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大型低剪切波速省(large low shear-wave velocity provinces,LLSVPs)最先由Dziewonski et al.(1977)提出,是指利用地震层析成像技术在非洲与太平洋底部核幔边界处发现的两个大型地震剪切波低速异常区(Garnero et al.,2007; 贺日政等,2010; 黄川,2017)。Burke et al.(2004)发现大火成岩省(large igneous provinces,LIPs)原始喷发位置多位于LLSVPs上部,由此认为大火成岩省可能起源于LLSVPs,但结论也受到较多质疑(Anderson et al.,2005)。Torsvik et al.(2006)发现了深源热点与LLSVPs亦存在空间位置相关性,并指出若以SMEAN模型-1%速度异常等值线作为LLSVPs的边界,大多数LIPs与深源热点均位于-1%等值线±10°范围内,改变了之前认为地幔柱起源于LLSVPs内部的结论,将深源热点与地幔柱和LLSVPs边界联系起来。Burke et al.(2008)将LLSVPs的-1%速度异常边界附近一定范围命名为热柱生成区(plume generation zones,PGZs),认为地幔柱和深源热点从此处产生,并推测LLSVPs位置具有长期稳定性,将非洲底部低速异常区命名为Tuzo,太平洋底部低速异常区命名为Jason。
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之后,LLSVPs和PGZ假说被广泛应用于地幔柱和深源热点的成因研究中(Deschamps et al.,2012; Cottaar et al.,2013; Burke et al.,2014; Torsvik et al.,2014; Tanaka et al.,2015; Huang Chuan et al.,2015,2020; Niu Yaoling,2018,2020; Bono et al.,2019; Thomson et al.,2019; Heyn et al.,2020; Wei Bitian et al.,2020; 李献华,2021; Jackson et al.,2021; Koppers et al.,2021)。但是将一个2800 km深度的地球物理异常与地表热点建立联系,存在诸多不确定性。在层析成像剖面图上,除了少数深源热点能够直接联系LLSVPs和地表特征外,大部分热点并未显示有从地表到核幔边界的连续层析成像异常。换言之,即使空间上相关,两者也未有直接的地球物理证据显示其垂向连通性。此外,LLSVPs边界±10°的缓冲区占地球表面积的32%,即热点与LLSVPs的基础重叠率达32%,不容忽视。因此,热点与LLSVPs的空间重叠性及成因关联性仍有待深入的研究,而空间叠置性是所有假说的前提,需要更多的统计学工作检验(Anderson et al.,2005; Austermann et al.,2014)。Austermann et al.(2014)和Davies et al.(2015)基于蒙特卡洛统计检验认为LIPs与LLSVPs空间相关性不大,且Tuzo和Jason两个区存在明显差别,Tuzo区与热点相关性较好的原因与Tuzo扁长的几何形态有关。本文避繁就简,采用最直接的点与面的空间拓扑关系分析,考虑随机状态下热点落入LLSVPs范围的概率,重新分析了全球热点与LLSVPs区域及边界的空间相关关系,认为二者的相关程度并没有预想的置信度高,对于热点与LLSVPs关系的研究仍有待新的观测技术和资料的补充。
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1 数据来源
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地幔柱活动相关的地表证据包括LIPs、热点及金伯利岩等(Torsvik et al.,2008,2010,2016),而其中的活动热点是最直接的证据,代表了现今地下某一深度的地幔异常,包括温度异常或物质组成异常。LIPs和金伯利岩绝大部分为地质历史时期的产物,需要古地理恢复到其原始喷发位置,才能与相应的深部地幔柱相匹配(Zhao Dapeng,2001)。为避免古地理恢复的不确定性和多解性,仅选取活动热点数据与LLSVPs空间位置进行相关性分析。
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1.1 热点数据来源
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关于全球热点的分布,各统计数据略有差异。Wilson(1973)根据地形、地球化学和重力异常等数据,共识别出全球66个热点; Vogt(1981)在前人研究基础上,重点考虑非洲板块中部非克拉通区域的活动热点,最终数据集共包含117个热点; Steinberger(2000)排除了俯冲带与亚洲区域,热点个数为44; Zhao Dapeng(2007)调查的热点与Steinberger(2000)基本一致,另增加了亚洲区域热点,最终数据集包含60个热点; Torsvik et al.(2006)考虑到研究对象是深部2800 km的LLSVPs,为尽可能减少浅源热点和陆内减压熔融热点对分析结果的干扰,使用Steinberger(2000)数据集,进行热点与LLSVPs空间位置关系分析。本文为了方便与前人研究结果进行对比,选择Steinberger(2000)数据集进行空间叠置性分析,用Zhao Dapeng(2007)的60个热点作对比参照(表1,图1)。
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1.2 LLSVPs模型
