Objective: Community composition, structure, and interspecific correlations in dominant natural populations of Betula fujianensis, an endangered species in Luoboyan Nature Reserve of Fujian Province were investigated to reveal the interspecific relationships of the main species at different levels of B. fujianensis community, and mechanism of threatening the speceis, in order to provides a theoretical basis for the protection, habitat creation and population restoration of B. fujianensis community. Method: Based on the investigation of sample plots, the interspecific correlations in arbor, shrub and herb layers of the dominant population of B. fujianensis natural forest was studied using variance ratio, Pearson correlation test and Spearman rank correlation test, and ecological species groups were identified at different levels based on principal component analysis (PCA). Result: There were 207 species belonging to 133 genera and 89 families in the B. fujianensis community, including 64 species belonging to 40 genera and 25 families in the arbor tree layer, 112 species belonging to 63 genera and 39 families in shrub layer and 31, species belonging to 30 genera and 25 families in herb layer. The B. fujianensis is the first dominant species in the arbor tree layer, with an importance value of 23.55, followed by Phoebe bournei and Ilex formosana, with an importance value of 7.40 and 4.32, respectively. In the shrub layer, the first dominant species is Sarcandra glabra, with an importance value of 10.23, followed by Eurya loquaiana, E. weissiae, and Castanopsis fissa, with an importance value of 7.35, 5.31 and 5.09, respectively. The dominant species of herb layer are Woodwardia japonica, Plagiogyria adnata and Nephrolepis auriculata, with importance values of 17.24, 14.80, and 10.51, respectively, followed by Angiopteris fokiensis, Selaginella doederleinii, and Coniogramme japonica, with an importance values of 6.82, 6.67, and 5.13, respectively. The arbor tree layer and shrub layer showed significant positive association, while the herb layer showed non-significant positive association, indicating that the B. fujianensis community is generally stable.The results of Pearson correlation test and Spearman rank correlation test showed that the species pairs of significant positive correlations is greater than those of significant negative correlations among dominant populations in the community, and mainly of the species pairs are not significantly correlated or uncorrelated, indicating that most species have an independent distribution pattern. No significant correlation was found among B. fujianensis and Phoebe bournei and other tree species in the arbor tree layer, but the B. fujianensis is facing great competitive pressure in succession process due to its poor regeneration, and the P. bournei has become the first dominant tree species with good regeneration cycle. According to the correlations between species and PCA analysis, the ecological species groups of different layers were identified. The arbor tree layer and the shrub layer can be divided into four ecological groups, and the P. bournei in the arbor tree layer is a single group, which shows that it has a high independence, while the herb layer can be divided into three ecological groups. The species within the groups have convergent adaptability to the habitat, and the species among the groups have different ecological requirements. Conclusion: The community of B. fujianensis is generally stable, most of the populations are not significantly correlated or uncorrelated, most of the species have independent distribution. As the dominant tree species in the arbor tree layer, B. fujianensis is facing great competitive pressure in the process of succession due to its poor regeneration. The results are of great theoretical and practical significance for the protection and restoration of B. fujianensis community.

Objective: The main purpose of this study is to investigate the effects of distances to and diameters at breast height (DBH) of neighboring trees on fine root biomass with different stocking densities, and to reveal the main factors affecting root biomass, for providing a theoretical basis for formulating a reasonable root sampling plan. Method: In Fraxinus mandschurica plantations with four stocking densities (Treatment Ⅰ to Ⅳ: 3 572, 3 128, 2 215 and 1 468 hm^-2, respectively), we employed the method of random sampling to estimate the biomass respectively of absorptive roots (diameter ≤ 0.5 mm) and fine roots (diameter ≤ 2.0 mm) in soil layers of 0-10, 10-20, and 20-30 cm and the totals of all soil layers, and measured the distance to and the DBH of the tree closest to the sampling point and four nearest neighbor trees. Linear regression analysis was used to examine the relationship between root biomass and the distance to and the DBH of the neighbor trees. Result: The total biomass of absorptive and fine roots (0-30 cm soil depth) significantly varied with stocking density, both of which showing the maximum in the stand with the lowest stocking density. From stocking density Ⅰ to Ⅳ, the proportions of biomass of absorptive roots in fine roots were 61.6%, 54.3%, 52.9%, and 63.4%, respectively. In all stands, more than 50% biomass of the fine roots and absorptive roots are distributed in the soil layer of 0-10 cm. In all the four stocking densities, there were no significant correlations between the total absorptive root or fine root biomass and the distance from the sampling point to the nearest one or four trees (P>0.05), except for the significantly positive correlation (P < 0.05) between fine root biomass in 10-20 cm soil layer and the mean DBH of the nearest four trees in the treatment Ⅲ. Compared with the total fine root biomass, the total absorptive root biomass showed a more general correlation with the DBH of neighbor trees, but the significance level of the correlation was related to the specific stocking densities. Both absorptive root and fine root biomass was positively correlated with the DBH of the nearest tree in the treatment Ⅰ (both R² >0.19), and with the mean DBH of the four neighbor trees in the treatment Ⅱ (both R²> 0.21). The correlations between the absorptive root biomass and the DBH of the nearest tree or the mean DBH of the four neighbor trees were significant in the treatment Ⅲ (both R²> 0.16), while no correlation was found in the treatment Ⅳ. Among the 3 soil layers, significant correlations between the biomass of absorptive roots and fine roots and the DBH of neighboring trees mainly occurred in the 0-10 cm soil layer, which showing similar patterns to that of the totals in 0-30 cm soil layer. Conclusion: According to our findings in the variations of the fine root biomass in F. mandschurica plantations, the distance between the sampling point and the neighboring trees can be set flexibly. It is necessary to consider the potential impact of the size of the neighboring trees around the sampling point, thus set the sampling points around the standard trees is an appropriate approach

