Fraxinus mandshurica is one of the precious broadleaf tree species in Northeast China. It has high economic and ecological value.There′s a shortage of F. mandshurica resources and a structural deficiency in resilient cultivars. It′s particularly important to select and breed F. mandshurica with excellent cold resistance in the context of global climate change. The F. mandshurica in Xiaoxing'an Mountains of Heilongjiang Province were selected as the reseach objects. Dendrochronology and wood anatomy were used to compare the radial growth of 52 F. mandshurica families（Families 1-77 in total）. The relationship between the radial growth and xylem anatomical characteristics of F. mandshurica and main climatic factors was clarified. The response of F. mandshurica families to low temperature event was studied. The results showed that there were significant differences in average annual radial growth of F. mandshurica families in Xiaoxing'an Mountains. The radial growth of No. 56， 46 and 38 F. mandshurica families were higher， the values were 4.07 mm， 3.82 mm and 3.71 mm， respectively. The radial growth of F. mandshurica was constrained by temperature and precipitation during the growing season. The radial growth was significantly negatively correlated with the temperature in October of the previous year， positively correlated with the temperature from January to April， and negatively correlated with the precipitation from March to April. Temperature was the primary climatic factor affecting xylem anatomical features of F. mandshurica families in Xiaoxing'an Mountains. Under low temperature stress， the ring width（RW）， mean vessel area （MVA）， total vessel area（TVA） and theoretical hydraulic conductivity（Kh） decreased by 25.5%， 38.2%， 21.8% and 55.1%， compared with non-low temperature years， while vessel density（VD） increased by 64.1%. There was difference in radial growth among F. mandshurica families under low temperature stress. No. 39， 70 and 36 families had stronger resistance to cold， the values of resistance were greater than 1. The recovery of No. 57， 17 and 70families were better， the values of recovery were higher than 1.63. The No.70 F. mandshurica family in Xiaoxing'an Mountains had excellent growth and stronger cold resistance， which could be used as an excellent F. mandshurica family for directional cultivation.

With the popularization of automated production lines， the pressing process of tea cakes has become particularly important for product quality. However， the quality control of Pu'er mini tea cakes produced by automated production lines often falls short of those made by hand. Therefore， the detection of the appearance quality of tea cakes after production by automated lines has become an urgent issue to be addressed. To this end， this study proposes an automated quality detection algorithm for Pu'er tea cakes based on machine vision. The algorithm comprehensively applies various image processing techniques， including Otsu threshold segmentation and Canny edge detection， and introduces multiple algorithm optimization strategies to improve detection accuracy and efficiency. The algorithm can automatically complete the detection and evaluation of the appearance quality of tea cakes and transmit the results in real-time to a Programmable Logic Controller （PLC）. Experimental results show that the algorithm can accurately identify appearance defects of tea cakes， with an average computational accuracy of 95.75%， demonstrating high robustness and reliability. It is suitable for quality control in automated production lines and has a wide range of application prospects， especially in the intelligent transformation of the tea production industry， where it has significant reference value.

The optimization of stand spatial structure is a key issue in achieving sustainable forest management. Traditional optimization methods often exhibit low efficiency in handling complex spatial relationships and large-scale data. This study proposed a stand spatial structure optimization method based on Graph Attention Networks （GAT）. An integrated spatial structure evaluation system was established using the entropy-weighted matter-element analysis method， and a graph neural network model was constructed based on stand data from the Tanglin Forest Farm of the Xinqing Forestry bureau in northern Yichun，Heilongjiang Province. The model was applied to perform multi-objective optimization analysis of stand spatial structure. Experimental results showed that at a 25% harvesting intensity， the integrated spatial structure index improved from 4.336 to 7.256. The GAT model demonstrated superior performance in capturing complex spatial relationships and optimizing multi-objective tasks. This study provides an innovative and intelligent approach for optimizing stand spatial structure and managing forests， contributing to the enhancement of forest ecosystem health and stability.

The failure of structures or components in permafrost caused by foundation diseases poses a certain threat to the ecological security of forest region. Based on field investigations of foundations of power foundations along the section Jagdaqi-Mo'he of Beijing-Mo'he national highway and China-Russia crude oil pipelines （CRCOPs） near the forest region in permafrost in Northeastern China， the main distress characteristics and countermeasures of the foundations were analyzed and summarized， and improved countermeasures were proposed. The results from field surveys showed that transmission line towers foundations suffered from frost jacking accounted for 18.1%， including uniform frost jacking （8.5%） and nonuniform frost jacking （9.6%）， while foundations with thaw settlement occupied only 3.7%. Fissures （2.7%）， spalling （2.7%）， cracks （4.3%）， erosion （5.9%）， tilt （3.7%）， and fracture （0.5%） occurred on the concrete foundation surface. The influences of nonuniform frost jacking and tilting had great influence on the safety of the tower. The concrete protective caps were more severely damaged by frost action， exhibiting fissures （15.4%）， spalling （8.5%）， cracks （15.4%）， and erosion （58%）. Similarly， the tilting and collapse of utility poles were primarily caused by frost jacking and crack. Based on the above damages， it is suggested to build long-term monitoring systems for tracking the structures in permafrost regions， improve and optimize the existing mitigative measures. The findings provide some references for the design， construction， and damage prevention of infrastructures in permafrost regions， aiming to mitigate the impact of engineering on the ecological environment of natural forest region.

Plant residues are an important source of forest soil carbon pool， and changes in soil carbon flux in woodland are closely related to soil carbon pool and carbon cycle. However， current studies on soil organic carbon stability mainly focus on farmland soil. In order to clarify the influence of exogenous carbon input changes on the stability of soil organic carbon， an indoor constant temperature culture experiment was set to study the litter species （Cherry， YH； Sycamore， WT； Poplar， YS）， additive amount （0， 2%， 4% and 6%）， particle size （2 mm， D； 0.25mm， X） as variables， 18 different treatments and 2 controls were concluded. The changes of soil CO₂ release， soil organic carbon content and mineralization intensity under different factors and their interactions were analyzed. Results showed that different litters had significant effects on soil total CO₂ release， and cherry blossom and poplar were more likely to promote soil total organic carbon mineralization. The highest total CO₂ release rate was observed in YHX6 treatment， and the cumulative total CO₂ release of YHD6 treatment was 4.37 times that of CK1. Compared with CK1， the potential mineralizable organic carbon C _p value of 6% added dose was significantly increased. The dynamic changes of soil total organic carbon accumulation mineralization over time can be fitted by the first-order kinetic equation， and the fitting results showed that exogenous carbon input accelerated soil carbon turnover， while litters in small particle size， 6% addition amount and YH type yielded the highest total soil organic carbon turnover rate. WTX2 significantly decreased total organic carbon mineralization intensity， which was only 1.67%. Organic carbon intensity in soil with small particle size was lower than that of large particle size treatment. Therefore， sycamore leaves in small particle size and added with low addition amount can be applied to increase the stability of soil organic carbon and promote the retention of carbon in soil in regional soil organic carbon management.

