The effect of lithology on the relationship between denudation rate and chemical weathering pathways. Evidence from the eastern Tibetan Plateau.

. The denudation of rocks in mountain belts exposes a range of fresh minerals to the surface of the Earth that are 10 chemically weathered by acidic and oxygenated fluids. The impact of the resulting coupling between denudation and weathering rates fundamentally depends on the types of minerals that are weathering. Whereas silicate weathering sequesters CO 2 , the combination of sulfide oxidation and carbonate dissolution emits CO 2 to the atmosphere. Here, we combine the concentrations of dissolved major elements in stream waters with 10 Be basin-wide denudation rates from 35 small catchments in eastern Tibet to elucidate the importance of lithology in modulating the relationships between denudation rate, chemical 15 weathering pathways, and CO 2 consumption or release. Our catchments span three orders of magnitude in denudation rate in low-grade flysch, high grade metapelites, and granitoid rocks. For each stream, we estimate the concentrations of solutes sourced from silicate weathering, carbonate dissolution, and sulfide oxidation using a mixing model. We find that for all lithologies, cation concentrations from silicate weathering are largely independent of denudation rate, but solute concentrations from carbonates and, where present, sulfides increase with increasing denudation rate. With increasing denudation rates, 20 weathering may, therefore, shift from consuming to releasing CO 2 in both (meta)sedimentary and granitoid lithologies. For a given denudation rate, we report 5 2 – 10-times higher dissolved solid concentrations and inferred weathering fluxes in catchments underlain by (meta)sedimentary rock compared to catchments containing granitoid lithologies, even though climatic and topographic parameters do not vary systematically between these catchments. Thus, varying proportions of exposed (meta)sedimentary and igneous rocks during orogenesis could lead to substantial changes in the sequestration and 25 release of CO 2 that are independent of denudation rate


Introduction
The relationship between chemical weathering and CO2 drawdown modulates the global carbon cycle and Earth's climate (Berner et al., 1983;Walker et al., 1981).Uplift and denudation of rock control the supply of unweathered minerals to the surface of the Earth and impact the residence time of these minerals in the weathering zone (e.g.Gabet and Mudd, 2009;Hilley et al., 2010;Riebe et al., 2001;West et al., 2005).Thus, increases in denudation rates can boost chemical weathering and ultimately affect Earth's climate (Caves Rugenstein et al., 2019;Hilton and West, 2020;Kump and Arthur, 1997;Raymo and Ruddiman, 1992).The impact of chemical weathering on the attendant emission or drawdown of CO2 depends on the relative importance of different weathering pathways (Berner et al., 1983;Bufe et al., 2021;Calmels et al., 2007;Hartmann et al., 2009;Hilton and West, 2020;Torres et al., 2016;Torres et al., 2014).Weathering of silicate minerals by carbonic acid consumes CO2 from the atmosphere and drives the sequestration of this carbon over timescales longer than marine carbonate compensation (Walker et al., 1981).In turn, sulfuric acid produced by the oxidation of pyrite can drive rapid dissolution of carbonate minerals that releases CO2 into the atmosphere over timescales that exceed the timescale of carbonate compensation in the Ocean (Calmels et al., 2007;Das et al., 2012;Spence and Telmer, 2005;Torres et al., 2014), although the impact of that inorganic carbon source and its link to the organic carbon cycle remain debated (Maffre et al., 2021;Torres et al., 2014).
Even though lithology exerts a fundamental control on the link between weathering and Earth's carbon cycle, few studies have directly compared and quantified the impact of lithologic variation on the link between physical denudation and chemical weathering and on the importance of different weathering pathways.Such knowledge is important in the context of mountain building, as ongoing exhumation progressively exposes successions of different lithologies to chemical weathering (Hilton and West, 2020).Landscape-scale weathering fluxes are typically estimated by measuring the solute concentration and runoff in rivers that integrate water fluxes across the upstream catchment (Drever and Clow, 2018;Drever and Zobrist, 1992;Gaillardet et al., 1999;White and Blum, 1995).In many settings, denudation gradients coincide with gradients in precipitation, temperature, tectonics, biomass, and/or substrate properties such as fracture density or metamorphic grade (Dixon et al., 2016); gradients that affect weathering kinetics independently of denudation rates (Drever and Zobrist, 1992;Gaillardet et al., 2018;Godsey et al., 2019;Guo et al., 2019;Ibarra et al., 2016;Li et al., 2016;Oeser and von Blanckenburg, 2020;Uhlig and von Blanckenburg, 2019;White and Blum, 1995).These co-variations can complicate the interpretation of changes in weathering.
Here, we investigate the impact of lithologic variations on chemical weathering across a nearly three-order of magnitude wide denudation rate gradient along the eastern margin of the Tibetan Plateau that includes three well-separated groups of lithology (Fig. 1) and relatively small changes in precipitation, elevation, and temperature (Fig. 2, Table S1).

