Investigating δ13C values in stalagmites from tropical South America for the last two millennia

Valdir Felipe Novello, Francisco William da Cruz, Mathias Vuille, José Leandro Pereira Silveira Campos, Nicolás Misailidis Stríkis, James Apaéstegui, Jean-Sébastien Moquet, Vitor Azevedo, Angela Ampuero, Giselle Utida, et al.

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To cite this version:

Valdir Felipe Novello, Francisco William da Cruz, Mathias Vuille, José Leandro Pereira Silveira Campos, Nicolás Misailidis Stríkis, et al. .. Investigating δ13C values in stalagmites from tropical South America for the last two millennia. Quaternary Science Reviews, 2021, 255, pp.106822. 10.1016/j.quascirev.2021.106822. insu-03141092

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Distributed under a Creative Commons Attribution 4.0 International License
1 Investigating δ¹³C values in stalagmites from tropical

2 South America for the last two millennia

3 Valdir Felipe Novelloª*; Francisco William da Cruzª, Mathias Vuilleᵇ, José Leandro

4 Pereira Silveira Camposª, Nicolás Misailidis Stríkisᶜ, James Apaésteguiᵈ, Jean Sebastien

5 Moquetᵉ, Vitor Azevedoª, Angela Ampueroª, Giselle Utidaª, Xianfeng Wangf, Gustavo

6 Macedo Paula-Santosg, Plinio Jaquetoh, Luiz Carlos Ruiz Pessendai, Daniel O Breeckerj,

7 Ivo Karmannª

8 ªInstitute of Geosciences, University of São Paulo, São Paulo, 05508-080, Brazil.

9 ᵇDepartment of Atmospheric and Environmental Sciences, University at Albany, Albany, 12222, USA.

10 ᶜDepartamento de Geoquímica, Universidade Federal Fluminense, Niterói, 24020-141, Brazil.

11 ᵈInstituto Geofísico del Perú, Lima, 15012, Peru.

12 ᵉInstitut des Sciences de la Terre d'Orléans, Orléans, 45100, France.

13 ᵈEarth Observatory of Singapore, Nanyang Technological University, Jurong West, 639798, Singapore.

14 ᵉInstitute of Geoscience University of Campinas, 13083-855.

15 ᵇInstituto de Astronomia, Geofísica e Ciências Atmosféricas, University of São Paulo, São Paulo, 05508-090, Brazil

16 ᵈCenter for Nuclear Energy in Agriculture (CENA), University of São Paulo, São Paulo, 13416-000, Brazil.

17 ᵉJackson School of Geosciences, University of Texas, Austin, 2305, USA.

20 *Correspondence to: Valdir F. Novello (vfnovello@gmail.com).

21

22 Abstract

23 Due to the many factors controlling δ¹³C values in stalagmites, complicating their paleoclimatic
24 and paleoenvironmental interpretation, most studies do not present δ¹³C values, but instead focus mainly
25 on δ¹⁸O values. This is also the case for most cave studies from tropical South America, where many new
26 δ¹⁸O stalagmite records covering the last millennia were recently published. Here, we review the δ¹³C
27 values in stalagmites, investigating the influence of local hydroclimate, altitude, temperature and
28 vegetation types on δ¹³C values in stalagmites, by employing a new dataset composed of published and
29 unpublished carbon isotope records from various sites in tropical South America. The main factors
30 influencing δ¹³C values are associated with the local hydroclimate, followed by minor effects from
31 temperature. Most of the isotopic records show a significant correlation between the δ¹³C and δ¹⁸O values,
32 indicating a close relationship between local hydroclimate and atmospheric convective processes related
33 to the South American Monsoon System.

34

35 **Keywords:** δ¹³C, speleothem, stalagmite, hydroclimate, South America.
## 1 Introduction

Measurements of carbon isotope (δ¹³C) ratios are essential for (paleo)environmental studies, such as those regarding the carbon cycle, past food consumption by pre-historic societies, paleo-vegetation reconstructions, soil dynamics, aspects regarding animal migration and food consumption, etc. (Rayner et al., 1999; Calo and Cortés, 2009; Pansani et al., 2019; Novello et al., 2019). However, δ¹³C values of speleothems are generally considered difficult to interpret and, in most cases, are not reported in isotopic studies based on speleothems. Studies from tropical South America, in particular, have almost completely neglected δ¹³C values from stalagmites and instead relied solely on δ¹⁸O values for reconstruction of the South American Monsoon System (SAMS) (Reuter et al., 2009; Novello et al., 2012; 2016; 2018; Apaéstegui et al., 2014; 2018; Vuille et al., 2012; Kanner et al., 2013; Wang et al., 2017). Here we present a compilation of 25 δ¹³C records (13 of them hitherto unpublished) from stalagmites collected at different sites throughout tropical South America and covering the last two millennia (referred to here as the δ¹³C_2k_SA dataset) with aims to revise and characterize the main factors controlling δ¹³C variability in these stalagmites and provide possible paleoclimate and paleoenvironmental reconstructions for the region.

In Section 2 we review the mechanisms that control the δ¹³C values in the stalagmites and the related global and regional forcings. In Section 3 we present the data, the stalagmites and methods. In Section 4 we present the study sites and describe the environmental and climate characteristics that might affect the δ¹³C values in the stalagmites from tropical South America. In Section 5 we show the results (data set) and in Section 6 we discuss the interpretations of the new records and their regional relationships. Additionally, using Principal Component Analysis (PCA), we propose a new hydrological index for South America based on the δ¹³C_2k_SA dataset.

## 2. Background

### 2.1 Main processes controlling δ¹³C values in speleothems

The initial source of carbon for speleothems is the CO₂ present in the soil, mainly provided by plant roots' respiration and decomposition of organic matter. It forms carbonic acid in contact with water, which dissolves cave host-rock (limestones or dolostones) according to the equation:

$$ \text{Eq.} \quad CaCO_3 + H_2O + CO_2 \leftrightarrow Ca^{2+} + 2HCO_3^- \quad (1) $$
Open and closed system models were proposed to explain two extreme cases of dissolution of calcium carbonate in the percolating solution (Fohlmeister et al., 2011; McDermott et al., 2004; Hendy, 1971). In an open system, the percolating solution remains in equilibrium with the infinite reservoir of soil CO₂ and, thereby, the bicarbonate in solution receives the δ¹³C fingerprint of this reservoir. Under these conditions, the contribution of the δ¹³C values from the bedrock to the HCO₃⁻ in solution can be neglected. In a closed system, during the percolation into the epikarst, the solution loses contact with the soil CO₂, and the CO₂ in solution is progressively consumed through the dissolution of the bedrock. The rock dissolution is limited by the initial amount of CO₂ and, consequently, through this process the δ¹³C from the bedrock influences the isotopic composition of the remaining solution (McDermott, 2004). In most caves, the interaction between the percolation solution and the host-rock occurs as an intermediate way between open and closed systems.

