基于深度卷积嵌入式聚类（DCEC）的海洋环境特征提取对渔情预报模型的改进研究

In order to improve the forecasting ability of the fishery forecast model for the longline bigeye tuna (Thunnus obesus), we proposed a marine environment feature extraction method based on deep convolutional embedded clustering (DCEC), combined with generalized additive model (GAM) for forecasting the longline bigeye tuna fishing grounds in the Southwest Indian Ocean. We used the MODIS-Aqua and MODIS-Terra sea surface temperature (SST) three-level inversion image data (in days) from January to December in 2018 at 0.041 6°×0.041 6° to construct a DCEC model, determined the optimal number of clusters based on the Davies-Bouldi index (DBI), and extracted the category feature value (F_M) of each month’s sea surface temperature (SST); we used monthly 1°×1° bigeye tuna longline fishery data from January to December in 2018 generated from the Indian Ocean Tuna Commission (IOTC), and calculated the catch per unit effort (CPUE); we matched the monthly category feature value F_M and the monthly average value of Chl a concentration with the CPUE data to construct an improved GAM; we matched the monthly average SST, the monthly average Chl a concentration and CPUE data to build a basic GAM; we used the joint hypothesis test (F test) to verify the influence of model explanatory variables; we used akaike information criterion (AIC), mean square error (MSE), and draw the frequency distribution diagrams and box diagrams of measured and predicted values, etc., to analysis the improvement effect of the improved GAM compared to the basic GAM. The results showed that: (1) the category feature value (F_M) extracted based on the DCEC model could better reflect the temporal and spatial dynamic characteristics of SST in the Southwest Indian Ocean, and was related with the climatic conditions, monsoon conditions, and hydrological characteristics in the Southwest Indian Ocean; (2) the factor interpretation of F_M was higher than that of the monthly average SST in GAM, which means F_M had more significant impact on the CPUE of bigeye tuna. The high catch rate was concentrated in the areas where the F_M category was 2, 10, 24 with intersections between the warm and cold currents; (3) the AIC of the improved GAM was reduced by 9.17% than that of the basic GAM and MSE of the improved GAM was reduced by 26.7% than that of the basic GAM; the frequency distribution of the CPUE logarithmic value predicted by the improved GAM was closer to the normal distribution, and the high frequency distribution interval was closer to that of the measured value; the scatter plot showed that the CPUE predicted by the improved GAM had a significant correlation with the measured CPUE, with r equaled to 0.60. This study proves the effectiveness of the DCEC model in extracting marine environmental features, and can provide a reference for the further study on the bigeye tuna fishery forecast.     

中国天气发生器的降水模拟

A stochastic model for daily precipitation simulation in China was developed based on the framework of a ‘Richardson-type‘ weather generator that is an important tool in studying impacts of weather/climate on a variety of systems including ecosystem and risk assessment. The purpose of this work is to develop a weather generator for applications in China. The focus is on precipitation simulation since determination of other weather variables such as temperature is dependent on precipitation simulation. A framework of first order Markov Chain with Gamma Distribution for daily precipitation is adopted in this work. Based on this framework, four parameters of precipitation simulation for each month at 672 stations all over China were determined using daily precipitation data from 1961 to 2000. Compared with previous works, our estimation for the parameters was made for more stations and longer observations, which makes the weather generator more applicable and reliable. Spatial distributions of the four parameters are analyzed in a regional climate context. The seasonal variations of these parameters at five stations representing regional differences are discussed.Based on the estimated monthly parameters at 672 stations, daily precipitations for any period can be simulated. A 30-year simulation was made and compared with observations during 1971-2000 in terms of annual and monthly statistics. The results are satisfactory, which demonstrates the usefulness of the weather generator.     

