Lignin, a crucial component of plant cell walls, together with cellulose and hemicellulose, constitutes the largest renewable organic carbon reservoir in terrestrial ecosystems. Due to its inherent heterogeneity, complex interunit linkages, and highly branched structure, lignin exhibits strong recalcitrance to degradation. This characteristic not only restricts the high-value utilization of lignin, but also greatly limits the efficient conversion of lignocellulose. As a green and sustainable approach, biodegradation has shown great potential for the valorization of lignin and lignocellulosic materials. Advanced studies of lignin biodegradation not only enhance our understanding of global carbon sequestration but also drive technological innovations in biomass conversion and renewable chemical production, offering promising solutions to climate change and energy crises. Fungi, as the primary decomposers in terrestrial ecosystems, have evolved highly sophisticated and diverse enzymatic systems for lignin degradation. However, critical gaps remain in our understanding of fungal-lignin interactions and their underlying mechanisms. In recent years, notable progress has been made in some studies. For example, the soft-rot fungus Parascedosporium putredinis NO1 secretes a novel lignin-oxidizing enzyme capable of cleaving β-ether bonds in lignin in the absence of cofactors, leading to lignin depolymerization and releasing triazine. In addition, the white-rot fungus Echinodontium taxodii generates manganese peroxidase, laccase, and esterase, which act synergistically to selectively delignify bamboo by cleaving cross-linkages between lignin and xylan, thereby enhancing cellulase accessibility and improving saccharification efficiency. Furthermore, Phanerochaete chrysosporium produces lignin peroxidase PcLiP03, which exhibits high affinity for lignin but minimal binding to cellulose, effectively preventing competitive adsorption. This interaction is primarily driven by electrostatic interactions arising from functional groups and hydrophobic interactions related to its structural features. At the metabolic level, ¹³C isotope-labeling studies have revealed that the basidiomycete Agaricus bisporus depolymerizes native lignin and its derivatives extracellularly and subsequently metabolizes the resulting products intracellularly as carbon and energy sources for anabolism. Additionally, the anaerobic fungus Neocallimastigomycete californiae has been shown to mediate lignin depolymerization through small-molecule-mediated redox reactions, altering lignin monomer composition and cleaving multiple interunit linkages. Collectively, these findings provide new insights into fungal lignin degradation mechanisms and highlight the potential for developing efficient, cost-effective, and sustainable lignin degradation technologies. The next step of research should further clarify the enzymatic mechanism of fungal degradation of lignin and continue to explore the potential of fungal metabolic pathways in the high-value utilization of lignin.

Objective: The Ning-Meng reach of the upper Yellow River is a major source of sediment input, posing urgent ecological threats such as the formation of a “new suspended river” and ice-flood-induced breaches. This study aims to analyze the mechanisms and spatiotemporal patterns of sediment transport into the river in this region, and identify key hazard areas along the main channel, so as to provide scientific support for the implementation of the “Yellow River Bend” campaign under the Three-North Shelterbelt Forest Program. Method: This study focused on the Tengger Desert, Ulan Buh Desert, and Kubuqi Desert. The methods of field surveys, remote sensing interpretation, and multi-source data integration were comprehensively applied to systematically analyze the patterns of aeolian sand input into the Yellow River from these three deserts and identify the affected areas. Result: 1）Aeolian sand from the proximal deserts such as the Tengger, Ulan Buh, and Kubuqi Deserts and the underlying soft sandstone formations were the primary source of coarse sediment in the Ning-Meng reach of the Yellow River. This sediment entered the channel mainly through four processes: wind erosion, dune migration, suspension and deposition, and transport by flood events. 2）With the Toudaoguai hydrological station as the basin outlet, the sediment transport in the Ning-Meng reach from 1950 to 2023 ranged from 1.630×10⁷ t to 3.162 1×10⁸ t, with an average of 9.405×10⁷ t. The Mann-Kendall test showed a significant decreasing trend in sediment transport (P<0.01) at a rate of 1.80×10⁶ t·a^?1 during this period. 3）The amount of sediment input into the river in the Ning-Meng reach showed a gradual downward trend from 1986 to 2013. From a seasonal perspective, the sediment input from the Ulan Buh Desert was dominated by spring, with contributions of 46.8%, 24.7%, 21%, and 7.5% in spring, summer, autumn, and winter, respectively. 4）There were significant spatial differences in sediment input from the three deserts. The Ulan Buh Desert had the largest annual average input at 9.369 7×10⁶ t, followed by the Kubuqi Desert at 6.534 2×10⁶ t, and the Tengger Desert the smallest at only 7.649×10⁵ t. Conclusion: The sediment input into the Yellow River in Ning-Meng reach exhibits significant spatial and temporal heterogeneity: it predominantly occurs in the spring and shows an annual decline over time. In space, it forms a gradient pattern of sediment input into the Yellow River with Ulan Buh Desert>Kubuqi Desert>Tengger Desert. This study provides a scientific basis for desertification prevention and ecological restoration in the sandy hazard areas along the Ning-Meng reach of the Yellow River, which holds practical significance for ensuring the stability of the Yellow River and the ecological security of the basin.