Geologic setting
On the eastern Tibetan Plateau west of the Sichuan Basin lies the Songpan-Ganze (or Songpan-Garzê) fold belt, which formed during the late Triassic to early Jurassic closure of part of the Paleotethys ocean (Burchfiel et al., 1995;Chen et al., 2007;Weller et al., 2013).The Songpan-Ganze terrane is characterized by a 5 -15 km thick sequence of tightly folded Triassic flysch that overlies Paleozoic metasedimentary rocks and Precambrian basement (Roger et al., 2010;Weller et al., 2013) (Fig. 1).These units have been intruded by granitoids during both the Mesozoic and Cenozoic.Reactivation of the region during the Cenozoic Indo-Eurasian collision formed zones of rapid uplift and denudation within and at the eastern edge of the slowly eroding Tibetan plateau.Here, we focus on the southeastern part of the Songpan-Ganze fold belt in the region around the Danba Structural culmination and the zone of rapid uplift centred around Gongga Shan (Fig. 1).In this area, in-situ 10 Bederived basin-wide denudation rates vary more than 200-fold over a distance of 100-200 km, from 0.018 mm/yr on the plateau margin (Fig. 1) to 7 mm/yr around Mt Gongga and the Danba structural culmination (Cook et al., 2018;Ouimet et al., 2009) (Fig. 1).This variation of denudation rates is reflected in the topography with variations of basin averaged relief between 340 m -5260 m and basin-averaged slopes of 10° -37.9°.The region features three principal lithologic groups.Most of the area exposes the Triassic Songpan-Ganze flysch, a sequence of deep sea turbidites that is unmetamorphosed or weakly metamorphosed over large areas but can reach greenschist facies close to Gongga Shan and the Danba Structural culmination (Burchfiel et al., 1995;Chen et al., 2007).The underlying Paleozoic sequence is exposed in the Danba structural culmination and in the Longmen Shan and consists of a passive margin sequence, which has undergone metamorphism up to amphibolite facies (Huang et al., 2003;Weller et al., 2013).Finally, granitic rocks of a range of ages from Precambrian to Cenozoic are exposed throughout the area (Roger et al., 2010;Roger et al., 2004;Searle et al., 2016) (Fig. 1, Table S1).Rocks within each one of these three broad lithologic groups have varying compositions, but the difference in chemical compositions and mineralogy between these three lithologic groups is greater than the variability within each one of the groups (Chen et al., 2007;Jiang et al., 2018;Weller et al., 2013) (Table S3, Fig. 3).Moreover, minor carbonate and sulfide phases occur in varying proportions in these dominantly silicate lithologies (Chen et al., 2007;Jiang et al., 2018;Weller et al., 2013).
The region is characterized by a cold and humid climate with a pronounced wet monsoon season during the summer months and drier winter months.Mean annual precipitation rates derived by the Tropical Rainfall Measuring Mission (TRMM) vary ~4-5-fold between 300 -1340 mm/yr (Bookhagen and Burbank, 2010) (Fig. 2b).This range of precipitation values is very similar to the range of runoff values previously estimated for small catchments around the Gongga Shan (Table 1 in Jiang et al. (2018)).Our sampled catchments feed the Dadu, Min, and the Yalongjiang rivers, tributaries to the Yangtze river.They are all headwater catchments that fall within a relatively narrow elevation window with catchment averaged elevations of 3500-4800 m with three exceptions at lower mean elevations of 2600 -2800 m (Fig. 2a, Table S1).The treeline lies between ~3500 -4100m.Thus, the majority of catchments spans across the treeline and includes forested areas, grasslands and rocky slopes.
Neither the elevation, nor the annual precipitation in the studied catchments or the temperature of sampled stream waters correlate strongly with the denudation rate across the area (Fig. 2) 3 Methods