Objective: Airborne LiDAR is an advanced technology used for the inventory and monitoring of forest resources and ecology, many site-specific and species-specific models had been developed for the estimation of forest inventory attributes. However, the estimations between forest types derived from these models were poorly comparable, thus it would be necessary to develop a model or formula with a stable structure and being suitable for various forest types. Method: In this paper, a south subtropical hilly region with an area of 22 100 km² was taken as the study site to estimate three forest attributes such as the stand volume(VOL), basal area(BA) and mean diameter at breast(DBH) of four forest types(Chinese fir, masson pine, eucalyptus and broadleaf forest) using the airborne discrete return LiDAR and field plot data. Seven LiDAR-derived metrics which describing the complementary 3D structural aspects of the stand canopy were selected to construct five multivariate power models. We tested the performances of these models with 383 field plot measurement data. Result: The results indicated that the model consisting of the LiDAR-derived mean point cloud height, canopy coverage, variation coefficient of leaf area density, variation coefficient of point cloud height distribution and 50% height quantile density had the best performance. The R² of VOL prediction models of four forest type were 0.765, 0.711, 0.748 and 0.683, respectively, the relative root mean square error(rRMSE) ranged from 18.53% to 36.32%, and the mean prediction error(MPE) ranged from 3.37% to 6.95%. The R² of BA estimation models were 0.572, 0.582, 0.706, and 0.568, respectively, the rRMSE ranged from 16.11% to 30.82%, and the MPE ranged from 3.27% to 5.89%. The R² of DBH estimation models were 0.574, 0.501, 0.709 and 0.240, respectively, the rRMSE ranged from 1.09% to 28.27%, and the MPE ranged from 1.83% to 5.55%. The relative differences of R² between the optimal generalizing formula and the optimal model of three attributes of four forest types were less than 5%, and those between rRMSE and MPE were less than 7%. Conclusion: The metrics of our model offer clear insights on forestry biophysics, have greats in forestry analytics by accurately depicting the three-dimensional structure of the stand canopy, and perform well in the estimation of various forest types and different forest parameters. The model provides accurate generalization for adaptation, which is beneficial to the operational application of the airborne LiDAR technology on the dynamic monitoring of forest resources.

Objective: Aiming at the problems of high cost, low timeliness and poor uniformity of the results of traditional forest inventory method, based on multi-source remote sensing data, machine learning method was used to select characteristic variables and establish an estimation model to make the map products of aboveground biomass(AGB) in the study area in order to provide technical means for forest resource information survey. Method: Taking the northwest of Hunan Province as the study area, the AGB reference values of 393 sample plots were selected by using allometric growth equations to convert the survey data into AGB. The Landsat-8 data were used as the optical remote sensing data source to extract spectral information, vegetation index, texture feature and the components of tasseled cap transformation. ALOS PALSAR-2 and Sentinel-1 data were used as radar remote sensing data sources to extract backscatter intensity and normalized polarization difference index for each polarization mode. A total of 122 candidate feature variables were obtained including topographical variables(elevation, slope and aspect). Multivariate linear regression(MLR), random forest(RF) and support vector regression(SVR) models were established after selecting the modeling variables by stepwise regression and random forest method. Using the coefficient of determination(R²) and root mean square error(RMSE) as model evaluation index, the models were evaluated by ten-fold cross-validation method, the best model was selected to complete biomass mapping, and five biomass map products at China or global scale were selected for comparative analysis. Result: For the training set, the random forest model performed the best with RMSE=12.8 mg·hm^-2, rRMSE=21.1%, and R²=0.93, which fitted the data well, followed by the support vector regression model (RMSE=26.1 mg·hm^-2, rRMSE=43.3%, R²=0.55) and the multivariate linear regression model(RMSE=30.9 mg·hm^-2, rRMSE=50.5%, R²=0.39). On the test set, the model performance achieved by RF method (RMSE=30.1 mg·hm^-2, rRMSE=51.3%, R²=0.42) was also better than that of MLR(RMSE=32.6 mg·hm^-2, rRMSE=54.1%, R²=0.30) and SVR(RMSE=32.8 mg·hm^-2, rRMSE=55.3%, R²=0.25). At the same time, all three models showed a certain degree of underestimation over small AGB and overestimation over large AGB. The RF model selected 13 modeling variables, including PALSAR-2 backscatter information, elevation and Landsat-8 spectral information, vegetation index, and the difference between tasseled cap transformation humidity and greenness components. Regional biomass mapping was completed using the RF model. Compared with other products, this model could basically reflect the distribution of biomass in the study area and showed abundant detailed information on biomass distribution. The range of biomass in the study area was 0-119 mg·hm^-2, the average biomass was 37.5 mg·hm^-2 and the standard deviation was 35.9 mg·hm^-2. Conclusion: Combined with multi-source remote sensing data and machine learning algorithm, large-scale biomass could be accurately and quickly calculated, which would be great application potentials. Compared with SVR model and MLR model, RF model performed better in AGB estimation for the study area. The RF algorithm could effectively select variables for AGB machine learning modeling from multi-source variables.

