Platinum-group elements in alpine-type ultramafic rocks and related chromite ores of the main ophiolite belt of the Urals

On the basis of a representative collection of ultramafic rocks and chromite ores and a series of technological samples from the largest (Central and Western) deposits in the Rai-Iz massif of the Polar Urals and the Almaz-Zhemchuzhina and Poiskovy deposits in the Kempirsai massif of the southern Urals, the distribution and speciation of platinum-group elements (PGE) in various type sections of mafic-ultramafic massifs of the Main ophiolite belt of the Urals have been studied. Spectral-chemical and spectrophotometric analyses were carried out to estimate PGE in 700 samples of ultramafic rocks and chromite ores; 400 analyses of minerals from rocks, ores, and concentrates and 100 analyses of PGE minerals (PGM) in chromite ores and concentrates were performed using an electron microprobe. Near-chondritic and nonchondritic PGE patterns in chromitebearing sections have been identified. PGE mineralization has been established to occur in chromite ore from all parts of the mafic-ultramafic massifs in the Main ophiolite belt of the Urals. The PGE deposits and occurrences discovered therein are attributed to four types (Kraka, Kempirsai, Nurali-Upper Neiva, and Shandasha), which are different in mode of geological occurrence, geochemical specialization, and placer-forming capability. Fluid-bearing minerals of the pargasite-edenite series have been identified for the first time in the matrix of chromite ore of the Kempirsai massif (the Almaz-Zhemchuzhina deposit) and Voikar-Syn’ya massif (the Kershor deposit). The PGE grade in various types of chromite ore ranges from 0.1–0.2 to 1–2 g/t or higher. According to technological sampling, the average PGE grade in the largest deposits of the southeastern ore field of the Kempirsai massif is 0.5–0.7 g/t. Due to the occurrence of most PGE as PGM 10–100 mm in size and the proved feasibility of their recovery into nickel alloys, chromites of the Kempirsai massif can be considered a complex ore with elevated and locally high Os, Ir, and Ru contents. The Nurali-Upper Neiva type of ore is characterized by small-sized primary deposits, which nevertheless are the main source of large Os-Ir placers in the Miass and Nev’yansk districts of the southern and central Urals, respectively.     

利用Sentinel-3A OLCI可见光通道反演台湾岛气溶胶光学厚度

OLCI（Ocean Land Colour Instrument）作为MERIS（Medium Resolution Imaging Spectrometer）的后继升级版传感器,在气溶胶反演中存在潜在优势,但是目前利用OLCI数据进行气溶胶监测的研究较少。因此,本文针对OLCI多通道反射特征开发了OLCI云检测算法,并对传统查找表构建方法进行改进,根据观测几何特征提出动态查找表法,并通过光谱卷积方式等效转换MODIS和OLCI红蓝通道地表反射率并获取OLCI红蓝通道地表反射率固定关系,进而实现台湾岛550 nm处的AOD反演。与550 nm处AERONET level 2.0 AOD验证结果首先表明不同季节、不同站点的精度表现存在一定差异,其次相对于同期MOD04_3K AOD产品,本文反演结果与全球气溶胶自动观测网（AERONET）站点实测值之间表现出更显著 的相关性（R²=0.8199）,均方根误差（RMSE）从0.175下降到0.113,相对平均误差（RME）从33.6%下降到26.7%,且67.5%的OLCI AOD落在预测误差（EE）区间内,明显大于MOD04_3K AOD落在预测误差区间的百分比（55.7%）。此外,误差分析表明,当实际AOD值较低时,红蓝通道地表反射率之间关系的误判会导致较为明显的AOD反演相对误差。     

二维Delaunay三角网的任意点删除算法研究

针对目前基于影响域多边形剖分的点删除算法缺陷,提出一种二维Delaunay三角网点删除算法。首先利用具有拓扑关系的三角网搜索影响多边形,并以三角形矢量面积为工具三角剖分影响域多边形,最后通过镶嵌优化后的剖分三角网完成点的删除,且满足Delaunay法则。通过测试证明了算法的可靠性和高效性。     

