Northeast Institute of Geography and Agroecology, Chinese Academy Of Sciences
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Effects of Litter Evenness, Nitrogen Enrichment and Temperature on Short-Term Litter Decomposition in Freshwater Marshes of Northeast China
No full textKnowledge about the effects of global change factors on litter decomposition is critical for accurate prediction of future carbon (C) and nutrient cycles in terrestrial ecosystems. Here, we collected Deyeuxia angustifolia and Carex lasiocarpa litters from freshwater marshes in Northeast China, and conducted an incubation study to examine the effects of nitrogen (N) enrichment (0 and 25 mg N g(-1) litter), temperature (5, 15, and 25 A degrees C), and litter evenness on litter mixing effect and decomposition. Non-additive effects were more common than additive effects during decomposition of litter mixtures, and synergistic effect was detected in two thirds of the litter mixtures. Moreover, litter mixing effects on decomposition varied with N enrichment, incubation temperature, and litter evenness. Both increased proportions of D. angustifolia in litter assemblages and elevated temperature generally accelerated litter decomposition. However, N enrichment slowed litter decomposition at 5 and 15 A degrees C, but had positive or neutral effect at 25 A degrees C. Our results highlight the importance of the interactive effects of N enrichment, temperature, and plant community structure on litter mixing effects during decomposition, and suggest that accelerated litter decomposition induced by climate warming and altered vegetation community would be modulated by N enrichment in freshwater marshes of Northeast China
Effects of Agricultural Biomass Burning on Regional Haze in China: A Review
No full textBurning agricultural straw before and/or after harvest is a common farming practice. Regional and extensive agricultural open field straw burning can cause serious air pollution events. This paper looks at the effects of biomass burning emission on regional haze that should be considered in the forecasting of regional haze. It describes the current state of crop residue burning in China, and analyzes the relationship between biomass burning and regional haze in terms of temporal/spatial patterns and chemical composition. Finally, some suggestions/recommendations are proposed for the recycling of agricultural straw to reduce the impact of biomass burning on regional haze and air quality. We suggest that prescribed open burning would be a more suitable solution in China. We hope that this report about biomass burning and regional haze will bring the issue to the attention of governments and other researchers
Effects of Vegetation and Temperature on Nutrient Removal and Microbiology in Horizontal Subsurface Flow Constructed Wetlands for Treatment of Domestic Sewage
No full textThe promotive effect of constructed wetlands (CWs) with polyculture on treatment efficiency is still a controversial problem. Additionally, there is limited information regarding the influence of temperature on CWs. In this study, the influence of vegetation type, different NH4+-N loading rates, and environmental temperatures on performance of CWs were investigated. Results of different vegetation type indicated that removal of NH4+-N and total phosphorus (TP) in polyculture was higher than other CWs. In polyculture, tested nutrients had removal percentages greater than 94.5%. Results of different NH4+-N loading rates demonstrated that NH4+-N was almost completely removed (around 99.5%) in polyculture under both NH4+-N loading rates. Temperature could substantially influenced the performance of CWs and the removal percentages of NH4+-N, NO3+-N, total nitrogen (TN), and TP in all CWs tended to decrease with a decline of temperature. Especially, a sharp decline in the removal percentage of NO3--N of all CWs (greater than 39%) was observed at low temperature (average temperature of 8.9 degrees C). Overall, the polyculture also showed the best performance with the decline of temperature as compared to other CWs. This study clearly documented that polyculture was an attractive solution for the treatment of domestic sewage and polyculture systems were effective for domestic sewage treatment in CWs even at low temperature (8.9 degrees C)
Effect of Irrigation Regime on Soybean Biomass, Yield, Water Use Efficiency in a Semi-Arid and Semi-Humid Region in Northeast China
No full textSoybean growth is sensitive to soil water conditions. Seasonal drought can cause the loss of soybean yield due to the uneven distribution of annual precipitation in Northeast China. Irrigation could be an effective practice to mitigate the effect of water stress on soybean. The response of soybean growth, yield, water use efficiency (WUE) and irrigation water use efficiency (IWUE) to four amounts of water inputs was investigated. The experiment was conducted in the National Field Research Station of Agro-ecosystem in the Chinese Academy of Science in Hailun County Heilongjiang province Northeast China in 2011 and 2012, and included four water application treatments, they were no irrigation (R), soil water content was kept at 80% (T80), 60% (T60) and 40% (T40) of field water capacity (FWC). Rainproof shelters were used to control rainfall. The effect of different water entry on soybean biomass and plant height was shown in an increasing order of T40 < R < T60 < T80. Soil water kept at about 60% (T60) increased soybean 100 weight by over 5.1% than T40, T80 and R, and reduced flat pod per plant. The soybean yield was the highest in the treatment of T60, and increased averagely by 16.58% compared with that in the treatments of R, T80 and T40. WUE reached the largest values at T40 in 2011 and at T60 in 2012, IWUE were the largest at T80 in 2011 and 2012.. Though more water of 35.7% and 50.3% was applied in the treatment of R than that in the treatment of T60, respectively, in 2011 and 2012, higher soybean yield was found in T60 treatment, suggesting time of water applied was more important than the amount of water entry. Soil water content kept at about the 60% of FWC was optimum in terms of increasing soybean yield and saving irrigation amount in Northeast China
Comparison of different satellite bands and vegetation indices for estimation of soil organic matter based on simulated spectral configuration
No full textSoil organic matter content (SOM) is an important indicator of soil productivity that governs biological, chemical, and physical processes in the soil environment. Previous studies have shown that remote sensing data provide useful information for SOM estimation in different soil types. However, no studies have estimated SOM based on simulated spectral configurations of different satellite sensors. Further study is required to investigate whether SOM estimation accuracy can be improved by combining data from different satellite sensors and developing appropriate algorithms. Therefore, this study investigated new methods for SOM estimation with the following three objectives: (1) analyze the reflectance changes of simulated bands for different SOMs using the spectral response function of various satellite sensors; (2) develop optimal difference index (ODI), optimal ratio index (ORI), optimal normalized vegetation difference index (ONDVI), and optimal enhanced vegetation index (OEVI) algorithms for estimating SOM based on simulated band reflectance; (3) evaluate all bands, ODI, ORI, ONDVI, and OEVI for all simulated bands derived from the data of each satellite, and then combine the simulated data to estimate SOM using the particle swarm optimization (PSO)-support vector machine (SVM) algorithm. The OEVI analysis of simulated WorldView-2 data provided the best SOM estimation accuracy (R-2 = 0.43 and RMSE = 2.62%). The OEVI and ODI algorithms provided better estimation accuracy of SOM from the different simulated satellite data than the ORI and ONDVI algorithms. The best estimation accuracy of SOM was achieved using the PSO-SVM algorithm and simulated WorldView-2 data (R-2 = 0.77, RMSE = 1.66%, and AIC = 99.62). Combination of simulated bands 4-9 of ASTER data and all bands, ODI, ORI, ONDVI, and OEVI of WorldView-2 data provided optimum SOM estimation results (R-2 = 0.82, RMSE = 1.41%, AIC = 82.86). The results indicate that a combination of different satellite data and the PSO-SVM algorithm significantly improves the estimation accuracy of SOM
