Rock quantity and age are fundamental features of Earth's crust that pertain to many problems in geoscience. Here we combine new estimates of igneous rock area in continental crust from the Macrostrat database (https://macrostrat.org/) with a compilation of detrital zircon ages in order to investigate rock cycling and crustal growth. We find that there is little or no decrease in igneous rock area with increasing rock age. Instead, igneous rock area in North America exhibits four distinct Precambrian peaks, remains low through the Neoproterozoic, and then increases only modestly toward the recent. Peaks in Precambrian detrital zircon age frequency distributions align broadly with peaks in igneous rock area, regardless of grain depositional age. However, detrital zircon ages do underrepresent a Neoarchean peak in igneous rock area; young grains and ca. 1.1 Ga grains are also overrepresented relative to igneous area. Together, these results suggest that detrital zircon age distributions contain signatures of continental denudation and sedimentary cycling that are decoupled from the cycling of igneous source rocks. Models of continental crustal evolution that incorporate significant early increase in volume and increased sedimentation in the Phanerozoic are well supported by these data.Quantitative constraints on the age-varying properties of rocks in Earth's crust are critical for generating and testing hypotheses about the long-term evolution of Earth systems. A priori expectations for the quantity-age distribution of some rock types can be formulated with assumptions about how geological processes operate. For example, a fundamental prediction of the sedimentary cycle is that surviving sediment quantity should decrease exponentially with increasing age (e.g., Mackenzie and Pigott, 1981). The same principles of rock cycling apply to igneous rocks in continental crust, but models are less firmly grounded in a steady-state world view. This is because it is accepted that while today continents occupy ∼30% of Earth's surface, at some early point in Earth's history there cannot have been any continental crust. Between these two constraints, nearly all possible models have been proposed, each with different preferences for the relative importance of cycling versus time-varying production (Armstrong, 1981; Roberts and Spencer, 2015; Puetz et al., 2017; Condie et al., 2018; Dhuime et al., 2018; Condie and Aster, 2010). Resolving these models and calibrating rock cycling has implications for how we interpret deep-time records and for generating and testing hypotheses for drivers of long-term changes in Earth systems (e.g., Hayes and Waldbauer, 2006; Husson and Peters, 2018).Several attempts have been made to estimate continent- or global-scale rock quantity so as to constrain rock cycling and crustal growth models with minimum estimates of original volume. Some are based on geological maps (e.g., Blatt and Jones, 1975; Goodwin, 1996; Wilkinson et al., 2009), the most widely produced models for the lithology and age of rocks in Earth's crust, albeit only explicitly for a surface. Studies that integrate both surface and subsurface data provide a more complete description of crustal age and composition, but most