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Author: Adloff, Markus Title: Quantitative constraints on carbon fluxes and volcanic activity during Oceanic Anoxic Event 1a

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Your claim will be investigated and, where appropriate, the item in question will be removed from public view as soon as possible. Quantitative constraints on carbon fluxes and volcanic activity during Oceanic Anoxic Event 1a

By

Markus Adloff

School of Geographical Sciences University of Bristol

A dissertation submitted to the University of Bristol in accordance with the requirements of the degree of Doctor of Philosophy in the Faculty of Science.

September 2020

Word count: sixty three thousand

Abstract

The geologic record provides opportunities to study the long-term Earth-System response to exogenic Carbon (C) emissions. In this thesis, I extend and apply the Earth-System model cGENIE to reconstruct and evaluate the uncertainty of C emissions and volcanism during the Oceanic Anoxic Event 1a (OAE 1a) based on sedimentary records of C, Os, Sr, Li and Ca isotopes. OAE 1a (120 Ma) was a major C cycle perturbation featuring the formation of a transient marine organic C sink. Combining C isotope records with reconstructed CO2 concentration changes, I determine the size and isotopic composition of net C fluxes at the event onset. This inverse C flux reconstruction indicates that 4,300 - 29,200 Pg C were emitted, predominantly from volcanism. Radiogenic Os and Sr isotopes have previously been used to reconstruct volcanic activity during the main event, when the effect of enhanced organic C burial prevents C flux reconstructions from the C isotope record. The weathering response has been quantified using Li and Ca isotopes. However, interactions between the C and these metal cycles during C injections are poorly understood. After implementing Os cycling into cGENIE and validating existing parameterisations of Sr, Li and Ca cycling, I show that concurrent changes in volcanism and weathering noticeably affect Os, Sr, Li and Ca isotope excursions in cGENIE simulations, and that further constraints on the isotopic effect of weathering flux changes are required to use trace metals as C flux proxies during long-lasting volcanic episodes. Further analysis of metal cycling prior to OAE 1a reveals that substantial amounts of volcanic C must have been emitted throughout the event to cause the observed isotope excursions and support organic C burial and enhanced weathering for millions of years. C flux reconstructions remain too uncertain to determine the relative importance of these negative C cycle feedbacks.

i

Dedication and acknowledgements

At the beginning of this thesis, I would like to acknowledge and thank the many people who supported me over the last four years. First, I would like to thank my supervisors Sarah E. Greene, Fanny M. Monteiro, Dan Lunt and B. David A. Naafs without whom I could not have written this thesis. I am very grateful that they gave me the opportunity to work with them on this project, and for their extensive support. Their guidance, patience, trust, dedication and encouragement helped me to grow so much over the last four years, academically and personally. I could not have wished for better mentors and collaborators!

Secondly, I want to thank all collaborators and project partners for their continued support and valuable inputs to this project. Namely, I would like to thank Steve Hesselbo for inviting me to an unforgettable field trip to the Jurassic Coast and seminars at Exeter University, Ian J. Parkison and Alex Dickson, who helped me understand Os and Sr cycling, and, of course, Andy Ridgwell, who invited me to a research stay in Riverside and whose ideas and support were indispensable for the outcome of this thesis.

I am particularly grateful for the social and moral support I received from friends and family. I would like to thank the wonderful new friends I made during my PhD time, who made my life in Bristol such a joyful experience, and my good old friends and family everywhere for being close whatever the distance between us. Thank you to Dominik for his friendship and for making me feel at home in Bristol and Riverside. Thank you to Hazel, Alex, Cara, Olly, Steph and Philip for their friendships and four incredible years of shared meals, houses and invaluable experiences.

Finally, I would like to thank NERC and the GW4+ DTP for their financial and administrative support throughout my project.

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Author’s declaration

I declare that the work in this dissertation was carried out in accordance with the requirements of the University’s Regulations and Code of Practice for Research Degree Programmes and that it has not been submitted for any other academic award. Except where indicated by specific reference in the text, the work is the candidate’s own work. Work done in collaboration with, or with the assistance of, others, is indicated as such. Any views expressed in the dissertation are those of the author.