The δ¹³C values in pedogenic carbonate are closely related to the isotopic values from the surrounding vegetation (Cerling, 1984; Quade et al., 1989), defined by the plant type (C₃, C₄ or CAM), which in turn, will be conditioned by climatic parameters such as temperature, pluviosity, rainfall seasonality and atmospheric CO₂ (Ehleringer et al., 1997). Vegetation dominated by C₃ plants has δ¹³C values between -32 ‰ and -20 ‰, while vegetation dominated by C₄ plants is characterized by values between -17 ‰ to -9 ‰ (Badeck et al., 2005). CAM plants have δ¹³C values that overlap with both C₃ and C₄ plants. In addition, δ¹³C values of individual C₃ plant species can vary approximately 1 to 2 ‰, depending on water availability (e.g., Hartman and Danin, 2010). The differences in the δ¹³C values from total organic matter in soil resulting from the dominant plant types are transferred to stalagmites precipitated under their respective environment. Thus, stalagmites precipitated in caves under conditions dominated by C₃ plants typically have values ranging from -14 ‰ to -6 ‰, while those forming below C₄ plant cover range from -6 ‰ to +2 ‰ (McDermott, 2004; Baker et al., 1997; Dreybrodt, 1988). Variations in soil δ¹³C values and their evolution over time are controlled by carbon inputs from vegetation, which is proportional to the organic matter amount and vegetation density; thus denser vegetation is also associated with more depleted values in soil δ¹³C and vice-versa (Pessenda et al., 2010). However, the presence of CAM plants can complicate this interpretation since this type of plant present a large range of δ¹³C values. In addition, the δ¹³C values of C₃ plants are sensitive to atmospheric CO₂ levels (Van de Water et al., 1994; Schubert and Jahen, 2012), producing a signal that is transferred to stalagmites (Breecker, 2017).
In the cave system, δ¹³C values from dissolved inorganic carbon (DIC) can undergo fractionation through prior calcite precipitation (PCP), which is forced by CO₂ degassing that preferentially removes ¹²C from the solution to the cave atmosphere (Mickler et al., 2019), depleting ¹²C from the final isotopic product recorded in stalagmites (Baker et al., 1997). PCP increases during drier periods due to the increased exposure of seepage solution to air. This can occur during the contact of the solution with air pockets along the epikarst flow routes and/or with the increase of dripping interval, where the solution is exposed to the cave air for longer time at the stalactites; both results in CO₂ degassing from the solution, promoting the carbonate precipitation in the epikarst and/or stalactites with higher δ¹³C values (Fairchild and Baker, 2012). Therefore, the variations in the PCP rate are climate related. In monsoonal climates, such as in (sub)tropical South America, the amount effect is the dominant process that affects the δ¹⁸O value of rainwater, such that an increase in the amount of rainfall results in waters with lower δ¹⁸O values (Vuille et al., 2012). This increase in rainfall amount might also cause a decrease in the δ¹³C value of speleothem calcite, by increasing the soil moisture content and soil respiration rates or by reducing PCP, resulting in a positive correlation between the δ¹⁸O and δ¹³C values of speleothem calcite/aragonite (Cruz et al., 2006; Mickler et al., 2006; and references therein). While δ¹³C and δ¹⁸O values may be correlated for different reasons, high correlation between both isotopic ratios can also be indicative of forced kinetic fractionation, since carbon and oxygen are fractioned in the same direction in this process (Hendy et al., 1971). The isotopic disequilibrium increases with enhanced ventilation of the cave, which depends on the temperature gradient between the air inside and outside of the cave. However, the range of values resulting from the fractionation factor between CaCO₃ and HCO₃⁻ in tropical temperatures of 15–30 °C has been documented to be < 0.5 ‰ (Polag et al., 2010 and references therein). Recently, Fohlmeister et al. (2020), using a large dataset of δ¹³C values in stalagmites deposited post-1900 CE, show evidence for a temperature control on this proxy, likely driven by vegetation and soil processes, while PCP can explain the wide δ¹³C range observed for concurrently deposited samples from the same cave.

119

## 2.2 Processes controlling the δ¹³C values in speleothems from South America

The main mode of climate variability in tropical South America is defined by the SAMS behavior, which also influences vegetation changes. Most of the δ¹⁸O records from stalagmites in South America show a weak monsoon activity during the Medieval Climate Anomaly (MCA, 900-1100 years CE), in contrast with a strong activity during the Little Ice Age (LIA, 1600-1850 years CE) (Bird et al.,
2011; Vuille et al., 2012; Novello et al., 2016; 2018). During the LIA period, a moisture dipole was documented between the eastern and western portions of tropical South America, due to the displacement of the South Atlantic Convergence Zone (SACZ) toward the southwest (Campos et al., 2019; Novello et al., 2018). This change in climate is still not investigated with the δ¹³C values in stalagmites.

Few studies focused on the δ¹³C values from speleothems in South America. Cruz et al. (2006) interpreted the δ¹³C from Botuverá cave (southeastern Brazil, point 8 in Fig. 1) as a proxy for soil CO₂ productivity, which is modulated at orbital time scales by changes in local temperature brought about by shifts between summer monsoonal and winter extratropical circulation. Novello et al. (2019) reported a decrease of 9‰ in the δ¹³C values from Jaraguá cave (point 6 in Fig. 1) during the transition between the last Glacial and the Holocene periods, resulting from a combination of changes above the cave, including: changes in the predominant vegetation type from C₄ to C₃, increase of organic matter and soil horizons, which were mainly caused by the increase in temperature and atmospheric CO₂. For the last two millennia, Jaqueto et al. (2016) show that the concentration of magnetic minerals and δ¹³C values in the ALHO6 stalagmite from Pau d'Alho cave (point 4 in Fig. 1) is governed by soil dynamics and changes in vegetation cover above the cave. Dry periods are associated with less stable soils, resulting in high erosion and increased mineral flux into karst systems, which occurs simultaneously with increasing δ¹³C values. Conversely, wetter periods with low δ¹³C values are associated with soils topped by denser vegetation that retains micrometer-scale pedogenic minerals and thus reduces detrital fluxes into the cave.

