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主管单位:中国地质调查局

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中国地质学会

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    鄂东南铁铜金钨钼多金属矿集区基底属性:来自继承锆石年龄和Hf同位素的约束

    谢应波, 褚刚, 罗华, 郭盼

    谢应波,褚刚,罗华,等. 鄂东南铁铜金钨钼多金属矿集区基底属性:来自继承锆石年龄和Hf同位素的约束[J]. 西北地质,2024,57(5):283−297. doi: 10.12401/j.nwg.2024059
    引用本文: 谢应波,褚刚,罗华,等. 鄂东南铁铜金钨钼多金属矿集区基底属性:来自继承锆石年龄和Hf同位素的约束[J]. 西北地质,2024,57(5):283−297. doi: 10.12401/j.nwg.2024059
    XIE Yingbo,CHU Gang,LUO Hua,et al. Basemental Attribution of the Fe-Cu-Au-W-Mo Polymetallic Ore Cluster in the Southeastern Hubei: Constraint from the Ages and Hf Isotopes of the Inherited Zircons[J]. Northwestern Geology,2024,57(5):283−297. doi: 10.12401/j.nwg.2024059
    Citation: XIE Yingbo,CHU Gang,LUO Hua,et al. Basemental Attribution of the Fe-Cu-Au-W-Mo Polymetallic Ore Cluster in the Southeastern Hubei: Constraint from the Ages and Hf Isotopes of the Inherited Zircons[J]. Northwestern Geology,2024,57(5):283−297. doi: 10.12401/j.nwg.2024059

    鄂东南铁铜金钨钼多金属矿集区基底属性:来自继承锆石年龄和Hf同位素的约束

    基金项目: 湖北省地质局2022年矿产地质调查项目“鄂东南矿集区1∶10万构造建造填图”(KCDZ2022-14)资助
    详细信息
      作者简介:

      谢应波(1979−),男,本科,主要从事区域矿产地质调查与研究。E−mail:513334884@qq.com

      通讯作者:

      罗华(1987−),男,硕士研究生,主要从事区域矿产地质调查与研究。E−mail:270132397@qq.com

    • 中图分类号: P596

    Basemental Attribution of the Fe-Cu-Au-W-Mo Polymetallic Ore Cluster in the Southeastern Hubei: Constraint from the Ages and Hf Isotopes of the Inherited Zircons

    • 摘要:

      长江中下游成矿带鄂东南矿集区的基底存在统一的川中式基底和北部川中式基底、南部江南式基底的争议。笔者对灵乡岩体西段闪长玢岩开展锆石U-Pb定年和Hf同位素分析,结果显示闪长玢岩的锆石具有复杂的组成与来源:最年轻的4颗锆石加权平均年龄为(141±4) Ma,结合前人测年结果推测其可作为闪长玢岩的成岩年龄;其余16颗锆石具有较为宽泛的年龄(217~2550 Ma)和Hf同位素组成(εHf(t) = −11.2~11.7)。进一步结合前人获得的鄂东南矿集区岩浆岩继承锆石数据,分别对比川中式基底崆岭杂岩、江南式基底梵净山群及下江群的锆石数据,发现其与崆岭杂岩具有明显差异,但和梵净山群及下江群具有高度相似性。并且鄂东南矿集区岩浆岩继承锆石和梵净山群、下江群均记录了~1.5 Ga地壳增生事件。结合区域地球物理特征,笔者认为鄂东南矿集区南部为江南式基底,北部为川中式基底,两者的分界线大致为灵乡-大冶-网湖一线。

      Abstract:

      There are two different opinions about the basemental attribution of the ore cluster in the southeastern Hubei Province, Middle-Lower Yangtze Metallogenic Belt that all attributed to the Chuanzhong-type basement or the north part related to Chuanzhong-type basement and the south part classified to the Jiangnan-type basement. In this study, zircon U-Pb dating and Hf isotope analysis were conducted for diorite porphyrite in the western Lingxiang pluton. The results indicate that the zircons of diorite porphyrite show complex compositions and sources. The youngest four zircons yield a mean 206Pb/238U age of (141±4)Ma, which coincide with previous researches and interpreted as the crystallization age of the diorite porphyrite. In addition, The other 16 older zircons have varied ages (217~2 550 Ma) and Hf isotopic compositions (εHf(t) = −11.2~11.7). Combined with the reported ages and εHf(t) values of inherited igneous zircons from the ore cluster in the southeastern Hubei, we compared with the data from Chuanzhong-type and Jiangnan-type basements respectively. The results suggest that they are different from Kongling Complex of the Chuanzhong-type basement, but are similar to the Fanjingshan and XiaJiang Groups of the Jiangnan-type basements. Particularly, the ~1.5 Ga crustal accretion both record in the ore cluster in the southeastern Hubei and the Fanjingshan and XiaJiang Groups. Combined with the regional geophysics, bounded by the line from Lingxiang, Daye to Wanghu Lake, the north part of ore cluster in the southeastern Hubei belong to Chuanzhong-type basement and the south part relate to Jiangnan-type basement.

