CO2加富对塔玛亚历山大藻叶绿素荧光参数及产毒的影响

由大气中CO_2浓度升高引起的海洋酸化,是全球性的重大环境问题之一。本研究采用实验生态学的方法,以塔玛亚历山大藻(Alexandrium tamarense)为研究对象,分析其在CO_2加富条件下叶绿素荧光动力学参数及产毒特征的变化。调制叶绿素荧光结果显示,CO_2加富对塔玛亚历山大藻的PSⅡ最大光化学量子产量(Fv/Fm)、最大相对电子传递效率(r ETRmax)有显著影响(P0.05),且随着培养时间的增长Fv/Fm、r ETRmax均降低,对半饱和光强(Ik)、快速光曲线初始斜率(α)却无显著影响(P0.05)。结果说明CO_2加富能促进塔玛亚历山大藻的PSⅡ最大光化学量子产量,提高其最大光能转换效率和相对最大电子传递效率。高效液相色谱法分析结果显示,该株塔玛亚历山大藻主要产漆沟藻毒素1(GTX1)、漆沟藻毒素4(GTX4)、N-磺酰氨甲酰基毒素(C1)及N-磺酰氨甲酰基毒素(C2)四种PSTs毒素,CO_2加富不改变主要麻痹性贝毒(PSTs)的种类组成,但能显著提高氨基甲酸酯类毒素(GTX1、GTX4)产量(P0.05),而降低N-磺酰氨甲酰基类毒素(C1、C2)产量(P0.05),说明加富能使塔玛亚历山大藻所产毒素发生转化,进而影响藻细胞的整体毒性。     

温度、饵料种类对中华哲水蚤(Calanus sinicus)油脂积累与生长发育的影响

中华哲水蚤(Calanus sinicus)C5期幼体的油脂积累是种群在黄海冷水团中得以顺利度夏的关键过程。本研究对温度(10°C和19°C恒温,10—19°CⅠ和10—19°CⅡ变温)与饵料种类(硅藻饵料,自然饵料)双因子培养实验进行研究,探讨温度和饵料种类对中华哲水蚤油脂积累与生长发育的影响作用。结果表明,不同的温度和饵料种类对C5期幼体的油脂积累均有影响。C5期幼体在变温组的油脂积累是10°C组的31%—102%,是19°C组的1.8—6.1倍,低温有利于C5期幼体降低个体代谢消耗以增加油脂的积累。在恒温培养下,C5期幼体在硅藻饵料组的油脂积累是自然饵料组的2.8倍,硅藻饵料比自然饵料更有利于油脂的积累。雌体的体长和油囊体积均随着温度的升高而减小。与硅藻饵料相比,在自然饵料组中雌体的性腺发育速度更快,性腺成熟度更高(繁殖指数:58%—65%)。     

天津市滨海新区芦苇湿地恢复适宜性评价

利用综合评价模型,结合地理信息系统技术的空间分析功能,以土地利用、土壤类型、坡度、降雨量和人类干扰活动作为评价因子,对天津滨海新区芦苇湿地恢复进行了适宜性评价。结果表明,较适宜开展湿地恢复的比例为21.46%,一般适宜比例为21.87%,不适宜比例占56.68%,其中较适宜湿地恢复的区域集中分布在北大港湿地自然保护区周边、独流减河下游、北塘入海口以及沿海滩涂,海河流域两侧也有零星分布。在适宜性评价基础上,对未来芦苇湿地恢复与建设的重点区域进行了成效预评估,芦苇对TC、TN、TP的年吸收通量约为1.3935×104、0.0258×104、0.0017×104t,能有效地减少入海排污压力和污染物对近岸海域环境质量的影响。研究结论可为天津湿地治理与生态恢复、土地利用结构调整、景观优化等提供理论依据和科学参考。     

LA-ICP-MS测定锡石U-Pb同位素年龄时两种普通铅扣除方法的原理及适用性比较

根据近年来激光烧蚀电感耦合等离子体质谱仪锡石微区原位U-Pb同位素定年的实验结果,结合相关资料,对实验过程中普通铅扣除的2种主要方法,即谐和图法和等时线法的原理、效果、优点和局限性进行了深入的比较。研究成果表明,2种主要方法各有不同的优点及局限性。在实际工作中,要想获得比较准确的测试结果,需要根据具体矿物样品的年龄范围、总的U和Pb含量、普通铅相对含量、测年精度要求等因素,灵活地选择普通铅扣除的方法。     

Development and Extension of An Aggregated Scale Model: Part 1 – Background to ASMITA

Whilst much attention has been given to models that describe wave, tide and sediment transport processes in sufficient detail to determine the local changes in bed level over a relatively detailed representation of the bathymetry, far less attention has been given to models that consider the problem at a much larger scale (e.g. that of geomorphological elements such as a tidal flat and tidal channel). Such aggregated or lumped models tend not to represent the processes in detail but rather capture the behaviour at the scale of interest. One such model developed using the concept of an equilibrium concentration is the Aggregated Scale Morphological Interaction between Tidal basin and Adjacent coast (ASMITA). In this paper we provide some new insights into the concepts of equilibrium, and horizontal and vertical exchange that are key components of this modelling approach. In a companion paper, we summarise a range of developments that have been undertaken to extend the original model concept, to illustrate the flexibility and power of the conceptual framework. However, adding detail progressively moves the model in the direction of the more detailed process-based models and we give some consideration to the boundary between the two.     