Due to the decreasing supply of petroleum based plastics resources， the development of biomass resources has attracted extensive attention of researchers recently. The research on environmental friendly antibacterial packaging materials has increasingly become a new trend. Nanocellulose （CNC） derived from biomass has attracted particular attention. In recent years， nanocellulose has been widely used in packaging materials， medical fields， filter media and other fields. It is a good substrate， modifier and additive. Polylactic acid （PLA） is an environmentally friendly and renewable polymer， which can be widely used in the field of food packaging to replace petroleum based plastics. However， its high brittleness and poor antibacterial properties limit the application of PLA in the field of packaging. In this study， two kinds of polylactic acid/carvacrol/nanocelluluse-zinc oxide （PLA/CRV/CNC-ZnO） composite films with antibacterial effect were successfully prepared by solution casting and electrospinning. The effects of CRV and CNC-ZnO hybrid on the properties of the composite films were studied. At the same time， two kinds of composite films were applied to strawberry preservation experiment to explore their preservation effect on strawberry. The PLA/CRV20%/CNC-ZnO3% composite film prepared by solvent casting method and F-PLA/CRV20%/CNC-ZnO3% composite film prepared by electrospinning method were used to freshen strawberries in the same environment， and the fresh-keeping effect of strawberries was evaluated by sensory evaluation， weight loss rate and other tests， and the effects of packaging films prepared by different processes on the fresh-keeping effect of strawberries were compared and analyzed. The results showed that both casting film and spinning film had better preservation effect on strawberry， and the preservation effect of F-PLA/CRV20%/CNC-ZnO3% spinning film on strawberry was better than PLA/CRV20%/CNC-ZnO3% casting film， and the shelf life of strawberry was successfully extended to 10 days at 25 ℃. This study has a certain guiding role in expanding the application of PLA composite film in antibacterial food packaging.

In order to solve the problems of conventional radiative cooling devices limited by the theoretical cooling power limit of 150 W/m² and by the inhibition of radiant power by low-temperature condensate on the radiant surface and the intrinsic water under high humidity conditions， an asymmetric functional structure design based on unidirectional liquid transport proposes a passively cooled wood （REW） with radiative refrigeration and evaporative cooling integrated in series. The wood is delignified by a sodium chlorite solution to enhance its hydrophilicity； then a hydrophobic silica/epoxy solution with high reflectivity and infrared emission properties is coated on the top of the hydrophilic wood to form a hydrophobic radiative cooling layer， while the hydrophilic wood at the bottom serves as an evaporative cooling layer. By virtue of the asymmetric wetting design with unidirectional water transport， low-temperature condensate can be spontaneously transported through the radiation-cooling layer to the evaporative-cooling layer for evaporative cooling， whereas the native water in the evaporative-cooling layer is unable to pass through the radiation-cooling layer to inhibit radiation. As a result， based on the tandem integration of radiant-evaporative cooling， the REW achieves a maximum cooling power of 214 W/m² during daytime， and 172 W/m² even at high humidity of 80%， which is more than 2.8 times higher than that of radiant cooling alone. The potential application of REW in energy-efficient cooling of buildings is demonstrated through building models， providing a universal optimisation strategy for expanding the practical application of passive cooling and new insights into the functional utilisation of wood resources.

The production of plywood consumes a large amount of energy. In order to improve economic efficiency， support carbon peak and carbon neutrality goals， it is necessary to improve energy efficiency and reduce energy consumption. This article took 5 heat exchange logistics in the production process of plywood as the research object， used pinch point technology to analyze the heat exchange network under existing production conditions， and proposed optimization and improvement plans. Aspen Plus was applied to establish a heat exchange network in the plywood production process， calculate the stream flow rate and physical property data of each side line， divide the temperature range， determine the minimum heat transfer temperature difference， and calculate the pinch point temperature. The traditional pinch point method determined the minimum heat transfer temperature difference ∆ T_{\mathrm{m}\mathrm{i}\mathrm{n}} to be 9 ℃. After considering carbon emissions， the minimum heat transfer temperature difference ∆ T_{\mathrm{m}\mathrm{i}\mathrm{n}} was adjusted to 7 ℃， and the average pinch point temperature was 116.5 ℃. The pinch point temperature was used to analyze and diagnose the phenomenon of crossing pinch points in the heat exchange network， accurately located the bottleneck position of the heat exchange network， adjusted the improperly configured cold and hot stream heat exchangers， and achieved the goal of optimizing the entire heat exchange network. After optimization， the usage of cold and hot utilities in the system decreased by 862 465.0 kW and 202 642.0 kW respectively， significantly reducing the energy consumption of the equipment.

The identification of dominant tree species is an important part of forestry resource surveys. Improving the accuracy of dominant tree species identification has significant practical implications for conducting forest resource surveys and related research. Using the Google Earth Engine （GEE） cloud platform， we obtained Sentinel-2 time series images for the Huodong mining area from January to December 2023. The annual growth trajectory features of dominant tree species were constructed based on the CCDC algorithm and the NDFI index. A dominant tree species hierarchical identification method combining "trajectory features + spectral features + texture features" of long-time series remote sensing images was proposed. A control group of "spectral features + texture features" was set up， and hierarchical classification and random forest classification algorithms were used to identify 7 dominant tree species （Pinus tabuliformis， Quercus wutaishansea， Betula playphylla， Larix principis-rupprechtii， Platycladus orientalis， Populus davidiana， and poplars spp.） in the Huodong mining area. The results showed that：1） The NDFI index can effectively distinguish between deciduous forests and evergreen forests； 2） The dominant tree species identification based on "trajectory features + spectral features + texture features" performed well， with an overall classification accuracy of 79.6% and a Kappa coefficient of 0.742 in the study area， which was 7.3% higher than the control group.

In the customization process of passive wooden window manufacturing， reducing material waste during frame cutting is key to cost reduction. This problem is modeled as a one-dimensional cutting stock problem. To address the issue of traditional genetic algorithms where the individual encoding method tends to lead to the destruction of cutting patterns and low exploration efficiency during iterations， a new individual encoding method is proposed to maintain the integrity of cutting patterns throughout the evolutionary process. Additionally， a heuristic strategy and a correction strategy are introduced for individual correction and population evolution. Simulation results show that for different test cases， the average material utilization rate， excluding the last remnants， exceeds 99%， with some improvements in the length of the last remnants compared to other algorithms. For two sets of real production data from enterprises， the proposed algorithm achieves the theoretical lower bound， with average utilization rates （excluding the last remnants） of 99.49% and 99.66%， respectively， outperforming the results of the company's existing software. This demonstrates the algorithm's potential to effectively reduce costs and provide practical solutions in engineering applications.

