Daily salinity fluctuation alleviates salt stress on seedlings of the mangrove Bruguiera gymnorhiza

Salinity is a vital factor that regulates leaf photosynthesis and growth of mangroves, and it frequently undergoes large seasonal and daily fluctuations creating a range of environments – oligohaline to hyperhaline. Here, we examined the hypotheses that mangroves benefit opportunistically from low salinity resulting from daily fluctuations and as such, mangroves under daily fluctuating salinity (FS) grow better than those under constant salinity (CS) conditions. We compared growth, salt accumulation, gas exchange, and chlorophyll fluorescence of leaves of mangrove Bruguiera gymnorhiza seedlings growing in freshwater (FW), CS (15 practical salinity units, PSU), and daily FS (0–30 PSU, average of 4.8 PSU) conditions. The traits of FS-treated leaves were measured in seedlings under 15 PSU. FS-treated seedlings had greater leaf biomass than those in other treatment groups. Moreover, leaf photosynthetic rate, capacity to regulate photoelectron uptake/transfer, and leaf succulence were significantly higher in FS than in CS treatment. However, leaf water-use efficiency showed the opposite trend. In addition to higher concentrations of Na⁺ and Cl⁻, FS-treated leaves accumulated more Ca²⁺ and K⁺. We concluded that daily FS can enhance water absorption, photosynthesis, and growth of leaves, as well as alter plant biomass allocation patterns, thereby positively affecting B. gymnorhiza. Mangroves that experience daily FS may increase their adaptability by reducing salt build-up and water deficits when their roots are temporally subjected to low salinity or FW and by absorbing sufficient amounts of Na⁺ and Cl⁻ for osmotic adjustment when their roots are subsequently exposed to saline water.     

Influence of a coarse interlayer on seawater intrusion and contaminant migration in coastal aquifers

Vertical 2D slice laboratory experiments were carried out in homogenous and layered sand tanks to elucidate the effects of a highly permeable (coarse‐grained sand) interlayer on seawater intrusion and transport of contaminants to a coastal sea. Tidal fluctuations produced oscillations in the seawater–freshwater transition zone, fluctuations of the contaminant infiltration rate and a zigzag contaminant plume outline. The seawater wedge became discontinuous at the (vertical) edges of the interlayer because of increased lateral movement of the seawater–freshwater interface within the interlayer. The contaminant plume formed a tail within the interlayer depending on the tidal stage, and similar to the wedge, its movement was accentuated. A simple analytical model that neglected vertical flow reliably predicted steady‐state seawater intrusion into the coastal aquifer. Numerical modeling was used to gain insight into the groundwater hydrodynamics and contaminant migration. The numerical results confirmed the experimental findings, i.e. that a highly permeable interlayer can provide a rapid transit path for contaminants to reach the seaward boundary and that the interlayer amplifies the effects of tidal fluctuations, resulting in wider transition zones for the seawater wedge and contaminant plume. Numerical simulations further showed that, with increasing interlayer hydraulic conductivity, the maximum seawater intrusion distance inside the interlayer increases approximately linearly. For the fixed‐head contaminant injection condition used, the model showed that contaminant infiltration increases approximately logarithmically with increasing interlayer hydraulic conductivity (other factors held fixed). Copyright © 2013 John Wiley & Sons, Ltd.     

Piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events on the Loess Plateau,China

Establishing a universal watershed‐scale erosion and sediment yield prediction model represents a frontier field in erosion and soil/water conservation. The research presented here was conducted on the Chabagou watershed, which is located in the first sub‐region of the hill‐gully area of the Loess Plateau, China. A back‐propagation artificial neural model for watershed‐scale erosion and sediment yield was established, with the accuracy of the model, then compared with that of multiple linear regression. The sensitivity degree of various factors to erosion and sediment yield was quantitatively analysed using the default factor test. On the basis of the sensitive factors and the fractal information dimension, the piecewise prediction model for erosion and sediment yield of individual rainfall events was established and further verified. The results revealed the back‐propagation artificial neural network model to perform better than the multiple linear regression model in terms of predicting the erosion modulus, with the former able to effectively characterize dynamic changes in sediment yield under comprehensive factor conditions. The sensitivity of runoff erosion power and runoff depth to the erosion and sediment yield associated with individual rainfall events was found to be related to the complexity of surface topography. The characteristics of such a hydrological response are thus closely related to topography. When the fractal information dimension is greater than the topographic threshold, the accuracy of prediction using runoff erosion power is higher than that of using runoff depth. In contrast, when the fractal information dimension is smaller than the topographic threshold, the accuracy of prediction using runoff depth is higher than that of using runoff erosion power. The developed piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events, which introduces runoff erosion power and runoff depth using the fractal information dimension as a boundary, can be considered feasible and reliable and has a high prediction accuracy. Copyright © 2013 John Wiley & Sons, Ltd.     

