Mathieu Dellinger

Julien Bouchez

Jérôme Gaillardet

Laetitia Faure

Julien Moureau

Tracing weathering regimes using the lithium isotope composition of detrital sediments

Lithium (Li) isotopes are a promising tracer of chemical weathering processes for both modern and ancient times. In order to improve the use of Li isotopes in the sedimentary record, here we calibrate the relationship between weathering intensity and detrital Li isotope composition ( 7 Li) using the fine fraction of modern large river sediments. By using independent estimates for sediment provenance to calculate the Li isotope signature of the rock from which the sediments derive through weathering, we show that source rock variability (in particular the relative contribution of sedimentary vs. igneous rocks) must be corrected for before using Li isotopes as a weathering proxy. We also show that for rivers draining mountain ranges, the contribution of particles derived from sedimentary rocks to river sediments is correlated to their Li/Al ratio, making it possible to use Li contents to estimate the average source rock composition. Once corrected for bedrock variability, the Li isotope signature defines a negative relationship with the weathering intensity (ratio between silicate weathering rate and total denudation

INTRODUCTION

The surface of Earth evolves through the combined action of chemical weathering reactions and physical denudation. The former process partly dissolves the continental crust, exports cations to the ocean, and consumes atmospheric CO2 from the atmosphere, whereas physical denudation exports solid products to the ocean. Hence, over long time scales, silicate weathering is one of the major processes regulating the amount of atmospheric CO2 and therefore controlling the evolution of climate [START_REF] Berner | The carbonate-silicate geochemical cycle and its effect on atmospheric carbon dioxide over the past 100 million years[END_REF].

Despite this recognition, it is still poorly known how silicate weathering has changed in the past and what are the parameters controlling weathering rates and intensities over long timescales. The emerging Li isotope proxy has a great potential for tracing silicate weathering because Li is a soluble element predominantly hosted in silicate rocks and its isotopes are fractionated during water-rock interactions [START_REF] Huh | Lithium isotopes as a probe of weathering processes: Orinoco River[END_REF]. Although the relation between the river dissolved Li isotope composition ( 7 Li) and weathering is still a matter of debate (e.g., Dellinger et al., 2015;[START_REF] Huh | Lithium isotopes as a probe of weathering processes: Orinoco River[END_REF][START_REF] Pogge Von Strandmann | The Li isotope response to mountain uplift[END_REF], this has served as a basis to investigate the 7 Li of ancient marine carbonates (e.g., [START_REF] Misra | Lithium isotope history of Cenozoic seawater: Changes in silicate weathering and reverse weathering[END_REF][START_REF] Pogge Von Strandmann | Lithium isotope evidence for enhanced weathering during Oceanic Anoxic Event 2[END_REF] in order to unravel global past weathering conditions [START_REF] Bouchez | Modeling novel stable isotope ratios in the weathering zone[END_REF][START_REF] Li | Evolution of Cenozoic seawater lithium isotopes: Coupling of global denudation regime and shifting seawater sinks[END_REF][START_REF] Misra | Lithium isotope history of Cenozoic seawater: Changes in silicate weathering and reverse weathering[END_REF].

Overall, for rivers draining mountain ranges, the Li concentration of river sediments ranges from 10 to 102 g g -1 (ppm) and the 7 Li of the sediments ( 7 Lisuspended_load, precision better than ‰) from -4‰ to +5‰ (Fig. 1). The rivers draining lowlands have on average lower 7 Li ( 6.5‰ to 3‰) and Li concentration compared to rivers draining mountain ranges. Interestingly, the 7 Li is negatively correlated to the Li concentrations in large rivers draining mountain ranges, whereas no relationship is observed for rivers draining the lowlands (Fig. 1).

REMOVING THE NON-WEATHERING EFFECTS

In large rivers draining mountain ranges, the 7 Li and Li concentration of river sediments are strongly dependent upon grain size and lithological source (Dellinger et al., 2014). In order to extract the weathering signal contained in river sediments, it is Publisher: GSA Journal: GEOL: Geology DOI:10.1130/G38671.1

Page 5 of 17 necessary to remove the effect of both grain size and lithological variability on the Li isotope composition.

Grain Size Effects

Fine sediments have generally lower 7 Li and higher Li concentration than coarse sediments (Fig. 1). This is because they contain a higher proportion of particles sourced from sedimentary rocks and a higher proportion of weathering products sourced from modern soils that carry the fingerprint of the modern weathering regime (Dellinger et al., 2014). Therefore, similarly to element ratios (e.g., Lupker et al., 2013), large changes of the 7 Li in sedimentary archives can simply arise from change of the sediment grain size and lead to false interpretation in terms of shift in weathering conditions. In order to mitigate this grain size effect, in the present study we use for each river the finest sediment sample available (size < 63 µm), which for most cases has been collected at or near the river channel surface. However, even these fine sediments contain a nonnegligible fraction of unweathered material that needs to be taken into account for the interpretation of their 7 Li data.

The Influence of Lithology

The Li isotope signature that can be measured in weathered detrital material depends upon (1) the initial 7 Li of river sediments, prior to chemical weathering (i.e., the Li isotope signature of its source rock material, hereafter referred to as " 7 Lisource_material"), which is a lithological effect and (2) the extent of fractionation between this initial signature and the neoformed weathering material, which in turn depends on isotope fractionation factors and on Li partitioning between secondary minerals and the dissolved load [START_REF] Bouchez | Modeling novel stable isotope ratios in the weathering zone[END_REF]. The weathering signal is contained only in the second effect.

Publisher: GSA Journal: GEOL: Geology DOI:10.1130/G38671.1 Page 6 of 17 This is why in the following, we consider the difference in isotope composition between the fine suspended sediment and the original bedrock, 7 Lifine-source = 7 Lifine suspended_load- 7 Lisource_material.

The " 7 Lisource_material" corresponds to the weighted average of the 7 Li of the various erosion sources: igneous, metamorphic and sedimentary rocks (hereafter referred to as "shale" because shales are by far the most important type of sedimentary rock contributing to the Li budget; [START_REF] Holland | The chemical evolution of the atmosphere and oceans[END_REF] that have distinct average Li concentration and isotope composition (Dellinger et al., 2014;[START_REF] Sauzéat | New perspectives on the Li isotopic composition of the upper continental crust and its weathering signature[END_REF][START_REF] Tomascak | Advances in Lithium Isotope Geochemistry[END_REF]. Indeed, the Li isotope variability of the present-day upper continental crust (UCC), as characterized by using inherently integrative samples like large river sand (Dellinger et al., 2014) or desert loess [START_REF] Sauzéat | New perspectives on the Li isotopic composition of the upper continental crust and its weathering signature[END_REF], corresponds mostly to a mixture between a Li-rich, low- 7 Li, shale end member ( 7 Li of 0.5 ± 1‰ and Li/Al of 1.0 ± 0.1 × 10 3 ) and a Li-poor, high- 7 Li, igneous end member ( 7 Li of 3.5 ± 1.5‰, Li/Al of 0.30 ± 0.12 × 10 3 ). This mixing trend can be used to determine the Li isotope composition of river sediments prior to weathering ( 7 Lisource_material) provided that the relative contribution of the different source materials to the sediments is known.

Quantification of the provenance of sediments can be achieved using Sr-Nd isotopes and/or insoluble trace element ratios, provided that the composition of the major bedrock drained by each river basin is known and that they have contrasted signatures (e.g., Allègre et al., 1996). Here, we use independent tracers of provenance (Nd, Sr isotopes and trace elements) in order to quantify the erosion sources of the fine sediments and determine the 7 Lisource_material for fine sediments from each of the large rivers. We note that the procedure of choice to characterize average source rock is specific to each Publisher: GSA Journal: GEOL: Geology DOI:10.1130/G38671.1 Page 7 of 17 large river basin. In the Amazon, Congo, and Ganges-Brahmaputra basins, sedimentary, igneous, and metamorphic rocks have distinct Nd isotope composition making it possible to quantify precisely the provenance of fine sediments using Nd isotopes (see the GSA Data Repository 1 ). For the Mackenzie River, we use trace elements (Cr, Ti, Cs) ratios (see the Data Repository). We emphasize that this calculation provides information on source rocks for fine sediments only, which can be different for other grain sizes (Bouchez et al., 2011a;Dellinger et al., 2014;[START_REF] Garçon | Where is basalt in river sediments, and why does it matter?[END_REF].