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Cu2+/SnO2复合纳米光催化剂的制备及其对海洋柴油污染物的降解

采用化学沉淀法成功制备了Cu2+/SnO2复合纳米光催化剂,采用XRD、SEM等测试手段对复合纳米光催化剂的粒径、形态等进行表征。在紫外光条件下,分别改变催化剂掺杂比、催化剂煅烧温度、催化剂投加量、柴油初始含量和光照时间等单因素,探究不同条件对Cu2+/SnO2复合纳米光催化剂降解海洋柴油污染物的影响。结果表明,自制复合纳米光催化剂可以有效降解海水中的柴油污染物,在紫外光作用下,于400℃下煅烧Cu/Sn掺杂比为0. 03的Cu2+/SnO2复合纳米光催化剂、投加量为0. 2 g/dm3、柴油初始含量为0. 15 g/dm3、H2O2溶液含量为0. 2 g/dm3、溶液的p H为7、光照时间3 h时效果最好,海水中柴油的去除率最高,达到86. 98%。Cu2+/SnO2复合纳米光催化剂用聚丙烯纳米球负载后可以实际应用于海洋中,便于回收。     

中国天山地区的黄土

黄土问题一向为国内外众多学者所关注。尤其是黄土的成因问题,更是众说纷纭,诸如风成、冰水、洪积、坡积……等成因,至今仍在争论。我们认为对黄土成因不可一概而论,要按具体地域和自然环境而具体分析。对我国新疆境内天山地区的黄土,虽曾有人著文作过记述,对黄土成因也提出了“风成”、“水成”、“风水共成”、“洪积”等不同的看法。但是对这方面的研究仍显不足。我们在前人工作的基础上,根据多年的野外考察和室内分析,提出了一些看法。如有不妥,请批评指正。     

对藏北嘎色地区沙木罗组的新认识

笔者在西藏班公错-怒江结合带中段南缘嘎色地区的一套缺少化石依据的地层中,发现有孔虫Mesorbitolina sp.等化石,地层时代确定为晚侏罗世—早白垩世,层位应归属沙木罗组上部。该套地层地质时代的确定,对研究沙木罗组的沉积相,重塑古地理环境有十分重要意义。     

北秦岭二郎坪杂岩变沉积岩碎屑锆石年代学及其构造地质意义

碎屑锆石为沉积岩中最稳定的矿物,其年龄谱系不仅可限定沉积物的最大沉积年龄与物源性质,而且能够为探讨其形成构造环境提供关键约束。作为北秦岭构造带主要构造岩石地层单元之一,二郎坪杂岩由北、中、南三个构造岩片——北部碎屑岩片、中部蛇绿岩片和南部变碎屑岩片组成。本文对二郎坪杂岩南部变碎屑岩片中的碎屑锆石进行了LA-ICP-MS U-Pb年龄测试研究,获得样品锆石谐和年龄值分布在500±7Ma~3894±5Ma之间,1个年龄高频集中区为0.9~1.0Ga,6个次要年龄集中区分别为500~600Ma、750~850Ma、1.35~1.48Ga、1.6~1.75Ga、2.6~2.7Ga和3.0~3.4Ga。研究结果表明:1)最小峰值年龄限定二郎坪杂岩南部碎屑岩片原岩的最大沉积时代为500Ma,结合西庄河花岗闪长岩侵入南部岩片的地质事实,南部岩片的形成时代应为早古生代寒武-奥陶纪(500~475Ma),明显早于中部蛇绿岩片中的火山岩的形成时代(463~475Ma);2)通过与邻区地质事件年龄谱峰及其锆石阴极发光图像特征的对比,二郎坪杂岩变碎屑岩原岩的物源分别主要来自南部秦岭杂岩中的早新元古代花岗岩和北部华北南缘熊耳群中元古代火山岩,其物源具有双源性,暗示其形成于与伸展作用相关的裂谷或弧后盆地构造背景,而二郎坪蛇绿岩片所代表的古洋盆可能正是在此基础上发育产生的;3)结合区域地质背景资料分析,二郎坪杂岩中的沉积碎屑岩片可能形成于商丹洋向北俯冲期间所产生的弧后伸展盆地构造环境;4)通过与宽坪岩群沉积岩中的碎屑锆石年龄数据的对比,揭示二者碎屑锆石具有相似的年龄谱峰,结合宽坪群变沉积岩中发现大量疑源类、几丁虫和虫颚等早-中奥陶世化石组合以及二郎坪杂岩蛇绿岩片中的火山岩夹层硅质岩中发现早-中奥陶世牙形石和放射虫的研究,分析认为二者沉积物的沉积时代相近,沉积物源几乎完全一致,暗示它们形成的构造环境可能具有一致性;5)二郎坪蛇绿岩片中的典型的与洋壳俯冲有成因联系的弧火山岩的形成时代(463~475Ma)明显迟后于区内高压-超高压岩石的峰期变质时代(514~484Ma)约20~30Myr,清楚地表明二郎坪洋壳拖曳秦岭杂岩发生陆壳俯冲-深俯冲作用的可能性不大;6)二郎坪杂岩南部碎屑岩片和宽坪岩群碎屑沉积物中碎屑锆石中最主要的年龄集中区(0.9~1.0Ga)的物源来自秦岭杂岩中的早新元古代花岗质岩石,而缺少秦岭杂岩中的早古生代岩浆岩和HP/UHP变质岩石锆石的年龄信息,明确指示二郎坪与宽坪盆地沉积时,秦岭杂岩重要组成的早新元古代花岗质岩石已出露于地表接受剥蚀,而秦岭杂岩中出露的HP/UHP岩石和早古生代岩浆岩未抬升出露地表,即秦岭杂岩现今出露的前早古生代陆壳物质不是整体而是部分经历了陆壳俯冲-深俯冲作用。     

