[Temporal and spatial variations of vegetation coverage in Heilongjiang Basin and its responses to climate change]. / é»‘é¾™æ±ŸæµåŸŸæ¤è¢«è¦†ç›–åº¦æ—¶ç©ºåŠ¨æ€åŠå ¶å¯¹æ°”å€™å˜åŒ–çš„å“åº”.

Exploring the temporal and spatial dynamics of vegetation coverage in the Heilongjiang Basin and its response to climate change can provide a theoretical basis and data support for integrated basin management for three countries (Mongolia, China and Russia) in the region. We used MOD13Q1 remote sensing data from Google Earth Engine (GEE) platform between 2000 and 2020 to process the normalized vegetation index (NDVI) through the maximum value composites method, and calculated the vegetation coverage (FVC) using the dimidiate pixel model. The Sen+MK trend analysis method was employed to monitor the dynamics of FVC, while the Pearson correlation coefficient was utilized to quantify the responses of FVC to climate change. The results showed that the overall FVC in the Heilongjiang Basin exhibited a slight decreasing trend during 2000-2020, with an annual rate of 0.1%. The FVC in Mongolia showed a fluctuating increase trend (0.13%), while slight decrease trends were observed for Russia (0.15%) and China (0.08%). The FVC predominantly slightly degraded and severely degraded, accounting for 34% and 17% of the area, respectively, while the significantly improved area only accounted for 9%. The impact of precipitation on FVC in the study area was significantly greater than that of temperature. The proportion of areas where precipitation and temperature had a significant impact on FVC was 8.2% and 2.2%, respectively. The correlation coefficient between precipitation and FVC was the highest in Mongolia (r=0.446, P<0.05), and the lowest in Russian region (r=-0.442, P< 0.05).

[Effect of competition on the prediction accuracy of individual tree biomass model for natural Larix gmelinii forests]. / ç«žäº‰å¯¹å ´å®‰è½å¶æ¾å¤©ç„¶æž—å•æœ¨ç”Ÿç‰©é‡æ¨¡åž‹é¢„ä¼°ç²¾åº¦çš„å½±å“.

Quantifying the impact of competition on individual tree biomass and its distribution pattern can provide a basis for improving the prediction accuracy of forest biomass models. To accurately quantify the effects of competition factors on individual biomass and its distribution, we constructed three different individual biomass models by using nonlinear coupling equations based on the biomass survey data of 50 Larix gmelinii from 18 plots of Pangu Forest Farm in Daxing'an Mountains. M-1 was a traditional singly additive biomass model. M-2 and M-3 were models taking the distance dependent simple competition index (CI) and distance independent relative diameter (Rd) into account, respectively. Those models were used to reveal the influence of competition factors on the prediction accuracy and distribution pattern of single tree biomass model of L. gmelinii. The results showed that the adjusted R2 of three additive models ranged from 0.694 to 0.974, mean prediction errors ranged from -0.017 to 0.021, and mean absolute errors ranged from 0.152 to 0.357. The introduction of Rd could improve the fitting degree and prediction accuracy of most biomass models, but CI did not affect the model fitting effect and prediction ability. Among the three models, M-3 model had the best performance, with good fitting degree and prediction accuracy of the biomass of each part, which could accurately estimate the single tree biomass of L. gmelinii. Further simulation results showed that the variation of biomass with DBH was mainly affected by CI and Rd grade, and the influence of Rd was stronger than CI. CI had greater influence on root and dry biomass, but less influence on branch and leaf biomass. Rd had a more significant effect on biomass of branch and leaf than on that of root and trunk.

Driving forces of herbaceous species diversity in natural broadleaf forests from in Maoershan from Northeast China.

