RESEARCH

Eastern margin of Tibet supplies most sediment to the Yangtze River

Gregory K. Wissink* and Gregory D. Hoke DEPARTMENT OF EARTH SCIENCES, SYRACUSE UNIVERSITY, 204 HEROY GEOLOGY LABORATORY, SYRACUSE, NEW YORK 13244, USA

ABSTRACT

Zircon provenance studies of modern and ancient fluvial systems help reveal the relative contributions and importance of upstream sediment sources. A 2014 study of detrital zircon U-Pb age distributions from the Yangtze River (China) and its tributaries proposed a strong anthropo- genic control on sediment flux. Those data, along with other data from the region, were reanalyzed using multiple detrital zircon U-Pb age distribution comparison techniques and a distribution-mixing model to construct an improved and quantitative view of provenance. The variability in the Yangtze River trunk stream U-Pb age distributions is evaluated with respect to trunk-to-trunk stream comparisons, trunk-to- tributary comparisons, and in mixture models that consider tributary and bedrock contributions, the latter using a comprehensive compilation of bedrock source terranes. Uniformity in the zircon age distribution of the Yangtze River trunk stream is established in the upper reaches, downstream of the first bend, and maintained by the left-bank tributaries to its outlet. Whether considering the bedrock source terranes or only the modern Yangtze River sediments, the major source of sediments contributing to Yangtze River is clearly the eastern edge of the Tibetan Plateau (e.g., Songpan Ganze complex, Longmenshan Range), where rock uplift rates are high. The purported increase in anthropo- genic impact on sediment yield in the lowlands, at least as viewed through detrital zircon age distributions, is insignificant.

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INTRODUCTION local and regional tectonic events (Gehrels et al., southeastern margin of the Tibetan Plateau. 2003, 2011; Darby and Gehrels, 2006; Hoang Punctuated episodes of rapid river incision into The Yangtze River has headwaters in the et al., 2009; Yan et al., 2012; Wang et al., 2013; the eastern and southeastern margins of the Tibetan Plateau, and is the longest river in Asia He et al., 2013; L. Wang et al., 2014). At its sim- plateau reached localized rates of >300 m/m.y. and fourth longest river in the world. The Yangtze plest, erosion and rock uplift control the zircon (Clark et al., 2005; Ouimet et al., 2010), with River traverses the eastern two-thirds of China contributions of progressively unroofed rock to an abrupt decrease ca. 7 Ma (McPhillips et al., and integrates multiple large tributaries draining fluvial sediments; thus, measured zircon ages 2016). The Yangtze River catchment, like much crustal terranes with characteristic detrital zircon should be traceable to a unique source. Studies of China, is subject to moderate to intense agri- U-Pb age signatures. Zircon U-Pb ages may help have shown that variable zircon concentrations cultural activity (He et al., 2014). At values of fingerprint the dominant sediment sources to the in source areas (Moecher and Samson, 2006; 30 m/m.y., 10Be-derived erosion rates in the main trunk stream of the Yangtze River and thus elu- Malusà et al., 2013, 2015) can affect downstream course of the upper Yangtze River (Jinsha River) cidate the spatial pattern of erosion across the age distributions, and U-Pb age distributions of are remarkably low, yet some small tributaries catchment. Accurate constraints on the zircon detritus may differ significantly from its assumed are rapidly eroding at 500 m/m.y. (Henck et contribution from different catchments enhance source over very short distances (Bonich et al., al., 2011). Immediately following large earth- our understanding of catchment-wide erosional 2013). The interpretation of U-Pb ages from quakes, such as the 2008 Wenchuan earthquake, patterns and may help frame future studies on larger river systems may be further complicated the mountain rivers of the eastern plateau mar- how the river’s course has evolved over time. by spatial variability in erosion due to climate gin become choked with material shed off the The expeditious and inexpensive acquisition change, or large but irregular influxes of sediment, failed hillslopes (Parker et al., 2011). Active rock of data made possible by laser ablation–induc- for example, from coseismic landslides (Gallen uplift decreases dramatically east of the plateau tively coupled plasma–mass spectrometry (e.g., et al., 2015). However, despite some limitations, margin (Richardson et al., 2008), and variations Gehrels et al., 2008) has made zircon the min- detrital zircon U-Pb ages have proven a valuable in anthropogenic activity, principally from agri- eral of choice for many modern and ancient provenance tool in studies of basin evolution (Yan culture, likely become important agents of ero- provenance studies. In ancient settings, detrital et al., 2012; Zheng et al., 2013; C. Wang et al., sion (Wilkinson and McElroy, 2007). Previous zircon ages are routinely used to deduce drain- 2014), crustal evolution (Wang et al., 2010; Xu work examining the detrital zircon U-Pb age age network reorganization and the timing of et al., 2014), and tectonic and erosional histories distributions from the Yangtze River and its (e.g., Weislogel et al., 2010; Lang et al., 2013). tributaries used here concluded that high zircon Much of the landscape traversed by the flux to the trunk stream is driven by tributaries *E-mail: [email protected] Gregory Wissink http://orcid.org​/0000​-0003​ Yangtze River and its tributaries is tectonically characterized by high agricultural land use (He -1723-6231​ inactive, with the exception of the eastern and et al., 2014). We revisit these data through a

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more detailed analysis of the modern U-Pb age combine clearly dissimilar age distributions, for summed difference is two, therefore, the differ- distributions, and include an extensive compila- example, keeping the Songpan Ganze complex ence is halved and subtracted from one, giving tion of bedrock zircon data across the Yangtze divided into the three depocenters (southeast, likeness values that vary from 0 to 1, with higher River catchment (Figs. 1 and 2). Our attempt to central, and northeast) identified by Weislogel et values indicating greater intersample similarity. resolve the provenance of zircon in the Yangtze al. (2010). Unimodal bedrock units, particularly Probability function cross-plots are generated River includes multiple visual representations plutonic outcrops, were only combined when age by plotting the probabilities of two distributions of qualitative and quantitative zircon U-Pb age distributions were statistically indistinguishable. against one another over a given range of ages distribution comparisons and two mixing mod- (Saylor et al., 2013). The coefficient of deter- els that consider (1) the modern fluvial distribu- METHODS mination (R2 value), calculated from a linear fit tions and (2) potential bedrock sources within to the plot, provides the CPR value. Similar to the modern drainage area to determine their rela- We apply multiple conventional and new likeness, values range from 0 to 1, with 1 reflect- tive contributions of zircon to the Yangtze River approaches of detrital zircon data analysis in our ing identical distributions. sedimentary budget. We combine multiple statis- reexamination of the spatial distribution of prov- tical approaches to describe the variance in the enance changes for the modern Yangtze River. Multidimensional Scaling zircon U-Pb age signal of the Yangtze River with Through robust analytical evaluation of the data the goal of evaluating the distribution of ages set, we can better understand key characteristics Multidimensional scaling (MDS) is a tech- in the context of erosional variability through- of the Yangtze River sediment budget. nique common in statistical analysis of data sets out the Yangtze River catchment. This study not (e.g., Carroll and Arabie, 1980; Hayward and only reinterprets the data of He et al. (2014), but Kolmogorov-Smirnov Test, Likeness, and Smale, 1992; Smosna et al., 1999); however, it is also provides a framework for thorough analysis Cross-Plot R2 values relatively new in its application to detrital zircon of detrital data sets for future studies. U-Pb age data sets (Vermeesch, 2013; Vermeesch The two-sample Kolmogorov-Smirnov test and Garzanti, 2015; Spencer and Kirkland, 2016). DATA SETS (K-S test) is one of the most widely utilized MDS in detrital zircon geochronology attempts nonparametric statistical tests in detrital zircon to translate pairwise dissimilarities measured We reexamine the modern Yangtze River data geochronology (e.g., Press et al., 1987). The null between sample age distributions (e.g., likeness, set, which comprises 25 sand samples, with an hypothesis of the K-S test is that two sample CPR, or K-S statistic) into Euclidian distances, average of 96 ages per sample spanning nearly distributions are derived from the same distribu- generally into two-dimensional configurations the entire length of the river and its major tribu- tion, thus, a rejection implies that they are drawn (Vermeesch, 2013). In this construct, greater taries, first reported by He et al. (2013) (Figs. 1 from distinct distributions. The results of the plotted distances between two samples, repre- and 3). At the first bend (Shigu), we included age K-S test are contingent on the K-S statistic, or sented as points in MDS configurations, indi-

data from Kong et al. (2012) making the total sample effect size (K-SSE), which is the maxi- cate increasing degrees of dissimilarity. MDS number of zircon U-Pb ages at that location 182. mum difference between the empirical cumula- attempts to find the optimal spatial distribution As part of the He et al. (2013) study, samples were tive distribution functions for each sample. The of the sample points for the matrix of distances

collected in 2008 and 2009 from channel deposits K-SSE is used to calculate the K-S test p-value (e.g., translated dissimilarities). There are mul- (mid-channel, lateral, and point bars) exposed at to evaluate the null hypothesis. The K-S test tiple evaluative loss functions for MDS, but low river levels. They collected riverbed sand in provides a binary representation of whether any the most common is stress (S) (Kruskal, 1964). multiple locations around each sampling site to two distributions are statistically unique from Lower S values, generally <0.1, indicate a good sample a representative mixture at each locale. one another (Table 1). The goal of this approach fit of the translated dissimilarity configuration, The detrital zircon age data are coupled with is to statistically test if downstream samples are while S > 0.2 indicates a poor fit. MDS can be the zircon age distributions of 35 potential bed- derived from the same or different distributions applied to detrital data using either metric or rock sources compiled from the literature (Figs. than their upstream counterparts. nonmetric MDS. Metric MDS uses the absolute 1 and 2). The major geologic provinces encom- As the K-S test is both binary and weighted measures of the dissimilarities to solve for the passed by the Yangtze River catchment and toward the center of age distributions, other configuration and stress value simultaneously described by these 35 bedrock units include the comparison metrics are better suited to highlight (Vermeesch, 2013). Nonmetric MDS ranks the Songpan Ganze complex, the eastern Qiangtang differences between zircon age distributions. dissimilarities (i.e., ordinal data) and numeri- terrane, the Yidun terrane, the Sichuan Basin, the Likeness (Satkoski et al., 2013) and probabil- cally (e.g., isotonic regression) finds the optimal Yangtze craton, the Longmenshan, the Qinling- ity function cross-plot R2 (CPR) values (Saylor configuration by minimizing the loss function Dabieshan fold belt, the South China fold belt, et al., 2013) have been proposed as alternative (Vermeesch, 2013). Along with the stress value, and several smaller geologic provinces that also quantitative metrics of comparison. The value a Shepard plot is a good tool for MDS evalu- may contribute zircons (Figs. 1 and 2). The of CPR and likeness is their sensitivity to both ation (Vermeesch, 2013); here, the measured majority of the 35 bedrock U-Pb age distribu- shapes of components within the distributions dissimilarities are plotted against the translated tions represent the combined zircon ages of mul- and the presence and absences of components. distances, and a better fit to either a linear (met- tiple, genetically related samples (e.g., shared Likeness (Satkoski et al., 2013), or its inverse, ric MDS) or some nonparametric monotonically depositional, emplacement, or metamorphic his- percent area mismatch (Amidon et al., 2005), is increasing function (nonmetric MDS) indicates tories). For example, sandstone samples with a measure of the summed absolute subtracted a better configuration. similar geographic extent, sedimentary facies, difference at incremental age values between For this study we use likeness as measure of

