Urban agroforestry ecosystems, formed by the intermixing of croplands and urban forests, play a crucial role in enhancing ecological resilience and supporting sustainable landscape management. However, how different proportions of forest and farmland contribute to ecosystem multifunctionality and modify interactions among ecosystem services (ESs) remains insufficiently understood, particularly within rapidly urbanizing environments. In this study, we quantified four keys-grain production, water conservation, soil retention, and carbon sequestration-across urban–rural agroforestry compositions in Changchun City, Northeast China. Using multisource satellite products and biophysical models, we assessed spatiotemporal changes in ES supply, evaluated multifunctionality across five agroforestry composition types, and examined trade-offs and synergies among ESs. The results show clear spatial differentiation driven by the urban-rural forest gradient. Among the five compositions, multifunctionality was lowest in the agricultural area (AA, farmland > 80%), while in mixed urban agroforestry zones-including agriculture-forest area (AFA, farmland > 60% and forest > 20%), agriculture–forest balance area (AFBA, farmland > 40% and forest > 40%), forest-agriculture area (FAA, farmland > 20% and forest > 60%), and forest area (FA, forest > 80%)-multifunctionality declined progressively as forest proportion increased. Strong synergy between grain production and water conservation was observed in AA, whereas in the other compositions, soil retention and water conservation formed the dominant synergistic pair, with synergy slightly strengthening as forest percentage increased. Notably, in FA, the relationship between grain production and soil retention shifted from synergy to trade-off, reflecting functional shifts along the urban forest gradient. These findings provide a scientific basis for optimizing the spatial configuration of urban forests and farmlands, and support nature-based solutions and integrated landscape planning aimed at balancing food security and ecological sustainability in urbanizing regions.

Pine wilt disease (PWD) is one of the fastest-spreading invasive forest pathogens worldwide, causing rapid mortality of infected trees and posing a severe threat to global forest ecosystem security and carbon sink capacity. However, the spatial dynamics and diffusion characteristics of PWD at the stand scale remain poorly understood. In this study, we selected a typical epidemic area in Qingyuan County, Liaoning Province, China, as the study site. By integrating 23 phases of unmanned aerial vehicle (UAV) multispectral imagery, airborne LiDAR data, and field survey observations, we reconstructed the spatiotemporal diffusion process of PWD from 2023 to 2025 and developed a stand-scale, tree-level mortality risk prediction model. Our results show that 50% of transmission events occurred within 17.2 m, and the spatial autocorrelation range was approximately 28 m. The peak of the lethal latency period occurred 17 days after infection, with 40% of mortality events occurring within 11–22 days and 50% of infected trees dying within 40 days. The latency period was significantly shorter in spring and summer than in winter (p<0.01). Among tree-level mortality risk prediction approaches, the random forest model performed best, improving overall accuracy by more than 15% compared with other methods and correctly identifying 98.6% of high-risk individuals. The distance to the nearest infected or dead tree was identified as the dominant predictor, followed by tree height and vegetation parameters reflecting host physiological status. This study reveals the spatial diffusion characteristics of PWD at the stand scale and proposes a tree-level risk prediction framework, providing a theoretical foundation and technical support for dynamic monitoring, early warning, and precision management of PWD.

Grassland carbon storage depends on microbial-mediated interactions between grazing and nitrogen (N) addition, which regulates the balance between soil organic carbon (SOC) retention and priming effects. However, uncertainties regarding these interactive mechanisms constrain projections of SOC vulnerability under global change. We conducted a factorial field experiment involving grazing and N addition in a Leymus chinensis meadow in north-eastern China. In the fifth year of the experiment, we collected soil to conduct a 70-day soil incubation combined with labile carbon (glucose) addition to examine the effects of the grazing and N addition treatments soil carbon priming and carbon retention. Grazing consistently increased priming effects regardless of N addition. In contrast, N addition strongly reduced priming by 41.0% in ungrazed plots but had minimal increase effects (3.2%) under grazing. Mechanistically, bacterial glucose assimilation capacity primarily mediated grazing-dependent N effects on priming, explaining 65.0% of the variation and correlating positively with priming intensity. Grazing notably decreased the net SOC balance (35.7 mg kg-1 soil) and diminished the beneficial effect of N addition on SOC (+79.6% in ungrazed vs. +12.3% in grazed plots). Priming effects and bacterial glucose assimilation were dominant drivers of SOC responses under grazing, exhibiting negative correlations with net SOC balance. Synthesis and applications. Our results show that grazing-induced bacterial dominance in carbon assimilation alters priming effects and net soil carbon balance under N addition, offsetting potential carbon sequestration benefits by accelerating native organic matter decomposition. Thus, microbial carbon assimilation capacity, particularly bacterial substrate assimilation, may serve as an indicator of SOC vulnerability under global change.