The understory herbaceous flora plays a pivotal role in regulating the structural stability, complexity, and ecological function of forest communities. It is crucial to investigate the impact of the intricate connections between these factors and the forces driving the diversity of herbaceous species within natural broadleaf understory forests can assist forest managers in developing optimal forest structure optimization techniques, allowing them to adjust the forest species diversity. In this study, Pearson correlation analysis, conventional correlation analysis, and multiple linear regression were employed to elucidate the relationship between stand structure, soil nutrients, and understory herbaceous species richness in natural broadleaved forests. Structural equation modeling was utilized to ascertain the influence of multiple factors on understory herbaceous species diversity and to evaluate the underlying pathways. The results indicated a significant negative correlation between stand closure and the Simpson's and Shannon-Wiener's indices, and between the mixing degree and the Pielou evenness index, Simpson's index, and Shannon-Wiener's index (p<0.05). Furthermore, a significant positive correlation was observed between soil nutrients, specifically organic matter and total phosphorus, and the Pielou evenness index and Shannon-Wiener's index (p<0.05). It was found that total phosphorus was significantly positively correlated with both the Pielou evenness index and the Shannon-Wiener index (p<0.05). The correlation coefficients of the first group of typical variables in the typical correlation analysis were 0.498 and 0.585, respectively (p<0.05). From the set of typical variables of stand structure, it can be seen that the Hegyi competition index and the canopy density affected the diversity of understory herbaceous plants. The composite index demonstrated the greatest impact, with loadings of 0.872 and -0.506, respectively. The Simpson and Shannon-Wiener indices exhibited the most sensitive loadings of -0.441 and -0.408, respectively. The soil nutrients of SOM and TN affected the understory herbaceous plant species diversity composite index, with greater loadings of -0.184 and 1.002, respectively. The path coefficient of the understory herbaceous diversity stand structure was 0.35. The path coefficient with soil nutrient content was found to be 0.23 following structural equation analysis and the path coefficient between stand structure and soil nutrient content was 0.21, which indirectly affect the diversity of understory herbaceous species. To enhance the diversity of herbaceous species, it is recommended that the canopy density and tree density of the upper forest be reduced appropriately, while the degree of mixing and the level of spatial distribution of trees be adjusted in a manner that maintains a reasonable stand structure. Furthermore, a comprehensive forest management program for improving soil nutrients should be considered.

How to maximize the joint benefits of timber production and carbon sequestration for rural areas? A case study of larch plantations in northeast China.

BACKGROUND: Implementing large-scale carbon sink afforestation may contribute to carbon neutrality targets and increase the economic benefits of forests in rural areas. However, how to manage planted forests in China to maximize the joint benefits of timber production and carbon sequestration is still unclear. Therefore, the present study quantified the effects of different rotation lengths, thinning treatments, site quality (SCI), stand density (SDI), and management costs on the joint benefits of carbon sequestration and timber production based on a stand-level model system developed for larch plantations in northeast China. RESULTS: The performances of the different scenarios on carbon stocks were satisfactory, where the variations in the outcomes of final carbon stocks could be explained by up to 90%. The joint benefits increased significantly with the increases of SDIs and SCIs, regardless of which rotation length and thinning treatments were evaluated. Early thinning treatments decreased the joint benefits significantly by approximately 131.53% and 32.16% of middle- and higher-SDIs, however longer rotations (60 years) could enlarge it by approximately 71.39% and 80.27% in scenarios with and without thinning when compared with a shorter rotation length (40 years). Discount rates and timber prices were the two most important variables affecting joint benefits, while the effects of carbon prices were not as significant as expected in the current trading market in China. CONCLUSIONS: The management plans that promote longer rotations, higher stand densities, and no thinning treatments can maximize the joint benefits of carbon sequestration afforestation and timber production from larch plantations located in northeast China.

[Age estimation model for individual tree in natural Larix gmelinii forest based on random forest model]. / åŸºäºŽéšæœºæ£®æž—çš„å ´å®‰è½å¶æ¾å¤©ç„¶æž—å•æœ¨å¹´é¾„é¢„ä¼°æ¨¡åž‹.

To accurately estimate the age of individual tree and to achieve full-cycle sustainable management of natural Larix gmelinii forest in Great Xing'an Mountains of northeastern China, we constructed individual tree age prediction model using stepwise regression and random forest algorithms based on 44 fixed plots data and 280 stan-dard tree cores obtained from the Pangu Forest Farm. We analyzed the influence of stand structure, site conditions, and competition index on the accuracy of model prediction. The model was evaluated by the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The results showed that the random forest model had the highest prediction accuracy when number of decision trees was 1500 and number of node con-tention variables was 8. The random forest model had better accuracy and prediction ability than the stepwise regression model, with R2, RMSE and MAE of 0.5882, 9.9259 a, 8.1155 a. Diameter at breast height was the most important factor affecting age prediction (83.8%), followed by tree height (34.4%), elevation (17.9%), and basal area per hectare (17.5%). The random forest algorithm exhibited better adaptability and modeling effect on constructing a predictive model for individual tree age. This research contributed to improving the accuracy of growth and harvest estimation for L. gmelinii, and could provide a reference for other scientific studies related to tree age estimation in forests.