隧道结构在施工及运营期间，受诸多复杂因素的共同作用，其受力状态与变形特性会随时间逐渐演变。为此，提出一种融合注意力机制的深度学习概率模型，旨在精准预测与评估隧道衬砌结构中关键不利位置的安全状态。首先，采用斯皮尔曼秩相关系数进行数据预处理，筛选出与衬砌结构最不利位置高度相关的土压力数据和混凝土应变数据作为输入特征；随后，设计多层卷积神经网络（CNN）进行多源数据特征提取，并构建特征共享层以融合不同位置的数据信息；接着，将提取的特征送入长短期记忆网络（LSTM）进行时间序列分析预测，并引入自注意力（Attention）机制对特征进行加权优化，从而进一步提高预测的精确度；最后，建立高斯概率回归模型，以解决结构响应预测误差所引起的安全系数计算不确定性量化和评价问题。使用实际隧道工程项目的数据，对不利位置的响应预测结果显示，该模型能够全面考虑多源测点数据在时间和空间上的相关性。在训练集、验证集和预测集上，混凝土应变的预测平均误差分别为0.89、1.02、1.24με，未出现过拟合现象，从而验证所提方法在处理复杂非线性问题的良好泛化能力。此外，采用高斯概率区间预测方法，结合预测得到的安全系数进行了90%置信水平的区间估计，结果显示，二次衬砌3个不利位置的安全系数均位于该置信区间内，从而进一步验证所提模型在隧道衬砌结构安全性评估中的可靠性和实用性。

为降低蒙古栎（Quercus mongolica）组培过程褐化现象，阐明褐化发生是否与抗氧化酶系统及酚类物质产生有关。以蒙古栎成熟合子胚为材料，利用组织培养技术优化蒙古栎再生植株体系获得再生植株，探究聚乙烯吡咯烷酮（PVP）抑制褐化处理对蒙古栎合子胚萌发的生理生化指标的影响。结果表明，PVP 40(40代表PVP平均分子量范围)抑制褐化效果最佳，添加0.2 g/L PVP 40不定芽诱导率最高，为71.17%，其芽增殖系数为3.90，芽生根率为40.37%，移栽存活率为73%;PVP降低了蒙古栎外植体抗氧化酶、多酚氧化酶活性及总酚酶活力，有效抑制褐化现象。PVP有效降低蒙古栎组培褐化效果抑制褐化不再加剧，优化蒙古栎器官再生植株体系，分析PVP抑制褐化处理对蒙古栎合子胚萌发的内在生理机制，为栎属其他树种抑制褐化提供参考。

为探究基于主成分分析（Principal Component Analysis,PCA）下贝叶斯优化（Bayesian Optimization,BO）卷积神经网络（Convolutional Neural Network,CNN）算法（PCA-BO-CNN）模型对人工林树种识别的方法，以提高遥感技术在人工林树种识别中的准确率和鲁棒性。以塞罕坝机械林场为研究区域，利用Sentinel-1遥感数据、Sentinel-2遥感数据、数字高程模型（digital Elevation Model,DEM）数据及森林资源二类调查数据和PCA-BO-CNN算法模型结合，并与其他不同算法模型对比分析，以提高人工林树种识别的准确性。结果表明，1）相比PCA算法处理前，PCA算法处理后多源数据特征的PCA1—PCA39共计39个特征的标准差和特征间的区分性明显提升。因此，PCA算法处理有利于提升对华北落叶松、白桦、樟子松、蒙古栎和云杉主要优势树种及非林地的识别精度；2）在PCA算法处理前，BO-随机森林（random forest,RF）算法模型对主要优势树种及非林地识别的总体准确度（OA）和Kappa系数精度，分别为81.87%,0.754 5。在PCA算法处理后，PCA-BO-CNN算法模型对主要优势树种及非林地识别的OA和Kappa系数精度相对提高，分别为83.10%,0.770 3;3）相比PCA算法处理前的BO-RF算法模型，PCA算法处理后的PCA-BO-CNN算法模型对塞罕坝林场主要优势树种及非林地识别的调和平均数（F1）、OA和Kappa系数的整体精度相对较高。具体，相比BO-RF算法模型PCA-BO-CNN算法模型的OA提升了1.24%，且相比PCA算法处理前PCA-BO-CNN算法模型OA提升了3.71%。与其他算法模型相比，基于PCA-BO-CNN算法模型的人工林树种识别方法具有很强的准确性和鲁棒性，为掌握塞罕坝林场人工林的树种分布，进而了解森林碳储量、森林对气候变化的响应、制定碳减排政策以及推动森林可持续发展提供重要的理论依据。

Microwave curing technology of concrete can significantly improve the early strength of concrete， but there is no uniform design standard for microwave curing method， resulting in great differences in material properties after curing. To explore the influence of microwave curing methods， this study employed the response surface methodology to systematically analyze the influence of microwave curing method on the compressive strength of cement mortar. The relationship model between key microwave curing parameters and material properties was established， and the optimal microwave curing method was determined when the heating temperature was under 40℃ and the heating power was 1 000 W for 30 min. Chemical components and microstructure impacts were studied using X-ray diffraction （XRD）， mercury intrusion porosimetry （MIP）， and scanning electron microscope （SEM）， and it was revealed that a reasonable microwave curing method can promote the hydration degree of mortar and form a denser structure. The temperature variation in microwave curing process was analyzed by combining experimental data and computer simulation， and it was found that microwave curing temperature had hot spot effect. It is concluded that microwave curing temperature is the most important factor affecting the strength of mortar.

The Larix gmelinii forests is one of the most important forest types in Northeast China， playing a crucial role in maintaining the stability of the forest ecosystem in the region. The woody plants in the permanent plot of Larix gmelinii forests in Northeast China were taken as the research object. Through field plot investigation， diversity index and spatial structure characteristics calculation， combined with variance partitioning analysis and redundancy analysis， this study explored the characteristics and influencing factors of tree species diversity in Larix gmelinii forests. The results showed that the average tree species richness of Larix gmelinii forests was 10.75 in Northeast China， Simpson index was 0.72， Shannon-Wiener index was 1.69， and Pielou evenness index was 0.76. The average mingling intensity was 0.57， indicating that the forest stands were moderately mixed. The uniform angle index was 0.54， and the forest stands were clustered. The breast diameter dominance was 0.51， indicating that the forest growth was in a moderate state. The spatial structure characteristics of forest stands and geoclimatic conditions jointly explained 35.9% of the changes in tree species diversity， followed by spatial structure characteristics， with an explanatory rate of 29.2%. Simple term effects showed that spatial structure and geoclimatic indicators such as mingling intensity， latitude， annual mean temperature， and annual mean precipitation were the main influencing factors of tree species diversity changes. The research results will provide theoretical basis and data support for the formulation of management strategies for Larix gmelinii forests in Northeast China.