However, in some cases like that of the Changjiang basin, neither Sr-Nd isotopes nor trace elements can be used to assess the provenance of sediments because the signatures of the main rock sources are under-constrained or not significantly different [START_REF] Chetelat | Assessing the influence of lithology on weathering indices of Changjiang river sediments[END_REF]. An alternative method is to identify another tracer that correlates with an independent measure of the proportion of shale-derived particles (i.e., the amount of sedimentary recycling) quantified across the rest of our river set. Among all the chemical elements tested, the best correlation with the proportion of shale-derived particles is obtained for the Li/Al ratio (Fig. 2). Li concentrations are normalized to Al to remove dilution effect by quartz or other Li-free phases. This good relationship stems mostly from the fact that (1) shales and igneous rocks have significantly distinct Li contents, and (2) that chemical weathering has a minor impact on sediment Li content for a majority of samples. However, we note that sediments from some lowland rivers have lost a significant fraction of Li because of their higher weathering intensity (Fig. 3).

Using the relationship between Li and the proportion of sediments derived from erosion of shales calibrated on rivers draining mountain ranges, we infer the proportion of shales Publisher: GSA Journal: GEOL: Geology DOI:10.1130/G38671.1 Page 8 of 17 contributing to the fine sediment load of the Changjiang basin river, which makes our set of 7 Lisource_material estimates complete (see Data Repository).

Using the calculated proportion of shales and igneous rocks with the 7 Li of the rock end members, we estimate the Li isotope composition of the rock source ( 7 Lisource_material) for each fine river sediment sample (see the Data Repository). We note that the calibration of the Li provenance tracer in detrital sediments might also serve to determine the provenance and the 7 Lisource_material of ancient detrital sedimentary archives for which the potential bedrock sources are usually not constrained.

RELATION BETWEEN THE LITHIUM ISOTOPE SIGNATURE AND WEATHERING INTENSITY

In this section we evaluate the relation between sediment 7 Li, Li weathering index and the weathering intensity previously defined as the W/D ratio. The Li weathering index of the detrital sediment can be expressed as (Li/Al)fine_sediments / (Li/Al)source_material, where (Li/Al) source_material corresponds here to the (Li/Al) ratio the suspended sediments would have in the absence of any silicate weathering reactions. A value of 1 means no loss or gain of Li by the solids during weathering while a value lower than 1 implies loss of Li during weathering. The "(Li/Al)source_material" values are determined using the rock end member compositions defined in the previous section and the proportion of shales calculated above. The Li weathering index values are negatively correlated to the weathering intensity (Fig. 2.b) with most of the rivers draining mountain ranges having a Li weathering index higher than 0.8 (except for the Solimões and Pastaza rivers), whereas rivers draining lowlands have Li weathering index values between 0.9 and 0.4. The higher Li depletion in sediments transported by lowland rivers is compatible Publisher: GSA Journal: GEOL: Geology DOI:10.1130/G38671.1 Page 9 of 17 with the higher proportion of dissolved Li transported by these rivers (see the Data Repository). This shows that significant Li depletion in sediments occurs only for very intense weathering conditions (Fig. 2).

The relationships between Li isotope signature in modern fine river sediments corrected for the source rock signature ( 7 Lifine-source) can be examined as a function of the weathering regime. A significant negative relationship is observed between the weathering intensity (W/D) and 7 Lifine-source (Fig. 3a, r 2 = 0.75). This correlation is stronger than that between 7 Lifine_sediments and W/D (Fig. 3b, r 2 = 0.48), showing that source rock composition indeed introduces some scatter in this relationship. Sediments from rivers characterized by high W/D have the lowest 7 Lifine-source whereas rivers having low W/D have 7 Lifine-source close to zero. The 7 Lised and 7 Lifine-source also correlate well with more traditional weathering proxies such as CIA (r 2 = 0.76, not shown) or /Th ratio (r 2 = 0.62, not shown). We observe no relationship between 7 Lifinesource and chemical silicate weathering rates.

To explain this relationship, we suggest that at high denudation rate (and hence low W/D), incorporation of Li into secondary minerals is hindered by short mineral residence times in soils making the dissolved 7 Li close to 7 Lisource_material [START_REF] Bouchez | Modeling novel stable isotope ratios in the weathering zone[END_REF]Dellinger et al., 2015;Wang et al., 2015). Therefore, the small amount of secondary minerals formed should have a low 7 Li, which could be expected to be reflected in the 7 Li of fine sediments [START_REF] Dosseto | Rapid response of silicate weathering rates to climate change in the Himalaya[END_REF]. We suggest that this is not observed because at very low weathering intensity (W/D < 0.01), typical of high-erosion settings, the sediments carried by the rivers contain a high proportion of primary minerals ( 7 Lised-rock = 0) compared to secondary minerals formed during the modern weathering Publisher: GSA Journal: GEOL: Geology DOI:10.1130/G38671.1 Page 10 of 17 cycle, even in the fine sediments (Dellinger et al., 2014(Dellinger et al., , 2015)). At high weathering intensity (W/D > 0.1) such as in lowland areas, secondary minerals formed during the present-day weathering cycle and characterized by low 7 Lifine_sediments, compose the majority of the sediments and therefore control the bulk sediment Li isotope signature.

The contribution of unweathered debris to river fine sediment load is likely to be more prominent for rivers draining fine-grained sedimentary rocks (which is the case of large, lithologically mixed rivers), as these lithologies are highly erodible and produce fine sediments.

IMPLICATIONS AND CONCLUSIONS

These results have important implications regarding the use of Li isotopes in clastic sediments to trace weathering regimes both in the present-day and in the past.

First, the 7 Li of modern river sediments is primarily related to weathering intensity (that is, in the modern Earth, mostly a function of the erosion rate; [START_REF] Dixon | Soils as pacemakers and limiters of global silicate weathering[END_REF] and not to the silicate weathering rate as inferred by other studies (e.g., [START_REF] Dosseto | Rapid response of silicate weathering rates to climate change in the Himalaya[END_REF].

Second, the 7 Li of fine river sediments is sensitive only to large changes of the weathering intensity (i.e., by an order of magnitude; Fig. 3a.). In particular, a 7 Lifine-source value between 1‰ and 3.5‰ can correspond to a large range of possible weathering intensity comprised between 0.005 and 0.08. Indeed, in high-erosion rate settings, the contribution of soil-derived weathered particles is minor compared to that of debris of unweathered bedrock mobilized by mass wasting processes, even in the finest river sediments fraction [START_REF] Dixon | Soils as pacemakers and limiters of global silicate weathering[END_REF]Dellinger et al., 2014). However, The third important implication is related to the use of Li isotopes in detrital sediments as a proxy for palaeo-weathering regimes. Tracing ancient weathering processes using conventional geochemical tracers in detrital sediments (e.g. chemical index of alteration CIA, or chemical ratios combining a soluble and an insoluble element, such as Na/Sm, U/Th or K/Al) can be challenging because these proxies are also influenced by sediment provenance, grain size effects or post-depositional alteration (Bouchez et al., 2011a;[START_REF] Carpentier | Large U loss during weathering of upper continental crust: The sedimentary record[END_REF][START_REF] Li | Is chemical index of alteration (CIA) a reliable proxy for chemical weathering in global drainage basins?[END_REF]Lupker et al., 2013).

