Review of pre-processing technologies for ice cores

High-resolution ice core records covering long time spans enable reconstruction of the past climatic and environmental conditions allowing the investigation of the earth system’s evolution. Preprocessing of ice cores has direct impacts on the data quality control for further analysis since the conventional ice core processing is time-consuming, produces qualitative data, leads to ice mass loss, and leads to risks of potential secondary pollution. However, over the past several decades, preprocessing of ice cores has received less attention than the improvement of ice drilling, the analytical methodology of various indices, and the researches on the climatic and environmental significance of ice core records. Therefore, this papers reviews the development of the processing for ice cores including framework, design as well as materials, analyzes the technical advantages and disadvantages of the different systems. In the past, continuous flow analysis (CFA) has been successfully applied to process the polar ice cores. However, it is not suitable for ice cores outside polar region because of high level of particles, the memory effect between samples, and the filtration before injection. Ice core processing is a subtle and professional operation due to the fragility of the nonmetallic materials and the random distribution of particles and air bubbles in ice cores, which aggravates uncertainty in the measurements. The future developments of CFA are discussed in preprocessing, memory effect, challenge for brittle ice, coupling with real-time analysis and optimization of CFA in the field. Furthermore, non-polluting cutters with many different configurations could be designed to cut and scrape in multiple directions and to separate inner and outer portions of the core. This system also needs to be coupled with streamlined operation of packaging, coding, and stacking that can be implemented at high resolution and rate, avoiding manual intervention. At the same time, information of the longitudinal sections could be scanned and identified, and then classified to obtain quantitative data. In addition, irregular ice volume and weight can also be obtained accurately. These improvements are recorded automatically via user-friendly interfaces. These innovations may be applied to other paleomedias with similar features and needs.     

秦皇岛近岸海域绿藻微观繁殖体的分布以及在绿潮形成中的作用

2015年以来，秦皇岛近岸海域暴发了绿潮，对北戴河旅游区的环境和生态系统造成了严重影响。绿藻微观繁殖体在绿潮的形成过程中起到重要作用，主要包括孢子、配子、幼苗和营养片段。绿藻微观繁殖体作为绿潮的“种源”，其分布规律可以反映绿潮的“藻源”位置。本研究于2016年4-9月和2017年1月对秦皇岛近岸海域绿藻微观繁殖体的调查，探究了其分布规律以及生物量变化。结果显示，绿藻微观繁殖体主要分布在近岸海域，由近岸向远岸海域逐渐降低。绿藻微观繁殖体的数量在7、8月份最高，在冬季最低。受绿潮影响严重的海域微观繁殖体数量高于其它海域。秦皇岛近岸海域的绿藻微观繁殖体为该海域绿潮的种源，其分布规律表明秦皇岛近岸海域绿潮起源于本地。     

贵州夜郎湖表层水体地球化学昼夜变化及其影响因素

为探究岩溶水库水文地球化学行为过程,对贵州普定夜郎湖表层水体进行了为期3 d的高分辨率昼夜监测。结果表明：1）多变的天气和水文条件叠加导致水体离子指标昼夜变化不显著,规律性较差。而水温、DO、pH值、SpC、SIc、pCO₂等常规理化指标受水温变化和生物作用表现出明显的昼夜波动。2）利用亨利常数和主成分分析,得到温度变化、生物作用、人类活动、水库的蓄水与放水对夜郎湖水库水文地球化学特征变化的贡献率分别为21.66%、17.28%、14.08%和10.22%,说明作用于水库水文地球化学行为的因子具有多元性。3）δ ¹⁸O表现出与DO一致的波动趋势,即白天上升,晚上下降,反映在短时间尺度上,氢氧稳定同位素变化受控于生物过程（主要是呼吸作用过程）;而对比水库水体和大气降水的d-excess（d值）发现,水库水体的d值（8.21‰）显著偏低于当地大气降水的d值（9.64‰）,说明在长时间尺度上,主要受蒸发效应引起的不平衡分馏影响。     

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。     

南极罗斯海沉积物中可培养菌株的分离及胞外水解酶活性检测

研究了南极罗斯海地区沉积物中可培养微生物多样性,并检测了菌株胞外酶活性,为开发利用南极资源奠定基础。采用Zobell2216E培养基、土豆培养基(PDA)及稀释平板划线法分离并获得纯培养的细菌和真菌,分别通过16SrDNA、18S/ITS序列鉴定分析了可培养微生物的多样性和系统发育。从南极罗斯海沉积物样品中获得78株细菌和54株真菌,细菌、真菌的优势菌株分别为嗜冷杆菌属(Psychrobacter)、枝孢属(Cladosporium);78株细菌菌株中有2株与模式菌株的16SrDNA基因序列相似性小于97%,可能是潜在的细菌新物种。细菌API20NE生理生化和真菌产胞外酶活性结果表明,获得的细菌和真菌大多数可检测到胞外水解酶活性。本研究丰富了南极可培养微生物资源,为南极罗斯海地区可培养微生物的多样性研究以及南极微生物资源的应用研究奠定了基础。     

A case study on Landscape Component Niche based on Landscape Pattern Indices: Yanchi,Ningxia Province,China