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Dziewonski et al.(1977)使用层析成像数据发现在核幔边界处存在大范围的地震波速异常,推测为横向尺度小于5000 km的异常体引起,这应当是LLSVPs概念的雏形(黄川,2017)。后续Dziewonski et al.(1984)和Castillo(1988)的层析成像数据进一步证实了核幔边界大型低速异常区的存在。之后,各种全球层析成像模型不断涌现,如NGRAND、S20RTS、SB4L18等,对地球深部圈层结构进行更准确地约束(Ritsema et al.,1999; Kárason et al.,2000; Ni Sidao et al.,2002; Romanowicz et al.,2002)。
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但由于数据处理方式以及建模方法不同,不同模型的结果存在较大的差异,Becker et al.(2002)将NGRAND、S20RTS和SB4L18模型加权平均获得了综合的SMEAN模型,弱化了各模型间的差异,而汇集了各模型的优点,被后续研究广泛采用。Torsvik et al.(2006)将SMEAN模型的-1%速度等值线视为LLSVPs边界。本文为方便对比,采用SMEAN模型来指示LLSVPs,利用-1%速度等值线作为LLSVPs边界(图1)。
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2 分析方法
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基于全球热点数据和LLSVPs边界的SMEAN模型,利用ArcGIS软件提取SMEAN模型的-1%速度异常为LLSVPs边界,并建立其不同宽度的缓冲区(图1)。前人常选择±10°为LLSVPs边界的缓冲区范围(Torsvik et al.,2006,2010; Burke et al.,2008,2011),为方便对比,本研究重点讨论±10°(约1000 km)的范围的LLSVPs边界与全球热点的空间相关性。另一方面,±10°范围的选择本身并不具有特别的地质意义,因此同时考虑了±2°、±5°、±15°的缓冲区情况。
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通过统计全球热点与缓冲区的空间叠置性,分析热点与LLSVPs边界是否存在空间相关性。落入缓冲区的热点数占全部热点数的比例为“重叠率”,当重叠率>60%时,认为可能存在相关性,而反之则排除两者的相关性。但LLSVPs是全球尺度的地幔异常体,两个 LLSVPs±10°缓冲区的地表投影面积之和约1.62×108 km2,约占据全球表面积的32%。即在随机条件下,32%的热点也可能会出现在缓冲区内。考虑热点与缓冲区的空间相关性强度时,需要充分考虑随机条件下的基础重叠率(LLSVPs缓冲区面积与地球表面积的比值)。去除基础重叠率的影响,可以使用“叠置指数”来评估二者的相关性公式(1)。
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注:数据来源1表示来自Steinberger(2000),2表示来自Zhao Dapeng(2007),1/2表示共有; 粗体表示深源热点; 热点与LLSVPs最短距离为热点与低速异常区-1%速度等值线(映射到地表)的欧式距离,即地表最短直线距离。
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图1 全球热点与LLSVPs空间位置分布图
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Fig.1 The locations of the global hotpots and LLSVPs
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黑色粗曲线指示SMEAN模型-1%速度异常等值线(LLSVPs边界),灰色阴影区域指示±10°缓冲区范围,灰色圆点表示Zhao Dapeng(2007)热点数据,白色十字指示Steinberger(2000)热点数据,投影方式为Mollweide
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The thick black line indicates the-1% contour of velocity anomaly of SMEAN model, i.e. the margins of LLSVPs; the shaded grey area indicates the ±10° buffer zones of the LLSVPs' margin; the grey dots show the location of hotspots from Zhao Dapeng
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叠置指数值越大,表明扣除基础重叠率外,依然有较多热点与缓冲区重叠,热点与LLSVPs空间相关性较强。反之,则空间相关性不明显。对于±10°缓冲区,若叠置指数大于0.32,即热点与缓冲区的实际重叠率达到基础重叠率的两倍,表明两者的空间相关性较强。
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此外,针对热点起源深度的不同,在分析全球热点的基础上,着重分析了深源热点与LLSVPs的空间叠置情况。同时,对太平洋和非洲两个LLSVPs分区Jason和Tuzo分别进行了空间叠置分析。
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3 结果
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3.1 热点与LLSVPs边界空间相关性
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基于Steinberger热点数据,24个热点位于LLSVPs边界±10°缓冲区内,重叠率为55%,叠置指数0.23(表2),重叠率和叠置指数均小于预期(>60%,>0.32),因此相关性强度一般。基于Zhao热点数据的统计结果与此类似。