Sample collection and analysis
We collected water samples from 35 small catchments around the region of Mt Gongga and the Danba structural culmination (Fig. 1, Table S1).Water samples were collected in mid-May 2018, prior to the rainy season, over a period of 5 days when all catchments were subject to similar hydrological conditions.Most of the sampled catchments drain a single lithologic group: Thirteen catchments drain the Triassic flysch that is dominantly composed of unmetamorphosed or weakly metamorphosed mixed carbonate-siliciclastic sediments.Only two of the flysch catchments include rocks that have been metamorphosed to garnet-bearing greenschists (S18-35 & S18-36, Fig. 3c).Eleven catchments drain granitic rocks, and six catchments drain high-grade Paleozoic and Precambrian metasedimentary rocks, whereas five catchments drain a mix of granitic rocks and Triassic flysch (Fig. 3c, Table S1).Samples were taken as close to sites sampled for cosmogenic nuclide-derived denudation rates (Cook et al., 2018) as possible, and upstream of potential major anthropogenic influences.Water samples were filtered in situ with single-use 0.2 μm filters and collected in HDPE bottles.Aliquots for cation analysis were acidified on-site to a pH of ~2 with 3M ultrapure HNO3.Temperature, pH, and conductivity were measured in the field using a WTW Multi 3430 multimeter.
Anion and cation analyses were conducted at the GFZ Potsdam on a Dionex ICS-1100 Ion Chromatograph and a Varian 720 ICP-OES, respectively, following the procedure described in Bufe et al. (2021).The concentration of bicarbonate was estimated by charge balance.Such estimation is reasonable in active mountain settings where organic acids are scarce and estimates of bicarbonate from charge balance are within uncertainty of alkalinity values from titrations (Galy and France-Lanord, 1999).Analytical uncertainties for cation analyses were derived from the largest deviation of the calibration standards from the calibration line.For anions, uncertainty estimates were derived from the standard deviation of three repeat measurements (Table S2).

Unmixing of solute sources
We consider four major sources of cations to rivers in the study area: Silicate weathering, carbonate weathering, cyclic contributions (assumed to be dominated by wet precipitation), and hotsprings contributions (Table 1).We assume that evaporites are a minor component of the dissolved solids because: (i) Existing petrologic and geochemical studies do not report evaporite deposits in the upper Triassic flysch or in the Paleozoic metamorphic rocks around the Danba Structural culmination (Chen et al., 2007;Jiang et al., 2018), (ii) except for one sample, chloride concentrations range between 4-20 µmol/L and are thus well within the range of concentrations expected for atmospheric chloride input (Gaillardet et al., 1999), and (iii) the ratios of [  2+ + ] concentrations are higher than expected for typical evaporite deposits (Chen et al., 2007;Gaillardet et al., 1999;Jiang et al., 2018).Moreover, we assume that secondary precipitation of carbonate minerals is negligible in the area.This assumption is based on the observation that all samples are either undersaturated with respect to calcium carbonate or are within uncertainty of saturation, except for two Flysch basins that suggest slightly super-saturated conditions (Fig. A1).
We used a 4-endmember inverse model to unmix these contributions based on the relative concentration of the three major soluble cations ( + ,  2+ , and  2+ ) and chloride ( − ) (Bufe et al., 2021;Gaillardet et al., 1999;Kemeny and Torres, 2021;Moon et al., 2014;Torres et al., 2016).The mixing model requires that each one of the endmembers is unique and, therefore, occupies a range of compositions that is distinct from the composition of other endmembers in the considered space (Fig. 3a-b).In the model, we minimized the following set of equations using the constrained linear least squares solver lsqlin in MATLAB: (1-3) With  =  + ,  =  2+ , and  =  − (three equations) under the conditions that: , +  , +  , +  ,ℎ = 1 (4) and Here, [   2+ ] is the ratio of concentrations of ion  and calcium, and  , is the fraction of calcium sourced from endmember .The subscript  denotes the sampled ratio in the river water.The endmember subscripts , , , and ℎ denote contributions from silicate, carbonate, cyclic (precipitation), and hotspring sources respectively.
Equations 1-5 were then solved separately for each of the 35 samples based on the input endmember compositions , see Table 1) and the measured ratios ([ , see Table S2).Note that one out of three different silicate endmembers was chosen for each sample, depending on the lithology in the sampled catchments (Table 1, Table S1).Where catchments contain a mix of different lithologies (for example S18-22 and S18-23, see Table S2), the input silicate endmember was determined by the average between the silicate endmembers from the lithologies weighted by the areal coverage of each lithology class in the catchment (see Table S1).
In order to represent the uncertainty of the endmember compositions in the inversion result, we implemented a Monte Carlo approach and ran 100,000 iterations of the inversion for each sample.For each iteration, we randomly picked the endmember from a normal distribution with mean and standard deviation defined by the endmember estimate and its uncertainty (Table 1).For the hotspring endmember, we instead picked from a uniform distribution defined by a minimum and maximum estimate (see rational below, Table 1).For each sample (35 samples) and each iteration (100,000 iterations) we used a reduced chisquared statistic to estimate the goodness of fit of that sample and iteration.(see Table S2 for data and uncertainties) and ( 2) , the squared distances between the endmember ratios picked from the normal distribution [ (see Table 1 for endmember values and uncertainties) with: and where The choice of this weighting is arbitrary, and the absence of any weighting does not change the results substantially.For each sample, the best fit set of endmembers and corresponding fractions,   , was then chosen from the iteration with the lowest total misfit,