促进我国大洋矿产资源商业化开发的思考

自1991年以来,我国大洋矿产资源开发事业取得了长足进步,包括大洋资源调查、技术装备研发、国际事务方面等。然而,与西方发达国家相比,我国大洋矿产资源开发事业仍存在较大差距,调查装备质量、标准化和国产化水平均仍较低,深海采矿、冶炼技术较为落后,商业化开发步伐远落后于发达国家。在西方国家广泛开展深海矿产开发技术研发的情况下,我国应加强深海矿产商业化开采的顶层设计研究,深化深海调查采矿冶炼技术研发,推动技术设备通用化和标准化。     

Microbial community changes in the digestive tract of the clam Meretrix petechialis in response to Vibrio parahaemolyticus challenge

Journal of Oceanology and Limnology - Disease in clams frequently occurred over the last decade and has become a serious threat to the clam aquaculture industry and natural stocks. Mass clam...     

盐碱化湿地稻-鱼复合生态系统微生物特征

为揭示盐碱化湿地稻-鱼复合生态系统微生物群落结构特征,1994-1995年,对松嫩平原苏打盐碱化湿地稻-鱼复合生态系统水体与土壤中的微生物数量及种群组成进行了初步研究。结果表明,稻-鱼湿地水体中异养细菌数量显著高于稻田湿地(P<0.05),季节变化特点为秋季>夏季>春季。异养细菌的数量分布与鱼产量有显著相关关系(r=0.879)。稻-鱼湿地系统的土壤微生物数量明显高于稻田湿地(P<0.01)。稻-鱼湿地和稻田湿地分别检测出10个和11个属的异养细菌。稻-鱼湿地系统1个生长期细菌的平均生物量为0.973g/m3,生产量为307.5 kg/hm2,所提供的鱼产力为7.0 kg/hm2。     

全球气候变化下南海诸岛保护优先区识别分析

全球变化下,珊瑚礁保护区是保护生物多样性、增强珊瑚礁对气候变暖抵抗力的有效方式,而维持珊瑚礁弹性是其核心内容。针对珊瑚礁最具有威胁性的热压力因子,基于南海1982—2009年卫星观测海表面温度（SST）数据和CMIP5加拿大地球系统模式CanESM2模型预估的2006—2100年南海SST数据构建热压力强度模型,从维持珊瑚礁弹性的角度识别IPCC RCP 4.5和RCP 8.5情景下南海诸岛保护优先区。结果表明：RCP 4.5和RCP 8.5情景下13%左右的南海诸岛珊瑚礁识别为保护优先区。根据热压力强度与珊瑚抵抗力及避难所关系,西沙群岛七连屿和晋卿岛近年观测与未来预估的热压力强度均比较低,在保障其服务功能的基础上建议实施完全保护;东沙群岛东沙环礁和中沙环礁排洪滩近年观测急性热压力强度较高但未来预估热压力强度较低,建议实施50%禁止利用保护;中沙群岛黄岩岛近年观测和未来预估的急性热压力强度均比较低,建议实施50%多用途保护。南沙群岛有14%左右的珊瑚礁识别为保护优先区,根据其热压力强度可实施30%~100%禁止利用保护或30%~50%多用途保护。RCP 4.5和RCP 8.5情景下的南海诸岛保护优先区及保护对策,可为维持珊瑚礁生态弹性及应对全球气候变化提供重要的参考价值。     

新疆公共服务资源空间配置与城乡互动耦合协调发展评价

公共服务资源是社会发展的"先行资本",对于区域社会经济发展与城乡融合发展具有正面外部效应。依据公共服务资源公平性、效益性与协调性原则,结合AHP、熵值与聚类分析方法,建立新疆公共服务资源配置与城乡互动效益评价指标体系,利用协调耦合发展模型,揭示研究区公共服务、城乡互动发展以及两者耦合协调度的总体特征和空间特征。结果表明:(1)新疆各地不同类型公共服务资源空间配置公平性有所差异,空间非公平性>人口非公平性。(2)公共服务资源综合效益以及城乡互动发展水平呈现较低、一般(中等)、较高三个类型。(3)公共服务效益空间分异特征呈现出东南片区>西北片区;城乡互动水平空间差异呈现出天山北坡经济带高于其他区域。(4)新疆大部分处于城乡互动与公共服务相互影响、相互磨合的过渡发展阶段,导致公共服务损益或城乡互动损益,个别区域处在两个系统相互制约、失调衰退阶段。通过进一步提出加快建立健全城乡互动公共服务体系,构建大、中、小多层次城镇空间格局,继续完善和开拓新的公共服务增长点以满足不断增长的城乡社会发展需求等建议措施,为确保城乡居民生存发展公平与效率,促进公共服务与城乡互动耦合协调发展提供参考借鉴...     