Hence, some recent studies have used Li isotopes in fluvial alluvial deposits (Dosseto et al., 2015), marine detrital sediments [START_REF] Bastian | Investigating Li isotope composition of Nile deltaic sediments as paleotracer of continental alteration[END_REF] or ancient siliciclastic rocks [START_REF] Li | Insights into chemical weathering of the upper continental crust from the geochemistry of ancient glacial diamictites[END_REF] to determine palaeo-weathering conditions. In comparison to marine carbonates, clastic sediments record the fingerprint of local weathering conditions and have the advantage of not being influenced by biological fractionation ("vital effects") observed during carbonate precipitation [START_REF] Vigier | Lithium isotopes in foraminifera shells as a novel proxy for the ocean dissolved inorganic carbon (DIC)[END_REF].

The results from this study can be used as a framework for interpreting the detrital 7 Lifine_sediments and Li/Al ratio in sediment archives. It demonstrates the importance of correcting for grain size and lithological variability in order to interpret the detrital Li isotope composition in terms of weathering intensity. It also shows that the 7 Lifine-source value is a function of the weathering intensity only for W/D values higher than 0.05.

Overall, the combined use of Li/Al, 7 Li and other more traditional weathering proxies (like CIA) has great potential for quantifying both sedimentary recycling and weathering intensity in sediment archives. which 90% of the grains are found in a given sample). For lowland rivers, grain size was not measured, but all lowlands sediment are surface samples, which are generally finegrained [START_REF] Filizola | Transfert sédimentaire actuel par les fleuves amazoniens[END_REF]. b.

FIGURE CAPTIONS

Li Al

Li Al

( ) Sed ( ) Rock

Analytical methods

Here, we briefly describe the analytical methods used for measurements of the Li and Nd isotope composition of sediments.

Li isotopes: the digestion, column chemistry and Li isotope measurement procedure for the sediments has been described in Dellinger et al., (2014). About 20 mg of sediment were digested in HF-HNO 3 at 100°C during 24 to 48 hours. Li was then separated from the matrix by ionexchange chromatography using a method modified from James and Palmer (2000) and described in Dellinger et al. (2014). The lithium isotope composition was measured using a MC-ICP-MS Neptune (Thermo Scientific, Bremen) at IPGP (Paris). Details on the analytical procedure are available in Dellinger et al. (2014). Accuracy and reproducibility of the isotopic measurements were checked through repeated analyses of the basalt reference materials JB-2 yielded δ 7 Li = +4.47±0.53 (± 2σ, n = 30 separations and 15 digestions).

Nd isotopes: Nd isotope composition was measured in the same aliquot used for Li isotopes. Nd was separated from the rest of the matrix by ion-exchange chromatography using the TRU-spec and Ln-spec resins and measured by MC ICP-MS Neptune in IPGP following the method described in [START_REF] Cogez | Constraints on the role of tectonic and climate on erosion revealed by two time series analysis of marine cores around New Zealand[END_REF].

Supplemental file

Click here to download Supplemental file Data Repository -Accepted -MD.pdf values (Allègre et al., 1996;[START_REF] Roddaz | Sediment provenances and drainage evolution of the Neogene Amazonian foreland basin[END_REF][START_REF] Viers | Seasonal and provenance controls on Nd-Sr isotopic compositions of Amazon rivers suspended sediments and implications for Nd and Sr fluxes exported to the Atlantic Ocean[END_REF]. In the following we consider that river sediments in the Amazon Basin result from a binary mixture between two end members, such that the following mixing equation can be written:

With ε Nd (0) sed , ε Nd (0) sha and ε Nd (0) Ign , respectively the Nd isotope composition of river sediment, shale and igneous rock. The proportion of shales-derived particles ("g sha " in mass %) can be calculated as:

As the average Nd concentration of shale and igneous rocks is not significantly different [START_REF] Condie | Chemical composition and evolution of the upper continental crust: Contrasting results from surface samples and shales[END_REF], we consider that g sha = g sha Nd .

As explained below, the composition of the igneous end member (ε Nd (0) Ign ) varies between the different sub-basins, while the composition of the shale end member (ε Nd (0) sha ) is considered homogenous throughout the Amazon River basin.

The Beni River drains exclusively shales from the Bolivian Andes and we use the ε Nd (0) of its sediments to estimate the average ε Nd (0) value of Andean sedimentary rocks. The ε Nd (0) of Beni sediments ranges between -12.2 and -12.9, in good agreement with the range of ε Nd (0) values measured in Andean sedimentary rocks (-10 to -13;[START_REF] Pinto | Traçage de l'érosion cénézoı̈que des Andes centrales à l'aide de la minéralogie et géochimie des sédiments (Nord du Chili et Nord-Ouest de la Bolivie)[END_REF][START_REF] Viers | Seasonal and provenance controls on Nd-Sr isotopic compositions of Amazon rivers suspended sediments and implications for Nd and Sr fluxes exported to the Atlantic Ocean[END_REF] and Neogene South Amazonian foreland basin sediments from [START_REF] Roddaz | Sediment provenances and drainage evolution of the Neogene Amazonian foreland basin[END_REF]. Similarly, the

ε Nd (0) sed = ε Nd (0) sha × γ sha + ε Nd (0) Ign × (1-γ sha ) γ sha Nd = γ sha × Nd [ ] sha Nd [ ] sed
Yata river that drains exclusively the lowlands Tertiary sedimentary rocks (originated from the erosion of the region of the Andes) have a ε Nd (0) of -11.6, in good agreement with the ε Nd (0)

value measured in Beni river sediments. Therefore, we assume a ε Nd (0) sha of -12.0±1.0 for the shale end member. The same value of -12.0 was also assumed for the metasedimentary endmember of the Madre de dios river basin by [START_REF] Basu | Nd, Sr-isotopic provenance and trace element geochemistry of Amazonian foreland basin fluvial sands, Bolivia and Peru: implications for ensialic Andean orogeny[END_REF]. In addition, we consider that this value is also representative of the shales from the northern Andes. Indeed, the ε Nd (0) of Solimões sediments defines a trend with the Al concentration (grain size proxy) that tends toward a similar shale ε Nd (0) value (Fig. DR2) and Neogene North Amazonian foreland basin sediments from [START_REF] Roddaz | Sediment provenances and drainage evolution of the Neogene Amazonian foreland basin[END_REF] also plot on the same trend. Bouchez et al., (2011a), Dellinger et al., (2015) and [START_REF] Viers | Seasonal and provenance controls on Nd-Sr isotopic compositions of Amazon rivers suspended sediments and implications for Nd and Sr fluxes exported to the Atlantic Ocean[END_REF]. Data for foreland basin sediments are from [START_REF] Roddaz | Sediment provenances and drainage evolution of the Neogene Amazonian foreland basin[END_REF]. The grey band corresponds to the estimated ε Nd (0) of the mean shale end-member in the Amazon basin.

