In the permafrost region of northeastern China, vegetation and soil environment have showed response to permafrost degradation triggered by global warming, but the corresponding variation of the soil microbial communities remains poorly investigated. Here, a field investigation in the continuous permafrost region was conducted to collect 63 soil samples from 21 sites along a latitudinal gradient to assess the distribution pattern of microbial communities and their correlation with environmental factors. High-throughput Illumina sequencing revealed that bacterial communities were dominated by Proteobacteria, Acidobacteria, Bacteroidetes and Actinobacteria. Both microbial richness and phylogenetic diversity decreased initially and then increased as the latitude increased. UniFrac analysis of microbial communities detected significant differences among latitudes. Variation partitioning analysis and structural equation models revealed that environmental variables, including geographic factors, plant-community factors and soil physicochemical factors, all played non-negligible roles in affecting the microbial community structures directly or indirectly. Redundancy analysis and boosted regression tree analysis further highlighted the influences of soil pH and plant richness on microbial community compositions and diversity patterns. Taken together, these results suggest that the distribution pattern of soil microbial communities shows distinct changes along the latitudinal gradients in northeastern China and is predominantly mediated by soil pH and plant diversity.

In a greenhouse pot experiment, dandelion (Taraxacum platypecidum Diels.) and bermudagrass (Cynodon dactylon[Linn.] Pers.), inoculated with and without arbuscular mycorrhizal fungus (AMF) Rhizophagus irregularis, were grown in chromium (Cr)-amended soils (0 mg/kg, 5 mg/kg, 10 mg/kg, and 20 mg/kg Cr[VI]) to test whether arbuscular mycorrhizal (AM) symbiosis can improve Cr tolerance in different plant species. The experimental results indicated that the dry weights of both plant species were dramatically increased by AM symbiosis. Mycorrhizal colonization increased plant P concentrations and decreased Cr concentrations and Cr translocation from roots to shoots for dandelion; in contrast, mycorrhizal colonization decreased plant Cr concentrations without improvement of P nutrition in bermudagrass. Chromium speciation analysis revealed that AM symbiosis potentially altered Cr species and bioavailability in the rhizosphere. The study confirmed the protective effects of AMF on host plants under Cr contaminations.

h i g h l i g h t sDMA was detected only in shoots of mycorrhizal plants. Mycorrhizal inoculation increased the percentage of As(III) in total As in plants. AM fungi are potentially involved in As transformation in the plant-soil continuum.a r t i c l e i n f o t r a c tIn two pot experiments, wild type and a non-mycorrhizal mutant (TR25:3-1) of Medicago truncatula were grown in arsenic (As)-contaminated soil to investigate the influences of arbuscular mycorrhizal fungi (AMF) on As accumulation and speciation in host plants. The results indicated that the plant biomass of M. truncatula was dramatically increased by AM symbiosis. Mycorrhizal colonization significantly increased phosphorus concentrations and decreased As concentrations in plants. Moreover, mycorrhizal colonization generally increased the percentage of arsenite in total As both in shoots and roots, while dimethylarsenic acid (DMA) was only detected in shoots of mycorrhizal plants. The results suggested that AMF are most likely to get involved in the methylating of inorganic As into less toxic organic DMA and also in the reduction of arsenate to arsenite. The study allowed a deeper insight into the As detoxification mechanisms in AM associations. By using the mutant M. truncatula, we demonstrated the importance of AMF in plant As tolerance under natural conditions.

Vegetation is an essential component of terrestrial ecosystems, and is important in regulating climate change, the carbon cycle, and energy exchange via biophysical factors such as photosynthesis, evapotranspiration, surface albedo, and roughness [1][2][3][4]. Vegetation has obvious interannual and seasonal variations that are recognized as indicators for the detection of climate trends in global change studies [5][6][7][8]. Thus, we can better understand and simulate the dynamic characteristics of terrestrial ecosystems and reveal the regulation of global change by monitoring long-term vegetation variations. Studies of the Pol. J. Environ. Stud. Vol. 26, No. 4 (2017), 1521-1529 Original Research AbstractVegetation is an essential component of terrestrial ecosystems, and it plays an important role in regulating climate change, the carbon cycle, and energy exchange. And permafrost is extremely sensitive to climate change. In particular, aboveground vegetation on permafrost has great sensitivity to that change. The permafrost zone of northeastern China, within middle and high latitudes of the northern hemisphere, is the second-largest region of permafrost in China. It is at the southern edge of the Eurasian cryolithozone. This study analyzes growing-season spatiotemporal variation of the normalization difference vegetation index (NDVI) in this permafrost zone and the correlation between NDVI and climate variables during 1981-2014. Mean growing-season NDVI significantly increased by 0.0028 yr -1 over the entire permafrost zone. The spatial dynamics of vegetation cover in the zone had strong heterogeneity on the pixel scale. Pixels that showed increasing trends accounted for 80% of the permafrost area, and were mostly found in the permafrost zone with the exception of western steppe regions. Pixels that showed decreasing trends (approximately 20% of the permafrost area) were mainly in the cultivated and steppe portions of the study area. Our results indicated that temperature was the dominant influence on vegetation growth during the growing season in most permafrost zones.

