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岩溶区植被与岩石地球化学背景间相互作用机制研究进展

朱帅, 曹建华, 杨慧, 梁建宏, 劳昌玲

朱帅, 曹建华, 杨慧, 梁建宏, 劳昌玲. 岩溶区植被与岩石地球化学背景间相互作用机制研究进展[J]. 岩矿测试, 2023, 42(1): 59-71. DOI: 10.15898/j.cnki.11-2131/td.202108090095
引用本文: 朱帅, 曹建华, 杨慧, 梁建宏, 劳昌玲. 岩溶区植被与岩石地球化学背景间相互作用机制研究进展[J]. 岩矿测试, 2023, 42(1): 59-71. DOI: 10.15898/j.cnki.11-2131/td.202108090095
ZHU Shuai, CAO Jianhua, YANG Hui, LIANG Jianhong, LAO Changling. A Review of the Interaction Mechanism and Law between Vegetation and Rock Geochemical Background in Karst Areas[J]. Rock and Mineral Analysis, 2023, 42(1): 59-71. DOI: 10.15898/j.cnki.11-2131/td.202108090095
Citation: ZHU Shuai, CAO Jianhua, YANG Hui, LIANG Jianhong, LAO Changling. A Review of the Interaction Mechanism and Law between Vegetation and Rock Geochemical Background in Karst Areas[J]. Rock and Mineral Analysis, 2023, 42(1): 59-71. DOI: 10.15898/j.cnki.11-2131/td.202108090095

岩溶区植被与岩石地球化学背景间相互作用机制研究进展

基金项目: 

广西科技基地和人才专项项目 桂科AD20297090

广西科技基地和人才专项项目 桂科AD22035030

中国地质科学院基本科研业务费项目 CSJ-2021-03

详细信息
    作者简介:

    朱帅,硕士,助理研究员,主要从事岩溶区元素迁移研究。E-mail: zhu15131215153@126.com

    通讯作者:

    曹建华,博士,研究员,主要从事生物岩溶、岩溶生态系统、岩溶碳循环及碳汇效应研究。E-mail: cjianhua@mail.cgs.gov.cn

  • 中图分类号: P588.245

A Review of the Interaction Mechanism and Law between Vegetation and Rock Geochemical Background in Karst Areas

  • 摘要:

    岩溶地貌主要是由碳酸盐溶解形成的特殊景观,岩溶区植被的生长发育受到基岩的制约,并演化出各种机制来适应岩溶区的独特环境。本文综述了岩溶地区植物对岩溶环境适应机制及植物生长对碳酸盐岩风化的驱动作用。通过总结发现:①植物主要通过分泌碳酸酐酶等有机物促进矿物分解、生物钻孔作用改善岩石表面的持水性能、根劈作用加速破碎岩石的崩解等化学生物和物理作用,促进了碳酸盐岩的风化溶解,形成独特的岩溶地球化学背景。②岩溶区植物通过调整自身结构和生理功能来适应干旱、高钙和营养元素缺乏等逆境。植物的抗旱性主要通过生理生化过程、形态结构和水分的利用方式来适应干旱或缺水环境,不同的植物进化出不同水分利用方式,提高水分利用效率,减少蒸腾;植物的高钙适应性是通过生理结构和生理过程来实现的,在高钙环境下的优势植物可通过形成钙化根、草酸钙含晶细胞和叶片调节等方式保持植株钙含量处于相对稳定的状态,并且植物还可以通过调节体内钙库和控制钙的吸收转运来控制细胞内钙离子浓度;根系分泌的有机酸和菌根能帮助植被在土壤中获取营养元素,以应对土壤的营养元素缺乏。③岩溶植被在正向演替过程中,土壤保水保肥能力增强、稳定性增加,物种的生存几率增加,物种多样性也随着增加。植被演化出的适应机制影响了植物的分布和生长,推进植物群落的演替过程和促进植物多样性的形成。但是多样性与群落生态系统的稳定性间的内在关系,以及与非岩溶区的对比特征仍需要开展深入的研究和探索。

    要点

    (1) 植物的岩溶作用、适应机制、演替特征和生物多样性是一个相互作用的整体。

    (2) 植被的立地生长促进了碳酸盐岩的风化成土,植被的演替改变了土壤的理化性质,土壤的特性影响植物的生长和多样性。

    (3) 植被演化出的适应机制影响植物的分布和生长,这种影响促进了植物群落的演替和多样性的形成。

    HIGHLIGHTS

    (1) The four aspects of karstification, plant adaptation mechanisms, karst vegetation succession characteristics shown in the adaptation process, and vegetation biodiversity formed in the adaptation and succession process are an interactive whole.