2
. The uncertainty in these parameters was estimated from all Monte Carlo runs that fit the data within a threshold of   2 ≤ 1 (on average 9% of runs).The high number of runs above the threshold of   2 > 1 is linked to our approach of picking groups of endmembers independently for each Monte Carlo iteration from the entire endmember space (see example in Fig. A2) without an optimization (e.g.Moon et al., 2014).
The most important parameters in the mixing model are the endmember estimates (Table 1).Both, silicate and carbonate endmembers are based on compiled bedrock compositions around the study area (Chen et al., 2007;Jiang et al., 2018;Weller et al., 2013) (Table S3) as well as the assumption that: 2+ ]  = 0. Published bulk rock analyses of rocks in the region show a substantial variability.Nevertheless, samples from the three individual lithologic groups (granitoids, Paleozoic passive margin metapelites and Triassic flysch) form distinct trends in Mg 2+ /Ca 2+ -Na + /Ca 2+ space (Fig. 3a-b).The composition of the granitoids varies around the global silicate endmember estimated from small streams that drain pure silicate lithologies (Burke et al., 2018;Gaillardet et al., 1999).Compared to the granites, the Paleozoic metapelites are substantially enriched in magnesium and the flysch rocks are characterized by high calcium contents (Fig. 3a-b).Major carbonate phases are not reported in the Paleozoic metapelites (Weller et al., 2013) and in the granitoids (Jiang et al., 2018).
Even if trace carbonate minerals can strongly affect solutes sourced from chemical weathering (Anderson et al., 2000;Blum et al., 1998;Emberson et al., 2016b;Jacobson and Blum, 2003), the bulk-rock geochemistry measurement should be affected only negligibly.Thus, we assume that the bulk rock compositions are representative of the silicate endmember from these lithologies, and we use the mean and standard deviation of the elemental ratios from individual bedrock samples as an estimate for the silicate endmember of that bedrock group (Table 1).In turn, the flysch samples contain 4% -80% carbonate that occurs both as calcite minerals and as carbonate cement (Chen et al., 2007).Therefore, these samples represent a mix between a carbonate and a silicate endmember (Fig. 3b).Based on two sediment samples with the highest carbonate content and zero sodium (Table S3), we estimated the magnesium content of carbonates in the area to = 0.038 ± 0.006 and 〈   〉   = 0.023 ± 0.004 where subscript  denotes data from bedrock samples and the angle brackets denote the concentration in weight percent rather than in moles.This low ratio is consistent with the absence of reported dolomite in the area (Chen et al., 2007).Based on knowledge of the carbonate endmember, [ And   is the molar mass of component  (Bufe et al., 2021).We estimated both ratios based on the assumption that the carbonate content of the bedrock flysch sample with the lowest carbonate content (farthest away from the origin along the regression in 2+ ]-space) has a carbonate content of 〈 0.96 ,  0.04  3 〉 = 4-10 wt%.The minimum value (4%) is from the lowest observed carbonate content in the field (Chen et al., 2007), whereas the upper bound is chosen so that the range of resulting values reaches the global endmember value of 2.7.We then used an average of the resulting ratios estimates with an uncertainty based on half of the range (Fig. 3a-b).
For the cyclic endmember, we used a volume weighted average of rainwater compositions from the eastern flank of Gongga Shan (Jiang et al., 2018) (Table 1, Table S4).The hotspring endmember is also based on hotspring compositions around Mt Gongga (Jiang et al., 2018) (Table S5).All hotsprings are very distinct from rock samples, and notably characterized by [  +  2+ ]ratios that are 3 -150-times higher than the highest measured stream water samples (Fig. 3a, Table S5).Nevertheless, hotspring compositions are highly variable (Fig. 3a), despite a relatively small area that was sampled.In the inversion, we therefore did not sample the hotspring endmembers from a normal distribution around a mean value.Instead, we picked As an alternative to the inverse model, we decomposed the data with a common forward approach (Bufe et al., 2021;Galy and France-Lanord, 1999;Jacobson and Blum, 2003;Meybeck, 1987;Moon et al., 2014).We assumed that all chloride in the river water samples was atmospherically derived and use precipitation-averaged [   − ]  -ratios of the measured rainwater (Jiang et al., 2018) (Table S4) to adjust the sample concentrations for rain input.We assumed that our rainwater correction accounts for possible anthropogenic input of SO4 from the industrialized Sichuan Basin through acid rain, and we neglected hotspring contributions.Then, the contributions of silicate and carbonate to the total dissolved Ca 2+ and Mg 2+ concentrations were estimated as: 16).
Equivalent to the inverse model (equations 10 -11), the silicate endmember ratios for the flysch samples were found by correcting for the carbonate content of the flysch bedrock samples:

Cation sums and fractions
The total sums of cations from silicate and carbonate weathering are: and in charge equivalents: The fraction of carbonate weathering is: The fraction of weathering by sulfuric acid (as opposed to carbonic acid) was estimated from sulfate concentrations (Bufe et al., 2021;Emberson et al., 2018;Galy and France-Lanord, 1999;Torres et al., 2016): where [ 4 2− ]  is the sulfate concentration that is sourced from sulfide oxidation given by: Note that this estimate of [ 4 2− ]  assumes that contributions of sulfate from evaporites are negligible in the area, and that any (likely minor) anthropogenic input as well as minor salts associated with the metasedimentary rocks are captured by the cyclic endmember measured in rainwater samples.

Estimate of denudation rate
Denudation rates were obtained from existing cosmogenic nuclide concentrations of in situ-produced 10 Be (Cook et al., 2018;Ouimet et al., 2009).For two sampled catchments (S18.08 and S18.29) without previous denudation rate estimates, we processed two additional samples for analysis of in situ 10 Be following the procedure in Cook et al. (2018).Denudation rates were calculated using CRONUS scripts and the Lal/Stone scaling scheme with a sea-level low latitude nucleogenic production rate of 3.7 (Balco et al., 2008) (Table S6).These denudation rates integrate over the time denuding material resides in the first few upper meters of Earth surface.Although this integration time varies between catchments with different denudation rates, it reflects the timescale of mineral supply to the weathering zone, and is therefore appropriate for comparison to weathering proxies.Where landslides dominate, their stochastic occurrence may disrupt the relationship between soil formation and chemical weathering (Emberson et al., 2016a;Emberson et al., 2016b) and may bias the denudation rate estimates (Chen et al., 2020;Niemi et al., 2005;Tofelde et al., 2018;Yanites et al., 2009).We assume that any such bias is within uncertainty of the denudation rate measurement.Cosmogenic-derived denudation rates incorporate both physical denudation and chemical weathering, but physical denudation rates commonly greatly dominate denudation in active orogens uplifting siliceous rocks with minor carbonates, such as the ones described here (Dixon and von Blanckenburg, 2012;Erlanger et al., 2021;Gaillardet et al., 1999;Riebe et al., 2001;West et al., 2005).Thus, we assume that increasing denudation rates correspond to increasing physical erosion rates.Finally, in situ 10 Be-derived denudation rates measure the denudation of quartz-containing bedrock.
Based on published bedrock descriptions (Burchfiel et al., 1995;Chen et al., 2007;Jiang et al., 2018;Weller et al., 2013) and observations by the authors (Cook et al., 2018), we assume that carbonate and silicate phases in granitoids and metasediments are mixed to a degree that quartz-derived denudation rates approximate the denudation of the entire rock mass.We acknowledge that unquantified uncertainties may arise where significant weathering occurs below the top few meters of the regolith (Riebe and Granger, 2013), or where significant differences in quartz mineral contribution within the bedrock occur, but these uncertainties are unlikely to change the major trends observed in this work.