SIGNED: ...... DATE: ......

v

Table of Contents

Page

List of Tables xiii

List of Figures xvii

1 Introduction 1 1.1 Identifying and quantifying past C emissions...... 5 1.1.1 Indirect reconstruction of C emissions based on C isotopes ...... 6 1.1.2 Direct reconstruction of C fluxes based on metal isotopes...... 7 1.2 Carbon and metal fluxes during the emplacement of Large Igneous Provinces...... 8 1.2.1 Emission of mantle-derived substances via volcanic eruptions, hydrothermal venting and alteration of fresh basalt ...... 9 1.2.2 Emissions of surface-derived substances via sediment intrusions, contact meta- morphism and Earth system feedbacks...... 10 1.3 Oceanic Anoxic Event 1a: window into OAE formation and metal cycle perturbation during LIP emplacements...... 10 1.3.1 The Early Aptian, the paleogeographic and -climatological context of OAE 1a . 12 1.3.2 Lithological expression...... 13 1.3.3 Temperature...... 13

1.3.4 CO2 concentrations...... 14 1.3.5 Biological impact...... 14 1.3.6 Marine oxygenation...... 15 1.3.7 Euxinia...... 15 1.3.8 Weathering...... 15 1.3.9 Duration ...... 16 1.3.10 The role of volcanism in the formation of OAE 1a ...... 16 1.3.11 Published C flux reconstructions for OAE 1a ...... 17 1.4 Scope and structure of this thesis...... 17

2 Methods 19 2.1 The cGENIE model ...... 19

vii TABLE OF CONTENTS

2.2 cGENIE set-ups...... 22 2.2.1 Pre-Industrial ...... 22 2.2.2 Aptian ...... 23 2.3 C flux inversions in cGENIE ...... 27 2.4 Interpreting Sr, Os, Li and Ca isotope excursions as indicators of C cycle perturbations . 27

3 Unravelling the sources of carbon emissions at the onset of Oceanic Anoxic Event (OAE) 1a 29 3.1 Introduction...... 30 3.2 Methods...... 32 3.2.1 The Cau section...... 32 3.2.2 Model setup and experiment design...... 32 3.2.3 Osmium isotope analysis...... 35 3.3 Results...... 36 3.4 Discussion...... 38 3.5 Conclusion ...... 41

4 Inclusion of a suite of weathering tracers in the cGENIE Earth System Model - muffin release v.0.9.10 43 4.1 Introduction...... 44 4.2 Observational constraints ...... 45 4.2.1 Strontium...... 45 4.2.2 Osmium ...... 47 4.2.3 Lithium...... 48 4.2.4 Calcium ...... 49 4.2.5 Metal distributions in seawater...... 51 4.2.6 Application of Sr, Os, Li and Ca isotopes as proxies of weathering and mantle emissions...... 53 4.3 Model implementation...... 54 4.3.1 Continental weathering and run-off...... 55 4.3.2 Hydrothermal inputs ...... 56 4.3.3 Aeolian inputs...... 57 4.3.4 Metal export in carbonates...... 57 4.3.5 Scavenging from the water-column...... 58 4.3.6 Clay formation...... 59 4.3.7 Recrystallization...... 59 4.3.8 Rock alteration and metal deposition at the sea floor ...... 59 4.3.9 Isotopes...... 60 4.4 Model configuration and validation...... 63

viii TABLE OF CONTENTS

4.4.1 Pre-industrial configuration ...... 63 4.4.2 Comparison between simulated and observed trace metal contents of seawater . 65 4.4.3 Transient perturbation experiments...... 69 4.5 Conclusion ...... 72

5 Interpreting strontium, osmium, lithium and calcium isotopic excursions during LIP emplacements 75 5.1 Metal isotopes as tracers of C-cycle changes during LIP emplacements...... 75 5.2 Methods...... 77 5.2.1 High-temperature emission phase of LIP emplacement...... 80 5.2.2 Low-temperature alteration of LIP basalts...... 82 5.2.3 Assumed analytical uncertainties ...... 83 5.3 Results...... 83 5.3.1 High-temperature hydrothermal event ...... 83 5.3.2 Assessing the impact of low-temperature alteration during recovery ...... 93 5.4 Discussion...... 95 5.4.1 The effect of C release during high-temperature hydrothermal metal emissions . 96 5.4.2 Negligible direct isotopic signal of enhanced low-temperature alteration effects . 97 5.4.3 C-cycle driven timings of metal isotope excursion peaks...... 99 5.4.4 The proxy-potential of 187Os/188Os, 87Sr/86Sr, δ88Sr, δ7Li, δ44Ca during igneous forcing ...... 100 5.4.5 A new framework for metal-isotope-derived quantitative constraints on contem- poraneous C-cycle perturbations...... 101 5.4.6 The quantitative importance of the background state ...... 103 5.5 Conclusions...... 104