have emphasized sediments (Ronov et al., 1980; Husson and Peters, 2017). Recent advances in high-throughput zircon U-Pb geochronology and geochemistry provide a proxy for crustal growth and recycling (e.g., Cawood et al., 2013; Payne et al., 2016; Korenaga, 2018; Rosas and Korenaga, 2018; Puetz and Condie, 2020), but these methods rely on several key assumptions, including that the frequency of crystallization ages among compilations of detrital zircon (DZ) is proportional to the quantity of igneous rocks that sourced the sediment.We leverage advances in geoinformatics in order to provide new constraints on the area-age relationship of igneous rocks in continental crust. Our study is focused on North America, where surface and subsurface data are available, but we consider this record in the context of global map data.Geologic maps in the Macrostrat database (https://macrostrat.org/; Peters et al., 2018) are grouped into four scales that combine sources into coherent two-dimensional representations. Here, we use the two scales that are globally complete for continents: “tiny” (∼1:20,000,000 scale) and “small” (∼1:5,000,000 scale; Fig. 1). The tiny-scale map derives from Chorlton (2007), and the small-scale map was composited from this and other sources (see Table S1 in the Supplemental Material1). All bedrock maps in Macrostrat consist of polygons for unit boundaries, each of which minimally has chronostratigraphic age(s) and lithology descriptions linked to vocabularies (see https://macrostrat.org/api/defs/).Two map scales are considered here to illustrate the effects of different temporal binning schemes and rock unit definitions. To make the scales as comparable as possible, polygons were clipped to the outline of land today, and major oceanic islands were removed. Map polygons containing igneous or metaigneous rock are shown in Figure 1A and 1B, along with outlines for other rock types. For an online interactive version, see https://macrostrat.org/map/.We also include geologic column data that summarize the lithologies and ages of rocks in the surface and subsurface regionally. Macrostrat columns are not yet global in coverage, and here we focus on 949 columns in North America (Fig. 1C). Column rock units acquire an age model that incorporates correlations to chronostratigraphic bins and relative age constraints between units within bins (Peters et al., 2018). Thus, the ages of rock units in columns are typically more finely resolved than in maps. Columns can also include igneous rocks of different ages and lithologies through a thickness of crust that is covered by sediment, a more volumetrically relevant representation of igneous rock quantity than that provided by maps (Fig. 1).Area versus age was calculated for 1 m.y. increments by summing the Cartesian area in square kilometers (World Geodetic System 1984 [WGS84] spheroid) of all polygons (Fig. 1) containing igneous and/or metaigneous rocks with an intersecting age estimate. We also include concordant U-Pb “best ages” (Spencer et al., 2016) for 69,453 DZ from 746 samples matched to 392 Phanerozoic sedimentary units in North American columns. DZ measurements derive from multiple sources, most aggregated by Puetz (2018) and all of which are