Long-term vegetation restoration promotes lignin phenol preservation and microbial anabolism in forest plantations: Implications for soil organic carbon dynamics.

Vegetation restoration contributes to soil organic carbon (C; SOC) sequestration through the accumulation of plant and microbial residues, but the mechanisms underlying this microbially mediated process are not well resolved. To depict the dynamics of plant- and microbial-derived C in restored forest ecosystems, soil samples were collected from Robinia pseudoacacia plantations of different stand ages (15, 25, 35, 45 years old) established on degraded wheat fields. The results showed that the degree of lignin phenol oxidation decreased with increasing stand age (P < 0.05), and hemicellulose-degrading genes were detected at higher relative abundances than other functional gene categories, indicating selective preservation of recalcitrant lignin phenols. Despite both glucosamine (R2 = 0.61, P < 0.001) and muramic acid (R2 = 0.37, P < 0.001) contents trending upward over time, fungal residual C accounted for a greater proportion of SOC compared with bacterial residual C. Accordingly, fungal residual C, which exhibited a similar response pattern as total microbial residual C to vegetation restoration, was considered a major contributor to the SOC pool. These results provided evidence that long-term vegetation restoration enhanced SOC sequestration in R. pseudoacacia forest by promoting the preservation of plant-derived lignin phenols and concomitant microbial anabolism. Partial least squares-discriminant analysis identified two important ecological clusters (i.e., modules) in the fungal network that profoundly influenced lignin phenol oxidation (P < 0.05) and microbial residual C accumulation (P < 0.01). Among the dominant taxa in microbial networks, the bacterial phyla Proteobacteria and Acidobacteriota had potential to degrade recalcitrant C compounds (e.g., cellulose, lignin), whereas the fungal phylum Ascomycota could outcompete for labile C fractions (e.g., dissolved organic C). Findings of this study can enable a mechanistic understanding of SOC stability driven by microbial turnover in restored forest ecosystems.

Compatibility predictive model for regeneration quantities of Larix gmelinii natural forest in Daxing'anling Mountains, China.

The natural regeneration grade is an important foundation for formulating forest management measures. Traditional studies have only considered the regeneration quantities predictive model of the total stand or dominant tree species, but the consistency among the prediction results of different tree species and the total regeneration quantities of stand is not solved. That is, the regeneration prediction results at the stand level are not equal to the sum of the predicted results of all tree species. To address this, on the basis of the traditional counting model, we attempted to construct a compatibility predictive model for regeneration quantities of different tree species within the stand, which would provide a theoretical basis for the rational management and decision-making of natural forest. Based on the survey data from 96 standard plots of Cuigang Forest Farm, Xinlin Forest Farm, and Zhuangzhi Forest Farm in Daxing'an Mountains, we selected 30 basic indices from five aspects of site factor, soil factor, stand factor, tree diversity and stand spatial structure, and used Poisson model and negative binomial model as the basic models to construct the regeneration prediction models of Larix gmelinii, Betula platyphylla and other tree species. By comparing the accuracy and fitting effect of the two traditional counting models, we selected the optimal model and used the seemingly unrelated regressions to further construct the compatibility predictive model for regeneration quantities of different tree species. Poisson model was the best one for the regeneration of L. gmelinii, B. platyphylla, and other tree species. The test index RMSE of the compatibility predictive model for regeneration quantities of L. gmelinii, B. platyphylla, other tree species and total stand regeneration quantities were 388, 413, 504, and 871 trees·hm-2, respectively. The adjusted R2 was 0.389, 0.421, 0.488, and 0.407, respectively. The most influential variables for regeneration quantities of L. gmelinii, B. platyphylla and other tree species were Pielou evenness index of DBH (25.2%), herbal coverage (34.6%) and organic matter in B layer (23.2%). In this study, the compatibility predictive model system for regeneration quantities satisfied the additive logic among L. gmelinii, B. platyphylla, other tree species, and total stands, and provided a basis for accurately estimating natural regeneration.

Height-diameter models of regenerated saplings of Larix gmelinii based on dummy variable and quantile regression.