The moisture content of forest floor litter is a key factor in forest fire occurrences， and its accurate detection is crucial for fire prevention. Near-infrared spectroscopy （NIRS） can directly invert moisture content from spectral data， enabling rapid detection of litter moisture content. However， spectral characteristics differ between fuel types due to variations in light intensity data at different wavelengths， requiring separate detection models for litter from different tree species to match specific light intensity-moisture content inversion relationships. Collecting and labeling spectral data across different forest stands is time-consuming， limiting the practical application of the spectral method. To address this issue， this study proposes a moisture content detection method for forest floor litter based on Bi-LSTM （Bidirectional Long Short-Term Memory） transfer learning. By transferring the trained model parameters to new models， we avoid training models from scratch， thereby improving model learning efficiency and reducing the data required for training. The study demonstrates that the Bi-LSTM method surpasses the traditional inversion approach using LSTM in terms of detection accuracy. Specifically， the mean absolute error （MAE） for Quercus mongolica and Larix gmelinii is reduced by 0.62% and 0.87%， respectively， while the mean squared error （MSE） is reduced by 0.28% and 0.70%， respectively. Moreover， the Bi-LSTM-based transfer learning approach significantly lessens the reliance on labeled NIR spectral data. With a target domain sample size of 300 and a source domain sample size of 1 000， the detection model record an MAE of 3.27%， an MSE of 1.10%， and an R² of 0.918. When compared to models without source domain training， the MAE and MSE show reductions of 2.36% and 1.02%， respectively， and an increase in R² of 0.114. A comparative analysis before and after implementing transfer learning reveals that this methodology offers a novel strategy to diminish the time cost associated with modeling moisture content in spectral litter and to enhance the practical application of spectral detection.

新疆是中国重要的林果产业基地，特色林果业是区域经济发展的重要组成部分。为预防果树病害制约林果业发展，设计一款归一化注意力（normalization-based attention module,NAM）轻量级深度卷积神经网络（MobileNet-V2）果树叶片分类及病害识别模型。其中融入轻量型的归一化注意力机制，提高模型对特征信息的敏感度，使模型关注显著性特征。同时，将L1正则化（L1 regularization或losso）添加到损失函数中，对权重进行稀疏性惩罚，抑制非显著性权重。试验结果表明，在叶片分类中，模型对自构建植物叶片病害识别数据集（Plant Village）、混合数据集的分类结果均表现良好，准确率分别达到97.05%、98.73%、94.91%，具有较好的泛化能力。在病害识别中，MobileNet-V2 NAM模型实现94.55%的识别准确率，高于深度卷积神经网络（AlexNet）、视觉几何群网络（VGG16）经典卷积神经网络（Convolutional Neural Networks,CNN）模型，且模型参数量只有3.56 M。MobileNet-V2 NAM在具有良好准确率同时保持了较低的模型参数量，为深度学习模型嵌入到移动设备提供技术支持。

探究营林措施和环境因子对刺槐生长的综合影响，为黄河流域乃至其他类似生态环境下的造林和生态恢复提供重要的科学依据。以黄土高原刺槐林为研究对象，通过测量地形以及刺槐的生长指标，测定土壤理化性质，采用线性拟合、冗余分析和Pearson相关性分析各因素对刺槐生长的影响。结果表明，1）刺槐胸径与造林密度呈极显著负相关（P<0.01），树高与造林密度呈显著负相关（P<0.05），冠幅与造林密度、坡度呈显著负相关（P<0.05）;2）刺槐树高、冠幅与土壤全磷质量分数呈极显著正相关（P<0.01），胸径、冠幅与土壤铵态氮质量分数呈显著正相关（P<0.05）;3）海拔较高时，土壤结构更为疏松，但养分含量相对较低；坡度较大时土壤养分流失严重，对刺槐的生长产生不利影响；4）土壤毛管孔隙度是影响刺槐生长的最重要因素。因此，在造林和管理过程中，根据实际地形和土壤条件，合理确定造林密度，提升土壤肥力，促进刺槐的生长发育。

By conducting multi-point regional trials on introduced Kazakhstan birch， analyzing its adaptability， screening out good family lines， and providing a theoretical basis for the selection and application of introduced birch family lines. In this study， we analyzed the genetic variation patterns of tree height， diameter at breast height （DBD）， volume of timber， straightness and other traits in 23 11-year-old Kazakhstani birch family lines and two Chinese birch family lines of the Mao'ershan seed source， which were planted in Daqing， Heilongjiang Province， Shangzhi， Heilongjiang Province， and Jinzhou City， Liaoning Province， and fitted a mixed linear model with heteroscedasticity by using the software package R-language ASReml4.0. Best linear unbiased prediction （BLUP） method was used to obtain the breeding values of each family line at different test locations， and combined with Genotype main effects and genotype × environment interaction （GGE） bisplot plots for comprehensive evaluation and selection of each participant and family line. In the mixed-effects model with location as a fixed effect， it was found that the environmental effects were significant among locations， and growth traits reached significant differences （P<0.05， （Z ratio）>1.5） among locations and among family lines within the same test site； family line No. 17 in the Daqing test site had the highest preservation rate and breeding value， and had better salt tolerance； the GGE biplot based on the BLUP method showed that the introduced birch fast-growing property of No.3 family line was the best， and the stability of No.9 family line was the strongest. Based on the comprehensive ranking of the stability and rapidity of each family line， four excellent family lines， No.20， 9， 7 and 24， were selected according to the 30% selection rate and combined with the genetic gain of the volume of each family line.

木材及其制品被广泛应用于人们日常生活，包括家具制造、室内装饰和建筑等领域。木材工业的年产值总量已经超过3万亿元，是重要的国民经济基础产业。然而，木业发展过程中仍存在产品附加值低、企业创新能力弱和生产供应链分散等问题，向新出发、向绿而行，孵化功能木质制造新技术、新材料，培育木业新质生产力是助推行业发展、蓄能助力低碳转型的重要方向。为此，聚焦木材科学前沿发展方向，针对木业新质生产力重要论述，阐明科技创新对木业发展的重要意义，提出木材科学未来发展向极微观深入、向极宏观拓展、向极端条件迈进、向极综合交叉发力4个发展方向，并综述了现阶段具代表性研究成果，梳理代表性木质新产品和功能新材料的发展现状和发展趋势，为进一步提出我国木业新质生产力发展路径奠定基础。