Azevedo et al. (2019) further explored the relationship between δ¹³C and δ¹⁸O during the last millennium in a speleothem (MV3) from the Brazilian Central region (point 9 in Fig. 1), where wetter (drier) periods are also associated with lower (higher) values of δ¹⁸O and δ¹³C and higher (lower) speleothem growth rates. The same interpretation was utilized for the δ¹³C values of the stalagmites from Tamboril cave, located further south (point 10 in Fig. 1). However, at this site the δ¹⁸O and δ¹³C do not co-vary, which the authors interpret as a result of the decoupling between the local hydroclimate and SAMS, documented
149 by the δ¹³C and δ¹⁸O, respectively (Wortham et al., 2017).

<figure><img src="image_3.png" /></figure>

150

<caption>**Fig. 1.** Map of tropical South America with vegetation types (Olson et al., 2001), the main biomes, precipitation (blue isolines - mm/month, derived from the annual mean for the period from 1998 to 2017, with data from TRMM 3b43 - Huffman et al., 2014) and location of the study sites from the δ¹³C_2k_SA dataset. 1- Huagapo cave; 2- Palestina cave; 3- Umajalanta-Chiflonkhakha; 4- Pau d'Alho cave; 5- Curupira cave; 6- Járaguá cave; 7- Paraiso cave; 8- Botuverá cave; 9- Mata Virgem cave; 10- Tamboril cave; 11- São Matheus and São Bernardo cave system; 12- Anjos cave; 13- Diva, Torrinha, Lapa Doce caves; 14- Furna Nova cave; 15- Trapiá cave.</caption>

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The global increase of the atmospheric CO₂ concentration and temperature likely also influenced the δ¹³C values of stalagmites during the last century. Since 1850 the land surface air temperature increased by about 1.44 °C (Jia et al., 2019), affecting the fractionation between the seepage solution and the carbonate precipitated inside the caves (Lachniet, 2009), as well as promoting changes in cave ventilation (Baldini et al., 2008). Furthermore, depleted isotopic carbon has been emitted into the atmosphere due to the burning of fossil fuels, thereby decreasing the atmospheric δ¹³C that is transferred to vegetation. The increase of atmospheric CO₂ can also favor the flourishing of C₃ plants, which are less adapted than C₄ plants to low atmospheric CO₂ concentrations (Ehleringer et al., 1997).

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167 **3 Data Material and Methods**

168 **3.1 δ¹³C data**

169 The dataset used in this study comprises 25 speleothem δ¹³C records, of which 13 were hitherto
170 unpublished. δ¹⁸O records and chronological models have been published for all stalagmite records. Data
171 from the published records were obtained from the supplementary material of the respective papers or
172 downloaded from the NOAA speleothem database (http://www.ncdc.noaa.gov/data-
173 access/paleoclimatology-data/datasets/speleothem). Our main goal with this study is to introduce new
174 cave records to the speleothem community and contextualize their interpretation in a regional framework
175 for South America during the last two millennia. For that, we used only datasets that were available to us
176 with speleothem δ¹³C data from the last two thousand years (since year 0 CE). Therefore, we only
177 consider this time period for the analyses presented here. All records used, including their references,
178 cave names, locations and climatic parameters, are listed in Table 1. They are composed of 11,601 δ¹³C
179 values from 25 speleothems, published in 15 different papers (Table 1).

