Northeast Institute of Geography and Agroecology, Chinese Academy Of Sciences
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Does Warming Influence Freeze-Thaw Treated Dissolved N in Wetland Soil Solutions
No full textWetland soil columns with water overlying and without snowpacks were exposed to freeze thaw treatment (FTT1), freeze-thaw treatment with elevated 2 degrees C (FTT2) and growing-season treatment (GST). We found elevating 2 degrees C under freeze-thaw condition without snowpacks and with water overlying could not significantly influence NH4+-N and NO3--N concentrations in wetland soil solutions (p>0.05). Except for the first treatment cycle and 5-10 cm soil layer, NH4+-N and NO3--N concentrations of GST were not significantly different from that of FTT1 and FTT2 (p>0.05) indicating there might be not significant differences of NH4+-N and NO3--N concentrations in wetland soil solutions between in freeze-thaw season and growing season
Effects of sediment burial disturbance on macro and microelement dynamics in decomposing litter of Phragmites australis in the coastal marsh of the Yellow River estuary, China
No full textFrom April 2008 to November 2009, a field decomposition experiment was conducted to investigate the effects of sediment burial on macro (C, N) and microelement (Pb, Cr, Cu, Zn, Ni, and Mn) variations in decomposing litter of Phragmites australis in the coastal marsh of the Yellow River estuary. Three one-off sediment burial treatments [no sediment burial (0 mm year(-1), S-0), current sediment burial (100 mm year(-1), S-10), and strong sediment burial (200 mm year(-1), S-20)] were laid in different decomposition sites. Results showed that sediment burials showed significant influence on the decomposition rate of P. australis, in the order of S-10 (0.001990 day(-1)) a parts per thousand aEuro parts per thousand S-20 (0.001710 day(-1)) > S-0 (0.000768 day(-1)) (p 0.05). With increasing burial depth, N, Cr, Cu, Ni, and Mn concentrations generally increased, while C, Pb, and Zn concentrations varied insignificantly. Sediment burial was favorable for C and N release from P. australis, and, with increasing burial depth, the C release from litter significantly increased, and the N in litter shifted from accumulation to release. With a few exceptions, Pb, Cr, Zn, and Mn stocks in P. australis in the three treatments evidenced the export of metals from litter to environment, and, with increasing burial depth, the export amounts increased greatly. Stocks of Cu and Ni in P. australis in the S-10 and S-20 treatments were generally positive, evidencing incorporation of the two metals in most sampling times. Except for Ni, the variations of C, N, Pb, Cr, Cu, Zn, and Mn stocks in P. australis in the S-10 and S-20 treatments were approximated, indicating that the strong burial episodes (S-20) occurred in P. australis marsh in the future would have little influence on the stocks of these elements. With increasing burial depths, the P. australis was particularly efficient in binding Cu and Ni and releasing C, N, Pb, Cr, Zn, and Mn, implying that the potential eco-toxic risk of Pb, Cr, Zn, and Mn exposure might be very serious. This study emphasized the effects of different burials on nutrient and metal cycling and mass balance in the P. australis marsh of the Yellow River estuary
Evaluating general allometric models: interspecific and intraspecific data tell different stories due to interspecific variation in stem tissue density and leaf size
No full textThe ability of general scaling models to capture the central tendency or dispersion in biological data has been questioned. In fact, the appropriate domain of such models has never been clearly articulated and they have been supported and challenged using both interspecific and/or intraspecific data. Here, we evaluate several simplifying assumptions and predictions of two prominent scaling models: West, Brown and Enquist's fractal model (WBE) and a null model of geometric similarity (GEOM). Using data for 53 herbaceous angiosperm species from the Songnen Grasslands of Northern China, we compared both the interspecific and intraspecific scaling relationships for plant geometry and biomass partitioning. Specifically, we considered biomass investment in shoots and leaves as well as related several traits not commonly collected in plant allometric analyses: shoot volume, leaf number, and mean leaf mass. At the interspecific level, we find substantial variation in regression slopes, and the simplifying assumptions of WBE and predictions of both the WBE and GEOM models do not hold. In contrast, we find substantial support for the WBE model at the intraspecific level, and to a lesser extent for GEOM. The differences between our results at interspecific and intraspecific levels are due to the fact that leaf size and stem tissue density vary considerably across species in contrast to the simplifying assumptions of WBE. These results highlight the domain within which simplifying model assumptions might be most appropriate, and suggest allometric models may be useful points of departure within some species, growth forms or taxonomic groups
Holocene peatland initiation and carbon storage in temperate peatlands of the Sanjiang Plain, Northeast China
No full textThe Sanjiang Plain (SJP) wetland is the largest freshwater marshland in China. Peatlands were initiated early and are widely distributed across the SJP and form a large carbon (C) pool. Consequently, there is a growing interest in understanding past, present, and future peatland dynamics. Most studies on peatland dynamics have been carried out on boreal and subarctic region; however, there are limited data about peatland dynamics on temperate region, such as SJP wetland, which is sensitive to climate change and human disturbance. Here, we presented a data synthesis of basal peat ages, peatland area, and peat C accumulation rate in the SJP to examine Holocene peatland dynamics and climate sensitivity, along with total C storage and their future fate. We show that peatland initiation in the SJP started in the early Holocene, but the most intense period of peatland initiation occurred during the late Holocene, when the climate was colder and drier than the early and mid-Holocene. And the C accumulation rate also continued to increase during the late Holocene. Our results suggest that insolation and monsoon intensity as well as the local topographic characteristics and hydrology during the late Holocene in the SJP might have played an important role in causing the highest rates of peatland initiation and C accumulation. Based on the Second National Wetland Resources Survey data, we estimated that the total peatland covered an area of about 10,520km(2) on the SJP and currently stores similar to 0.26PgC. However, human activities, together with the widespread warming on the SJP over the past 60years, not only reduce the area of wetlands but also have switched it from being a net C sink to a significant C source