沥青胶砂-集料界面相的低温黏结性能对寒区沥青混合料的低温抗裂性、水稳性等性能有重要影响。基于拉拔试验并采用ImageJ软件对破坏面进行图像分析，通过黏结强度和黏结失效比2个指标，分析不同低温（-10、-20、-30℃）和有水条件下沥青、沥青胶浆、沥青砂浆与石灰岩集料组成的界面相黏结性能。研究结果表明，沥青-集料界面相在-20℃黏结强度最大，黏结失效比随着温度的降低在增大；水的介入会使界面相低温黏结强度的衰减率达到49%，界面连续脱落，黏结失效比增大44%；合适的粉胶比能提高沥青胶浆的低温黏结强度，粉胶比为1.2的沥青胶浆黏结强度为沥青基质的1.44倍，并通过弯曲蠕变劲度试验验证与沥青胶浆低温黏结强度结果的一致性；矿粉和细集料的加入改变了界面的接触形式，破坏位置和黏结失效比也发生了明显变化；沥青胶浆的破坏位置发生于胶浆内部，沥青砂浆的破坏位置多发生于界面处，其黏结失效比远大于沥青胶浆。

目前，虽然已经有一些基于图像处理技术的竹片缺陷检测方案，但这些方案检测存在种类较少、实用性较差且难以部署在机器上等缺陷，为此，提出一种改进的竹片缺陷检测模型。该模型为改进的可变形-端到端目标检测（DeformableDETR）模型，首先将骨干网络替换成由DCNv3卷积为核心而堆叠设计的InternImage，该网络在保留卷积神经网络（CNN）先验特性的情况下还能捕捉到长距离依赖，使提取到的特征空间语义更丰富；然后在特征提取后新增一个采样模块，该采样模块将图像特征抽象为精细的前景特征和少量粗糙的背景特征，不仅能去除冗余的背景特征信息，还能提取高语义前景信息；最后引入一种新颖的协作混合分配训练策略，该策略通过训练由一对多标签分配监督的多个并行辅助头，提高编码器在端到端检测器中的学习能力。此外，使用数据增强来扩展数据集，并使用迁移学习，以增强竹片缺陷的检测。试验结果表明，该改进方法可以提高模型的缺陷特征提取与解析的能力，并在测试数据集上取得了85.7%mAP50（全类平均精确度），单张图片推理时间为0.28 s，检测精度优于其他主流目标检测模型，为竹片缺陷检测提供新的方法。

砂石骨料属于不可再生资源，然而砂石资源短缺与建筑领域大规模扩张之间的供需矛盾日益升级。在我国“双碳”政策的大背景下，将西北地区丰富的风积沙、卵石资源应用到桩基骨料当中，是工程领域实现绿色环保、降本增效的重要手段。基于前期试验得到的新型卵石-风积沙混凝土配合比浇筑混凝土模型桩，再通过模型试验研究新型卵石-风积沙混凝土桩与土复合之后的承载性能变化规律。结果表明，优化配比后的卵石-风积沙混凝土能较好地满足复合地基的强度要求；增加桩长，减小桩径和桩间距，有助于减小地基的沉降量；在400 kPa加载作用下，桩的长度提升至一倍，地基总沉降量减小89%，在桩径和桩间距减小的工况对比可知，沉降量分别减小24%和36.4%。对于桩身应力，提高桩长、桩径，减小桩距，应力均表现出变大的趋势；对于桩土应力，提高桩长、桩径，减小桩距，地基土均表现出应力水平有所降低；对于桩土应力比，桩长越长桩土应力比越大。研究成果可以为卵石和风积沙的推广应用提供数据支持。

针对传统半监督自训练分类方法易导致数据集混乱，影响后续小样本树种分类精度这一问题，基于熵权法（en-tropy weight,EW）与集成学习（ensemble learning,EL）提出EW-EL的半监督小样本树种分类方法。EW-EL在传统半监督自训练分类方法的理论上引入EL的思想，以熵权法作为基础理论设计按基分类器当前训练周期下的F1分数计算的信息熵作为计算权重因子，再依信息熵越大基分类器越不稳定思想设计权重，使集成分类器分类概率更集中，减少集成分类器偏向性。结果显示，EW-EL较传统半监督自训练方法能更有效地均衡数据分布，使新加入数据的伪标签样本类别更准确。EW-EL所得到的小样本树种分类总精度（OA）为0.97、召回率（Recall）为0.96及Kappa系数为0.97,3种指标均优于监督分类、传统半监督自训练方法及利用传统EL机制所构建的半监督自训练方法。其中，EW-EL方法较融合软投票机制的半监督自训练方法，OA与Recall均提升了1%。EW-EL联合简单线性迭代聚类所制成的树种图在所选测试区内达到了94%。此外，进一步分析证明，EW-EL能通过集成诸多分类器，来实现更佳的小样本树种分类结果，更适用于低成本下的相关部门进行林业资源统计的工作。

由于桉树人工林种植模式基本为多代连栽的单一模式，导致了诸多生态学问题的出现。因此，确保人工桉树林能够实现长期、稳定的可持续经营，已成为人工桉树林栽培技术的热点问题。为实现这一目标，采取恰当的树种配置与适度的郁闭度是调整林分结构、增强土壤质量的有效方法。选取佛山市西岸林场6个桉树纯林样地进行改造，研究2种树种配置模式（A为5种山茶科树种，B为5种山茶科树种和2种落叶阔叶树种）和3种桉树郁闭度（Y1为0%,Y2为15%,Y3为30%）对土壤理化性质、酶活性和土壤化学计量比的影响。在不同树种配置模式中，B模式Y3样地3个土层（0～20、20～40、40～60 cm）的土壤毛管持水量、土壤毛管孔隙度和土壤孔隙比与0～20 cm土层的全氮、氮磷比（N∶P）、过氧化氢酶活性和脲酶活性显著高于A模式Y3样地（P<0.05）。在不同郁闭度中，A模式Y3样地3个土层的全磷、有效磷、速效钾、过氧化氢酶活性和脲酶活性显著高于Y1样地（P<0.05），且B模式Y3样地3个土层的有机碳、全氮、碱解氮、有效磷、过氧化氢酶活性和N∶P显著高于Y1样地（P<0.05）。综上所述，合适的树种配置模式和郁闭度有益于土壤养分和酶活性的提高，30%桉树郁闭度下山茶科树种与落叶阔叶树种的模式在华南地区的改造具有良好的应用前景。

Soluble solids content （SSC） is a key indicator for assessing the internal quality of fruits. This study proposes a non-destructive detection method based on hyperspectral image fusion to predict the SSC of blueberries. Three widely used wavelength dimensionality reduction algorithms are employed：Monte Carlo uninformative variable elimination （MC-UVE）， Competitive Adaptive Reweighted Sampling （CARS）， and Successive Projections Algorithm （SPA）， to identify optimal wavelengths. Additionally， a strategy integrating Local Binary Patterns （LBP） and Gray Level Co-occurrence Matrix （GLCM） is proposed for feature extraction. Using spectral features， image features， and fused features， Partial Least Squares （PLS）， Backpropagation Neural Network （BPNN）， and Support Vector Machine （SVM） models are developed for SSC prediction. The results demonstrate that the BPNN model， utilizing spectral features extracted via the CARS algorithm and image features derived from the LBP+GLCM algorithm， yields the highest prediction accuracy. The model's coefficient of determination （R {}_p^{\mathrm{2}}） is 0.926 1， while the Root Mean Square Error of Prediction （RMSEP） is 0.364 1. This study indicates that hyperspectral image fusion technology holds significant potential for the non-destructive prediction of blueberry SSC.