Black carbon (BC) from incomplete combustion of biomass and fossil fuel is widespread in sediments and soils because of its high stability in nature and is considered an important component of the global carbon sink. However, knowledge of BC stocks and influencing factors in forest ecosystems is currently limited. We investigated soil BC contents in burned boreal forests of the Great Khingan Mountains, northeast China. We collected soil samples from 14 sites with different fire severities, slope positions and aspects. The samples were analyzed by the chemo-thermal oxidation method to obtain their BC concentrations. The BC concentrations of the studied soils ranged from 0.03 to 36.91 mg C g −1 , with a mean of 1.44 ± 0.11 mg C g −1 . BC concentrations gradually decline with depth, and that was significantly less in the 20-30 cm layer compared to all shallower layers. Forests burned by moderate-severity fires had the highest soil BC, the shady aspect had higher soil BC than the sunny aspect. Our results provide some basic data for evaluating the soil BC sink in boreal forests, which is a useful amendment to current carbon budget and carbon cycle in boreal forest ecosystems.

Background Soil microorganisms in the thawing permafrost play key roles in the maintenance of ecosystem function and regulation of biogeochemical cycles. However, our knowledge of patterns and drivers of permafrost microbial communities is limited in northeastern China. Therefore, we investigated the community structure of soil bacteria in the active, transition and permafrost layers based on 90 soil samples collected from 10 sites across the continuous permafrost region using high-throughput Illumina sequencing. Results Proteobacteria (31.59%), Acidobacteria (18.63%), Bacteroidetes (9.74%), Chloroflexi (7.01%) and Actinobacteria (6.92%) were the predominant phyla of the bacterial community in all soil layers; however, the relative abundances of the dominant bacterial taxa varied with soil depth. The bacterial community alpha-diversity based on the Shannon index and the phylogenetic diversity index both decreased significantly with depth across the transition from active layer to permafrost layer. Nonmetric multidimensional scaling analysis and permutation multivariate analysis of variance revealed that microbial community structures were significantly different among layers. Redundancy analysis and Spearman’s correlation analysis showed that soil properties differed between layers such as soil nutrient content, temperature and moisture mainly drove the differentiation of bacterial communities. Conclusions Our results revealed significant differences in bacterial composition and diversity among soil layers. Our findings suggest that the heterogeneous environmental conditions between the three soil horizons had strong influences on microbial niche differentiation and further explained the variability of soil bacterial community structures. This effort to profile the vertical distribution of bacterial communities may enable better evaluations of changes in microbial dynamics in response to permafrost thaw, which would be beneficial to ecological conservation of permafrost ecosystems.

Land use regression (LUR) modeling is a promising method for assessing the spatial variation of air pollutant concentrations. We developed an LUR model for air pollutants (SO 2 , NO 2 , and PM 10 ) in the central cities of Liaoning Province using monitoring data collected during 2013. We evaluated whether the addition of annual satellite aerosol optical depth (AOD) observations and fi ve canyon indicators (building height, building coverage ratio, fl oor area ratio, building shape coeffi cient, and high-rise building ratio) improved the LUR models. Out-of-sample "10-fold" cross validation was used to quantify the accuracy of the model predictions. Our results showed that the gross domestic product (GDP) and the distance to the nearest industrial emissions were the common variables for the models. Annual AOD demonstrated weak correlations with air pollutant concentrations because of its instantaneity, low resolution, and limited precision; however, it was useful for improving the coeffi cient of determination (R 2 ) of the LUR models. The full models incorporating the annual AOD data and canyon indicators showed further improvement. The improvements of R 2 were 0.22, 0.19, and 0.39 for SO 2 , NO 2 , and PM 10 , respectively, demonstrating that the consideration of canyon indicators could still be valuable and could be used in LUR models.

Frequent hazy weather has been one of the most obvious air problems accompanying China’s rapid urbanization. As one of the main components of haze pollution, fine particulate matter (PM2.5), which severely affects environmental quality and people’s health, has attracted wide attention. This study investigated the PM2.5 distribution, changing trends and impact of urban factors based on remote-sensing PM2.5 concentration data from 2000 to 2015, combining land-use data and socioeconomic data, and using the least-squares method and structural equation model (SEM). The results showed that the high concentration of PM2.5 in China was mainly concentrated in the eastern part of China and Sichuan Province. The trends of the PM2.5 concentration in eastern part and Northeast China, Sichuan, and Guangxi Provinces were positive. Meanwhile, the ratios of increasing trends were strongest in built-up land and agricultural land, and the decreasing trends were strongest in forest and grassland, but the overall trends were still growing. The SEM results indicated that economic factors contributed most to PM2.5 pollution, followed by demographic factors and spatial factors. Among all observed variables, the secondary industrial GDP had the highest impact on PM2.5 pollution. Based on the above results, PM2.5 pollution remains an important environmental issue in China at present and even in the future. It is necessary for decision-makers to make actions and policies from macroscopic and microscopic, long-term and short-term aspects to reduce pollution.