Influence of environmental factors on spectral characteristics of chromophoric dissolved organic matter (CDOM) in Inner Mongolia Plateau, China
No full textSpectral characteristics of chromophoric dissolved organic matter (CDOM) were examined in conjunction with environmental factors in the waters of rivers and terminal lakes within the Hulun Buir plateau, northeast China. Dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorous (TP) were significantly higher in terminal lakes than rivers waters (p < 0.01). Principal component analysis (PCA) indicated that non-water light absorption and anthropogenic nutrient disturbances were the likely causes of the diversity of water quality parameters. CDOM absorption in river waters was significantly lower than terminal lakes. Analysis of the ratio of absorption at 250 to 365 nm (E-250:365), specific ultraviolet (UV) absorbance (SUVA(254)), and the spectral slope ratio (S-r) indicated that CDOM in river waters had higher aromaticity, molecular weight, and vascular plant contribution than in terminal lakes. Furthermore, results showed that DOC concentration, CDOM light absorption, and the proportion of autochthonous sources of CDOM in plateau waters were all higher than in other freshwater rivers reported in the literature. The strong evapoconcentration, intense ultraviolet irradiance, and landscape features of the Hulun Buir plateau may be responsible for the above phenomenon. Redundancy analysis (RDA) indicated that the environmental variables total suspended matter (TSM), TN, and electrical conductivity (EC) had a strong correlation with light absorption characteristics, followed by total dissolved solid (TDS) and chlorophyll a. In most sampling locations, CDOM was the dominant non-water light-absorbing substance. Light absorption by non-algal particles often exceeded that by phytoplankton in the plateau waters. Study of these optical-physicochemical correlations is helpful in the evaluation of the potential influence of water quality factors on non-water light absorption in cold plateau water environments. The construction of a correlation between DOC concentration and water quality factors may help contribute to regional estimates of carbon sources and fate for catchment carbon budget assessments
Retrieving soil surface temperature under snowpack using special sensor microwave/imager brightness temperature in forested areas of Heilongjiang, China: an improved method
No full textSoil surface temperature (T-s) is an important indicator of global temperature change and a key input parameter for retrieving land surface variables using remote sensing techniques. Due to the masking in the thermal infrared band and the scattering in the microwave band of snow, the temperature of soil surfaces covered by snow is difficult to infer from remote sensing data. We attempted to estimate T-s under snow cover using brightness temperature data from the special sensor microwave/imager. T-s under snow cover was underestimated due to the strong scattering effect of snow on upward soil microwave emissions at 37 GHz. The underestimated portion of T-s is related to snow properties, such as depth, grain size, and moisture. Based on the microwave emission model of layered snowpacks, the simulated results revealed a linear relationship between the underestimated T-s and the brightness temperature difference (TBD) at 19 and 37 GHz. When TBDs at 19 and 37 GHz were introduced to the T-s estimation method, accuracy improved, i.e., the root mean square error and bias of the estimated T-s decreased greatly, especially for dry snow. This improvement allows T-s estimation of snow-covered surfaces from 37 GHz microwave brightness temperature. (C) 2016 Society of Photo-Optical Instrumentation Engineers (SPIE
Source identification and availability of heavy metals in peri-urban vegetable soils: A case study from China
No full textThe purpose of this study was to investigate the total and available concentrations of Pb, Cr, Cu, Ni, and Zn in the vegetable soils from the outskirts of a heavy industry city, Northeast China, and to assess the sources of heavy metals and their availability. The average concentrations of Pb, Cu, and Zn were significantly higher than their background values of Changchun topsoil. Principal component analysis, cluster analysis, and geostatistical analysis results suggested that Pb, Cu, and Zn were consistently from anthropogenic sources, while Cr and Ni were from natural sources with low concentrations. Kriging results showed that several hotspots of high metal concentration were identified by the geochemical maps and caused by different environmental factors. Although the available (ethylene-diamine-tetraacetic acid-extractable) fractions showed much lower values than total concentrations of metals, Pb and Cu had relatively high AR(a) (average availability ratio of metals) values. Our findings show that most of the studied metals had accumulated to some extent in vegetable soils and several hotspots of high metal concentration appeared at the peri-urban of Changchun. The concentrations of some metals in peri-urban vegetable soils have been largely affected by anthropogenic activities. Appropriate measures should be taken to effectively control heavy metal levels in vegetable soils and thus protect human health
Water Quality Analysis and Prediction Using Hybrid Time Series and Neural Network Models
No full textChagan Lake serves as an important ecological barrier in western Jilin. Accurate water quality series predictions for Chagan Lake are essential to the maintenance of water environment security. In the present study, a hybrid AutoRegressive Integrated Moving Average (ARIMA) and Radial Basis Function Neural Network (RBFNN) model is used to predict and examine the water quality [Total Nitrogen (TN), and Total Phosphorus (TP)] of Chagan Lake. The results reveal the following: (1) TN concentrations in Chagan Lake increased slightly from 2006 to 2011, though yearly variations in TP were not significant. The TN and TP levels were mainly classified as Grades IV and V, (2) The hybrid ARIMA and RBFNN model's RMSE values for the observed and predicted data were 0.139 and 0.036 mg L-1 for TN and TP, respectively, which indicated that the hybrid model describes TN and TP variations more comprehensively and accurately than single ARIMA and RBFNN model. The results serve as a theoretical basis for ecological and environmental monitoring of Chagan Lake and may help guide irrigation district and water project construction planning for western Jilin Province