depositional age, and age distributions were two probability curves, where greater dissimi- dissimilarities, rather than K-SSE as originally combined to generate an average distribution larity between two probability curves results in applied by Vermeesch (2013), because likeness for a particular suite of samples, simplifying the larger calculated differences. As both probability more accurately represents the dissimilarities data set. However, great care was taken to not curves are normalized to unity, the maximum between two distributions (Wissink, 2016). Here

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0 125 250 500 750 1,000 Kilometers

8 China 35° N 13

A 32 Jialingjiang Hanjiang 35 N 33 30 O Tibetan Plateau 22 Minjiang 25 Jinsha 9 gtze 34 Yangtze IX n M Daduhe K Ya 29 Ya H G 30° N 5 longjiang V L 7 III I 1 16 2 J 20 6 14-15 II IV F VI VII X g 31 E VIII Ne jian pal Bhutan 23 I jiang Wu Yuanjiang Ganjiang 27-28 12 10 Xiang 17 B D India 25° N 24 C 18 11 21 N Taiwan 3 Bangladesh 19 Burma 4

Vietnam 90° E 100° E 110° E 120° E Figure 1. The Yangtze River catchment and sampling locations. Letters indicate trunk stream location of river sediment samples. Trunk samples: A—Tuotuohe; B—Shigu (First Bend of the Yangtze; note that sample contains data from both He et al., 2014 and Kong et al., 2012); C—Panzhihua-1; D— Panzhihua-2; E—Yibin; F—Chongqing; G—Fuliang; H—Yichang; I—Yueyang-1; J—Yueyang-2; K—Wuhan; L—Hukou; M—Datong; N—Nanjing; O—Changxing Island. Roman numerals indicate the tributary samples (from He et al., 2013, 2014). Tributary samples: I—Yalongjiang; II—Daduhe; III— Minjiang-1; IV—Minjiang-2; V—Jialingjiang; VI—Wujiang; VII—Yuanjiang; VIII—Xiangjiang; IX—Hanjiang; X—Ganjiang. Black filled circles indicate the approximate sampling locations of potential bedrock source zircon age components (for bedrock names and references, see supplementary material). Source sampling locations may represent geologically contiguous units with extents in and outside of the Yangtze River catchment.

90°E 100°E 110°E 120°E 35°N Kunlunshan Qilianshan OB SP

Songpan Ganze THB SYSB Complex Qinling Dabieshan Qiangtang Terrane g

Jialingjiang Hanjian

ngtze Minjian Ya 30°N Lhasa Terrane Yalongjiang Daduhe LMS-DS FB

g SB Yangtze Craton g

Yidun r anjian Himalayan G Wujiang uanjiang N Y XiangjiangSouth China Fold Belt Himalayan Foreland Yangtze Rive (Cathaysia) 25°N Assam North LSB Burma Indian Shield Lincang Baoshan 02125 50 500 750 1,000 Kilometers

Figure 2. Geologic terrane map for the Yangtze River catchment (modified from Burchfiel and Zhiliang, 2013; Hearn et al., 2001). Terranes are colored if they are areally extensive in the Yangtze River catchment (bold black line). OB—Ordos Basin; SP—Shanxi Plateau; THB—Taikang Hefei Basin; SYSB— Subei–Yellow Sea Basin; LSB—Lanping Simao Basin; SB—Sichuan Basin; LMS-DS FB—Longmenshan–Dabieshan fold belt.

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A. Tuotuohe (N = 96)

B. Shigu (First Bend) (N = 182) I. Yalongjiang (N = 98)

C. Panzhihua-1 (N = 103) II. Daduhe (N = 98) D. Panzhihua-2 (N = 95)

III. Minjiang-1 (N = 100) E. Yibin (N = 98)

IV. Minjiang-2 (N = 95)

F. Chongqing (N = 96) V. Jialingjiang (N = 98) G. Fuling (N = 92)

VI. Wujiang (N = 96)

Downstream H. Yichang (N = 89)

VII. Yuanjiang (N = 94)

Probabilities I. Yueyang-1 (N = 94)

J. Yueyang-2 (N = 92) VIII. Xiangjiang (N = 97)

K. Wuhan (N = 97) IX. Hanjiang (N = 95)

L. Hukou (N = 91) X. Ganjiang (N = 92)

M. Datong (N = 97) 0 500 1000 1500 2000 2500 3000 Age (Ma) N. Nanjing (N = 92)

O. Changxing Isl. (N = 113)

0 500 1000 1500 2000 2500 3000 Age (Ma)

Figure 3. Probability density curves for each of the Yangtze River samples. On the right are the 15 trunk stream samples and the left are the 10 tributar- ies samples (locations in Fig. 1; Isl—island). Groups and solid lines extending from the tributaries indicate approximate confluence of these tributaries to the trunk stream. N is the number of zircon grain ages per sample.

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TABLE 1. KOLMOGOROV-SMIRNOV (K.S.) TEST RESULTS, YANGTZE RIVER TRUNK AND TRIBUTARY SAMPLES Upstream to the left (trunk samples) Upstream to the left (tributary samples) . 2 1

Sample Name u ujiang uanjiang eyang- 2 uha n chan g eyang- 1 ibin uotuohe Y alongjiang Yi Y Yu . Minjiang- Jialingjiang Yu Y Chongqing A. T B. Shigu C. Panzhihua-1 D. Panzhihua-2 E. F. G. Fuling H. I. J. K. W L. Huko M. Datong N. Nanjing O. Changxing Is I. II. Daduhe III. Minjiang- IV V. VI. W VII. VIII. Xiangjiang IX. Hanjiang X. Ganjiang A. Tuotuohe -FFF -FFFFFFFFFF------F-- B. Shigu --F---F---F-FF ------F-- C. Panzhihua-1 -F-FFFFFF-F------F-F--- D. Panzhihua-2 --FFFFFFFFFF------FF-- E. Yibin -F-F-FF-FFF------F- F. Chongqing -FFFFFFFFF ------FF -- G. Fuling -FFFF-F------F-F--- H. Yichang -FFFFFFF------FF-- I.Yueyang-1 -FF-F------F-F--- J.Yueyang-2 -F-FFF ------F-- K.Wuhan -FFFF ------F--- L. Hukou -FFF -FFF ---F-F M. Datong -FF------F--- N. Nanjing -F ------F-F O. Changxing Island -- -FF---F-- I. Yalongjiang ------II. Daduhe -FF------III. Minjiang-1 -F------IV. Minjiang-2 ------V. Jialingjiang ------VI. Wujiang ----- VII. YuanJiang ---- VIII. Xiangjiang --F IX. Hanjiang -F X. Ganjiang - Note: F—Failure to reject the null hypothesis. Shaded—Tributaries within the upstream catchment.

we use nonmetric MDS as it yields lower stress both their detrital data set and bedrock source Mixing Model values than metric MDS, which yields stress val- data suggests that these broad age brackets do not ues >0.2. Theoretically, MDS will highlight dif- adequately represent distinct geologic emplace- We apply a mixing model of U-Pb age dis- ferences in the Yangtze trunk stream samples and ment events. Instead, we divide the data set into tributions modified from Lang et al. (2013) to identify which tributaries appear to be the most individual Gaussian components that more effec- assess whether changes in sediment source similar to trunk stream samples, if any. For exam- tively describe the true trunk stream distributions. explain age distribution variations observed in ple, if several tributaries account for the major- Here a component is, at its simplest, a normally the Yangtze River trunk stream detrital zircon ity zircon in the trunk streams, these tributaries distributed suite of ages around some mean value data set. The Lang et al. (2013) mixing model should surround and possibly cluster within the that represents some discrete geologic zircon- determines the optimal mixing proportions of trunk stream samples that are downstream from producing event. Our goal is to identify the potential contributing sources to recreate the the confluence of the tributaries. The remaining variation in the Yangtze trunk stream samples in original distribution with no a priori knowledge tributaries, which contribute minimal zircon to relation to its tributaries and associated bedrock of which sources to include. Source distributions, the trunk stream, should plot at greater distances sources; therefore, we isolate the major compo- here represented by PDFs, are mixed at vary- from the trunk samples around the periphery, nents associated with the trunk stream distribu- ing proportions over a range of possible com- assuming they have distinct age distributions tions, following an approach described in Wissink binations. These mixed PDFs are then quanti- from the contributing tributaries. A dramatic shift and Hoke (2015). The probability density curves tatively compared to the true sample. Mixtures in provenance following the incorporation of a of all trunk stream samples are summed and nor- are generated by multiplying the PDFs of each specific tributary should become readily appar- malized to unity. From this summation, unique source distribution by some percentage contri- ent, with an obvious downstream and upstream age components are identified using a deconvolu- bution (because PDFs are normalized to unity) clustering of trunk stream samples and the down- tion algorithm that fits a Gaussian curve to each and summing each (summed proportions must stream samples closer in configuration to the of the largest (in integrated area) age modes, by equal 100%), resulting in the mixed PDF. An major contributing tributary. Should an upstream minimizing the mean square error for each. The optimal mixing of sources corresponds to the catchment dominate zircon supply, there would two standard deviations above and below the mixture with the highest comparison metric (e.g., be little to no differentiation between upstream mean of each curve define an age component. likeness, CPR, or K-S statistic) to the original and downstream trunk samples. Similarly to He et al. (2014), we calculate the pro- sample comparison. We use likeness (Satkoski et portions of zircon ages within the Yangtze River al., 2013), because it best represents the overall Gaussian Component Breakdown sediments for each defined component. This is shape of the distributions. We apply the mixing achieved by integrating the probability density model to the detrital sediments of the Yangtze He et al. (2014) divided the Yangtze River functions (PDFs) for each sample between the River using two separate constructs of source, data set into 6 age brackets based on visual end points defined by each component. Using this bedrock and upstream modern sediments. assessment of the sample age distributions; approach, we identify the major components and For the first model, sources are defined as their age intervals were 0–65 Ma, 100–300 Ma, their overall variance within trunk stream sam- any possible contributing lithologic unit, rang- 300–600 Ma, 600–1000 Ma, 1700–2000 Ma, and ples. We can use these component percentages to ing from large sedimentary sequences to local- 2000–2700 Ma. However, closer inspection of make components inferences that are more robust. ized plutons. The contribution of a bedrock unit