Regarding the igneous rock end member, the Nd isotope composition measured in Andean Neogene granitoid rocks from the Sierra Blanca in Peru have ε Nd (0) generally between -3 to 0 [START_REF] Petford | Na-rich Partial Melts from Newly Underplated Basaltic Crust: the Cordillera Blanca Batholith, Peru[END_REF]. Pemian-Triassic and Carboniferous granitoids in southern Peru have a median ε Nd (0) of -4.7±0.6 [START_REF] Miskovic | Magmatic evolution of the Peruvian Eastern Cordilleran intrusive belt: insights into the growth of continental crust and tectonism along the proto-Andean Western Gondwana[END_REF]. Accordingly, bed sediments from the

Shale end member

Yata River Suspended sediments

Solimões River draining the Peruvian and Ecuadorian Andes, and for which the major and trace element signature reflect an igneous rock provenance (Bouchez et al., 2011a;Dellinger et al., 2014), have ε Nd (0) ranging from -6.5 to -2.0. However, volcanic rocks in Ecuador (mostly andesites) have a higher ε Nd (0) ranging between +2 and +6 with [START_REF] Bryant | Geochemical Constraints on the Origin of Volcanic Rocks from the Andean Northern Volcanic Zone, Ecuador[END_REF], and bed sediments from the Pastaza River derived from the erosion of andesite in Ecuador has a ε Nd (0) of +1.9 (Dellinger et al., 2015a). This high ε Nd (0) indicates that Pastaza sediments predominantly derive from the erosion of more recent (Quaternary) andesite. In the following, we use a ε Nd (0) Ign of -3.0±2.0 for the igneous end member of all the Andean-fed rivers, except for the Pastaza River for which we use a ε Nd (0) Ign value of +2.0±1.0. Regarding the shield regions, the range of ε Nd (0) measured in rock samples from the Rio Negro, Central Amazon and Tapajos-Parima provinces is very large (-20 to -30) and positively correlated to the Sm/Nd ratio as a result of magmatic differentiation (Allègre et al., 1996;[START_REF] Basu | Nd, Sr-isotopic provenance and trace element geochemistry of Amazonian foreland basin fluvial sands, Bolivia and Peru: implications for ensialic Andean orogeny[END_REF][START_REF] Hoorn | The Amazonian Craton and its Influence on Past Fluvial Systems (Mesozoic-Cenozoic, Amazonia)[END_REF][START_REF] Roddaz | Sediment provenances and drainage evolution of the Neogene Amazonian foreland basin[END_REF][START_REF] Santos | A new understanding of the provinces of the Amazon Craton based on integration of field mapping and U-Pb and Sm-Nd geochronology[END_REF]. The Sm/Nd ratio of rivers draining the shield range between 0.15 to 0.20, and for a given Sm/Nd ratio, lowlands rivers generally have higher ε Nd (0) than cratonic rocks (Fig. DR3) and plot on a line trending towards the shale end member (defined as the mean Sm/Nd and ε Nd (0) of Beni River sediments). Only the Tapajós and Trombetas river sediments have a Nd isotope composition similar to that of the cratonic rocks in the Amazon basin whereas the Rio Negro and Urucara rivers have a ε Nd (0) intermediate between cratonic rocks and Andean-derived shales, consistently with the findings of Allègre et al., (1996). We consider therefore the Trombetas River composition as representative of the mean Nd isotope composition of the shield end member (ε Nd (0) Ign = -20.0±2.0).

Congo River: The lithology of the Congo Basin is mainly composed of Archean and Proterozoic TTG along the basin border, and of sedimentary rocks in the center. To our knowledge, there is no available Nd isotope data on Congo rocks in the literature. However, Allègre et al. (1996) report ε Nd (0) values for the major Congo tributaries. The ε Nd (0) range from -12.9 for the Lobaye River to -18.2 for the Likouala. We also measured the ε Nd (0) on a lateritic soil profile sampled 100 km downstream from Bangui (Henchiri et al., 2016) and developed on TTG rocks. The Nd isotope values range from -18.1 to -18.9 (See table DR2) and is similar to the value of the Likouala.

Fig. DR4: Crustal Na/Sm for Congo rivers inferred by [START_REF] Gaillardet | A global geochemical mass budget applied to the Congo basin rivers: Erosion rates and continental crust composition[END_REF] as a function of the sediment ε Nd . The Nd isotope composition of the cratonic end member is estimated to be -18.5±0.5 based on the above trend, the Na/Sm of UCC [START_REF] Rudnick | 4.1 -Composition of the Continental Crust[END_REF] and the Nd Shales [START_REF] Condie | Chemical composition and evolution of the upper continental crust: Contrasting results from surface samples and shales[END_REF] UCC [START_REF] Rudnick | 4.1 -Composition of the Continental Crust[END_REF] Soil profile on cratonic rocks

Shield rocks

Shales isotope composition of a soil profile developed on cratonic rocks in Bangui (this study). The Nd isotope composition of the shales end-member is estimated to be -12±0.5 by projecting the typical Na/Sm value of global Phanerozoic shales (from [START_REF] Condie | Chemical composition and evolution of the upper continental crust: Contrasting results from surface samples and shales[END_REF] on the mixing trend. This value is also compatible with the Nd isotope composition of the Lobaye River.

Interestingly, the ε Nd (0) of Congo tributaries sediments is negatively correlated to the Na/Sm ratio of the Congo tributaries continental crust (sediments + dissolved) inferred by [START_REF] Gaillardet | A global geochemical mass budget applied to the Congo basin rivers: Erosion rates and continental crust composition[END_REF] (Fig. DR4). This crustal Na/Sm ratio can be used to distinguish TTG (high Na/Sm) from shales (low Na/Sm resulting from Na depletion during ancient weathering processes). The Likouala has a TTG-like Na/Sm signature whereas the Lobaye has a signature close to that of shales. Altogether, the range of variation of ε Nd (0) in Congo sediments can be explained at first order as resulting from a mixture between a TTG igneous end member of high ε Nd (0) Ign around -19 and a metasedimentary end member of low ε Nd (0) sha (around -12), as for the Amazon. Using eqs. ( 1) and ( 2), we calculate that the proportion of shale-derived particles in the Congo River sediments is 40±10%. We note that the correlation between ε Nd (0) and Na/Sm is scattered and therefore that this method for determining the provenance of Congo River sediments gives only a first-order estimate of the proportion of shale-derived particles.

Ganges-Brahmaputra rivers: In the Ganges-Brahmaputra system, the source of sediments has been characterized using Nd and Sr isotopes by previous studies [START_REF] Galy | Higher erosion rates in the Himalaya: Geochemical constraints on riverine fluxes[END_REF]Lupker et al., 2013;[START_REF] Singh | Sr and Nd isotopes in river sediments from the Ganga Basin: Sediment provenance and spatial variability in physical erosion[END_REF][START_REF] Singh | Tracing the distribution of erosion in the Brahmaputra watershed from isotopic compositions of stream sediments[END_REF]. The Ganges sediments are mostly derived from the erosion of the high-grade metamorphic rocks from the High Himalaya Crystalline (HHC, about 70%) and the rest of the sediments from the low-grade metasedimentary rocks of the Lesser Himalayas (LH, 30%). For the Brahmaputra, Singh and

France-Lanord (2002) estimate that in average, between 50 and 70% of the sediments are derived from the erosion of the HHC, about 10% from the LH and the rest from the erosion of the Trans-Himalayan Batholith (igneous rocks). However, the provenance of the Brahmaputra sediments can be quite variable depending upon the depth and the sampling date (Lupker et al., 2013). As the Nd and Sr isotope composition of the Brahmaputra sediment sample from this study (BR8210) has been measured by Lupker et al., (2013), we can use these data along with the estimate of the Himalayan rock end-members [START_REF] Galy | Higher erosion rates in the Himalaya: Geochemical constraints on riverine fluxes[END_REF][START_REF] Singh | Sr and Nd isotopes in river sediments from the Ganga Basin: Sediment provenance and spatial variability in physical erosion[END_REF][START_REF] Singh | Tracing the distribution of erosion in the Brahmaputra watershed from isotopic compositions of stream sediments[END_REF] to determine the provenance for this sample. We calculate that for this Brahmaputra sample, the proportion of LH, and therefore of shales-derived sediments, is 20±10%.

