宁夏生态移民村空间剥夺测度及影响因素

生态移民村是一种具有扶贫脱贫与生态保护双重意义的特殊乡村类型,是乡村振兴不可或缺的重要对象。在空间重构过程中形成的空间剥夺现象,是当前生态移民村全面振兴面临的一个新问题。为探究生态移民村空间剥夺规律,以宁夏70个生态移民村2017年相关数据为基础,构建了以收入就业、教育培训、社会生活、居住环境及公共服务可达性为主要内容的空间剥夺指标体系并进行水平测度,进而运用地理加权回归和地理探测器对其影响因子进行探测。结果显示：① 宁夏生态移民村空间剥夺整体水平较低,但总指数均值相对于非生态移民村显著高出0.023;② 宁夏生态移民村空间剥夺时空分异特征明显,总指数均值在时间上呈现“先较低—后上升—再下降”趋势,在空间上呈现“北部低—中部高—南部次高”分布;③ 民族构成、地形地貌、移民时段、依托资源和经济区带是影响生态移民村空间剥夺的重要因子,前3项对空间剥夺总指数的解释力分别达到了22.4%、10.6%和14.0%。空间剥夺水平测度为生态移民生产生活评价和政策调整完善提供新的客观依据,相关部门可据此优化调节生态移民村空间资源配置,增加其获取资源的能力和机会,推动生态移民村全面振兴。     

基于卫星遥感数据的森林病虫害监测与评价

森林病虫害由于在森林资源中造成的重大破坏而被人们称为“不冒烟的火灾”,其对生态系统的研究具有重要意义。现有基于遥感数据的病虫害研究多集中在森林病虫害的监测、爆发原因以及发病区域内生产力的变化情况,而对于森林病虫害发生后森林中植被指数与叶面积指数之间的相关性的变化情况还相对较少,处于需要持续性深入探讨的阶段。以加拿大不列颠哥伦比亚地区2002—2012年森林病虫害数据为基础,分析不同严重程度的病虫害对叶面积指数（LAI）与归一化植被指数（NDVI）和增强型植被指数（EVI）的影响。结果表明：① 受病虫害感染的像元在轻度（Light）、中度（Moderate）和重度（Severe）三个严重级别中,NDVI与LAI之间的相关性由弱变强,又由强变弱;② EVI与LAI之间的相关性,在轻度（Light）、中度（Moderate）和重度（Severe）三个严重级别的像元中则依次变强。这一研究将为今后利用遥感数据识别病虫害、评价生态系统影响提供基础。     

一种潜艇装备作战能力比较研究方法

对潜艇装备作战能力评估问题进行了研究，发现运用定量评估方法的过程中存在指标评价所需数据无法完全获取的问题。结合美弗吉尼亚潜艇改进情况，分析了影响潜艇作战能力的一些关键因素，重点基于潜艇武器装载能力，对国外典型潜艇进行了作战能力比较分析，最后对分析结果进行了评价，并讨论了未来潜艇作战能力评估方法的发展方向。     

苏北浅滩沉积物中的大型绿藻微观繁殖体的垂直分布和物种多样性

本研究通过在2017年秋冬季组织实施的2个绿潮种源调查航次,研究苏北浅滩紫菜养殖区沉积物中的大型绿藻微观繁殖体的垂直分布和物种多样性。对沉积物中的微观繁殖体的定量实验结果表明:表层泥样中绿藻微观繁殖体的丰度最高,随着深度的增加迅速降低。在9月份表层沉积物中丰度为9±2ind./g,而在11月份表层丰度达到98±25ind./g;与9月份相比, 11月份浅滩沉积物中绿藻繁殖体数量呈现出显著升高的趋势。通过对51个绿藻样品的分子鉴定发现:沉积物中存在石莼属(Ulva)、尾孢藻属(Urospora)、盘苔属(Blidingia)等大型绿藻的微观繁殖体;数量占优是石莼属繁殖体,主要包括曲浒苔(Ulva flexuosa)、浒苔(Ulva prolifera)、扁浒苔(Ulva compressa)、缘管浒苔(Ulva linza);其中曲浒苔占据的比例最高,在9和11月份分别达到80.94%和73.33%。在2个调查航次中,都从沉积物中发现了绿潮浒苔的微观繁殖体,这些微观繁殖体是绿潮浒苔在苏北浅滩种源维持的重要方式和关键阶段,也构成了黄海浒苔绿潮连年暴发的"种子库"。     