Objective: This study quantitatively evaluated the differences in windbreak efficiency and sand-fixation efficiency of typical sand-fixing tree species (Populus simonii, Pinus sylvestris var. mongolica, and Caragana korshinskii) within the shelterbelt systems of the Bashang region during winter and spring. It further investigated the response relationships and driving mechanisms linking these differences to key near-surface attributes, including vegetation morphology, surface cover, and soil properties. This study aims to provide a scientific basis for optimizing the local vegetation-based protection system and enhancing its year-round windbreak and sand-fixation performance. Method: Field observations were conducted in Kangbao County, Hebei Province, in November 2024, March and April 2025. The shelterbelts of three dominant tree species (P. simonii, P. sylvestris var. mongolica, and C. korshinskii) were selected as experimental objects, with the adjacent bare land as control plots. For each vegetation type, three observation points were set up along the prevailing wind direction at the windward side, within, and leeward side of the shelterbelt, and wind speed and sand transport flux were measured synchronously using cup anemometers and omnidirectional rotating sand collectors to calculate windbreak efficiency and sand-fixation efficiency. The tree height, crown width, coverage, litter thickness and density (undecomposed and semi-decomposed layers), understory vegetation height and coverage were investigated, and the surface soil (0–10 cm) properties: particle size distribution (sand, silt, clay), soil density, and moisture content were analyzed. One-way ANOVA was used to compare differences, Pearson correlation was used to examine associations, and redundancy analysis combined with multiple regression was used to quantify key drivers and their contributions. Result: There were significant differences in windbreak effectiveness and sand-fixation efficiency among vegetation types during winter and spring: the windbreak effectiveness was shown as the order of P. sylvestris var. mongolica (81.16%) > P. simonii (63.94%) > C. korshinskii (47.96%), while sand-fixation efficiency was ranked as P. simonii (97.78%) > P. sylvestris var. mongolica (96.23%) > C. korshinskii (89.39%). Compared to bare land, vegetation restoration significantly modified near-surface characteristics, reducing surface soil clay content by 1.80%–2.62%, increasing silt content by 10.88%–11.84%, and decreasing soil density by 11.52%–20.00%. The litter characteristics and understory vegetation height of the P. simonii plots were significantly better than those of the other species plots. Redundancy analysis indicated that near-surface characteristics collectively explained 89.2% of the variation in protective functions, with crown width identified as the dominant driver (60.3%), followed by soil moisture content (9.4%), clay content (6.0%), and density of the undecomposed litter layer (4.5%). The multiple regression model quantitatively characterized the contribution of key factors. Conclusion: During the wind-prone winter and spring seasons in arid regions, there are significant differences in windbreak and sand-fixation efficiency among different sand-fixing vegetation types. The evergreen arbor maintains the highest windbreak efficiency owing to their persistent canopy, while deciduous trees exhibit optimal sand-fixation performance due to substantial litter accumulation. Crown width is the most critical factor regulating protective efficiency, yet its direct management remains constrained. Enhancing ground coverage, particularly through high-litter accumulation, proves to be an effective approach for strengthening wind erosion control in winter and spring. The findings suggest that vegetation restoration practices should account for seasonal protection needs: in areas with severe wind erosion, P. sylvestris var. mongolica should be prioritized to reduce wind speed, whereas in areas with vulnerable surface soil, greater emphasis should be placed on P. simonii to suppress particle transport. This tailored approach can enable effective year-round control of regional soil wind erosion and support sustainable ecosystem management.

Objective: In the context of exacerbated urban heat island (UHI) effect, the evapotranspiration cooling effect of suburban forests plays a crucial role in alleviating UHI and regulating urban heat island circulation. However, the cooling regulation process remains poorly understood. This study aims to quantitatively analyze the transpiration cooling [ΔT(E_f)] and soil evaporation cooling [ΔT(E_s)] of Pinus tabuliformis plantation around Miyun Reservoir in Beijing, and determine the regulating factors of these two cooling processes at diurnal and seasonal scales, so as to provide scientific support for the formulation of strategies to mitigate the UHI effect in Beijing. Method: During the growing season from May to November 2021, thermal diffusion probes and eddy covariance methods were used to continuously monitor sap flow density (SFD) and evapotranspiration (ET) of the plantation. The forest evapotranspiration (E_f) and soil evaporation (E_s) were calculated, and the major meteorological factors and soil water content (SWC) were simultaneously monitored. Mantel-Test and random forest algorithms were used to analyze the temporal variation characteristics of E_f, E_s, ΔT(E_f), and ΔT(E_s) in P. tabuliformis plantation and their influencing factors. Result: 1) At diurnal scale, ΔT(E_f) and ΔT(E_s) dominated during the day and night, respectively. During the day, air temperature (T_a) had the most significant influence on ΔT(E_s), while soil water content (SWC) and shortwave radiation (RSD) significantly influenced ΔT(E_f) (Mantel’s P<0.01, 0.2≤r<0.4). 2) At seasonal scale, ΔT(E_f) contributed more than ΔT(E_s), and both ΔT(E_f) and ΔT(E_s) were higher in summer than in other seasons. From July to September, the daily averages of ΔT(E_f) and ΔT(E_s) were 3.49 and 1.66 ℃, respectively, while E_f and E_s had daily averages of 1.64 and 0.77 mm. T_a and SWC were the main environmental factors affecting the seasonal variations of ΔT(E_s) and ΔT(E_f), respectively. 3) After parameter optimization, the random forest model showed good simulation results for ΔT(E_s) and ΔT(E_f) (R²>0.93). Conclusion: The proportions of transpiration cooling and soil evaporation cooling differ significantly at diurnal and seasonal scales. Thermal conditions (soil temperature and air temperature) and soil water content are the most important factors influencing soil evaporation and transpiration cooling, respectively. Compared to soil evaporation cooling, plant stomatal regulation allows transpiration cooling to quickly respond to the vapor pressure deficit and air temperature.

Objective: This study investigated the effects of seedling biomass allocation trade-offs on growth and their responses to neighborhood competition and environmental factors of temperate forests in northeast China. The correlations between biomass allocation traits and organ-level traits with seedling growth were compared. This study aims to deepen the understanding of seedling biomass allocation and provide theoretical foundations for community regulation mechanisms and dynamic patterns of temperate forests in northeast China. Method: Based on data of individual seedlings from 130 quadrats surveyed in a coniferous-broadleaved mixed forest in Jiaohe, Jilin Province, principal component analysis was used to determine the trade-offs in seedling biomass allocation. Linear mixed-effects models were employed to construct a biomass allocation trade-off model, a seedling growth model, and a comparison model for biomass allocation traits and organ-level traits, analyzing the impact of biomass allocation trade-offs as well as biomass allocation traits and organ-level traits on seedling growth. Result: 1) The biomass allocation trade-offs of temperate forest seedlings in northeast China were mainly manifested in two categories: one was the root biomass investment trade-off at the expense of leaf biomass, and the other was the stem biomass investment trade-off at the expense of both leaf and root biomass. Specifically, as soil organic matter content decreased, seedlings reduced biomass allocation to roots. As canopy openness declined, seedlings increased biomass allocation to leaves. Under the combined effects of conspecific and heterospecific competition, seedlings allocated more biomass to either roots or leaves. 2) The root biomass investment trade-off at the expense of leaf biomass promoted seedling growth, while canopy openness, soil total phosphorus content, and soil total potassium content had negative effects on seedling growth. 3) Compared with organ-level traits, biomass allocation traits were more correlated with seedling growth, but the seedling growth rate was negatively correlated with resource acquisition traits such as specific stem length, specific leaf area and specific root length. Conclusion: The trade-offs in seedling biomass allocation promote seedling growth. Compared with organ-level traits, biomass allocation traits show stronger correlations with seedling growth. These findings indicate that biomass allocation plays a crucial role in shaping plant community growth dynamics and resource acquisition strategies.