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to a trunk stream sample is contingent on its RESULTS with the Yangtze River occurring in the lower inclusion within the drainage area upstream of quarter of the catchment (Fig. 1; Table 1). Of a sample collection location. The compilation of Results of K-S Test, Likeness, and CPR the tributary-to-tributary comparison, only three lithologic units are presented in Figure 1, with Values pairs of tributaries fail to reject the null hypoth- either the exact geographic coordinate given for esis: the pairs of Daduhe-Minjiang, Xiangjiang- single representative sample, or approximate The K-S test was used for each pairwise cou- Ganjiang, and Hanjiang-Ganjiang samples. The locations for aggregates of related samples. pling of the Yangtze River trunk and tributary trunk-to-tributary and tributary-to-tributary com- In the second approach, we assume that the samples. The results are summarized in Table 1, parisons suggest far greater variation among trib- sources of the Yangtze River trunk stream sedi- where an F indicates a failure to reject the null utary samples, possibly making more focused ments are described by the mixture of U-Pb age hypothesis, meaning that, statistically, the sam- and less binary characterization possible. It is distributions of the upstream trunk and tributary ples are likely not derived from different distri- important to note that although a trunk stream samples. Ideally, the model would exclusively butions. Two-thirds of all Yangtze River trunk- sample may reject the null hypothesis in trunk- use tributary distributions to represent the fluvial to-trunk sample comparisons fail to reject the to-tributary comparison, this does not preclude system. However, the upstream area from the null hypothesis, indicating shared provenance the possibility of the tributary contributing to the sampling points of He et al. (2013, 2014) often with no obvious differentiation between the trunk stream sediment budget. It only suggests only represent a portion of the full tributary upper and lower reaches of the trunk stream that the trunk stream sample is not exclusively catchment, and are not at the point of confluence. samples. The trunk samples that appear to have derived from a given tributary. Considering only the tributary catchment areas the strongest differentiation, i.e., reject the null Likeness and CPR values, which are more upstream of the He et al. (2013) sampling loca- hypothesis most frequently, are at the first bend sensitive to the overall similarities and differ- tions, the tributary catchments compose only of the Yangtze River (Shigu; Fig. 1, sample B), ences in the detrital U-Pb age distributions, 25%–58% of the upstream catchment area at and at Yibin (Fig. 1, sample E), suggesting a yield similar results to the K-S test (Fig. 4). any trunk stream sample (Fig. 1), and, therefore, greater uniqueness (Figs. 2 and 3; Table 1); how- Likenesses of trunk-to-trunk comparisons vary ignore ~50% of the possible contributing area. ever, these samples still fail to reject the null between 37% and 63%, with an average of 52% To mitigate this, we include all upstream tribu- hypothesis in 40% and 47% of all trunk-to-trunk ± 6% (Fig. 4A). Despite the wide range of ages tary and trunk sample distributions as possible comparisons, respectively. In contrast, only 18% in the Yangtze River samples, the mean value source contributors for the mixing model. This of trunk-to-tributary comparisons fail to reject for trunk-to-trunk sample comparisons is rela- approach is predicated on each fluvial sample the null hypothesis, indicating far greater vari- tively close to the lower threshold of maximum adequately representing the integrated U-Pb dis- ability in provenance within the tributary age likeness value of 72% ± 6% established by sam- tributions of its upstream catchments, despite distributions compared to the trunk. The shaded pling a single, multimodal parent distribution for being composed of a finite number of ages. portion below the bold black line in Table 1 high- multiple 100-age samples (Satkoski et al., 2013). In practice, it is difficult to identify more lights the tributaries that are upstream of the Tributary-to-trunk comparisons yield lower like- than 10 unique sources with confidence, given trunk samples of the same row. The tributaries nesses from 23% to 61% with an average of random sampling uncertainties as well as large most closely resembling trunk samples (using 46% ± 7% (Fig. 4B). Intertributary comparisons computational times. For the bedrock-source the K-S test) are from the Xiangjiang, one of yield the lowest values of 42% ± 10% (Fig. 4C). scenario, there are more than 30 possible con- the tributaries identified by He et al. (2014) as CPR values follow a similar pattern to likeness tributing sources for trunk samples collected a principle sediment contributor, and Yuanjiang. (Figs. 4D–4F), although exhibiting more scat- in the lower Yangtze River reaches. Therefore, This is despite the merger of these tributaries ter and lower average values with an average of we modify how the mixing algorithm is applied depending on the number of potential contrib- uting sources. When fewer than 7 sources are identified as possible contributors, the mixing Trunk-to-Trunk Trunk-to-Trunk N = 105 A D algorithm uses all combinations of source PDFs at 5% incremental changes. For 8–12 possible sources, the incremental changes are increased to 10% for computational efficiency. If the total Trunk-to-Trib Trunk-to-Trib number of possible contributing sources exceeds N = 150 B E 12, we use a grid search technique that prioritizes those sources with the highest initial similarity metric values of source to sample comparisons Trib-to-Trib Trib-to-Trib (see Supplementary Material in the GSA Data N = 45 C F Repository1) to determine the optimal mixture for each detrital sample. The grid search tech- nique will be biased toward sources with initially higher similarities. 0.2 0.4 0.6 0.8 0 0.2 0.4 0.6 0.8 Likeness Value CPR Value 1 GSA Data Repository Item 2016285, which includes four additional figures, one movie of a 3-D MDS visual- Figure 4. Intersample likeness and probability function cross-plot R2 (CPR) values. Results ization, an overview of the mixing model, and a list of shown using the likeness comparison metric (left) and CPR values (right) for trunk-to-trunk, references used for bedrock U/Pb ages, is available trunk-to-tributary (Trib.), and tributary-to-tributary intersample comparisons. N equals the at www.geosociety.org/pubs/ft2016.htm, or on request number of comparisons per histogram. Higher values indicate higher similarity between from [email protected]. pairwise comparisons. Note that the trunk-to-trunk comparisons are on average higher.

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trunk-to-trunk CPR values of 0.26% ± 0.13%. large tributary for each of the respective trunk the Yangtze River trunk stream distributions The tributaries with the highest CPR and like- stream samples. The tributaries (unfilled circles) (Fig. 6A). However, just 6 describe 75% of the ness values in trunk-to-tributary comparisons plot on the outer rim of the MDS map (Fig. 5), total variance. In decreasing order of propor- are the Daduhe, Minjiang, Yuanjiang, and Hanji- ringing the trunk samples. While this configu- tional contribution and given in the format of ang tributaries, with no relationship between ration may suggest that all tributaries are con- m – 2s: m + 2s, these 6 are 675–904 Ma, 1734– downstream incorporation and high values tributors in some fashion, the clustering of trunk 1974 Ma, 389–481 Ma, 199–225 Ma, 2417–2605 (see Supplementary Tables 1 and 2 in the Data stream samples demonstrates a lack of down- Ma, and 2342–2492 Ma. These ranges represent Repository). Assuming a significant single shift stream differentiation. Of the 10 Yangtze River substantial revisions to those described by He et in provenance, one would expect some bimodal- tributaries, those closest to the trunk sample clus- al. (2014) through visual assessment. Using the ity in likeness values of the intertrunk compari- ter are the Minjiang, Daduhe, and Jialingjiang Gaussian components defined here, we calcu- sons driven by samples downstream exhibiting tributaries, all of which occupy the northwestern late the proportions of each component in every a positive increase in comparative likeness and portion of the Yangtze River catchment, and cor- Yangtze River sediment sample, individually, decrease compared to the upstream samples. It is respond to tributaries identified by Vezzoli et al. and the average proportion of each component clear that there is no such step function present in (2016) as major sediment contributors. for the trunk sediment samples. This average the measures of similarity of downstream versus allows us to examine the deviation of each sam- upstream samples. Trunk samples exhibit strong Results of Gaussian Component Analysis ple age distribution from the trunk stream mean overall similarities, particularly at the confluence value for each component (Fig. 6B). The mean of the Yalongjiang at Panzhihua. We identify 15 prominent components that value for each component is normalized to zero, define ~80% of the overall variance within and the deviation for each sample is given as a Results of MDS

The variability in the Yangtze River data 0.8 set using MDS is summarized in Figure 5; the Stress =0.14 MDS configuration results in a strong clustering of trunk stream samples (filled circles) in the Ganjiang 0.6 center of the MDS map. This clustering closely resembles the scatter seen when randomly sam- 0.4 pling ~100 ages from a larger population of Xiangjiang 0.2 ages, highlighting their overall similarity while Hanjiang