Apatite-hosted melt inclusions from the Panzhihua gabbroic-layered intrusion associated with a giant Fe–Ti oxide deposit in SW China: insights for magma unmixing within a crystal mush

The ～?2-km-thick Panzhihua gabbroic-layered intrusion in SW China is unusual because it hosts a giant Fe–Ti oxide deposit in its lower zone. The deposit consists of laterally extensive net-textured and massive Fe–Ti oxide ore layers, the thickest of which is ～?60 m. To examine the magmatic processes that resulted in the Fe enrichment of parental high-Ti basaltic magma and the formation of thick, Fe–Ti oxide ore layers, we carried out a detailed study of melt inclusions in apatite from a ～?500-m-thick profile of apatite-bearing leucogabbro in the middle zone of the intrusion. The apatite-hosted melt inclusions are light to dark brown in color and appear as polygonal, rounded, oval and negative crystal shapes, which range from ～?5 to ～?50 µm in width and from ～?5 to ～?100 µm in length. They have highly variable compositions and show a large and continuous range of SiO₂ and FeO_t with contrasting end-members; one end-member being Fe-rich and Si-poor (40.2 wt% FeO_t and 17.7 wt% SiO₂) and the other being Si-rich and Fe-poor (74.0 wt% SiO₂ and 1.20 wt% FeO_t). This range in composition may be attributed to entrapment of the melt inclusions over a range of temperature and may reflect the presence of µm-scale and immiscible Fe-rich and Si-rich components in different proportions. Simulating results for the motion of Si-rich droplets within a crystal mush indicate that Si-rich droplets would be separated from Fe-rich melt and migrate upward due to density differences in the interstitial liquid when the magma unmixed. Migration of the Si-rich, immiscible liquid component from the interstitial liquid caused the remaining Fe-rich melt in the lower part to react with plagioclase primocrysts (An_59–60), as evidenced by fine-grained lamellar intergrowth of An-rich plagioclase (An_79–84)?+?clinopyroxene in the oxide gabbro of the lower zone. Therefore, magma unmixing within a crystal mush, combined with gravitationally driven loss of the Si-rich component, resulted in the formation of Fe-rich, melagabbro and major Fe–Ti oxide ores in the lower part and Si-rich, leucogabbro in the upper part of the intrusion.     

卷积神经网络及其在矿床找矿预测中的应用——以安徽省兆吉口铅锌矿床为例

大数据人工智能地质学刚刚起步,基于大数据智能算法的地质研究是非常有意义的探索性实验。利用大数据和机器学习解决矿产预测问题,有助于人们克服不能全面考虑地质变量的困难及评估当前模型在已有数据中的可靠性。元素地表分布特征量主要受原岩成分、成矿作用影响和地表过程的影响,它们携带某些指示矿体就位的信息,即矿体在地下空间就位时在地表的响应,且未在地表过程中消失。以往的地球化学勘查工作仅仅识别异常,但未能发现矿体在地表响应的成矿特征量。本文以安徽省兆吉口铅锌矿床为例,通过机器学习,利用卷积神经网络算法,不断挖掘元素Pb分布特征与矿体地下就位空间的耦合相关性。经过1000次训练后,可以得到准确率0. 93,损失率0. 28的卷积神经网络模型。这种神经网络模型就是矿体在地下就位时元素在地表分布的响应,可以用来进行矿产资源预测。应用该模型对未知区进行预测,结果显示第53号区域具有很大概率存在尚未发现的矿体。     

基于支持向量机的喀斯特山区土壤环境质量评价——以贵州北部一茶叶园区为例

以贵州北部一茶叶园区80个表层土壤样品为研究对象,对其Hg、As、Cd、Pb、Cr和Cu含量进行测定,在MATLAB中应用支持向量机构建土壤环境质量评价模型,并与模糊综合评价法和内梅罗综合污染指数法的评价结果对比分析,探究支持向量机模型在喀斯特山区土壤环境质量评价中的适用性,其结果表明:研究区土壤质量Ⅰ类与Ⅱ类样品比例为33∶7,土壤环境质量大多数为I类;支持向量机方法的评价结果与模糊综合评价法和内梅罗综合污染指数法结果的相同率分别达到82.5%和80.0%,并分析结果有差异的样品,发现支持向量机评价结果更符合实际情况,这说明该模型适用于土壤环境质量的评价。