accessible via Macrostrat's application programming interface (API) and included in the Supplemental Material. DZ data were not used to construct Macrostrat age models.Area-age results for igneous and metaigneous rocks in Macrostrat's global geological maps and North American columns (Fig. 1) share many similarities over 3.5 b.y. (Fig. 2). First, the absolute values of the area estimates are similar. This coincidence occurs because igneous rocks compose 19.8% and 21.9% of the total global area of the tiny- and small-scale maps, respectively, whereas columns occupy 17.1% of the total global map area. Thus, North America stripped of sediments to reveal all igneous rocks in the surface and subsurface has approximately the same total area as surface-exposed igneous rocks do globally; North America does have proportionally more igneous rock at the surface compared to globally (22.8% and 29.6% of the tiny- and small-scale map area in North America is igneous).The more salient similarities between igneous rock area in global maps and North American columns involve temporal patterns (Fig. 2), including shared late Archean and late Paleoproterozoic peaks followed by a decrease into the Mesoproterozoic and then a smaller mid- to late Phanerozoic rise. The better temporal resolution of the small-scale map makes patterns more apparent, but results are consistent between map scales. Importantly, neither the global geological map nor North American column data exhibit a sustained increase in igneous area toward the present (Fig. 2A). To further assess this long-term trend and to address potential overweighting of poorly time-resolved rock units, we normalized the area of each igneous polygon by its estimated duration in millions of years. Such normalization does impact the temporal trajectory (Fig. 2B). Notably, the Archean and Paleoproterozoic peaks are lower and there is a large increase in area toward the recent during the Phanerozoic. Normalization by duration may, however, introduce bias by increasing the area per million years of units from extant igneous systems that will range into the future while decreasing that of igneous units that formed over an area for a long duration. Despite such distortions, and regardless of which estimate is used, there is little or no long-term decrease in igneous rock area with increasing age for most of the past 3.5 b.y. (Fig. 2).Detrital zircon age frequencies in North America share many similarities with igneous rock area estimated from columns in the same region (Fig. 3A). This is true for combined DZ ages and for Precambrian-aged grains when they are subdivided by the depositional age of their host sediments. Notably, both igneous area and DZ ages exhibit Neoarchean and late Paleoproterozoic peaks, but their relative magnitudes are different. DZ age frequency also aligns broadly with a peak in column area at ca. 1.4 Ga, and there is a shared late Mesoproterozoic peak, albeit one that is larger and somewhat younger in DZ. Both igneous area and DZ age frequencies are low through the Neoproterozoic and Paleozoic and then increase in the Mesozoic–Cenozoic, with DZ becoming richer in grains relative to igneous rock area toward the recent (Fig. 3B).Data on igneous-metaigneous rock