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.

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In this study, linear spectral mixture analysis (LSMA) is used to characterize the spectral heterogeneity of lava flows from Nyamuragira volcano, Democratic Republic of Congo, where vegetation and lava are the two main land covers. In order to estimate fractions of vegetation and lava through satellite remote sensing, we made use of 30 m resolution Landsat Enhanced Thematic Mapper Plus (ETM+) and Advanced Land Imager (ALI) imagery. 2 m Pleiades data was used for validation. From the results, we conclude that (1) LSMA is capable of characterizing volcanic fields and discriminating between different types of lava surfaces; (2) three lava endmembers can be identified as lava of old, intermediate and young age, corresponding to different stages in lichen growth and chemical weathering; (3) a strong relationship is observed between vegetation fraction and lava age, where vegetation at Nyamuragira starts to significantly colonize lava flows ~15 years after eruption and occupies over 50% of the lava surfaces ~40 years after eruption. Our study demonstrates the capability of spectral unmixing to characterize lava surfaces and vegetation colonization with time, which is particularly useful for poorly known volcanoes or those not accessible for physical or political reasons.

In recent years, the importance of microbial diversity and function to ecosystem restoration has been recognized. The aim of this work was to investigate the diversity and composition of bacterial communities in response to reclamation of a soil subsidence area affected by mining activities. Soil samples were taken in two seasons (December 2012 and July 2013) from a mining reclamation region at the Liuxin national reclamation demonstration area in China and an adjacent coal‐excavated subsidence region. 454 high‐throughput sequencing technology was used to compare the composition and diversity of bacterial communities in reclaimed soil to that in subsided soil. Predominant phyla in soils were Proteobacteria, Actinobacteria, Acidobacteria, and Planctomycetes, with Proteobacteria making up the majority of the community. Long‐term reclamation was found to have significant influences on bacterial communities, and the bacterial community diversity and composition varied between reclaimed and subsided soil. Seasonal fluctuations also contributed to variation in soil bacterial diversity and community composition, but were minor in comparison to effects of reclamation. Differences observed in bacterial community structure and diversity were related to both fertilizer treatment and vegetation, likely through the effects of soil attributes. Soil organic matter and total nitrogen and available potassium were important factors shaping the microbial communities. The reclaimed soil had higher community diversity of bacteria than subsided soil, which suggests that long‐term applications of organic amendments and vegetation mixed sowing had significant impacts on soil remediation and microbial diversity.

The amount and growth rate of carbon emissions have been accelerated on a global scale since the industrial revolution (1800), especially in recent decades. This has resulted in a significant influence on the natural environment and human societies. Therefore, carbon emission reduction receives continuously increasing public attention and has long been under debate. In this study, we made use of the land-use specific carbon emission coefficients from previous studies and estimated the land-use carbon emissions and carbon intensities of the Yangtze River Delta Urban Agglomeration (YRDUA)—which consists of 26 eastern Chinese cities—from Landsat image data and socio-economic statistics in 1995, 2005, and 2015. In addition, spatial autocorrelation models including both global and local Moran’s I were used to analyze the spatial autocorrelation of carbon emissions and carbon intensities. It was found that (1) the YRDUA witnessed a rapidly increasing trend for net carbon emissions and a decreasing trend for carbon intensity over the two decades; (2) the spatial differences in carbon intensity had gradually narrowed, but were large in carbon emissions and had gradually increased; and (3) the carbon emissions in 2005 and 2015 had significant spatial autocorrelations. We concluded that (1) from 1995 to 2015 in the YRDUA, carbon emissions were large for the cities along the Yangtze River and carbon intensities were high for Anhui province’s resource-based cities, while both carbon emissions and carbon intensities were small for Zhejiang province’s cities; (2) over two decades, the increase in carbon emissions from urban land was approximately twice the increase in urban land area. Our study can provide useful insights into the assignment of carbon reduction tasks within the YRDUA.