Based on data collected from 2054 saplings of Larix gmelinii forest in 55 fixed plots in 2018-2019 in Cuigang Forestry Station, Daxing'anling area, we classified the stand density index (SDI) into four classes, i.e., Class Ⅰ (SDI1<1863 plants·hm-2), Class Ⅱ (1863 plants·hm-2≤SDI2<2155 plants·hm-2), Class Ⅲ (2155 plants·hm-2≤SDI3<2459 plants·hm-2) and Class Ⅳ (SDI4≥2459 plants·hm-2) by using the quartile method. We constructed a dummy variable model and quantile regression model for the height-breast diameter of saplings of L. gmelinii with dummy variable method introduced SDI. The results showed that among the five selected representative non-linear tree height curve models, the Richards model fitted the best, with Ra2, RMSE and MAE of 0.7637, 0.8250 m and 0.5696 m. The dummy variable model including the SDI constructed based on the Richards model showed a 1.3% increase in Ra2 compared with the base model, while RMSE, MAE, and AIC decreased by 2.1%, 1.5%, and 11.2%, respectively. When the quantile τ was 0.5, Ra2 of quantile regression model was the maximum, and RMSE, MAE, AIC was the minimum, being 0.7612, 0.8294 m, 0.5657 m, and -767.19, respectively. Compared with SDI1, sapling height in SDI2-SDI4 was increased by 5.6%, 5.6%, and 11.3%, suggesting reasonable that regulation of stand density was conducive to increase the height growth of saplings in regeneration.

[Height to diameter ratio model of Larix gmelinii in Daxing'anling Mountains, China]. / å¤§å ´å®‰å²­åœ°åŒºå ´å®‰è½å¶æ¾çš„é«˜å¾„æ¯”æ¨¡åž‹.

Based on data from 56 plots of natural Larix gmelinii forest in Cuigang Forest Farm of Daxing'anling Mountains, we constructed the height to diameter ratio (HDR) model of L. gmelinii with exponential decay function as the base model. We used the tree classification as dummy variables and the method of reparameterization. The aim was to provide scientific evidence for evaluating the stability of different grades of L. gmelinii trees and stands in Daxing'anling Mountains. The results showed that except for diameter at breast height, the dominant height, dominant diameter, individual tree competition index all had significant correlations with the HDR. The involvement of these variables significantly improved the fitted accuracy of the generalized HDR model, with the adjustment coefficients, root mean square error and mean absolute error being 0.5130, 0.1703 m·cm-1 and 0.1281 m·cm-1, respectively. When the tree classification as a dummy variable was added to parameters 0 and 2 of the generalized model, the fitting effect of the model was further improved. The three above-mentioned statistics were 0.5171, 0.1696 m·cm-1 and 0.1277 m·cm-1, respectively. Through comparative analysis, the generalized HDR model with tree classification as dummy variable had the best fitting effect, which was superior to the basic model, and had higher prediction precision and adaptability.

[Simulation of carbon sequestration and timber production in Larix olgensis plantation based on CO2FIX model]. / 基于CO2FIX模型的长白落叶松人工林碳汇和木材生产模拟.

Based on datasets from plot survey and bibliographic of Larix olgensis plantations in Maoer Mountain, the CO2FIX model was used to quantitatively simulate the effects of different rotations (30, 40, 50, 60 years), site indices (12, 16, 20 m), and initial densities (2500, 3333, 4444 trees·hm-2) on the stand level carbon flows among different carbon pools (i.e., biomass carbon pool, soil carbon pool, and product carbon pool). The results showed that the CO2FIX model had high reliability for simulating the processes of L. olgensis plantation, with the average relative errors of stand biomass and volume between analog and measured values being 6.4% and 3.7%. Under the baseline conditions of initial density of 3333 trees·hm-2, site index of 16 m and rotation of 40 years, the carbon stock of total and sub-pool of L. olgensis plantation changed periodically with rotation. The total stand carbon stock and volume for L. olgensis plantation increased with the extension of rotation, the improvement of site index, and the increase of initial density. The stand carbon stock and volume would be increased by 12.2% and 31.2%, 36.7% and 67.8%, respectively, when the reference rotation was correspondingly extended by 10 and 20 years. However, if the reference rotation was shortened by 10 years, stand carbon stock and volume would be correspondingly decreased by 20.9% and 40.4%, respectively. When the initial density was set as 3333 and 4444 trees·hm-2, stand carbon stock and volume were increased by 27.8% and 50.9%, 27.4% and 49.1%, respectively. When the site index was under the range of 12 to 20 m, stand carbon stock and volume could be increased by 36.0% and 40.3%, 39.3% and 44.2%, respectively, with each increase of 4 m in site index. During one rotation, 271.57 t C per hectare could be fixed into L. olgensis plantation. At the end round of the rotation, 27.47 and 56.75 t C were transferred to soil and wood product carbon pools. Therefore, when the site condition was good, the management model with a higher initial density (4444 trees·hm-2) and longer rotation (60 years) would be more beneficial to maximizing the carbon sink and timber benefits of L. olgensis plantation.