area in the continental surface and subsurface combined with DZ age distributions have several implications. The simplest is that North America is sufficiently large and tectonically diverse to capture a signal of igneous rock quantity with parallels seen globally (Fig. 2). This result is consistent with the finding that the sedimentary record of North America contains a global signal (Ronov et al., 1980; Peters and Husson, 2017) and probably reflects the fact that “global tectonics” is quantitatively expressed in all such syntheses of rocks from large samples of continental crust. Nevertheless, there are clear differences between the global and regional data. For example, the small-scale global map shows a Neoproterozoic increase in igneous area whereas igneous area declines to a minimum in North America (Fig. 2), a likely signal of the Gondwanan Pan-African orogeny.Another useful result is that both igneous rock area in North America and DZ age frequencies in the same region have similar temporal variation (Fig. 3A). Thus, both records are likely detecting the same quantity-age property of the crust. More interesting, however, are the differences in these records. Notably, Archean igneous rocks are more abundant in direct measures of quantity (Fig. 2) than suggested by DZ age frequencies. Indeed, there is an overall decrease in grain frequency relative to igneous area with increasing age (Fig. 3B). One hypothesis for this discrepancy is that zircon fertility is lower in older igneous rocks because they are more mafic on average (Moecher and Samson, 2006; Lee et al., 2016). However, the mean felsic-to-mafic ratio of igneous rocks in Macrostrat columns is not markedly different in the Archean (Fig. S1 in the Supplemental Material), and major elemental data from sediments also indicate that Archean crust had a compositional diversity similar to that of modern continents (Lipp et al., 2021). Correcting DZ abundance for changes in the zircon saturation of magmas (Keller et al., 2017) does significantly increase DZ density estimates in the Archean (Fig. S2), but not enough to account for the discrepancy (Fig. 3B).In the absence of a compositional shift in igneous source rocks, another explanation for the observed change in DZ abundance relative to igneous rock area is that DZ grains undergo attrition in a way that is much faster than that of their igneous source rocks. This is expected if older grains are more likely to have undergone metamictization and Pb loss as well as physical destruction during transport (e.g., Markwitz et al., 2017; Andersen et al., 2019). The DZ record may also be inherently overprinted by its sedimentary origin (e.g., Andersen et al., 2016), with igneous rocks yielding fewer grains per unit area as they age due to increasing isolation from active orogens and lowering of their mean elevation (Spencer et al., 2018).On shorter time scales, a notable difference between DZ age frequency and igneous area occurs at ca. 1.1 Ga, where the well-known peak in DZ ages associated with the assembly of Rodinia (Condie and Aster, 2010) is larger and younger than the peak in igneous area. It is possible that this offset reflects error in the column age model or overweighting by columns of small