Forest defoliating pests are significant global forest disturbance agents, posing substantial threats to forest ecosystems. However, previous studies have lacked systematic analyses of the continuous spatiotemporal distribution characteristics over a complete 3–5 year disaster cycle based on remote sensing data. This study focuses on the Dendrolimus superans outbreak in the Changbai Mountain region of northeastern China. Utilizing leaf area index (LAI) data derived from Sentinel-2A satellite images, we analyze the extent and dynamic changes of forest defoliation. We comprehensively examine the spatiotemporal patterns of forest defoliating pest disasters and their development trends across different forest types. Using the geographical detector method, we quantify the main influencing factors and their interactions, revealing the differential impacts of various factors during different growth stages of the pests. The results show that in the early stage of the Dendrolimus superans outbreak, the affected area is extensive but with mild severity, with newly affected areas being 23 times larger than during non-outbreak periods. In the pre-hibernation stage, the affected areas are smaller but more severe, with a cumulative area reaching up to 8213 hectares. The spatial diffusion characteristics of the outbreak follow a sequential pattern across forest types: Larix olgensis, Pinus sylvestris var. mongolica, Picea koraiensis, and Pinus koraiensis. The most significant influencing factor during the pest development phase was the relative humidity of the year preceding the outbreak, with a q-value of 0.27. During the mitigation phase, summer precipitation was the most influential factor, with a q-value of 0.12. The combined effect of humidity and the low temperatures of 2020 had the most significant impact on both the development and mitigation stages of the outbreak. This study’s methodology achieves a high-precision quantitative inversion of long-term disaster spatial characteristics, providing new perspectives and tools for real-time monitoring and differentiated control of forest pest infestations.

Tilia amurensis is an economically valuable broadleaf tree species in Northeast China.The production of highquality T. amurensis varieties at commercial scales has been greatly limited by the low germination rates.There is thus a pressing need to develop an organogenesis protocol for in vitro propagation of T. amurensis to alleviate a shortage of high-quality T. amurensis seedlings.Here, we established a rapid in vitro propagation system for T. amurensis from mature zygotic embryos and analyzed the effects of plant growth regulators and culture media in different stages.We found that Woody plant medium (WPM) was the optimal primary culture medium for mature zygotic embryos.The highest callus induction percentage (68.76%)and number of axillary buds induced (3.2) were obtained in WPM + 0.89 µmol/L 6-benzyladenine (6-BA) + 0.46 µmol/L kinetin (KT) + 0.25 µmol/L indole-3-butryic acid (IBA) + 1.44 µmol/L gibberellin A3 (GA 3 ).The multiple shoot bud development achieved the highest percentage (83.32%) in the Murashige and Skoog (MS) + 2.22 µmol/L 6-BA + 0.25 µmol/L IBA + 1.44 µmol/L GA 3 .The rooting percentage (96.70%)was highest in 1/2 MS medium + 1.48 µmol/L IBA.The survival percentage of transplanting plantlets was 82.22% in soil:vermiculite:perlite (5:3:1).Our study is the first to establish an effective organogenesis protocol for T. amurensis using mature zygotic embryos.