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若以LLSVPs边界±2°、±5°为缓冲区,重叠率在18%~35%,明显小于60%,相关性较差。以±15°为缓冲区时,重叠率虽然均大于60%,但移除基础概率44%后,叠置指数为0.21~0.26,明显小于预期,与随机分布相差不大(图2)。
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注:±2°、±5°、±10°、±15°缓冲区的基础重叠率分别为7%,17%,32%,44%。
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图2 全球热点与LLSVPs边界的重叠率及叠置指数
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Fig.2 Spatial correlation between global hotpots and the different buffer zones of LLSVPs' margin
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虚线为各缓冲区基础重叠率
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The dashed line is the basic overlapping rate of each buffer zone
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3.2 深源热点与LLSVPs空间位置相关性
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Steinberger深源热点共有11个(图3),其中8个位于LLSVPs边界±10°缓冲区内部,重叠率为73%,叠置指数0.41(表3),重叠率和叠置指数均较好(>60%,>0.32),相关性较强。但作为对照组的Zhao深源热点,重叠率仅为43%,叠置性指数为0.11,二者相关性较弱(表3)。这可能与两者对深源热点的判别标准不同有关。
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若以LLSVPs边界±2°、±5°和±15°为缓冲区,移除基础重叠率后,Steinberger热点的叠置指数在0.29~0.41之间,而Zhao热点仅为0.11~0.22之间,两者差异明显(图4)。因此深源热点与LLSVPs的相关性也存在很大争议。
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3.3 Jason和Tuzo分区与热点的空间相关性
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LLSVPs的两个分区Jason和Tuzo与邻近的热点具有明显不同的空间叠置关系。Jason边界的±10°缓冲区内部,热点重叠率仅为27%~33%,叠置指数-0.05~0.01(表4)。其他±2°、±5°、±15°缓冲区的情形相似,表明热点与Jason分区不具有空间相关性。深源热点的重叠率略有提升,但仍然低于预期,不能指示两者的相关性。
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图3 深源热点与LLSVPs边界±10°缓冲区关系图
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Fig.3 The spatial correlation of the deep origin hotpots and±10° buffer zone of LLSVPs' margin
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红色实线为LLSVPs边界,灰色区域为缓冲区范围,黄色十字图标表示Steinberger(2000)深源热点位置,绿色圆形图标表示Zhao Dapeng(2007)深源热点位置; 字母缩写表示热点名称,详见表1; 底图为表1全部热点密度图,红色为热点高密度区,蓝色为低密度区
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The red line indicates the LLSVPs' margin. Thegrey area indicates the buffer zones of the margin. The yellow crosses indicate the location of deep origin hotspots from Steinberger (2000) , while the green circles indicate those from Zhao Dapeng (2007) ; the abbreviations for the hotspots can be found in Table1; the background is the density map of global hotspots, in which the red indicates the high density, and the blue is low
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图4 深源热点与LLSVPs边界的重叠率及叠置指数
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Fig.4 Spatial correlation between deep origin hotpots and the different buffer zones of LLSVPs' margin
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虚线为各缓冲区基础重叠率
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The dashed line is the basic overlapping rate of each buffer zone