Yanchi County is located in the agro-pastoral ecotone and belongs to the ecologically fragile area of Northwest China.It is important to study the evolution of landscape pattern to curb its environmental degradation.In order to intuitively show how the landscape pattern of the study area changes over time,Landsat Thematic Mappers(TM)and Landsat Operational Land Imager(OLI)data of 1991,2000,2010 and 2017 were used.This paper attempts to apply niche theories and methods into landscape ecology,and constructs a niche model of landscape components by using"n-dimentional hypervolume niche theory"and landscape pattern indices.By evaluating the spatial and temporal evolution of niche from the perspective of two-dimensional space to reflect the changes of landscape pattern in the study area over the past 26 years,new theories and methods were introduced for the characterization of landscape pattern.The results indicate that:1)The larger the attribute and dominance value of landscape components,the higher the ecological niche and the stronger the control effect on the overall landscape.2)The ecological niche of each landscape component was significantly different,just as its control effect on the overall landscape.3)The dynamic change of the ecological niche of each landscape component was different,with grassland,unused land and arable land always in a high dominant position,although the ecological niche of construction land and water area was always low.In general,the introduction of niche theory into the landscape ecology provided a new method to study the changes in regional landscape pattern.     

Fe3O4/Mg(OH)2复合材料的制备及形貌控制

通过种子沉积法制备出Fe_3O_4/Mg(OH)_2复合材料并进行XRD、SEM测试分析。探究了氨水的浓度与加入速度、搅拌速度及等因素对磁性复合材料形貌的影响。氨水浓度与注入速度的降低,对氢氧化镁基体形貌的影响是相同的,但要使合成磁性复合材料形貌和四氧化三铁粒子在氢氧化镁中分散性均匀,应控制氨水浓度(ω=2.5%)或加入速度在一个合理的较低值。     

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.     

生物土壤结皮对风沙土和黄绵土膨胀特性的影响

作为重要的土壤物理性质，膨胀性在影响土壤导水性、持水性、抗蚀性以及土壤结构的形成和发育等方面发挥着重要作用。为了探讨生物土壤结皮（BSCs）土壤的膨胀特性及其主要影响因素，针对黄土高原风沙土和黄绵土两种典型土壤，利用膨胀仪测定并比较了有、无藓结皮及其在不同因素（初始含水量、干湿循环、冻融循环、温度）下膨胀率的差异，分析了BSCs对土壤膨胀性的影响及其与环境因素和BSCs性质的关系。结果显示：风沙土上藓结皮的膨胀率为1.93%，较无结皮增加了8.65倍；而黄绵土上藓结皮的膨胀率为2.05%，与无结皮相比降低了76.68%。藓结皮的生物量和厚度与其膨胀率在风沙土上均呈线性正相关关系（P < 0.05），在黄绵土上分别呈二次函数（P=0.02）和线性正相关关系（P=0.02）。初始含水量同时影响了土壤最大膨胀率和稳定膨胀时间，影响程度风沙土远大于黄绵土（包括藓结皮和无结皮）；干湿循环次数对无结皮土壤膨胀率的影响程度大于藓结皮土壤，其中风沙土和黄绵土上无结皮的膨胀率分别是50.00%~620.00%和-2.28%~10.81%，而两种土壤上藓结皮的膨胀率分别是-5.70%~10.88%和-10.24%~-21.46%；冻融循环下4种土壤的膨胀率均有不同程度的降低，降幅为0~18.54%。黄绵土无结皮的膨胀率受温度影响程度较大，50℃下黄绵土无结皮的膨胀率分别是25℃和35℃下的1.17倍和1.21倍。BSCs显著地改变了风沙土和黄绵土表层的膨胀性，其影响的程度和方向取决于土壤类型。同时，BSCs的膨胀性受含水量、温度、干湿以及冻融循环等关键因素影响。     

乡村空间重构的理论研究进展与理论框架构建

在新时代城乡融合发展、乡村地域人地关系日益复杂的背景下，乡村空间重构成为乡村地理学研究的重要课题。西方“后生产主义”语境下，乡村空间研究开始出现消费转向、社会-文化转向和后现代转向，多功能、全球化乡村转型与空间重构研究成为西方乡村空间研究的热点；国内研究主要基于乡村地理学人地关系地域系统理论展开乡村空间重构过程—机理—调控研究以及微观视角下农户经济空间行为研究；当前，中国乡村空间重构呈现自上而下的政治经济学转型特征，具有中国特色的农村集体组织与政府、企业、个人等其他主体之间的空间-权力关系成为乡村空间重构的重要视角。政治经济地理学及“社会-空间”二元辩证法为乡村空间重构研究提供了很好的研究范式与研究方法，乡村空间重构研究应系统整合空间生产、主体能动性、土地资本化、社会关系网络、人地关系地域系统和农户地理等政治经济学、地理学理论，强化自然、经济、社会和文化等多要素相互作用及其空间响应机制研究，重点开展多要素多维度的乡村空间格局形成及演变规律研究、乡村社会空间再生产研究、能动性视角下乡村劳动力空间生产研究、政府政策制度与城乡空间治理体系创新研究。