Leaf surface is a multifunctional interface between a plant and its environment, which affects both ecological and biological processes. Leaf surface topography directly affects microhabitat availability and ability for deposition. In this study, atomic force microscopy (AFM) and the resuspended particulate matter method were applied to evaluate the adsorptive capacity of the leaf surface. Patterns of particulate‐capturing capacities in different tree species and the effect of leaf surface features on these capacities were explored. Results indicated the following: (1) more total suspended particles (TSP) per unit leaf area were captured by coniferous tree species than by broad‐leaved tree species in a particular order—i.e., Pinus tabuliformis > Pinus bungeana > Salix matsudana > Acer truncatum > Ginkgo biloba > Populus tomentosa; (2) Significant seasonal variation in particulate‐capturing capacities were determined. During the observation period, the broad‐leaved tree species capturing TSP and coarse particulate matter (PM10) clearly exhibited a ∩‐shape pattern— that is, increasing initially and later on decreasing; meanwhile, the ∩‐shape pattern was not clearly shown in P. tabuliformis and P. bungeana. However, no obvious patterns in the absorption of fine particulate matter (PM2.5) were found in the tested tree species; (3) The leaf surface topography, as observed by AFM and scanning electron microscopy, revealed that the broad‐leaved tree exhibits a good correlation between micro‐roughness of leaf surfaces and density of particles settling on leaf surfaces over time. However, the main factors affecting the adsorptive capacities of the leaves in coniferous trees are the number of stomata as well as the amount of epicuticular wax and the properties of the cuticle in different seasons.

The spatial variability of soil organic carbon (SOC) and total nitrogen (STN) levels is important in both global carbon-nitrogen cycle and climate change research. There has been little research on the spatial distribution of SOC and STN at the watershed scale based on geographic information systems (GIS) and geostatistics. Ninety-seven soil samples taken at depths of 0–20 cm were collected during October 2010 and 2011 from the Matiyu small watershed (4.2 km²) of a hilly area in Shandong Province, northern China. The impacts of different land use types, elevation, vegetation coverage and other factors on SOC and STN spatial distributions were examined using GIS and a geostatistical method, regression-kriging. The results show that the concentration variations of SOC and STN in the Matiyu small watershed were moderate variation based on the mean, median, minimum and maximum, and the coefficients of variation (CV). Residual values of SOC and STN had moderate spatial autocorrelations, and the Nugget/Sill were 0.2% and 0.1%, respectively. Distribution maps of regression-kriging revealed that both SOC and STN concentrations in the Matiyu watershed decreased from southeast to northwest. This result was similar to the watershed DEM trend and significantly correlated with land use type, elevation and aspect. SOC and STN predictions with the regression-kriging method were more accurate than those obtained using ordinary kriging. This research indicates that geostatistical characteristics of SOC and STN concentrations in the watershed were closely related to both land-use type and spatial topographic structure and that regression-kriging is suitable for investigating the spatial distributions of SOC and STN in the complex topography of the watershed.

Urban landscape plants are an important component of the urban ecosystem, playing a significant role in the adsorption of airborne particulates and air purification. In this study, six common landscape plants in Beijing were chosen as research subjects, and the adsorption capacities for each different plant leaf and the effects of the leaf structures for the adsorption capacities for particulates were determined. Preliminary results show that needle-leaved tree species adsorbed more airborne particulates than broad-leaved tree species for the same leaf area. Pinus tabuliformis exhibits the highest adsorption capacity, at 3.89 ± 0.026 μg·cm⁻², almost two times as much as that of Populus tomentosa (2.00 ± 0.118 μg·cm⁻²). The adsorption capacities for PM₁₀ of the same tree species leaves, in different polluted regions had significant differences, and the adsorption capacities for PM₁₀ of the tree species leaf beside the Fifth Ring Road were higher than those of the tree species leaves in the Botanical Garden, although the adsorption capacities for PM_2.5 of the same tree species in different polluted regions had no significant differences. By determining the soluble ion concentrations of the airborne particulates in two regions, it is suggested that the soluble ion concentrations of PM₁₀ in the atmosphere in the Botanical Garden and beside the Fifth Ring Road have significant differences, while those of PM_2.5 in the atmosphere had no significant differences. In different polluted regions there are significant adaptive changes to the leaf structures, and when compared with slightly polluted region, in the seriously polluted region the epidermis cells of the plant leaves shrinked, the surface textures of the leaves became rougher, and the stomas’ frequency and the pubescence length increased. Even though the plant leaves exposed to the seriously polluted region changed significantly, these plants can still grow normally and healthily.

Soil microorganisms play a vital role in the biogeochemical cycle, whereas land use change is one of the primary factors that affects the biodiversity and functionality of terrestrial ecosystems. The composition and diversity of bacterial communities (by high-throughput sequencing of the bacterial 16S rRNA gene) were evaluated in the soils of the Montane Region of Northeast China, across different land use types, e.g., natural secondary forest (Quercus mongolica, QM), shrubland (SL), coniferous plantation (Larix gmelinii, LG, and Pinus koraiensis, PK), and agricultural land (Zea mays, ZM). Significant differences in the chemical characteristics and bacterial communities in soils under different land uses were observed in this study. Soil resident TC (total carbon) and TN (total nitrogen) were much higher in secondary natural forest soils, than in coniferous plantation and agricultural soils. Compared with forest and shrubland soils, soil bacterial OTUs, the Chao1 index, and the ACE index were the lowest in the ZM. There were high proportions of Proteobacteria, Actinobacteria, Acidobacteria, Chloroflexi, Gemmatimonadetes, Verrucomicrobia, Bacteroidetes, Planctomycetes, Saccharibacteria, and Nitrospirae in agricultural and forest soils, which accounted for over 90% of the reads in each sample. We found that the dominant group in the forest and shrubland soils was Proteobacteria, while the most dominant group in the ZM was Actinobacteria. The results of both heatmap and principal component analyses displayed groups according to land use types, which indicated that the bacterial communities in the areas under study were significantly influenced by long term differently managed land use. Furthermore, redundancy and Pearson correlation analyses revealed that the bacterial communities were primarily regulated by soil characteristics. This suggested that altered land use patterns initiated changes in the chemical properties of the soils, which affected the composition of microbial communities in this area. This provides a scientific basis for the evolutionary mechanism of soil quality, as well as the rational development and utilization of land resources.

The accurate assessment and prediction of forest ecosystem quality is an important basis for evaluating the effectiveness of regional ecological protection and restoration, establishing a positive feedback mechanism for forest quality improvement and restoration policies, and promoting the construction of an ecological civilization in China. Based on the existing studies at home and abroad, this paper mainly analyzes and summarizes the connotation of forest ecosystem quality, assessment index systems, assessment and prediction methods, and outlooks on the existing problems of imperfect forest ecological quality assessment index systems, preliminary assessment and prediction capabilities, and unknown dynamic responses of forest ecological quality to climate change, etc. Efforts should be made to develop a scientific and standardized assessment index system, produce high-quality forest ecological data products, develop localization of assessment model parameters, and explore forest quality–climate change response mechanisms to provide references for in-depth research to realize the transformation of forest ecosystem quality assessments from historical and status quo assessments to future predictions, and to support the construction of a national ecological civilization.