6 Significant variations in the ocean residence time of Osmium with changes in biogeo- chemistry 107 6.1 Introduction...... 108 6.2 What is the evidence for a variable marine residence time of Osmium? ...... 110 6.3 Methods...... 113

6.3.1 Organic matter, O2 and Os cycling in cGENIE ...... 113 6.3.2 Simulation set-ups...... 114 6.3.3 The marine residence time and its dependence on the sink strength ...... 115 6.4 Results...... 116 6.4.1 Simulations of different Os sink mechanisms under pre-industrial conditions . . 116 6.4.2 Simulations of the marine Os reservoir under varying environmental conditions 119 6.5 Discussion...... 119 6.6 Conclusion ...... 122

ix TABLE OF CONTENTS

7 Simulating proxy-consistent Cretaceous seawater composition 123 7.1 Introduction...... 123 7.2 The Early Aptian Earth system state ...... 124 7.2.1 Seawater composition of the Early Aptian ...... 124 7.2.2 Atmosphere and Climate of the Early Aptian ...... 125 7.2.3 Tectonics, spreading rates and weathering regimes ...... 125 7.2.4 Model representations of the Early Aptian Earth system state ...... 126 7.3 Impact of boundary condition changes on the seawater composition ...... 127 7.3.1 Methods ...... 127 7.3.2 Results ...... 130 7.3.3 Discussion...... 135 7.4 Simulations of the Early Aptian Earth system...... 138 7.4.1 Methods ...... 138 7.4.2 Results ...... 141 7.4.3 Discussion...... 145 7.5 Conclusions...... 147

8 Re-interpreting the isotope record of OAE 1a. 149 8.1 What was the role of volcanism in the evolution of OAE 1a? ...... 149 8.2 Constraining C and metal fluxes during OAE 1a ...... 151 8.2.1 Reconstruction of elemental fluxes during the emplacement of the Ontong-Java- Hikurangi-Manihiki Plateau...... 152 8.2.2 Estimating the isotopic forcing of continental weathering flux changes during OAE 1a...... 156 8.3 Discussion: Re-evaluating the isotopic record of OAE 1a ...... 162 8.3.1 Reconstructing the processes that affected C and metal fluxes during OAE 1a . . 165 8.3.2 Quantitative constraints on C fluxes from metal isotope excursions ...... 168 8.4 Conclusion ...... 171

9 Conclusions 173 9.1 Implications for the interpretation of isotopic records of other OAEs and LIP emplacements177 9.2 How does anthropogenic environmental forcing compare to LIP emplacements? . . . . . 179 9.3 Directions for future work...... 180

A Appendix for chapter 3 183 A.1 Aptian bathymetry used for our simulations...... 183 A.2 Range of measured OAE 1a negative CIE amplitudes ...... 183 A.3 Comparison between model forcing and output...... 184 A.4 Sensitivity studies ...... 185

x TABLE OF CONTENTS

A.5 Os data table ...... 189 A.6 Simulated surface ocean calcite saturation and temperature changes ...... 189 A.7 Model-data reconstruction of oceanic phosphate inventory for pre-OAE 1a ...... 193

B Appendix for chapter 4 197 B.1 Observed and simulated metal distributions in the water column ...... 197 B.2 Site specific model-data comparison...... 201

C Appendix for chapter 6 203 C.1 Simulated and observed vertical profiles of 187Os/188Os...... 203 Bibliography ...... 205

xi

List of Tables

Table Page

1.1 Segments of the carbon isotopic excursions associated with OAE 1a and their estimated durations. Underlying cyclostratigraphic studies are Li et al.(2008); Malinverno et al.(2010); Stein et al.(2011); Hu et al.(2012); Li et al.(2016); Graziano and Raspini(2018); Beil et al. (2020)...... 16

