Riverine dominance of a nearshore marine demersal food web: evidence from stable isotope and C/N ratio analysis

The Thukela Bank, KwaZulu-Natal, supports a diverse ecosystem and South Africa’s only prawn fishery. Oceanographic studies suggest riverine input is not important for the biology of this system, whereas biological studies suggest the contrary, with prawn catches increasing with increased fluvial run-off. The aim of this study was to determine (i) the importance of riverine and marine organic matter for the Thukela Bank food web; and (ii) whether there are seasonal changes in the Thukela River stable isotope values, and, if so, whether these are reflected in the isotope values of demersal organisms. Estuarine organic matter, sediments and demersal organisms were collected from several sites across the bank in the wet and dry seasons of 2008, 2009 and 2010. Marine particulate organic matter was also collected in 2010 and analysed for δ13C and δ15N, as well as C/N ratios. There were strong seasonal changes in isotopic values of organic matter and fauna, especially faunal δ13C. There was an apparent time-lag in organisms assimilating riverine organic matter isotopic values, with the isotopic signature of demersal organisms reflecting that of riverine organic matter from the previous season, which is likely the result of tissue turnover time. In 2010, Thukela Bank sediment organic matter was of riverine origin and this maintained the demersal food web. We conclude that Thukela River organic matter is an important input to the food web of the Thukela Bank, indicating that any future damming of the catchment area could have serious consequences for this ecosystem.     

辅助模型辨识方法(3):输入非线性输出误差自回归系统

输入非线性系统包括输入非线性方程误差类系统和输入非线性输出误差类系统.针对输入非线性输出误差自回归系统,分别基于过参数化模型,基于关键项分离原理,基于数据滤波技术,研究了相应的基于过参数化模型的辅助模型递推辨识方法、基于关键项分离的辅助模型递推辨识方法、基于数据滤波的辅助模型递推辨识方法.这些方法可以推广到其他输入非线性输出误差系统、输出非线性输出误差系统、反馈非线性系统等.并给出了几个典型辨识算法的计算步骤、流程图和计算量.     

Real-time genetic spatial optimization to improve forest fire spread forecasting in high-performance computing environments

Abstract

Forest fires are a kind of natural hazard with a high number of occurrences in southern European countries. To avoid major damages and to improve forest fire management, one can use forest fire spread simulators to predict fire behavior. When providing forest fire predictions, there are two main considerations: accuracy and computation time. In the context of natural hazards simulation, it is well known that part of the final forecast error comes from uncertainty in the input data. These data typically consist of a set of GIS files, which should be appropriately conflated. For this reason, several input data calibration methods have been developed by the scientific community. In this work, the Two-Stage calibration methodology, which has been shown to provide good results, is used. This calibration strategy is computationally intensive and time-consuming because it uses a Genetic Algorithm as a solution. Taking into account the aspect of urgency in forest fire spread prediction, it is necessary to maintain a balance between accuracy and the time needed to calibrate the input parameters. In order to take advantage of this technique, one must deal with the problem that some of the obtained solutions are impractical, since they involve simulation times that are too long, preventing the prediction system from being deployed at an operational level. A new method which finds the minimum resolution reduction for such long simulations, keeping accuracy loss to a known interval, is proposed. The proposed improvement is based on a time-aware core allocation policy that enables real-time forest fire spread forecasting. The final prediction system is a cyberinfrastructure, which enables forest fire spread prediction at real time.     

Global estimates of wind energy input to subinertial motions in the Ekman-Stokes layer

By incorporating the wave-induced Coriolis-Stokes forcing into the classical Ekman model, the wind energy input to the Ekman-Stokes layer is investigated, with an emphasis on the surface wave effects when the direction of Stokes drift deviates from that of wind stress. Theoretical analysis of the kinetic energy balance of the Ekman-Stokes layer shows that the total wind energy input consists of the direct wind energy input and the wave-induced energy input. Details of the direct wind and wave-induced energy input are discussed. Based on the ECMWF ERA-40 Re-Analysis wind stress and surface wave data, the global total wind energy input to subinertial motions in the Ekman-Stokes layer is estimated at 2.19 TW, including 0.26 TW (12%) wave-induced energy input and 1.93 TW (88%) direct wind energy input. The effect of sea-ice coverage on the energy input to the Ekman-Stokes layer is also considered. It is shown that the global total energy input could be overestimated by 0.08 TW (about 4%) without taking the sea-ice coverage into account.     

Spatial variation of nutrients and primary productivity in the Rufiji Delta mangroves,Tanzania

Determinations of spatial and temporal variations in organic matter and nutrient dynamics in water and sediments are crucial for understanding changes in aquatic bodies. In this study, we (i) determine the spatial dynamics of dissolved inorganic nutrients, during the transition from the dry to the rainy season, and (ii) provide future productivity predictions for the Rufiji Delta mangroves, Tanzania, based on the input of various nutrients. Water samples were collected from six locations, three times per year between April 2012 and January 2014, and analysed for dissolved nutrients, total organic and inorganic carbon, chlorophyll a, chlorophyll b and total carotenoids. The prediction of future net primary productivity in the Rufiji mangroves was undertaken using the software STELLA. The mean nutrient concentrations were of the order: nitrate > phosphate > ammonium > silica > dissolved organic carbon. The study revealed that high nutrient concentrations occurred in the northern part of the Rufiji Delta as a result of anthropogenic influence in the watershed. Modelling of nutrient inputs into the delta indicated enhanced primary productivity, which is expected to increase the vulnerability of water quality in the near future due to eutrophication.     