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<table><caption>**Table 1.** Caves, locations and regional characteristics. Information obtained from the original papers.</caption><thead><tr><th>Stalagmite</th><th>Cave</th><th>Latitude °N</th><th>Longitude °E</th><th>Reference</th><th>Annual Precipitation (mm)</th><th>Mean annual T (°C)</th><th>Elevation (m.a.s.l)</th></tr></thead><tbody><tr><td>JAR4</td><td>Jaraguá</td><td>-21.08</td><td>-56.58</td><td>Novello et al. (2018; 2019)<br>This study</td><td>1400</td><td>21.4</td><td>570</td></tr><tr><td>JAR1</td><td>Jaraguá</td><td>-21.08</td><td>-56.58</td><td>Novello et al. (2018)<br>This study</td><td>1400</td><td>21.4</td><td>570</td></tr><tr><td>SBE3</td><td>São Bernardo</td><td>-13.81</td><td>-46.35</td><td>Novello et al. (2018);<br>Moquet et al. (2016)<br>This study</td><td>1270</td><td>23.0</td><td>630</td></tr><tr><td>SMT5</td><td>São Matheus</td><td>-13.81</td><td>-46.35</td><td>Novello et al. (2018)<br>This study</td><td>1270</td><td>23.0</td><td>630</td></tr><tr><td>ALHO6</td><td>Pau d'Alho</td><td>-15.21</td><td>-56.8</td><td>Novello et al. (2016)<br>Jaqueto et al. (2016)</td><td>1440</td><td>25.5</td><td>340</td></tr><tr><td>CUR4</td><td>Curupira</td><td>-15.02</td><td>-56.78</td><td>Novello et al. (2016)<br>This study</td><td>1440</td><td>25.5</td><td>340</td></tr><tr><td>DV2</td><td>Diva</td><td>-12.37</td><td>-41.57</td><td>Novello et al. (2012)<br>This study</td><td>700</td><td>24.5</td><td>480</td></tr><tr><td>TR5</td><td>Torrinha</td><td>-12.37</td><td>-41.57</td><td>Novello et al. (2012)<br>This study</td><td>700</td><td>24.5</td><td>480</td></tr><tr><td>LD12</td><td>Lapa Doce</td><td>-12.37</td><td>-41.57</td><td>Novello et al. (2012)<br>This study</td><td>700</td><td>24.5</td><td>480</td></tr><tr><td>TRA7</td><td>Trapiá</td><td>-5.59</td><td>-37.70</td><td>Utida et al. (2020)</td><td>700</td><td>28.0</td><td>72</td></tr><tr><td>FN1</td><td>Furna Nova</td><td>-5.60</td><td>-37.44</td><td>Cruz et al. (2009)<br>Utida et al. (2020)</td><td>700</td><td>28.0</td><td>100</td></tr><tr><td>TM0</td><td>Tamboril</td><td>-16.80</td><td>-47.27</td><td>Wortham et al. (2017)</td><td>1400</td><td>22.5</td><td>600</td></tr><tr><td>ANJOS1</td><td>Lapa dos Anjos</td><td>-14.39</td><td>-44.30</td><td>Stríkis (2015)<br>This study</td><td>940</td><td>23.7</td><td>640</td></tr><tr><td>BTV21a</td><td>Botuverá</td><td>-27.21</td><td>-49.09</td><td>Bernal et al. (2016)<br>This study</td><td>1400</td><td>22.0</td><td>200</td></tr><tr><td>PAR3</td><td>Paraiso</td><td>-4.07</td><td>-55.45</td><td>Wang et al. (2017)</td><td>2400</td><td>26.0</td><td>60</td></tr><tr><td>PAR1</td><td>Paraiso</td><td>-4.07</td><td>-55.45</td><td>Wang et al. (2017)</td><td>2400</td><td>26.0</td><td>60</td></tr><tr><td>MV3</td><td>Mata Virgem</td><td>-11.62</td><td>-47.49</td><td>Azevedo et al. (2019)</td><td>1570</td><td>26.8</td><td>365</td></tr><tr><td>POO-H1</td><td>Huagapo</td><td>-11.27</td><td>-75.79</td><td>Kanner et al. (2013)</td><td>459</td><td>10.4</td><td>3800</td></tr><tr><td>P09-H2</td><td>Huagapo</td><td>-11.27</td><td>-75.79</td><td>Kanner et al. (2013)</td><td>459</td><td>10.4</td><td>3800</td></tr><tr><td>BOTO3</td><td>Umajalanta-<br>Chiflonkhakha</td><td>-18.12</td><td>-65.77</td><td>Apaéstegui et al. (2018)<br>This study</td><td>518</td><td>17.0</td><td>2650</td></tr><tr><td>BOTO7</td><td>Umajalanta-<br>Chiflonkhakha</td><td>-18.12</td><td>-65.77</td><td>Apaéstegui et al. (2018)<br>This study</td><td>518</td><td>17.0</td><td>2650</td></tr><tr><td>BOTO10</td><td>Umajalanta-<br>Chiflonkhakha</td><td>-18.12</td><td>-65.77</td><td>Apaéstegui et al. (2018)<br>This study</td><td>518</td><td>17.0</td><td>2650</td></tr><tr><td>BOTO1</td><td>Umajalanta-<br>Chiflonkhakha</td><td>-18.12</td><td>-65.77</td><td>Apaéstegui et al. (2018)<br>This study</td><td>518</td><td>17.0</td><td>2650</td></tr><tr><td>PAL3</td><td>Palestina</td><td>-5.92</td><td>-77.35</td><td>Apaéstegui et al. (2014)</td><td>1570</td><td>22.8</td><td>870</td></tr><tr><td>PAL4</td><td>Palestina</td><td>-5.92</td><td>-77.35</td><td>Apaéstegui et al. (2014)</td><td>1570</td><td>22.8</td><td>870</td></tr></tbody></table>

## 3.2 Stalagmites and regional settings

As presented in the original papers, all speleothems used in this study were collected with the initial goal to reconstruct the SAMS using the $\delta^{18}$O values. Therefore, stalagmites with a candle-type shape and uniform growth were preferentially collected in isolated chambers located far from the cave entrance. At such locations, temperature displays only minor variations throughout the year (characteristic of tropical caves), the air circulation is restricted, $CO_2$ concentrations are higher than atmospheric values, and the air is saturated in humidity. These conditions minimize the seasonal effects of ventilation and temperature, degassing and overall kinetic effects on the isotopic composition of the stalagmites.
The speleothem δ¹³C records used here are distributed throughout tropical South America (Fig. 1), covering a region spanning the latitudes 4 °S to 21 °S and longitudes 42 °W to 76 °W. The domain comprises the following climates (according to the Köppen climate classification): monsoon (Am), tropical savanna (Aw), warm semi-arid (BSh) and humid subtropical (Cwa). The annual precipitation amount ranges from 450 to 2400 mm, mainly related to the SAMS and its subcomponent the SACZ (Novello et al., 2018). The equatorial portion is also under direct influence of the Intertropical Convergence Zone (ITCZ). Except for the sites located in the Andes, all records are located at altitudes below 700 m.a.s.l. (Table 1). At these lowland sites, precipitation amount and the length of the rainy season define the three main vegetation types (Fig. 1). High precipitation amounts that are well distributed over the year are typical of Tropical Forest, while Caatinga is characterized by an environment with lower precipitation, concentrated during a few months. Cerrado, the main biome of central South America, presents hydrological conditions in-between these two end-members. In general, temperature decreases with increasing latitude and altitude; the mean annual temperature in the lowlands ranges from 21.4 to 26.8 °C, while the sites in the Andes reach temperatures around 10 °C (Table 1).

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## 3.3 Methods

To assess the shared variance among the δ¹³C records from the different cave sites, while considering the stalagmites' age uncertainties, we employ a Monte-Carlo Principal Component Analysis (MC-PCA) as described in Campos et al. (2019), which consists of the following steps: (1) A linear age-depth model was constructed for each record, accounting for the ±1σ standard deviations in the dating uncertainty through a set of 1000 Monte-Carlo simulations, which resulted in 1000 age models for each isotopic sample. The corresponding isotopic time series are obtained through linear interpolation between ages using the age-depth model (Deininger et al., 2017); (2) Stalagmite records from the same karst region were merged into a single time series by synchronizing the time series using a cubic spline during the overlap period, and each time series was normalized to unit variance (z-scores) before they were averaged into one time series; (3) The time series were reconstructed using the inversion of the normalization of the longer time series (using standard deviation and the mean of the longer time series); (4) The time series were resampled to annual resolution before being low-pass filtered at the band of 1/30 years⁻¹; (5) From the 1000 Monte-Carlo age model simulations, one time series is randomly chosen from
each record, generating a set of time series; the Principal Component Analysis (PCA) is then performed
over this set of data. This procedure is repeated 1000 times, in such a way that all the simulations are
being used, generating a set of spatial patterns (or loadings), principal components (or scores) and
eigenvalues (containing the explained variance of the spatial pattern and principal component). These
analyses were carried out in Matlab with codes written using its native routines.