Distances/Disparities 0.2 also lending no evidence of significant changes Yuanjiang in provenance further downstream. This is not Yueyang-2 unexpected, given the results of the likeness test. 0 0.1 Nanjing 0 0.2 0.4 0.6 0.8 The four trunk samples, nearest the mouth of Daduhe Dissimilarities the Yangtze River (Hukou, Datong, Nanjing, and Shigu Minjiang-2 Changxing Island), show no dramatic differen- Changxing Isl. Minjiang-1 tiation in MDS with samples collected from the Yalongjiang upper reaches. The minimal geographic clus- 0 Wuhan Panzhihua-2 Datong Hukou tering of samples observed (i.e., minor upper Tuotuohe versus lower trunk stream separation) is not unexpected, because proximity should lead to a Yueyang-1 Fuling Yibin certain degree of similarity. The nearest neighbor -0.1 Yichang lines (samples with highest and second highest Panzhihua-1

Chongqing Downstream Downstream l likeness values between them), however, hint at 1 g 1 2 its limited significance. There is an apparent shift Jialingjiang g n u u hihua− downstream of Shigu toward the Daduhe, Minji- -0.2 yang−yang− otuohe nz e njin uha ang, and Yalongjiang tributaries, suggesting that ue Tu Shig Pa Panzhihua−2 Yibin ChongqinFuliang YichangY Yu W Huko DatongNa Changxing Is the Jinsha portion (upper reaches) of the Yangtze g

iang may contribute less than the tributaries feeding Wujiang ng−1 j jia Daduhe jiang−2 Wujiang off the east and southeast margins. The trunk in HanjiangGanjiang Yuanjiang -0.3 ialing M Min Xiangjiang samples furthest from the center include Tuo- Yalongjian J tuohe, Shigu, Yueyang-2, and Yibin. Tuotuohe -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 and Shigu represent the upper reaches and least Figure 5. Multidimensional scaling (MDS) plot of Yangtze River data. The nonmetric MDS plot (main) integrated portion of the Yangtze River and thus and Shepard plot (inset) for the translated configuration of dissimilarities (likeness) for the Yangtze possibly differing provenance or limited contri- River data set. Trunk stream samples are given as filled colors, with warmer colors (red-orange-yellow) butions to the river downstream of Panzhihua, indicating farther downstream sampling; tributary edge colors indicate downstream location. Solid mirroring the results of He et al. (2014), Zhang and dashed lines indicate the closest neighbors and second closest neighbors in likeness, respec- et al. (2014), and Vezzoli et al. (2016). Yibin and tively. Greater interpoint distances indicate greater dissimilarity between samples. Inset: Shepard plot for the given data. Points represent the scatter plot of the measured dissimilarities (likeness Yueyang are more closely linked to the Yalongji- values) versus the distances in MDS space. Because the MDS is nonmetric, the monotonic function ang and Xiangjiang tributaries, respectively; both that best translates the data (red line) is calculated numerically. Better fits plot closer along function tributaries represent the immediately preceding line. A stress value of ~0.14 indicates a fair translation of the data (Kruskal, 1964) into MDS space.

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Gaussian Components (Ma) 283−351 34−48 389−481 A 122−144 537−565 149−161 572−624 164−176 676−904 199−225 1734−1974 Summed Trunk Distribution 244−258 2342−2492

Probability 262−284 2417−2605

0 500 1000 150020002500 3000 Age (Ma)

1 1 ing -2

n han bi ichang ueyang- Tuotuohe Shigu (FB) Panzhihua-Panzhihua-2 Yi ChongqFuling Y Y YueyangWu Hukou Datong Nanjing Changxing Isl. 30

s Modeled range of 20 B deviation from mean 10 0 -10 Deviation from μ

Percentage Point Trunk Samples -20 Approximate Distance Downstream

34-48 (μ = 1.3%) 30 199-225 (μ = 5.5%) s 20 389-481 (μ = 6.4%) Modeled range of 676-904 (μ = 22.4%) deviation from mean 10 1734-1974 (μ = 16.6%) 0 2342-2492 (μ = 3.8%) -10 2417-2605 (μ = 4.9%) Deviation from μ Percentage Point Tributary Samples -20 g g g g ng n ng a a ng-1 ji a Daduhe Wuji Hanjia Gan MinjiMinjiang-2 XiangjianYuanjian Yalongjiang Jialingjian

30 Synthetic Components Comp-5.5% 20 C Modeled range of Comp-1.3% Comp-6.4% lu e deviation from mean Comp-3.8% Comp-16.6% Va 10 Comp-4.9% Comp-22.4%

0

-10 Population

Deviation from Mean Synthetic Samples -20 123456789101112131415 Resample Number from Single Distribution of Ages

Figure 6. Results of the Gaussian component analysis of the Yangtze River data set. (A) The black line indicates the summed curve of all trunk stream samples of the Yangtze River. The colored, dashed curves are the Gaussian components that best describe the overall variance of the data set. The range of each curve at ±2s from the mean value is given in the legend in millions of years. (B) The deviations (in percentage points) in proportion of the seven components, which account for >75% of the overall variance of the Yangtze River, at each sampling location from the mean value (m) of that component; m is given as a percentage in the legend. Top of B is for trunk samples; bottom is for tributary samples. Vertical dashed lines indicate the confluence point of the tributaries. Note that the Daduhe and Minjiang tributaries share a confluence point, as do the Xiangjiang and Yuanjiang tributaries. FB—First Bend. (C) Model of deviation plot for synthetic unique components with proportions equivalent and color coordination to the seven components in B. Note the similarity in curve shapes to trunk samples of B. The shaded pink areas in B and C represent the approximate range of deviations seen in the synthetic distribution of C, overlain on the plots of B. This shows how the variability seen in the trunk stream samples of B is difficult to separate from random sampling.

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percentage point difference between the mean We examine how much variance one can excluded nine from any of the sample optimal value and the proportion within that sample. For expect if a single distribution of ages containing mixtures. For geographic and geologic simplifi- example, if component one has a mean value of seven unique components in proportions consis- cation, we can further reduce the number of geo- 20%, and the sample Z age distribution contains tent with the trunk stream averages (Fig. 6B; µ logically distinct bedrock units to 17 units that 25% component one, it would be represented as values) is sampled randomly to create 100-age contribute in one or more optimal mixtures. The a +5 percentage point (pp) deviation for sample distributions. To do so, we create distribution full 26-source mixture model can be found in the Z from the normalized 0 mean value. In Figure of 100,000 ages composed of 7 components in supplementary material in the Data Repository. 6B, we plot the deviations of the 6 components proportions equal to the trunk stream averages of The units of the Songpan Ganze complex described here as well as the Cenozoic compo- Figure 6B. This is done by assigning each com- (SGC), the Triassic flysch deposits found near nent of 34–48 Ma to better match the components ponent an age defined by the mean age of the the headwaters and left-bank tributaries of the of He et al. (2014). The deviations for the remain- Gaussian component. Because the averages of upper Yangtze River (Fig. 1 and I–IV, Fig. 7A) ing components can be seen in Supplementary the 7 components sum only to 61%, the remain- show a clear dominance in zircon supply to mod- Figure 3 in the Data Repository. A striking fea- ing ages of the distribution are randomly, uni- ern trunk stream sediments. Deposits related the ture revealed in Figure 6B is the low deviation formly distributed between 1 and 3000 Ma. This southern depocenter of the SGC (Weislogel et from the mean value for nearly all components distribution of ages is then randomly sampled al., 2010) make up the majority of contribut- for trunk stream distributions, generally within with replacement, to represent a nearly infinite ing sediments from this complex (see Supple- ±5 pp, throughout most of the fluvial system source of ages, for 15 (number of trunk stream mentary Table 3). Sediments from the Qamdo downstream of Shigu. The same cannot be said samples) 100-age samples. The proportions and Basin, which shares a depositional history with for the tributary component proportions, which deviations from mean values for each compo- the SGC (Shang and Weislogel, 2014), and the differ widely, deviating 10–20 pp from the mean nent in each sample are then calculated. The Jurassic sediments of Yunnan Provence (Su et al., trunk values for the same components (Fig. 6B). results of this model yield nearly indistinguish- 2014), are included in two-thirds of trunk optimal The establishment of the mean component able curves from the majority of trunk stream mixtures. These units each have likeness values values for the trunk stream appears to occur in samples found downstream of the First Bend of exceeding 45% with the southeast depocenter of the upper Yangtze River between Shigu, where the Yangtze. The results of a single model run the SGC, and thus may be difficult for the mixing component deviations are high (10–20 pp), and are given in Figure 6C. In multiple model runs, model to differentiate, although all are present Panzhihua, where trunk stream proportions settle components with of a mean value between 1% in the northwestern margin of the Yangtze River around the mean (Fig. 6B). Following Panzhihua, and 4% yield standard deviations generally of catchment. By simply grouping sources derived trunk stream proportions rarely deviate signifi- ±1.5–2.5 pp (1s), 5%–10% components have from geologic terranes upstream of sample Pan- cantly from mean proportions (pink in Fig. 6B). standard deviations of ~±2–3 pp, and compo- zihua-2, optimal trunk mixtures are composed There are clear spikes of certain components at nents with >10% yield standard deviations of of 65%–100% of these bedrock units, averag- trunk stream sites near Yibin (676–904 Ma) and ±2.5–5.5 pp (Fig. 6C). Therefore, the possible ing ~85% for the 15 trunk stream distributions. Yueyang (389–481 Ma). Both increases occur deviations of a single random sampling can be Together this grouping constitutes <20% of the after the incorporation of tributaries containing >±10 pp, particularly for larger components, but overall area of the Yangtze River catchment. higher than average proportions of those spe- <±10 pp deviations are difficult to distinguish Two volcanic units associated with the Long- cific age components (see tributaries Minjiang from random draws. Samples from Yibin and menshan Range and South China block both and Daduhe, and Xiangjiang). Nonetheless, they Yueyang-2, which show the largest and likely not share Neoproterozoic emplacement ages and immediately return to proportions closer to the randomly derived deviations, are easily associ- make clear contributions to the trunk stream sam- mean value by the next downstream trunk sam- ated with immediately upstream tributaries. The ples; these units, in dark red and pink, respec- ple. The trunk samples with the greatest distance remaining trunk samples at and downstream of tively, in Figure 7 are essentially unimodal and downstream from the incorporation of any major Panzhihua exhibit a striking resemblance to the share a 33% likeness. While less likely to affect tributary are Yichang, Nanjing, and Changxing simple model, suggesting shared provenance. the final mixture output of <12 sources, these Island, and are likely the most homogenized. units may be difficult for the grid-search mix- These samples have roughly equal proportions Results of Yangtze River Mixture Models ture model to differentiate. Following the incor- to Panzhihua; in other words, they show no poration of the Ganjiang and Yuanjiang Rivers, greater deviations in mean values than would be The results of the mixture model applied to which both have very high South China block expected from multiple random 100-age draws the Yangtze River data set are described here and components, we observe an increase in South from a single distribution of ages with compo- illustrated in Figure 7. The optimal mixtures of China–derived units in the mixture model at the nent proportions consistent with trunk stream bedrock sources achieved likeness values of rang- apparent expense of Longmenshan units. The averages (Figs. 6B, 6C; shaded area). The low ing from 57% to 75% when comparing the mixed similarity between Longmenshan and South deviation in values around the mean of the trunk distributions to the original sample distributions. China block Neoproterozoic zircon make it dif- samples (Fig. 6B), and the relatively high devia- Of these bedrock mixtures, the Yangtze River ficult for this simple mixture model construct to tion for tributary samples (Fig. 6C) match well trunk samples, with the exception of Tuotuohe in differentiate between them. Neoproterozoic ages with the results of the K-S test and calculated the headwaters, yielded maximum average like- account for ~5%–25% of the overall composi- dissimilarity values. The high deviations in val- nesses of 67% ± 4%, within the achievable 100- tion of our mixtures. Other minor contributors ues of tributary samples, and thus, the unique- age resampled likeness of 72% ± 6% described include Cenozoic volcanics, the Laji and Dabie- ness of these age distributions, also suggests that by Satkoski et al. (2013). Tributaries also return shan mountain ranges, and sediments from the any major flux of sediments from one or more similar averages of 67% ± 5.5% (see Supplemen- Sichuan Basin. tributaries should appear and persist downstream tary Table 3). The bedrock source distribution The second mixture model using major tribu- of its incorporation, depending on how sediment data set consisted of a maximum of 35 possible taries and upstream trunk samples as sources flux varies downstream. source units; the results of the optimal mixtures for the downstream trunk distributions (Fig. 7B;