Enhancing forest carbon storage and carbon sequestration capacity is crucial for achieving carbon neutrality. Scientific forest management can maintain a high level of carbon sequestration capacity in forests, and considering the carbon pool of wood products can extend the time of carbon fixation. However, current predictions of large-scale forest carbon storage and carbon sequestration capacity have overlooked changes in forest carbon absorption with forest age and the buffering effect of wood product carbon pools in the carbon release process. In this paper, we used the Forest Simulation and Optimization System model (FSOS) to analyze the wood supply and carbon sequestration capacities of different management scenarios based on data from the Forest Resources Inventory (2014-2018). The results showed that China's forests could export significant amounts of timber in the future; According to the 9th forest survey report, China's forests produce only 88 million m3 yr-1. Among them, the harvested objects were mainly planted forests, and if all forests (planted forests and natural forests) are involved in forest management planning, the maximum sustainable annual wood supply will reach 286 million m3 yr-1. Moreover, due to the current large proportion of younger forests in China, 358 million m3 of annual wood supply will be achievable in the future (as of the year 2039). Forest management can increase the carbon sequestration capacities in forest ecosystems as well as the wood supply compared to the no management options. In summary, the carbon sequestration potential of unmanaged forests is limited. Appropriate forest management can increase the carbon sequestration potential of forests. The substitution of carbon emission reduction of wood products and bioenergy can also greatly reduce the pressure to achieve carbon neutral strategies.

Particulate pollutants, particularly PM2.5 and PM10, pose serious threats to human health and environmental quality. Therefore, effectively mitigating and reducing the concentrations of these pollutants is crucial for human survival and development. In this study, we analyzed the distribution characteristics of air particulate pollutants in a typical high-latitude city, extracted urban forest areas from high-resolution remote sensing images, and examined the changing characteristics of PM concentration and the relationship between landscape pattern indexes and PM at different scales. The results showed that the concentrations of PM2.5 and PM10 were highest in winter and lowest in summer. At the small scales of 0.5 km × 0.5 km to 1.5 km × 1.5 km, PM concentration decreased with the decrease in PARA (Perimeter–Area Ratio). At the mesoscales of 2 km × 2 km to 2.5 km × 2.5 km, both PARA and CIRCLE (Related Circumscribing Circle) were highly significant (p < 0.001) correlated with PM concentration. At the large scales of 3 km × 3 km to 4 km × 4 km, PARA and PAFRAC (Perimeter–Area Fractal Dimension) were positively correlated with PM concentration. Our study indicates that reducing the complexity of forest patches in small-scale planning can help mitigate particulate air pollution. In the medium scale of urban forest planning, the more regular the forest patch shape and the more similar the patch shape to the strip, the better PM can be alleviated, while in large-scale planning, increasing the forest area and making the patches more normalized and simplified can reduce PM concentration. Moreover, reducing the complexity of forest patches can significantly mitigate PM pollution at all scales. The results of this research provide theoretical support and guidance for improving air quality in urban forest planning at different scales.

Leaf area index (LAI) stands as a pivotal parameter for the quantitative assessment of vegetation growth dynamics, and the rapid acquisition of the effective leaf area index (LAIe) in different scales is crucial for forest ecological monitoring. In this study, forest structure parameters were derived from fusion point cloud data obtained through Airborne Laser Scanning and Terrestrial Laser Scanning in three coniferous forests. The influence of point diameter on the extraction of different forest structure parameters was examined, and an in-depth analysis of the correlations between these parameters and measured LAIe was undertaken. The LAIe inversion model was constructed, and its performance for different forest types was studied. The results show that the precision of the extracted forest structure parameters was highest when the point diameter was set to 0.1 cm. Among the 10 forest structure parameters, internal canopy structures such as canopy openness (CO), gap fraction (GF) and canopy closure (CC) were significantly correlated with measured LAIe (p < 0.01), and the correlations between different forest types were significantly different. In addition, the multiparameter LAIe inversion model was able to distinguish forest type and thus better stimulate measured LAIe; also, it appeared closer to the 1:1 relationship line than the voxel model. This study made up for the inefficiency of LAIe measurement with optical instruments and the inaccuracy of passive remote sensing measurement and proved the possibility of LAIe extraction at a large scale via LiDAR in the future.

本文综述了我国多年来杨树抗旱性的研究进展.目前我国已建立起了杨树抗旱研究的指标体系,研究了在不同胁迫强度下、不同时间段各项抗旱指标的变化规律,以及与抗旱性的相关关系.用主成分分析等方法筛选出了与抗旱性相关的抗旱指标,用隶属度等方法对树种的抗旱性进行综合评价.多年来,我国已通过抗旱指标的综合评价及转基因技术筛选出多个杨树无性系,其抗旱性研究主要集中在苗期,今后有必要进行成年杨树的抗旱性研究以及与苗期抗旱性的相关关系研究,通过分子生物学技术提高自身抗旱能力是适应干旱环境的根本.

