Forest biodiversity plays a pivotal role in regulating ecological functions and critical ecosystem services, while exacerbating climate change is jeopardizing forest biodiversity, health and stability. To tackle climate change and protect biodiversity, it is particularly important to enhance the multifunctionality, sustainability, and resilience of forest ecosystems. Tree species diversity, as a core issue of forest ecosystem management, directly contributes to shaping forest multifunctionality, stability and resilience, which has become a research hotspot and frontier of forest ecology worldwide. In view of complexity of forest ecosystem (e.g., diverse forest types, complex stand structure and spatiotemporal dynamics in response to environmental disturbances), our understanding of the mechanisms underlying effects of tree species diversity on ecosystem multifunctionality and resilience remains poorly understood. This article systematically synthesizes the key ecological principles illustrating how biodiversity influences ecosystem multifunctionality, including niche differentiation, resource partitioning, functional trait integration and trade-offs, complementarity and selection effects, as well as leverage effects and functional redundancy. This article reviews the research progress on tree species diversity and ecosystem multifunctionality in recent years, covering the effects of tree species diversity on tree growth, stand productivity, root dynamics and exudates, soil organic carbon, soil nutrients, soil microbial communities, and root-soil-microbe interactions. Additionally, how tree species diversity enhances ecosystem stability and resilience in response to droughts, pest outbreaks, and invasive species is also examined. Based on practical management practices, four synergistic silvicultural strategies are proposed to improve forest quality and multifunctionality, such as tree species selection and genetic diversity optimization, mixed-species reforestation and functional trait-based species assemblages, rotation period adjustment and soil fertility maintenance, and landscape-level multifunctional configuration. Finally, in perspective of the nature-based solutions for shaping synergies between climate change mitigation and adaptation and biodiversity conservation as well, future research priorities and directions of tree diversity and multifunctionality of forest ecosystems are looked forward, which will provide theoretical basis and practical guidelines for navigating sustainable forest management, particularly for plantation forests.

Objective: The objectives of this study are to investigate the effects and regulatory mechanisms of roots and mycelium of Pinus massoniana and Castanopsis hystrix forests and their mixed forest on the content of different soil phosphorus fractions, so as to provide a theoretical basis for the species selection and nutrient management in the establishment of subtropical mixed-species plantations. Method: Sampling plots were set up in P. massoniana and C. hystrix forests and their mixed forest. Ingrowth bags with varying pore sizes (2 mm, 48 μm, and 1 μm) were used to physically distinguish the regulatory effects of roots and mycelium on the contents of different soil phosphorus fractions. Soil physicochemical properties such as phosphorus fraction contents, along with microbial biomass carbon, nitrogen, and phosphorus contents, and enzyme activities were measured. A systematic comparison was conducted on the effects of roots and mycelia on different soil phosphorus fractions across the three types of forests. Key regulatory factors were identified using correlation analysis, variance partitioning, and redundancy analysis. Result: 1) Compared to the pure P. massoniana stand, the mixed stand of P. massoniana and C. hystrix exhibited a significant increase in the positive root effect on the moderately active phosphorus fraction (NaOH-Po) and the negative root effect on the active phosphorus fraction (NaHCO₃-Po). Additionally, the mixed stand substantially elevated the positive mycelial effect on the active phosphorus fraction (NaHCO₃-Po) and the negative mycelial effect on the stable phosphorus fraction (HCl-Pi) (P<0.05). 2) On the one hand, mixed tree species significantly promoted the accumulation of moderately active phosphorus fractions (NaOH-Po) through root-mediated biological processes (inhibition of β-1,4-glucosidase activity) and abiotic processes (decreasing soil pH) (P<0.05), thereby promoting the transformation of active phosphorus fractions (NaHCO₃-Po) into moderately active phosphorus fractions. On the other hand, the mixed stand significantly enhanced the content of active phosphorus fractions (NaHCO₃-Po) through mycelium-mediated processes (increasing microbial biomass carbon content and microbial biomass nitrogen content) (P<0.05). This process also activated stable phosphorus components, facilitating their conversion into the active phosphorus fractions. 3) Variance decomposition, redundancy analysis, and correlation analysis consistently demonstrated that biotic factors were the primary determinants influencing the regulation of different soil phosphorus fraction contents by roots and mycelium. Conclusion: Tree species mixing primarily regulates the contents of different soil phosphorus fractions through root-mediated biotic and abiotic processes and mycelium-mediated biotic processes, with biological factors playing a central role. In the management of plantations, full consideration should be given to the ecological strategies of roots and mycelia of different tree species, and species configuration should be optimized to enhance soil phosphorus availability and plantation productivity.