[Classification of forest types in Cuigang Forest Farm based on time series data of Landsat 8]. / 基于Landsat 8æ—¶é—´åºåˆ—æ•°æ®çš„ç¿ å²—æž—åœºæ£®æž—ç±»åž‹åˆ’åˆ†.

To explore the practical role of enhanced vegetation index (EVI) time series data in improving the accuracy of forest type recognition could promote the deep application of optical remote sensing data in forest resources investigation and monitoring. With Cuigang Forest Farm of Xinlin Forestry Bureau in Daxing'anling as the object, we constructed six classification schemes, using random forest algorithm with spectral feature, texture feature and EVI time series feature. The data sources were 20-view Landsat 8 OLI time series data from 2014 to 2018, 56 fixed plots data from 2017-2019, and the 2016 Class II survey data. Our aims were to realize the classification of forest types in Cuigang Forest Farm and to evaluate the accuracy of different classification schemes. The results showed the EVI values of Larix gmelinii forest, Betula platyphylla forest, coniferous-broadleaved mixed forest, coniferous mixed forest and broadleaved mixed forest were significantly different in non-growing seasons (36-111 days and 287-367 days), with the EVI value of mixed conifer forest being significantly higher, and that of mixed broadleaf forest being always lower than the other four forest types. In the early growing season (111-143 days), the EVI value of B. platyphylla forest were higher than L. gmelinii forest, which could effectively distinguish the two forests. Among the six classification schemes, spectral feature, texture feature, and EVI time series feature had the highest classification accuracy, with a Kappa of 0.82 and a classification accuracy of 86.1%. The comparison results showed that the overall accuracy of adding vegetation index time series feature was improved by 14.3% compared with that of spectral feature. The random forest algorithm with combined spectral, texture and EVI time series features could effectively classify forest stand types in Cuigang Forest Farm, with good recognition accuracy and confidence.

[Structure and dynamics of co-dominant species in different succession stages of natural forests in Daxing'an Mountains, China]. / å¤§å ´å®‰å²­å¤©ç„¶æž—ä¸åŒæ¼”æ›¿é˜¶æ®µå ±ä¼˜åŠ¿ç§ç§ç¾¤ç»“æž„ä¸ŽåŠ¨æ€.

Affected by the disturbance of forest fire and logging, the primary forest in Daxing'an Mountains gradually degenerates into secondary forest. In this study, we established 16 plots in each of three typical forests, including natural Betula platyphylla pure forest (pioneer stage), natural B. platyphylla and Larix gmelinii mixed forest (transition stage) and natural L. gmelinii pure forest (top stage). The methods of population age and tree height structure, static life table, survival analysis, dynamic index and time series prediction were used to quantitatively analyze the dynamics of dominant species (B. platyphylla and L. gmelinii) and all the arbors, aiming to provide scientific basis for the restoration and development of natural L. gmelinii forest. The results showed that the abundance of young co-dominant species and total arbors in each stage was large, and that all population had strong self-renewal potential. With the progress of succession, the abundance of B. platyphylla in each age class gradually decreased, whereas that of L. gmelinii gradually increased. The mortality and disappearance rates of total arbors and B. platyphylla in the transition stage and L. gmelinii in the pioneer stage gradually increased with the increases of age class, and the survival curve was Deevey-Ⅰ type. The survival analysis results showed that the population was stable in the early stage, increased in the middle stage, and declined in the later stage. In other stages, the mortality rates fluctuated slightly, the survival curves were Deevey-Ⅱ type, and the population increased in the early stage, declined in the middle stage, and stable in the later stage. The co-dominant species and total arbors were growing in the three succession stages, among which B. platyphylla in the pioneer stage, L. gmelinii and total arbors in the top stage showed the lowest sensitivity to the environment. The results of time series prediction showed that the co-dominant species and total arbors in each stage would increase in the future. During forest succession, it was necessary to strengthen the protection of seedlings and young trees, thin the forest with large coverage, and take appropriate measures to ensure population renewal.