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90°E 100°E 110°E 120°E 35°N A A N O QT QDS Jialingjian Hanjiang NYB M LMS K Yangtze H SGC Minjiang SB

g L Daduhe Y F 30°N alongjiang G J Bedrock Mixing Model I Y Songpan Ganze Complex Qiangtang Volcanics (T) E YC ang

Zheduo-Gonggar Massif Yidun Group g Yunnan S.S. (J) Jomda Weixi Arc (T) g ujiang Ganji Qamdo Basin Longmenshan (Neopro.) B W D Yuanjian CA-SC Dabieshan Yangtze Block South China Plutons (Neopro.) Xiangjian N Cenozoic Volcanics Yangtze Craton C 25°N Cathaysia - Oujiang Sichuan Basin S.S. (J) CB Cathaysia - North River Caledonian 02125 50 500750 1,000 South China - Caledonian Kilometers

35°N B A N O

Jialingjiang Hanjiang M K H Minjiang 30°N F L

Yalongjian Daduhe G J Yangtze I Fluvial Mixing Model E Tuotuohe Yichang Yalongjiang g Shigu Yueyang1 Daduhe-Minjiang(1-2) g g Panzhihua1 Yueyang2 Jialingjiang g ujian Ganjiang Panzhihua2 Wuhan Wujiang B D W Yuanjian Yibin Hukou Hanjiang Xiangjian N 25°N Chongqing Datong Xiangjiang C Fuling Nanjing Ganjiang Yuanjiang 02125 50 500750 1,000 Trunk Distributions Kilometers Tributary Distributions 90°E 100°E 110°E 120°E Figure 7. Model results for the Yangtze River data set; results are for mainstream samples (labels as in Fig. 1). Pie charts represent optimal mixtures of bedrock (A) and fluvial (B) components for each sample. (A) Model results of mainstream samples of the Yangtze River using mixed bedrock zircon age data. The Yangtze River catchment is outlined by the heavy black line; tributaries are outlined by thin black lines. Trunk stream samples contain dispro- portionate zircons from the Songpan Ganze complex and Longmenshan. Major geologic terranes are colored and labeled as follows: QT—Qiangtang terrane; SGC—Songpan Ganze complex; SB—Sichuan Basin; TU—transitional unit; YC—Yangtze River craton; CA-SC—Cathaysia–South China; QDS— Qinling–Dabishan fold belt; LMS—Longmenshan fold belt; Y—Yidun unit; NYB—Nanyang Basin. Geologic terranes map is modified from Burchfiel and Zhiliang (2013) and Hearn et al. (2001). In legend: T—Triassic; J—Jurassic, Neoprot.—Neoproterozoic, S.S.—Sandstone. (B) Results of fluvial mixture model for trunk stream samples of the Yangtze River, using upstream fluvial samples as sources. Colored map regions represent the corresponding catchments for each tributary and correspond with colors of the pie chart. Trunk stream samples within the pie charts are represented as red outlined slices and show continual, disproportionate inclusion of ages derived trunk rather than tributary sources.

Supplementary Table 4) yields optimal mixtures remaining samples, those near Yibin, Fuliang, grains in the mixing model (Fig. 7B). This is with far stronger trunk stream contributions Yichang, and Wuhan range from 30% to 55% notable, given that the Wujiang River only than tributary contributions. There are 12 trunk trunk stream contributions. Yibin, due to its accounts for ~8% of the total catchment area at stream samples that contain at least one major high Neoproterozoic concentrations, favors the the sample locations. Figure 7 shows that these tributary within their catchment, 8 of which are incorporation of the Yalongjiang. It is interest- two samples both have slightly higher than aver- best described by mixtures that contain >70% ing that this is despite the obvious lack of strong age Paleoproterozoic age zircons and may be trunk stream zircon (red outlined wedges of pie Neoproterozoic age proportions at Panzihua-2 why Wujiang, which shares this characteristic, charts; see Fig. 7). These require minimal con- immediately following the incorporation of the is favored in the model. Samples at both Yibin tributions from tributaries to push the mixing Yalongjiang (Fig. 7B). Fuliang and Yichang have and Yueyang-2 mirror the results shown in Fig- model toward higher optimal metric values. The elevated incorporation of the Wujiang tributary ure 7, where higher than average concentrations

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of particular age modes of the most immedi- of higher than average erosion or zircon fertility sampling the same catchment. Therefore, it is ately incorporated tributaries lead the mixture from these tributaries. However, following these likely more related to variation in the homogeni- model to include higher than expected tributary jumps in contribution from the nearest upstream zation of the samples at the specific sample loca- concentrations. tributary, the high signal is consistently lost at tion. We note, as did Vezzoli et al. (2016), that the the next downstream trunk sample (Fig. 6B). For data from the Yalongjiang tributary in Yang et al. DISCUSSION the remaining samples, the deviations from mean (2012) match much more closely the component trunk stream values are essentially impossible to proportions at Panzhihua-2 and downstream sed- Statistical and quantitative analysis is critical distinguish from the noise of random sampling iments, indicating that it may hold more signifi- to our understanding of large detrital data sets. (Fig. 6C). The uniformity of the remaining trunk cance than is initially apparent due to its dispro- By applying rigorous quantitative techniques samples suggests either poor homogenization of portionately high Neoproterozoic concentrations. to the Yangtze River data set, we are able to the tributary sediments in the trunk or remobi- We therefore believe that the samples at Yibin reevaluate and expand upon the work of He et lization of stored sediments. If we assume that and Yueyang-2 likely reflect poor homogeniza- al. (2014). Each analysis of zircon ages explored concentration spikes are indicative of drainage tion of the sediment downstream of a major con- here demonstrates that the zircon U-Pb age dis- dominance, as He et al. (2014) argued, then one fluence point or source with disproportionately tribution of the Yangtze River is established early could assume that reworked sediments from ter- high component concentrations causing a spike in its upper reaches near the sampling location races could add an additional flux of sediment in sample concentrations. of Panzhihua-2 and is, on average, statistically that renormalizes the zircon age signal. However, The issue of poor homogenization is recog- invariant downstream. Proportions of identified this supposition requires the sediment of the river nized as a pitfall in detrital studies. If a sample significant age components downstream of the terraces, and thus total sediment flux, be domi- in modern fluvial systems can potentially be so first bend, with the exception of samples from nated by sediment from the upper reaches, sup- easily biased by a nearby contributor and does Yibin and Yueyang-2, are consistent with the porting our initial claim. This also requires that not necessarily reflect the true upstream integra- sampling of a single distribution of ages (Fig. the rate of remobilization would need to exceed tion, it becomes difficult to say whether pre- 6). This at least partially refutes the claim of He the sediment flux of the tributaries. However, served ancient sediments are not susceptible to et al. (2014), who argued that the tributaries of if we assume that the spikes in concentration the same problem. Future tests may focus on the the Hanjiang, Xiangjiang, and Jialingjiang, and represent poor homogenization, much like sam- variation in trunk stream components between the trunk between Panzhihua and Yibin, consti- pling dye concentrations right near the point of the confluence of two major tributaries rather tute the largest contributions of sediment to the input, then the total remobilized sediment does than immediately before and after major conflu- Yangtze. The conclusion of He et al. (2014) relied not need to exceed tributary flux, making poor ence points, as is more common. heavily on a coarse grouping of zircon age com- homogenization seem most likely. Looking spe- ponents and just eight bedrock units to charac- cifically between Yibin and Chongqing, there is a MDS Discussion terize the structural blocks of the Yangtze River 24% increase in total catchment area; 70% of the catchment, a total that we have greatly expanded increase is from the addition of the Jialingjiang MDS analysis also supports the notion of a upon and refined here. Our more robust bedrock catchment. Using the component concentrations shared derivation of zircon at and downstream data set, Gaussian component analysis, and mul- at Yibin, Chongqing, and the Jialingjiang, and of Panzhihua. Within MDS space, the progres- tiple techniques to analyze zircon age distribu- assuming equal fertility (Vezzoli et al., 2016), sive incorporation and dominance of zircon ages tions argue for the more tectonically active and a simple mass balance calculation determines from downstream tributaries would result in a steeper topographic regions of the Yangtze River that over an order of magnitude greater sediment drift in zircon ages across MDS space. Instead, catchment to dominate the sediment budget of flux from the Jialingjiang catchment is required we observe the majority of trunk stream samples the modern river. to compensate for the component proportions clustering together in MDS space centered on at Chongqing. This is inconsistent with erosion the Panzhihua trunk stream samples, suggest- Measures of Similarity and Deviations rates estimates of these catchments (Chappell et ing little deviation in zircon age downstream of al., 2006; Kong et al., 2011), and supports the those sampling localities (Fig. 5). Unfortunately, The K-S test demonstrates a consistent, seem- notion that the spike in zircon concentration at because MDS is projecting an N-dimensional set ingly shared provenance for the vast majority of Yibin and subsequent decrease to mean values of data into two or three dimensions, the true the trunk stream samples along the length of the at Chongqing is due to poor homogenization at projection of the relationship between samples Yangtze River. This argument is at least bolstered Yibin and homogenization at Chongqing. This is can be difficult to interpret. The low variability by the rejection of the K-S test null hypothesis not to suggest that flux from the Jialingjiang does in dissimilarities between samples also leads to in most trunk-to-tributary comparisons, dem- not also help bring components back to mean the poor projection into two dimensions (Fig. 5) onstrating that no one tributary dominates the trunk values, but a ten-fold increase in sediment and three dimensions (see supplementary mate- fluvial system, but rather it is the left-bank tribu- load is unrealistic. Sample selection effects are rial), as a maximum of three samples of equal taries that supply the most zircon. The K-S test, further highlighted by comparing the data of He dissimilarity in two dimensions, or four samples likeness, CPR, and component deviations from et al. (2014) to the data of Yang et al. (2012), in three dimensions can be perfectly configured; the mean trunk values all point toward a uniform looking specifically at Yalongjiang. In He et al. any more leads to distortion of the configura- character of the detrital zircon component down- (2014), the sample from the Yalongjiang has tion. MDS configurations are not sensitive to the stream of Panzhihua. The few trunk samples that Neoproterozoic ages proportions >70%, while geographic relationships between samples (i.e., exhibit large variations in components occur Neoproterozoic ages only account for 40% in upstream versus downstream), only of the best immediately downstream of specific tributar- the Yalongjiang sample from Yang et al. (2012). ordination for the measure of dissimilarity, so ies or within zones of known higher concentra- This difference is well outside the range of ran- caution must be taken when analyzing scatter tions (Fig. 6B). It is plausible to assume that the dom sampling error and cannot be attributed to in MDS plots. We argue that the overall striking upward spike in zircon contributions is indicative higher erosion rates or sediment flux as they are clustering of both upper and lower reaches of the