Objective: Genomic selection for optimizing dynamic growth traits during the seedling stage of poplar is crucial for improving prediction accuracy and facilitating early selection of superior offspring. Method: A total of 400 F₁ hybrid progeny derived from a cross between Nanlin 895 poplar (female parent) and Jingxing Yihao poplar (male parent) were used as materials. Ground diameter and plant height were measured monthly from April to September, and genotypic data were obtained through whole-genome resequencing. Six genomic selection models, such as GBLUP, BayesA, BayesC, support vector regression, gradient boosting, and random forest, were employed to evaluate the impact of monthly phenotypic data on the prediction accuracy of genomic selection. Additionally, final ground diameter and plant height were measured at the end of the growing season in December to validate the predictive accuracy of each genomic selection model for final phenotypic values. Result: The mean values of ground diameter and plant height in the hybrid population increased gradually over the months, reaching their maximum in September. The coefficients of variation ranged from 0.23 to 0.34 for ground diameter and from 0.18 to 0.54 for plant height, indicating substantial genetic variation and significant selection potential. Narrow-sense heritability estimates ranged from 0.42 to 0.47 for ground diameter and from 0.39 to 0.62 for plant height. Among the genomic selection models, GBLUP, BayesA, BayesC, and support vector regression consistently had higher prediction accuracy for ground diameter and plant height across all months compared to gradient boosting and random forest. The highest prediction accuracies for ground diameter and plant height were observed in June and September, respectively. The final growth data collected in December was used to evaluate the prediction accuracy of different genomic selection models, and the results showed that models constructed with phenotypic data from June, July, August, and September had significantly higher prediction accuracies for ground diameter and plant height compared to those built with data from April and May. Among them, the BayesA model based on September phenotypes exhibited the highest prediction accuracy for the both traits and was therefore selected to predict and screen the breeding values of the 400 hybrid progenies. Based on the December phenotypic observations and the predicted breeding values through genome selection, four hybrid progenies were consistently selected by both methods for their superior genotype. Conclusion: Genomic selection can effectively identify superior progeny for dynamic growth traits during the seedling stage of poplar, providing an efficient method for the early selection of superior progeny in poplar breeding.

Objective: In this study, an ecosystem health assessment framework and a comprehensive resistance surface were constructed to identify ecological source areas and key nodes in the Sichuan-Yunnan ecological barrier area, aiming to lay a foundation for optimizing the ecological security pattern in the study area and provide a scientific basis for ecological protection and restoration. Method: Based on multi-source basic data in 2021 and the “ecological vigor-organization-resilience-ecosystem services” framework, software such as InVEST, Fragstats, and TerrSet were used to evaluate the spatial distribution of ecosystem health in the study area and determine the optimal ecological source protection plan. The random forest model was adopted to calculate the future land-use development probability, and a comprehensive ecological resistance surface was constructed by combining natural and social factors. The ecological security pattern of the study area was constructed through the circuit theory model. Result: In 2021, there were obvious spatial differentiations in the ecosystem physical health index, vigor, organization, and resilience of the ecosystem in the study area. The average values of the ecosystem physical health index and vitality were 0.533 and 0.546 respectively, showing a distribution pattern of high in the south and low in the north. The high-value areas were mainly distributed in the south, southwest, central, and north regions with diverse ecosystem types, abundant wildlife resources, high vegetation coverage, and sufficient water resources. The physical health and vitality levels in the northwest and east were relatively low. The average value of organization was 0.583. Affected by terrain barriers, the high-value areas were mostly in regions with flat terrain, good traffic connectivity, high vegetation coverage, and traversed by rivers. The low-value areas were concentrated in areas with complex terrains such as the Minshan Mountains, Micang Mountains, Qionglai Mountains, Daliang Mountains, and Gaoligong Mountains. The average value of resilience reached 0.667. The western and northwestern regions exhibited low values due to grassland degradation, salinization, and desertification caused by overgrazing. The areas with developed towns, intensively cultivated land, and lakes were also low values. The distribution of the ecosystem health showed a pattern of low in the west, northwest, east, and southeast and high in the northeast, central, and south. The average value of the comprehensive ecological resistance surface was 32.716, opposing the distribution trend of ecosystem health. The ecological security pattern included 210 ecological source areas with an area of 66 990.64 km², accounting for 28.28% of the total area. There were 511 ecological corridors with a total length of 5 951.475 km, showing a dense distribution in the west and sparse in the east. The general ecological corridors (250) were long and scattered, connecting relatively distant ecological sources. The important ecological corridors (178) were short and densely distributed, forming a corridor network with general corridors. The core ecological corridors (83) connected large-area source areas. A total of 143 ecological pinch-points and 248 ecological barrier points were identified, primarily distributed on general ecological corridors, with land uses mainly consisting of grasslands, other land uses and cultivated land. Conclusion: This study reveals the regional differences in the physical health, and the overall distribution pattern of the ecosystem health is “high in the north and south, low in the east and west”. The northeast, central, and south regions are the concentrated distribution areas of ecological source areas and pinch points, and the integrity of natural vegetation should be protected as a priority. The Aba Prefecture, Ganzi Prefecture, and Shangri-La region are significantly affected by natural factors and human activities and should be preferentially restored. Additionally, spatial planning of the northeast and south regions should be further optimized to coordinate the sustainable development of the ecosystem and the economy.

Objective: This study aims to compare the plasticity of root system structure and the seasonal variations of non-structure carbon in interspecific and intraspecific competition between Q. variabilis and P. tabuliformis, and elucidate the competitive mechanism in forest succession, so as to provide theoretical basis for the efficient cultivation of oak-pine mixed forests. Method: Two-year-old seedlings of Q. variabilis and P. tabuliformis were used as research objects, and three competition scenarios of P. tabuliformis–P. tabuliformis, P. tabuliformis–Q. variabilis, and Q. variabilis–Q. variabilis were set up. Root system structural traits and non-structure carbon were measured, and the two-factor analysis of variance was used to explore the effects of competition scenarios and seasons on root system structure and non-structure carbon were explored using. Result: Compared with intraspecific competition, the interspecific competition of P. tabuliformis–Q. variabilis inhibited the root length, root surface area, fine roots, and total root volume of P. tabuliformis seedlings, while the interspecific competition promoted the coarse root volume of Q. variabilis seedlings. The soluble sugar, starch and non-structural carbohydrate contents in fine roots and whole plant of P. tabuliformis seedlings under the P. tabuliformis–Q. variabilis interspecific competition were significantly lower than those in the P. tabuliformis intraspecific competition, while the above-mentioned indicators of Q. variabilis seedlings in the interspecific competition were basically higher than those in the Q. variabilis intraspecific competition, and the differences were even more pronounced at the end of August. Conclusion: Q. variabilis seedlings shows stronger adaptability and competitive advantage in P. tabuliformis–Q. variabilis interspecific competition. Both species can adjust their root system structure and non-structure carbon levels seasonally to optimize their competitive strategies. These findings help to understand the succession process of P. tabuliformis–Q. variabilis mixed forests and provide theoretic basis for efficient cultivation of P. tabuliformis–Q. variabilis mixed forests.