The MC-PCA was focused on the time period between 650 and 1950 CE because this is the time
interval covered by most sites This procedure resulted in a set of ten time series, each corresponding to a
site shown in Fig. 3: Jar (composed by JAR1 + JAR4), SBE (composed by SBE3 + SMT5), ALH
(composed by ALHO6 + CUR4), DV2 (composed by DV2 + TR5 + LD12), TMO (composed only by
TMO), ANJ (composed only by ANJOS1), PAR (composed by PAR1 + PAR3), HUA (composed by
P00-H1 + P09-H2), BOTO (composed by BOTO1 + BOTO3 + BOTO7 +BOTO10) and PAL (composed
by PAL3 + PAL4). Four stalagmites presented in Fig. 1 (MV3, FN1, TRA7, BTV21a) were not included
in the PCA because these records cover only a limited time period and no other stalagmites from the same
karst systems exist that could be merged, or because their data resolution is significantly lower (more than
15 years between individual data points in the geochronological model).

Regression analyses between the δ¹³C data and other parameters were performed using the data
presented in Table 1 and 2 to test possible climatic influences on the δ¹³C values from stalagmites. Many
stalagmites from this study are experience similar precipitation amounts and/or temperature. Hence, we
used a single averaged δ¹³C value for the stalagmites that are located within regions that experience
similar precipitation amount or temperature (listed in Table 1) to provide regression analysis tests: “δ¹³C
vs. precipitation amount” and “δ¹³C vs. temperature”. Precipitation and temperature values that fall within
a range of 50 mm and 1°C, respectively, were considered as similar. This approach results in one δ¹³C
value per climatic region entering the regression model, ensuring that climatic regions where stalagmites
are more common are not overrepresented and therefore do not lead to regionally biased results. Sites
from the high-altitude Andes (Umajalanta-Chiflonkhakha and Huagapo cave systems) were excluded in
the correlation and regression analyses, as these sites introduce large outliers due to the differences in
altitude and temperature, that would equally bias the results. The average δ¹³C value over the last two
millennia was used in the analysis, which allows us to use all stalagmites to provide a spatially more
complete picture of the records from South America and minimize possible inconsistencies in the data
related to geochronology and resolution. Restricting the analysis to only modern δ¹³C values would be
limiting the use of our dataset since only a few stalagmites present data from the last 50 years. In theory, the recent δ¹³C values should be more closely related to current temperature and precipitation. However, as is shown in Fig. 2 and discussed in sections 4 and 5, using the δ¹³C averaged over the full record still results in a high R² with high statistical significance (p<0.01) of the relationship between δ¹³C and climatic parameters, which suggest that average δ¹³C values over the last two millennia are indeed representative of the current climatic conditions.

To establish the correlation between the δ¹³C and the growth rate from speleothems, we calculated the growth rate based on the length of the interval between two consecutive U/Th ages and used the mean δ¹³C value, averaged over the respective interval.

270

## 4 Results

The δ¹³C values from the δ¹³C_2k_SA dataset range from -11.5 to 6.8 ‰, although the vast majority of the data lie within -11 and -1 ‰ (Figures 1 to 25 in supplementary material). The highest values and largest variability stem from the TR5 stalagmite, ranging from -3.8 to 6.8 ‰ (amplitude of 10 ‰), which contrasts with the average amplitude of 4.5 ‰ from the other stalagmites.

The coefficient of determination (R²) between the time series of δ¹⁸O and δ¹³C was calculated for each stalagmite and is listed in Table 2. The highest coefficient of determination (r²: 0.96, p<0.01) is displayed by the TR5 stalagmite, while the average r² of the δ¹³C_2k_SA dataset is 0.29. Average δ¹³C values from the speleothems display a high negative correlation with the annual mean precipitation amount (r²: 0.67, p < 0.01) and a weaker, positive correlation with temperature (r²: 0.45, p<0.05) of their respective regions (Fig. 2). No significant correlation was found with altitude (p>0.05). The relationships between the growth rate and average δ¹³C values are statistically significant (p≤0.05) only in the stalagmites JAR4 (r²: 0.21), DV2 (r²: 0.50), TR5 (r²: 0.75), LD12 (r²: 0.70) and TRA7 (r²: 0.20), all with negative slopes (Table 2).