    (2) The vegetation promotes the dissolution and weathering of carbonate rocks, the succession of vegetation changes the physical and chemical properties of soil and improves the soil quality, and the karst of carbonate rocks promotes the growth of vegetation and the formation of species diversity.

    (3) The adaptive mechanism evolved by vegetation affects the distribution and growth of plants, which promotes the succession and diversity of plant communities.

  • X射线衍射在物相定量分析方面应用广泛,常用的方法有内标法、外标法、K值法、绝热法等[1-3],其建立的理论基础是物质参与衍射的体积或质量与其产生的衍射强度成正比。实际上,由于受样品所含物相组成元素的影响,各物相吸收系数是存在差异的,因此每个物相衍射峰的强度与质量并不呈线性;样品中多个物相混合导致衍射峰重叠、择优取向明显;地质样品成分复杂多变,难以获得纯矿物。以上诸多因素都影响着衍射定量分析结果的准确性。以全谱拟合法(Rietveld)为基础的X射线衍射全谱拟合法,无需标样、不用引入其他的内标物、能够一次获得样品中所有物相的含量与结构信息,因此在岩石矿物定量相分析方面具有广阔的应用前景。目前国内外已有报道将全谱拟合法应用于石灰石、铁矿石、水泥熟料以及铝土矿精炼尾矿的物相分析[4-8]和土壤样品中主要矿物成分定量分析[9]等,获得的分析结果经与其他方法比较,证明是可靠的。

    长石是重要的造岩矿物。在基础地质工作中对长石进行研究有助于理解岩石成因与成矿关系,区分岩石类型,分析岩石形成与变化过程;在油气储层研究中,长石的含量影响岩石的电性,因此对长石进行准确定量具有重要意义。通常长石分类定名需要根据钠、钾、钙等元素的化学分析结果计算长石矿物组成,分析流程长、计算复杂。利用光学显微镜测定长石含量的方法易受切片位置的影响,代表性不足;长石的类质同象替代很发育,不同的长石有时在显微镜下面是很难区分的。X射线衍射全谱拟合法采用制备好的粉末进行物相分析,样品具有足够的代表性;一次扫谱不仅能够获得样品中各种物相的含量,还能够了解其结构参数,解决有序、无序问题。方法操作简便、分析速度快。因此本文尝试采用多晶X射线衍射全谱拟合法对野外长石样品和钾长石国家一级标准物质中的矿物含量进行分析,并与其他衍射定量分析方法和化学分析方法的结果进行比较,以探讨X射线衍射全谱拟合法应用于该类样品快速物相定量分析的可行性。

    全谱拟合法起源于粉末中子衍射结构分析,其实质是采用最小二乘法对数字化的粉晶衍射数据和图形进行拟合,使计算谱无限趋近于实验谱从而达到定量分析的目的。全谱拟合定量相分析充分利用整个衍射谱图的信息,用散射总量替代单个(hkl)散射量,有效地克服了多个物相共存时可能造成的衍射峰叠加,通过分离各相散射量,实现了多相同时定量;拟合过程中用数学模型对实验数据进行限定,不断调节模型中的参数值,逐步使实验数据与模型计算值间达到最佳吻合,从而提高了定量物相分析的准确度和可靠性。

    全谱拟合分析所使用的模型参数是晶体结构参数和微结构参数。各相的质量分数计算式[10]为:

    $ {w_{\rm{p}}} = \frac{{{{\left( {SZMV} \right)}_{\rm{p}}}}}{{\sum {{{\left( {SZMV} \right)}_{\rm{j}}}} }} $

    式中:S-标定因子,其物理意义是实验数据强度值与模型计算衍射强度间的换算因子;Z-单位晶胞中的分子数;M-化学式分子量;V-晶胞体积。

    全谱拟合的效果通过判断因子R值来判断,其中常用的有图形剩余方差因子(Rp)和权重图形剩余方差因子(Rwp)[11]RpRwp两值越小,表明衍射强度的观察值与计算值越吻合,则得到正确的定量结果的可能性越大。通常判断因子R的值达到10%左右时,即可认为定量结果是可靠的。