安徽省硫铁矿成因类型及潜力分析

安徽省是我国硫铁矿储量大省,截止2013年底,全省累计查明非伴生硫铁矿9.1亿吨,保有资源储量8.2亿吨,居全国第二位,华东第一位。     

A timescale decomposed threshold regression downscaling approach to forecasting South China early summer rainfall

A timescale decomposed threshold regression(TSDTR) downscaling approach to forecasting South China early summer rainfall(SCESR) is described by using long-term observed station rainfall data and NOAA ERSST data. It makes use of two distinct regression downscaling models corresponding to the interannual and interdecadal rainfall variability of SCESR.The two models are developed based on the partial least squares(PLS) regression technique, linking SCESR to SST modes in preceding months on both interannual and interdecadal timescales. Specifically, using the datasets in the calibration period 1915–84, the variability of SCESR and SST are decomposed into interannual and interdecadal components. On the interannual timescale, a threshold PLS regression model is fitted to interannual components of SCESR and March SST patterns by taking account of the modulation of negative and positive phases of the Pacific Decadal Oscillation(PDO). On the interdecadal timescale, a standard PLS regression model is fitted to the relationship between SCESR and preceding November SST patterns. The total rainfall prediction is obtained by the sum of the outputs from both the interannual and interdecadal models. Results show that the TSDTR downscaling approach achieves reasonable skill in predicting the observed rainfall in the validation period 1985–2006, compared to other simpler approaches. This study suggests that the TSDTR approach,considering different interannual SCESR-SST relationships under the modulation of PDO phases, as well as the interdecadal variability of SCESR associated with SST patterns, may provide a new perspective to improve climate predictions.     

Changes in the boreal summer intraseasonal oscillation projected by the CNRM-CM5 model under the RCP 8.5 scenario

Climate Dynamics - The 30–60-day boreal summer intraseasonal oscillation (BSISO) is the predominant intraseasonal variability in the Asian summer monsoon (ASM) region, representing the...     

Logs Fluid Typing Methods and Adaptive Analysis of Tight Sandstone Reservoir of Yingcheng Formation in Lishu Fault

Tight clastic reservoirs are characterized with low porosity and low permeability, which reduce contributions of reservoir fluids to geophysical logging responses, and it is more difficult to identify fluids of the reservoir. Therefore, it is necessary to study log interpretation and comprehensive evaluation methods for such clastic reservoirs. This study focused on geological characteristics of tight clastic reservoir of Yingcheng formation in Lishu Fault. Based on logs sensitivity to fluids, some fluid typing methods were discussed in detail, which included log curve overlap method, acoustic time overlapping method from density and neutron logs, porosity difference and ratio method, porosity-resistivity crossplot, normal distribution method, and other methods, and some effective fluid evaluation method were established and optimized. These above-mentioned methods were verified, which could achieve layer qualitative identification of tight sandstone in the study area. By contrast, two logs overlapping methods, porosity difference and ratio method, resistivity-porosity crossplot are more suitable for natural gas reservoirs, while porosity difference and ratio method, porosity-resistivity chart, normal distribution method are more suitable for oil and water reservoirs. The case study suggests that these methods be combined to archive more correct log interpretation in the study area, which provides important decision-making reference for oilfield exploration and development.     

加权Logistic回归模型在火山岩型铜矿预测中的应用:以宁芜盆地中段为例

文中探讨了加权Logistic回归模型在宁芜盆地中段火山岩型铜矿预测中的应用。首先,结合研究区的成矿地质背景,提取地质体、构造、围岩蚀变三大类证据因子;其次,分析各证据因子与铜矿点之间的空间关系,认为姑山旋回、娘娘山旋回火山机构控制了本区火山岩型铜矿的空间分布,根据计算结果,选取与火山岩型铜矿密切相关的龙王山组、姑山组地层,姑山旋回粗面斑岩、娘娘山旋回二长斑岩、NW向构造1.5 km缓冲区、NE向构造1.3 km缓冲区、EW向构造4.5 km缓冲区、硅化、褐铁矿化、黄铜矿化等作为模型自变量;最后采用加权Logistic回归模型进行成矿概率计算,并结合成矿地质背景,圈定四个成矿远景区,分别为P1、P2、P3、P4,其中P1、P2、P3呈北东向展布,主要受娘娘山和姑山火山机构控制,P4为东西向分布,主要受龙王山火山机构控制,在这些预测区中,均存在已发现的铜矿体,说明预测可信度较高。