Mackenzie River: The upper crust drained by the main Mackenzie tributaries is composed by a mixture between shales and igneous rocks having granodioritic to granitic composition [START_REF] Driver | Petrogenesis of the Cretaceous Cassiar batholith, Yukon-British Columbia, Canada: Implications for magmatism in the North American Cordilleran Interior[END_REF][START_REF] Reeder | Hydrogeochemistry of the surface waters of the Mackenzie River drainage basin, Canada-I. Factors controlling inorganic composition[END_REF]. The Nd and Sr isotope composition has not been measured on sediments from the Mackenzie tributaries. However, a large dataset of shale chemical composition from the Liard River basin is available in [START_REF] Ross | Investigating the use of sedimentary geochemical proxies for paleoenvironment interpretation of thermally mature organic-rich strata: Examples from the Devonian-Mississippian shales, Western Canadian Sedimentary Basin[END_REF]. [START_REF] Dellinger | Apport des isotopes du lithium et des éléments alcalins à la compréhension des processus d'altération chimique et de recyclage sédimentaire[END_REF] shows that some insoluble elements (Cr, Ti, Eu, Cs) have significantly distinct concentration between shales and granitic rocks. larger, yet small fraction of igneous-derived material compared to the Peel. We estimate the composition of the shale end member using the data from [START_REF] Ross | Investigating the use of sedimentary geochemical proxies for paleoenvironment interpretation of thermally mature organic-rich strata: Examples from the Devonian-Mississippian shales, Western Canadian Sedimentary Basin[END_REF], [START_REF] Garzione | Provenance of Paleozoic sedimentary rocks in the Canadian Cordilleran miogeocline: a Nd isotopic study[END_REF] and [START_REF] Morrow | Lower Paleozoic stratigraphy of northern Yukon Territory and northwestern District of Mackenzie[END_REF]. For the shale end member, we estimate that Ti/Al = 0.057±0.002

(median value ± 2σ/Ön, n=101), Cr/Al = 1.54±0.12×10 -3 (n=106) and Cs/Al = 0.10±0.01×10 -3 (n=50). For the granitic end member, we use data from [START_REF] Driver | Petrogenesis of the Cretaceous Cassiar batholith, Yukon-British Columbia, Canada: Implications for magmatism in the North American Cordilleran Interior[END_REF] and [START_REF] Heffernan | Temporal, geochemical, isotopic, and metallogenic studies of midcretaceous magmatism in the Tintina Gold Province, southeastern Yukon and southwestern Northwest Territories[END_REF]: Ti/Al = 0.030±0.005 (n=60), Cr/Al = 0.13±0.29×10 -3 (n=23) and median Cs/Al = 0.050±0.005×10 -3 (n=50). We calculate that the Mackenzie tributaries contain between 70 and 100% of shale-derived sediments. The igneous and shales end members are also represented (as discussed in the section 2 of the data repository).

Western Cordillera: Most of the bedrock of the Canadian western cordillera rivers is formed of volcanic rocks, with a minor contribution of shales. The Sr isotope composition of both dissolved and suspended material for the Skeena and Stikine rivers is unradiogenic (<0.707; [START_REF] Gaillardet | Chemical denudation rates of the western Canadian orogenic belt: The Stikine terrane[END_REF] so we consider that the proportion of shales is lower than 10±10%.

Changjiang: For the Changjiang, we determined the proportion of shales by using the Li concentration in sediments and the relation between the Li concentration and proportion of shales defined by other rivers (see section "The influence of lithology" in the main text). We note that samples CJ33 and CJ34 correspond to rivers draining lowland areas (Wang et al., 2015). Hence, the provenance method based on Li might not be applicable to these rivers. However, their weathering intensity is quite low compared to lowland rivers of the Amazon. In addition, the Li content of the sediments is higher than 85 ppm indicating that even if they have lost a significant proportion of Li, their main source is the erosion of shales (in agreement with the lithology in these two river basin; Wang et al., 2015). Based on the uncertainty on the trend between Li concentration and proportion of shales defined by other rivers, the estimated uncertainty on the proportion of shale-derived particles for Changjiang samples is ±15%. With the shale end member composition being δ 7 Li of -0.5±1‰ and Li/Al of 1.0±0.1×10 -3 and the igneous end member δ 7 Li of +3.5±1.5‰, Li/Al of 0.30±0.12×10 -3 (Dellinger et al., 2014;[START_REF] Sauzéat | New perspectives on the Li isotopic composition of the upper continental crust and its weathering signature[END_REF]. For the Congo River, Henchiri et al., (2016) show that the TTG of the Congo basin have possibly high δ 7 Li (+6 to +7‰) due to their Archean age. Therefore, we use a higher δ 7 Li ign end member of +5±2‰ for the Congo River.

Calculation of the

For the Ganges-Brahmaputra (G-B) system, we note that G-B sands, which are derived mostly from the erosion of high-grade metasedimentary rocks, have a distinct composition (d 7 Li of 0 ± 1‰, Li/Al of 0.40 ± 0.10 × 10 -3 ; Dellinger et al., 2014) relative to igneous and sedimentary rocks. Hence, for the Ganges-Brahmaputra, we consider a mixing between a shale end member and a high-grade metamorphic end member having a δ 7 Li of 0±1‰ and a Li/Al ratio of 0.40±0.10×10 -3 (Dellinger et al., 2014).

Comparison between the Li depletion in sediments and the fraction of Li transported into the dissolved load

As Li is a soluble element, Li concentration in river sediments is sensitive to weathering.

In particular, for a given proportion of shales, lowland rivers have a lower Li/Al ratio than rivers draining mountain ranges (Fig. 2). Yet, this Li-depletion in lowland rivers could be explained by i) the loss of Li by weathering processes and/or ii) an incorrect estimation of the bedrock (i.e. the proportion of shales and/or the composition of the rock end members). Following the approach of Gaillardet et al., (1999), we can test these two hypotheses using a steady state assumption. At steady state, the fraction of Li transported as dissolved should be equal to the Li depletion (Li weathering index (Li/Al) sed /(Li/Al) rock , see main text) in the sediments. The proportion of Li riverine export occurring as dissolved (w Li as defined by [START_REF] Bouchez | Modeling novel stable isotope ratios in the weathering zone[END_REF]) can be calculated using the Li concentration in the dissolved and suspended load and the concentration of suspended sediment transported by the rivers.

< => = 1 1 + Li +:; Li ;>++ × SPM
With [Li] sed , [Li] diss and [SPM] being respectively the Li concentrations in sediment, and dissolved load, and the suspended sediment concentration. The comparison between (1-w Li ) and the weathering index (Fig. DR6) shows that at first order, there is a relatively good agreement between the amount of Li depletion in the sediments and the fraction of dissolved Li export, within uncertainties. This calculation does not take into account the change in Li concentration in the sediments with depth. Indeed, in large rivers draining mountain ranges, the grain size distribution of the suspended sediment load is generally bimodal with a fine mode composed of clay and silt particles and a coarse mode composed of sands (Bouchez et al., 2011a;[START_REF] Dellinger | Apport des isotopes du lithium et des éléments alcalins à la compréhension des processus d'altération chimique et de recyclage sédimentaire[END_REF][START_REF] Lupker | Predominant floodplain over mountain weathering of Himalayan sediments (Ganga basin)[END_REF]. The fine sediments (< 63 µm) are relatively homogeneously distributed in the water column while coarse sediments (size > 63 µm) concentration strongly increases from the surface toward the bottom of the river channel (Bouchez et al., 2011b;[START_REF] Galy | Efficient organic carbon burial in the Bengal fan sustained by the Himalayan erosional system[END_REF][START_REF] Lupker | A Rouse-based method to integrate the chemical composition of river sediments: Application to the Ganga basin[END_REF]. As coarse sediments are mostly composed of quartz, the Li concentration in sediments decreases toward the bottom of the channel because of dilution by increasing quartz amount. This implies that the (1-w Li ) values calculated from surface sediments are underestimated. However, as

