Spatial distribution characteristics of soil organic carbon in subtropical forests of mountain Lushan, China.

The study on the spatial distribution of forest soil organic carbon (SOC) is of great significance for accurate assessment of carbon storage in forest ecosystems. In the present study, by taking eight kinds of forest soils of Mountain Lushan in the subtropical area as the research object, we studied the spatial distribution characteristics of SOC in this mountainous area. The results showed that the SOC content and SOC density (SOCD) of main forest types in the Mountain Lushan were lower than the national and the world average. The soil layer of Lushan forest was thinner, and the SOC and active SOC (ASOC) contents of different forest types and SOCDs are the highest in the surface soil. SOCD of the topsoil accounts for 32.64-54.03% of the total SOCD in the whole soil profile. Surface litter is an important source of SOC, and the different vegetation types are the important reason for the different spatial distribution of SOC in this area. Soil SOC contents in the high-altitude forest (bamboo forest, deciduous broadleaf forest, Pinus taiwanensis forest, evergreen-deciduous forest, and coniferous-broadleaved mixed forest) were higher than those in the low-altitude forest (evergreen broadleaf forest, shrub, and Pinus massoniana forest). However, the difference in SOC content exhibited at the altitude gradient is significantly lower than that in SOC in the soil profile. This indicates that both soil depth and elevation are the important factors that affected SOC distribution. However, the influence of soil depth on spatial distribution of SOC may be more complex than that of altitude. Vegetation types and soil properties are the main reasons for the large differences of reduction rate in the contents of SOC and ASOC.

Rule-based land use/land cover classification in coastal areas using seasonal remote sensing imagery: a case study from Lianyungang City, China.

Land use/land cover (LULC) inventory provides an important dataset in regional planning and environmental assessment. To efficiently obtain the LULC inventory, we compared the LULC classifications based on single satellite imagery with a rule-based classification based on multi-seasonal imagery in Lianyungang City, a coastal city in China, using CBERS-02 (the 2nd China-Brazil Environmental Resource Satellites) images. The overall accuracies of the classification based on single imagery are 78.9, 82.8, and 82.0% in winter, early summer, and autumn, respectively. The rule-based classification improves the accuracy to 87.9% (kappa 0.85), suggesting that combining multi-seasonal images can considerably improve the classification accuracy over any single image-based classification. This method could also be used to analyze seasonal changes of LULC types, especially for those associated with tidal changes in coastal areas. The distribution and inventory of LULC types with an overall accuracy of 87.9% and a spatial resolution of 19.5 m can assist regional planning and environmental assessment efficiently in Lianyungang City. This rule-based classification provides a guidance to improve accuracy for coastal areas with distinct LULC temporal spectral features.

Simulation of Land Use Change and Ecosystem Service Value Dynamics under Ecological Constraints in Anhui Province, China.

Land use change has a significant impact on the structure and function of ecosystems, and the transformation of ecosystems affects the mode and efficiency of land use, which reflects a mutual interaction relationship. The prediction and simulation of future land use change can enhance the foresight of land use planning, which is of great significance to regional sustainable development. In this study, future land use changes are characterized under an ecological optimization scenario based on the grey prediction (1,1) model (GM) and a future land use simulation (FLUS) model. In addition, the ecosystem service value (ESV) of Anhui Province from 1995 to 2030 were estimated based on the revised estimation model. The results indicate the following details: (1) the FLUS model was used to simulate the land use layout of Anhui Province in 2018, where the overall accuracy of the simulation results is high, indicating that the FLUS model is applicable for simulating future land use change; (2) the spatial layout of land use types in Anhui Province is stable and the cultivated land has the highest proportion. The most significant characteristic of future land use change is that the area of cultivated land continues to decrease while the area of built-up land continues to expand; and (3) the ESV of Anhui Province is predicted to increase in the future. The regulating service is the largest ESV contributor, and water area is the land use type with the highest proportion of ESV. These findings provide reference for the formulation of sustainable development policies of the regional ecological environment.

Assessing the Impact of Land-Use Planning on the Atmospheric Environment through Predicting the Spatial Variability of Airborne Pollutants.