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Yangtze sediment highlights the minimal varia- et al., 2010), are the principle contributors to sed- weight to U-Pb changes in individual samples tion in age distributions and thus provenance iment reaching the East China Sea. Both studies rather than to the overall characteristics of U-Pb moving downstream. noted that the higher contributions of these tribu- ages of the Yangtze. The notable increase in taries and regions correlate well with slope steep- contributions associated with Neoproterozoic Mixture Model Discussion ness, precipitation, stream power, and tectonic zircon related to the South China block in our hazard (Zhang et al., 2014; Vezzoli et al., 2016). mixing model is the one outlier in our results. Our mixture models, both of bedrock mix- Vezzoli et al. (2016) found that the Hanjiang is However, the contributions of the South China tures and upstream tributary mixtures, further a relatively significant contributor, contributing block never exceed 20% in optimal mixtures, support our supposition of a quickly established >20% of the sediment load, and gave less weight averaging ~11%, which closely resembles the and maintained zircon age distribution for the to the Yalongjiang tributary. The Hanjiang being 6%–10% areal proportions of the Xiangjiang Yangtze. In the bedrock model we find that high a major contributor downstream does not nec- and Ganjiang tributaries that source the South concentrations of eastern Tibetan Plateau bed- essarily conflict with our interpretations, as its China block. Without more data to distinguish rock units yield the highest likeness values of any overall zircon characteristics share key ages with Longmenshan from South China block Neo- mixture model, reaching likenesses near the pro- the other left-bank tributaries. The contribution proterozoic ages, it is difficult to determine posed threshold of 72% ± 6% established by Sat- of the Hanjiang would likely blend with the whether these Neoproterozoic zircons are cor- koski et al. (2013). Although we do not test all U-Pb ages signal seen upstream. rectly grouped with the South China block units possible mixtures for samples containing 12 or The results of the fluvial sediment-mixing or merely incorrect substitutions of their western more possible contributing sources, nor can we model (Fig. 7B) are consistent with the previ- Longmenshan counterpart. Vezzoli et al. (2016) guarantee that similar age distributions are not ously established results that the sediment of the estimated that right-bank zircon concentrations substituted at the expense of the correct source trunk stream and left-bank tributaries dominates are an order of magnitude higher than those of (e.g., South China block versus Longmenshan the U-Pb age signal of trunk samples. The major- the left-bank tributaries. One would expect that Neoproterozoic ages), the corroborating results ity of trunk stream samples downstream of Pan- a shift in zircon provenance driven by the right- of the bedrock mixture model with the previously zhihua are best described by mixtures of almost bank anthropogenic input should therefore be described methods suggest a high confidence in exclusively trunk stream sediments. Notable amplified, an amplification we do not see. the overall results of the bedrock-mixing model exceptions, such as samples near Yibin and Yuey- Our analysis of provenance is limited exclu- and interpretations. The U-Pb age distribution of ang-2, can be attributed to high proportions of sively to U-Pb zircon ages and could potentially the Yangtze River is arguably fixed after the river particular components linked closely to recently be refined with a second layer of data, such as

traverses the upper reaches of the Yangtze, which incorporated tributaries that do not maintain con- cooling ages (e.g., Reiners et al., 2005), eHf (e.g., largely sources the SGC and the Longmenshan. sistently high proportions downstream. Andersen et al., 2011), or using Th/U ratios (e.g., The Longmenshan zircon, or more specifically L. Wang et al., 2014). Other limitations endemic Neoproterozoic zircon, is commonly found in Tectonic vs Anthropogenic Driven Erosion to nearly all regional- and continental-scale the Longmenshan mountain range and surround- detrital zircon provenance include potentially ing regions of the upper reaches of the Yangtze Based on our analysis, the interpretation of incomplete descriptions of zircon ages from River, at and downstream of Panzhihua, and the enhanced erosion within the Hanjiang, Jialingji- source terranes, because these are typically com- Yalongjiang, Minjiang, Daduhe, and Jialingji- ang, and Xiangjiang catchments due to anthro- plex and strikingly different. The Wujiang mix- ang tributaries. Therefore, the high exhumation pogenic activity proposed by He et al. (2014) ture (see Supplementary Fig. 3) is predominantly rates at the eastern margin of the Tibetan Pla- cannot be substantiated. Anthropogenic activ- derived from the Sichuan Basin despite its rela- teau (Kirby et al. 2012; Densmore et al. 2007; ity clearly plays a significant role in the overall tively minor areal contribution to the Wujiang Wang et al., 2012) likely provide much of the movement of sediment on Earth (Wilkinson and catchment. The Yuanjiang catchment does not Yangtze’s overall sediment load. This is consis- McElroy, 2007), and future studies may focus on contain the Sichuan Basin and results in a very tent with well-documented large sediment flux examining the zircon U-Pb age characteristic of different mixture despite the shared South China to valleys (Parker et al., 2011) after large earth- remobilized soil. However, in no analysis per- block catchment. This implies either that the quakes. Such persistent, far-traveled, geochemi- formed here is there evidence that these tributar- Sichuan Basin is much more fertile in zircon or cal signals that traverse thousands of kilometers ies contribute disproportionately to the overall has considerably higher erosion rates. of lowlands are not unique to the Yangtze, as is trunk stream catchment, while it appears the evidenced by data from the Amazon River (e.g., right-bank tributaries of the southern catchment CONCLUSIONS Dobson et al., 2001; Wittmann et al., 2011). It do not dominate the sediment flux. Vezzoli et al. is important that our results are consistent with (2016) argued that the mischaracterization of He We reinterpret the Yangtze River detrital zir- those with other detrital studies of the Yangtze et al. (2014) may be in part due to higher zircon con data of He et al. (2014) and conclude that that focus on nonzircon systems. Zhang et al. fertility of the right-bank tributaries. We do not the upper Yangtze, more specifically the trunk (2014) characterized Pb isotopic composition refute the Vezzoli et al. (2016) suggestion that stream area between the first bend and Panzhi- of potassium feldspar and demonstrated that fertility might play a role in the Yangtze River’s hua and the Yalongjiang, Daduhe, Minjiang, and erosion of the Longmenshan and neighboring downstream evolution, and support the supposi- Jialingjiang tributaries, is the major source of regions is the important sediment supplier to tion that mineral fertility can possibly impart a zircon, and therefore sediment, to the Yangtze the middle-lower Yangtze. The high-resolution bias to a single mineralogical characterization of River. He et al. (2014) interpreted the Yangtze petrographic and heavy mineral analysis of Vez- provenance (e.g., Malusà et al., 2015). However, River detrital zircon data to represent an increase zoli et al. (2016) found that left-bank tributaries we argue that the mischaracterization in He et in erosion rates in three tributaries of the Yang- draining the topographic front of the Longmen- al. (2014) is the result of only considering broad tze, the Hanjiang, Xiangjiang, and Jialingjiang, shan and Qinling mountains, believed to be a age ranges, using over generalized bedrock age and the trunk stream between Panzhihua-2 and major source of sediment to the SGC (Weislogel distributions, and giving a disproportionate Yibin related to Holocene human disturbance