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288
<table><caption>**Table 2:** Stalagmites and their respective data information. Coefficients of determination (R²) between growth rate and δ¹³C values was calculated based on the length interval between ages and the mean δ¹³C values of each interval. Confidence levels at this column equal to or higher than 95% (p≤0.05) are shown in bold and the signal "+" and "-" denotes positive and negative slopes, respectively. (1) Novello et al. (2019); (2) Lima (2011); (3) Nogueira et al. (2006); (4) Caird et al. (2017); (5) Utida et al. (2020); (6) Alvarenga et al. (2014); (7) Caetano-Filho et al. (2019); (8) Campos (2013). (*) Site where the δ¹³C values were measured in the bedrock that hosts the cave.</caption><thead><tr><th>Stalagmite</th><th>δ<sup>18</sup>O mean</th><th>δ<sup>13</sup>C mean</th><th>R<sup>2</sup> δ<sup>18</sup>O x δ<sup>13</sup>C</th><th>Time period covered (years BP)</th><th>Isotopic data points</th><th>Mean resolution (years)</th><th>R<sup>2</sup> Growth rate x δ<sup>13</sup>C</th><th>δ<sup>13</sup>C of the main rock formation</th><th>Host geology</th></tr></thead><tbody><tr><td>JAR4</td><td>-4.8</td><td>-8.5</td><td>0.50 (p&lt;0.01)</td><td>-50 to 760</td><td>237</td><td>3.4</td><td>(-) 0.21 (p=0.05), n° of segments: 18</td><td>1* (1)</td><td>Bocaina Fm, Corumba Group (Neoproterozoic)</td></tr><tr><td>JAR1</td><td>-3.8</td><td>-7.2</td><td>0.21 (p&lt;0.01)</td><td>499 to 1508</td><td>318</td><td>3.2</td><td>(+) 0.24 (p=0.17), n° of segments: 9</td><td>1* (1)</td><td>Bocaina Fm Corumba Group (Neoproterozoic)</td></tr><tr><td>SBE3</td><td>-4.3</td><td>-8.9</td><td>0.04 (p&lt;0.01)</td><td>-60 to 827</td><td>1710</td><td>0.5</td><td>(+) 0.29 (p=0.12), n° of segments: 10</td><td>-5.5 to -3 (2)</td><td>Urucuia Fm, Mata da Corda Group (Cretaceous)</td></tr><tr><td>SMT5</td><td>-4.2</td><td>-8.3</td><td>0.13 (p&lt;0.01)</td><td>749 to 1686</td><td>575</td><td>1.6</td><td>(-) 0.35 (p=0.60), n° of segments: 3</td><td>-5.5 to -3 (2)</td><td>Urucuia Fm, Mata da Corda Group (Cretaceous)</td></tr><tr><td>ALHO6</td><td>-6.2</td><td>-6.6</td><td>0.57 (p&lt;0.01)</td><td>90 to 1458</td><td>1169</td><td>1.2</td><td>(+) 0.03 (p=0.63), n° of segments: 11</td><td>-5 to 0 (3)</td><td>Guia Fm, Araras Group (Neoproterozoic)</td></tr><tr><td>CUR4</td><td>-7.6</td><td>-9.9</td><td>0.25 (p&lt;0.01)</td><td>-21 to 155</td><td>252</td><td>0.7</td><td>(+) 0.00 (p=0.94), n° of segments: 7</td><td>-5 to 0 (3)</td><td>Guia, Araras Group (Neoproterozoic)</td></tr><tr><td>DV2</td><td>-3.7</td><td>-9.2</td><td>0.35 (p&lt;0.01)</td><td>39 to 2765</td><td>538</td><td>5.0</td><td>(-) 0.50 (p=0.02), n° of segments: 10</td><td>-9 to +10 (4)</td><td>Salitre Fm, Una Group (Neoproterozoic)</td></tr><tr><td>TR5</td><td>-2.9</td><td>-1.1</td><td>0.96 (p&lt;0.01)</td><td>-57 to 76</td><td>90</td><td>1.5</td><td>(-) 0.75 (p&lt;0.01), n° of segments: 7</td><td>-9 to +10 (4)</td><td>Salitre Fm, Uma Group (Neoproterozoic)</td></tr><tr><td>LD12</td><td>-3.2</td><td>-7.7</td><td>0.35 (p&lt;0.01)</td><td>-61 to 39</td><td>122</td><td>0.8</td><td>(-) 0.70 (p=0.04), n° of segments: 6</td><td>-9 to +10 (4)</td><td>Salitre Fm, Una Group (Neoproterozoic)</td></tr><tr><td>TRA7</td><td>-2.8</td><td>-3.0</td><td>0.05 (p&lt;0.01)</td><td>17 to 5507</td><td>818</td><td>6.4</td><td>(-) 0.20 (=0.03), n° of segments: 23</td><td>0* (5)</td><td>Jandaíra Fm, Apodi Group (Cretaceous)</td></tr><tr><td>FN1</td><td>-2.3</td><td>-4.9</td><td>0.87 (p&lt;0.03)</td><td>-54 to 2275</td><td>88</td><td>26.5</td><td>X, n° of segments: 3</td><td>0* (5)</td><td>Jandaíra Fm, Apodi Group (Cretaceous)</td></tr><tr><td>TM0</td><td>-5.4</td><td>-9.7</td><td>0.24 (p&lt;0.01)</td><td>-32 to 1678</td><td>471</td><td>3.6</td><td>0.00 (p=0.87), n° of segments: 12</td><td>-5 to +16 (6)</td><td>Sete Lagos Fm, Bambuí Group (Neoproterozoic)</td></tr><tr><td>ANJOS1</td><td>-3.7</td><td>-7.2</td><td>0.09 (p&lt;0.01)</td><td>-57 to 2927</td><td>1272</td><td>2.4</td><td>0.00 (p=0.72), n° of segments: 26</td><td>-5 to +2 (7)</td><td>Sete Lagoas Fm, Bambuí Group (Neoproterozoic)</td></tr><tr><td>BTV21a</td><td>-3.8</td><td>-8.2</td><td>0.03 (p&lt;0.01)</td><td>196 to 9211</td><td>230</td><td>39.2</td><td>X, n° of segments: 3</td><td>X</td><td>Botuverá Fm, Brusque Group (Neoproterozoic)</td></tr><tr><td>PAR3</td><td>-5.7</td><td>-8.9</td><td>0.42 (p&lt;0.01)</td><td>-48 to 768</td><td>144</td><td>5.7</td><td>(-) 0.26 (p=0.24), n° of segments: 7</td><td>-2.2 to 5.2 (8)</td><td>Itaituba Fm Tapajos Group (Paleozoic)</td></tr><tr><td>PAR1</td><td>-6.6</td><td>-9.5</td><td>0.00 (p&lt;0.44)</td><td>714 to 4812</td><td>449</td><td>9.1</td><td>X, n° of segments: 3</td><td>-2.2 to 5.2 (8)</td><td>Itaituba Fm Tapajos Group (Paleozoic)</td></tr><tr><td>MV3</td><td>-1.9</td><td>-4.7</td><td>0.45 (p&lt;0.01)</td><td>250 to 1032</td><td>537</td><td>1.4</td><td>(-) 0.46 (p=0.10), n° of segments: 7</td><td>X</td><td>Mato Virgem Fm, Natividade Group (Precambrian)</td></tr><tr><td>P00-H1</td><td>-13.3</td><td>-5.9</td><td>0.24 (p&lt;0.01)</td><td>-50 to 1391</td><td>289</td><td>5.0</td><td>(+) 0.55 (p=0.26), n° of segments: 4</td><td>X</td><td>Aramachay Fm, Pucara Group (Triassic)</td></tr><tr><td>P09-H2</td><td>-13.0</td><td>-5.2</td><td>0.20 (p&lt;0.01)</td><td>1099 to 7146</td><td>1272</td><td>5.7</td><td>(-) 0.35 (p=0.29), n° of segments: 4</td><td>X</td><td>Aramachay Fm, Pucara Group (Triassic)</td></tr><tr><td>Boto3</td><td>-9.7</td><td>-1.7</td><td>0.26 (p&lt;0.01)</td><td>171 to 1242</td><td>256</td><td>4.0</td><td>(-) 0.94 (p=0.01), n° of segments: 8</td><td>X</td><td>Miraflores Fm, Pucara Group (Cretaceous)</td></tr><tr><td>Boto7</td><td>-10.8</td><td>-3.9</td><td>0.00 (p=0.6)</td><td>78 to 388</td><td>97</td><td>1.8</td><td>X, n° of segments: 2</td><td>X</td><td>Miraflores Fm, Pucara Group (Cretaceous)</td></tr><tr><td>Boto10</td><td>-9.7</td><td>-3.1</td><td>0.34 (p&lt;0.01)</td><td>543 to 1217</td><td>207</td><td>3.3</td><td>(+) 0.36 (p=0.40), n° of segments: 3</td><td>X</td><td>Miraflores Fm, Pucara Group (Cretaceous)</td></tr><tr><td>Boto1</td><td>-10.2</td><td>-1.2</td><td>0.41 (p&lt;0.01)</td><td>218 to 383</td><td>20</td><td>7.9</td><td>X, n° of segments: 1</td><td>X</td><td>Miraflores Fm, Pucara Group (Cretaceous)</td></tr><tr><td>PAL3</td><td>-7.1</td><td>-10.1</td><td>0.00 (p=0.2)</td><td>21 to 850</td><td>192</td><td>4.3</td><td>(+) 0.65 (p=0.10), n° of segments: 4</td><td>X</td><td>Chambara Fm, Pucara Group (Triassic_Jurassic)</td></tr><tr><td>PAL4</td><td>-7.1</td><td>-9.4</td><td>0.25 (p&lt;0.01)</td><td>151 to 1536</td><td>248</td><td>5.4</td><td>(+) 0.12 (p=0.27), n° of segments: 11</td><td>X</td><td>Chambara Fm, Pucara Group (Triassic_Jurassic)</td></tr></tbody></table>