Quantifying the urban supply and demand of carbon sequestration services is an important prerequisite for achieving global carbon neutrality goals. However, the spatiotemporal patterns for balancing the supply and demand of carbon sequestration services in urban agglomerations remain unclear. In this study, NPP/VIIRS nighttime light data were used to identify the carbon sequestration service demand and were then combined with the carbon sequestration service supply to analyze the spatiotemporal patterns of supply and demand for carbon sequestration services in the Harbin-Changchun urban agglomeration (HCUA) in Northeast China. Our results indicate that both the supply and demand of carbon sequestration services showed increasing trends from 2012 to 2020 in the HCUA. The regions with increasing supply and demand trends were mainly located in the eastern mountainous and western urban areas, respectively. The total supply and demand of carbon sequestration services in the HCUA were 2080.3 Mt·C yr−1 and 433.6 Mt·C yr−1, respectively. Carbon surpluses (supply > demand) were found in most areas (98%), although particularly in the southeastern mountainous region. However, with rapid urbanization, in most cities, the supply–demand ratio decreased from 2012 to 2020, and the proportion of carbon deficit regions showed a continuous increase, which was mainly distributed in newly developed urban areas. The low supply–high demand (L-H) pattern showed significant spatial mismatching for supply and demand in the HCUA. The proportion of regions with the L-H pattern also showed a rapidly increasing trend from 2012 to 2020, indicating a more obvious carbon deficit trend in the future. This study provides important guidelines for formulating effective policies for energy consumption and carbon sequestration to combat global warming under China’s rapid urbanization.

研究温室内吲哚丁酸(IBA)对紫椴嫩枝扦插生根的影响,探究插穗生根过程中相关理化特征,旨为紫椴优良种质资源的扩大繁殖提供技术和理论依据.采用不同质量浓度IBA处理半木质化插穗,记录生根情况,插后定期取样,测定相关氧化酶活性及内源激素含量的变化.研究结果表明,100 mg/L IBA处理 8 h,紫椴生根率、平均根长和根鲜质量均为最高,分别为 89.52%、14.19 cm、913.43 mg,优于其他处理.IBA处理生根过程中,插穗超氧化物歧化酶(SOD)、过氧化物酶(POD)活性在20、40 d较低,30 d出现峰值,多酚氧化酶(PPO)活性在20、30、40 d均较低,吲哚乙酸氧化酶(IAAO)活性20、30 d处于较低水平,40 d出现峰值;插穗中内源吲哚乙酸(IAA)与IAA/ABA(脱落酸)、IAA/ZR(玉米素核苷),在 20、40 d出现低谷值,30 d出现峰值;GA3(赤霉素)含量 20 d处于低谷值,之后上升,并保持较高水平;ABA含量 0～30 d处于较低水平,随后上升;ZR含量在 20、40 d达到峰值,30 d处于低谷值.由此得到,100 mg/L IBA处理 8 h插穗生根效果最佳.插穗生根过程中,SOD、POD、PPO、IAAO活性低有利于愈伤组织的产生(20 d),SOD、POD活性高有利于不定根的形成(30 d),IAAO活性高有利于不定根的伸长(40 d).较高的ZR含量有利于愈伤组织的产生(20 d),较高的IAA、GA3 含量有利于不定根的诱导产生(30 d),较高的GA3、ABA、ZR含量有利于不定根的伸长发育(40 d).IAA/ABA、IAA/ZR比值较低有利于愈伤组织的产生、不定根的伸长生长,较高有利于不定根的产生.