包含CO2因子的冠层光合作用简化模型及其关键参数数值敏感分析

利用美国Licor公司生产的Li-6200便携式光合作用测定仪对冬小麦叶片光合作用进行了较为系统的测定研究,在实测资料支持下建立了包含CO2因子的叶片和冠层光合作用模型,验证结果表明,模型具有较高准确性.利用模型对CO2影响参数μ进行数值敏感分析,结果表明:对叶片光合而言,μ=0.83时叶片光合作用模型拟合最好,随μ减小或增大,拟合精度均下降;对冠层光合而言,μ=0.83时模拟光合日总量达到最大值,μ减小或增大,光合日总量均下降.多因子数值分析表明:在辐射值较大的状况下,μ对冠层光合的影响更为显著.     

吉林中部平原区浅层地下水温度对全球气候变暖的响应

水温变化除引起水的多种物理性质的变化外, 还会引起水化学反应速度等方面的变化. 以吉林中部平原地区为例, 对影响浅层地下水温因素的分析发现, 研究区浅层地下水温变化的本质原因是受全球气候变化的影响, 降水量的减少以及地下水位的下降对浅层地下水温受气候变化的影响起到削减作用. 通过对全区近200眼地下浅层观测井水温的多年变化分析, 发现在研究区气温近20 a来升高(约1.5 ℃)的影响下, 浅层地下水温从1978年的7 ℃左右上升到2001年的8.3 ℃, 在20余年间水温升高约1.3 ℃     

中国大陆地壳单颗粒锆石U-Pb年代学特征:国内文献数据的初步分析

锆石U-Pb年代学方法已经成为地质学研究必不可少的方法。本文收集整理了二十世纪八十年代以来分散在期刊论文、学位论文等多种出版载体中的锆石U-Pb年代学数据,建成中国大陆单颗粒锆石数据库中文子库。该数据子库涉及截至到2017年底的文献2331篇,有效数据154768条目,数据总量已经能够用来进行数据的初步分析和相关地球科学研究。数据子库中年龄-年龄绝对误差关系的分析表明,Age(~(206)Pb/~(238)U)、Age(~(207)Pb/~(235)U)、Age(~(207)Pb/~(206)Pb)在不同的地质年代区间误差表现有所不同。在小于1684.4Ma、1684.4~2855.2Ma、大于2855.2Ma年龄区Age(~(206)Pb/~(238)U)、Age(~(207)Pb/~(235)U)、Age(~(207)Pb/~(206)Pb)的误差最小、置信度最好,除了Age(~(207)Pb/~(235)U)测试方法的原因外,Age(~(206)Pb/~(238)U)和Age(~(207)Pb/~(206)Pb)可分别作为不同年龄段的推荐年龄。将选用的推荐年龄运用于LA-ICP-MS、SHRIMP、SIMS三种方法的比较,得出其适用于不同地质年代的范围。推荐年龄运用于年龄-频数图中并使用高斯多峰拟合,则可发现中国大陆锆石存在6个生长峰期,分别为131.71Ma、255.17Ma、442.42Ma、811.56Ma、1868.36Ma和2505.31Ma等;更小尺度下的新生代则存在七个峰期,分别为16.99Ma、27.64Ma、35.26Ma、43.44Ma、48.27Ma、52.74Ma和62.07Ma等,峰期及其对应测试点的位置可与中国大陆地壳演化重大历史事件对应。