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<figure><img src="image_4.png" /></figure>

**Fig. 2.** Relationship between the δ¹³C from the δ¹³C_2k_SA dataset with annual precipitation (a) and annual mean temperature (b) of each study site.

The MC-PCA methodology was applied to the full δ¹³C_2k_SA dataset. The first principal component (PC1) explained ~36% of the total variance (Fig. 3 and 4). Positive loadings are associated with the δ¹³C records from the caves Huagapo (Hua), Palestina (PAL), Jaraguá (Jar), and the merged records from the caves Pau d'Alho/Curupira (Alh) and São Bernardo/São Matheus (SBE), whereas negative loadings are linked to the records from the caves Diva de Maura/Torrinha/Lapa Doce (DV2), Paraiso caves (PAR) and Umajalanta-Chiflonkhakha (BOTO) (Fig. 3), indicating out of phase δ¹³C variability between the two cave site groups. Positive values characterize the time interval of ~600–1500 CE in PC1, while negative values are predominant during the period ~1500–1950 CE, with an incursion to more negative values centered at ~1180 CE (Fig. 4). PC2 explained ~16% of the variance, with large positive loadings displayed by the records located in central Brazil, especially the TM0 and DV2 records, whereas large negative loadings are displayed by the records from high altitudes (PAL and BOTO). The other study sites present low and variable contributions for PC2.
<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Maps of South America with the main loadings of the Principal Component Analysis (PCA) and explained total variance. Blue and red dots represent positive and negative loadings, respectively. The magnitude of the loadings is represented by the size of the dots. The larger the dot, the more representative it's loading is of the respective PC.</figcaption></figure>

315

## 5 Discussion

The host-rocks of the caves in this study are predominantly of Neoproterozoic age, located in the Brazilian shield (Table 2). Isotopic studies carried out in these carbonate rock sequences show a wide range of values, varying between ~ -5 to 16 ‰ within the same rock unit or even the same outcrop (Table 2). The absence of isotopic studies in the same bedrock where the caves are located, precludes a precise quantification of the influence of these different rock sequences on the δ¹³C values of the stalagmites. Of the study sites presented here, the δ¹³C from its host-rock was only measured at Jaraguá and Trapiá caves (Novello et al., 2019; Utida et al., 2020). In both sites, more positive δ¹³C values close to bedrock values were reported in their stalagmites during periods of sparse vegetation and thin soil layers above the caves. Although both papers are describing environmental changes at orbital timescales, nowadays these are the typical characteristics of the sites Huagapo, Umajalanta-Chiflonkhakha, Mata Virgem, Trapiá and Torrinha; all featuring stalagmites with high δ¹³C values (Table 2). Aside from the stalagmites of these sites and ALHO6, all other stalagmites have δ¹³C values lower than -6 ‰ throughout the last two millennia, indicating the predominance of thick soil with higher organic matter content from the regions of Cerrado and/or Tropical Forest. δ¹³C values below -6‰ in stalagmites are also considered indicative of predominance of C₃ plants above the caves in geochemical models (McDermott, 2004; Baker et al., 1997;
332 Dreybrodt, 1988), if considering bedrock with δ¹³C values around +1 ‰ (which is the average value for
333 South American carbonates, Table 2).

334 TR5 presents δ¹³C values that are significantly higher than all other samples, and the abrupt
335 increase in δ¹³C occurs just before the complete stop of carbonate deposition at ~1920 CE and ~2006 CE
336 (Table 2), both of which are periods of predominantly dry conditions in the region (Novello et al., 2012).
337 High values followed by an abrupt decrease also occur after the depositional hiatus at ~1960 CE. The r²
338 between δ¹³C and δ¹⁸O is close to 1 (Table 2), which indicates that both isotopes underwent fractionation
339 together in this sample. These results support the notion that the TR5 stalagmite was precipitated under
340 strong kinetic effects due to high evaporation rates and/or significantly reduced dripping rates (resulting
341 in a long time period for isotope re-equilibration between solution and cave atmosphere) at the moment of
342 carbonate precipitation, which is accentuated during drier periods, culminating in a complete halt of
343 carbonate precipitation. Although the kinetic effect might be the main factor responsible for the high
344 amplitude and isotopic values in TR5, this stalagmite still preserves paleoclimate information regarding
345 the δ¹⁸O in precipitation that co-varies with the δ¹⁸O from other stalagmites in the region, as well as with
346 pluviometric data from meteorological stations (Novello et al., 2012).