    高质量的原始数据谱是定量相分析的重要基础,实验采用荷兰帕纳科公司生产的X’Pert Pro型多晶X射线衍射仪。工作条件为:铜靶(λ=0.154060 nm),X光管工作电压40 kV,电流40 mA,2θ范围5°~80°,步长0.013°,扫描每步时间8.67 s,发散狭缝0.87°,记录相应的衍射强度。

    实验选用长石野外样品和钾长石国家一级标准物质(GBW03116)。将块状长石样品粉碎,仔细研磨至手摸无颗粒感(350目左右)。制备好的样品粉末填充于仪器配备的铝制样品托中,压平压实即可上机测试。

    定性分析结果是进行全谱拟合分析的重要基础,其准确性直接影响到全谱拟合定量分析结果的准确度。通过定性分析选定物相,调取其晶体结构参数是制约全谱拟合定量分析的关键因素之一[12-14]。样品定性分析选用国际无机晶体结构数据库(ICSD)中的卡片。图 1是样品的衍射谱,经确定背景、寻峰处理后,进行定性分析。软件采用残谱顺序检索的方法,逐一对样品中物相的衍射峰进行检索,直至扫描范围内强度足够的衍射峰基本得到匹配。检索得到样品所含物相有两种:微斜长石(Microcline,ICSD98-004-5732,Al1K1O8Si3)、钠长石(Albite low,ICSD98-004-6405,Al0.91Na1O8Si3),未见其他杂质。

    图  1  研究样品衍射谱
    Figure  1.  The X-ray diffraction spectrum of sample

    数据拟合采用HighScore Plus 3.0版本。根据定性分析结果,导入物相;先对谱图进行自动拟合,在此基础上分别对全局变量(Global variables)和所涉及物相的结构参数进行手动拟合,包括择优取向(preferred orientation),全局因子(Boverall),比例因子(scale factor),晶胞参数(abcαβγ)和峰形参数(UVW)等。原子配位对定量分析结果的影响很小,一般情况下不予修正[6]

    由于样品自身特点造成的择优取向是影响定量相分析准确度的重要因素。拟合过程中软件提示的差谱结果表明钾长石的{200}、{013}晶面,钠长石的{200}晶面存在明显的择优取向,通过物相复制分别对上述晶面进行修正,直至计算谱和实验谱残差较小。多次拟合后最终结果的判定因子:Rp=7.72%,Rwp=10.09%,结果可靠。全谱拟合分析结果显示,样品中的微斜长石含量为75.34%,钠长石含量为24.66%(图 2)。从拟合后的样品晶体结构参数(表 1)来看,与ICSD给出的物相参数基本一致。

    图  2  研究样品Rietveld精修分析结果
    Figure  2.  Rietveld refinement results of sample
    表  1  样品Rietveld定量相分析结果和组成相的结构参数
    Table  1.  Rietveld quantitative phase analysis results and crystal structure data of samples
    矿物名称 化学结构式 结构参数 含量 数据来源
    a(Å) b(Å) c(Å) α(°) β(°) γ(°) Rietveld法 参比法(RIR法)
    微斜长石 Al1K1O8Si3 7.2230 7.6230 7.9190 113.075 104.240 103.651 75.34 84 ICSD
    7.2229 7.6352 7.9129 113.026 104.267 103.704 本研究
    钠长石 Al0.91 Na1O8 Si3 7.1580 7.4370 7.7140 115.080 107.329 100.419 24.66 16 ICSD
    7.1576 7.4456 7.7161 115.106 107.305 100.432 本研究
    下载: 导出CSV 
    | 显示表格

    目前很多粉晶衍射数据分析软件都具备参比法(RIR)定量相分析功能,可以简单、快捷地对样品进行半定量分析。RIR值就是K值,是将样品与刚玉标准物质按照1: 1的质量比混合后测量得到的样品最强衍射峰积分强度与刚玉最强衍射峰积分强度的比值[15]。通常,国际衍射数据中心出版发行的PDF卡都附有物相的RIR值。根据软件RIR法的分析结果,样品中的微斜长石含量为84%,钠长石含量为16%。与2.2节全谱拟合分析结果相比较,微斜长石含量的相对偏差为10.9%, 钠长石含量的相对偏差为42.6%,不能满足检测质量控制要求。造成两种方法分析结果差异较大的原因是:微斜长石的最强衍射峰为2θ=27.4410°的{200}晶面,钠长石的最强衍射峰为2θ=27.9040°的{200}晶面,这两个晶面都存在明显的择优取向,造成衍射强度发生改变;另一方面,虽然样品仅有两种物相,但仍然无法避免衍射峰重叠的问题。这两个因素使两种物相的最强衍射峰积分强度发生了变化,而RIR法计算样品含量使用的是最强衍射峰的积分强度,因此必然带来较大的分析误差。全谱拟合分析结果修正了择优取向的影响,解决了衍射峰重叠的问题,因此能够获得比RIR法更为准确的分析结果。