Hydrothermal Aging Mechanisms of All-Steel Radial Tire Composites.

This work focused on the effects of the hydrothermal environment on the aging of all-steel radial tire (ASRT) composites. Composite specimens were conditioned by immersion in deionized water at 30, 60 and 90 °C. Its water absorption, thermal and mechanical properties (tensile strength, elasticity modulus, elongation at break and interfacial shear strength), morphological structure, as well as molecular cross-linking reaction were investigated before and after aging. Results indicated that there was no dynamic equilibrium of water absorption of ASRT composites after deviating from the Fickian model. The molecular cross-linking density of the rubber matrix showed an increase in the early stage of aging. Then, the mechanical properties suffered of a drop due to the degradation of the rubber matrix and the poor interface between the steel fiber and rubber matrix. Additionally, a systematic hygrothermal aging mechanism was proposed.

Variations in Plant Water Use Efficiency Response to Manipulated Precipitation in a Temperate Grassland.

Water use efficiency (WUE) plays important role in understanding the interaction between carbon and water cycles in the plant-soil-atmosphere system. However, little is known regarding the impact of altered precipitation on plant WUE in arid and semi-arid regions. The study examined the effects of altered precipitation [i.e., ambient precipitation (100% of natural precipitation), decreased precipitation (DP, -50%) and increased precipitation (IP, +50%)] on the WUE of grass species (Stipa grandis and Stipa bungeana) and forb species (Artemisia gmelinii) in a temperate grassland. The results found that WUE was significantly affected by growth stages, precipitation and plant species. DP increased the WUE of S. grandis and S. bungeana generally, but IP decreased WUE especially in A. gmelinii. And the grasses had the higher WUE than forbs. For different growth stages, the WUE in the initial growth stage was lower than that in the middle and late growth stages. Soil temperature, available nutrients (i.e., NO3 -, NH4 +, and AP) and microorganisms under the altered precipitations were the main factors affecting plant WUE. These findings highlighted that the grasses have higher WUE than forbs, which can be given priority to vegetation restoration in arid and semi-arid areas.

Effects of vegetation restoration types on soil nutrients and soil erodibility regulated by slope positions on the Loess Plateau.

Soil degradation is significantly increased driven by soil nutrient loss and soil erodibility, thus, hampering the sustainable development of the ecological environment and agricultural production. Vegetation restoration has been widely adopted to prevent soil degradation given its role in improving soil nutrients and soil erodibility. However, it is unclear which vegetation type has the best improving capacity from soil nutrient and soil erodibility perspectives. This study selected three vegetation restoration types of grasslands (GL), shrublands (SL), and forestlands (FL) along the five slope positions (i.e., top, upper, middle, lower, and foot slope), to investigate the effects of vegetation restoration types on soil nutrients and soil erodibility. All vegetation restoration types were restored for 20 years from croplands (CL). We used comprehensive soil nutrient index (CSNI) and comprehensive soil erodibility index (CSEI) formed by a weighted summation method to reflect the effect of vegetation restoration on the improving capacity of soil nutrient and erodibility. The results showed the vegetation types with the highest comprehensive soil quality index (CSQI) at the top, upper, middle, lower and foot slope were FL (1.92), FL (1.98), SL (2.15), FL (2.37) and GL (3.93), respectively. When only one vegetation type was considered on the entire slope, SL (0.59) and FL (0.59) had the highest CSNI, the SL had the lowest CSEI (0.34) and the highest CSQI (1.89). The CSNI was mainly influenced by soil structure stability index (SSSI), sand content, silt + clay particles, and CSEI was controlled by soil organic matter (SOM), macroaggregates and microaggregates. Moreover, the CSQI was influenced by pH, silt and clay content, and biome coverage (BC). The study suggested the SL were advised as the best vegetation restoration type on the whole slope from improving soil nutrients and soil erodibility.