As an important contributor to pollutant emissions to the atmosphere, land use can degrade environmental quality. In order to assess the impact of land-use planning on the atmosphere, we propose a methodology combining the land-use-based emission inventories of airborne pollutants and the long-term air pollution multi-source dispersion (LAPMD) model in this study. Through a case study of the eastern Chinese city of Lianyungang, we conclude that (1) land-use-based emission inventorying is a more economical way to assess the overall pollutant emissions compared with the industry-based method, and the LAPMD model can map the spatial variability of airborne pollutant concentrations that directly reflects how the implementation of the land-use planning (LUP) scheme impacts on the atmosphere; (2) the environmental friendliness of the LUP scheme can be assessed by an overlay analysis based on the pollution concentration maps and land-use planning maps; (3) decreases in the emissions of SO2 and PM10 within Lianyungang indicate the overall positive impact of land-use planning implementation, while increases in these emissions from certain land-use types (i.e., urban residential and transportation lands) suggest the aggravation of airborne pollutants from these land parcels; and (4) the city center, where most urban population resides, and areas around key plots would be affected by high pollution concentrations. Our methodology is applicable to study areas for which meteorological data are accessible, and is, therefore, useful for decision making if land-use planning schemes specify the objects of airborne pollutant concentration.

Spatiotemporal Dynamics of Ecosystem Service Value Determined by Land-Use Changes in the Urbanization of Anhui Province, China.

Urbanization-induced land-use change will lead to variations in the demand and supply of ecosystem services, thus significantly affecting regional ecosystem services. The continuous degradation of ecosystem functions has become a serious problem for humanity to solve. Therefore, quantitative analysis of the corresponding impact of land-use change on ecosystem service value (ESV) is important to socio-economic development and ecological protection. The Anhui province in China has experienced rapid urbanization in recent years, and ecological environmental remediation and protection have become important goals for regional development. In this paper, the province of Anhui has been selected as a case of study, we analyzed the land-use change using Landsat images from 2000, 2005, 2010, and 2015. We then adjusted the equivalent factor of ESV per unit area and estimated the ESV of Anhui province from 2000 to 2015 to analyze the impact of land-use change on ESV. Our results show that (1) paddy field is the main land-use type in Anhui province, the built-up land area has continuously increased, and the water area has continuously decreased; (2) the total ESV of Anhui province decreased from 30,015.58 × 107 CNY in 2000 to 29,683.74 × 107 CNY in 2015 (the rate of change was -1.11%), and regulating services make the greatest contribution to ESV; and (3) land-use change has led to severe ESV variations, especially for the expansion of water area and built-up land. Our study results provide useful insights for the development of land-use management and environmental protection policies in Anhui province.

Urban growth simulation in different scenarios using the SLEUTH model: A case study of Hefei, East China.

As uncontrolled urban growth has increasingly challenged the sustainable use of urban land, it is critically important to model urban growth from different perspectives. Using the SLEUTH (Slope, Land use, Exclusion, Urban, Transportation, and Hill-shade) model, the historical data of Hefei in 2000, 2005, 2010, and 2015 were collected and input to simulate urban growth from 2015 to 2040. Three different urban growth scenarios were considered, namely a historical growth scenario, an urban planning growth scenario, and a land suitability growth scenario. Prediction results show that by 2040 urban built-up land would increase to 1434 km2 in the historical growth scenario, to 1190 km2 in the urban planning growth scenario, and to 1217 km2 in the land suitability growth scenario. We conclude that (1) exclusion layers without effective limits might result in unreasonable prediction of future built-up land; (2) based on the general land use map, the urban growth prediction took the governmental policies into account and could reveal the development hotspots in urban planning; and (3) the land suitability scenario prediction was the result of the trade-off between ecological land and built-up land as it used the MCR -based (minimum cumulative resistance model) land suitability assessment result. It would help to form a compact urban space and avoid excessive protection of farmland and ecological land. Findings derived from this study may provide urban planners with interesting insights on formulating urban planning strategies.

Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta during the 2014-2017 Period.