Rare and endangered plants have formed a stable association with their associated tree species in the long-term evolution process， but whether this association is related to allelopathy produced by litters is still unknown. Taking the unique rare and endangered plant Davidia involucrata Baill. and its associated species Cornus controversa Hemsl. in China as research objects， the allelopathic effects of water extracts from different types of litter （branch litter， leaf litter， and their mixture litter） at natural concentrations on each other's seedlings were studied. The results revealed that， 1）the water extract from the branch litter of C. controversa significantly promoted the basal diameter and root length growth of D. involucrata seedlings， and increased the contents of chlorophyll a and b， total chlorophyll， leaf mass fraction of N， and P， while the extracts from leaf litter and branch-leaf mixture litter did not show significant promotional effects. 2）The water extract from the branch litter of D. involucrata significantly promoted the basal diameter growth of C. controversa seedlings and increased the contents of chlorophyll a and b， and total chlorophyll， whereas the extracts from leaf litter and branch-leaf mixture litter significantly reduced the contents of chlorophyll a and b， total chlorophyll， leaf mass fraction of N. 3）The allelopathic effect index indicated that different litter types from C. controversa had allelopathic promotional effects on D. involucrata seedlings， the intensity from large to small was branch， branch-leaf mixture， and leaf； the allelopathic effects of different litter types from D. involucrata on C. controversa seedling were varied， showing promotion by branch litter， and inhibition by leaf litter and branch-leaf mixture litter， with the mixture litter exhibiting stronger inhibitory effects. These findings suggest that the water extracts from different types of litter from D. involucrata and C. controversa have distinct allelopathic effects on each other's seedling growth， and the extracts from the two types of branch litter exhibit the greatest allelopathic promotional effects on seedlings.

This study aims to clarify the spatial distribution characteristics of ridge plant belts on soil water-holding capacity and soil structure in sloping farmland， providing a scientific basis for optimizing ridge plant belt configurations and soil and water conservation measures in Northeast China's black soil region. Sloping farmland with ridge plant belts was selected as the research object （Ridge 1：ridge spacing of 12.5 m； Ridge 2：ridge spacing of 19.5 m）， and sloping farmland was selected as the control. The uniform spatial point sampling method was obtained using basic physical property indicators in the surface layer （0-15 cm）， and to quantify the differences in the spatial distribution characteristics of soil water-holding capacity and soil structure in sloping farmland with different spacing of ridge plant belts. The result showed that， the sloping farmland with ridge construction showed a significant increase in total porosity， capillary porosity， saturated water-holding capacity， field capacity， and capillary water-holding capacity， with a relatively uniform distribution across the slope. In addition， compared to the Ridge 2， the soil of Ridge 1 showed an increase of 0.96-1.11 times in total porosity， 1.21-1.31 times in capillary porosity， 1.03-1.25 times in saturated water-holding capacity， 1.22-1.78 times in field capacity， and 1.33-1.52 times in capillary water-holding capacity， respectively. The soil mechanical stable aggregate mass fraction， MWD （mean weight diameter）， water-stable aggregate mass fraction， and GMD （geometric mean diameter） in the sloping farmland with ridge showed significant improvements across all fields. Compared to the controls， the sloping farmland with ridge increased by 1.01-1.15 times， 0.94-1.61 times， 1-1.17 times， and 1.05-1.55 times， respectively. This indicated that the sloping farmland with ridge effectively improved soil structure compared to the control. Moreover， compared to the sloping farmland with Ridge 2， the soil mechanical stable aggregate mass fraction， MWD， water-stable aggregate mass fraction， and GMD in the sloping farmland with Ridge 1 increased by 1.08-1.14 times， 0.95-1.28 times， 1.07-1.15 times， and 1.14-1.40 times， respectively. Constructing ridges can improve water-holding capacity and soil structure characteristics， with a more significant improvement effect observed in relatively small distances smaller distances between ridges.

为实现冶金固废材料的高值化、规模化利用，采用冶金固废材料（高炉矿渣、粉煤灰、电石渣、石膏）协同制备土壤固化剂，通过正交配比优化试验研究不同固废材料对固化土力学性能的影响并获取最优的参数配方。系统研究固废基固化剂（SWC）固化土的力学性能（无侧限抗压强度、劈裂强度、延迟成型）和耐候性能（水稳定性、冻融循环），并与PO 42.5硅酸盐水泥（OPC）进行对比。结果表明，电石渣对固化剂体系起到重要作用，合理的石膏掺量对强度增长有积极作用；固化土的强度随SWC掺量和养护龄期的增加而增大，4%掺量下的固化土7 d无侧限抗压强度大于1 MPa，劈裂强度与OPC固化土基本相当；SWC固化土表现出更久的施工容许延迟时间，拌和后12 h内强度无下降趋势；掺量大于5%时水稳定系数大于90%，同掺量下抗冻系数与水泥相比提高3%～5%，具备良好的水稳定性与抗冻性；X射线衍射（XRD）和扫描电子显微镜（SEM）分析表明，SWC固化土在水化过程中会生成膨胀性水化产物钙矾石（AFt）和硅酸钙（C-S-H），钙矾石晶体对改善固化土的劈裂强度和抵抗开裂变形能力提高作用显著。

为探究东北红豆杉对全球变暖的适应对策，基于稳定同位素技术，以不同生长阶段东北红豆杉（幼苗、幼树、成树）为研究对象，分析其叶片稳定碳同位素组成(δ¹³C)、水分利用效率（water use efficiency,WUE）的季节动态及影响因子。结果表明，不同生长阶段东北红豆杉叶片δ¹³C值变化范围为-3.051%～-2.939%，平均值为-2.981%±0.061%;WUE变化范围为58.96～71.68μmol/mol，平均值为66.87μmol/mol±6.90μmol/mol。东北红豆杉δ¹³C值和WUE随季节变化由大到小排序为生长季前期（6月）、生长季中期（8月）、生长季后期（9月），不同生长阶段由大到小为成树、幼树、幼苗。不同生长阶段东北红豆杉WUE均与10 cm土壤含水量呈显著线性负相关（幼苗，y=-0.82x+107.29,R²=0.80,P<0.01；幼树，y=-0.34x+84.17,R²=0.45,P<0.05；成树，y=-0.93x+101.32,R²=0.44,P<0.05），土壤含水量是东北红豆杉WUE的主控因子。不同生长阶段东北红豆杉根据植株个体水分需求及受外界水热因子影响程度选择不同的水分利用策略。