Objective: Based on the national forest inventory sample plot data of larch plantation in northeast China, the best model form of biomass conversion and expansion factor(BCEF) were discussed, and the spatial autoregressive BCEF model was established for larch plantation in northeast China. The model is useful for accurate stand biomass estimations. Method: Selecting a variety of model forms to establish BCEF general regression model, from which the best fitting model is selected. The two spatial autoregressive methods, spatial error model(SEM) and spatial lag model(SLM), were used to renew the BCEF model. The determination coefficient(R²), root mean square error (RMSE) and relative root mean square error(rRMSE) were used to evaluate the model. Moran index(MI) was applied to test the spatial autocorrelation of all variables and BCEF model residuals. Result: 1) There is obvious spatial autocorrelation in BCEF data. When the spatial distance is small, the BCEF attributes of stands within a province are similar. The differences of BCEF attributes among provinces are gradually appeared with the increase of spatial distance, and tend to random distribution finally. 2) The fitting results of allometric model, logarithmic model and hyperbolic model are better than those of other regression models, and the optimal models varied with independent variables. Stand quadratic mean diameter (D_g) is the best variable for interpreting BCEF. The R² of the effective model with D_g as an independent variable is between 0.945 and 0.958. Followed by stand mean height(H) and volume(V), the R² of the effective model is more than 0.60. The explanatory ability of stand average age is slightly lower than that of D_g, H and V, and the R² of its effective model is only about 0.50. Stand basal area(BA) and density(N) are poorly to explain the variance of BCEF with R² less than 0.50. The residuals of the general regression model showed spatial autocorrelation. 3) The spatial autoregressive model of hyperbolic function with D_g as an independent variable is the best one with SEM better than SLM. Compared with the corresponding ordinary regression model, the R² of SEM is increased by 3%, and the RMSE and rRMSE are reduced by 33% and 35%, respectively. The MI of the model residual is less than 0.02, which eliminates the spatial autocorrelation. Conclusion: The hyperbolic model is the most stable model for BCEF, and D_g is the best independent variable. It is recommended to adopt the hyperbolic function with the inclusion of spatial error model and with D_g as the predictor to estimate BCEF.

Objective: The objective of this study is to explore the effect of aerated irrigation on the growth of Malus hupehensis and the rhizosphere soil environment, which would provide reference for the effects of this irrigation method on fruit trees under field cultivation. Method: In this study, one-year-old and two-year-old potted M. hupehensis seedlings were used as test materials. Three kinds of irrigation water with different oxygen content were set up to explore their effects on the growth of aboveground part, and the response of root systems to the treatments, and the differences of enzyme activity and microbial community in the rhizosphere soil were investigated. Result: The treatment with oxygen content of (5±0.1) mg·L^-1 in the irrigation water had the best significance. The plant height, ground diameter and aboveground dry weight of one-year-old seedlings were significantly increased by 37.1%, 35.0% and 50.3%, and those parameters of two-year-old seedlings were significantly increased by 17.1%, 16.4% and 17.2%, respectively. This treatment promoted to different degrees the photosynthetic performance and fluorescence characteristics of plant leaves, and the contents of nitrogen, phosphorus, potassium, calcium, magnesium, iron and zinc were significantly increased. The root length, root surface area, root tip number and root respiration rate of the seedlings treated with oxygen content of (5 ±0.1) mg·L^-1 in the irrigation water were significantly higher than those in other treatments. The activities of root antioxidant enzymes such as SOD, POD, CAT in the treatment with oxygen content of (5±0.1) mg·L^-1were higher than those in other treatments, and the treatment with oxygen content of (5±0.1) mg·L^-1significantly increased the activities of soil sucrase, urease and phosphatase, increased soil micro bacteria and actinomycetes, and reduced fungi. Conclusion: The oxygen content in irrigation water ranges from (1±0.1) mg·L^-1 to (5±0.1) mg·L^-1. The higher the oxygen content is, the more obvious the effect on the improvement of potted M.hupehensis growth. The higher the oxygen content the more obvious the effect on soil environment in root area and soil microbial structure.