Timely and effective estimation and monitoring of soil moisture (SM) provides not only an understanding of regional SM status for agricultural management or potential drought but also a basis for characterizing water and energy exchange. The apparent thermal inertia (ATI) and Temperature Vegetation Dryness Index (TVDI) are two widely used indices to reflect SM from remote sensing data. While the ATI-based model is routinely used to estimate the SM of bare soil and sparsely vegetated areas, the TVDI-based model is more suitable for areas with dense vegetation coverage. In this study, we present an iteration procedure that allows us to identify optimal Normalized Difference Vegetation Index (NDVI) thresholds for subregions and estimate their relative soil moisture (RSM) using three models (the ATI-based model, the TVDI-based model, and the ATI/TVDI joint model) from 1 January to 31 December 2017, in the Chinese Loess Plateau. The initial NDVI (NDVI0) was first introduced to obtain TVDI value and two other thresholds of NDVIATI and NDVITVDI were designed for dividing the whole area into three subregions (the ATI subregion, the TVDI subregion, and the ATI/TVDI subregion). The NDVI values corresponding to maximum R-values (correlation coefficient) between estimated RSM and in situ RSM measurements were chosen as optimal NDVI thresholds after performing as high as 48,620 iterations with 10 rounds of 10-fold cross-calibration and validation for each period. An RSM map of the whole study area was produced by merging the RSM of each of the three subregions. The spatiotemporal and comparative analysis further indicated that the ATI/TVDI joint model has higher applicability (accounting for 36/38 periods) and accuracy than the ATI-based and TVDI-based models. The highest average R-value between the estimated RSM and in situ RSM measurements was 0.73 ± 0.011 (RMSE—root mean square error, 3.43 ± 0.071% and MAE—mean absolute error, 0.05 ± 0.025) on the 137th day of 2017 (DOY—day of the year, 137). Although there is potential for improved mapping of RSM for the entire Chinese Loess Plateau, the iteration procedure of identifying optimal thresholds determination offers a promising method for achieving finer-resolution and robust RSM estimation in large heterogeneous areas.

Abstract. Despite a multitude of studies, overall erosion rates as well as the contribution of different erosion processes on Chinese Loess Plateau (CLP) remain uncertain, which hampers a correct assessment of the impact of soil erosion on carbon and nutrient cycling as well as on crop productivity. In this paper we used a novel approach, based on field evidence, to reassess erosion rates on the CLP before and after conservation measures were implemented (1950 vs. 2005). We found that current average topsoil erosion rates are 3 to 9 times lower than earlier estimates suggested. Under 2005 conditions, more sediment was produced by non-topsoil erosion (gully erosion (0.23 ± 0.28 Gt yr−1) and landsliding (0.28 ± 0.23 Gt yr−1) combined) than by topsoil erosion (ca. 0.30 ± 0.08 Gt yr−1). Overall, these erosion processes mobilized ca. 4.77 ± 1.96 Tg yr−1 of soil organic carbon (SOC): the latter number sets the maximum magnitude of the erosion-induced carbon sink, which is ca. 4 times lower than one other recent estimate suggests. The programs implemented from the 1950s onwards reduced topsoil erosion from 0.51 ± 0.13 to 0.30 ± 0.08 Gt yr−1 while SOC mobilization was reduced from 7.63 ± 3.52 to 4.77 ± 1.96 Tg C yr−1. Conservation efforts and reservoir construction have disrupted the equilibrium that previously existed between sediment and SOC mobilization on the one hand and sediment and SOC export to the Bohai sea on the other hand: nowadays, most eroded sediments and carbon are stored on land. Despite the fact that average topsoil losses on the CLP are still relatively high, a major increase in agricultural productivity has occurred since 1980. Fertilizer application rates nowadays more than compensate for the nutrient losses by (topsoil) erosion: this was likely not the case before the dramatic rise of fertilizer use that started around 1980. Hence, erosion is currently not a direct threat to agricultural productivity on the CLP but the long-term effects of erosion on soil quality remain important.

Abstract:To date, little attention has been given to remote sensing-based algorithms for inferring urban surface evapotranspiration. A multi-source parallel model based on ASTER data was one of the first examples, but its accuracy can be improved. We therefore present a modified multi-source parallel model in this study, which has made improvements in parameterization and model accuracy. The new features of our modified model are: (1) a characterization of spectrally heterogeneous urban impervious surfaces using two endmembers (high-and low-albedo urban impervious surface), instead of a single endmember, in linear spectral mixture analysis; (2) inclusion of an algorithm for deriving roughness length for each land surface component in order to better approximate to the actual land surface characteristic; and (3) a novel algorithm for calculating the component net radiant flux with a full consideration of the fraction and the characteristics of each land surface component. HJ-1 and ASTER data from the Chinese city of Hefei were used to test our model's result with the China-ASEAN ET product. The sensitivity of the model to vegetation and soil fractions was analyzed and the applicability of the model was tested in another built-up area in the central Chinese city of Wuhan. We conclude that our modified model outperforms the initial multi-source parallel model in accuracy. It can obtain the highest accuracy when applied to vegetation-dominated (vegetation proportion > 50%) areas. Sensitivity analysis shows that vegetation and soil fractions are two important parameters that can affect the ET estimation. Our model is applicable to estimate evapotranspiration in other urban areas.