Objective: Based on continuous monitoring data of soil respiration and environmental factors in the fixed sample plots of stratified mixed stand of Eucalyptus spp. and Manglietia glauca, over a period of one year, a multi-factor prediction model for plantation soil respiration was constructed and screened, aiming to clarify key environmental drivers influencing the spatiotemporal variation of soil respiration in the plantations of the region, and provide a scientific basis for improving the accuracy of carbon emission simulations in plantations and calibrating large-scale predictive models. Method: The stratified mixed stand of E. spp. and M. glauca in Leizhou Peninsula was taken as the study object. Six machine learning algorithms (Random Forest, Time Convolutional Neural Network, Long and Short-Term Memory Network, Support Vector Regression, Extreme Learning Machine, and BP Neural Network) and two empirical models (Q₁₀ and Gamma) were introduced to simulate soil respiration changes at 1-hour and 24-hour scales. The accuracy evaluation metrics of the models were compared to select the optimal model algorithm suitable for the study area. Result: The soil respiration in the mixed forests was higher in the rainy season than in the dry season. Cumulative fluxes of soil respiration were 616.83 g·m^?2 in rainy season, 319.81 g·m^?2 in dry season, and 936.64 g·m^?2 throughout whole year. Six machine learning algorithms and two empirical models were able to successfully simulate soil respiration changes in the mixed forests, but the machine learning models outperformed empirical models. The Random Forest model achieved the highest consistency, with R² values of 0.89 (training set) and 0.76 (test set) using soil temperature and moisture as inputs. When the input variables increased soil electrical conductivity, soil heat flux, air temperature, air relative humidity, total solar radiation, and photosynthetically active radiation, R² values increased to 0.99 (training set) and 0.93 (test set). In addition to soil temperature and humidity, soil electrical conductivity significantly affected soil respiration. Conclusion: The soil respiration in a stratified mixed stand of E. spp. and M. glauca exhibits distinct temporal variation, machine learning algorithms are more advantageous than traditional empirical models in predicting soil respiration changes, among which the random forest model performs best. The predictive ability of the random forest model can be greatly improved by adding input variables such as soil electrical conductivity, and the addition of these factors can be a better prediction of soil respiration changes, which can provide a reliable basis for assessing the carbon sequestration status of plantations.

Objective: This study aims to investigate the impacts of typical sand-fixing vegetation（Caragana microphylla shrubs and Populus alba var. pyramidalis trees) on deep percolation and soil moisture in different hydro-meteorological years in Horqin Sandy Land, so as to provide a scientific basis for water management in forest and grassland ecosystems to support the “Three-North” Shelter Forest Program and the ecological restoration efforts in Horqin and Hunsanzhake sandy regions. Methods: During growing seasons (April to October) of 2022 (wet year) and 2023 (dry year), the real-time quantitative monitoring of deep percolation across typical shrub and tree vegetation covers and mobile sandy areas in Horqin Sandy Land was conducted by using a self-developed deep percolation recorder (YWB-01). The differences in deep percolation were compared between different sand fixing vegetation types in two different hydro-meteorological years on a daily and monthly scale. Soil moisture at 0–200 cm depths was monitored to elucidate variations in the relative extractable water in the shallow (0–40 cm), middle (40–120 cm), and deep (120–200 cm) soil layers between the wet and drought years. Finally, based on water balance analysis, the water replenishment capacity of different vegetation types was assessed. Result: 1) In each hydro-meteorological year, the relative extractable water in all soil layers was significantly higher in mobile sandy areas than in vegetated sites (P<0.05). There was no significant difference in the relative extractable water in shallow layer (0–40 cm) between shrub and tree sites, while the middle and deep layers (40–120 cm and 120–200 cm) had significantly higher relative extractable water in shrub sites compared to tree sites (P<0.05). 2) The variation characteristics of deep percolation across different hydro-meteorological years exhibited similar patterns in different vegetation types, with the highest percolation flux in mobile sand dunes, followed by shrublands, and lowest in forested areas. The magnitude of deep percolation was greater in the wet year than that in drought year. On daily scales, deep percolation in mobile sand dunes in different hydro-meteorological years exceeded that in shrublands at least approximately 73.86% of days, with an even higher proportion on a monthly basis. Throughout the study period, deep percolation was consistently higher in mobile sand dunes and shrublands than that in forested sites. 3) The evapotranspiration in shrub and tree vegetation was significantly higher in the wet year compared to the drought year. Shrublands contributed to soil water recharge, whereas forests led to soil moisture deficits. Conclusion: In different hydro-meteorological years, vegetation-covered sites exhibit significantly reduced deep percolation relative to mobile sand dunes at both daily and monthly scales, with a more pronounced reduction observed in forested sands. The relative extractable water within the soil profile beneath vegetation is markedly lower than in mobile sand dunes; forested sites consume more mid- and deep-layer soil water, resulting in notable soil moisture deficits.