shown by Dellinger et al., (2015), the difference is relatively small (less than 0.05 units of w Li values). In addition, we note that in lowland rivers suspended sediments collected at any depth contain a negligible amount of coarse (> 63µm) particles [START_REF] Meade | Suspended sediment in the Amazon River and its tributaries in Brazil during 1982-84[END_REF]. Therefore, the conclusions about the agreement between (1-w Li ) values and (Li/Al) sed / (Li/Al) rock stands whether these values are depth-integrated or calculated with surface sediments only. and "Q" the discharge) and erosion rates are from multiple sources [START_REF] Armijos | Suspended sediment dynamics in the Amazon River of Peru[END_REF]Dellinger et al., 2015b;[START_REF] Gaillardet | A global geochemical mass budget applied to the Congo basin rivers: Erosion rates and continental crust composition[END_REF][START_REF] Guyot | Dissolved solids and suspended sediment yields in the Rio Madeira basin, from the Bolivian Andes to the Amazon[END_REF][START_REF] Moquet | Chemical weathering and atmospheric/soil CO2 uptake in the Andean and Foreland Amazon basins[END_REF][START_REF] Wittmann | Sediment production and delivery in the Amazon River basin quantified by in situproduced cosmogenic nuclides and recent river loads[END_REF]. [Li] diss corresponds to the dissolved Li concentration, TDS sil to the total dissolved load deriving from silicates weathering (in mg/L). Sediment concentration corresponds to the mean measured suspended sediment concentration for each river (in mg/L). Henchiri et al., (2016).

Sample name River

Weathering Intensity (W/D) Amazon Lowlands AM01-17 Orthon 0.137 0.73 ± 0.12 -0.10 ± 0.89 -5.58 ± 1.07 0.77 ± 0.09 0.83 ± 0.11 Dellinger et al., (2014Dellinger et al., ( , 2015) ) AM01-18 Yata 0.259 0.95 ± 0.14 -0.36 ± 0.93 -4.90 ± 1.12 0.84 ± 0.07 0.91 ± 0.12 Dellinger et al., (2014Dellinger et al., ( , 2015) ) AM01-27 Trombetas 0.504 0.00 ± 0.10 3.50 ± 1.50 -8.63 ± 1.75 0.38 ± 0.14 0.58 ± 0.10 Dellinger et al., (2014Dellinger et al., ( , 2015) ) AM01-22 MES Negro 0.291 0.73 ± 0.10 -0.11 ± 0.90 -2.61 ± 1.20 0.68 ± 0.15 0.49 ± 0.07 Dellinger et al., (2014Dellinger et al., ( , 2015) ) AM6/1-09 MES Urucara 0.367 0.65 ± 0.11 0.04 ± 0.90 -4.02 ± 1.10 0.66 ± 0.12 0.52 ± 0.08 Dellinger et al., (2014Dellinger et al., ( , 2015) ) AM01-29 Tapajos 0.581 0.28 ± 0.14 1.37 ± 1.11 -7.37 ± 1.50 0.45 ± 0.18 0.42 ± 0.20 Dellinger et al., (2014Dellinger et al., ( , 2015) ) Congo

the 7

 7 Li of clastic sediments can clearly discriminate between high weathering intensity Publisher: GSA Journal: GEOL: Geology DOI:10.1130/G38671.1 Page 11 of 17 settings (typical of tropical lowland areas like the Congo River basin) and intermediate to low weathering intensity regimes.

Figure 1 .

 1 Figure 1. Li isotope composition as a function of Li concentration for large river

Figure 2 .

 2 Figure 2. A: The Li/Al ratio in fine sediments as a function of the proportion of shales in

Figure 3 .

 3 Figure 3. A: Li isotope composition of fine large river sediments corrected from the

  Figure 2Click here to download FigureFig2.pdf

Figure DR1 :

 DR1 Figure DR1: Maps of the river basins (elevation on the left, geology on the right) from this study,with the locations of the samples. The Geological maps are fromHartmann and Moosdorf (2013). The Changjiang samples are fromWang et al., (2015)

Figure DR2 :

 DR2 Figure DR2: ε Nd (0) as a function of the Al concentration in sediments. Solimões and Beni data are fromBouchez et al., (2011a),Dellinger et al., (2015) and[START_REF] Viers | Seasonal and provenance controls on Nd-Sr isotopic compositions of Amazon rivers suspended sediments and implications for Nd and Sr fluxes exported to the Atlantic Ocean[END_REF]. Data for

Fig

  Fig.DR3: Sm/Nd as a function of the ε Nd of lowland river sediments. Shield rock data are from[START_REF] Santos | A new understanding of the provinces of the Amazon Craton based on integration of field mapping and U-Pb and Sm-Nd geochronology[END_REF]. The Tapajós and Pastaza rivers have a εNd(0) and Sm/Nd close to the signature of shield rocks whereas Urucara and Negro river sediments contain shale-derived sediments. The shale end-member corresponds to the average composition of Beni river sediments.

  It is therefore possible to use these element contents to calculate the proportion of shale-derived and igneous rock-derived particles in the fine sediments of the Mackenzie rivers (Fig. DR.5). The Peel River that drain almost exclusively shales have sediments having chemical signature similar to the mean composition of shales from Ross and Bustin (2009). Other rivers have lower Al-normalized concentrations showing that they contain a

  Fig. DR5: Cr/Al as a function of the Cs/Al and Ti/Al ratio for Mackenzie River fine sediments.

Figure DR6 :

 DR6 Figure DR6: Proportion of solid Li transported by the river (1-w Li ) as a function of the Li weathering index calculated as (Li/Al) sed / (Li/Al) rock . The 1:1 line corresponds to the line for which (1-w Li ) is equal to (Li/Al) sed / (Li/Al) rock , meaning that the fraction of Li dissolved export is compatible with that of the solid export, a requisite for steady state denudation.

  download Supplemental file Table-DR1 -Geology -Accepted.xlsx

Table DR1

 DR1

	and DR2
	References

δ 7 Li rock and (Li/Al) rock To

	δ 9 Li %&'( = δ 9 Li +,-×	Li Al +,-Li Al +:;	×γ +,-+ δ 9 Li 123 ×	Li Al 123 Li Al +:;	×(1 -γ +,-)
	Li Al %&'(	=	Li Al +,-	×γ +,-+	Li Al 123	×(1 -γ +,-)
	and

calculate the Li isotope composition of the bedrock, δ 7 Li rock (which is the δ 7 Li that the sediments would have in absence of chemical weathering) and (Li/Al) rock values, we can use the proportion of shales calculated before (γ sha ) in combination with the mixing equation in Dellinger et al., (2014):

Table DR1 :

 DR1 Data for all the clastic river sediment samples from this study. The "references" column

indicate the source of Li isotope and concentration data used for this study. CIA values have been calculated using similar formula as in

[START_REF] Mclennan | Weathering and Global Denudation[END_REF]

. Silicate weathering rates (calculated as Q×

([Na]

sil +[K] sil +[Ca] sil +[Mg] sil ), with "[X] sil " the silicate-derived dissolved concentration of the element X

Table DR1 (next):

 DR1 The parameter "1-w Li " corresponds to the proportion of Li transported in the solid form by the river. The parameter "(Li/Al) sed / (Li/Al) rock " is the ratio between the Li/Al of the sediments and the Li/Al of the rock.