Objective: To address ecological issues such as soil degradation caused by long-term continuous monoculture of Cunninghamia lanceolata (Chinese fir), it is necessary to establish and transform plantations into multi-layered, uneven-aged mixed forests of Chinese fir and broadleaved species to enhance the sustainability of forest ecosystems. This study evaluated changes in soil quality under different understory enrichment planting modes of native tree species, aiming to identify suitable understory enrichment planting modes and provide a scientific basis for maintaining soil health and sustainable management of Chinese fir plantations. Method: In a Chinese fir plantation established in 1998, the third thinning was conducted in 2014 (retaining an average density of 225 tree·hm^–2). In 2015, four understory enrichment planting modes were conducted: a pure plantation served as the control without thinning or planting (M0), understory replanting of Phoebe bournei only (M1), understory replanting of Phoebe bournei and Taxus wallichiana var. chinensis (M2), and understory replanting of P. bournei, T. wallichiana var. chinensis, and Schima superba (M3). The proportion of Chinese fir to understory planted species was 3∶7 in all modes. In 2022, seven years after understory replanting, soil samples were collected from 0–60 cm depth to determine chemical properties, extracellular enzyme activities, and bacterial community characteristics (16S rRNA). A minimum data set (MDS) was selected to establish a soil quality index (SQI) model. Variance partitioning analysis (VPA) was used to quantify the contributions of biotic factors (enzyme activities, microbial metabolic limitations, and community structure) and abiotic factors (chemical properties and stoichiometric ratios) to soil quality. Structural equation model (SEM) was applied to analyze the relationships among “understory replanting mode–soil quality index”. Result: Compared with the pure plantation (M0), the multi-layered uneven-aged Chinese fir and broad-leaved species mixed forests (M1, M2, M3) formed by understory replanting significantly improved soil quality and microbial ecological functions. The content of key nutrients in the 0–20 cm soil layer, including total nitrogen (TN), total phosphorus (TP), available nitrogen (AN), available potassium (AK), and soil organic carbon (SOC), increased by 29.87%–72.62%, with the greatest improvements observed in M2. Understory enrichment planting drove carbon, nitrogen, and phosphorus cycling by optimizing soil enzyme activities. The soil sucrase (SUC) activity and glucosidase (GLU) activity of M1, and urease (URE) activity of M3 reached their peak in the 0–20 cm layer. In contrast, the pure plantation had higher acid phosphatase (ACP) and catalase (CAT) activities, reflecting differences in catabolic pathways. The average microbial phosphorus limitation in M2 decreased by 12.05% compared with the pure plantation. Additionally, M2 optimized nutrient utilization strategies by enhancing the relative activity of nitrogen hydrolase (RAN) in the 0–20 cm layer and alleviating microbial carbon limitation in the 40–60 cm layer. Microbial community analysis revealed that the established multi-layered uneven-aged mixed forests significantly increased the Shannon diversity index of soil microorganisms and altered the abundance of functional bacterial phyla such as Acidobacteriota and Proteobacteria. Understory enrichment planting modes indirectly affected soil quality by regulating total phosphorus (path coefficient: 0.68), nitrogen-to-phosphorus ratio (0.71), SOC (0.33), pH (0.34), nitrogen hydrolase activity (0.17), and soil microbial Shannon diversity (0.60). The SQI values of the three understory enrichment planting modes were higher than that of the pure plantation, with M2 exhibiting the highest soil quality in the 0–20 cm layer and the pure plantation showing the lowest soil quality in the 40–60 cm layer. Conclusion: Transforming pure Chinese fir plantations into multi-layered uneven-aged mixed forests by understory replanting native broadleaved species can enhance soil nutrient levels, balance stoichiometric limitations, optimize enzyme activities and microbial diversity, and improve overall soil quality. Among them, understory replanting of P. bournei and T. wallichiana var. chinensis (M2) demonstrates the most significant soil improvement effects. These findings provide a theoretical basis for the sustainable management of Chinese fir plantations.

Objective: This study aims to explore the adaptability of the joint retrieval of regional forest aboveground biomass (AGB) by the new generation of ice, cloud, and land elevation satellite (ICESat-2), airborne LiDAR and Sentinel-2 multi-source data, providing scientific basis for large-scale forest resource management and dynamic monitoring. Method: Wangyedian Forest Farm in Chifeng City was selected as the research area, and a high-precision AGB estimation model was established based on airborne LiDAR data and sample plot measured data. The AGB of the sample plot was extended from discrete “points” to “surface” data on a large regional scale to overcome the problem of difficulty in matching sample points with spaceborne points. On this basis, ICESat-2 and Sentinel-2 remote sensing data were combined for AGB inversion, and the optimal variable combination and optimal inversion model were finally selected to draw the spatial distribution map of forest AGB in the study area. Result: 1) The three-dimensional structural information extracted from airborne LiDAR was highly correlated with forest AGB, and the inversion results of the random forest model had the highest accuracy with r of 0.91, root mean squared error (RMSE) of 17.00 t·hm^?2, and estimation accuracy (EA) of 88.90%. 2) After combining the ICESat-2 and Sentinel-2 variables, the accuracy of the inversion model was further improved (R²=0.74, RMSE=27.44 t·hm^?2, EA=69.32%), with R² and EA increasing by 30.26% and 14.18%, respectively. 3) The spatial distribution results of forest AGB in the study area showed that the forest AGB in the southeast was relatively low (with an average of 97.13 t·hm^?2), while that in the mid-east and northeast was relatively high (with an average of 117.03 t·hm^?2), which was consistent with the actual distribution. Conclusion: The AGB inverted from airborne LiDAR data has high accuracy, which can be used as an intermediate parameter to connect measured data and satellite data. Combining airborne LiDAR, Sentinel-2 and ICESat-2 data can not only further improve the estimation accuracy of forest AGB, but also provide a new reference for large-scale forest resource management and dynamic detection in the future.