Objective: This study aims to clarify the leaf-fine root phenotypic plasticity of Populus tomentosa and the response mechanism of growth rhythm to thinning, so as to provide theoretical reference for the optimization of efficient structural control techniques for fast-growing tree species. Method: The 8-year-old triploid P. tomentosa plantation in the North China Plain was taken as the research object, and three thinning intensities were set: no thinning (NT), alternate row thinning (50% thinning intensity, T50), and alternate row and alternate plant thinning (75% thinning, intensity T75). By monitoring the growth indicators and leaf and fine root traits of P. tomentosa after thinning, analyzing the diameter at breast height (DBH), leaf area growth rhythm and the plasticity of leaf and fine root phenotypes during the growing season of P. tomentosa, this study explores the growth strategies of leaves and fine roots under different thinning intensities and the coupling relationship with forest growth. Result: 1) Thinning had a significant impact on specific leaf area (SLA) and leaf mass per area (LMA). As the thinning intensity increased, the leaves had smaller SLA and greater LMA. Compared with thinning intensity, the influence of soil depth on fine root traits was more significant. Fine roots showed completely opposite growth strategies in shallow soil layers and deep soil layers. 2) The growth rhythm of DBH and leaf area change pattern in thinning treatment were similar to those of NT treatment: DBH growth started in early April and stopped at the end of October, showing a “slow-fast-slow” unimodal growth pattern. In mid-to-late March, P. tomentosa started to unfold its leaves. From early April to early May, it went through a period of rapid growth and development. From early May to early August, changes in the leaf area index were comparatively steady, and after August, it started to decline. 3) Thinning was able to promote the growth of DBH of P. tomentosa and extend the period of rapid DBH growth (July–August). At the end of October, the DBH cumulative growth in T75 and T50 treatments was significantly increased by 91.57% and 56.59% compared to the NT treatment, respectively. In addition, thinning was able to regulate the tree to form a larger canopy and promote tree growth, especially in the direction of thinning. 4) Leaf traits and root traits explained 88.25% and 72.31% of forest growth variation, respectively. Leaf traits positively regulated forest growth, while fine root traits negatively regulated forest growth. Among them, leaf mass per area (LMA) and fine root biomass density (FRBD) were the most interpretable phenotypic parameters. Conclusion: After thinning, the growth rate of DBH and leaf phenotype of P. tomentosa undergo plastic changes, but the growth rhythm of DBH and leaf area do not be changed. Thinning can adjust the SLA and LAM of the vegetative organs of the forest tree, adopt a “high investment-low return”single leaf growth strategy, and promote the diameter growth of P. tomentosa by forming a larger crown and a greater number of leaves. In addition, fine roots after thinning are more prone to shallow distribution, and preferentially choose the survival strategy of “changing their biomass distribution characteristics rather than morphological characteristics” to obtain water and nutrient resources.

Objective: To address the problems of complex detection images with ground penetrating radar (GPR), difficult interpretation, and low inversion accuracy in tree root zone, an improved fully convolutional networks (MWFCNet) based on migration weight guidance is proposed to invert the relative dielectric constant of tree root zone, achieving high-precision inversion and reconstruction of the underground relative dielectric constant environment in tree root zone, providing an efficient and reliable technical means for non-destructive testing of tree roots and detection of root zone soil environment, aiming to provide new tools and methods for in-depth research on the interaction mechanism between trees and soil dielectric environment. Method: The mature triploid Populus tomentosa root zone environment was taken as the research object. The open source software gprMax was used to generate GPR B-scan simulation samples, and combining CycleGAN to achieve sample style transfer, and construct 3 000 pairs of training samples for GPR B-scan and corresponding two-dimensional relative dielectric constant models of measurement line profiles. To solve the problem of poor inversion performance of background media by inversion networks, GPR migration image sequences and their corresponding migration weight sequences were introduced into the input module, and a network architecture with encoder decoder as the backbone was constructed. Two different convolution sizes were used for parallel processing, and multi-scale feature extraction of feature images was achieved through skip connections. The image features were further integrated with fully connected layers to enhance feature expression ability, and output a two-dimensional relative dielectric constant model of the measured root zone underground. Structural similarity index (SSIM) was selected, peak signal to noise ratio (PSNR), and mean squared error (MSE) were used as evaluation indicators for GPR inversion performance, and background variance was used as an evaluation indicator for the degree of background medium restoration. Result: Compared with existing methods such as Enc-Dec, U-net, PInet, etc., the MWFCNet method improved SSIM by 0.11%?3.23%, MSE by 0.11?0.73, and PSNR by 0.31?5.83 dB in the inversion of the same test set. In the restoration of the background medium, the background variance of the MWFCNet method decreased by 0.035?0.15. Conclusion: The MWFCNet based method for inverting the relative dielectric constant of tree roots can accurately identify the position of thick roots of trees, and also achieve two-dimensional reconstruction and restoration of the underground relative dielectric constant map of GPR survey lines. Combined with GPR sampling method, it can reconstruct and restore the three-dimensional relative dielectric environment of the root zone underground.

