term dynamic changes in forest ecosystem C sinks, thereby providing stronger support for China’s efforts to achieve its “C neutrality” strategic objectives.

Forest soil organic carbon is an important component of the terrestrial ecosystem carbon pool, and its dynamics are closely linked to the ecosystem carbon balance and the response capability to climate change. As an important forest management practice, thinning can influence the input, transformation, and stabilization of soil organic carbon by altering stand structure, microenvironmental conditions, and plant-microbe interactions. In recent years, a large number of studies have examined the effects of thinning on forest soil organic carbon, but the relevant knowledge remains scattered. This review systematically summarizes the response patterns of soil organic carbon under different thinning intensities, recovery stages, and forest types, as well as the underlying regulatory mechanisms. Existing studies show that light thinning generally has little effect on soil organic carbon content and stock, moderate thinning is overall conducive to the accumulation of soil organic carbon content and stock, whereas heavy thinning may either increase or decrease soil organic carbon content and stock. In the short term after thinning, soil organic carbon content and stock often decline, whereas over the medium to long term they tend to increase continuously or gradually approach a new stable state. In coniferous forests and coniferous-broadleaf mixed forests, soil organic carbon content and stock usually increase or show no significant change following thinning, whereas in broadleaf forests they may increase, decrease, or remain unchanged. These differences are mainly related to the combined regulation of carbon input and output processes in forest soils following thinning. Future research should strengthen the integration of long-term field observations with modeling, optimize thinning regimes under different site and management conditions, and deepen research on the coupling between soil carbon sequestration and ecosystem multifunctionality, so as to better clarify the mechanisms by which thinning affects forest soil organic carbon.

In the context of the ever-expanding scale of the bamboo industry and the robust support from national policies, the demand for bamboo product processing has witnessed a substantial upsurge. The technological level of the bamboo splitting machine, as a pivotal piece of equipment for the primary processing of bamboo, plays a crucial role in determining the efficiency and quality of the industry’s development. To comprehensively understand its technological evolution, this study adopts the literature research approach to systematically review relevant theories and technical accomplishments. In the realm of theoretical research, scholars have focused on the physical and mechanical properties of bamboo, as well as explored the mechanics underlying bamboo splitting. Through in-depth exploration, they have uncovered the influence mechanisms of parameters such as splitting speed and blade angle on splitting quality, thereby laying a theoretical foundation for equipment research and development. At the technical application aspect, bamboo splitting machines have evolved into three major categories: manual, semi-automatic, and fully automatic, successfully transitioning from manual operation to intelligent processing. Regarding key technologies, continuous optimization has been carried out in structural design. Adjustable knife discs and self-adaptive centering mechanisms have been developed, significantly enhancing the equipment’s adaptability to bamboos of various specifications. Breakthroughs have also been made in detection technology, enabling precise measurement of bamboo diameter by leveraging machine vision. Moreover, the control system has been upgraded to intelligence, establishing a closed-loop control system with the integration of programmable logic controllers and sensors. These technological advancements have markedly improved the processing efficiency and adaptability of bamboo splitting machines, offering reliable technical support for the automation of bamboo processing. Nevertheless, the current bamboo splitting machines still encounter several technical bottlenecks. For instance, the accuracy of bamboo diameter recognition remains insufficient, there exists a conflict between knife disc design and processing efficiency, the adaptability to complex bamboo is relatively weak, and the level of intelligence is limited. These issues pose challenges in meeting the requirements of large-scale and high-precision production. To further enhance the performance and adaptability of bamboo splitting machine technology and facilitate the high-quality development of the bamboo processing industry, the following key research directions for future bamboo splitting technology are proposed: 1) Given the diversity of bamboo's biomechanical properties, it is essential to deepen the research on the interaction mechanism between splitting force and bamboo structural parameters. A multi-factor coupling splitting theory model should be established to provide a scientific basis for the optimization design of equipment. 2) An intelligent bamboo recognition system grounded in deep learning, which is integrated with multi-spectral imaging and 3D point cloud technology, to achieve precise detection and adaptive positioning of features such as bamboo diameter and knots under complex working conditions. 3) It is necessary to innovate designs of the splitting mechanism, break through the structural constraints of traditional rotating knife discs, and develop composite cutting devices and dynamic adjustment systems, resolving the conflict between splitting efficiency and quality. 4) It is necessary to construct an intelligent production system for bamboo splitting machines, and integrate internet of things monitoring, big data analysis, and autonomous decision-making technologies to enable real-time monitoring of equipment status, dynamic optimization of process parameters, and intelligent management of the entire production process. These technological innovations are expected to drive bamboo splitting machines towards more intelligence, efficiency, and environmental friendliness. They will not only provide robust equipment support for the high-quality development of the bamboo processing industry but also offer novel technological pathways for the transformation and upgrading of China’s bamboo equipment manufacturing industry.