Objective: The differences in stem morphology and canopy structure among individuals of the same tree species result in the uncertainties in estimating individual tree volume or carbon stock based on allometric growth equations. To address the uncertainties, this study developed a new method for three-dimensional measurement of individual tree aboveground carbon stock based on terrestrial laser scanning (TLS) point clouds. Method: The concept of space colonization modeling was based to reconstruct individual Eucalyptus trees in 3D and determine their aboveground carbon storage. The workflow included branch-stem separation, skeleton extraction and optimization, 3D reconstruction, and branch-stem volume calculation. Layer-by-layer judgment method combined with clustering analysis was used to separate trunk and branch point clouds, avoiding misclassification caused by drooping branches. Skeleton optimization removed redundant fine branches and merged nearly parallel branches belonging to the same branch. Cardinal curve interpolation algorithm was used to fill the missing skeleton segments, and a smoothed, completed skeleton was expanded to generate high-precision 3D geometric models of individual trees. Based on the three-dimensional structure extraction of branch and stem volumes, and combined with destructively sampling 41 Eucalyptus trees for wood density and carbon content measurements, the volume was further converted into individual tree aboveground carbon storage. Result: The accuracy of the method for extracting individual tree parameters was as follows: The linear fit of tree height measurements and reference values had an R² of 0.94 and CV(RMSE) of 19.00%, the linear fit of diameter at breast height (DBH) measurements and reference values had an R² of 0.94 and CV(RMSE) of 19.00%, the linear fit of stem volume measurements and reference values had an R² of 0.94 and CV(RMSE) of 19.00%, and the linear fit of branch volume measurements and reference values had an R² of 0.95 and CV(RMSE) of 38.84%. The method for estimating individual tree aboveground carbon stock had an accuracy of: R² of 0.96 and CV(RMSE) of 16.23% for the linear fit of measured and reference values. Conclusion: The carbon storage is directly measured by extracting individual Eucalyptus volume parameters and combining them with measured density and carbon content rate. This study focuses on addressing the differences in aboveground carbon storage measurement caused by variations in the morphology and structure of different Eucalyptus individuals, providing a technical basis for forest inventory compilation, smart forestry applications, and carbon sink accounting.

Objective: This study aims to identify key environmental factors influencing the internode length of moso bamboo (Phyllostachys edulis), so as to provide a theoretical basis for targeted cultivation of superior bamboo germplasm with long-internodes. Method: Based on the distribution of moso bamboo resources in China, survey sites were established using a 150 km×150 km latitude-longitude grid. Regression analysis was employed to reveal the effects of geographic, climatic, topographic, and soil factors on internode length, and key environmental factors were screened using regularization methods. Result: 1) The internode length at 1.5 m of moso bamboo in China ranged from 17 cm to 34 cm, with an average of (24.39±2.86) cm and a coefficient of variation of 11.72%. 2) Internode length was negatively correlated with longitude, annual average temperature, annual average precipitation, annual average sunshine duration, slope, and carbon-to-nitrogen ratio, and positively correlated with latitude, elevation, and pH, with correlations reaching a significant level (P<0.01). For every 1° increase in longitude, internode length decreased by 0.6 cm, for every 1° increase in latitude, internode length increased by 0.33 cm, for every 1 °C increase in temperature, internode length decreased by 0.48 cm, for every 100 mm increase in annual precipitation, internode length decreased by 0.18 cm, and for every 100 h increase in sunshine duration, internode length decreased by 0.13 cm. 3) Climate factors, topographic factors, and soil factors explained 24.52% of the total variance in internode length. Among them, climate factors contributed 8%, the interaction between climate and soil contributed 5.28%, and topographic factors contributed 4.58%. 4) Based on latitude and longitude geographic coordinates with exponential spatial correlation, the environmental factors influencing moso bamboo internode length were identified as precipitation in the coldest month and slope. Conclusion: The length of moso bamboo internodes is primarily influenced by a combination of climatic and topographical factors, with the key environmental factors being precipitation during the coldest month and slope gradient. The targeted cultivation of long-internode moso bamboo forests requires comprehensive consideration of regional climatic conditions to ensure proper management of environmental conditions during critical growth periods.

Objective: In response to the problem of scattered indicators and fuzzy thresholds for dividing the development stages of secondary forests, a quantitative division method based on stand state characteristics was constructed to explore the comprehensive thresholds of key indicators for development stage division, providing more scientific support for precise forest management throughout the entire cycle. Method: Different types of Quercus aliena var. acuteserrata secondary forests in Xiaolongshan forest area of Gansu were taken as the research object, and 15 indicators expressing stand state characteristics were selected. The systematic clustering method was used to cluster the different types of Q. aliena var. acuteserrata secondary forests. The Kruskal-Wallis non-parametric tests were used to screen the factors affecting the clustering of Q. aliena var. acuteserrata secondary forests, and a development stage division indicator system was constructed. The analytic hierarchy process (AHP) and entropy weight method (EWM) were used to determine the comprehensive weights of key indicators, and combining with Lagrange multiplier method to calculate the comprehensive values, and the development stages of secondary forests based on stand state characteristics were given. Result: 1) Based on stand characteristics, 15 sample plots were classified into four types via hierarchical cluster method (measured with average linkage), and subjected to non-parametric tests. Among them, regeneration level, stock volume, q-value of stand diameter distribution, average tree height, dominance of group species, uniform angle index, mingling, Shannon-Wiener index, Margalef index, Simpson index and Pielou index reached statistically significant levels (P<0.05). 2) Nine indicators including stock volume, q-value of stand diameter distribution, average tree height, dominance of group species, uniform angle index, mingling, and Shannon-Wiener index were selected. The Margalef index and regeneration level formed a classification index system for secondary forest development stages. Their comprehensive weights were 17.69%, 8.76%, 7.09%, 14.07%, 10.61%, 10.75%, 10.81%, 14.33% and 5.89%, respectively. Based on the stand state characteristics, the development stage of secondary forests was able to be divided into four stages, namely, regeneration period (gap period, canopy period), differentiation period, establishment period and stable period. 3) This method was used to divide the development stages of 15 secondary forests of Q. aliena var. acuteserrata, with two stands were in the regeneration period, eight stands were in the differentiation period, three stands were in the establishment period and two stands were in the stable period. Conclusion: The key factors affecting the division of secondary forest development stages are the stock volume, q-value of stand diameter distribution, average tree height, dominance of group species, uniform angle index, mingling, diversity index and regeneration level. Based on the stand state characteristics, the secondary forests can be divided into four development stages. This method can provide a theoretical basis for the division of development stages and precise management of secondary forests of Q. aliena var. acuteserrata.