    • 植被是陆地生态系统的重要组成部分,在地表能量交换、水平衡和生物循环等方面发挥重要作用。植被对温度、降水等气候因子尤为敏感,被称为气候变化“指示器”,是研究生态系统脆弱程度和全球变化的重要内容(李晓兵等,2000;马明国等,2006)。归一化植被指数(Normalized Difference Vegetation Index,NDVI)能够较好地反映植被覆盖度和长势,被广泛应用于不同时空尺度的植被生长监测中,用于探讨植被与气候因子之间的关系(朴世龙等,2001杨元合等,2006尤南山等,2019杜臻等,2023黄煜等,2023王化齐等,2023)。

      陈云浩等(2001)根据中国植被覆盖与气候因子驱动的区域分异规律,将植被区共划分4个一级区、6个二级区和14个三级区。Wardlow等(2008)研究了美国中部大平原密集种植区植被覆盖与环境条件之间的关系,为农业管理提供科学支持。崔林丽等(2010)分析了中国东部NDVI与气温和降水的响应特征,表明植被NDVI与气温和降水的最大相关系数在中国东部由北向南逐渐减小。袁丽华等(2013)分析黄河流域NDVI时空变化趋势和Hurst指数特征,研究植被覆盖变化的可持续特征。武正丽等(2015)基于MODIS NDVI等数据研究了祁连山地区植被覆盖变化与气候因子的响应关系。孟丹等(2015)通过分析2001~2013年间京津冀地区NDVI数据与降水、气温资料之间的相关关系,表明该区域植被覆盖变化主要受非气候因子驱动,面积占比为89.63%。徐嘉昕等(2020)分析了三江源区17年来NDVI时空分布特征及其与气温和降水之间的关系,表明植被生长季初期气温对NDVI变化的影响大于降水量,但在生长季中期,降水量对部分类型植被的生长影响较大。

      大凌河流域属辽西生态环境脆弱区,流域内山高谷深、地形复杂,受人为与自然因素影响,石漠化、水土流失等问题突出。生态系统稳定直接关系着辽西的经济发展和沿河居民生活(邸志强等,2007王炜航等,2010),前人对该区植被覆盖与气候之间的关系研究较少,且数据陈旧。鉴于此,笔者以大凌河流域为研究区,基于GIS等平台分析最近20年间流域NDVI的时空演变特征,研究了植被变化与降水和温度等气候条件之间的响应关系,为流域生态环境保护与修复提供了科学依据(强建华等,2021王鹏等,2021)。

      大凌河全长为435 km,上游分南、北两支,于喀左县大城子东南汇合后,流经朝阳、北漂、凌海、义县等地,最终汇入渤海。大凌河流域地理范围为:E 118°53'~121°52' 、N 40°28'~42°38' ,流域总面积为2.33×104 km2图1)。该流域地貌类型以山地丘陵为主,少量平原区;气候类型属于中温带气候,四季冷暖干湿分明,温度变化较大。该流域多年平均气温为8.3 ℃,平均相对湿度为53%,日照时数为2800 h,年均降雨量为465 mm,年蒸发量为1974.4 mm,年均径流量为1.79×109 m3

      图  1  大凌河流域地理位置图
      Figure  1.  Geographical location map of Daling river basin

      NDVI数据来自中国科学院资源环境科学数据中心发布的中国月度植被指数(NDVI)空间分布数据集(http://www.resdc.cn/DOI),该数据是基于连续时间序列的SPOT/VEGETATION NDVI卫星遥感数据,采用最大值合成法生成的。数据获取时间为1998~2019年,数据格式为ARCGIS GRID格式,空间分辨率为1 km。

      气象数据来源于中国气象数据网(https://data.cma.cn/)。研究区内共有建昌站、喀左站、凌源站、建平站、朝阳站、北票站、阜新站、义县站和凌海站等9个国家气象站点,选取各气象站点1998~2019年每日降水和气温数据,采用平滑样条函数进行插值生成1 km分辨率栅格数据。本研究中地理数据处理与分析采用ArcGIS和Anusplin等软件完成。

      最大值合成法(MaximumValue Composites,MVC)是国际通用的NDVI数据统计方法。通过最大值合成法可以消除大气污染、云、太阳高度角等因素的干扰(陈云浩等,2001王强等,2017)。本研究选取了大凌河流域1998~2019年期间每年3~11月的NDVI值,取每月2期数据的平均值为该月植被指数数据,再通过最大值合成法,提取每个像元的最大值为该年NDVI值,计算公式为:

      $$ {NDVI}_{i}=Max({NDVI}_{ij}) $$ (1)

      式中:NDVIi表示第i年的NDVI值;i取值1~22,分别代表1998~2019年;NDVIij表示第i年第j月的NDVI值;j取值1~9,分别代表3~11月。

