ALBERT

Description: We applied Gravity Recovery and Climate Experiment (GRACE) Tellus products in combination with Global Land Data Assimilation System (GLDAS) simulations and data from reports, to analyze variations in terrestrial water storage (TWS) in China as a whole and eight of its basins from 2003 to 2013. Amplitudes of TWS were well restored after scaling, and showed good correlations with those estimated from models at the basin scale. TWS generally followed variations in annual precipitation; it decreased linearly in the Huai River basin (−0.56 cm yr−1) and increased with fluctuations in the Changjiang River basin (0.35 cm yr−1), Zhujiang basin (0.55 cm yr−1) and southeast rivers basin (0.70 cm yr−1). In the Hai River basin and Yellow River basin, groundwater exploitation may have altered TWS's response to climate, and TWS kept decreasing until 2012. Changes in soil moisture storage contributed over 50 % of variance in TWS in most basins. Precipitation and runoff showed a large impact on TWS, with more explained TWS in the south than in the north. North China and southwest rivers region exhibited long-term TWS depletions. TWS has increased significantly over recent decades in the middle and lower reaches of Changjiang River, southeastern coastal areas, as well as the Hoh Xil, and the headstream region of the Yellow River in the Tibetan Plateau. The findings in this study could be helpful to climate change impact research and disaster mitigation planning.

Description: The aim of this study was to explore the effects of grazing on the formation of the spatial pattern of elm growth in a sparse woodland steppe. We used a point pattern method to analyze the elm trees within different diameter at breast height (DBH) classes in both grazed and fenced plots, which were established in Horqin Sandy Land of northeastern China. The results showed that, in the grazed plot, the distances where transformation between random and clustered patterns occurred in class 1 (10 cm  ≤  DBH  ≤  15 cm) and class 2 (15 cm   20 cm) were 3.13, 3.13 and 7.85 m, respectively. In the fenced plot, at distances larger than 67.72 m there was a negative association between classes 1 and 2, which was also the case between classes 2 and 3 and between classes 1 and 3 for distances greater than 104.09 and 128.54 m, respectively. Meanwhile, negative associations occurred only at distances larger than 29.38 m in the grazed plot. These findings suggest that grazing reduced the competition intensity between elm trees; and therefore, grazing management could be an effective strategy used to regulate the elm population in the degraded sandy land of northern China.

Description: Changes in elemental stoichiometry, in most cases, attributed to land use alterations may cause vital impacts on the nutrient status and environmental quality of ecosystems. Here, we studied the stoichiometry and spatial distribution patterns of soil organic carbon (SOC), total soil nitrogen (TN), and total soil phosphorus (TP) in topsoil (0–20 cm; 1207 samples) ecosystems in a representative catchment of subtropical hilly region of China. Its main land uses are woodland, paddy fields, and tea farmlands. Data obtained show that the medians of SOC, TN, and TP were 16.97, 1.83, and 0.52 g kg−1, and medians of C : N, C : P, and N : P molar ratios were 10.0, 78.6 and 7.9, respectively. The best-fitting model were exponential models for SOC, TN, TP, C : N, and N : P, while for C : P was Gaussian model. The nugget values for SOC, TN, TP, C : N, C : P, and N : P were 1.0, 0.06, 0.01, 6.0, 56.0, and 1.0, respectively. And their ranges were 750, 1290, 570, 2970, 810, and 720, respectively. The nugget-to-sill ratio (NSR) for SOC, TN, TP, C : P, and N : P were 2.7 %, 14.3 %, 20.0 %, 4.0 %, and 10.0 %, respectively, and showed strong spatial autocorrelation. While C:N molar ratios had a moderate spatial correlation, with NSR of 49.95 %. Spatial analyses showed that agriculture derived land use changes alter largely the spatial distribution and stoichiometry of C, N, and P elements in individual landscapes and entire catchment. For woodland ecosystems, topography factors (elevation and slope) determined the elemental spatial distributions and stoichiometry (C : N, C : P, and N : P molar ratios). However, this status had been merged in agricultural ecosystems, due to the relative similarity in cropping and managing (N and P inputs through fertilization). Agriculture significantly increases N, and P contents but narrows C : N, C : P, and N : P molar ratios. Thus, our findings demonstrate that agricultural activities can affect carbon and nutrient stoichiometry at the catchment scale.

Description: To explore the intrinsic spatial patterns of N2O emissions in agricultural systems, not only should the spatial and temporal variability in N2O emissions be analyzed separately, but the joint spatio-temporal variability should also be explored by applying spatio-temporal semivariogram models and interpolation methods. In this study, we examined the spatio-temporal variability in N2O emissions from a tea-planted soil from 28 April 2014 to 27 May 2014 using 96 static mini chambers in an approximately regular grid on a 40 m2 tea field (sampling 30 times), and the results were compared with long-term observations of the N2O emissions recorded using large static chambers (sampling 5 times). The N2O fluxes observed by the mini chambers during a 30 min snapshot (10:00–10:30 a.m. China Standard Time) ranged from −2.99 to 487.0 mg N m−2 d−1 and were positively skewed with a median of 13.6 mg N m−2 d−1. The N2O flux data were then log-transformed for normality. After detrending the influences from the chamber placement positions (Position) and the precipitation accumulated over two days (Rain2), the log-transformed N2O fluxes (FLUX30t) exhibited strong spatial, temporal and joint spatio-temporal autocorrelations, which were used as three components of spatio-temporal semivariogram models and were characterized by models based on Stein's parameterized Matérn (Ste) function, exponential function and again the Ste function, respectively. The spatio-temporal experimental semivariogram of the N2O fluxes was fitted using four spatio-temporal semivariogram models (separable, product-sum, metric and sum-metric). The sum-metric model performed the best and provided meaningful effective ranges of spatial and temporal dependence, i.e., 0.41 m and 5.4 days, respectively. Four spatio-temporal regression-kriging interpolations were applied to estimate the spatio-temporal distribution of N2O emissions over the study area. The cross-validation results indicated that the four interpolations exhibited similar performances (r = 0.817–0.824, RMSE = 0.456–0.486, p 〈 0.001), and outperformed the multiple linear regression prediction (r = 0.735, RMSE = 0.560, p 〈 0.001). The predictions of the four kriging interpolations for the total N2O emissions from the 40 m2 tea field ranged from 18.3 to 18.5 g N; these values were approximately 25 % higher than the results predicted using the observations of large static chambers. Furthermore, compared with the other three models, the metric model exhibited weak sensitivity for peak prediction, although the cross-validation results indicated that they had same prediction capabilities. Our findings suggested: (i) that the size of large static chambers used for long-term observations of N2O fluxes should be no less than 0.4 m and the time interval for gas sampling should be constrained to approximately 5 days; and (ii) that more efficient testing methods should be adopted to replace the conventional cross-validation methods for evaluating the performance of spatio-temporal kriging.

Description: This paper presents a two-dimensional theoretical model to study the formation process of multiple layers of small ice particles in the polar summer mesosphere as measured by rockets and associated with polar mesosphere summer echoes (PMSE). The proposed mechanism primarily takes into account the transport processes induced by gravity waves through collision coupling between the neutral atmosphere and the ice particles. Numerical solutions of the model indicate that the dynamic influence of wind variation induced by gravity waves can make a significant contribution to the vertical and horizontal transport of ice particles and ultimately transform them into thin multiple layers. Additionally, the pattern of the multiple layers at least partially depends on the vertical wavelength of the gravity wave, the ice particle size and the wind velocity. The results presented in this paper will be helpful to better understand the occurrence of multiple layers of PMSE as well as its variation process.