	Sample name Basin	River		Location	Longitude	Latitude	References for Li isotope data Surface	Discha rge	D90 Al	Li	143 Nd/ 144 Nd εNd(0) δ 7 Li	Li/Al (×10 -3 )	CIA [Li]diss TDS Sil
										(km 2 )	(m 3 /s)	(µm) (µg/g)	(µg/g)			(‰)	(g/g)	(mmol/L) (mg/L)
	Amazon Lowlands
	AM01-17	Amazon	Orthon		Riberalta	66°02'11,0'' W 10°48'39,9'' S Dellinger et al., (2014, 2015)	33485	475	89835 59	0.512158	-9.37	-5.7	0.66	82 0.31	19.6
	AM01-18	Amazon	Yata		Mouth	65°35'00,2'' W 10°58'44,8'' S Dellinger et al., (2014, 2015)	20770	222	115390 100 0.512043	-11.61 -5.3	0.87	86 0.08	10.4
	AM01-27	Amazon	Trombetas		Mouth	N.D.	N.D.	Dellinger et al., (2014, 2015)	250000	6200	115312 20	0.511609	-20.08 -5.1	0.17	92 0.037	7.8
	AM01-22 MES Amazon	Negro		Paricatuba	N.D.	N.D.	Dellinger et al., (2014, 2015)	691000	29000	113016 44	0.511930	-13.81 -2.7	0.39	87 0.031	4.3
	AM6/1-09 MES Amazon	Urucara		Mouth	N.D.	N.D.	Dellinger et al., (2014, 2015)	150000	3000	110691 43	0.511895	-14.50 -4.0	0.39	87 0.049	8.7
	AM01-29	Amazon	Tapajos		Mouth	N.D.	N.D.	Dellinger et al., (2014, 2015)	490000	13500	129350 27	0.511698	-18.33 -6.0	0.20	93 0.038	11.5
	Congo
	C89-63 PK 1105 Congo	Congo		Mouth	N.D.	N.D.	Henchiri et al., (2016), this study 3700000 38026		29	0.511796	-16.43 -6.2	0.10	15.0
	C89-65 PK 1105 Congo	Congo		Mouth	N.D.	N.D.	Henchiri et al., (2016), this study 3700000 38026	117769 23	0.511833	-15.70 -5.1	0.19	92 0.10	15.0
	Amazon Andes
	AM01_08	Amazon	Alto Beni		Mouth	67°40'18' W	15°07'24'' S	Dellinger et al., (2014, 2015)	21197	750	84800 79	0.512011	-12.24 -1.8	0.93	74 1.62	26.4
	AM07_04	Amazon	Beni		Rurrenabaque	67°32'05,2" W 14°28'26,8" S Dellinger et al., (2014, 2015)	69980	2153	44 95289 87	0.511998	-12.49 -3.1	0.91	76 1.28	17.4
	AM07_09	Amazon	Beni		Riberalta	66°05'53,8'' W 10°58'44,8'' S Dellinger et al., (2014, 2015)	114379	3772	50 83319 78	0.511994	-12.56 -2.9	0.94	76 0.57	14.9
	AM05_19	Amazon	Madeira		Foz Madeira	58°48′30,1" W 03°27′00,9" S Dellinger et al., (2014, 2015)	1325000 31250 36 111822 99	0.512097	-10.55 -3.4	0.89	78 0.18	12.8
	AM06_65	Amazon	Amazonas		Obidos	55°30′18,6" W 01°56′05,3" S Dellinger et al., (2014, 2015)	4618750 182200 27 107370 81	0.512141	-9.70	-3.6	0.75	78 0.14	11.4
	AM08_13	Amazon	Ucayali		Jenaro Herrera 73°40′28" W	04°54′28" S	Dellinger et al., (2014, 2015)	352593	12090 50 85664 58	0.512158	-9.37	-1.9	0.73	68 0.66	15.6
	AM06_14	Amazon	Solimoes		Manacapuru	60°33′11,0" W 03°19′41,0" S Dellinger et al., (2014, 2015)	2148000 103000 35 100535 58	0.512101	-10.48 -2.6	0.58	76 0.14	13.1
	AM08_36	Amazon	Pastaza		Embouchure	N.D.	N.D.	Dellinger et al., (2014, 2015)	39000	2770	61 97031 26	0.512512	-2.45	-0.2	0.27	68 0.14	24.2
	AM07_14	Amazon	Madre de Dios Riberalta	66°05′54" W	10°57′46" S	Dellinger et al., (2014, 2015)	124231	5602	35 94447 75	0.512106	-10.38		0.79	77 0.22	14.6
	Mackenzie
	CAN09_51	Mackenzie	Red Arctic		Tsiigehtchic	133°46′44.3" W 67°25′34.2" N Dellinger et al., (2014)	18600	159	23 79022 78.1 0.512066	-11.16 -2.4	0.99	77 0.89	8.0
	CAN09_04	Mackenzie	Liard		Fort_Simpson	121°17′6.2" W 61°50′8.6" N Dellinger et al., (2014)	275000	2450	49 64955 51.2 0.511904	-14.31 -1.7	0.79	73 0.63	8.7
	CAN09_47	Mackenzie	Mackenzie		Tsiigehtchic	133°43′23.8" W 67°27′30.1" N Dellinger et al., (2014)	1680000 8990	76477 67.5 0.512013	-12.19 -1.9	0.88	76 0.57	9.5
	CAN10_32	Mackenzie	Middle Channel Inuvik	134°4′49.8" W 68°24′33.3" N Dellinger et al., (2014)	1805200		14 90608 79.3 0.511979	-12.86 -1.7	0.88	79
	CAN09_40	Mackenzie	Peel		Fort_McPherson 134°52′8.6" W 68°19′56.6" N Dellinger et al., (2014)	70600	686	18 80981 81.5 0.512062	-11.23 -2.1	1.01	77 0.71	8.8
	CAN09_28	Mackenzie	Slave		Fort_Smith	111°53′25.7" W 60°0′59.5" N Dellinger et al., (2014)	616400	3200	17 77069 52.8 0.512014	-12.18 -1.3	0.68	76 0.60	12.0
	Changjiang
	CJ1	Changjiang Jinshajiang	Panzhihua	101°37.551' E 26°34.503' N Wang et al., (2015)	285556	1309	24 80546 48.5			-2.2	0.60	69 2.07	18.6
	CJ4	Changjiang Jinshajiang	Yibin	104°33.385' E 28°42.164' N Wang et al., (2015)	485000	8239	22 82252 48.7			-0.5	0.59	73 0.97	18.5
	CJ14	Changjiang Changjiang	Chongqing	N.D.	N.D.	Wang et al., (2015)	867000	10945 24 84970 53.8			-1.0	0.63	71 0.78	13.4
	CJ60	Changjiang Changjiang	Yueyang	113°18.739' E 29°38.079' N Wang et al., (2015)	1250000 15844		76.6			-1.3	0.37	14.2
	CJ52	Changjiang Changjiang	Wuhan	114°29.876' E 30°40.747' N Wang et al., (2015)	1488000 22340 45 83606 61.9			-1.6	0.74	72 0.44	16.9
	CJ36	Changjiang Changjiang	Datong	117°38.324' E 30°46.085' N Wang et al., (2015)	1705000 28266 26 98071 70.9			-1.7	0.72	76 0.27	16.7
	CJ2	Changjiang Yalongjiang	Panzhihua	101°49.200' E 26°40.127' N Wang et al., (2015)	128444	1857	161917 41.3			0.1	0.26	63 0.68	17.0
	CJ5	Changjiang Minjiang		Yibin	104°33.721' E 28°48.779' N Wang et al., (2015)	133000	2732	33 83956 67.0			0.0	0.80	67 0.45	18.3
	CJ33	Changjiang Xiangjiang		Changsha	112°56.795' E 28°07.364' N Wang et al., (2015)	94700	2405	15 108398 86.7			-3.4	0.80	82 0.16	13.3
	CJ34	Changjiang Ganjiang		Nanchang	115°52.053' E 28°40.206' N Wang et al., (2015)	80900	2104	103092 88.6			-4.7	0.86	80 0.25	22.4
	Ganges-Brahmaputra
	IND99-19 MES Ganges	Ganga		Harding bridge 89°1'28.739" E 24°3'10.44" N Dellinger et al., (2014)	1050000 15622	94322 55.0 0.511725	-17.81 -1.02 0.58	0.49	29.8
	BR8210	Brahmaputra Brahmaputra	Jamuna bg.	N.D.	N.D.	Dellinger et al., (2014)	580000	16161	87063 47	0.511897	-14.45 -1.38 0.54	66 1.08	11.8
	Western cordillera
	CAN99-28 MES Skeena	Skeena		Kitwanga	N.D.	N.D.	This study	42200	962	83647 28.7			2.0	0.34	64 0.05	7.9
	CAN99-39 MES Stikine	Stikine		Iskut		N.D.	N.D.	This study	29300	755	75071 24.5			1.2	0.33	63 0.10	7.2
	Sample name	e Nd	143 Nd/	144 Nd
	Betou 1A	-18.30	0.511700
	Betou 1B	-18.13	0.511709
	Betou 1C	-18.16	0.511707
	Betou 2A	-18.44	0.511693
	Betou 2B	-18.92	0.511668