    绝热法也是X射线衍射定量分析中常用的方法之一。其分析的基础为假设待测样中多个物相均为结晶相(不可有非晶相)且K值已知,由待测样中某一相充当标样,通过实测各相特定峰的强度求得所有结晶相的含量。由于该方法不用加内标,无需制作定标曲线,不稀释基体,也不会增加额外的谱线,用一个试样可测全部物相含量,实验误差较小[16],因此在各相K值已知的情况下,可用于未知样品的半定量分析。

    以样品中含有的钠长石为内标,采用绝热法计算该样品中各相的含量,结果为:微斜长石74.92%,钠长石25.08%。与2.2节全谱拟合分析结果相比较,微斜长石含量的相对偏差为0.56%, 钠长石含量的相对偏差为1.69%,两种分析方法结果吻合较好。可见,对于物相组成简单的样品,全谱拟合法与绝热法的定量分析结果可比性强。不同的是,全谱拟合法仅通过软件处理即可得出结果,无需进行计算,操作更为简单。

    化学分析方法是目前公认的能够获得岩石矿物中特定元素准确含量的方法之一。由于缺乏用于X射线衍射物相定量分析的岩石矿物标准物质,为证明全谱拟合定量分析方法的准确度,实验采用化学分析测试结果按选定物相的化学结构式换算成相应的矿物含量,用以佐证方法的准确度。

    样品用盐酸-氢氟酸-高氯酸溶解后定容,以北京有色金属研究总院制备的混和标准溶液制作标准曲线,采用美国ThermoElemental公司的iCAP 6300型全谱直读电感耦合等离体子发射光谱仪测试样品中K和Na元素的含量,分别为9.94%和2.20%。根据化学结构式换算为矿物含量,获得样品中的微斜长石含量为70.76%,钠长石含量为24.86%。与2.2节全谱拟合分析结果相比较,微斜长石含量的相对偏差为6.27%,钠长石含量的相对偏差为0.81%,两种分析方法结果吻合较好。

    根据DZ/T 0130-2006《地质矿产实验室测试质量管理规范》对X射线衍射定量分析的质量要求,“测试结果的绝对误差一般不超过10min(1,C+0.06)(百分含量),其中C为被测物相含量分数(C≤1,真值或准确度较高的分析值)”。采用化学分析结果换算得到的矿物含量与全谱拟合分析结果相比较,微斜长石含量的绝对误差为4.58%,钠长石含量的绝对误差为0.20%。以化学分析结果换算的矿物含量为基础计算绝对误差允许限,从表 2可以看出,全谱拟合法分析结果的绝对误差小于行业标准规定的绝对误差允许限,能够满足日常检测工作的质量要求,测量结果也是可靠的。

    表  2  X射线衍射全谱拟合法与化学分析结果的比较
    Table  2.  A comparison of analytical results of ore determined by XRD and chemical analysis
    矿物名称 全谱拟合分析结果(%) 化学分析结果换算(%) 绝对误差允许限(%) 绝对误差(%)
    微斜长石 75.34 70.76 5.86 4.58
    钠长石 24.66 24.86 2.04 0.20
    下载: 导出CSV 
    | 显示表格

    由于目前缺乏用于X射线衍射定量相分析的标准物质,实验选用钾长石国家一级标准物质(GBW03116),采用与野外样品相同的实验方法进行全谱拟合分析,获得物相组成后进行换算比较,用以进一步验证方法的准确度。

    该标准物质定性分析结果为钾长石、含钙钠长石和石英。全谱拟合分析的最终判定因子为:Rp=5.39,Rwp=6.99,拟合结果可靠。样品中钾长石、含钙钠长石的含量分别为56.6%和36.2%。根据选定的物相结构式,将GBW03116的K、Na分别换算成相应的矿物,其含量分别为56.74%和37.54%,与全谱拟合分析获得结果的绝对误差分别为0.14%和1.34%(表 3),小于DZ/T 0130-2006规定的绝对误差允许限,结果可靠。