Objective: This study aimed to provide references for exploring the mechanism of walnut resistance to anthracnose. For this end, we identified 130 phenolic compounds after the infection of Colletotrichum gloeosprioides into the walnut husk, carried out absolute quantification of the compounds, analyzed their changes, and screened the potential effective components against anthracnose. Method: In this study, walnut (Juglans regia) cultivars, 'Xiangling' and 'Taile', were used as the materials, and the walnut husk were inoculated with C. gloeosporioides, then the contents and related changes of phenolic compounds in walnut husk after infection were analyzed by targeted metabonomics. Result: With the increase of days after infection of C. gloeosporioides, the plaques on 'Xiangling' husk gradually increased and changed significantly on the 6th day, while the plaques on 'Taile' husk remained basically unchanged. The total amount of phenolic compounds in 'Xiangling' and 'Taile' husk was basically the same. The compounds were divided into 9 categories, among which were mainly procyanidins/anthocyanins, benzoic acid derivatives, flavonols and phenylpropanoids. 'Xiangling' had the most benzoic acids, accounting for more than 60%, and they were mainly gallic acid, syringic acid, ellagic acid and vanillic acid. While 'Taile' contained the most flavonols, nearly 30%, and they were mainly hyperin, quercitrin, avicularin and myricetin. On the 6th day of anthracnose infection, comparing with 'Xiangling', there were 60 different metabolites in 'Taile', among which52 different metabolites were up-regulated and 8 different metabolites were down-regulated. Among them, epicatechin 3-O-gallate, 4-Hydroxycinnamic acid, proanthocyanidin B1/2/3, phlorizin, syringic acid, ellagic acid and ferulic acid had significant differences. In addition, 47 substances such askaempferol and m-coumaric acid were not detected. On analysis of the differential metabolites in the 'Xiangling' and 'Taile' husk infected for 4-6 days with anthracnose, it was found that 6 compounds of caffeic acid, naringenin, eriodictyol, avicularin, quercetin and gallic acid changedobviously, which might be related to the significant changes in husk plaques. Conclusion: We have identified 130 phenolic compounds in the anthracnose resistant cultivar 'Taile' and the susceptible cultivar 'Xiangling'. Potential effective components against anthracnose, including proanthocyanidin B1/2/3, caffeic acid, naringenin, eriodictyol, avicularin, quercetin and gallic acid, have been screened by analyzing the dynamic changes of substances after anthracnose infection by using metabolomics. This study would provide references for the later development of anthracnose-related natural medicines and for exploring the mechanism of anthracnose.

Objective: Differences in flower morphology and flower aroma components of different aroma types of Chionanthus retusus were investigated in order to reveal the patterns of temporal and spatial dynamics of the aroma components. The study lays a foundation for further effective development and utilization of the flowers and genetic improvement of the floral aroma of C. retusus. Method: Morphological characteristics of C. retusus of different aroma types were observed and analyzed by recording the total number of flowers, the total length of inflorescence, the length of floral branches, the length and width of corolla lobes, the length and width of sepals. Meanwhile, headspace solid-phase microextraction(HS-SPME) and gas chromatography-mass spectrometry (GC-MS) were used to analyze the aroma components of different aroma types and the diurnal variation of aroma components at full flowering stage of strong aroma type. Result: Morphological differences of flowers of different aroma types were mainly reflected in the color and shape of corolla lobes. At the full flowering stage, there were significant differences in the total number of florets, the total length of inflorescence, the length of flower branch, the length and width of corolla lobes and the length and width of sepals of different floral aroma types. Among them, the strong aroma type had the largest number(49) of flowers, the longest(112.67 mm) inflorescence, the largest corolla lobes and sepals, while its flower branches were shorter(45.00 mm) than those of the non-aroma type(66.67 mm) and longer than those of the medium aroma type(38.00 mm), displaying in general larger number of flowers, longer inflorescence and larger corolla lobes. A total of 106 aroma components, mainly including esters, nitriles, aldehydes, ketones, alcohols, alkanes, olefins, terpenes and aromatic hydrocarbons, were detected in different aroma types at four different flowering stages of budding, initial flowering, full flowering and final flowering. There were 0, 18, 45 and 38 aroma components detected at four flowering stages of the strong aroma type, 0, 7, 35 and 19 in the medium aroma type, and 3, 4, 13 and 2 in the non-aroma type. In the diurnal variation of floral aroma at full flowering stage, 86 aroma components were detected in the strong aroma type, and only 17 components were common at all the four stages, among which methyl acetate, (E) -4, 8-dimethyl-1, 3, 7-nonatriene, and cis-β-farnesene were the main floral components at the full flowering stage. Conclusion: There were significant differences in the color and shape of corolla lobes of Chionanthus retusus among different floral aroma types. The total number of flowers, the total length of inflorescence, the length and width of corolla lobes and the length and width of sepals of the strong aroma type were the largest at full flowering stage, while the flower branches were shorter than those of the non-aroma type and longer than those of the medium aroma type. The strong aroma type had the largest number of aroma components and the highest relative content, followed by the medium aroma type and the non-aroma type. The number of aroma components and their relative contents were very small at the budding stage, followed by an increase at the initial flowering stage, and reached the maximum at the full flowering stage, and declined again at the final flowering stage. The diurnal variation of the overall aroma content of the strong aroma type at full flowering stage displayed a pattern of first increase followed by decreases, and reaching the maximum at 14:00.