      变异系数(Coefficient of Variance,CV),又称为标准离差率或单位风险,是衡量资料中各观测值变异程度的一个统计量,计算公式为:

      $$ CV=\frac{\delta }{\mu }\times 100\text{%}$$ (2)

      式中:$ \delta $为样本标准差,$ \mu $为样本的平均值。

      为反映植被变化的年际和年内特征,采用生长季(3~11月)、春季(3~5月)、夏季(6~8月)和秋季(9~11月)NDVI合成值来表征植被生长,各季节分别为时段内各月份NDVI的平均值。笔者基于像元尺度,计算NDVI与年份的一元线性回归斜率slop(式3)。若slop>0表示NDVI呈增加趋势,slop<0则表示NDVI呈减少趋势。结合回归系数的显著性水平(p值),将研究区NDVI年际变化情况划分为6个类型:极显著降低(p<0.01,slop<0)、显著降低(0.01<p<0.05,slop<0)、不显著降低(p>0.05,slop<0)、不显著增加(p>0.05,slop>0)、显著增加(0.01<p<0.05,slop>0)和极显著增加(p>0.01,slop>0)(尤南山等,2019张新悦等,2021)。

      slop计算公式为:

      $$ slope=\frac{n* \displaystyle \sum\nolimits _{i=1}^{n}i*{NDVI}_{i}- \displaystyle \sum\nolimits _{i=1}^{n}i \displaystyle \sum\nolimits _{i=1}^{n}{NDVI}_{i}}{n* \displaystyle \sum\nolimits _{i=1}^{n}{i}^{2}-{\left( \displaystyle \sum\nolimits _{i=1}^{n}i\right)}^{2}} $$ (3)

      式中:n为监测时间段的年数22,NDVIi表示第i年的植被指数。

      偏相关分析是在消除其他变量影响的前提下计算某两个变量之间的相关性,笔者利用基于像元的偏相关分析法分别研究了气温和降水量对植被NDVI变化的贡献程度,计算公式如下:

      $$ {R}_{xy,z}=\frac{{R}_{xy}-{R}_{xz}{R}_{yz}}{\sqrt{(1-{R}_{xz}^{2})}\sqrt{(1-{R}_{yz}^{2})}} $$ (4)

      式中:Rxyz为自变量z固定后因变量x与自变量y的偏相关系数。RxyRxzRyz分别为变量xy、变量xz、变量yz的皮尔逊相关系数。若Rxy,z>0,表示正相关;若Rxy,z<0,则表示负相关。偏相关系数越大,说明二者相关性越强。偏相关系数的显著性检验采用t检验法完成。

      偏相关系数的显著性检验采用t检验法完成,计算公式如下:

      $$ t=\frac{{R}_{xy,z}}{\sqrt{1-{R}_{zy,z}^{2}}}\sqrt{n-m-1} $$ (5)

      式中:n为样本数(时间序列1998~2019,即n=22),m为自变量的数量。

      复相关分析可研究一个变量与多个变量之间的相关程度,复相关的显著性检验可采用F检验法。复相关系数计算公式如下:

      $$ {R}_{x,yz}=\sqrt{1-(1-{R}_{xy}^{2})(1-{R}_{xz,y}^{2})} $$ (6)

      复相关的显著性检验可采用F检验法,计算公式如下:

      $$ F=\frac{{R}_{x,yz}^{2}}{1-{R}_{x,yz}^{2}}\times \frac{n-k-1}{k} $$ (7)

      式中:n为时间序列年份数,k为自变量的数量。

      从区域尺度看,1998~2019年间大凌河流域多年平均NDVI值为0.49,总体呈显著上升趋势(R2=0.48,p<0.01),其NDVI值从1998年的平均0.49增至 2019 年以来的0.52,年平均增长量为0.0014(图2)。

      图  2  1998~2019年大凌河流域生长季NDVI值变化趋势图
      Figure  2.  NDVI variation trend during the growing season of Daling river basin from 1998 to 2019

      按照不同季节来看,1998~2019年间大凌河流域在春季、夏季、秋季的NDVI均值分别为0.362、0.739和0.642,整体呈缓慢增长趋势。其中,夏季NDVI增长率最大,为0.0059;秋季(0.0041)次之,春季(0.0034)最小。春季变异系数最大(0.135),其次为夏季(0.065),秋季最小(0.090),说明春季植被覆盖的波动性最明显(图3)。

      图  3  1998~2019年大凌河流域NDVI值按季节变化趋势图
      Figure  3.  Seasonal variation trend of NDVI in Daling river basin from 1998 to 2019

      1998~2019年间,大凌河流域逐像元NDVI值在不同季节的变化趋势见图4图5

      图  4  大凌河流域1998~2019年逐像元NDVI值变化趋势图
      a.春季;b.夏季;c.秋季;d.生长季
      Figure  4.  NDVI variation trend per pixel in Daling river basin from 1998 to 2019
      图  5  大凌河流域1998~2019年逐像元NDVI值变化趋势的显著性图
      a.春季;b.夏季;c.秋季;d.生长季
      Figure  5.  Significance of NDVI trend per pixel in Daling river basin from 1998 to 2019