开鲁盆地奈曼凹陷北部地区下白垩统地层剥蚀量恢复及其对油气藏的影响

恢复地层剥蚀厚度是研究盆地演化史和进行油气资源评价的重要基础工作。奈曼凹陷作为开鲁盆地中一个重要的沉积凹陷,整体勘探程度不高。本文运用地震地层厚度趋势法辅之以构造沉积综合法恢复了奈曼凹陷北部地区下白垩统九佛堂组上段和下段的古地层厚度及地层剥蚀量分布范围;同时结合奈曼地区构造演化特征和沉积相特征确定了奈曼凹陷北部地区的沉降中心位于奈10井区域,明确了九佛堂组时期原始沉积相展布特征。在物源供给方面,北部物源受搬运距离远及剥蚀难以存留的影响未能沉积,主要来自于西部陡坡带发育的扇三角洲相沉积及东部缓坡带发育的辫状河三角洲相沉积。此外,研究还发现奈曼凹陷北部地区下白垩统古地层厚度地质模型特征为北东向受抬升剥蚀最严重,剥蚀范围广,剥蚀厚度大。此次研究对于揭示该区域的构造演化历史及油气成藏过程有一定的参考价值。同时,本次研究方法的应用对于类似沉积盆地的剥蚀量恢复研究也具有借鉴意义。

     

Silicon limitation on primary production and its destiny in Jiaozhou Bay, China——Ⅳ：Study on cross-bay transect from estuary to ocean

The authors analyzed the data collected in the Ecological Station Jiaozhou Bay from May 1991 to November 1994, including 12 seasonal investigations, to determine the characteristics, dynamic cycles and variation trends of the silicate in the bay. The results indicated that the rivers around Jiaozhou Bay provided abundant supply of silicate to the bay. The silicate concentration there depended on river flow variation. The horizontal variation of silicate concentration on the transect showed that the silicate concentration decreased with distance from shorelines. The vertical variation of it showed that silicate sank and deposited on the sea bottom by phytoplankton uptake and death, and zooplankton excretion. In this way, silicon would endlessly be transferred from terrestrial sources to the sea bottom. The silicon took up by phytoplankton and by other biogeochemical processes led to insufficient silicon supply for phytoplankton growth. In this paper, a 2D dynamic model of river flow versus silicate concentration was established by which silicate concentrations of 0.028–0.062 μmol/L in seawater was yielded by inputting certain seasonal unit river flows (m³/s), or in other words, the silicate supply rate; and when the unit river flow was set to zero, meaning no river input, the silicate concentrations were between 0.05–0.69 μmol/L in the bay. In terms of the silicate supply rate, Jiaozhou Bay was divided into three parts. The division shows a given river flow could generate several different silicon levels in corresponding regions, so as to the silicon-limitation levels to the phytoplankton in these regions. Another dynamic model of river flow versus primary production was set up by which the phytoplankton primary production of 5.21–15.55 (mgC/m²·d)/(m³/s) were obtained in our case at unit river flow values via silicate concentration or primary production conversion rate. Similarly, the values of primary production of 121.98–195.33 (mgC/m²·d) were achieved at zero unit river flow condition. A primary production conversion rate reflects the sensitivity to silicon depletion so as to different phytoplankton primary production and silicon requirements by different phytoplankton assemblages in different marine areas. In addition, the authors differentiated two equations (Eqs. 1 and 2) in the models to obtain the river flow variation that determines the silicate concentration variation, and in turn, the variation of primary production. These results proved further that nutrient silicon is a limiting factor for phytoplankton growth. This study was funded by NSFC (No. 40036010), and the Director's Fund of the Beihai Sea Monitoring Center, the State Oceanic Administration.