Table DR2 :

 DR2 Nd isotope composition of the Soil profile samples from the Congo river basin. The ε Nd (0) are calculated by normalizing to the CHUR value (0.512638). For details about the samples, see

Al)rock Sample name Basin River Location Longitude Latitude References for Li isotope data Surface Dischar ge D 90 Al Li 143 Nd/ 144 Nd ε Nd (0) δ 7 Li Li/Al (×10 -3 ) CIA [Li] diss

				Proportion of shales	δ 7 Li rock	Δ 7 Lised-rock	1-w Li	(Li/Al)sed / (Li/	References
					(‰)	(‰)
	C89-63 PK 1105 Congo	0.396	0.35 ± 0.10			0.51 ± 0.13	Henchiri et al., (2016), this study
	C89-65 PK 1105 Congo	0.396	0.48 ± 0.11 1.00 ± 1.11 -6.05 ± 1.20 0.45 ± 0.12 0.31 ± 0.07 Henchiri et al., (2016), this study
	Amazon Andes
	AM07_04	Beni	0.005	1.00 ± 0.10 -0.50 ± 1.00 -2.59 ± 1.12 0.97 ± 0.03 0.91 ± 0.08 Dellinger et al., (2014, 2015)
	AM07_09	Beni	0.015	1.00 ± 0.10 -0.50 ± 1.00 -2.38 ± 1.12 0.95 ± 0.03 0.94 ± 0.08 Dellinger et al., (2014, 2015)
	AM05_19	Madeira	0.049	0.85 ± 0.12 -0.30 ± 1.00 -3.08 ± 1.10 0.95 ± 0.03 0.98 ± 0.12 Dellinger et al., (2014, 2015)
	AM06_65	Amazonas	0.058	0.76 ± 0.12 -0.2 ± 1.00 -3.43 ± 1.09 0.94 ± 0.03 0.92 ± 0.12 Dellinger et al., (2014, 2015)
	AM08_13	Ucayali	0.029	0.70 ± 0.08 -0.10 ± 0.89 -1.80 ± 1.05 0.87 ± 0.06 0.92 ± 0.10 Dellinger et al., (2014, 2015)
	AM06_14	Solimoes	0.096	0.80 ± 0.12 -0.24 ± 0.96 -2.36 ± 1.10 0.88 ± 0.06 0.69 ± 0.15 Dellinger et al., (2014, 2015)
	AM08_36	Pastaza		0.32 ± 0.10 1.10 ± 0.93 -1.28 ± 1.14	Dellinger et al., (2014, 2015)
	AM07_14	Madre de Dios 0.035	0.82 ± 0.10			0.95 ± 0.03 0.92 ± 0.10 Dellinger et al., (2014, 2015)
	Mackenzie
	CAN09_51	Red Arctic	0.003	0.95 ± 0.10 -0.47 ± 0.91 -1.94 ± 1.10 0.95 ± 0.03 1.04 ± 0.10 Dellinger et al., (2014)
	CAN09_04	Liard	0.007	0.75 ± 0.10 -0.04 ± 0.91 -1.62 ± 1.08 0.87 ± 0.06 0.97 ± 0.12 Dellinger et al., (2014)
	CAN09_47	Mackenzie	0.016	0.80 ± 0.10 -0.20 ± 0.91 -1.72 ± 1.08 0.87 ± 0.06 1.00 ± 0.12 Dellinger et al., (2014)
	CAN10_32	Middle Channel		0.70 ± 0.10 -0.04 ± 0.91 -1.65 ± 1.05	1.10 ± 0.12 Dellinger et al., (2014)
	CAN09_40	Peel	0.006	1.00 ± 0.10 -0.50 ± 0.91 -1.56 ± 1.10 0.94 ± 0.03 1.01 ± 0.10 Dellinger et al., (2014)
	CAN09_28	Slave	0.020	0.65 ± 0.10 0.15 ± 0.91 -1.45 ± 1.07 0.82 ± 0.08 0.92 ± 0.14 Dellinger et al., (2014)
	Changjiang
	CJ1	Jinshajiang	0.008	0.50 ± 0.15 0.82 ± 1.13 -3.02 ± 1.26 0.80 ± 0.09	Wang et al., (2015)
	CJ4	Jinshajiang	0.016	0.50 ± 0.15 0.78 ± 1.16 -1.28 ± 1.20 0.79 ± 0.09	Wang et al., (2015)
	CJ14	Changjiang	0.003	0.58 ± 0.15 0.48 ± 1.03 -1.48 ± 1.20 0.92 ± 0.04	Wang et al., (2015)
	CJ60	Changjiang	0.006	0.84 ± 0.15 0.49 ± 1.02 -1.79 ± 1.13 0.96 ± 0.03	Wang et al., (2015)
	CJ52	Changjiang	0.012	0.68 ± 0.15 -0.3 ± 0.99 -1.29 ± 1.11 0.92 ± 0.04	Wang et al., (2015)
	CJ36	Changjiang	0.010	0.78 ± 0.15 -0.2 ± 0.99 -1.52 ± 1.10 0.95 ± 0.03	Wang et al., (2015)
	CJ2	Yalongjiang	0.032	0.38 ± 0.15 1.40 ± 1.20 -1.30 ± 1.63 0.64 ± 0.12	Wang et al., (2015)
	CJ5	Minjiang	0.019	0.74 ± 0.15 -0.1 ± 0.97 0.07 ± 1.09 0.92 ± 0.04	Wang et al., (2015)
	CJ33	Xiangjiang	0.014	0.92 ± 0.15 -0.4 ± 0.93 -3.04 ± 1.10 0.92 ± 0.04	Wang et al., (2015)
	CJ34	Ganjiang	0.023	1.00 ± 0.15 -0.50 ± 1.00 -4.20 ± 1.20 0.90 ± 0.06	Wang et al., (2015)
	Ganges-Brahmaputra
	IND99-19 MES Ganga	0.026	0.30 ± 0.10 -0.40 ± 0.95 -0.62 ± 1.00 0.95 ± 0.03 0.99 ± 0.15 Dellinger et al., (2014)
	BR8210	Brahmaputra	0.013	0.20 ± 0.10 0.33 ± 1.10 -1.71 ± 1.30 0.85 ± 0.07 1.02 ± 0.12 Dellinger et al., (2014)
	Western cordillera
	CAN99-28 MES Skeena	0.016	0.00 ± 0.10 3.50 ± 1.10 -1.45 ± 1.00 0.97 ± 0.03 1.02 ± 0.10 This study
	CAN99-39 MES Stikine	0.007	0.10 ± 0.10 2.06 ± 1.20 -0.86 ± 1.00 0.96 ± 0.03 0.86 ± 0.10 This study

GSA Data Repository item

2017xxx, methods, supplementing text, FiguresDR1-DR6and TablesDR1 and DR2, is available online at http://www.geosociety.org/datarepository/2017/ or on request from editing@geosociety.org.

ACKNOWLEDGMENTS

We thank Catherine Chauvel, Philip Pogge von Strandmann, Paul Tomascak, and an anonymous reviewer for constructive comments, and Éric Gayer for his help with map design. This study was funded by the CNRS-INSU program Syster. This is IPGP contribution 3815.