      大凌河流域22年来生长季92.8%的区域NDVI值呈正增长,其中,增长率大于0.005的面积占总面积的46.8%,主要分布于大凌河中上游。NDVI值增长率位于0.003~0.005、0.001~0.003两个区间的面积比例分别为23.7%、16.3%,主要分布于阜新市以南至锦州市一带,朝阳县、建平县和建昌县有零星分布。此外,阜新市东北部、锦州市南部、朝阳市西部等地,NDVI呈现局部斑块状缓慢负增长,增长率绝对值<0.001(图4表1)。从NDVI变化显著性来看,生长季NDVI以增加趋势为主,面积占比90.8%。其中,不显著增加区域占比为71.2%,主要分布于大凌河流域中上游地区,极显著增加和显著增加区域分别占18.0%和1.6%,主要分布于大凌河中下游的朝阳市、锦州市和阜新市等地(图5表2)。

      表  1  大凌河流域1998~2019年间NDVI变化趋势表
      Table  1.  NDVI variation trend in Daling river basin from 1998 to 2019
      变化率春季(%)夏季(%)秋季(%)生长季(%)
      <−0.00118.54.26.24.8
      −0.001~06.41.22.82.6
      0~0.0018.12.85.45.8
      0.001~0.00314.36.216.016.3
      0.003~0.00514.815.425.023.7
      >0.00537.970.344.746.8
      下载: 导出CSV 
      | 显示表格
      表  2  大凌河流域1998~2019年间NDVI变化的显著性表
      Table  2.  Significance of NDVI change in Daling rver basin from 1998 to 2019
      变化显著性春季(%)夏季(%)秋季(%)生长季(%)
      极显著降低18.23.16.64.3
      显著降低3.30.70.80.1
      不显著降低4.12.12.14.8
      不显著增加33.376.931.071.2
      显著增加12.67.519.31.6
      极显著增加28.69.840.218.0
      下载: 导出CSV 
      | 显示表格

      不同季节,NDVI变化规律存在一定差异。从NDVI增长率来看,不同季节超过六成的区域NDVI变化率大于0.001,尤其是夏季,这一比例为91.9%。另有部分区域NDVI呈缓慢负增长,春季负增长区最大,占总面积24.9%,秋季占比9.0%,夏季最小(占比5.4%)(图4表1)。从NDVI变化的显著性来看,秋季极显著增加区面积占比达40.2%,为所有季节中最高,主要分布于朝阳市东北部、阜新—锦州一带。春季极显著增加区面积占比28.6%,最低的是夏季,这一比例为9.8%。显著增加区,秋季面积最大,占比为19.3%。极显著降低区中,比例最大的是春季,为18.2%,主要集中分布在大凌河下游阜新–锦州一带,建平、喀左等局部有零星分布(图5表2)。

      对大凌河流域22年来生长季NDVI与年降水和平均气温进行偏相关性分析(图6图7)。结果显示,生长季NDVI与气温和降水的评价偏相关系数,分别为−0.24、0.32,表明年际变化水平上,大凌河流域NDVI与气温呈负相关、与降水量呈正相关,且NDVI与年降水量关系更密切。研究区域内NDVI与平均气温呈正、负相关的区域分别占总区域的5.40%、94.60%,对偏相关系数进行显著性检验,可知0.02%的区域通过p<0.01的显著性检验,主要分布在大凌河口。研究区域内NDVI与降水量呈正、负相关的区域,分别占总区域的97.36%、2.64%,其中通过p<0.01显著性检验区域比例为4.40%,主要分布于阜新–义县一带,朝阳和建平等地有零星分布。

      图  6  大凌河流域生长季NDVI与气温的偏相关关系图
      Figure  6.  Partial correlation between NDVI and air temperature in the growing season of Daling river basin
      图  7  大凌河流域生长季NDVI与降水量的偏相关关系图
      Figure  7.  Partial correlation between NDVI and precipitation in the growing season of Daling river basin

      大凌河流域生长季NDVI与气温、降水复相关系数为0~0.90(图8),平均复相关系数为0.38,高值主要集中在阜新县—义县一带,以及朝阳县和建平县部分区域,低值区分布较广,主要分布于大凌河中上游。根据表3确立的分区规则(王强等,2017),统计大凌河流域降水驱动型区域占比为4.33%,主要分布在阜新县、朝阳市等地区,还有部分零星分布在建平县和义县;气温驱动型区域所占面积比为0.03%,主要分布锦州市大凌河入海口;降水、气温共同驱动区域占总面积的2.73%,主要分布在阜新市周边,其他县市均有零星分布。