but widespread intrusive rocks, such as the Mackenzie dike swarm (western Canada) spike at ca. 1260 Ma (Fig. 2). Indeed, the ca. 1.2 Ga peak in igneous area is driven primarily by mafic rocks (Fig. S1), which may account for some of the difference with DZ ages. It is also possible that the offset reflects the unroofing of zircon-rich igneous rocks from a narrow, active stretch of the eastern North American margin (Park et al., 2010) or input of grains from outside of North America.Importantly, Precambrian-aged DZ age densities are similar relative to each other and to igneous area, no matter the depositional age of their host sediment (Fig. 3A). Post-Cambrian Paleozoic sediments do contain more Ediacaran grains, a signature that reflects the docking of Ediacaran-aged arcs and terranes along the eastern margin of Laurentia (Park et al., 2010), and Cambrian sediments are richer in Archean grains, but the overall differences are small.The similarities in Precambrian DZ age frequencies among depositional cohorts, combined with clear evidence of early Paleozoic reburial of most if not all of the igneous source rocks in North America (Fig. 3; Peters and Gaines, 2012; Keller et al., 2019), raises the possibility that much of the Precambrian DZ grain population was introduced en masse to the surface environment during late Precambrian continental denudation. Under this model, Precambrian-aged DZ grains in post-Cambrian Phanerozoic sedimentary rocks did not come predominantly from exposed igneous rocks, but rather from sediments that were recycled from the margins of a largely denuded continent. This pool of DZ was then spread back over the continent during progressive Phanerozoic reburial of the Great Unconformity, beginning with a thin blanket of predominately marine sediments that covered essentially all of Laurentia by the end-Ordovician. The possibility that a similar episode of continental denudation followed by reburial occurred during the Paleoproterozoic (Husson and Peters, 2018; Keller et al., 2019) provides an intriguing, if speculative, hypothesis for the low abundance of Archean DZ. In this scenario, Archean grains in post-Cambrian sediments would have undergone two such major cycles of continental exhumation and reburial.Finally, regardless of sampling approach or geographic scale (Fig. 2), igneous rock quantity does not decrease exponentially with increasing age, as predicted by most basic models of rock cycling. Scaling igneous area by unit duration (Fig. 2B) does produce a decrease, but only over the recent to mid-Paleozoic. This is the same time scale over which there is a large decrease in nonmarine sediment (Peters and Husson, 2017), a higher elevation, faster-cycling component of the sedimentary system that does include igneous rocks. Thus, the rock age distributions reported here provide minimum bounds on net continental crustal quantities that account for rocks in the subsurface and in more rapidly cycling geomorphic systems. Covariance in old igneous and sedimentary rock quantity and the shifting abundance of sediment in continental crust (Fig. 3C) reinforces crustal evolution as a critical driver of long-term changes in Earth systems. Critical tests of this hypothesis and many new