Results
In the studied catchments, the concentration of dissolved cations (TDC) generally increases with denudation rates (Fig. 4a).
However, the strength of that relationship is greatly influenced by lithology (Fig. 4a).Whereas TDC increases 5 -10-fold in the Triassic Songpan Ganze flysch, the increase of TDC with denudation in the granitic catchments is less than 2-fold and associated with substantial uncertainty (Spearman's p value of 0.19) (Fig. 4a).Mixed flyschgranitic catchments fall inbetween the two trends (Fig. 4a).Catchments with Paleozoic metamorphic lithologies have scattered TDC values, many of which fall within the range of values of the Triassic rocks (Fig. 4a).Magnesium and calcium dominate the solute load and constitute 42 -96% (median 84%) of the TDC.The pattern of increasing TDC is dominated by an increase in calcium concentrations (Fig. 4b), whereas correlations between denudation rate and magnesium, sodium, and potassium concentrations are uncertain (Spearman's p values between 0.1 -0.9) (Figs.4c-e).Similarly, no relationship between chloride concentrations and denudation rates is evident (Fig. 4e), but sulfate concentrations show a strong increase with denudation rates in both granites and flysch lithologies (Fig. 4g).
The unmixed cation contributions follow the expectations from the raw data: Cation concentrations from carbonate weathering, Ccarb, and sulfate from sulfide oxidation, [ 4 2− ]  , display a strong relationship with denudation (Fig. 5a, c).In the flysch and in the Paleozoic metamorphics they increase strongly with denudation rate, whereas the increase in the granitic catchments is weaker, and the mixed catchments are in-between (Fig. 5a, c).In contrast, cations from silicate weathering, precipitation sources, and hotsprings generally show no relationship to denudation rate for any of the lithologies (Fig. 5b, d-e).
The contribution of carbonate weathering to the total solute load from weathering, Fcarb, strongly increases with denudation irrespective of rock type (Fig. 6a).Even in granitic catchments carbonate weathering contributes 30 -89% (median 65%) of the cation concentration (Fig. 6a).Thus, both granites and (meta)sedimentary lithologies have comparable fractions of carbonate weathering (Fig. 6a), even if the absolute concentrations differ (Fig. 4).The fraction of weathering by sulfuric acid, Fsulf, also increases with increasing denudation rate, although there is a large amount of scatter at higher denudation rates (Fig. 6b).
In 24 out of 35 samples (67% of samples), the inferred silicate and/or carbonate cation contributions differ by more than 20% between forward and inverse approaches (Fig. A3).For example, forward-modelled carbonate cation concentrations are more than 20% higher than results from the inversion in 11 samples (31% of samples) and more than 50% higher in 3 samples (9% of samples) (Fig. A3).Silicate cation concentrations inferred from the forward approach are lower in these samples.These samples lie outside of the zone formed between the silicate, carbonate, hotspring, and precipitation endmembers (Fig. 3b) which may explain the offset in the results.Conversely, 9 samples (26%) have more than 20% higher silicate cation concentrations inferred by the forward model (Fig. A3).In these samples, the inversion predicts 3 -47% (median 13%) cation contributions from hotsprings whereas the median of the cation contributions from hotsprings across all samples is 2%; The hotspring contribution is ignored in the forward approach, and all of the Na + is attributed to silicate instead, thereby leading to higher silicate cation contributions in the forward model.Despite these differences and resulting outliers, the first order trends described in this contribution are unaffected by the choice of unmixing method (Figs.A4, A5).
Our concentration measurements cannot be converted into weathering fluxes, because we lack discharge or runoff data for the sampled catchments.However, in comparison to the nearly three-orders-of-magnitude-wide denudation gradient, the mean annual precipitation does not vary widely across the catchments: 82% of the catchments differ by less than a factor of two and 90% by less than a factor of three of precipitation (Table S1).Further, there is no co-variation between precipitation and denudation rate (Fig. 2b, Table S1).The first-order patterns described above do not change substantially when we consider "inferred" weathering fluxes that are obtained by using mean annual precipitation values as a proxy for runoff (Fig. A6).
Therefore, it is unlikely that differences in runoff between catchments strongly affect our data, and we interpret the observed patterns as reflecting the response of the weathering system to changes in denudation fluxes.