Objective: Among forest pests, tree trunk borers have hidden life and are difficult to control, thus they are a major hidden danger of ecological security. In this study, Semanotus bifasciatus was selected as the research object, and a recognition model was designed based on the convolutional neural network to recognize the feeding sounds, and the noise immunity of the model was tested in order to realize the early warning for the tree trunk borers. Method: In this study, the SP-1 L probe was connected with NI 9215 voltage collection module to collect the feeding sounds of S. bifasciatus and the noise in typical outdoor environment, and the sounds were saved as audio format. Part of the noise was selected as the noise-added audios, and the feeding sound of S. bifasciatus was mixed with the environmental noise with the signal-noise ratio from -3 dB to 3 dB to produce the training data set and the simple test set. Then the average log spectrums of the audios were calculated as the input of the model through the three steps of short-time Fourier transform, logarithm calculation and the average pooling. The proposed recognition model based on the convolutional neural network and the traditional Gaussian mixture model was used to extract the features of the spectrums and judge whether the audio was the feeding sounds of S. bifasciatus. In order to further test the noise immunity of the model, this study used the independent noise-added audios to mix the feeding sounds of S. bifasciatus with the signal-noise ratios from -7 dB to 3 dB, which were wider compared with the training set. Then the noise immunity of the convolutional neural network and the traditional Gaussian mixture model were tested. Result: On the simple test set, the recognition accuracy of the recognition model based on the convolutional neural network was 98.80%, which was 0.88% lower than that of the Gaussian mixture model. On the noise immunity test set, the overall accuracy of the recognition model based on convolution neural network to recognize the feeding sounds of S. bifasciatus was 97.37%, which was 6.76% higher than that of the Gaussian mixture model. What's more, the recognition accuracy at -3 dB signal-noise ratio of the recognition model based on the convolutional neural network was 98.13%, which was 9.80% higher than that of the Gaussian mixture model, and the recognition accuracy at -6 dB signal-noise ratio of the recognition model based on the convolutional neural network was 92.13%, which was 5.67% higher than that of the Gaussian mixture model. Conclusion: The results demonstrate that the convolutional neural network can effectively synthesize the audio spectrum features and accurately judge whether there is the feeding sound of S. bifasciatus. At the same time, the convolutional neural network has better generalization ability, and can ensure the high recognition accuracy even under low signal-noise ratio. Therefore, the feeding sounds recognition model based on the convolutional neural network can adapt to the field monitoring environment of tree trunk borers, and can provide technical support for the automatic monitoring and early warning of the stealthy tree trunk borers.

Objective: Global climate change is one of the main factors causing biodiversity reduction and species extinction. The research on the potential habitat changes of brown-eared pheasants, a species endemic and endangered to China under the present and future climate change scenarios has great significance for establishing relevant conservation policies. Method: Based on the data at 152 distribution locations and 26 high-resolution environmental variables, the potential habitat of brown-eared pheasant was analyzed by using MaxEnt model under the current conditions, and the future distributions were also simulated for the periods of 2050s and 2070s under the climate change scenarios of RCP4.5 and RCP8.5 predicted in the Special Report of Intergovernmental Panel on Climate Change (IPCC). Result: The AUC values for all training and testing model were greater than 0.8, indicating that MaxEnt model is good in predicting its potential habitat. At present, the contribution rates of the dominate factors to brown-eared pheasant habitat were annual precipitation (15.4%), mean diurnal range (15.3%), vegetation types (9.7%), precipitation in the driest season (9.1%) and in the wettest season (8.7%), distance to road (8.2%) and water source (7.8%), with their cumulative contributions of 74.2%. The thresholds of each factor were 525-580 mm, 8.2-10.8℃, preference for broadleaved forest and mixed forest, 12.4-17.1 mm, 310-340 mm, 0~2.5 km, 0~0.63 km and more than 10 km, respectively. The suitable habitats of brown-eared pheasant were mainly distributed in Huanglong Mountain of Shaanxi Province, Lüliang Mountain of Shanxi Province, Xiaowutai Mountain in Hebei Province and Baihua Mountain of Beijing. The proportion of suitable, moderate and unsuitable areas was 6.45%, 19.92% and 73.62%, respectively. Compared with that in the current condition, the livable habitat of the pheasant shows a increase trend in the future, and the suitable and moderately suitable habitat has the same trend. Meanwhile, it is almost unchanged between 2050s and 2070s. Conclusion: The potential distribution areas of the pheasant in this study area are mainly in Huanglong Mountain of Shaanxi Province, Lüliang Mountain of Shanxi Province, Xiaowutai Mountain in Hebei Province and Baihua Mountain of Beijing City. The livable habitats of the pheasant will increase in the future. The dominate factors affecting the distribution of brown-eared pheasant are annual precipitation, mean diurnal range, vegetation types, precipitation of the driest and the wettest quarter, distance to road and water source. This study reminds us to strengthen the protection and management of the suitable and moderate areas, and meanwhile, strengthen evergreen coniferous forest planting and population control in the reserve.