2.1 Step-wise alteration of physical boundary conditions to achieve an Early Aptian spin-up. . . 23

4.1 Estimates of pre-industrial Sr fluxes between surface reservoirs and their isotopic composition. 47 4.2 Estimates of pre-industrial Os fluxes between surface reservoirs and their isotopic composition. 48 4.3 Estimates of pre-industrial Li fluxes between surface reservoirs and their isotopic composition. 49 4.4 Estimates of pre-industrial Ca fluxes between surface reservoirs and their isotopic composi- tion. δ44/40Ca are given relative to NIST SRM915a (offset by +1.8825 0.07 from seawater ± (Holmden et al., 2012))...... 51 4.5 Model parameters setting weathering-related trace metal fluxes...... 56 4.6 Model parameters setting hydrothermal metal input...... 57 4.7 Model parameters setting the Os, Li and Sr contents of calcite shells...... 58 4.8 Model parameters setting Os scavenging...... 58 4.9 Model parameters for weathering-related trace metal fluxes...... 59 4.10 Model parameters for Sr recrystallization...... 59 4.11 Model parameters for metal deposition in sediments...... 60 4.12 Isotopic standards in cGENIE...... 61 4.13 Model parameters for the representation of isotopes and isotopic fractionation...... 62 4.14 Metal fluxes for pre-industrial spin up...... 64 4.15 Marine trace metal concentrations and residence times in our pre-industrial spin up compared to those reported in literature (see scientific background)...... 70

xiii LIST OF TABLES

5.1 List of experiment set-ups for this study. HT = high-temperature hydrothermal emissions, LT = low-temperature hydrothermal emissions. In ’pure C’ simulations I only increased

the CO2 degassing while the release of metal from the mantle stays constant. In ’no clay’ simulations, I assumed fully congruent weathering on land, i.e. continental run-off contains 4 times more Li and has a δ7Li = 2% (see description in the text). ’no Clim’ simulations

were run without simulating the climate change resulting from excess CO2 emissions. . . . . 79

5.2 Hydrothermal fluxes in the pre-industrial configuration, differentiated between high- and low-temperature components...... 80

5.3 Corresponding increase factors for elemental fluxes related to high-temperature and low- temperature alteration in simulations of a 100-kyr-long high-temperature hydrothermal event...... 82

5.4 Assumed analytical uncertainty for each simulated isotope system based on standard deviations during measurements of international carbonate standards (except for Os isotopes, which were measured on an internal standard) in recently published studies...... 83

5.5 Ratio of initial marine reservoir size and hydrothermal and continental influxes for Sr, Os, Li, Ca and C (atmospheric reservoir)...... 84

6.1 Compositions of marine Os sinks in our cGENIE simulations...... 115

7.1 Isotopic composition of seawater today and reconstructed for the Early Aptian...... 124

7.2 Overview of my simulations and respective variations in boundary conditions relative to the prescribed values in the pre-industrial set-up (see chapter4)...... 128

7.3 Atmospheric CO2 and seawater composition changes as a result of variations in boundary conditions in my pre-industrial model set-up. The table presents isotopic and concentration shifts from the most extreme boundary changes that I tested (see table 7.2). Negative and positive changes outside of measurement uncertainty are highlighted in blue and red, respectively. Colour shading indicates the scale of the change relative to the maximum change across all simulations...... 131

7.4 Range of isotopic run-off values which I considered geologically reasonable during the tuning of Early Aptian metal cycles...... 141

7.5 Proxy-consistency of my early Aptian simulations. Gray ’=’ signs indicate that the simulation result is within uncertainty of the reconstructed Aptian value. Analytical uncertainty of the proxy and uncertainty in the Aptian value are considered. Blue colouring indicates if the simulated value is smaller than the reconstructed Aptian value. The shading of the colours blue and red indicate how far off the simulated value is: the darker the colour, the bigger the offset...... 143

xiv LIST OF TABLES

8.1 Elemental composition of sample 1187-8 (hole 1187A, core section 10R-1, interval 114- 118cm) of fresh glass in Kroenke-type basalt and MORB glasses as reported by Ryan and Langmuir(1987); Chan et al.(1992); Verma(1992); Kushiro(1998); Fitton and Godard (2004)...... 153 8.2 Estimated total emissions during OJP emplacement. Upper-limit estimates for Os fluxes result from the assumption that Os concentrations in erupting OJ magma were 1000 those × in MORB melt, based on measurements (see section 8.2.1.2). Given missing controls on the extent of pre-eruptive differentiation and Os fractionation into crystals, these values could have been much higher...... 155 8.3 Isotopic composition of fluxes during OJP emplacement. Measured isotopic compositions are taken from Banerjee and Muehlenbachs(2003); Tejada et al.(2004, 2013); Sano and Nishio(2015)...... 155 8.4 Estimated annual elemental emissions (+) and sequestration (-) during OJP weathering. . . . 155