insights will be gained by expanding the geographic footprint and temporal acuity of surface-subsurface column data globally.Macrostrat development was supported by U.S. National Science Foundation grant EAR-1150082 and EarthCube grant ICER-1440312. C. Walton acknowledges the UK Natural Environment Research Council (NERC) and UK Research and Innovation (UKRI) for support through a NERC Doctoral training partnership (DTP) studentship, grant NE/L002507/1. O. Shorttle acknowledges support from NERC grants NE/T012633/1 and NE/T00696X/1. We thank Alan Carroll and the Adam Maloof Lab at Princeton University (USA) for discussion, and Christopher Spencer, Justin Payne, and an anonymous reviewer for insightful reviews.

中文翻译：

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大陆地壳火成岩面积和年龄

岩石数量和年龄是地壳的基本特征，与地球科学中的许多问题有关。在这里，我们将来自 Macrostrat 数据库 (https://macrostrat.org/) 的大陆地壳火成岩面积的新估计与碎屑锆石年龄汇编相结合，以研究岩石循环和地壳生长。我们发现，随着岩龄的增加，火成岩面积几乎没有减少。相反，北美的火成岩区呈现出四个不同的前寒武纪山峰，在新元古代期间保持低位，然后在最近才略有增加。无论颗粒沉积年龄如何，前寒武纪碎屑锆石年龄频率分布中的峰与火成岩区的峰大致一致。然而，碎屑锆石年龄确实不能代表火成岩地区的新太古代峰；年轻的谷物和约。1.1 Ga 晶粒相对于火成岩面积也过多。总之，这些结果表明碎屑锆石年龄分布包含大陆剥蚀和沉积循环的特征，这些特征与火成岩烃源岩的循环分离。这些数据很好地支持了包含显生宙早期体积显着增加和沉积作用增加的大陆地壳演化模型。对地壳中岩石年龄变化特性的定量约束对于生成和检验关于长期的假设至关重要。地球系统的演化。一些岩石类型的数量-年龄分布的先验预期可以通过关于地质过程如何运作的假设来制定。例如，沉积循环的一个基本预测是存活的沉积物数量应该随着年龄的增加呈指数下降（例如，Mackenzie 和 Pigott，1981）。岩石循环的相同原理也适用于大陆地壳中的火成岩，但模型在稳态世界观的基础上不那么牢固。这是因为公认的是，虽然今天大陆占据了地球表面的 30%，但在地球历史的某个早期，不可能有任何大陆地壳。在这两个约束之间，几乎所有可能的模型都被提出，每个模型对循环与时变生产的相对重要性都有不同的偏好（Armstrong，1981；Roberts 和 Spencer，2015；Puetz 等，2017；Condie 等。 ，2018 年；Dhuime 等人，2018 年；Condie 和 Aster，2010 年）。解析这些模型和校准岩石循环对我们如何解释深时记录以及为地球系统长期变化的驱动因素生成和测试假设有影响（例如，Hayes 和 Waldbauer，2006 年；Husson 和 Peters，2018 年）。已经尝试估计大陆或全球尺度的岩石数量，以便用最小的原始体积估计来约束岩石循环和地壳生长模型。有些基于地质图（例如，布拉特和琼斯，1975 年；古德温，1996 年；威尔金森等人，2009 年），这是生产最广泛的地壳岩石岩性和年龄模型，尽管只是明确地针对表面。整合地表和地下数据的研究提供了对地壳年龄和组成的更完整描述，但大多数都强调了沉积物（Ronov 等，1980；胡森和彼得斯，2017 年）。高通量锆石 U-Pb 年代学和地球化学的最新进展为地壳生长和再循环提供了一个代理（例如，Cawood 等人，2013 年；Payne 等人，2016 年；Korenaga，2018 年；Rosas 和 Korenaga，2018 年；Puetz 和Condie, 2020)，但这些方法依赖于几个关键假设，包括碎屑锆石 (DZ) 汇编中的结晶年龄频率与沉积物来源的火成岩数量成正比。为大陆地壳火成岩的面积-年龄关系提供了新的约束。我们的研究集中在北美，那里可以获得地表和地下数据，但我们在全球地图数据的背景下考虑了这一记录。 Macrostrat 数据库中的地质图 (https://macrostrat.org/; Peters et al., 2018) 分为四个尺度，将源组合成相干的二维表示。在这里，我们使用全球完整的两个大陆尺度：“小”（~1:20,000,000 尺度）和“小”（~1:5,000,000 尺度；图 1）。小比例尺地图源自 Chorlton (2007)，小比例尺地图由该来源和其他来源合成（参见补充材料 1 中的表 S1）。Macrostrat 中的所有基岩图都由单元边界的多边形组成，每个多边形至少具有与词汇相关的年代地层年龄和岩性描述（参见 https://macrostrat.org/api/defs/）。此处考虑了两种地图比例说明不同时间分箱方案和岩石单元定义的影响。为了使尺度尽可能具有可比性，今天，多边形被剪裁到陆地的轮廓，主要的海洋岛屿被移除。包含火成岩或变火成岩的地图多边形以及其他岩石类型的轮廓如图 1A 和 1B 所示。有关在线互动版本，请参阅 https://macrostrat.org/map/。我们还包括地质柱数据，这些数据总结了区域地表和地下岩石的岩性和年龄。Macrostrat 色谱柱的覆盖范围还不是全球性的，这里我们重点关注北美的 949 个色谱柱（图 1C）。柱状岩单元获得了一个年龄模型，该模型结合了年代地层单元的相关性以及单元内单元之间的相对年龄限制（Peters 等，2018）。因此，柱中岩石单元的年龄通常比地图更精细。柱子还可以通过被沉积物覆盖的地壳厚度包括不同年龄和岩性的火成岩，这是一种比地图提供的更具有体积相关性的火成岩数量表示（图 1）。面积与年龄的计算为 1 my通过对包含相交年龄估计的火成岩和/或变火成岩的所有多边形（图 1）的笛卡尔面积（World Geodetic System 1984 [WGS84] 球体）求和来增加增量。我们还包括来自与北美柱中 392 个显生宙沉积单元相匹配的 746 个样本的 69,453 个 DZ 的一致 U-Pb“最佳年龄”（Spencer 等人，2016 年）。DZ 测量来自多个来源，大部分由 Puetz (2018) 汇总，所有这些都可以通过 Macrostrat' 访问 s 应用程序编程接口 (API) 并包含在补充材料中。DZ 数据未用于构建 Macrostrat 年龄模型。Macrostrat 全球地质图和北美柱（图 1）中火成岩和变火成岩的面积年龄结果与 3.5 by（图 2）有许多相似之处。首先，面积估计的绝对值是相似的。之所以发生这种巧合，是因为火成岩分别占小比例尺和小比例尺地图全球总面积的 19.8% 和 21.9%，而柱子占全球地图总面积的 17.1%。