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注:Jason、Tuzo分区分布于两个半球,面积基本相等,其±2°、±5°、±10°、±15°缓冲区的基础重叠率与全球LLSVPs相当,分别近似为7%,17%,32%,44%。下同。
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Tuzo边界的±10°缓冲区内部,热点重叠率为71%~74%,叠置指数0.39~0.42(表5)。若缓冲区扩大到±15°,则重叠率更高。不同缓冲区情况下,重叠效率均明显好于Jason分区,表明热点与Tuzo分区具有良好的空间相关性。深源热点与Tuzo的空间相关性同样显著(表5)。
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4 讨论
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4.1 热点与LLSVPs的空间关系
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研究结果表明,热点与LLSVPs的空间位置相关性存在诸多不确定性。根据已有的热点数据,其与LLSVPs边界的空间相关性明显小于预期,重叠率不足60%,若考虑随机条件下的基础重叠率,两者的相关性更弱。深源热点总体上相关性略有提升,但仍然不及预期,并且对深源热点本身的定义和判别存在很大分歧。因此,简单的认为全球热点分布与LLSVPs空间相关的观点值得质疑。
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Jason和Tuzo作为LLSVPs的两个分区,与邻近热点具有明显不同的空间叠置关系。Jason边界与热点不具有空间相关性,而Tuzo分区与热点相关性较强。Burke et al.(2004)认为太平洋板块的高速移动使部分LIP受到破坏,造成了Jason与LIPs之间空间相关性较弱。Davies et al.(2015)通过蒙特卡洛模拟发现,热点和LIPs与Jason并不具有空间相关性,而与Tuzo相关性较好。因此在进行LLSVPs相关研究中,应将Tuzo和Jason区别对待。
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4.2 LLSVPs边界选择的不确定性
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目前较公认的LLSVPs范围是基于SMEAN层析成像模型,选择-1%速度异常等值线为边界(Burke et al.,2004; Torsvik et al.,2006)。而SMEAN模型是通过对NGRAND,S20RTS和SB4L18三种全球层析成像模型的加权平均而得出(Becker et al.,2002)。虽然加权计算突出了深部地幔的异常特征,但同时忽略了各模型间的细节差异,并且模糊了模型的地质意义。
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Torsvik et al.(2006)根据速度异常变化率,选择-1%速度异常值作为LLSVPs边界,有一定的合理性,但-1%速度异常等值线与变化率极值并非完全对应。并且SMEAN模型的-1%速度异常本身所指征的地质意义仍有待一步研究。
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此外,在评判LLSVPs与热点空间关系时,其相关性强度与边界的缓冲区宽度有关。缓冲区宽度大,占据面积大,落入的热点数增多,则相关性较高; 而宽度缩小,则相关性减弱。因此,缓冲区宽度的选择对热点与LLSVPs相关性强度起了决定作用,降低了两者之间本身的统计意义。简单地讨论热点与某一特定宽度LLSVPs边界的相关性,不能让人信服,需要明确LLSVPs边界宽度的选择依据及地质意义。
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4.3 深部异常与地表响应
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LLSVPs是地震层析成像揭示的核幔边界大型低速异常区,位于2800 km深度,而热点和LIPs是地幔柱在地表的岩浆表现。将一个深度2800 km的地球物理异常与地表热点建立联系,本身存在诸多不确定性。
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理论上,如果所有地幔柱起源于核幔边界,则热点与LLSVPs存在相关性的概率将增大。但事实上,很多热点并未显示有从核幔边界到地表的连续层析成像异常(Zhao Dapeng,2007; He Yumei et al.,2009)。这为讨论热点与LLSVPs的相关性提出了挑战。
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另一方面,即使空间位置上存在一定的相关性,如Tuzo分区及其附近的热点,但仍缺少证据支持两者之间的成因联系。需要借助更多的深部观测数据和地表探查资料,来证实地表与深部的直接联系。
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5 结论
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在考虑随机状态热点落入LLSVPs范围的基础概率后,重新判断全球热点与LLSVPs边界的空间关联性及置信度。结果显示,热点与LLSVPs边界的空间相关性强度一般,Tuzo和Jason之间存在较大差异,Jason与热点缺乏空间位置相关性,而Tuzo与热点空间相关性较强。总体上,热点的分布与LLSVPs之间的相关性远不及预期,两者之间的相关性问题并未得到充分的论证。因此,在具体的热点和地幔柱成因研究中,不能盲目认为热点与LLSVPs有关,而需要更加审慎的关注地质事实本身。另外,SMEAN-1%速度异常的地质意义以及如何联系深度2800 km的地球物理异常与地表热点等问题,仍有待进一步研究。