Objective: This study aims to analyze the spatial and temporal characteristics of forestry pest occurrence in China (1992—2022), and examine the multiscale impacts of natural climatic and socioeconomic factors on pest dynamics, providing a theoretical basis for prevention and control strategies. Method: Based on the occurrence area of forest pests in 31 provinces of mainland China from 1992 to 2022, STEM clustering analysis was used to classify the occurrence characteristics of the provinces. Combined with natural climatic factors and socioeconomic factors, the random forest, Pearson correlation, and coupling coordination degree models were employed to systematically analyze the influencing factors of forestry pest occurrence at multiple scales. Result: 1) From 1992 to 2022, forestry pest occurrence area in China showed an overall increasing trend. Temporally, plant diseases exhibited the most rapid growth after 2018, and spatially, the 31 provinces demonstrated 3 categories comprising 11 distinct growth models. 2) At the national scale, railway density, expressway density, temperature, and seedling production showed statistically significant importance (P<0.05) in driving forestry pest incidence changes. Temporally, all seven factors exhibited significant correlations with forestry pest incidence (P<0.05). Spatially, however, only railway density, expressway density and per capita GDP were significantly correlated with forestry pest incidence (P<0.05). 3) At the provincial scale, the coupling coordination degree between temperature and precipitation and forestry pest incidence was relatively low in Guangdong, Guangxi, and Hainan, while significantly higher in Shandong, Tianjin, and Shanghai. The coupling coordination degree between railway density, expressway density and forest pest occurrence was significantly higher in eastern regions including Shandong, Tianjin, and Shanghai compared to western regions such as Yunnan, Qinghai, and Xizang. 4) Further analysis was conducted to characterize the differential impacts of natural climatic and socioeconomic factors on native and invasive forestry pest incidence. Native forestry pest incidence showed higher prevalence in northern regions, demonstrating significant negative correlation with precipitation (P<0.05) but positive correlation with railway density (P<0.05). Invasive forestry pest incidence was higher in coastal areas, exhibiting highly significant positive correlations with both railway density (P<0.001) and expressway density (P<0.01). Conclusion: From 1992 to 2022, forestry pest occurrence area in China has an overall increasing trend temporally and displays multiple variation models spatially. At national and provincial scales, there are significant differences in the relative importance, correlation, and coupling coordination degree of natural climatic and socioeconomic factors on forestry pest incidence. There are significant differences in the spatial distribution of the incidence of native and invasive forestry pests and their correlation characteristics with various factors. Based on these multi-scale analysis results, a multi-level prevention and control system should be constructed, including factor-level prioritization, spatiotemporal synergy controls, regionalized prevention, and differentiated strategies for native versus invasive forest pests.

Objective: With the highly heterozygous hybrid poplar ‘84K’ as a model, this study aims to characterize the divergence of alleles in the IQD gene family from three dimensions of systematic evolution, protein structure, and expression regulation, in order to provide new insights into the genetic basis of complex traits in forest trees and the potential functional complementarity between alleles. Method: The sequence heterozygosity of PagIQD alleles was calculated, combined with systematic evolutionary analysis and chromosome localization, to determine the gene distribution and evolutionary relationship. Protein physicochemical properties, transmembrane structure, and subcellular localization were predicted. Motifs feature analysis, 3D structure modeling, and calmodulin-binding were conducted. The differences in allele protein characteristics were compared. The tissue and stress response patterns of allele-specific expression (ASE) were analyzed and its expression synergy was assessed by integrating cis-element analysis with RNA-seq data. Allele-dependent genome editing efficiency was further evaluated based on sequence divergence. Result: Phylogenetically, the number of PagIQD gene family members in 84K showed a slight contraction, and the average heterozygosity of coding regions, full-length genes, proteins, and promoters sequences were all higher than the genome-wide level (2.1%). Several IQD genes in 84K did not align perfectly with their chromosomal positions in the reference Populus alba genome. Allelic pairs displayed six distinct phylogenetic branching patterns, suggesting these alleles may originate from different ancestors origins or represent retention of ancient polymorphisms. At the protein level, some allele pairs differed markedly in physicochemical properties, especially in stability and hydrophobicity, and individual alleles showed discrepancies in predicted transmembrane regions and subcellular localization. Approximately 14% of allele pairs varied in motif number or arrangement, and some exhibited differences in secondary structure proportions and IQ67-domain spatial conformation, which may influence their calmodulin (CaM) binding mode and binding energy. In terms of expression regulation, there were significant differences in cis-element and transcription factor binding sites between alleles, resulting in widespread allele-specific expression, with about 88.5% of gene pairs showing biased expression in at least one tissue, and strong tissue specificity. Under stress, allelic pairs often showed different or even opposite responses in terms of responsiveness. Integrated analysis revealed three interaction patterns between alleles: synergistic response, expression buffering, and homeostasis maintenance. Sequence divergence also strongly affected the design and predicted efficiency of allele-specific genome-editing targets. Conclusion: This study demonstrates that multi-dimensional allelic divergence is a pervasive feature in the highly heterozygous genome of 84K. The results highlight the necessity of treating alleles as potentially distinct functional units, and two alleles should be considered simultaneously in functional analysis, expression analysis, and gene editing design of high heterozygous forest trees, which is of great significance for accurately analyzing the genetic mechanism of forest traits and guiding genetic improvement.