347 Most of the stalagmites from the δ¹³C_2k_SA dataset feature coefficients of determination
348 between their δ¹³C and δ¹⁸O values ranging from 0.20 to 0.56 (Table 2). The δ¹⁸O values in stalagmites
349 from tropical South America covering the last 2000 years have been interpreted as a proxy of the intensity
350 of the SAMS (Azevedo et al., 2019; Novello et al., 2012, 2016, 2018; Apaéstegui et al., 2014; 2018;
351 Wortham et al., 2017; Vuille et al., 2012) and the SACZ, a continuous band of low-level wind
352 convergence and precipitation that extends in a northwest-southeast direction across southeastern South
353 America (Novello et al., 2018). Since an increase in local rainfall promotes a decrease of PCP, an increase
354 of gas CO₂ derived from soil organic matter and favors C₃ plants over C₄ plants (all processes that result
355 in decreasing δ¹³C values in stalagmites), we argue that a correlation between δ¹³C and δ¹⁸O values is the
356 result of a close relationship between local hydroclimate and atmospheric convective processes (inferred
357 by δ¹⁸O). This hypothesis is supported by the existing correlation between the annual rainfall amount and
358 the average δ¹³C values of the stalagmites (r²: 0.67, Fig. 2), and by the PC1 loadings derived from the
359 δ¹³C_2k_SA dataset (Fig. 3), showing a very similar spatial distribution as those displayed in PC1 derived
360 from the δ¹⁸O dataset from speleothems over tropical South America by Campos et al. (2019). Both PC1-
361 δ¹³C and PC1-δ¹⁸O show positive loadings for the locations to the southwest of the SACZ and negatives
loadings for those records located to the northeast (Fig. 3), which characterizes the SACZ precipitation dipole in South America (Campos et al., 2019; Novello et al., 2018). The BOTO site (Fig. 3) is an exception in this scenario, but this region may have partially been under the influence from a different climate system with a different moisture source in the past (Apaéstegui et al., 2018). This relationship between the δ¹³C and local hydroclimate was already documented for the ALHO6 stalagmite using a multiproxy approach (Jaqueto et al., 2016).

<figure><img src="image_6.png" /></figure>

<caption>**Fig. 4.** Comparison between the first Principal component (PC1) derived from the δ¹³C_2k dataset (this study) representing the main mode of hydroclimate variability and PC1 based on the δ¹⁸O from stalagmites from South America (PC1 – δ¹⁸O) from Campos et al. (2019) representing the main mode of variability of the South American Monsoon System. The uncertainties associated with the PC1s are shown by the colored and gray shading. λ indicates the percentage of explained variance by each PC.</caption>

Strong correspondence throughout the time-series between scores of PC1-δ¹³C and PC1-δ¹⁸O further corroborates the overall coupling between the monsoon and local hydroclimate during the last ~1400 years (Fig. 4). This coupling ceases after ~1750 CE, when the monsoon weakened at a faster rate than the local hydrological response. However, the hydrologic variability inferred from PC1-δ¹³C is biased by vegetation changes, which responds to other influences beyond the local rainfall amount, such
as temperature, atmospheric CO₂, deforestation and fire (parameters that have increased significantly over the last 250 years).

PC2 explains only 16 % of the δ¹³C variability (Fig. 3). It shows large positive loadings at sites located in lowlands of central Brazil and negative loadings at sites located in the Andes (Fig. 3). This difference is possibly related to different effects of temperature at different altitudes. Changes in continental temperature are amplified at higher elevation (Ohmura, 2012), leading to a larger effect on the δ¹³C values at sites located at higher altitudes, thereby increasing the isotopic differences between sites located at low and high elevation.

Growth rates also show a weak correlation with the δ¹³C values from the δ¹³C_2k_SA dataset. The correlation between the growth rate and δ¹³C values is statistically significant (p-values ≤ 0.05) only in the stalagmites JAR4, DV2, TR5, LD12 and TRA7 (Table 2). In these stalagmites, all regression coefficients present a negative slope, which is expected, as a higher growth rate leads to lower δ¹³C values because the time for isotopic enrichment of the DIC through kinetic effects is reduced during carbonate precipitation (Fohlmeister et al., 2020).

## 6 Conclusions

Here we present a new set of δ¹³C records from speleothems collected over a broad region of tropical South America. These data were integrated with previously published speleothem δ¹³C records to characterize the main controls on carbon isotope variations in this region. The predominance of C₃ plants above most of the karst systems studied here is responsible for the low δ¹³C values (< -6 ‰) in most of the speleothems, while local hydroclimate associated with PCP process is the main driver behind its variability during the last two millennia. Unlike what was observed in the global compilation of δ¹³C records for the period after 1900 CE (Fohlmeister et al., 2020), local temperature and growth rate play a minor role in shaping the δ¹³C values in the δ¹³C_2k_SA dataset. The probable reason for this difference between studies is that most of the speleothems in our database formed under tropical conditions, characterized by a limited temperature range, whereas the SISAL_v1 dataset studied by Fohlmeister et al. (2020) is biased towards records from high latitudes with a much larger temperature range.
408 Using Monte Carlo Principal Component Analysis, we produce an index of the mean hydrologic
409 conditions and its changes over tropical South America for the last two millennia, which is closely related
410 to monsoon variability for the period prior to 1750 CE. The recent break-down in the relationship
411 between monsoon and local hydroclimate may have been caused by the increase in temperature, CO2,
412 deforestation and fire during the current warm period; however, further studies are required to test this
413 hypothesis.

414

415 **7 Data availability**

416 The new δ¹³C records from δ¹³C_2k_SA dataset will be available at PANGAEA.

417

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613

614 **Author contribution:** VFN designed the experiments, FWC and MV are the project PIs, JLPSC 615 performed statistical analysis, NMS and JSM performed isotopic analyses, VA, GU, PJ, IK, LCRP and 616 DOB assisted in the discussion and interpretations. AA created the map, GMPS provided a review on 617 carbonate formations. VFN prepared the manuscript with contributions from all co-authors.

618

619 **Acknowledgements**

620 We thank the São Paulo Research Foundation (FAPESP) for financial support through grants 621 2016/15807-5 to VFN, 2017/50085-3, and 2019/07794-9 to FWC and the US National Science 622 Foundation for award OISE-1743738 to MV. We thank the Instituto Chico Mendes de Conservação da
623 Biodiversidade (ICMBio) for providing the permission (number 22424-8) to undertake the cave studies in

624 Brazil.