城市森林凋落物在分散降水、减缓地表径流、防控城市内涝等方面具有重要作用.本研究采用野外调查和室内实验相结合的方法,以长春市南湖公园内5种常见树种蒙古栎(Quercus mongolica)、白桦(Betula platyphylla)、樟子松(Pinus sylvestris var.mongolica)、油松(Pinus tabaliformis)和沙冷杉(Abies holophylla)的凋落物为对象,探究其各分解层累积量及水文效应关系.结果表明:凋落物的厚度与累积量呈正相关;未分解层蒙古栎林凋落物厚度显著高于其他林分(P＜0.05),而半分解层樟子松林和油松林凋落物厚度显著高于其他3种林分(P＜0.05);未分解层凋落物累积量为2.44～9.06 t·hm-2,半分解层累积量为3.85～11.79 t· hm-2,其中油松林和樟子松林数值均较高;凋落物持水量随浸水时间的增加呈现先增长后趋于稳定直至饱和状态,将不同树种各分解层持水率、持水量与浸水时间进行曲线拟合,两者均存在幂函数关系(Y=atb);凋落物未分解层最大持水量为4.52～18.72 t·hm-2,其中蒙古栎林显著高于其他4种林分(P＜0.05),而半分解层凋落物最大持水量为6.00～27.51 t·hm-2;阔叶林未分解层持水性能明显优于针叶林,而在半分解层则针叶林更具优势,林龄是调控凋落物水文特性的重要因素之一;凋落物未分解层最大失水量为2.58～8.00t· hm-2,半分解层最大失水量为2.39～13.78 t·hm-2,其中油松林最大失水量显著高于其他4种林分(P＜0.05).建议长春市及相似立地条件的城市在今后城市公园绿地规划中可考虑多栽植蒙古栎纯林,或蒙古栎与油松、樟子松的混交林,可使城市公园绿地最大化发挥其水文调节功能,解决城市内涝及地下水位下降等问题,助力国家海绵城市建设.

ObjectiveThe aim of the research on the species composition and diversity of forest stands in Zhangguangcailing area was to provide scientific theoretical support for the rational management of forests and the improvement of stand quality in this area.MethodIn this study, a total of 63 plots of 0.1 hm2 were set up in Zhangguangcailing area using the method of geographic grid layout, the species composition, important value, abundance distribution and diversity of each layer under different stand densities (low, medium, high) were studied respectively.Result1) A total of 30 872 plants were surveyed in Zhangguangcailing area, belonging to 60 families,134 genera and 203 species. With the increase of stand density, the number of species at each level showed a trend of first increasing and then decreasing, and the number of species was the largest in medium-density stands. 2) Under each stand density, the arbor layer was mainly composed of Quercus mongolica and Acer mono, the shrub layer was mainly composed of sapling, and the herb layer was mainly composed of Carex, and with the increase of stand density, the herbs gradually changed from very light-loving plants to light-loving plants, and then to very shade-tolerant plants. 3) Under different stand densities, the species richness of each level was the highest in medium-density stands. With the increase of stand density, Shannon-Wiener diversity index (H′), Simpson diversity index (D) and Pielou evenness index (Jsw) of arbor layer and shrub layer showed a trend of first increasing and then decreasing. The Shannon-Wiener diversity index (H′) and Simpson diversity index (D) of the herb layer showed a decreasing trend with the increase of stand density, and the greater the stand density, the more significant the decreasing trend.ConclusionIn conclusion, the medium stand density in Zhangguangcailing area is more conducive to improving the species composition, richness and diversity of the stand, and is beneficial to the improvement of stand quality.

在吉林省敦化市13年生长白落叶松退耕还林林地上,对土壤进行对照(处理A)、去除凋落物(处理B)、去除凋落物并切根(处理C)3种处理,用CI-340光合作用系统对处理后的土壤进行呼吸观测.结果表明:5—9月生长季土壤平均呼吸速率(RS)为2.47μmol·m-2·s-1,凋落物平均呼吸速率(RL)为0.48μmol·m-2·s-1,自养呼吸速率(RA)为0.27μmol·m-2·s-1,异养呼吸速率(RH)为1.72μmol·m-2·s-1.RL、RA、RH占总RS的百分比依次为19.43％、10.93％、69.64％.在生长季节,3种处理的土壤呼吸速率和土壤温度均为单峰曲线,最大值出现在7月;土壤呼吸温度敏感指数Q10分别为2.14、2.15、2.33,表现出呼吸组分越复杂,敏感指数越低的趋势.土壤呼吸速率与土壤含水率呈现抛物线关系且相关显著,最大值出现在含水率为19％时.