为优化制备胺化改性竹粉（AMBP），考察碱预处理浓度、环氧化时间和温度、胺化改性剂和改性温度等因素的影响，并利用扫描电镜（SEM）、傅里叶红外光谱（FTIR）和X射线光电子能谱（XPS）等对其结构进行表征。结果表明，碱预处理浓度、环氧化温度和时间、胺化温度和改性试剂种类均对吸附剂的制备存在显著影响。吸附剂最佳制备条件为，原竹粉3.0 g，经2 mol/L NaOH碱处理，于100 mL的8%NaOH和15 mL的环氧氯丙烷中，40℃下环氧化反应8 h；再在5 mL四乙烯五胺（TEPA）、1 g Na₂CO₃、100 mL水中，40℃下反应2 h。原竹粉的竹纤维结构在改性过程中得到了较好保留，胺化改性后，氮元素质量分数显著增加，引入新的—NH₂、—NH—等基团。吸附剂AMBP-TEPA对水中游离态和络合态Cu（Ⅱ）均具有良好吸附效果。研究结果为竹材的资源化利用提供新的途径和技术支撑。

以大兴安岭呼中典型冻土区为研究对象，研究表层（0～15、15～30 cm）土壤碳储量空间分布规律。通过野外调查、采样和室内分析，基于Landsat 8 OLI影像，利用随机森林（RF）算法建模，分析大兴安岭冻土区表层土壤有机碳空间分布状况。在13个遥感变量因子中筛选相关性最高变量，确定海拔、ARVI、VIGreen、EVI、OSAVI、NDVI,6个环境变量相关性最高，可作为自变量。结果表明，当节点分裂次数（leaf）值为5，决策树数量（trees）值为900时，预测模型的训练集和测试集最为接近，表明此时的模型稳定性最好，0～15、15～30 cm土层训练集R²的拟合精度分别为0.23、0.43，测试集R²的拟合精度分别为0.35、0.24。以此参数预测表层（0～15、15～30 cm）土壤碳储量空间土壤碳空间分布状况分布特征，0～15和15～30 cm土壤碳密度平均值为7.40 kg/m²和14.80 kg/m²,0～15 cm土层土壤碳储量分布大致为由南向北逐渐增加，15～30 cm土层土壤碳储量分布差异不明显，但南向略高于北向。

为提高干形复杂树种材积无损估算的精度，利用地基激光雷达点云数据，构建基于人工蒙古栎最优削度模型的二元材积方程。以哈尔滨市城市林业示范基地的蒙古栎人工林为研究对象，使用地基激光雷达扫描获得完整点云数据，经过裁剪、高程归一化、滤波、单木分割和枝叶分离等处理提取树干结构参数。根据蒙古栎干形特征，选用6种削度方程模型(Biging（1984）、Amidon（1984）、孟宪宇（1982）、Kozak（2004）-Ⅱ、曾伟生等（1997）、Max and Burkhart（1976）)，通过非线性回归拟合，筛选最优模型并构建削度-二元材积方程。研究结果表明，单木定位识别精度为95.22%，树高和胸径的提取值与实测值决定系数（R2）分别为0.97和0.98；最优削度模型拟合结果的决定系数（R²）和均方根误差（RMSE）分别为0.99和0.38 cm。所构建的蒙古栎削度-二元材积方程与现有材积计算方法进行残差分析表明，其估算结果具备可靠性，可为利用地基激光雷达点云数据估算干形复杂的树种材积提供重要技术支持。

针对松材线虫病对松树等树种的威胁、传统处理大径级疫木的方法存在运输困难、效率低、传播风险高以及粉碎效果差等问题，研发大径级疫木粉碎装备，实现疫木的就地粉碎。为此，设计一种粉碎装备的履带底盘机构，采用液压劈砍技术预处理疫木，并通过盘式削片机和锤式粉碎机粉碎木材。利用多体动学仿真软件进行仿真，模拟履带底盘在20°坡度、200 mm高、400 mm宽的垂直壁和200 mm深、400 mm宽的壕沟等复杂地形下的运行特性，分析运行过程中的平移加速度、垂向加速度及俯仰角等关键参数。履带底盘在20°坡度、200 mm高、400 mm宽的垂直壁和200 mm深、400 mm宽的壕沟等复杂地形下，表现出良好的稳定性和通过能力，关键参数均在合理范围内，运行过程中未出现履带脱链等异常现象。大径级疫木粉碎装备可实现定点粉碎，为疫木粉碎和履带底盘设计提供思路和技术支持。

为提高林业运输车辆的保险杠喷涂合格率，以某公司汽车保险杠的涂装质量数据为例，运用排列图对涂装质量数据进行分析得出颗粒、桔皮属于影响喷涂质量的主要因素。从人、机、料、法、环5个方面分析产生颗粒、桔皮的主要原因，并采用斯皮尔曼（Spearman）相关系数进行特征提取以及重要性分析，得出喷漆房的温度、喷漆房相对湿度、机器人喷涂流量、旋杯转速、喷涂距离、喷涂速度、漆的品牌、机器人（机器(1)、机器(2)、…、机器(6)）均会影响保险杠的喷涂质量。运用决策树（classification and regression tree,CART）算法确定喷涂流量、喷漆房的温度、喷漆房相对湿度、机器人(2)和机器人(4)、漆的品牌是影响保险杠喷涂质量的较为关键的因素。结果表明，利用CART分类算法对喷涂质量数据进行分析能够实现对故障点的判别，对于提高保险杠喷涂质量具有借鉴意义。

研究森林公园空气负离子和空气颗粒物变化特征，利用森林生态功能发展康养事业，为地方经济发展提供科学支持。选择北极村国家森林公园兴安落叶松林、白桦林、山杨林和樟子松林为研究对象，并以北极村生活区为对照，使用便携式空气负离子监测仪，在2021年5—10月选择晴天和雨天进行空气负离子、PM₁₀与PM_2.5及其影响因子的观测。研究表明，1)晴天，4种林型空气负离子浓度日动态由大到小表现为展叶盛期（Leaf spreading period,LSP）、展叶初期（Leaf opening period,LOP）、落叶期（Leaf falling period,LFP），均呈单峰曲线变化趋势，峰值出现在12:00—14:00，最高可达到4 207个/cm³，此时期的4种林型空气负离子由大到小表现为兴安落叶松林、白桦林、山杨林、樟子松林；雨天，4种林型的空气负离子浓度呈波动式变化，最高可达6 000个/cm³，显著高于生活区（P<0.05）。晴天，4种林型PM₁₀与PM_2.5质量浓度的日动态变化趋势是双峰曲线，在早晚出现峰值，中午达到谷值，但雨天的波动较小，远远低于晴天的PM₁₀与PM_2.5质量浓度（P<0.05）;2)5—10月4种林型（晴天）空气负离子浓度月变化表现为单峰曲线的趋势，峰值出现在7月，最高可达4 500个/cm³，显著高于生活区（P<0.05），空气颗粒物质量浓度均呈先降低再升高的趋势；3)4种林型空气负离子、PM₁₀和PM_2.5质量浓度与气温、空气湿度、平均风速有显著的相关关系。寒温带森林公园森林生态系统空气负离子质量浓度在2 000～6 000个/cm³，空气颗粒物在40μg/m³以下，空气质量优良，利于人们休养身心。