      图  8  生长季NDVI气温、降水量的复相关系数(a)与不同驱动因子分区图(b)
      a.偏相关系数;b.不同驱动因子分区
      Figure  8.  (a) Multiple correlation coefficients between NDVI and temperature and (b) precipitation and partitioning of different driving factors in growing season
      表  3  大凌河流域植被覆盖驱动分区规则表
      Table  3.  Vegetation cover driving zoning criteria in the Daling river basin
      NDVI变化类型分区准则面积占比(%)
      rNDVI P,TrNDVI T,PRNDVI,TP
      降水驱动型tt0.01FF0.054.33
      气温驱动型tt0.01FF0.050.03
      气温、降水驱动型tt0.01tt0.01FF0.052.73
      其他因子驱动型FF0.0592.91
       注:表中rNDVIP,T、rNDVIT,P分别为NDVI与降水、气温的偏相关系数,RNDVI,TP则表示NDVI与气温和降水的复相关系数,tF分别为t、F检验的统计量,t0.01表示t检验的0.01显著性水平,F0.05表示F检验的0.05显著性水平。
      下载: 导出CSV 
      | 显示表格

      (1)1998~2019年,大凌河流域NDVI整体呈增加趋势,说明植被覆盖整体变好。不同季节变化趋势各异,夏季NDVI增长率最高,秋季次之,春季增长率最低,且波动最明显。

      (2)大凌河流域植被覆盖空间上呈现不同特征,中上游NDVI增长率较大,变化显著性以不显著为主,说明呈缓慢稳定增长规律。下游地区NDVI增长率整体较小,但变化显著性方面存在多种情况,特别是极显著增加和极显著降低区相邻共存。究其原因,大凌河流域上游以丘陵山区为主,自然资源开发程度较低;下游地区由于人类活动更频繁,对植被的破坏和修复同时进行,造成更复杂的植被覆盖变化规律。

      (3)大凌河流域NDVI总体与平均气温呈负相关、与降水量呈正相关,且NDVI与年降水量关系更密切。区内94.60%的区域NDVI与平均气温呈负相关,其中通过显著性检验(p<0.01)的比例为0.02%,主要分布于大凌河口。区内97.36%的区域NDVI与降水量呈正相关的区域,占总区域的,通过p<0.01显著性检验区域比例为4.40%,主要分布于阜新—义县一带。

      (4)根据前人研究中气候因子驱动评价模型,大凌河流域植被覆盖降水驱动型区域占比为4.33%,主要分布在阜新县、朝阳市等地区;气温驱动型所占面积比为0.03%,主要分布锦州市大凌河入海口;降水、气温共同驱动区域占总面积的2.73%,主要分布在阜新市周边。

    • 图  1   扬子板块前寒武基底露头空间分布

      Figure  1.   Geologic map showing the distribution of Precambrian rocks in the Yangtze Plate

      图  2   鄂东南地区岩浆岩和矿床分布简图(据Li et al., 2014a修改)

      Figure  2.   Distribution of igneous rocks and mineral deposits in southeastern Hubei Province

      图  3   灵乡岩体闪长玢岩野外(a)和镜下(b,正交光)照片

      Figure  3.   (a)The photographs of field and (b) microscope (under transmitted plane-polarized light) of the dioritic porphyrite from the Lingxiang pluton

      图  4   灵乡岩体闪长玢岩锆石CL图像(内圈代表年龄分析点,外圈代表Hf同位素分析点)

      Figure  4.   Zircon CL images of the Lingxiang diorite porphyrite (The outer circle represents the age analysis and the inner circle represents the Hf isotope analysis)

      图  5   灵乡岩体闪长玢岩锆石U-Pb年龄谐和曲线图

      Figure  5.   Zircon U-Pb age concordia diagram of the Lingxiang diorite porphyrite

      图  6   鄂东南矿集区继承锆石Th/U值

      Figure  6.   Th/U ratios for the inherited zircons from the Southeastern Hubei Province ore deposit cluster

      图  7   鄂东南矿集区继承锆石(a)与梵净山群和下江群碎屑锆石年龄统计直方图(b)

      Figure  7.   (a) Statistical histograms of inherited zircons from the southeastern Hubei Province ore deposit cluster and (b) detrital zircons from the Fanjingshan and Xiajiang Groups

      图  8   鄂东南矿集区继承锆石Hf同位素组成及其与江南造山带西段基底碎屑锆石和崆岭杂岩锆石Hf同位素对比

      图中黑色数据点均为鄂东南矿集区继承锆石数据,数据来源见表3;江南造山带西段基底碎屑锆石数据引自Wang et al.,(2010);崆岭杂岩数据范围据邱啸风等 (2014)、Li等(2014b)Guo等(2015);鄂东南地区晚中生代侵入岩范围据Xie等(2011a)

      Figure  8.   Inheritance zircon Hf isotopic composition in the southeastern Hubei mineral district and its comparison with the Hf isotopic compositions of detrital zircons from the western segment of the Jiangnan Orogen and zircons from the Kongling Complex