[Clarifying the factors affecting Larix gmelinii forest regeneration based on structural equation model]. / åŸºäºŽç»“æž„æ–¹ç¨‹æ¨¡åž‹çš„å ´å®‰è½å¶æ¾å¤©ç„¶æž—æ›´æ–°å½±å“å› ç´ .

Based on data from 49 plots of natural Larix gmelinii forests in Cuigang Forest Farm of Xinlin Forestry Bureau, Daxing'anling Mountains, China, we used 37 measurable variables that mainly focused on stand non-spatial structure, stand spatial structure, species diversity, soil condition, and site condition to construct the structural equation model of natural regeneration densities and size diversities (i.e., height and ground-diameter). The direct, indirect, and total influence coefficients of each path were quantified to extract the critical and controllable factors that influence regeneration density and diversity of natural L. gmelinii forests, which would help implement sustainable forest management. The results showed that the effects of various latent variables on rege-neration density were following an order as: stand non-spatial structure (-0.410) > species diversity (0.380) > soil condition (0.250) > site condition (0.249) > stand spatial structure (0.197), while the order were changed as: soil condition (0.778) > site condition (0.748) > stand spatial structure (0.684) > stand non-spatial structure (0.287) > forest diversity (0.105), when evaluated on the regeneration diversity. Generally, the critical and controllable factors affecting rege-neration quantity and diversity were soil pH, total potassium concentration, species diversity, tree height diversity, uniform angle index and stand volume per hectare. In the management, suitable thinning treatments or replanting broadleaved trees were recommended for optimizing and adjusting species composition, species diversity, soil pH and nutrition, which would promote natural regene-ration.

[Effects of selective cutting on the distribution pattern and inter-specific association of arbor seedlings in Tilia amurensis secondary forest]. / æ‹©ä¼å¯¹ç´«æ¤´æ¬¡ç”Ÿæž—ä¹”æœ¨å¹¼è‹—åˆ†å¸ƒæ ¼å±€åŠç§é—´å ³è”æ€§çš„å½±å“.

The distribution pattern and interspecific associations of arbor seedlings were examined in two Tilia amurensis forest stands in Zhangguangcailing, with one without man-made interference (natural recovery secondary forest) and the other one being 20-year-old after selective cutting (selective cutting secondary forest). The results showed that the importance value of the seedlings of the soft broad-leaved (heliophile) and tolerant tree species was 7.9 and 64.5 in natural recovery secondary forest, and was 3.9 and 68.9 in selective cutting secondary forest, respectively. The spatial distribution pattern of arbor seedlings in natural recovery and selective cutting secondary forests showed clustered distribution at the scale of 0-18 m and 0-15 m, respectively. Most of tree species pairs were negatively correlated at large scale (14-45 m) in the natural recovery secondary forest, whereas tree species pairs at all the scales were mostly uncorrelated in the selective cutting secon-dary forest. Most of the tree pairs of T. amurensis seedlings (57%) with other tree species showed negatively correlation at large scale (31-45 m). In the natural recovery secondary forest, the proportion of negatively correlated tree pairs was higher than 60%. In selective cutting secondary forest, Acer mono seedlings were negatively correlated with other tree species at more scales (6-45 m). In the natural recovery secondary forest, the pairs of A. mono and other arbor seedlings were positively correlated at small scale (0-5 m), but not at large scale (31-45 m). Therefore, selective cutting accelerated the succession of the secondary forest of T. amurensis, which induced random distribution of the arbor seedlings at the large scale (31-45 m), promoted a more coordinated inter-specific relationship, and adjusted the spatial competition between T. amurensis seedlings. Both stands were under succession, and thus suitable artificial management should be carried out to promote tree regeneration and community restoration.

Plant productivity and microbial composition drive soil carbon and nitrogen sequestrations following cropland abandonment.