8.5 Estimated total weathering-related metal emissions during OAE 1a and the CO2 emissions

required to maintain the reconstructed atmospheric CO2 concentrations during weathering- related C sequestration. The given range of values represents the spread of simulation results due to different assumptions about event duration and initial C and metal cycle configurations.160

A.1 Rhenium and Osmium isotopic data for Cau samples. Uncertainties on Re and Os concentra- tions and measured (abbreviated as m. in the table header) 187Os/188Os and 187Re/188Os ratios incorporate analytical uncertainties and propagated uncertainties from the blank correction. Uncertainties on initial 187Os/188Os ratio include propagation of uncertainties on measured 187Os/188Os and 187Re/188Os ratios, age (121.5 1.7 Ma; Parkinson et al.(2001)) ± 11 1 and decay constant (l = 1.666x10− a− ; Smoliar et al.(1996)). Full duplicate analysis of ∗ sample...... 189 A.2 Proxy evidence of pre-OAE 1a seafloor oxygenation...... 194 A.3 Model-data scores for pre-OAE 1a seafloor oxygenation...... 195

xv

List of Figures

Figure Page

1.1 Schematic of the proxy behaviour during OAE 1a. δ13C and the definition of C-segments is based on Menegatti et al.(1998), δ18O is an approximation of data presented in Jenkyns (2018), ∆13C is based on Naafs et al.(2016a) and nannoconid abundance on Erba et al.(2010). 11

1.2 Reconstructed Early Aptian (120 Ma) geography and locations of sites with isotope records spanning OAE 1a (different symbols indicate different component of sediments analysed) and potentially active large igneous province emplacement (dashed circles, ’HALIP’ = High Arctic Large Igneous Province, ’OJMHP’ = Ontong-Java-Manihiki-Hikurangi Plateau). The elevation data was taken from Scotese(2018). Indicated carbonate records are from Erba et al.(1999); Jenkyns and Wilson(1999); Bellanca et al.(2002); Immenhauser et al.(2005); Luciani et al.(2006); Heldt et al.(2008); Michalík et al.(2008); Millán et al.(2009); Keller et al.(2011); Millán et al.(2011); Najarro et al.(2011b); Quijano et al.(2012); Lorenzen et al. (2013); Phelps et al.(2014) and records of sedimentary organic matter re from Menegatti et al.(1998); Takashima et al.(2004); Dumitrescu and Brassell(2006); van Breugel et al. (2007a); Millán et al.(2009); Najarro et al.(2011b); Stein et al.(2011, 2012); Quijano et al. (2012); Gaona-Narvaez et al.(2013); Pauly et al.(2013); Westermann et al.(2013); Schlak et al.(2016)...... 12

2.1 Changes in atmospheric CO2 concentration and land-surface temperature under the stage change application of physical Aptian boundary conditions (see table 2.1). Arrows indicate the effect of adding an additional boundary condition change to the previous set-up. The respective additional boundary condition change is written in black text next to the arrow. The complete pre-industrial and Aptian set-ups are annotated with blue writing...... 24

2.2 Comparison of simulated Aptian surface temperatures in studies with FOAM (Pohl et al., 2020), HadCM3L (Farnsworth et al., 2019) and cGENIE (this study). Shown are the spatial

pattern of surface temperatures in the three models under 1120 ppm atmospheric CO2 concentrations and minimum TEX86 temperatures (Steinig et al., 2020, , upper row) and

below average temperatures for ocean, land, non-polar land (-60 – 60◦N) and the globe under

different CO2 concentrations...... 25

xvii LIST OF FIGURES

3.1 Reconstructed properties of the surficial carbon reservoir during OAE 1a (segments after

Naafs et al.(2016b)) and pCO2 forcings used in this study. a) Reconstruction of bulk 13 carbonate δ C variation and pCO2 across OAE 1a based on proxy data from Cau (Naafs et al. 2016a): b) Zoom into the onset of the negative CIE, showing δ13C changes and the 13 5 pCO2 scenarios we tested in cGENIE. δ C values are given as offsets from the highest 13 value in the smoothed δ Ccarb data series prior to the start of OAE 1a...... 34