      表  1   灵乡闪长玢岩锆石年龄数据

      Table  1   Zircon U-Pb age data of Lingxiang dioritic porphyrite

      分析点 Th
      (10−6
      U
      (10−6
      Th/U 同位素比值 年龄(Ma) 误差
      (%)
      207Pb/206Pb 207Pb/235U 206Pb/238U 207Pb/206Pb 207Pb/235U 206Pb/238U
      D020-3-1-01 47 32 1.5 0.1105 0.0052 5.1151 0.2333 0.3364 0.0070 1807 86.4 1839 38.8 1869 33.7 103
      D020-3-1-02 56 44 1.3 0.1017 0.0055 4.2227 0.2309 0.2991 0.0059 1655 101.1 1678 44.9 1687 29.3 102
      D020-3-1-03 1014 599 1.7 0.0949 0.0032 3.0391 0.0968 0.2297 0.0026 1528 62.7 1417 24.3 1333 13.7 87
      D020-3-1-04 250 287 0.9 0.1590 0.0048 9.2537 0.2654 0.4182 0.0048 2445 50.8 2363 26.3 2252 21.9 92
      D020-3-1-06 200 220 0.9 0.0545 0.0062 0.1602 0.0152 0.0219 0.0007 391 252.7 151 13.3 140 4.6 93
      D020-3-1-07 230 184 1.3 0.1080 0.0043 4.2916 0.1689 0.2860 0.0042 1765 72.2 1692 32.4 1621 21.0 92
      D020-3-1-09 554 881 0.6 0.0544 0.0024 0.3900 0.0277 0.0508 0.0026 387 98.1 334 20.2 319 15.8 96
      D020-3-1-10 363 561 0.6 0.0476 0.0029 0.1460 0.0092 0.0220 0.0004 79.7 140.7 138 8.1 140 2.6 102
      D020-3-1-11 199 193 1.0 0.1099 0.0033 5.0993 0.1651 0.3330 0.0052 1798 54.5 1836 27.5 1853 25.2 103
      D020-3-1-12 515 737 0.7 0.0917 0.0028 3.1650 0.0941 0.2478 0.0030 1461 52.9 1449 23.0 1427 15.4 98
      D020-3-1-13 293 562 0.5 0.0588 0.0025 0.6222 0.0261 0.0760 0.0010 567 94.4 491 16.3 472 5.9 96
      D020-3-1-14 241 205 1.2 0.0510 0.0052 0.1580 0.0164 0.0222 0.0005 243 218.5 149 14.4 142 3.0 95
      D020-3-1-15 255 743 0.3 0.0545 0.0027 0.2570 0.0123 0.0342 0.0005 391 113.0 232 9.9 217 3.2 93
      D020-3-1-16 313 401 0.8 0.0552 0.0022 0.5839 0.0236 0.0764 0.0009 420 92.6 467 15.1 474 5.5 102
      D020-3-1-17 2820 1631 1.7 0.0508 0.0052 0.1585 0.0188 0.0219 0.0009 232 218.5 149 16.5 140 5.9 93
      D020-3-1-18 135 64 2.1 0.0564 0.0070 0.5589 0.0592 0.0738 0.0018 478 275.9 451 38.6 459 10.9 102
      D020-3-1-19 437 757 0.6 0.0571 0.0028 0.3134 0.0144 0.0401 0.0007 494 107.4 277 11.1 254 4.1 92
      D020-3-1-20 384 565 0.7 0.0716 0.0028 1.4407 0.0595 0.1461 0.0026 976 79.6 906 24.8 879 14.4 97
      D020-3-1-21 113 96 1.2 0.1690 0.0057 10.7709 0.3818 0.4625 0.0067 2550 57.6 2504 33.0 2451 29.6 96
      D020-3-1-22 139 204 0.7 0.0571 0.0037 0.3524 0.0223 0.0452 0.0007 494 142.6 307 16.8 285 4.4 93
      下载: 导出CSV