Large amounts of aerosol particles suspended in the atmosphere pose a serious challenge to the climate and human health. In this study, we produced a dataset through merging the Moderate Resolution Imaging Spectrometers (MODIS) Collection 6.1 3-km resolution Dark Target aerosol optical depth (DT AOD) with the 10-km resolution Deep Blue aerosol optical depth (DB AOD) data by linear regression and made use of it to unravel the spatiotemporal characteristics of aerosols over the Pan Yangtze River Delta (PYRD) region from 2014 to 2017. Then, the geographical detector method and multiple linear regression analysis were employed to investigate the contributions of influencing factors. Results indicate that: (1) compared to the original Terra DT and Aqua DT AOD data, the average daily spatial coverage of the merged AOD data increased by 94% and 132%, respectively; (2) the values of four-year average AOD were high in the north-east and low in the south-west of the PYRD; (3) the annual average AOD showed a decreasing trend from 2014 to 2017 while the seasonal average AOD reached its maximum in spring; and that (4) Digital Elevation Model (DEM) and slope contributed most to the spatial distribution of AOD, followed by precipitation and population density. Our study highlights the spatiotemporal variability of aerosol optical depth and the contributions of different factors over this large geographical area in the four-year period, and can, therefore, provide useful insights into the air pollution control for decision makers.

Succession of bacterial community structure and diversity in soil along a chronosequence of reclamation and re-vegetation on coal mine spoils in China.

The growing concern about the effectiveness of reclamation strategies has motivated the evaluation of soil properties following reclamation. Recovery of belowground microbial community is important for reclamation success, however, the response of soil bacterial communities to reclamation has not been well understood. In this study, PCR-based 454 pyrosequencing was applied to compare bacterial communities in undisturbed soils with those in reclaimed soils using chronosequences ranging in time following reclamation from 1 to 20 year. Bacteria from the Proteobacteria, Chloroflexi, Actinobacteria, Acidobacteria, Planctomycetes and Bacteroidetes were abundant in all soils, while the composition of predominant phyla differed greatly across all sites. Long-term reclamation strongly affected microbial community structure and diversity. Initial effects of reclamation resulted in significant declines in bacterial diversity indices in younger reclaimed sites (1, 8-year-old) compared to the undisturbed site. However, bacterial diversity indices tended to be higher in older reclaimed sites (15, 20-year-old) as recovery time increased, and were more similar to predisturbance levels nearly 20 years after reclamation. Bacterial communities are highly responsive to soil physicochemical properties (pH, soil organic matter, Total N and P), in terms of both their diversity and community composition. Our results suggest that the response of soil microorganisms to reclamation is likely governed by soil characteristics and, indirectly, by the effects of vegetation restoration. Mixture sowing of gramineae and leguminosae herbage largely promoted soil geochemical conditions and bacterial diversity that recovered to those of undisturbed soil, representing an adequate solution for soil remediation and sustainable utilization for agriculture. These results confirm the positive impacts of reclamation and vegetation restoration on soil microbial diversity and suggest that the most important phase of microbial community recovery occurs between 15 and 20 years after reclamation.

454 pyrosequencing analysis of bacterial diversity revealed by a comparative study of soils from mining subsidence and reclamation areas.

Significant alteration in the microbial community can occur across reclamation areas suffering subsidence from mining. A reclamation site undergoing fertilization practices and an adjacent coal-excavated subsidence site (sites A and B, respectively) were examined to characterize the bacterial diversity using 454 high-throughput 16S rDNA sequencing. The dominant taxonomic groups in both the sites were Proteobacteria, Acidobacteria, Bacteroidetes, Betaproteobacteria, Actinobacteria, Gammaproteobacteria, Alphaproteobacteria, Deltaproteobacteria, Chloroflexi, and Firmicutes. However, the bacterial communities' abundance, diversity, and composition differed significantly between the sites. Site A presented higher bacterial diversity and more complex community structures than site B. The majority of sequences related to Proteobacteria, Gemmatimonadetes, Chloroflexi, Nitrospirae, Firmicutes, Betaproteobacteria, Deltaproteobacteria, and Anaerolineae were from site A; whereas those related to Actinobacteria, Planctomycetes, Bacteroidetes, Verrucomicrobia, Gammaproteobacteria, Nitriliruptoria, Alphaproteobacteria, and Phycisphaerae originated from site B. The distribution of some bacterial groups and subgroups in the two sites correlated with soil properties and vegetation due to reclamation practice. Site A exhibited enriched bacterial community, soil organic matter (SOM), and total nitrogen (TN), suggesting the presence of relatively diverse microorganisms. SOM and TN were important factors shaping the underlying microbial communities. Furthermore, the specific plant functional group (legumes) was also an important factor influencing soil microbial community composition. Thus, the effectiveness of 454 pyrosequencing in analyzing soil bacterial diversity was validated and an association between land ecological system restoration, mostly mediated by microbial communities, and an improvement in soil properties in coalmining reclamation areas was suggested.