Understanding the variations in soil organic carbon (SOC) and total nitrogen (STN) stocks in the different ages of abandoned cropland ecosystems of different ages is essential for land use decisions to maximize C sinks or improve ecosystem services. However, knowledge of the dynamics of SOC and STN stocks and their controlling factors after cropland abandonment is limited. Thus, this study investigated the changes in the SOC and STN stocks of loessal soil (Calcaric Regosols) with a chronosequence of 3, 8, 13, 18, 23 and 30 years following cropland abandonment on the Loess Plateau. As a whole, we examined 42 field plots and implemented multivariable linear regression analysis (MLRA) and structural equation modeling (SEM) using 22 influencing variables related to plant, soil and microbial properties to quantify the controls of SOC and STN stocks. The results revealed that SOC and STN stocks significantly increased after cropland abandonment for 30 years, and there were minor decreases in C and N sequestrations in the early restoration stage (<18 years). The SOC and STN changes had significant positive correlations, in which that exhibited STN stocks shifted concurrently with the rate of relative SOC stock changes. The MLRA models demonstrated that the SOC stocks were primarily controlled by aboveground biomass, STN, fungi, and the ratio of fungi to bacteria, while STN stocks were mainly driven by root biomass, above-ground biomass, STN, fungi and the ratio of fungi to bacteria after cropland abandonment. The SEM models further demonstrated that plant productivity not only directly determined the variations in SOC and STN stocks but also changed the microbial community following post-cropland restoration. These results suggest that long-term (>18 years) cropland abandonment can be a successful approach for reinstating SOC and STN stocks, while plants and microbes together mediate microbial C and N stocks during vegetation succession in a semiarid region.

[Spatial distribution pattern and scale effect of secondary forests in Daxing'anling, China]. / å¤§å ´å®‰å²­æ¬¡ç”Ÿæž—ç©ºé—´åˆ†å¸ƒæ ¼å±€åŠå ¶å°ºåº¦æ•ˆåº”.

We examined the spatial distribution patterns and their scale effects of different tree species (Larix gmelinii, Betula platyphylla and others) and different size classes of trees (1-5) of natural L. gmelinii secondary forest (LF), natural B. platyphylla secondary forest (BF) and the mixed secondary forest of both species (MF) in Daxing'anling. The results showed that among the three forest types, LF was the only one type reaching a good state of regeneration, while other two forest types were poorly regenerated. For different forest types, the abundance of seedlings and saplings in the regeneration layer were significantly different from that of the tree layer, and the diameter distribution (except for LF and BF) and height distribution of trees in each forest type were not reasonable, indicating that all the three forest types belonged to unstable communities. At species level, the spatial distributions of main species in each plot were mainly clumped. The five indicators used in this study varied significantly with the scales, which mainly focused on the linear increases (40%), the power increases (22%) and the negative quadratic polynomials (20%), respectively. For different size classes, significant clumped distributions were observed for the regeneration levels (1-3), while the spatial distribution of tree layers (4-5) usually fluctuated distinctly among various distribution patterns. The scale effects of different size classes were mainly dominated by the linear increases (44%), the power increases (15%) and the negative quadratic polynomials (12%). For each forest type and sampling scale, the cluster degrees of trees decreased significantly with increasing tree sizes. Within each forest type, the pattern size of non-dominant species was significantly larger than that of dominant species, while the pattern size of regeneration layers was significantly larger than that of tree layers.

[Seed rain dynamics of natural secondary forest in the central part of Greater Xing'an Mountains, China.] / å¤§å ´å®‰å²­ä¸­éƒ¨å¤©ç„¶æ¬¡ç”Ÿæž—ç§å­é›¨åŠ¨æ€.

We monitored seed rain in three forest types for two years (2018-2019) in the central part of Greater Xing'an Mountains, and analyzed the seasonal seed rain dynamics, deciduous dynamics, seed rain thousand-grain weight, inter-annual variation of seed rain, and spatial pattern of seed rain of the main tree species in different forest types. The results showed that seed rain of Larix gmelinii and Betula platyphylla in each forest type showed unimodal distribution. The leaf litter amount of coniferous and broad-leaved species (L. gmelinii, Pinus sylvestris var. mongolica, Picea koraiensis, B. platyphylla and Populus davidiana) also showed obvious seasonal dynamics, with a peak in the middle and early September. In coniferous and broadleaved mixed forests and coniferous forests, the 1000-grain weight of L. gmelinii at the peak period was significantly greater than that at the initial and final stages. The 1000-grain weight of B. platyphylla in the three forest types did not show obvious seasonal variation. Seed rain of L. gmelinii and B. platyphylla showed obvious inter-annual change. The year 2018 was a large seed set year, whereas 2019 was a year with small seed set. The spatial pattern of all seed rain was mainly dominated by aggregated distribution in both years, which was consistent with that of seedlings and saplings.