Objective: In order to address the technical challenge of transformation of hairy roots in medicinal plants, and based on the development potential of heterologous transformation technology, the fast-growing 84K poplar was selected to construct an efficient genetic transformation system of hairy roots in this study. Method: In this study, the tissue-cultured seedlings of 84K poplar were used as materials to construct an efficient hairy root genetic transformation system by comparing the strain types, explant types, bacterial liquid concentrations, and infection times. Furthermore, the downstream gene LOC110095726 (LOC2) of the terpenoid alkaloid synthesis pathway in Dendrobium nobile was cloned, and the effect of heterologous transformation was evaluated. Result: The best inducing strain was C58C1, and the induction rate of hairy roots reached 100% after 21 days. The average number of induced roots was 5.06 ± 2.36, the average root length was （12.83 ± 5.75） mm, and the transformation rate was 46.67% ± 11.55%. The best explant for induction was the leaf, and the induction rate of hairy roots reached 93.33% ± 11.55% after 14 days, with an average number of induced roots of 3.89 ± 2.53 and an average root length of （8.36 ± 4.24） mm. The optimal infection concentration was 0.8 （OD₆₀₀） value, and, the induction rate of hairy roots reached 100% after 21 days, with the average number of induced roots of 6.03 ± 2.10, and the average root length of （17.77 ± 9.23） mm. The optimal infection time was 15 minutes, and the induction rate of hairy roots reached 100% after 21 days, with an average number of induced roots of 6.03 ± 2.10 and an average root length of （17.76 ± 9.23） mm. LOC2 gene of D. nobile was successfully cloned into an overexpression vector and transferred into Agrobacterium rhizogenes C58C1. Positive hairy roots of LOC2 were obtained in 84K poplar. Conclusion: The optimal transformation system for the hairy roots of 84K poplar is to infect the leaves with C58C1 bacterial solution at a bacterial solution concentration (OD₆₀₀) of 0.8 for 15 minutes. This set of methods, with the advantages of simplicity, rapidity, high stability, etc., can be applied in the functional verification of active ingredients of metabolites in medicinal plants and the creation of plants with high active ingredients.This system is not only applicable to the functional verification of the active ingredients of medicinal plants with similar metabolic pathways, but also provides a reliable technical basis for the large-scale production of medicinal active ingredients.

Objective: In this study, multi-source data comprising natural climate variables, anthropogenic activity indicators, and geospatial features is used to analyze the key factors influencing the spread and expansion of pine wilt disease (PWD). Focusing on the ecological invasion process of PWD of ‘introduction-colonization-expansion’, a predictive model applicable at a fine spatial scale is constructed, aiming to achieve precise identification and early warning of high-risk outbreak areas of pine wilt disease. Method: This study utilized subcompartment-level outbreak records of PWD in Jiangsu Province published by the National Forestry and Grassland Administration of China. Based on the ecological characteristics and spatial distribution patterns of PWD, a total of 25 influencing variables were selected, covering natural climate conditions, human activity, and spatial features. Principal Component Analysis (PCA) was used for dimensionality reduction, and Spearman correlation analysis and the Apriori data mining algorithm were applied to examine the interactions between each influencing factor and the occurrence of PWD. Bayesian estimation was employed to enhance the feature of the variables. A Grey Wolf Optimizer-Cellular Automata (GWO-CA) model was constructed to simulate the spatiotemporal spread of PWD. The model’s predictive performance was further evaluated through horizontal comparison with five mainstream machine learning models, with precision, recall, and AUC as evaluation metrics. Result: The Grey Wolf Optimizer-Cellular Automata model developed in this study exhibited excellent performance in predicting the new occurrence of pine wilt disease in subcompartment. The model achieved a recall rate of 78.5%, and significantly outperformed the other five mainstream machine learning models. Additionally, the model yielded an AUC value of 89.0%, indicating a high level of predictive accuracy and discriminative ability in identifying new outbreak locations. This study also underscored the critical role of geospatial features in forecasting the spread of pine wilt disease, and confirmed the strong suitability of cellular automata for modeling complex spatiotemporal data, especially at fine spatial scales. Conclusion: This study has identified timber transportation as a key driver of the spread of pine wood nematode, and temperature and precipitation differences also exert significant influence on outbreak risk. As a modeling approach that integrates spatial heterogeneity and temporal dynamics, the Cellular Automata model has proven to be highly adaptable and effective for complex ecological data analysis and invasive species risk assessment. It offers robust technical support for the precise prevention and efficient management of pine wilt disease.

Objective: The existing blueberry fruit ripeness detection methods exhibit poor performance in complex natural environments and insufficient robustness against lens defocus blur and multi-angle imaging in actual harvesting operations, resulting in high contamination rates of unripe fruits and difficulties in ensuring harvest quality. Aiming at the above issues, an improved YOLOv9 detection method is proposed to achieve high-precision ripeness recognition, providing algorithmic support for vision-based dynamic adjustment of harvesting speed. Method: Based on the YOLOv9 model, MobileNetV4 was introduced into the YOLOv9 model as the backbone feature extraction network to reduce the number of parameters and computational burden of the network. Additionally, a GAM attention module was integrated into the neck network of YOLOv9, and the weight of each feature was adjusted to enable the model to better focus on the most important feature areas for target detection, thereby enhancing its ability to recognize key regions and improving detection accuracy and robustness. WIoU was employed as the loss function to optimize the model's localization accuracy, improve boundary box prediction accuracy, and accelerate network convergence. Blueberry harvesting experiments were conducted on a picking test platform to verify whether the model meets the precision and speed requirements for blueberry harvesters, and to determine the optimal harvesting speed when harvesting blueberries with different fruit maturity ratios. Result: The improved YOLOv9 model achieved a precision of 98.0%, recall of 97.2%, an average precision mean (mAP) of 98.2%, and a detection frame rate of 86.5 fps on the test set. Compared with SSD, Faster R-CNN, YOLOv5, and YOLOv8 models, the average precision mean improved by 6.8, 5.6, 4.0, and 2.7 percentage points, respectively. The improved model met the requirements of the harvesting system. When the proportion of mature fruits on blueberry plants was 90%~100%, 85%~90%, and 80%~85%, the optimal harvesting speeds were 125 r·min^?1, 130 r·min^?1, and 140 r·min^?1, respectively. Conclusion: The improved YOLOv9 model has significantly enhanced detection performance compared to the original model. The optimal harvesting speeds obtained through blueberry harvesting tests can reduce the rate of unripe fruits, providing strong technical support for the intelligent harvesting of blueberries.