Objective: Rubber wood was modified by silica sol combined with glyoxal-urea(GU) resin, and by silica sol combined with glyoxal-melamine-urea(GMU) resin. The effects of type and solution concentration of modifiers on the physico-mechanical and thermal properties of rubber wood were studied. Method: GU resin and GMU resin were prepared by adopting glyoxal, melamine and urea as the modified monomer. By controlling the mass ratio of GU/GMU resin to silica sol, a homogeneous, stable, and water-soluble solution was prepared. Furthermore, weight percent gain, dimensional stability and mechanical properties of modified rubber wood with the mixture of GU/GMU resin and silica sol were determined, and the performances of the thermal stability, chemical structure, and microcosmic structure were also investigated by thermogravimetry(TG), Fourier transform infrared spectroscopy(FTIR), and field emission scanning electron microscopy-energy dispersive X-ray spectroscopy(FESEM-EDS). Furthermore, those properties of silica sol modified rubber were compared. Result: 1) With the increase of solution concentration of modifier, the weight percent gain and dimensional stability of modified wood with the mixture increased. The weight percent gain and dimensional stability of S-GMU modified wood were superior than those of S-GU modified wood with the same fraction of solution for modified wood. The highest values of weight percent gain and anti-swelling efficiency were 28.32% and 42.02% under S-20%GMU modified wood, which raised 16.98% and 14.40% than those of modified rubber with S-20%GU modified wood, respectively. 2) With the increase of weight percent gain, the bending strength of modified wood with the mixture increased. The bending strength of S-20%GMU modified wood was 114.96 MPa, which raised 11.97% than that of modified rubber with S-20%GU modified wood, and no obvious difference in elasticity modulus was observed between unmodified wood and modified wood. 3) S-GMU mixture played a role in stabilizing wood residues, and the thermal stability of S-GMU modified wood was enhanced. The wood residues rates of S-20%GMU modified wood, were 5.25, 1.20 and 1.12 times that of unmodified wood, silica sol modified wood and S-20%GU modified wood, respectively. 4) The absorption peak of Si-O-Si and C-O-C could be seen near to 470 cm^-1 and 1 110 cm^-1, respectively, which proved that the silica sol and GMU resin had entered into S-GMU modified wood. Simultaneously, the absorption peak intensities near to 1 656 cm^-1 and 1 510 cm^-1 were weakened, which indicated that the lignin and carbohydrates of modified wood were degraded to a certain extent. While S-20%GMU modified wood had the lowest degree of degradation. 5) The solution for modified wood was entered into and deposited in the cell lumen and cell wall. There were more Si elements in S-20%GMU modified wood. The Si elements and mixture were evenly distributed of S-20%GMU modified wood, and the modification effect was better. The content of N elements in S-20%GMU modified wood increased, indicating that GMU resin entered the wood. Conclusion: The weight percent gain, dimensional stability and mechanical properties of modified wood with the silica sol combined with GU/GMU resin were superior than those of silica sol modified wood. The properties of S-GMU modified wood were superior than those of S-GU modified wood with the same fraction of solution for modified wood. The silica sol and S-GMU resin were entered into and deposited in the cell lumen and cell wall of S-GMU modified wood. The S-GMU mixture played a role in stabilizing wood residues, and the thermal stability of modified wood was enhanced. Therefore, this study produced evidences of improvement in physico-mechanical and thermal properties of rubber wood treated with S-GMU.