Objective: This study aims to explore the effects of fungal elicitors from different fungi and different types of fungal elicitors from the same fungus on the growth of mycelia & fruiting bodies and flavonoid content, effective medicinal components of Sanghuangporus vaninii, in order to comprehensively evaluate the efficiency of fungal elicitors in different growth stages and culture environments. Method: Three different types of fungal elicitors were prepared from 11 different soil fungi. A total of 33 different fungal elicitors were used to treat the mycelia of S. vaninii. The biomass, flavonoid content and flavonoid production were statistically analyzed, and three optimal fungal elicitors were screened out based on the three indicators. The real-time quantitative PCR was used to preliminarily verify the molecular mechanism by which three optimal fungal elicitors enhanced flavonoid content. The induction conditions of fungal elicitors were optimized by the response surface method. Three optimal fungal elicitors were applied to the fruiting bodies to verify the accumulation of flavonoid content. Finally, non-targeted metabolomics analysis was conducted on the mycelia and the fermentation broth of strain HSL, which had a better effect in increasing the flavonoid content of S. vaninii. Result: Three optimal fungal elicitors (NL-19M, NL-19ME and HSLFE) had the best induction effects on the biomass, flavonoid content and flavonoid production of S. vaninii. Moreover, the three fungal elicitors promoted the accumulation of flavonoid content by increasing the expression levels of different key enzymes in the flavonoid biosynthesis pathway. There were differences in the optimization conditions for the biomass, flavonoid content and flavonoid production by the elicitors of the same fungus. The flavonoid contents of the fruiting bodies treated with NL-19M, NL-19ME and HSLFE were all higher than those of the control. The active ingredients of fungal elicitors may be lipids and lipid-like molecules. Conclusion: Different optimal fungal elicitors treatments can activate the expression of different key enzymes for flavonoid biosynthesis and have different induction conditions, reflecting the complexity of fungal metabolic regulation and revealing the regulatory mechanism of fungal elicitors on the flavonoid biosynthesis. This study provides a more complete and systematic theoretical basis for the commercial application of fungal elicitors and the establishment of a technical system for improving the quality and efficiency of under-forest economy including medicinal and edible fungi.

Objective: This study aims to investigate the dynamic accumulation patterns of the main medicinal components (flavonoids and terpene lactones) in the seed kernel of Ginkgo biloba during development, to analyze the phenotypic traits, seed kernel nutrients, medicinal components, and allergenic components among different cultivars, so as to screen ginkgo fruit cultivars with high medicinal content and superior overall quality. Method: Four productive cultivars were selected to dynamically determine the changes in the content of medicinal components during development of the seed kernel. At maturity, the phenotypic characteristics of the nuts and the nutritional, medicinal, and allergenic components of the kernels in 36 cultivars were systematically determined. The coefficient of variation analysis, diversity index analysis, correlation analysis, principal component analysis, and fuzzy subordinate function method were comprehensively applied to evaluate the advantages and disadvantages of each cultivar and to screen the target cultivars. Result: The total flavonoid and total lactone contents in ginkgo seed kernels exhibited a development pattern of first increasing and then decreasing with the peaks occurring in July or September and the lowest in October during the maturation period. The coefficients of variation of the phenotypic traits across the 36 tested cultivars ranged from 10.46% to 36.88%, with diversity indices ranging from 3.54 to 3.58, while the coefficients of variation of the chemical composition ranged from 9.91% to 36.93%, with diversity indices ranging from 3.52 to 3.58. Correlation analyses revealed that starch content was highly significantly negatively correlated with ginkgolic acid content (P<0.01) and significantly negatively correlated with total flavonoid content (P<0.05). Medicinal constituents (flavonoids and terpene lactones) were significantly negatively correlated with the morphological indexes (nut shape coefficients and nut widths, nut thicknesses, and single nut weights) (P<0.05). Based on principal component analysis and the fuzzy subordinate function method, a comprehensive evaluation model was constructed for screening out two fruit cultivars (No. 25 and No. 33) with significantly higher medicinal content. The two cultivars exhibited an average total flavonoid content of 2.32 mg·g^–1, and an average total lactone content of 3.66 mg·g^–1. Conclusion: This research has systematically elucidated the dynamic accumulation pattern of medicinal components in ginkgo seed kernels, which exhibit an first increasing and then decreasing during development. It is confirmed that cultivated ginkgo cultivars exhibit high coefficients of variation in phenotypic traits, nutritional components, and medicinal constituents, and there are significant correlations between these traits. Two superior cultivars, No. 25 and No. 33, have been comprehensively evaluated. Especially, cultivar No. 25 has outstanding medicinal component content with relatively low allergenic components, demonstrating excellent comprehensive quality. The findings provide a material foundation for the targeted breeding of “high-medicinal, low-allergenic” ginkgo cultivars, and for the development of functional foods and industrial promotion.