Objective: This study aims to explore the influence of moisture content (MC) and temperature (T) on acousto-ultrasonic (AU) parameters of Larix gmelinii wood in order to provide theoretical basis and scientific basis for the application of acousto-ultrasonic nondestructive testing technology in wood research field. Method: Four acousto-ultrasonic parameters including wave velocity (V), amplitude voltage (A), root mean square voltage (RMS), frequency-centroid (FC) of small clear specimens of L. gmelinii were measured under four moisture content levels (6%, 12%, 24%, 85%) and four temperature levels (?20 ℃, 0 ℃, 20 ℃, 40 ℃). The significance of difference and changes of each AU parameter under different moisture content and temperature conditions were compared, the influence of moisture content and temperature on different acoustic-ultrasonic parameters of wood and the reasons were analyzed. Result: 1) Moisture content and temperature had significant effects on each acousto-ultrasonic parameter of wave velocity, amplitude voltage, root mean square voltage and frequency centroid (P<0.05), and the interaction between moisture content and temperature was extremely significant (P<0.001). 2) The wave velocity, amplitude voltage and root mean square voltage decreased with the increase of moisture content at the temperature of 0 ℃, 20 ℃ and 40 ℃. The wave velocity decreased with the increase of moisture content, but the change trend of amplitude voltage, root mean square voltage and frequency-centroid was not obvious and the change range was small at the temperature of ?20 ℃. 3) The difference of the frequency-centroid among the moisture content of 6%, 12% and 24% was small, and the frequency-centroid of the moisture content of 6%, 12% and 24% were all significantly higher than that of the moisture content of 85% at the temperature of ?20 ℃, 0 ℃, 20 ℃ and 40 ℃. 4) Temperature had little effect on wave velocity, amplitude voltage, root mean square voltage and frequency-centroid at the moisture content of 6%, 12% and 24%. The amplitude voltage, root mean square voltage and frequency-centroid at the temperature of ?20 ℃ were significantly higher than those at other temperatures, the differences among amplitude voltage, root mean square voltage and frequency-centroid at the temperature of 0 ℃, 20 ℃ and 40 ℃ were not significant, and there was no significant difference in wave velocity at the temperature of ?20 ℃, 0 ℃, 20 ℃ and 40 ℃ (P>0.05) at the moisture content of 85%. Conclusion: 1）For saturated larch wood, the water freezing significantly enhances the propagation ability of ultrasonic wave at the temperature of ?20 ℃. The amplitude voltage, root mean square voltage and frequency-centroid at the temperature of ?20 ℃ increases significantly compared with the temperature of 0 ℃, 20 ℃ and 40 ℃, but the change of wave velocity is not significant. For larch wood below fiber saturation point, temperature has little effect on ultrasonic wave propagation in wood. 2) When the temperature is greater than or equal to 0 ℃, moisture content has a significant effect on the propagation velocity and energy attenuation of ultrasonic wave in wood due to the viscosity of water, and the wave velocity, amplitude voltage and root mean square voltage decrease with the increase of moisture content. The wave velocity also tends to decrease with the increase of moisture content at the temperature of ?20 ℃. However, the moisture content has no significant effect on the propagation energy of ultrasonic wave in wood due to the phase change of water, and the change amplitude of amplitude voltage and root mean square voltage is small. 3) When the temperature is above or equal to 0 ℃, the influence of moisture content on the frequency-centroid is very small if the moisture content of wood is lower than the fiber saturation point, while the frequency-centroid decreases significantly if the moisture content of wood is higher than the fiber saturation point, because a large amount of free water in the cell cavity leads to the attenuation of high-frequency components in the ultrasonic signal. Moisture content has no significant effect on frequency-centroid atthe temperature of ?20 ℃.

Objective: Through resolving the differences in the physical and mechanical properties of Larix gmelinii var. principis-rupprechtii (larch) timber with different north-south orientation, this study explored the mechanisms underlying crack development in wooden columns during outdoor exposure, aiming to provide scientific theoretical guidance for the rational utilization of larch logs and solid wood. Method: Based on the growth characteristics of the trees, the southern edge and the northern edge trees of larch on the shady slope were selected as research subjects to analyze the influence of north-south orientation on growth ring width, microstructure, and physical-mechanical properties of wood. Additionally, an outdoor exposure test of log columns covered with a roof was performed to explore the impact of orientation on cracking in log columns. The changes in the length and width of cracks, as well as the crack locations, were recorded at monthly intervals. Result: Influenced by the comprehensive environmental factors, both the south edge and the north edge trees of larch exhibited wider annual ring of the northward growth. At the same tree height of a larch tree, there were no significant differences in microscopic morphology between the north-facing and south-facing samples. The air-dried moisture content of the north-facing samples was higher than that of the south-facing samples, but the density and shrinkage in all orientation of the south-facing samples were higher than those of the north-facing samples. The variation pattern in mechanical strength was highly positively correlated with the density trend. The north-south difference in mechanical strength of the northern edge wood was the greatest, and the bending strength, bending modulus of elasticity, and parallel-to-grain compressive strength of the south-facing sapwood were 53.7%, 76.9%, and 21.4% higher than those of the north-facing sapwood, respectively. During the 10-month outdoor exposure test of the larch log columns, cracks appeared rapidly after the bark was removed due to the moisture gradient formed between the inside and outside of the log. The moisture content of the sapwood decreased rapidly from 110%?130% to 54%?70%, while the moisture content of the heartwood remained relatively stable at 30%?38%. At this point, cracks were primarily manifested by an increase in length, with the width remaining relatively unchanged. When the moisture content of the sapwood decreased to the fiber saturation point (15%?21%), the crack length remained stable, but some cracks continued to widen. As the overall moisture content of the log columns dropped to 13%?15%, the crack morphology tended to stabilize. The south edge larch samples were more prone to develop larger cracks compared to the north edge ones. Sunlight exposure was the key factor influencing the crack distribution in the upright log columns. The exposure to sunlight due to their orientation can be a dominant factor influencing the distribution of cracks in the upright log columns. Conclusion: Within the scope of this experiment, the width of growth rings is a determinative factor for the differences in the physical and mechanical properties of wood between the southern and northern edge trees of larch. By measuring the width of the growth rings within the same larch plant, the differences in wood properties at different positions can be predicted. Moreover, cracks in log columns are more likely to propagate on surfaces with narrower growth rings during the outdoor exposure process of wooden columns. In practical use, positioning the wider growth ring side of the log columns against the sun can effectively reduce the appearance of cracking.