Discussion
Our analysis indicates that increasing denudation rates lead to an increase in carbonate weathering and sulfide oxidation in all sampled lithologies (Figs.5-6), likely due to the increased supply of carbonate and sulfide minerals during erosion (Bufe et al., 2021;Calmels et al., 2007;Torres et al., 2016).Conversely, silicate weathering appears to be insensitive to denudation rate and represent a small proportion of the total weathering budget (Figs.5-6).While the granitic catchments have systematically lower cation concentrations from carbonate weathering than the metasedimentary catchments (Fig. 5a), the fraction of carbonate weathering (Fcarb) is increasing with denudation and is of similar magnitude in all rock-types (Fig. 6a).Even in catchments underlain by granitoid rocks, weathering of carbonate phases dominates the solute load at denudation rates above 0.1 mm/yr (Fig. 6a).This finding likely arises from the dissolution of trace carbonate minerals disseminated in the crustal granitoids and metapelites that has been described in a number of active mountain ranges (Blum et al., 1998;Bufe et al., 2021;Emberson et al., 2017;Jacobson et al., 2003;Torres et al., 2016;White et al., 1999).In turn, the insensitivity of silicate cation concentrations to denudation (Fig. 5b) is consistent with a kinetic limitation of silicate weathering (Gabet and Mudd, 2009;West, 2012;West et al., 2005).Such kinetic limitation of silicate weathering in conjunction with increasing sulfide oxidation and carbonate weathering across multiple orders of magnitudes of denudation rates (Fig. 5) has recently been documented in the low-grade metasedimentary rocks of southern Taiwan (Bufe et al., 2021).The data presented here suggest that this pattern applies to metasediments in another mountain range, as well as to granitoid rocks.A series of studies on soil formation in metasedimentary and granitic rocks across denudation rates from 10 -3 mm/y to 2 mm/y has suggested a link between soil denudation rates and soil production rates, and this sensitivity of soil formation rates to denudation has been used to argue for a relationship between orogenesis and silicate weathering (Dixon et al., 2012;Dixon and von Blanckenburg, 2012;Larsen et al., 2014;Riebe et al., 2004;Riebe et al., 2001).Spanning a comparable range of denudation rates, our data confirm that these findings from soil profiles may not directly translate to the catchment scale (Dixon and von Blanckenburg, 2012;West et al., 2005).This disconnect is due, most likely, to the dilution of soil waters by fluids that drain parts of the landscape that are not soil-covered or follow deep pathways through bedrock.For example, mass movements, such as landslides, that dominate erosion in parts of the study area are expected to alter weathering fluxes (Emberson et al., 2016a).Thus, in active mountain ranges, landscape-scale silicate weathering may be largely insensitive to denudation rates independently of the major lithologies (Bufe et al., 2021;Gabet and Mudd, 2009;West, 2012).
Even though yearly average precipitation rates do not vary considerably across the denudation rate gradient, monthly precipitation can vary by a factor of ~5 -6 between the high-and low-flow seasons (Jiang et al., 2018).Nevertheless, in small catchments around Mount Gongga, the total dissolved cation concentrations of 80% of rivers is diluted by less than two -fold in the high-flow season (median 1.3-fold) and only Cl -and Mg 2+ show substantial dilution (Jiang et al., 2018).Thus, the patterns of concentrations that we describe here should broadly mirror the differences in annual weathering fluxes between catchments.Solute concentrations during the high-flow season are expected to carry an elevated proportion of carbonate weathering with respect to the low flow season (Kemeny et al., 2021;Tipper et al., 2006).Thus, by sampling during the low flow season, and by not accounting for cation exchange with suspended sediment from the clay minerals (Tipper et al., 2021), we might overestimate the proportion of silicate weathering (Kemeny et al., 2021;Tipper et al., 2006;Tipper et al., 2021).The dominance of carbonate weathering over silicate weathering in all catchments (Fig. 6) would, therefore, most likely be strengthened with more data across all seasons and/or with suspended sediment data.
The sulfuric-acid-derived sulfate concentrations [ 4 2− ]  and the cation concentrations from silicate weathering allow to estimate the concentration of CO2 that is sequestered or emitted during chemical weathering (Emberson et al., 2018;Torres et al., 2016).Beyond the calcium carbonate compensation time of ~10 ky; (Zeebe and Westbroek, 2003), the moles of CO2 produced (positive [ 2 ]) or sequestered (negative [ 2 ]) during chemical weathering per unit volume of weathering fluid can be expressed as: (Bufe et al., 2021;Torres et al., 2016) (Table S7).Note that this formulation is independent of the proportion of sulfuric acid that weathers carbonates or silicates (see supplement of Torres et al., 2016).The increase of Fcarb and Fsulf with denudation rate (Fig. 6) leads to a clear change from CO2 sequestration to dominantly CO2 release (Fig. 7).These observed trends are most likely explained by the combination of a supply limitation on coupled pyrite oxidation and carbonate weathering and a limitation of silicate weathering rates by the slow dissolution kinetics of silicate minerals (Bufe et al., 2021;Calmels et al., 2007;Gabet and Mudd, 2009;Torres et al., 2016).Eleven catchments fall into the long-term CO2 release field including all but two of the metamorphic catchments (Paleozoic and Triassic), two of the granitoid catchments, and three mixed granitic/metamorphic catchments (Fig. 7).All of these catchments have denudation rates above 0.19 mm/yr.Thus, increasing denudation rates, lead to decreases in the proportion of weathering that contributes to CO2 drawdown, as sulfate concentrations increase, while silicate cation concentrations are invariable .
Compared to the other lithologies, water samples from granite catchments have substantially lower solute concentrations than waters from (meta)sedimentary catchments (Fig. 4a) and weathering in granitoid catchments remains closest to a balance between CO2 release and CO2 consumption across the entire denudation rate gradient (Fig. 7).This contrast persists when we consider "inferred" weathering fluxes that are obtained using mean annual precipitation values as a proxy for runoff (Fig. A6d).In the absence of major differences in climate or topography between granitic and metasedimentary catchments (Fig. 2 ), this contrast in concentrations is most likely due to low proportions of minor carbonate and sulfide phases in the granitoid lithologies (Fig. 5a,c).In this case, variations in lithology may change the flux of CO2 drawdown or release by a factor of 2 weathering fluxes (up to a factor of 2 -10) independently of variations in denudation rates or runoff.