Objective: This study aims to elucidate the quantitative relationships among soil fertility, tree nutritional status, and yield of Juglans regia (walnut), and construct a multi-factor yield prediction model to guide fertilization management, and overcome the limitations of single nutritional diagnostic techniques, so as to provide a scientific basis for precision fertilization in walnut orchards. Method: Thirty-four walnut orchards in Baokang County, Hubei Province were selected as study objects. The orchards were classified into high-yield (≥1200 kg·hm^–2), medium-yield (450–1200 kg·hm^–2), and low-yield (<450 kg·hm^–2) groups based on yield per unit area. The Nemerow Comprehensive Index and Diagnosis and Recommendation Integrated System (DRIS) were comprehensively applied to systematically evaluate the nutrient status of soil, leaves, and terminal buds. Subsequently, correlation analysis and regression analysis were used to construct yield prediction models. Result: 1) Among the 34 walnut orchards, 25 had medium soil fertility and 9 had high soil fertility, and all of the latter were high-yield orchards. 2) The soil of high-yield orchards possessed significantly greater hydrolyzable N, available K, organic matter, available P, and soil fertility index than that of low-yield orchards, and hydrolyzable N deficiency was the primary factor restricting soil fertility. 3) The mean values of fresh and dry weights of terminal leaflets and rachises, as well as the length and diameter of terminal buds of walnut trees in high-yield orchards were significantly higher than those in low-yield ones (P<0.05), indicating that biomass accumulation and bud development of walnut trees in high-yield gardens were better. 4) The average contents of N, P, K, Ca, and S in the leaves of walnut trees in high-yield orchards were higher than those in low-yield orchards, and there were significant differences in the contents of N and Ca between high-yield orchards and low-yield orchards (P<0.05). The average contents of N, P, K, and S in the terminal buds of walnut trees in high-yield orchards were also higher than those in low yield gardens, whereas Ca content in the terminal buds and nutritional imbalance index of leaves and terminal buds were significantly lower than those in low-yield gardens (P<0.05). 5) Correlation analysis indicated that there were predominantly positive relationships between soil and leaf nutrients, and mixed positive/negative correlations between soil and bud nutrients. Soil pH affected leaf nutrient uptake, and bud Ca was negatively correlated with soil nutrients. The soil fertility index (FI) was positively correlated with yield (P<0.05), whereas the leaf (Lnila) and bud nutritional imbalance index (Bnila) were negatively correlated with yield (P<0.05 and P<0.01, respectively). 6) A segmented linear regression model for yield (Y, kg·hm^–2) was derived as follows: when FI≤0.9 or FI>2.7, Y = 72.782 ? 0.012 Bnila ? 0.017 Lnila + 46.441 FI; when 0.9<FI≤1.8, Y = 162.598 ? 0.011 Bnila ? 0.016 Lnila + 4.276 FI; when 1.8<FI≤2.7, Y = 126.558 ? 0.011 Bnila ? 0.016 Lnila + 4.276 FI. Conclusion: Soil fertility in Baokang walnut orchards is generally at a moderate level, and nitrogen deficiency is the primary factor limiting yield improvement. High-yield orchards are characterized by superior soil fertility and balanced nutritional status in leaves and terminal buds.

Objective: In response of the problems of low detection accuracy and inaccurate defect contour prediction in existing wood stress wave tomography algorithms, a wood defect detection framework integrating the SVAM and the LVCC algorithm was constructed to systematically improve the accuracy of stress wave tomography, providing technical support for the efficient detection of wood defects. Method: The imaging area was divided into grids to form the basic units for imaging. Stress wave propagation paths were established between each sensor and its neighboring sensors to form the basic sectors required for interpolation in the SVAM algorithm. The velocity on each sector edge represented the stress wave propagation speed along that path. The grid velocity was determined by all sectors covering that grid. The weighted sum of the influence velocities from these sectors was calculated to obtain the velocity values for all grids. The intersection points of all paths were computed to form a set of low-velocity points. A convex hull was constructed for this set, and the region within the convex hull is used as a constraint area to improve the accuracy of defect prediction. Result: Comparative experiments were conducted on four real wood samples and three simulated samples using the Fakopp algorithm, the RSIA algorithm, and the SVAM algorithm. Additionally, comparative experiments were performed on two Salix babylonica samples using the Fakopp algorithm and the SVAM algorithm. In the experiments on the four real log samples and three simulated samples, the SVAM algorithm achieved accuracy, precision, and recall rates of 85.5%, 94.1%, and 89.3%, respectively, outperforming the Fakopp algorithm (79.9%, 97.8%, and 78.8%) and the RSIA algorithm (80.9%, 92.8%, and 84.8%). In the experiments on the two living S. babylonica samples, both the SVAM and Fakopp algorithms demonstrated good prediction performance. Cross-validation was conducted on two paths of the defective sample using a micro-drilling resistance instrument. The prediction errors of the SVAM algorithm were 2.09% and 9.99% lower than those of the Fakopp algorithm, respectively. The experimental results validated the effectiveness of the proposed method in defect prediction across different types of samples. Conclusion: The proposed SVAM algorithm can effectively detect wood defects in three different types of data samples. The detection performance is less affected by the size, shape, and location of defects, demonstrating high robustness. The algorithm provides a reliable solution for accurate defect detection in trees.

Objective: In response to the issues of low utilization efficiency of processing residues (such as Chinese fir roots and chips) generated throughout the Chinese fir industrial chain, as well as the challenges of low yield and poor quality of traditional processing techniques for the preparation of smoke flavorings, the integrated technology of superheated steam distillation-cracking process (SSD-CP) was proposed in this study. This study aims to provide innovative solutions for the efficient and high-value utilization of Chinese fir processing residues through directional thermal conversion. Method: In this study, Chinese fir chips were used as the raw material, and experiments were conducted using a self-designed SSD-CP integrated system (including a steam generator, superheating device, cracking unit, and multi-stage condensation system). The distillates at 150–350 ℃ were collected, and the smoke flavoring was obtained by extracting the distillate, dehydrating it, and rotating evaporation to remove the solvent. The chemical composition of the smoke flavorings was analyzed via Gas Chromatography-Mass Spectrometry (GC-MS), and the aroma characteristics were systematically evaluated. Comparative assessments were conducted to assess differences in product yield and quality between steam distillation and dry distillation methods. Result: The smoke flavorings prepared via SSD-CP achieved a yield of 29.45%, which was 39 times higher than that of steam distillation (0.76%) and 4 times higher than that of dry distillation (6.94%), demonstrating a significant enhancement in resource conversion efficiency. The key aroma-contributing components were identified through GC-MS analysis, including α-cedrene, cedrol, 2-methoxy-4-methylphenol, β-cedrene, isoeugenol, guaiacol, α-terpineol, 4-ethyl-2-methoxyphenol, and 5-methyl-2-furaldehyde. In a high-temperature environment, cedrol was able to be converted into alkenes, and cellulose, hemicellulose and lignin generated heterocyclic and phenolic substances through chemical reactions such as pyrolysis and rearrangement, which impart the flavor with strong smoke characteristics. Sensory evaluation revealed that the SSD-CP smoke flavorings presented dominant smoky, caramelized, and woody notes with a subtle cooling sensation, featuring overall transparency and long-lasting. Conclusion: The SSD-CP technology significantly improves the yield of smoke flavorings, and the quality fraction and aroma of its main aroma components are better than those produced by the traditional technology. The technology results in the characteristic aroma of the smoke flavorings with the core of smoky, caramelized, and woody notes. A transformation system of “wood waste to smoke flavorings” has been constructed, and the efficient and high-value utilization of Chinese fir processing residues has been successfully realized.