Hydrological effects of climate change,groundwater withdrawal,and land use in a small Korean watershed

The effects of variability in climate and watershed (groundwater withdrawal and land use) on dry‐weather streamflows were investigated using SWAT (Soil and Water Assessment Tool). The equation to predict the total runoff (TR) using climate data was derived from simulation results for 30 years by multiple regression analysis. These may be used to estimate effects of various climate variations (precipitation during the dry period, precipitation during the previous wet period, solar radiation, and maximum temperature). For example, if daily average maximum temperature increases by 3 °C, TR during the dry period will decrease by 27·9%. Similarly, groundwater withdrawals strongly affect streamflow during the dry period. However, land use changes (increasing urbanization) within the forested watershed do not appear to significantly affect TR during the dry period. Finally, a combined equation was derived that describes the relationships between the TR during the dry period and the climate, groundwater withdrawal and urban area proportion in a small monsoon watershed. This equation will be effective to predict the water availability during the dry periods in the future since it is closely related to changes of temperature, precipitation, solar radiation, urban area ratio, and groundwater withdrawal quantity. Copyright © 2007 John Wiley & Sons, Ltd.     

Characteristics of Hydrogen and Oxygen Isotopes and Noble Gas Isotopes in the Groundwater of Weishan, Wudalianchi, Northeast China

According to the hydrochemical characteristics, hydrogen and oxygen isotope characteristics and the ratio of noble gas isotopes of the sandstone aquifer and basalt aquifer, this study calculated the recharge temperature and residence time of groundwater in the Weishan area of Wudalianchi, also calculating the contribution of noble gas components from different sources to the samples. Based on the characteristics of hydrogen and oxygen isotopes and noble gases Xe and Ne, the recharge altitude and recharge temperature of the two aquifers were estimated, and the recharge temperature fitting with the NGT model as verified, the results showing that the main recharge altitude of groundwater in the region was 500–600 m, the recharge temperature being 2–7°C. Heeq and Heea of the samples have been simulated using the OD model, the content of radioactive 4He in the crust being obtained, the groundwater ages under the two conditions (closed condition and open condition) both being simulated. The results show that groundwater from the sandstone layer water is older than groundwater from the basalt layer. Hydrochemical characteristics and noble gas isotope ratios indicate that in the basalt aquifer and sandstone aquifer in the Weishan area, in addition to atmospheric and crustal helium, there is also an input of mantle-derived helium. The fault constitutes the uplift channel for groundwater containings mantle components, which results in the mantle source composition in water samples near the fault being much higher than those form non-fault areas.     

基于共享社会经济路径的中国经济发展趋势及其影响要素分析

基于最新的经济和人口普查及逐年统计年鉴,采用柯布?道格拉斯(Cobb-Douglas)经济预测模型,分析了共享社会经济路径(SSPs)框架下中国“全面二孩”政策后2010—2100年经济发展趋势,并解析了劳动投入量、资本投入量和全要素生产率对经济发展的贡献率。研究发现：(1)不同的社会经济发展政策下,21世纪中国经济均呈增加趋势,GDP增速在2030年前基本维持在6%上下,但2030—2060年代迅速下降,2070年代起SSP1和SSP4路径下增幅低于0.5%,SSP2、SSP3和SSP5路径下增幅保持在0.5%~1.5%。(2)影响经济发展的三要素中,劳动投入量在SSP3路径下先减后增,于2060年代达到谷值;在其他路径下均先增后减,于2020年代达到峰值。资本投入量在SSP1路径下持续增加,2080年代起趋于平缓;其他路径下均呈持续增加趋势,但在SSP4路径下,在2060和2070年代有所下降。全要素生产率在所有路径下均呈增加趋势。(3)改革开放以来,资本投入量是影响我国经济增长最主要的因素。未来,SSP1和SSP2路径下,全要素生产率逐渐成为经济发展的主导因素;而SSP5路径下,资本投入量仍是影响经济发展的主要因素。     

基于异地潮位资料和BP神经网络的潮位推算研究

文章通过BP神经网络模型,利用西沙站的实测潮位推算三亚站潮位,研究用一地点的潮位资料去推算另一地点(异地)潮位的方法。文章比较了不同隐含层节点数和输入因子对潮位推算结果的影响,采用预测时间(t)之前N个小时(t–N+1,…,t–1,t)西沙站的实测潮位数据作为输入因子,输入因子数目在2~10之间,隐含层分别采用节点数3、4、5、10和15建模,分多种情况进行推算。结果显示,对文中使用的特定情形,隐含层为4个节点的效果最好,隐含层为15个节点的效果最差;输入层为2个节点的效果最好,输入因子增多会使得推算效果变差。隐含层为4个节点、输入因子为t–1、t时刻潮位的仿真验证的结果最好,推算值和实测值之间的相关系数为0.9901,均方根误差为0.06m,误差在–0.16~0.15m之间。结果表明,如果两个地点的潮位具有物理上的关联,通过BP神经网络模型,用一地点的实测潮位推算另一地点潮位的方法是可行的。