因此，北美剥离沉积物以显示地表和地下的所有火成岩的总面积与全球地表暴露的火成岩的总面积大致相同；与全球相比，北美地表的火成岩比例确实更多（北美小比例尺和小比例尺地图区域的 22.8% 和 29.6% 是火成岩）。全球地图中的火成岩区域与北美洲柱涉及时间模式（图 2），包括共享的太古代晚期和古元古代晚期峰，随后下降到中元古代，然后是中晚期显生宙较小的上升。小比例尺地图更好的时间分辨率使模式更加明显，但地图比例尺之间的结果是一致的。重要的是，全球地质图和北美柱状数据都没有表现出目前火成岩面积的持续增加（图 2A）。为了进一步评估这种长期趋势并解决时间分辨率差的岩石单元的潜在超重问题，我们根据每个火成岩多边形的估计持续时间（以百万年为单位）进行了标准化。这种归一化确实会影响时间轨迹（图 2B）。值得注意的是，太古宙和古元古代的峰值较低，在显生宙期间，面积向近期有很大的增加。然而，按持续时间归一化可能会通过增加现存火成岩系统每百万年单位的面积而引入偏差，这些单位将延伸到未来，同时减少在一个地区形成的长期火成岩单位的面积。尽管有这种扭曲，无论使用哪种估计，在过去 3.5 年的大部分时间里，火成岩面积随着年龄的增加几乎没有或没有长期减少（图 2）。北美的碎屑锆石年龄频率与从同一地区的柱子估计的火成岩面积有许多相似之处（图 3A）。当 DZ 年龄和前寒武纪颗粒按其寄主沉积物的沉积年龄细分时，这对于组合 DZ 年龄和前寒武纪颗粒是正确的。值得注意的是，火成岩区和 DZ 时代都表现出新太古代和晚古元古代高峰，但它们的相对大小不同。DZ 老化频率也与大约 20 倍的色谱柱面积峰值大致一致。1.4 Ga，并且有一个共享的中元古代晚期峰，尽管在 DZ 中更大且更年轻。火成岩区和 DZ 年龄频率在新元古代和古生界都较低，然后在中新生代增加，DZ 相对于最近的火成岩区颗粒变得更丰富（图 3B）。大陆表面和地下火成岩-变火成岩面积的数据与 DZ 年龄分布相结合，具有多种意义。最简单的是，北美洲足够大且构造多样，可以捕获全球范围内具有平行线的火成岩数量信号（图 2）。这一结果与北美沉积记录包含全球信号的发现一致（Ronov et al., 1980; Peters and Husson, 2017），可能反映了“全球构造”在所有此类综合中定量表达的事实。来自大陆地壳大样本的岩石。然而，全球和区域数据之间存在明显差异。例如，小比例尺全球地图显示火成岩面积在新元古代增加，而北美的火成岩面积下降到最小值（图2），冈瓦纳泛非造山运动的一个可能信号。另一个有用的结果是北美的火成岩区域和同一地区的 DZ 年龄频率具有相似的时间变化（图 3A）。因此，这两个记录很可能检测到地壳的相同数量-年龄特性。然而，更有趣的是这些记录的差异。值得注意的是，太古宙火成岩在数量的直接测量（图 2）中比 DZ 年龄频率建议的更丰富。事实上，随着年龄的增长，相对于火成岩区域，谷物频率总体上下降（图 3B）。这种差异的一个假设是，较旧的火成岩中的锆石生育率较低，因为它们平均具有更多的镁铁质（Moecher 和 Samson，2006 年；Lee 等人，2016 年）。然而，Macrostrat 柱中火成岩的平均长英质与基性质比在太古代没有显着差异（补充材料中的图 S1），来自沉积物的主要元素数据也表明太古代地壳具有类似于现代大陆（Lipp 等，2021）。根据岩浆锆石饱和度的变化校正 DZ 丰度（Keller 等人，2017 年）确实显着增加了太古代的 DZ 密度估计（图 S2），但不足以解释差异（图 3B）。由于火成岩烃源岩不存在成分变化，观察到的 DZ 丰度相对于火成岩面积变化的另一种解释是 DZ 颗粒以比其火成岩烃源岩快得多的方式进行磨损。如果较老的谷物更有可能在运输过程中发生变质化和铅损失以及物理破坏，这是可以预期的（例如，Markwitz 等人，2017 年；Andersen 等人，2019 年）。DZ 记录也可能被其沉积起源固有地重叠（例如，Andersen 等人，2016），由于与活动造山带的隔离增加和平均海拔降低，火成岩随着年龄的增长每单位面积产生的颗粒较少（Spencer等人，2018 年）。在较短的时间尺度上，DZ 年龄频率和火成岩区域之间的显着差异发生在大约 1.1 Ga，其中与 Rodinia 组装相关的著名 DZ 年龄峰值（Condie 和 Aster，2010 年）比火成岩地区的峰值更大更年轻。这种偏移可能反映了柱龄模型中的错误或由小而广泛的侵入岩柱造成的超重，例如约 1260 毫安（图 2）。事实上，约。1.2 火成岩区Ga峰主要受基性岩驱动（图S1），这可能是DZ年龄差异的部分原因。偏移量也有可能反映了北美东部边缘狭窄、活跃的带富锆石火成岩的开顶（Park et al., 2010）或来自北美以外的颗粒输入。重要的是，前寒武纪-无论其寄主沉积物的沉积年龄如何，老化的 DZ 年龄密度相对于彼此和火成岩区域是相似的（图 3A）。后寒武纪古生代沉积物确实含有更多的埃迪卡拉纪颗粒，反映劳伦大陆东缘埃迪卡拉纪弧和地体对接的特征(Park et al., 2010)，寒武纪沉积物中太古宙颗粒更丰富，但总体差异较小。 前寒武纪DZ时代的相似性沉积群之间的频率，结合早期古生代重新埋藏北美大部分火成岩烃源岩的明确证据（图 3；彼得斯和盖恩斯，2012 年；凯勒等人，2019 年），增加了这种可能性在晚前寒武纪大陆剥蚀期间，大量的前寒武纪 DZ 谷物种群被大量引入地表环境。在该模型下，后寒武纪显生宙沉积岩中的前寒武纪 DZ 颗粒并非主要来自暴露的火成岩，而是来自从大部分裸露大陆边缘回收的沉积物。这个 DZ 池随后在大不整合面的渐进显生宙重新埋藏期间散布到大陆上，开始是一层薄薄的海洋沉积物，在奥陶纪末期基本上覆盖了整个劳伦西亚。在古元古代（Husson 和 Peters，2018 年；Keller 等人，2019 年）发生了类似的大陆剥蚀和再埋葬事件的可能性为太古代 DZ 的低丰度提供了一个有趣的假设，如果是推测性的。在这种情况下，后寒武纪沉积物中的太古宙颗粒将经历两次大陆剥脱和重新埋藏的主要循环。 最后，无论采样方法或地理范围如何（图 2），正如大多数岩石循环的基本模型所预测的那样，火成岩的数量不会随着年龄的增加而呈指数下降。按单位持续时间缩放火成岩面积（图 2B）确实会产生减少，但仅在最近到中古生代。这与非海相沉积物大幅减少的时间尺度相同（Peters 和 Husson，2017 年），这是包含火成岩的沉积系统中海拔更高、循环速度更快的组成部分。因此，这里报告的岩石年龄分布提供了净大陆地壳数量的最小界限，这些数量可以解释地下和更快速循环的地貌系统中的岩石。古老火成岩和沉积岩数量的协方差与大陆地壳沉积物丰度的变化（图 2）。3C) 强化了地壳演化作为地球系统长期变化的关键驱动因素。通过在全球范围内扩大地表-地下柱数据的地理足迹和时间敏锐度，将获得对该假设的批判性测试和许多新见解。Macrostrat 的开发得到了美国国家科学基金会资助 EAR-1150082 和 EarthCube 资助 ICER-1440312 的支持。C. 沃尔顿感谢英国自然环境研究委员会 (NERC) 和英国研究与创新 (UKRI) 通过 NERC 博士培训合作伙伴关系 (DTP) 奖学金提供支持，资助 NE/L002507/1。O. Shorttle 承认 NERC 拨款 NE/T012633/1 和 NE/T00696X/1 的支持。我们感谢 Alan Carroll 和普林斯顿大学（美国）的 Adam Maloof 实验室的讨论，感谢 Christopher Spencer、Justin Payne 和一位匿名审稿人的深刻评论。