      表  2   灵乡闪长玢岩锆石Hf同位素数据

      Table  2   Zircon Hf isotope data of Lingxiang dioritic porphyrite

      样品编号 176Lu/177Hf 176Hf/177Hf 176Yb/177Hf 年龄(Ma) 176Hf/177Hf)i εHf(t TDM (Ma) T2DM (Ma)
      D20-3-1 - 1 0.000570 0.000005 0.281424 0.000009 0.021425 0.000240 1807 0.281404 −8.1 2526 2964
      D20-3-1 - 2 0.000663 0.000013 0.281489 0.000010 0.025059 0.000457 1655 0.281468 −9.3 2443 2921
      D20-3-1 - 3 0.001057 0.000021 0.282144 0.000011 0.038954 0.000827 1528 0.282113 10.7 1564 1585
      D20-3-1 - 4 0.000600 0.000006 0.281100 0.000008 0.022012 0.000191 2445 0.281072 −5.1 2963 3280
      D20-3-1 - 6 0.002287 0.000044 0.282495 0.000036 0.071227 0.001076 140 0.282489 −7.4 1108 1627
      D20-3-1 - 7 0.001532 0.000027 0.281691 0.000023 0.050118 0.000749 1765 0.281640 −0.7 2218 2477
      D20-3-1 - 9 0.001994 0.000048 0.282431 0.000026 0.064281 0.001985 319 0.282419 −5.8 1191 1670
      D20-3-1 - 10 0.001281 0.000031 0.282579 0.000013 0.050481 0.000824 140 0.282576 −4.3 959 1433
      D20-3-1 - 11 0.000457 0.000015 0.281549 0.000013 0.016213 0.000459 1798 0.281534 −3.7 2348 2687
      D20-3-1 - 12 0.001862 0.000045 0.282169 0.000018 0.062988 0.001202 1461 0.282118 9.3 1561 1617
      D20-3-1 - 13 0.001463 0.000028 0.282251 0.000010 0.049887 0.000612 472 0.282238 −8.8 1429 1975
      D20-3-1 - 14 0.002842 0.000031 0.282530 0.000031 0.092366 0.000907 142 0.282522 −6.1 1074 1552
      D20-3-1 - 15 0.001126 0.000022 0.282463 0.000009 0.037917 0.000721 217 0.282459 −6.7 1119 1646
      D20-3-1 - 16 0.002427 0.000064 0.282664 0.000013 0.075969 0.001666 474 0.282642 5.5 866 1075
      D20-3-1 - 17 0.000989 0.000032 0.282407 0.000015 0.032420 0.000913 140 0.282404 −10.4 1193 1815
      D20-3-1 - 18 0.001332 0.000025 0.282729 0.000016 0.055075 0.000864 459 0.282717 7.8 748 916
      D20-3-1 - 19 0.002403 0.000101 0.282322 0.000015 0.086403 0.003255 254 0.282310 −11.2 1364 1952
      D20-3-1 - 20 0.001155 0.000023 0.282295 0.000016 0.040620 0.000626 879 0.282276 1.7 1356 1635
      D20-3-1 - 21 0.000745 0.000029 0.281511 0.000020 0.028769 0.000946 2550 0.281475 11.7 2418 2338
      D20-3-1 - 22 0.001094 0.000019 0.282632 0.000012 0.042042 0.000667 285 0.282626 0.7 880 1230
       注:206Pb/238U 年龄<1000 Ma时,Con% = (206Pb/238U年龄/207Pb/235U年龄)×100%;206Pb/238U 年龄>1000 Ma时,Con% = (206Pb/238U年龄/207Pb/206Pb年龄)×100%。
      下载: 导出CSV

      表  3   鄂东南矿集区内继承锆石U-Pb年龄及Hf同位素数据汇总表

      Table  3   Inherited zircon age and Hf isotope data of intrusions in the Southeastern Hubei Province