In the context of rapid urbanization and global warming, how to use urban green space (UGS) with highefficiency to mitigate the urban heat islands (UHIs) effect in different climate zones has become an urgent issue. However, few studies have provided specific guidance for urban vegetation planning adapting to different climate zones on a global scale. In this study, a cooling effect framework was employed to analyze the influence of UGS patch characteristics, natural and anthropogenic factors on its cooling effect across different climatic zones. We found that the urban cooling islands (UCI) intensity, extent, and gradient of UGS increased with latitude, with lower cooling effect concentrated in arid zones around 30.N, while the largest (0.38 ha) and smallest (0.24 ha) threshold value of efficiency (TVoE) were found in the temperate and arid climate zones. The larger the UGS area, the better the cooling effect in all climate zones. Moreover, complex shapes have a greater UCI intensity in tropical and temperate zones than other regions, while the normalized difference vegetation index (NDVI) has a stronger effect in arid zones. In the continental zone, patch characteristics had little effect. The overall explanation rate of natural and anthropogenic factors on the cooling effect of UGS was 53.5 %, among which natural factors were approximately twice that of anthropogenic factors. Notably, natural factors dominated in the tropical and arid zones affecting UCI, and anthropogenic factors dominated in the temperate and continental zones. The findings of this study expand our understanding of the cooling effect of UGS in different climatic zones around the world and provide insights for urban sustainable development.

Taking trans-boundary area of Yalu River Basin as the study area, based on multi-source data, remote sensing interpretation, InVEST model are used to quantitatively analyze the changes of soil and water conservation functions in the Yalu River Basin from 1988 to 2018, and the trade-off or synergistic relationship between them was discussed. The results show that forestland and cropland are the dominant land use type in the Yalu River Basin. In 2018, the areal percent of forestland is 76.78% and 75.84% on the China side and the North Korea side, respectively; the areal percent of cropland is 20.02 % and 21.63 % on the China side and the North Korea side, respectively; in the past 30 years, the change rate of paddy field area in the basin was the largest, the wetland area increased 330.63 % and 127.52 % on the China side and the North Korea side, respectively. With land use changes, the water yield increased by 118.40×108 mm and 33.76×108 mm on the China side and the North Korea side, respectively; the soil conservation decreased by 111.71×108 t, 102.61×108 t on the China side and the North Korea side, respectively. From 1988 to 2018, the water and soil conservation function showed a synergetic relationship and a synergy−trade-off−synergy relationship on the China side and the North Korea side, respectively. This study provides important data for the function improvement and sustainable development of basin ecosystem.

Atmospheric pollution caused by fine particulate matter (PM2.5) seriously damages human health. Urban forests have the ecological function of purifying the atmosphere, which can effectively reduce the ambient PM2.5 concentration. This paper analyzed the ability of different forest types to mitigate PM2.5 pollution and explored the effects of forest quality and morphological parameters on PM2.5 concentration on the forest patch level. The results concluded that the PM2.5 concentration of the Landscape and Relaxation Forest (LF) was significantly lower than that of the Roadside Forest (RF) and Affiliated Forest (AF) due to the environmental quality of their location. The effective distance of LF on PM2.5 reduction was 80 m, which was significantly higher than RF and AF. The Normalized Difference Vegetation Index (NDVI), which indicated forest growth status, was the most effective parameter for improving the urban forest PM2.5 mitigation ability. The concentration of PM2.5 decreased linearly with the increase in NDVI. The area and perimeter of the forest patches had a significant nonlinear negative correlation with PM2.5 concentration. In addition, the more irregular the shape of the forest patch, the lower the PM2.5 concentration of the forest. Moreover, the simpler shape of RF and AF helped to alleviate PM2.5 pollution. The round shape of AF more efficiently reduced PM2.5 concentration. Our study demonstrated that the surrounding environment, forest growth status, and patch forms determined the PM2.5 reduction capacity of an urban forest. The corresponding management and adjustment methods should be implemented in future urban forest management.