    表  3  钾长石标准物质物相分析结果
    Table  3.  Phase analysis results of potassium feldspar standards
    矿物名称 参考卡片 化学结构式 全谱拟合分析含量(%) 标准值换算含量(%) 绝对误差(%) 绝对误差允许限(%)
    钾长石 01-072-1114 KAlSi3O8 56.6 56.74 0.14 4.24
    钠长石 98-001-8020 (Na0.84Ca0.16)Al1.16Si2.84O8 36.2 37.54 1.34 2.73
    石英 98-004-6143 SiO2 7.2 - - -
    下载: 导出CSV 
    | 显示表格

    根据全谱拟合分析结果计算标准物质的化学成分,结果见表 4。计算得到的化学成分含量与标准物质化学成分标准值的绝对误差最大值仅为0.93%,表明全谱拟合分析结果准确、可靠。

    表  4  GBW03116化学成分分析结果比较
    Table  4.  A comparison of analytical resuts of the chemical components in GBW03116 standard material
    标准物质成分 化学成分标准值(%) 全谱拟合结果计算化学成分含量(%) 绝对误差(%)
    SiO2 66.26 67.19 0.93
    Al2O3 18.63 18.45 0.18
    K2O 9.60 9.58 0.02
    Na2O 3.69 3.56 0.13
    CaO 0.76 1.23 0.47
    下载: 导出CSV 
    | 显示表格

    本文利用X射线衍射全谱拟合法对长石样品和钾长石国家一级标准物质进行全谱拟合分析,得到的拟合判断因子RpRwp值都≤10%,谱图吻合程度高,结果可靠。表明了全谱拟合法能够有效降低因物相增多造成的衍射峰重叠影响,修正择优取向或其他因素造成的衍射强度误差,分析结果的准确度优于参比法(RIR法),与绝热法和化学分析换算结果的可比性强,分析误差能够满足DZ/T 0130-2006《地质矿产实验室测试质量管理规范》对X射线衍射定量分析的质量要求。

    在实际工作中,由于该方法操作简单、快速,无需标准物质,也无需挑选纯净矿物制作标准工作曲线,因此可用于岩石矿物样品物相含量的快速分析。但是目前缺乏能用于矿物物相组成分析的标准物质,采用与化学成分分析结果进行比较的方法能够在一定程度上佐证方法的准确度,但仍有一定的局限性,因此推广该方法还需要进一步解决方法准确度的验证问题。

  • 图  1   岩溶地区苔藓叶片形态[25]

    A—苔藓幼苗;B1~B3—苔藓叶片;C—叶片的凹陷;D—叶横切面,细胞表面显示疣状结构。

    Figure  1.   Leaf morphology of bryophytes in karst area.

    A—Showing a young plant; B1-B3—Leaves; C—Obviously concaved leaf to reserve more water; D—Portion of leaf transeverse section showing mamilla on cell surface.

    图  2   岩溶植物在高钙环境中的适应机制[46]

    Figure  2.   Adaptation mechanism of karst plants under high calcium stress.Under high calcium stress, karst plants can regulate excessive calcium in two ways: (1) Absorbing excessive calcium through organelles in plants (mitochondria, chloroplasts, vacuoles, etc.); (2) Transferring excess calcium to other parts of plant, such as the cell wall, stoma, gland, epidermal hair, root, etc. Therefore, plants can adapt well to the high calcium environment.

    图  3   AM和ECM型植被根系影响根际土壤养分转运吸收的示意图[62]

    Figure  3.   Schematic diagram of AM and ECM plant roots affecting nutrient transport and absorption in rhizosphere soil. Ectomycorrhizal associations may invest more C in the production of N-acquisition enzymes to adapt to lower N availability and greater N acquisition capacity (relative to AM plants) in the rhizospheres. Arbuscular mycorrhizalassociations may increase rhizosphere soil P availability (relative to bulk soils) by allocating more C to produce P-acquisition enzymes that mineralizing organic P, and by secreting acidic compounds that liberate P from calcium compounds.

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出版历程
  • 收稿日期:  2021-08-08
  • 修回日期:  2022-02-07
  • 录用日期:  2022-04-28
  • 网络出版日期:  2022-12-13
  • 刊出日期:  2023-01-27

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