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and high specific stream power. We argue that Research, v. 17, p. 463–485, doi:​10​.1111​/j​.1365​-2117​.2005​ evolution of the eastern margin of the Tibetan Plateau : .00279​.x. Inferences from 40Ar/39Ar and (U-Th)/He thermochronol- the tectonics of the left-bank tributaries, and not Andersen, T., Saeed, A., Gabrielsen, R.H., and Olaussen, S., ogy: Tectonics, v. 21, doi:​10​.1029​/2000TC001246. anthropogenic influences, control sediment flux 2011, Provenance characteristics of the Brumunddal sand- Kong, P., Zheng, Y., and Fu, B., 2011, Cosmogenic nuclide burial to the Yangtze, consistent with K-feldspar data stone in the Oslo Rift derived from U-Pb, Lu-Hf and trace ages and provenance of late Cenozoic deposits in the Si- element analyses of detrital zircons by laser ablation IC- chuan Basin: Implications for early Quaternary glaciations and petrographic and heavy mineral analyses MPS: Norsk Geologisk Tidsskrift, v. 91, p. 1–18. in east Tibet: Quaternary Geochronology, v. 6, p. 304–312, of Zhang et al. (2014) and Vezzoli et al. (2016), Bonich, M.B., Samson, S.D., and Fedo, C.M., 2013, When sedi- doi:10​ .1016​ /j​ .quageo​ .2011​ .03​ .006.​ respectively. Our interpretation is based on and mentary geochemistry and geochronology fail as prox- Kong, P., Zheng, Y., and Caffee, M.W., 2012, Provenance and ies in provenance analysis: Welcome to the “Stepladder time constraints on the formation of the first bend of the supported by the results of K-S test, likeness and Effect”: Geological Society of America Abstracts with Yangtze River: Geochemistry, Geophysics, Geosystems, CPR analysis, Gaussian component analysis, and Programs, v. 45, no. 7, p. 605. v. 13, Q06017, doi:​10​.1029​/2012GC004140. Burchfiel, B.C., and Zhiliang, C., 2013, Tectonics of the south- Kruskal, J.B., 1964, Multidimensional scaling by optimizing mixing models of bedrock and fluvial distribu- eastern Tibetan Plateau and its adjacent foreland: Geo- goodness of fit to a nonmetric hypothesis: Psychometrika, tions. The U-Pb age distributions of trunk sam- logical Society of America Memoir 210, 164 p., doi:10.1130​ ​ v. 29, p. 1–27, doi:10​ .1007​ ​/BF02289565. ples are established ~400 km downstream of the /2012.1210​ (01).​ Lang, K.A., Huntington, K.W., and Montgomery, D.R., 2013, Carroll, J.D., and Arabie, P., 1980, Multidimensional scaling: Erosion of the Tsangpo Gorge by megafloods, eastern Hi- first bend of the Yangtze River at Panzhihua (Fig. Annual Review of Psychology, v. 31, p. 607–649, doi:​ malaya: Geology, v. 41, p. 1003–1006, doi:10​ .1130​ /G34693​ .1.​ 1) and maintained throughout the rest of the river. 10.1146​/annurev​.ps​.31​.020180​.003135. Malusà, M.G., Carter, A., Limoncelli, M., Villa, I.M., and Gar- Mixtures models indicate that trunk stream sam- Chappell, J., Zheng, H., and Fifield, K., 2006, Yangtse River zanti, E., 2013, Bias in detrital zircon geochronology and sediments and erosion rates from source to sink traced thermochronometry: Chemical Geology, v. 359, p. 90–107, ples are best described by high percentages of with cosmogenic 10Be: Sediments from major rivers: Pal- doi:​10​.1016​/j​.chemgeo​.2013​.09​.016. the Songpan Ganze complex and the Longmen- aeogeography, Palaeoclimatology, Palaeoecology, v. 241, Malusà, M.G., Resentini, A., and Garzanti, E., 2015, Hydraulic shan (Neoproterozoic) zircon. The Yalongjiang, p. 79–94, doi:​10​.1016​/j​.palaeo​.2006​.06​.010. sorting and mineral fertility bias in detrital geochronol- Clark, M.K., House, M.A., Royden, L.H., Whipple, K., Burch- ogy: Gondwana Research, v. 13, p. 1–19, doi:​10​.1016​/j​ Minjiang, Daduhe, and Jialingjiang tributaries fiel, B.C., Zhang, X., and Tang, W., 2005, Late Cenozoic .gr​.2015​.09​.002. help establish, and Hanjiang may help maintain, uplift of southeastern Tibet: Geology, v. 33, p. 525–528, McPhillips, D., Hoke, G.D., Liu-zeng, J., Bierman, P.R., Rood, doi:​10​.1130​/G21265​.1. D.H., and Niedermann, S., 2016, Dating the incision of this signal for the remainder of the catchment, Darby, B.J., and Gehrels, G.E., 2006, Detrital zircon reference the Yangtze River gorge at the first bend using three- although from just detrital zircon U-Pb ages it for the North China block: Journal of Asian Earth Sci- nuclide burial ages: Geophysical Research Letters, v. 43, is difficult to find conclusive evidence of the ences, v. 26, p. 637–648, doi:10​ .1016​ /j​ .jseaes​ .2004​ .12​ .005.​ p. 101–110, doi:​10​.1002​/2015GL066780. Densmore, A.L., Ellis, M.A., Li, Y., Zhou, R., Hancock, G.S., and Moecher, D.P., and Samson, S.D., 2006, Differential zircon Hanjiang tributary influence. Intersample K-S Richardson, N., 2007, Active tectonics of the Beichuan and fertility of source terranes and natural bias in the detrital tests and dissimilarity measures establish a clear Pengguan faults at the eastern margin of the Tibetan Pla- zircon record: Implications for sedimentary provenance high degree of similarity between trunk-to-trunk teau: Tectonics, v. 26, p. 1–17, doi:10​ .1029​ /2006TC001987.​ analysis: Earth and Planetary Science Letters, v. 247, Dobson, D.M., Dickens, G.R., and Rea, D.K., 2001, Terrige- p. 252–266, doi:​10​.1016​/j​.epsl​.2006​.04​.035. sample comparisons, a fact further supported nous sediment on Ceara Rise: A Cenozoic record of South Ouimet, W., Whipple, K., Royden, L., Reiners, P., Hodges, K., in MDS of the distributions. If specific down- American orogeny and erosion: Palaeogeography, Pal- and Pringle, M., 2010, Regional incision of the eastern aeoclimatology, Palaeoecology, v. 165, p. 215–229, doi:​ margin of the Tibetan Plateau: Lithosphere, v. 2, p. 50–63, stream tributaries contribute disproportionate zir- 10​.1016​/S0031​-0182​(00)00161​-9. doi:​10​.1130​/L57​.1. con fluxes to the main stream, particularly the Gallen, S.F., Clark, M.K., and Godt, J.W., 2015, Coseismic land- Parker, R.N., Densmore, A.L., Rosser, N.J., de Michele, M., Li, right-bank tributaries with their order of magni- slides reveal near-surface rock strength in a high-relief, Y., Huang, R., Whadcoat, S., and Petley, D.N., 2011, Mass tectonically active setting: Geology, v. 43, p. 11–14, doi:​ wasting triggered by the 2008 Wenchuan earthquake is tude higher zircon concentrations (Vezzoli et al., 10​.1130​/G36080​.1. greater than orogenic growth: Nature Geoscience, v. 4, 2016), there would be some quantifiable measure Gehrels, G.E., Yin, A., and Wang, X., 2003, Detrital-zircon geo- p. 449–452, doi:​10​.1038​/ngeo1154. seen in one more of the systematic approaches of chronology of the northeastern Tibetan Plateau: Detrital- Press, W., Teukolsky, S., Vetterling, W., and Flannery, B., 1987, zircon geochronology of the northeastern Tibetan plateau: Numerical recipes in C: The art of scientific computing: detrital analysis performed here. However, there Geological Society of America Bulletin, v. 115, p. 881–896, Cambridge, Cambridge University Press, 501 p. is no evidence of significant variation within the doi:10​ .1130​ /0016​ -7606​ (2003)115​ <0881.​ Reiners, P.W., Campbell, I.H., Nicolescu, S., Allen, C.M., Hou- Gehrels, G.E., Valencia, V.A., and Ruiz, J., 2008, Enhanced pre- rigan, J.K., Garver, J.I., Mattinson, J.M., and Cowan, D.S., overall trunk stream sample distributions down- cision, accuracy, efficiency, and spatial resolution of U-Pb 2005, (U-Th)/(He-Pb): Double dating of detrital zircons: stream of Panzhihua that cannot be explained by ages by laser ablation–multicollector–inductively coupled American Journal of Science, v. 305, p. 259–311. poor homogenization of recently incorporated plasma–mass spectrometry: Geochemistry, Geophysics, Richardson, N.J., Densmore, A.L., Seward, D., Fowler, A., Wipf, Geosystems, v. 9, Q03017, doi:10​ .1029​ /2007GC001805.​ M., Ellis, M.A., Yong, L., and Zhang, Y., 2008, Extraordi- tributaries. We demonstrate here how rigorous Gehrels, G.E., et al., 2011, Detrital zircon geochronology of nary denudation in the Sichuan Basin: Insights from low- analytical and statistical analysis of detrital zir- pre-Tertiary strata in the Tibetan-Himalayan orogen: Tec- temperature thermochronology adjacent to the eastern con data leads to robust interpretations of zircon tonics, v. 30, TC5016, doi:​10​.1029​/2011TC002868. margin of the Tibetan Plateau: Journal of Geophysical Hayward, B.W., and Smale, D., 1992, Heavy minerals and the Research, v. 113, B04409, doi:​10.1029​ /2006JB004739.​ provenance. As data sets continue to grow, and provenance history of Waitemata Basin sediments (early Satkoski, A.M., Wilkinson, B.H., Hieptas, J., and Samson, S.D., detrital provenance analysis proves increasingly Miocene, Northland, New Zealand): New Zealand Jour- 2013, Likeness among detrital zircon populations—An nal of Geology and Geophysics, v. 35, p. 223–242, doi:​ approach to the comparison of age frequency data in complex, quantitative analysis remains the best 10​.1080​/00288306​.1992​.9514516. time and space: Geological Society of America Bulletin, tool to characterize sedimentary pathways. The He, M., Zheng, H., and Clift, P.D., 2013, Zircon U-Pb geochro- v. 125, p. 1783–1799, doi:​10​.1130​/B30888​.1. comprehensive approach presented here can be nology and Hf isotope data from the Yangtze River sands: Saylor, J.E., Knowles, J.N., Horton, B.K., Nie, J., and Mora, A., Implications for major magmatic events and crustal evo- 2013, Mixing of source populations recorded in detrital used as a framework for future detrital zircon lution in Central China: Chemical Geology, v. 360–361, zircon U-Pb age spectra of modern river sands: Journal provenance system because it integrates multiple p. 186–203, doi:​10​.1016​/j​.chemgeo​.2013​.10​.020. of Geology, v. 121, p. 17–33, doi:10​ .1086​ /668683.​ quantitative comparison techniques. He, M., Zheng, H., Bookhagen, B., and Clift, P.D., 2014, Controls Shang, F., and Weislogel, A.L., 2014, Detrital zircon geo- on erosion intensity in the Yangtze River basin tracked by chronology from the Mesozoic Qamdo (Changdu) Ba- U-Pb detrital zircon dating: Earth-Science Reviews, v. 136, sin, southeastern Tibet: Implications for the paleo- and ACKNOWLEDGMENTS p. 121–140, doi:​10​.1016​/j​.earscirev​.2014​.05​.014. meso-Tethys evolution: Geological Society of America We thank Bruce Wilkinson and Devin McPhillips for thought- Hearn, P.J., Hare, T., Schruben, P., Sherrill, D., LaMar, C., and Abstracts with Programs, v. 46, no. 7, p. 441. ful discussions. Constructive and critical reviews from Aaron Tsushima, P., 2001, Global GIS database: Digital atlas of Smosna, R., Bruner, K.R., and Burns, A., 1999, Numerical Satkoski and an anonymous reviewer helped improve the South Asia: U.S. Geological Survey Digital Data Series analysis of sandstone composition, provenance, and pa- presentation of this work. This research was supported by DD-62-C, CD-Rom, scale 1:1,000,000. leogeography: Journal of Sedimentary Research, v. 69, National Science Foundation grant EAR-1019427 to Hoke. Henck, A.C., Huntington, K.W., Stone, J.O., Montgomery, D.R., p. 1063–1070, doi:​10​.2110​/jsr​.69​.1063. and Hallet, B., 2011, Spatial controls on erosion in the Spencer, C.J., and Kirkland, C.L., 2016, Visualizing the sedi- Three Rivers region, southeastern Tibet and southwest- mentary response through the orogenic cycle: A multi- REFERENCES CITED ern China: Earth and Planetary Science Letters, v. 303, dimensional scaling approach: Lithosphere, v. 8, p. 29–37, Amidon, W.H., Burbank, D.W., and Gehrels, G.E., 2005, Con- p. 71–83, doi:​10​.1016​/j​.epsl​.2010​.12​.038. doi:​10​.1130​/L479​.1. struction of detrital mineral populations: Insights from Kirby, E., Reiners, P.W., Krol, M.A., Whipple, K.X., Hodges, K. V, Su, J., Dong, S., Zhang, Y., Li, Y., Chen, X., and Cui, J., 2014, mixing of U-Pb zircon ages in Himalayan rivers: Basin Farley, K.A., Tang, W., and Chen, Z., 2002, Late Cenozoic Detrital zircon geochronology of pre-Cretaceous strata:

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Tectonic implications for the Jiangnan orogen, south isotopic constraints: Sedimentary Geology, v. 304, p. 44– in situ-produced cosmogenic nuclides and recent river China: Geological Magazine, v. 151, p. 975–995, doi:​10​ 58, doi:​10​.1016​/j​.sedgeo​.2014​.02​.003. loads: Geological Society of America Bulletin, v. 123, .1017​/S0016756813001003. Wang, L.-J., Griffin, W.L., Yu, J.-H., and O’Reilly, S.Y., 2010, Pre- p. 934–950, doi:​10​.1130​/B30317​.1. van Hoang, L., Wu, F.-Y., Clift, P.D., Wysocka, A., and Swiercze- cambrian crustal evolution of the Yangtze Block tracked Xu, Y., Sun, Q., Yi, L., Yin, X., Wang, A., Li, Y., and Chen, J., wska, A., 2009, Evaluating the evolution of the Red River by detrital zircons from Neoproterozoic sedimentary 2014, Detrital zircons U-Pb age and Hf isotope from the system based on in situ U-Pb dating and Hf isotope anal- rocks: Precambrian Research, v. 177, p. 131–144, doi:​10​ western side of the Taiwan Strait: Implications for sedi- ysis of zircons: Geochemistry, Geophysics, Geosystems, .1016​/j​.precamres​.2009​.11​.008. ment provenance and crustal evolution of the northeast v. 10, Q11008, doi:​10​.1029​/2009GC002819. Wang, L.-J., Griffin, W.L., Yu, J.-H., and O’Reilly, S.Y., 2013, Cathaysia Block: Terrestrial, Atmospheric and Oceanic Vermeesch, P., 2013, Multi-sample comparison of detrital age U-Pb and Lu-Hf isotopes in detrital zircon from Neo- Sciences, v. 25, p. 505, doi:10​ .3319​ /TAO​ .2014​ .02​ .18​ .01​ (TT).​ distributions: Chemical Geology, v. 341, p. 140–146, doi:​ proterozoic sedimentary rocks in the northern Yangtze Yan, Y., Carter, A., Huang, C.-Y., Chan, L.-S., Hu, X.-Q., and 10​.1016​/j​.chemgeo​.2013​.01​.010. Block: Implications for Precambrian crustal evolution: Lan, Q., 2012, Constraints on Cenozoic regional drainage Vermeesch, P., and Garzanti, E., 2015, Making geological Gondwana Research, v. 23, p. 1261–1272, doi:​10​.1016​ evolution of SW China from the provenance of the Jian- sense of “Big Data” in sedimentary provenance anal- /j​.gr​.2012​.04​.013. chuan Basin: Geochemistry, Geophysics, Geosystems, ysis: Chemical Geology, v. 409, p. 20–27, doi:​10​.1016​/j​ Weislogel, A.L., Graham, S.A., Chang, E.Z., Wooden, J.L., v. 13, Q03001, doi:​10​.1029​/2011GC003803. .chemgeo​.2015​.05​.004. and Gehrels, G.E., 2010, Detrital zircon provenance from Yang, S., Zhang, F., and Wang, Z., 2012, Grain size distribution Vezzoli, G., Garzanti, E., Limonta, M., Andò, S., and Yang, S., three turbidite depocenters of the middle-upper Triassic and age population of detrital zircons from the Changji- 2016, Erosion patterns in the Changjiang (Yangtze River) Songpan-Ganzi complex, central China: Record of col- ang (Yangtze) River system, China: Chemical Geology, v. catchment revealed by bulk-sample versus single-min- lisional tectonics, erosional exhumation, and sediment 296, p. 26–38, doi:​10​.1016​/j​.chemgeo​.2011​.12​.016. eral provenance budgets: Geomorphology, v. 261, p. 177– production: Geological Society of America Bulletin, v. 122, Zhang, Z., Tyrrell, S., Li, C., Daly, J.S., Sun, X., and Li, Q., 2014, 192, doi:​10​.1016​/j​.geomorph​.2016​.02​.031. p. 2041–2062, doi:10​ .1130​ /B26606​ .1.​ Pb isotope compositions of detrital K-feldspar grains in Wang, C., Liang, X., Xie, Y., Tong, C., Pei, J., Zhou, Y., Jiang, Y., Wilkinson, B.H., and McElroy, B.J., 2007, The impact of hu- the upper-middle Yangtze River system: Implications for Fu, J., Dong, C., and Liu, P., 2014, Provenance of upper mans on continental erosion and sedimentation: Geo- sediment provenance and drainage evolution: Geochem- Miocene to Quaternary sediments in the Yinggehai–Song logical Society of America Bulletin, v. 119, p. 140–156, istry, Geophysics, Geosystems, v. 15, p. 2765–2779, doi:​ Hong Basin, South China Sea: Evidence from detrital zir- doi:​10​.1130​/B25899​.1. 10​.1002​/2014GC005391. con U-Pb ages: Marine Geology, v. 355, p. 202–217, doi:​ Wissink, G.K., 2016, Innovative and conventional approaches Zheng, H., Clift, P.D., Wang, P., Tada, R., Jia, J., He, M., and 10​.1016​/j​.margeo​.2014​.06​.004. to detrital zircon provenance analysis: Looking to the Jourdan, F., 2013, Pre-Miocene birth of the Yangtze River: Wang, E., Kirby, E., Furlong, K.P., van Soest, M., Xu, G., Shi, X., past, present, and future [PhD thesis]: Syracuse, New National Academy of Sciences Proceedings, v. 110, Kamp, P.J.J., and Hodges, K. V., 2012, Two-phase growth York, Syracuse University, 253 p p. 7556–7561, doi:​10​.1073​/pnas​.1216241110. of high topography in eastern Tibet during the Ceno- Wissink, G.K., and Hoke, G.D., 2015, No Cenozoic connectiv- zoic: Nature Geoscience, v. 5, p. 640–645, doi:​ 10​.1038​ ity between Upper Yangtze River and Red River: Geo- /ngeo1538. logical Society of America Abstracts with Programs, v. 47, MANUSCRIPT RECEIVED 7 MAY 2016 Wang, L., Liu, C., Gao, X., and Zhang, H., 2014, Provenance no. 7, p. 506. REVISED MANUSCRIPT RECEIVED 29 JULY 2016 and paleogeography of the Late Cretaceous Mengyejing Wittmann, H., von Blanckenburg, F., Maurice, L., Guyot, J.L., MANUSCRIPT ACCEPTED 22 AUGUST 2016 Formation, Simao Basin, southeastern Tibetan Plateau: Filizola, N., and Kubik, P.W., 2011, Sediment production Whole-rock geochemistry, U-Pb geochronology, and Hf and delivery in the Amazon River basin quantified by Printed in the USA

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