      岩体 点号 Th(10−6 U(10−6 Th/U 年龄(Ma) εHft TDM(Ma) T2DM(Ma) 数据来源
      鄂城 CC375–16–5 1569 −0.5 2040 2311 Xie et al., 2011a
      铁山 TS3–7 399 596 0.7 1871 −0.7 2299 2558
      D20-3-1 - 1 47 32 1.5 1807 −8.1 2526 2964
      D20-3-1 - 2 56 44 1.3 1655 −9.3 2443 2921
      D20-3-1 - 3 1014 599 1.7 1528 10.7 1564 1585
      D20-3-1 - 4 250 287 0.9 2445 −5.1 2963 3280
      D20-3-1 - 7 230 184 1.3 1765 −0.7 2218 2477
      D20-3-1 - 9 554 881 0.6 319 −5.8 1191 1670 文中
      灵乡 D20-3-1 - 11 199 193 1.0 1798 −3.7 2348 2687
      D20-3-1 - 12 515 737 0.7 1461 9.3 1561 1617
      D20-3-1 - 13 293 562 0.5 472 −8.8 1429 1975
      D20-3-1 - 15 255 743 0.3 217 −6.7 1119 1646
      D20-3-1 - 16 313 401 0.8 474 5.5 866 1075
      D20-3-1 - 18 135 64 2.1 459 7.8 748 916
      D20-3-1 - 19 437 757 0.6 254 −11.2 1364 1952
      D20-3-1 - 20 384 565 0.7 879 1.7 1356 1635
      D20-3-1 - 21 113 96 1.2 2550 11.7 2418 2338
      D20-3-1 - 22 139 204 0.7 285 0.7 880 1230
      ZK02810-6-06c 133 170 0.8 1207 −8.9 2063 2549
      ZK02810-6-08c 53 133 0.4 2220 −2.6 2670 2953
      ZK02810-6-10c 67 139 0.5 2505 8.9 2483 2470
      ZK02810-6-11c 96 164 0.6 2046 3.6 2292 2435
      铜绿山 ZK02810-6-15c 79 76 1.0 2293 2.6 2541 2688 黄圭成等,2013
      ZK02810-6-17c 67 97 0.7 2613 8.9 2578 2556
      ZK02810-6-21c 158 466 0.3 1979 1.2 2318 2526
      ZK02810-6-18c 103 95 1.1 2895 6.2 2927 2946
      Dy254-1-13c 49 24 2.0 799
      Dy254-1-21c 69 109 0.6 1127 −15.0 2205 2861
      TLS801-103-3 31 22 1.4 1820 −7.0 2494 2909
      TLS801-103-4 172 286 0.6 751 −6.0 1543 2015
      TLS801-103-6 113 194 0.6 2613 −1.4 2974 3188
      TLS801-103-8 114 92 1.2 2061
      TLS801-103-9 41 61 0.7 1732 −7.1 2421 2846
      TLS801-103-14 202 155 1.3 299 −12.1 1400 2043
      TLS801-103-15 147 139 1.1 850
      TLS801-103-16 187 344 0.5 1862 −0.2 2276 2521
      TLS801-103-21 160 180 0.9 2457 5.8 2562 2627
      TLS801-103-22 316 426 0.7 1132
      TLS801-103-30 462 435 1.1 320
      TLS801-103-32 491 382 1.3 263
      TLS801-103-34 313 168 1.9 830
      铜绿山煌斑岩 TLS803-159-1 185 85 2.2 837 −20.6 2203 2982
      TLS803-159-2 108 136 0.8 323 11.5 480 572 Zhang et al., 2021a
      TLS803-159-3 30 61 0.5 1632 −9.0 2411 2885
      TLS803-159-14 251 397 0.6 836
      TLS803-159-15 545 563 1.0 997
      TLS803-159-16 140 201 0.7 2498
      TLS803-159-17 335 352 0.9 423
      TLS803-159-18 143 248 0.6 2345
      TLS803-159-19 50 149 0.3 2567
      TLS803-159-20 264 424 0.6 427
      TLS803-159-21 71 110 0.6 784
      TLS803-159-22 216 291 0.7 880
      TLS803-159-23 121 115 1.1 2147
      TLS803-159-24 332 388 0.9 835
      TLS803-159-25 195 148 1.3 421
      TLS803-159-26 89 411 0.2 1950
      TLS803-159-27 373 641 0.6 437
      TLS803-159-28 436 612 0.7 444
      TLS803-159-29 30 44 0.7 2469
      阳新 YX2–7 377 170 2.2 1117 −4.9 1812 2229 Xie et al., 2011a
      Dy116-06 872 1008 0.9 614 −7.6 1490 2006 丁丽雪等,2016
      Dy116-15 184 253 0.7 422
      Dy311-01 51 303 0.2 2258 −3.6 2738 3040
      Dy311-03 27 226 0.1 1713 −7.0 2408 2823
      Dy311-06 53 70 0.8 1158 −0.7 1685 2002
      姜桥 Dy311-10 11 27 0.4 2117 −14.4 3019 3588
      Dy311-13 120 143 0.8 1111 丁丽雪等,2013
      Dy311-15 101 114 0.9 1127
      Dy311-18 326 315 1.0 1124
      Dy311-19 68 122 0.6 1182
      Dy311-21 58 149 0.4 2032
      殷租* 08YZ38.1@6 227 117 1.9 2424 Li et al., 2010
      Dy314-13inh 77 107 0.7 1846
      Dy314-15 96 281 0.3 313
      Dy314-20 117 275 0.4 306
      Dy314-21inh 56 27 2.0 1798 −23.2 3100 3869
      铜鼓山 Dy314-22inh 161 126 1.3 1809 −23.2 3103 3881 夏金龙等,2013a
      Dy314-23inh 282 189 1.5 1884 −23.0 3173 3924
      Dy314-24inh 222 127 1.8 1888
      Dy314-25inh 50 61 0.8 1728
      Dy314-26inh 51 50 1.0 1574
      DY145-1inh 19 46 0.4 2959 3.1 3101 3188
      DY145-2inh 98 89 1.1 1785 −14.6 2769 3344
      DY145-5inh 72 83 0.9 1803
      DY145-8inh 92 60 1.5 1746 −18.1 2857 3526
      古家山 DY145-11inh 324 526 0.6 2499 夏金龙等,2013b
      DY145-12inh 107 109 1.0 1847 −1.0 2292 2558
      DY145-13inh 77 107 0.7 2342
      DY145-19inh 102 165 0.6 2036 1.1 2377 2583
      DY145-20inh 117 275 0.4 1929
      XNS1-6 180 215 0.8 2358
      阮家湾 XNS1-7 40 136 0.3 2379 颜代蓉等,2012
      XNS1-16 168 374 0.4 2337
      XNS17-15 109 657 0.2 1816
       注:εHft)和模式年龄值均按照本文提供的参数重新计算。
      下载: 导出CSV
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