Objective: In response to the current problems of high labor intensity, low transportation efficiency, high labor costs, and frequent safety accidents caused by manual handling and towing of bamboo products after logging, a UAV-based bamboo product and epidemic wood downhill lifting system was designed to enable the function of using UAVs for autonomous lifting in bamboo forests and emergency rescue in dangerous situations to protect UAVs, reduce manual involvement, ensure the safety of operators, and overcome the problem of large vertical drops in mountainous areas. Method: The measured morphological characteristic parameters of bamboo shoots and bamboo segments were used to design a hanging automatic decoupling device and a UAVs emergency rescue device. A 3D model of the devices was established using SOLIDWORKS software, and the corresponding hardware and software systems for operating the equipment were developed. Static structural analysis of ANSYS Workbench software and magnetostatic analysis were conducted using ANSYS Workbench to simulate and calculate the key structures of the lifting device and determine the structural parameters and electromagnet model. Indoor experiments were conducted to analyze the efficiency of the packaging methods (velcro, concave hooks, and knots), the stability of decoupling methods (gravity hooks and electromagnetic active hooks), and the feasibility of the escape mechanism. Forest experiments were also conducted to test the efficiency and stability of the entire lifting system in real working scenarios. Result: Indoor tests showed that the average time was 21 s for the velcro packing, 22.2 s for the concave hook group, and 25.8 s for the knot group, leading to the selection of velcro for packing. The success rate for gravity hook disengagement was 80%, while the success rate for electromagnetic active hook disengagement was 90%, confirming the adoption of the electromagnetic active hook detachment method. Field test results showed a disengagement success rate of 90%, with an average hook hanging time of 14.69 s and an average disengagement time of 1.19 s. The success rates for disengagement during ascending, descending, and forward flight were 80%, 90%, and 90%, respectively. Conclusion: The bamboo product and epidemic wood downhill lifting system based on UAV-based lifting system can reduce manual involvement, improve transportation efficiency, lower labor costs, and reduce the probability of safety accidents. Experiments have demonstrated that the system meets the requirements for on-site applications.

In recent years, China has been actively developing forestry Internet of Things (IoT) technology in order to promote modernization of forestry and facilitate the high-quality and smart development of forestry and grassland. Firstly, this paper outlines the development process of forestry IoT both domestically and internationally. Next, this paper introduces key technologies in the field from three aspects: perception, communication, and platform management. It elaborates on important technologies in the field of forestry IoT, such as radio frequency identification (RFID), sensors, ZigBee, LoRa, NB-IoT, data storage and quality control, and security and access control. On this basis, this paper analyzes in-depth the application of forestry IoT in many scenarios, such as forests, grasslands and wetlands resources supervision, forestry ecological environment monitoring, forest disaster monitoring and early warning, wildlife monitoring, intelligent supervision of nature reserves, and forestry industry. Forestry IoT is an important component of integrated sky-ground monitoring in forestry, playing a significant role in real-time collection of ground surveys and high-frequency, fine-scale observational data. It also serves as a crucial means for early monitoring and warning of forest fires and pests. Moreover, it plays an important role in rapidly developing fields such as traceability of forest products, ecotourism, and forest wellness in recent years. Analysis of the current application of forestry IoT reveals that although forestry IoT technology has been widely applied in various fields, there are still bottlenecks in the development of forestry IoT in China, such as an incomplete standard system, insufficient independent research and development capabilities for specialized sensors, and weak power and communication infrastructure in remote forest areas. Domestically developed forestry sensors still lag behind foreign counterparts in terms of accuracy, stability, and reliability. The challenges in power supply and communication continue to hinder the long-term, continuous, and automated acquisition and updating of forestry IoT monitoring data. In terms of data processing and analysis methods, new technologies and approaches such as artificial intelligence have not yet been effectively applied in certain forestry areas. Furthermore, forestry data sharing mechanisms and the protection of sensitive ecological data security still require further development and refinement. Finally, in response to the aforementioned challenges, this paper presents a forward-looking perspective on the development of forestry IoT in China. This includes promoting the establishment of a forestry IoT standard system through multi-stakeholder collaboration, developing forestry sensors with proprietary tailored to specific application scenarios and environments, and exploring multi-energy complementary field power supply system alongside intelligently integrated multi-network communication technologies. It also emphasizes advancing fundamental theories and intelligent algorithms for forestry IoT data analysis, systematically establishing the data security management framework for forestry IoT, and promoting the application of technologies such as drones, artificial intelligence, edge computing, and blockchain within the forestry IoT ecosystem. By reviewing the current application status of forestry IoT globally and the challenges faced in China, this paper aims to provide valuable insights for the advancement of forestry IoT and the development of smart forestry and grassland in China.