木材生物彩绘指利用真菌、细菌使木材变色，也称为花斑木。回顾花斑木历史、研究现状与难题并提出展望。花斑木的应用可追溯到500多年前的意大利，当时被广泛应用于镶嵌装饰工艺中。当前，花斑木的研究主要集中在菌纹木和软腐菌色素的研究与利用，由于微生物色素具有可再生、耐久等优点，为提高人工林木材的综合利用率和附加值提供新的途径，也有助于减少合成染料的使用。而心材型（细菌型）花斑木的研究难度较大，需要更多的科学探索和技术突破。目前利用真菌培育花斑木存在菌种保存与衰退、过程污染控制和培育条件控制等难题，而色素提取及媒染则需关注溶剂毒性、色牢度等问题。

The effects of ethephon （ETH）， ethephon inhibitor 1-methylcyclopropene （1-MCP） and cysteine （CYS） on the yield and main quality indexes of rubber tree latex were analyzed， and the dosage threshold was calculated. An optimized orthogonal experimental design was used to analyze 14 treatments with three factors （ETH， 1-MCP， CYS） and four levels （four concentrations of each reagent） for applying rubber tree cut surfaces. Key indicators such as rubber latex yield， dry rubber content， molecular weight， initial plasticity value， plasticity retention index and Mooney viscosity were measured， and the correlation between the indicators was analyzed. The results showed that there were significant differences in yield and dry rubber content of 14 treated rubber trees. Correlation analysis showed that the number-average molecular weight was positively correlated with the weight-average molecular weight and Mooney viscosity， and the correlation coefficient was 0.71 and 0.83， respectively， and the correlation coefficient was negative with the polydispersity indexes， and the correlation coefficient was -0.91. Initial plasticity value was positively correlated with Mooney viscosity， and the correlation coefficient was 0.73. The polydispersity indexes was negatively correlated with Mooney viscosity with the correlation coefficient -0.89. The regression equations based on dry rubber content index were established respectively. The maximum concentration of ethephon， 1-MCP and CYS were 0.15%， 1.08% and 0.41 g/L， respectively. The optimized orthogonal test method can effectively calculate the threshold of the regulator and provide theoretical and practical guidance for the subsequent experiments.

叶绿素作为植物光合作用的主体，在监测植被生长状态，评估固碳能力方面发挥着巨大的作用。遥感技术作为一种高效低成本的对地观测技术，能够通过叶片反射光谱特征实现叶绿素含量（chlorophyll content,Cab，含量为面密度）的估算。然而，叶片光谱会受到叶片含水量、叶细胞结构等影响，从而降低遥感估算Cab的精度。而日光诱导叶绿素荧光（solar-induced chlorophyll fluorescence,SIF）遥感是直接探测叶绿素激发荧光信息，其变化特征与Cab直接相关，在Cab估算中有巨大的潜力。为此，以荧光辐射传输模型（soil canopy observation,photo-chemistry and energy fluxes,SCOPE）为工具，通过敏感性分析确定Cab荧光敏感波段，并建立基于荧光光谱的Cab估算模型，最后利用实测数据验证模型的鲁棒性。研究结果表明，700、730 nm分别为叶绿素高、低敏感波段(SIF₇₀₀、SIF₇₃₀),760 nm为叶绿素高相关性波段(SIF₇₆₀)，以此3波段建立基于荧光比值的Cab估算模型，其中，以SIF₇₆₀与SIF₇₀₀的荧光比值建模精度最优，决定系数R²为0.998 1，均方根误差（root mean square error,RMSE）为0.043 5μg/cm²。SIF₇₀₀与SIF₇₃₀荧光比值和Cab的建模精度最低，但R²和RMSE也分别达到了0.904 8和0.088 6μg/cm²。利用实测数据独立样本对上述3种估算方法进行验证，SIF₇₆₀/SIF₇₃₀估算结果表现最佳，RMSE为0.210 8μg/cm²,SIF₇₀₀/SIF₇₃₀次之，RMSE为0.345 4μg/cm²，但呈现出整体高估现象；SIF₇₆₀/SIF₇₀₀估算结果与实测数据偏差较大，RMSE为0.743 5μg/cm²。综上，SIF₇₆₀/SIF₇₃₀构建的比值植被指数在估算Cab过程中不仅能够保证很好的建模精度，同时又表现出极佳的鲁棒性。研究结果为利用叶绿素荧光遥感手段进行叶片生化参数估算提供技术参考。

苔藓在森林水源涵养、养分固定和水质调控等方面发挥着重要作用，为揭示苔藓对降水化学特征的影响，在大兴安岭北部选取泥炭藓和赤茎藓为研究对象，对2023年6—9月生长季2种苔藓层穿透雨水化学特征进行观测和研究。结果表明，泥炭藓的最大持水量、最大持水率和厚度均显著大于赤茎藓（P<0.01）;2种苔藓穿透雨各离子质量浓度存在差异，泥炭藓淋溶作用最显著的为K⁺，截留作用最显著的为F^-，经过泥炭藓层后相较于林冠层穿透雨K⁺质量浓度提高241%,F^-质量浓度降低51.6%，经过泥炭藓层后金属离子总质量浓度提高71.7%，非金属离子总质量浓度降低19.9%。赤茎藓淋溶作用最显著的是PO₄^3-，截留作用最显著的为Ca²⁺，经过赤茎藓层后相较于林冠层穿透雨PO₄^3-质量浓度提高147.7%,Ca²⁺质量浓度降低5.2%，经过赤茎藓层后金属离子总质量浓度提高10.2%，非金属离子总质量浓度降低62.6%；苔藓层穿透雨离子淋溶质量浓度受p H、温度和林冠层穿透雨离子质量浓度的影响，其中除Fe³⁺、Cl^-外的其余离子均与林冠层穿透雨中离子质量浓度呈负相关性。研究表明林冠层穿透雨在经过苔藓层后水中各离子质量浓度发生了显著变化，进而会对森林土壤化学含量产生影响，结果可为大兴安岭寒温带森林水文和水化学研究提供科学支撑。