Conclusion
Water chemistry data from catchments on the eastern margin of the Tibetan plateau that span across three orders of magnitude in denudation rate illustrate the role of lithology in modulating the link between denudation rate and chemical weathering.
Perhaps surprisingly, our data show a uniformity in the first-order relationships between weathering and denudation between different lithologies.In particular, in all lithologies, silicate cation concentrations do not increase with increasing denudation rates whereas concentrations of sulfate and of cations from carbonate do show an increase.Whereas granitic and (meta)sedimentary rocks are characterized by similar fractions of carbonate weathering that are increasing with denudation rate, the (meta)sediments have higher absolute concentrations of sulfate and of cations from carbonate weathering, likely due to higher concentrations of these minor phases in the bedrock.In combination, the weathering reactions lead to a transition from CO2 drawdown to dominantly CO2 release at denudation rates higher than 0.2 mm/yr, that may .In turn, absolute weathering fluxes can vary by a factor of 2 -10 between catchments draining granites and (meta)sediments with implications for the role of changes in the relative exposure of igneous and sedimentary rocks during mountain growth.

Figure A3: Difference between forward and inverse unmixing approaches
Positive values indicate that the inverse approach predicts higher cation ratios than the forward approach.All samples in the upper left quadrant are outside of the carbonatesilicatehotspringprecipitation endmember space in Na + /Ca 2+ -Mg 2+ /Ca 2+ space (Fig. 3c).
Samples with lower inverse silicate cation concentrations are characterized by 3-47% hotspring contribution that is not accounted for in the endmember value normalized by the uncertainty of the endmember values  [   2+ ] ,,,ℎ and [ 2+ ] ℎ from uniform distributions that span the interquartile range of all hotspring samples.Because of a strong correlation between [ − ] ℎ and [ + ] ℎ in these hotsprings, we then picked [ − ] ℎ from the regression between [ − ] ℎ and [ + ] ℎ .

Figure 5 :
Figure 5: Unmixed contributions to the solute load (a) Cation concentrations from carbonate weathering.(b) Cation concentrations from silicate weathering.(c) Sulfate concentrations 445

Figure 6 :Figure 7 :
Figure 6: Fraction of carbonate weathering and weathering by sulfuric acid 450

Figure A1 :
Figure A1: Saturation index of samples with respect to calcium carbonate Catchments underlain by different lithologies are distinguished by symbols and color.Datapoints with a black dot are metamorphosed to greenschist facies or higher.

Figure A2 :
Figure A2: Example of mixing lines from Monte Carlo modelling in Na + /Ca 2+ -Mg 2+ /Ca 2+ space 470 480 forward model (see text).Catchments underlain by different lithologies are distinguished by symbols and color.Datapoints with a black dot are metamorphosed to greenschist facies or higher.

Figure A4 :
Figure A4: Forward model results for silicate, carbonate, and sulfide weathering contributions 485

Figure A5 :
Figure A5: Forward model results for the fraction of carbonate weathering and weathering by sulfuric acid Data from Fig. 6 plotted with results from the forward model (white points).Lithology in the data from the forward model is distinguished denudation are similar across all lithologies, the absolute weathering fluxes are not.As a consequence, our data suggest that changes in the exposed lithologies across an orogenic cycle can substantially alter