With the growing demands for wildlife conservation and ecological monitoring, deep learning-based image recognition methods have been increasingly applied in wildlife research. This paper first introduces commonly used public datasets for wildlife, provides a detailed review of the applications of different deep learning techniques in wildlife image recognition, classifies these recognition methods into three levels (image-level, object-level, and pixel-level) based on task requirements, and focuses on discussing the specific implementation and technical details of the methods at each level. On this basis, the paper further explores the core challenges faced by wildlife image recognition, including various data-level issues such as uneven data quality, high annotation costs with low efficiency, and imbalanced sample distribution. Meanwhile, it also analyzes several key technical problems from the perspective of models and algorithms, including fine-grained detection, cross-domain distribution shift, class-incremental learning, zero-shot learning, and cross-modal learning. In response to the above challenges, the paper summarizes the current research progress and coping strategies, and proposes potential future development directions, aiming to provide theoretical support and methodological references for constructing an efficient, robust, and practically applicable intelligent recognition system for wildlife in real monitoring scenarios.

Objective: This study aims to develop conversion models between the stand dominant height and the mean height of the four larch species (Larix spp.), providing a basis for evaluating the site quality and predicting the growth of larch plantations. Method: Based on the survey data of national forest and grass ecological comprehensive monitoring of plantation plots of Larix species from the 2021 and 2022, dual regression and mixed-effects models were applied to develop conversion models for stand dominant height and mean height. Model performance was assessed using residual sum of squares, coefficient of determination (R²), root mean square error (RMSE) and relative root mean square error (rRMSE). Result: 1) The conversion model between stand dominant height and mean height based on the dual regression model method performed the best, outperforming the linear mixed effect model approach. The dual regression model method had average R² exceeding 0.92, average RMSEs between 1.31 m and 1.34 m, and average rRMSEs between 9.63% and 9.85%, and was able to achieve mutual prediction between stand dominant height and mean height. 2) Incorporating tree species and province (city) groups into the dual regression model further improved model accuracy, and the model including province (city) groups showed higher accuracy. Conclusion: The dual regression model in incorporating province (city) groups had good applicability and predictive performance in establishing the conversion relationship between stand dominant height and mean height. This approach offers a more accurate and basic forecasting model for site quality evaluation of larch plantations.

Objective: Under altered precipitation patterns driven by global climate change, this study investigates the effects of throughfall reduction on soil macrofaunal communities in Quercus mongolica (Mongolian oak) forests of the Sanjiang Plain. The focus is on analyzing the changes in community composition, diversity, and trophic structure, providing a scientific basis for accurately predicting the potential impacts of climate change on biodiversity within the ecological function zone of Northeast China. Method: A throughfall reduction experiment was conducted at the Heilongjiang Fuyuan Forest Ecosystem Observation and Research Station from July to September 2024. Polyethylene permeable (PEP) membranes were utilized to intercept throughfall, achieving a 50% interception rate in the treatment group while maintaining natural throughfall conditions in the control group. Three pairs of treatment-control plots, each measuring 20 m by 20 m, were randomly established. To verify treatment efficacy, soil water content in the 0–10 cm layer was measured using the oven-drying method. Results showed that soil water content in the treatment group was on average 22.29% lower than in the control group, confirming that throughfall interception effectively achieved the experimental objective. Subsequently, both pitfall trapping and hand-sorting methods were employed to assess the composition and abundance of soil macrofauna. Furthermore, multiple soil physicochemical parameters were assessed, including soil organic matter, pH value, and soil fertility indicators such as total nitrogen, ammonium nitrogen, nitrate nitrogen, total phosphorus, and available phosphorus. The effects of throughfall reduction on the community composition, diversity, and trophic structure of soil macrofauna in Mongolian oak forests at the Sanjiang Plain were then analyzed. Result: 1) During the study period, a total of 23 953 soil macrofauna individuals were collected, belonging to 4 classes, 13 orders, and 34 families. The Formicidae family was the dominant group, accounting for 77.77% of the total. There were no significant differences in the community composition of soil macrofauna under throughfall reduction conditions compared to the control group. 2) The reduction in throughfall significantly increased the abundance of soil macrofauna and the Simpson dominance index (P<0.01), while significantly decreasing the Shannon-Wiener diversity index and Pielou evenness index (P<0.001). It had no significant effect on the richness of functional groups. Simultaneously, it significantly increased both the abundance and richness of carnivorous groups as well as the abundance of omnivorous groups (P<0.05). 3) Under throughfall reduction conditions, the soil macrofaunal community was predominantly influenced by available phosphorus, ammonium nitrogen, and soil organic matter. 4) The decrease in throughfall predominantly affected soil organic matter, pH value, and soil fertility indicators (such as total nitrogen, ammonium nitrogen, nitrate nitrogen, total phosphorus, and available phosphorus) through alterations in soil water content. Additionally, it had no discernible direct or indirect effects on the trophic structure of soil macrofauna. Conclusion: Throughfall reduction treatment increases the abundance of soil macrofauna in the Mongolian oak forest in the Sanjiang Plain while concurrently suppressing its diversity. This suppression, in turn, influences the availability of soil organic matter, pH value, and soil fertility for soil macrofauna. The projected future decline in throughfall in China’s Sanjiang Plain may lead to decoupled responses between soil physicochemical properties and soil macrofauna in Mongolian oak forests. Such disconnection could simplify the structure of soil macrofaunal communities, ultimately compromising the diversity and stability of these communities.