Objective: Laminated object manufacturing(LOM) technology stacks layer by layer to produce the required parts. In order to meet the requirements of bonding quality and machining precision of the forming workpiece, the LOM process flow was optimized and improved to solve the influences of the heat affected area on the physical properties of hot melt adhesive in laser cutting process. A mathematical method was used to describe the real-time temperature changes in the laminated hot-pressing process, and the influences of hot-pressing process parameters and temperature field distribution gradient were also discussed so as to provide a reference for ensuring the good adhesion of forming workpiece. Method: Based on the heat transfer theory of wood and the energy conservation equation, the heat transfer control equation of laminar thermal pressure process was established. By simplifying the model through basic assumptions, the three-dimensional unsteady heat conduction problem of laminar thermal pressure process had been simplified to the one-dimensional unsteady heat transfer problem. The forward difference method was used to discretize the governing equation, and MATLAB software was used to simulate the temperature field in the process of laminar hot-pressing. In addition, the temperature distribution curves of different depth layers were analyzed. According to the data obtained from the simulation, the two-dimensional line graph was drawn to explain the influence rule of temperature changing with the number of layers in the hot-pressing process. Results: According to the MATLAB simulation results and the mathematical model of the laminated hot-pressing temperature curve, the influences of hot-pressing plate on the temperature of thin wood layer was decreased with the increase of the number of layers. The temperature of the thin wood layer close to the hot-pressing plate was changed significantly. The reason was that when the hot-pressing plate worked, there was a strong convective heat transferred between the thin wood layer and the hot-pressing plate, which caused the temperature of the thin wood layer to rise. When the number of hot-pressing layers was 15, the temperature of the first thin wood layer close to the hot-pressing plate was 113.07℃. Along the vertical direction of the laminate, the influence of hot pressing on the temperature of the laminate was decreased with the increase of the laminate depth. It was because after leaving the hot-pressing plate, the cold air entered and conducted convective heat exchange with the thin wood layer, which caused the temperature of the thin wood layer to drop rapidly. Therefore, layer 3 temperature was 99.61℃, from layer 1 to layer 3, there was only one layer, and the temperature declined nearly 14.00℃. In the thin wood layer below a certain depth or close to the bottom plate, the temperature change was not obvious, layer 13 temperature was 77.50℃, layer 15 temperature was 75.64℃, from layer 13 to layer 15, there was one layer, the temperature declined less than 2.00℃. Conclusion: In the model, the goodness of fit between the predicted data and the experimental data is high, and the model has a strong guiding role in LOM manufacturing process. The established mathematical model and the innovatively designed working process of the LOM machine tool are related. The program written can be applied to the real-time simulation of the temperature field during the manufacturing process of the solid body. The simulation process of MATLAB can calculate the temperature change history of each point of the model, which is very important to improve the quality of thin wood bonding.

Seed dormancy is induced by external environmental factors or seed genetic characteristics, and it is a phenomenon that the viable seeds cannot germinate under a favorable environment. Seed dormancy and germination are two different and interrelated developmental states. Dormant seeds can enter into the germination state only after the dormancy isreleased. Seed dormancy to a certain extent determines the environment required for germination. In order to have a more comprehensive understanding ofseed dormancy and germination, this paper summarizes the causes of common forest seed dormancy and the classification system of the dormancy types based on the domestic and foreign literature regarding forest seed dormancy, dormancy release, and germination. Furthermore, in this paper we discuss the mechanism of seed dormancy, especially the theory of endogenous hormone regulating seed dormancy, expound the theories of light signal-regulating seed dormancy, Ca²⁺ regulating seed dormancy and gene controlling seed dormancy, cell membrane changes, etc; The methods of seed dormancy release by stratification, physical methods, chemical methods, and hormone treatments are summerized. The recovery of imbibition indicates that the seed has entered the germination stage, which is accompanied by complex changes in morphology, physiology, biochemistry, and molecular level. Moreover, this paper also discusses the limitation of current research and proposes that more in-depth research should be carried out on the molecular regulation mechanisms of seed dormancy and germination, such as initiation of transcription, gene regulation, genetic expression, in order to provide a basis for the study on dormancy and germination mechanism of forest seeds and provide a reference for forest seed storage, seedling breeding, planting promotion and development, and utilization.

Objective: With China's socioeconomic development, people's increasing demand for a better life has increased the possibility and enthusiasm of public participation in ecological forest conservation. The purpose of this study is to explore the willingness and impacts of public participation in ecological forest protection, in order to provide a scientific basis for policy making. Method: an onsite survey was conducted on tourists in Taibai Mountain National Forest Park in 2019, and 410 valid questionnaires were collected. In the view of forest eco-tourism, the theory of planned behavior was expanded by adding variables of environmental emotion and ecological forest cognition. A theoretical model of factors influencing the willingness to protect ecological forest including physical action, persuasive action, financial action, and civic action was constructed and empirically demonstrated through structural equation modeling. Results: 1) All the fitted parameters of the model met the recommended value requirements, indicating that the fitting of the model was acceptable with good fitting; 2) All the initial hypotheses used in the model were tested to be true, and most of the hypotheses were verified at the significance level of 0.01; 3) 90% (369), 80% (328) and 70% (287) of the number of questionnaires were selected for fitting, and the model passed the robustness test, indicating that the Results of this study were reliable; 4) From the perspective of gender, women were only stronger than men in the willingness of financial action, and there was no significant gender difference in the other three types of protective behavioral willingness. Age had a great influence on willingness of both civic action and physical action. Compared with groups younger than 19, the 30-49 age group had a higher level of willingness of both civic action and physical action, and the over-60 age group had a lower level of the willingness of financial action. There was a significant negative relationship between monthly disposable income and the willingness of civic action, the willingness of persuasive action and the willingness of physical action at the significance level of 0.05. Educational level had essentially no significant effect on willingness to engage in the four protective behaviors. Conclusion: Both cognition of ecological forest and environmental emotion had a positive impact on the attitude of protective behavior; besides, the cognition of ecological forest had a greater impact than the environmental emotion. The attitude of protective behavior had a positive impact on the four types of willingness of protective behavior. Overall, in addition to the willingness of financial action, the willingness of physical action, persuasive action and civic action were more vulnerable to the influence of individual subjective judgment. We also found that subjective norm and perceived behavioral control had positive effects on the four types of willingness of protective behavior, among which the willingness of financial action was the most affected by perceived behavioral control. In terms of demographic characteristics, gender, age and average monthly disposable income were found to have an impact on willingness of protective behavior, education level and individual occupation had no significant effects on willingness of protective behavior.