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致谢:感谢中国科学院海洋研究所张国良老师、广州地球化学研究所杨阳老师在地球系统科学会议上给予的相关问题的讨论和建议,感谢评审专家对本文提出的宝贵修改意见。
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摘要
地震层析成像显示在非洲和太平洋之下的核幔边界处(~2800 km)存在两个大型低剪切波速省(LLSVPs),分别被命名为Tuzo和Jason,指示温度或成分的异常。前人通过研究发现,大火成岩省喷发的古位置以及现今活动热点位置多位于LLSVPs边界±10°附近。由此,基于空间相关性,将LLSVPs狭窄的边界视为地幔热柱生成区,广泛用于解释地幔柱与热点的成因。但是,将一个深度2800 km的地球物理异常与地表热点建立联系,仍存在诸多不确定性。而且LLSVPs作为全球尺度的异常区,在地表的映射范围巨大,不可避免地与大量热点存在天然的空间叠置性,这种空间关联的程度以及是否具有成因联系仍然未知。本文考虑随机状态下热点落入LLSVPs范围的概率,对全球热点与LLSVPs边界重新进行空间分析,判断两者之间的空间叠置性。统计结果显示,全球热点与LLSVPs边界的空间相关性不及预期,Tuzo和Jason之间存在较大差异,Jason与热点缺乏空间位置相关性,而Tuzo与热点空间相关性较强。热点的分布与成因可能并不完全受控于LLSVPs。研究结果对普遍认为的LLSVPs与热点分布之间的强相关性提出质疑,在具体的热点和地幔柱成因研究中,不能盲目认为热点与LLSVPs有关,而需要更加审慎的关注地质事实本身。
Abstract
Seismic tomographic images show that there are two large low shear-wave velocity provinces (LLSVPs) beneath Africa and Pacific Ocean at the Earth's core-mantle boundary, named Tuzo and Jason, respectively. It implies the anomalies in temperature or composition of the deep mantle. Previous studies have found that the reconstructed eruption sites of large igneous provinces and current active hotspots are mostly located near the LLSVPs margins with a tolerance of ±10°. Based on spatial correlations the narrow margins of LLSVPs are regarded as the mantle plume generation zone and is widely used to explain the genesis of mantle plumes and hotspots. However, there are still many uncertainties in connecting the surface hotspots to a deep geophysical anomaly 2800 km beneath. Moreover, LLSVPs, as a global-scale anomalies, are huge in extent if projected on the Earth's surface, and will inevitably be overlapping with a large number of hotspots. Whether the two components are genetically connected remains unknown. Here, we consider the random probability of a hotspot falling into the LLSVPs ranges, and reanalyze the spatial correlation between LLSVPs' margins and global hotpots to determine the confidence level of the potential correlation. The statistical results show that the spatial correlation between global hotspots and LLSVPs' margins is not significant as proposed. There are great differences between Tuzo and Jason in their relationships to the hotspots. The Tuzo is considered well correlated with hotspots, while the Jason don't. Thus, the distribution and genesis of hotspots may not be fully controlled by LLSVPs. The result challenges the generally accepted strong correlation between LLSVPs and hotspots. We should not take it for granted that hot spots are related to LLSVPs, but should be more careful in study of the genesis of hot spots and mantle plumes, with more attention to the geological facts and observations.
Keywords
LLSVPs ; global hotpots ; plume generation zones ; mantle plume ; spatial correlation