Objective: In response of the issue of errors in measuring slab height using line laser in the production of ultra-thin high-density fiberboard (HDF), a blind-zone compensation and surface-morphology distortion correction method was proposed. The method can compensate for measurement blind zones caused by excessive height variations on the slab surface, reduce height-measurement errors induced by installation misalignment of a line-laser 3D profile sensor, and correct distortions in the reconstructed surface-morphology map to improve slab height measurement accuracy. The proposed approach aims to improve slab height measurement accuracy, thereby providing theoretical support for quantitatively evaluating slab forming uniformity and enhancing the precision of defect localization. Method: Based on the principle of line-laser triangulation, a quadratic-curve blind-zone compensation algorithm for slab height measurement was developed. Lagrange interpolation was used to reconstruct slab height data within the blind zone, and a corrected height map (height point-cloud color map) was established. The effects of sensor rotational misalignment about the x-axes, y-axes, and z-axes on both slab height readings and surface-morphology distortions were further analyzed, deriving corresponding distortion-correction formulations for rotations about each axis. Region-of-interest (ROI) cropping was then applied to extract the corrected mat area. Result: The proposed quadratic-curve blind-zone compensation algorithm effectively compensated for missing height data in blind zones during line-laser measurement. The x-axis rotation error of the laser 3D contour imaging instrument led to overestimation of slab height, the y-axis rotation error caused an overall widening trend in the surface-morphology map, and the z-axis rotation error produced a parallelogram-type distortion. Within the tested installation-error range of 0°–30°, the proposed correction methods achieved good rectification performance for height maps obtained under x-axis, y-axis, and z-axis rotational errors. To avoid substantial information loss in the corrected 3D point-cloud data, the sensor installation tilt angle should be controlled within 10°. Conclusion: The proposed blind-zone compensation and surface-morphology distortion correction method can effectively reconstruct missing height data on the slab surface blind zones and correct slab height measurement errors caused by installation misalignment of a line-laser 3D profile sensor. The method improves the accuracy and reliability of mat surface morphology measurement, strengthens the quantitative evaluation of forming uniformity for ultra-thin HDF mats, and helps to enhance defect localization precision. These outcomes are of significant research and practical value for improving the quality of ultra-thin HDF products.

Objective: This study aims to assess the impact of incorporating individual tree-specific traits into allometric growth equations for young Pinus elliottii (slash pine) plantations on model performance, and to develop a power-type biomass model suitable for estimating aboveground biomass (AGB) of the young slash pine, achieving precise, rapid, and efficient biomass prediction. Method: A total of 170 sample trees from a 4-year-old slash pine plantation were selected, and the AGB of various organs was determined through complete harvest method to analyze biomass allocation patterns. Different growth factors were used as predictive independent variables to construct power-function-based biomass models for total AGB, stems, branches, and needles. The performance of these models was then comprehensively evaluated. Result: Among the biomass models based on stem diameters measured at different heights above ground, the fitting performance followed the order: diameter at breast height (DBH) > ground diameter > diameter at 1.0 m height > diameter at 1.5 m height. The ternary biomass model (W=aDBH^bH^cρ^d, where a, b, c, and d are coefficients), which incorporated the optimal growth factors of measured tree height (H), DBH, and wood density (ρ) as predictive variables, achieved the highest accuracy for estimating aboveground and stem biomass (R² = 0.864 and 0.839, and RMSE = 1.107 and 0.541, respectively). In contrast, the model W=aDBH^bH_e^cA_c^d, incorporating UAV-estimated tree height (H_e), UAV-derived crown projection area (A_c), and DBH, provided the most accurate estimates for branch and needle biomass. The model achieved high accuracy, with R² values of 0.670 and 0.778, and RMSE values of 0.410 and 0.536 for branch and needle biomass, respectively. Conclusion: Incorporating tree-specific traits into allometric equations can significantly enhance the accuracy of biomass estimation in young slash pine plantations. The ternary biomass model constructed based on optimal growth factors is a reliable tool for rapid and accurate assessment of biomass in 4-year-old slash pine plantations in Zhejiang Province.

Objective: This study investigated the variations in microstructure and primary chemical constituents of surface timber in ancient architecture during natural aging processes. The aims of this study are to elucidate the correlation between the deterioration severity of load-bearing wood components and chemical degradation, quantify the differences in the degree of deterioration of wood components on different floors, providing a scientific basis for the conservation and restoration of ancient wooden architectural components. Method: Forty-eight samples of historically aged timber taken from the main load-bearing wooden components of the Holy Mother Hall at Jinci Temple were used as the experimental material, with one contemporary reference sample as the control. Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), and X-ray diffraction (XRD) were used to analyze the changes in wood micromorphology, chemical functional groups, and cellulose crystallinity. Additionally, the quantitative content of cellulose, hemicellulose, and lignin was determined and analyzed following the U.S. Department of Energy (NREL) standard protocol. Result: The surface timber of the load-bearing wooden components in the ancient architecture of the Holy Mother Hall has deteriorated to varying degrees, which was correlated with internal cellular damage modalities including bordered pit cracking, cell wall distortion, and structural fragmentation. Concurrently, cellulose, hemicellulose, and lignin underwent degradation in aged timber, with hemicellulose decomposition demonstrating being the most significant. Conclusion: Lignin content in historically aged timber exhibits a progressive increase with advancing cellular deterioration, whereas cellulose and hemicellulose contents demonstrate monotonic decline. There is a statistically significant positive correlation between cellulose content and its crystallinity index. Second-floor structural members in the Holy Mother Hall consistently exhibit heightened degradation of primary chemical constituents compared to first-floor counterparts.