Bibliometric Analysis of Global Research Progress on Coastal Flooding 1995–2016

Global research progress on coastal flooding was studied using a bibliometric evaluation of publications listed in the Web of Science extended scientific citation index. There was substantial growth in coastal flooding research output, with increasing publications, a higher collaboration index, and more references during the 1995–2016 period. The USA has taken a dominant position in coastal flooding research, with the US Geological Survey leading the publications ranking. Research collaborations at institutional scales have become more important than those at global scales. International collaborative publications consistently drew more citations than those from a single country. Furthermore, coastal flooding research included combinations of multi-disciplinary categories, including ‘Geology' and ‘Environmental Sciences Ecology'. The most important coastal flooding research sites were wetlands and estuaries. While numerical modeling and 3 S(Remote sensing, RS; Geography information systems, GIS; Global positioning systems, GPS) technology were the most commonly used methods for studying coastal flooding, Lidar gained in popularity. The vulnerability and adaptation of coastal environments, their resilience after flooding, and ecosystem services function showed increases in interest.     

Photosynthetic response of <Emphasis Type="Italic">Scirpus validus</Emphasis> and <Emphasis Type="Italic">Typha orientalis</Emphasis> to elevated temperatures in Dianchi Lake,Southwestern China

Understanding the effects of simulated warming on photosynthetic performance of aquatic plants may provide strong supports for predicting future dynamics of wetland ecosystems in the context of climate change. The plateau wetlands located in Yunnan province are highly sensitive to climate warming due to their high altitude and cold temperature. Here, we conducted a temperaturecontrolled experiment using two temperature manipulations (ambient temperature as the control and 2°C higher than ambient temperature as the warmed treatment) to determine the photosynthetic characteristics of two lakeside dominant species (Scirpus validus Vahl and Typha orientalis C. Presl.) in Dianchi Lake. Net photosynthetic rate (P_n), stomatal conductance (G_s), intercellular CO₂ concentration (C_i), and transpiration rate of S. validus that grew under warmed treatment were all significantly higher than those under the control. G_s and C_i of T. orientalis showed similar patterns as S. validus did. For the response curves of P_n to photosynthetic active radiation (Pn-PAR) and intercellular CO₂ concentration (P_n-C_i), S. validus had higher P_n values under elevated temperatures than the control, while P_n-PAR and P_n-C_i curves of T. orientalis did not separate clearly under two temperature scenarios. Both S. validus and T. orientalis had higher maximum net photosynthetic rate, light saturation point, dark respiration rate, the maximum rate of RuBP carboxylation (V_cmax), maximum electron transport rate driving RuBP regeneration (J_max), the ratio of V_cmax to J_max, triosephosphate utilization, and 1, 5-bishosphate carboxylase ribulose content under warmed treatment than those under the control. This study provides a preliminary step for predicting the future primary production and vegetation dynamics of plateau wetlands in Yunnan province.     

两株南极枝孢霉属真菌Cladosporium sp.NJF4和NJF6的次级代谢产物研究

南极因其独特的自然环境成为潜在、重要的微生物资源库,是产生新型生物活性物质和先导化合物菌株的潜在种源地,南极微生物正在成为创新药物研究新的重要资源。虽然近年来对南极微生物次级代谢产物的研究逐渐增加,但与温带和热带微生物研究相比仍处于初级阶段。对从南极普里兹湾海洋沉积物中获得的两株枝孢霉属真菌Cladosporium sp. NJF4和NJF6进行次级代谢产物分离及结构鉴定,获得20个化合物。化合物结构类型包括甾醇(1)、倍半萜类(7—8)、生物碱类(9—14)、二酮哌嗪(2—5、15—17)、芳香酸(6、18—19)等,其中倍半萜类(7—8)为首次从枝孢霉属真菌中分离得到,以上研究将为丰富南极微生物次级代谢产物库奠定一定的研究基础。     

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.     

Mobile Agent系统结构及其关键技术

Mobile Agent技术是一门新兴的技术,具有移动性、智能性和异步计算的特点,已成为计算机网络和分布式系统最具活力的发展方向.现对Mobile Agent的概念、系统结构及其关键技术进行了分析和探讨.     

Study of a model for correcting the effects of horizontal advection on surface fluxes measurement based on remote sensing

As well known, the methods of remote sensing and Bowen Ratio for retrieving surface flux are based on energy balance closure; however, in most cases, surface energy observed in experiment is lack of closure. There are two main causes for this: one is from the errors of the observation devices and the differences of their observational scale; the other lies in the effect of horizontal advection on the surface flux measurement. Therefore, it is very important to estimate the effects of horizontal advection quantitatively. Based on the local advection theory and the surface experiment, a model has been proposed for correcting the effect of horizontal advection on surface flux measurement, in which the relationship between the fetch of the measurement and pixel size for remote sensed data was considered. By means of numerical simulations, the sensitivities of the main parameters in the model and the scaling problems of horizontal advection were analyzed. At last, by using the observational data acquired in agricultural field with relatively homogeneous surface, the model was validated.