Objective: The impacts of species diversity (species richness, species Shannon-Wiener index and species evenness), structure diversity (DBH Shannon-Wiener index, DBH evenness, coefficient of DBH variation, and DBH gini index) and environmental factors on aboveground biomass of the forests of Quercus aliena var. acutiserrata in the north slope of Taibai Mountain of Qinling Mountains were investigated to provide a theoretical basis for biodiversity conservation and harmonization of forest ecosystem functions. Method: Q.aliena var. acutiserrata forests in the north slope of Taibai mountain of Qinling Mountains were studied. The effects of species diversity and structural diversity on the aboveground biomass were analyzed based on inventory data (diameter at breast height ≥ 1 cm) and environmental factors in the permanent observation plots (100 m×150 m). The correlation between species diversity and aboveground biomass was determined by multivariate regression. Coupling with environmental factors, the structural equation modeling was conducted to compare the effects of species diversity and structural diversity on aboveground biomass. Result: The linear regression and structural equation modeling showed no significant correlation between the 3 indices of species diversity with the aboveground biomass. Among the structure diversity indices, a significant negative correlation was obtained between DBH pielou and aboveground biomass. However, a low percentage of aboveground biomass variation can be explained by the diameter pielou. Environmental factors had direct and indirect effects on aboveground biomass, while direct effects were more prominent. Conclusion: Community structure was an important factor for the aboveground biomass of Q. aliena var. acutiserrata forests. However, structural diversity was an inhibiting factor rather than promoting factor on aboveground biomass, indicating that the increased complexity of community structure did not benefit the accumulation of aboveground biomass. Environmental factors directly affected aboveground biomass; however, no significant effect was found on the correlations of aboveground biomass with species diversity or structure diversity. Although the importance of community structure to the aboveground biomass was proved in this study, community structure may not be the dominant factor for aboveground biomass of Q. aliena var. acutiserrata forests.

Objective: To investigate the effects of polyvinyl pyrrolidone (PVP) treatment on the activities of related enzymes and phenolic acid content in explants during tissue culture of Pinus tabulaeformis var. mukdensis, in order to find the main substrates for enzymatic browning, and to provide theoretical basis and technical support for solving the bottleneck problem of browning during tissue culture of P. tabulaeformis var. mukdensis. Method: Using dormant buds of P. tabulaeformis var. mukdensis as explants, the effects of PVP treatments with different concentrations on the browning and germination of explants were detected. The optimal PVP concentration was determined, the changes of activities of the relevant enzymes in the explants under the optimal treatment concentration of PVP were detected, and the qualitative and quantitative analyses of the phenolic acid were conducted by using high performance liquid chromatography. Result: Addition of 300-1 500 mg·L^-1 PVP effectively inhibited the browning of explants and promoted the germination of the dormant buds of P. tabulaeformis var. mukdensis. Inhibition of the browning of explants was started on the 8th day of PVP treatment, the browning rate peaked on the 24th day, and then tended to stabilize. The most effective concentration of PVP for inhibiting the browning of P. tabulaeformis var. mukdensis explants was 1 500 mg·L^-1 under which the browning rate was only 25.56%, and the dormant bud germination rate was also the highest (37.78%). Analysis of changes in enzyme activities and phenolic acid content showed that polyphenol oxidase(PPO) and phenylalanine ammonia-lyase(PAL) activities were at a relatively low level during the whole treatment process under PVP treatments compared with the control, whereas the change of peroxidase (POD) activity was not significant. PPO activity under PVP treatments was significantly lower than that of the control starting from day 4, but PAL activity was obviously inhibited since day 8. The decrease of chlorogenic acid content under PVP treatments during days 8-12 when browning was aggravated was significantly lower than that of the control; the ferulic acid content under PVP treatments during days 0-12 did not change much, but was significantly higher than that of the control during days 16-32. The content of coumaric acid was maintained at a low level throughout the treatment. Conclusion: PVP effectively inhibits the browning of P. tabulaeformis var. mukdensis explants and promotes germination of the dormant buds. And the addition of 1500 mg·L^-1 PVP obtained the best effects. PVP treatment prevented browning of P. tabulaeformis var. mukdensis explants by reducing the activity of PPO and PAL. PVP treatment protects chlorogenic acid and ferulic acid from being oxidized so as to inhibit tissue browning.