Accurate and effective mapping of forest aboveground biomass (AGB) in heterogeneous mountainous regions is a huge challenge but an urgent demand for resource managements and carbon storage monitoring. Conventional studies have related the plot-measured or LiDAR-based biomass to remote sensing data using pixel-based approaches. The object-based relationship between AGB and multi-source data from LiDAR, multi-frequency radar, and optical sensors were insufficiently studied. It deserves the further exploration that maps forest AGB using the object-based approach and combines LiDAR data with multi-sensor images, which has the smaller uncertainty of positional discrepancy and local heterogeneity, in heterogeneous mountainous regions. To address the improvement of mapping accuracy, satellite LiDAR data from GEDI and ICEsat-2, and images of ALOS-2 yearly mosaic L band SAR (Synthetic Aperture Radar), Sentinel-1 C band SAR, Sentinel-2 MSI, and ALOS-1 DSM were combined for pixel- and object-based forest AGB mapping in a vital heterogeneous mountainous forest. For the object-based approach, optimized objects during a multiresolution segmentation were acquired by the ESP (Estimation of the Scale Parameter) tool, and suitable predictors were selected using an algorithm named VSURF (Variable Selection Using Random Forests). The LiDAR variables at the footprint-level were extracted to connect field plots to the multi-sensor objects as a linear bridge. It was shown that forests’ AGB values varied by elevations with a mean value of 142.58 Mg/ha, ranging from 12.61 to 514.28 Mg/ha. The north slope with the lowest elevation (<1100 m) had the largest mean AGB, while the smallest mean AGB was located in the south slope with the altitude above 2000 m. Using independent validation samples, it was indicated by the accuracy comparison that the object-based approach performed better on the precision with relative improvement based on root-mean-square errors (RIRMSE) of 4.46%. The object-based approach also selected more optimized predictors and markedly decreased the prediction time than the pixel-based analysis. Canopy cover and height explained forest AGB with their effects on biomass varying according to the elevation. The elevation from DSM and variables involved in red-edge bands from MSI were the most contributive predictors in heterogeneous temperate forests. This study is a pioneering exploration of object-based AGB mapping by combining satellite data from LiDAR, MSI, and SAR, which offers an improved methodology for regional carbon mapping in the heterogeneous mountainous forests.

As a symbol of urban civilization and history, old and notable trees (ONTs) are facing challenges brought by rapid urbanization. Changchun is the fastest growing city in Northeast China, and throughout its development process of over 100 years it has preserved many ONTs. This study investigated all the ONTs in Changchun, and analyzed the species diversity, spatial distribution characteristics, dimension, age, and health status of trees by using ecological index and mathematical statistics, and trying to find out the underlying factors regulating their distribution. The results showed that there were 773 old trees belonging to 25 species and 2 notable trees from 1 species in Changchun. Pyrus ussuriensis was the dominant species, followed by Salix matsudana and Ulmus pumila. The urban area, population density, greening rate, and construction history did not influence the species and quantity of ONTs, while the types of land use and tree protection planning were important factors affecting the richness, diversity, and growth conditions of trees. To explore the potential reasons for their existence, the ONTs’ data in Changchun was compared with two nearby cities—Harbin and Shenyang. The comparison indicated that the geographical location and climatic conditions also controlled the distribution of ONTs. The number and dimensions of trees were driven by the history and development process of the city. Our findings suggested that preserving favorable living environments and maintaining a low intensity of human disturbance are critical factors for the survival of ONTs in cities.

The rapid urbanization process and high-intensity construction mode have greatly changed the underlying surface structure and spatial distribution of the natural land surface, further amplified the possibility of urban floods, and made urban security face more serious threats. Urban forest could help to mitigate urban floods through water holding and interception by its unique structures, especially the litter layer. This paper compared the ability of different forest tree species on urban floods mitigation, through analyzing their litter accumulation, litter water holding characteristics, and water interception features of different decomposed layers. The results concluded that Quercus mongolica Fisch. ex Ledeb. (QM) forest, Betula platyphylla Sukaczev (BP) forest, Larix gmelinii (Rupr.) Kuzen. (LG) forest, and Picea koraiensis Nakai (PK) forest were the best choices for improving urban floods resistance in a high-urbanization winter city, for they had larger litter mass and higher maximum water holding and interception capacity. The corresponding results of this study could help environmental management departments worldwide in the selection of tree species in urban greening projects focusing on urban flood control.