3.2 Carbon fluxes and their isotopic signatures across the onset of the negative CIE as calculated

by cGENIE. (a) and (b) show differences due to different pCO2 change scenarios (see fig. 3.1), all assuming a CIE onset duration of 100 kyr. (c) and (d) show the influence of a different CIE onset duration (20-300 kyr) examplarily for scenario 3. The results are averaged over 1m depth equivalent...... 36

187 188 3.3 Os concentration and Os/ Os(i) between meters 39 and 65 of the Cau section. The onset of the negative CIE is marked by blue shading. Uncertainties on data are smaller than the symbols...... 37

3.4 Osmium isotopic changes (left) and reconstructed δ13C signature of emissions based on carbon isotopes (right) at Cau. The two shaded sections show phases of least (A) and most prominent (B) volcanic activity...... 39

4.1 Sr, Li, Os and Ca contents of seawater. Shown are composites of all published measured concentrations and isotope ratios with reported errors. From these, we calculated mean concentrations and isotope ratios which are indicated by horizontal lines. Shading indicates one standard deviation around the means. Data are taken from Angino et al.(1966), Fabricand et al.(1967), Bernat et al.(1972), Brass and Turekian(1974), De Villiers(1999), Pearce et al.(2015), Mokadem et al.(2015) and the compilation of Wakaki et al.(2017) for Sr, Angino and Billings(1966), Fabricand et al.(1967), Chan(1987), Chan and Edmond(1988), You and Chan(1996), Moriguti and Nakamura(1998), Tomascak et al.(1999), James and Palmer(2000), Košler et al.(2001), Nishio and Nakai(2002), Hall(2002), Bryant et al. (2003), Pistiner and Henderson(2003), Millot et al.(2004), Choi et al.(2010), Pogge von Strandmann et al.(2010), Phan et al.(2016), Lin et al.(2016), Henchiri et al.(2016), Weynell et al.(2017), Fries et al.(2019), Gou et al.(2019), Hindshaw et al.(2019), Murphy et al. (2019) and Pogge von Strandmann et al.(2019) for Li, Levasseur et al.(1998), Woodhouse et al.(1999) and Gannoun and Burton(2014) for Os and Fabricand et al.(1967), De Villiers (1999) and Fantle and Tipper(2014) for Ca...... 52

4.2 Processes included in the cGENIE trace metal implementation and the number of the subsection containing their explanation. Hashed arrows indicate processes during which isotopic fractionation occurs in the model...... 55

xviii LIST OF FIGURES

4.3 Comparison between measured and simulated Sr composition of seawater. Shown are measured Sr concentrations and isotope ratios and the values of all ocean grid cells from the model simulations, sorted by value from smallest to biggest. Mean concentrations and isotope ratios are indicated by horizontal lines, and shading indicates one standard deviation around the means. Data is taken from Angino et al.(1966), Fabricand et al.(1967), Bernat et al.(1972), Brass and Turekian(1974), De Villiers(1999), Mokadem et al.(2015) and Wakaki et al.(2017)...... 66

4.4 Comparison between measured and simulated Os composition of seawater. Shown are all available measured Os concentrations and isotope ratios and the values of all ocean grid cells in the simulation, sorted by value from smallest to biggest. Mean concentrations and isotope ratios are indicated by horizontal lines, and shading indicates one standard deviation around the means. Data is taken from Levasseur et al.(1998), Woodhouse et al.(1999) and Gannoun and Burton(2014)...... 67

4.5 Comparison between measured and simulated Li composition of seawater. Shown are all available measured Li concentrations and isotope ratios and the values of all ocean grid cells in the simulation, sorted by value from smallest to biggest. Mean concentrations and isotope ratios are indicated by horizontal lines, and shading indicates one standard deviation around the means. Data is taken from Angino and Billings(1966), Fabricand et al.(1967), Chan(1987), Chan and Edmond(1988), You and Chan(1996), Moriguti and Nakamura (1998), Tomascak et al.(1999), James and Palmer(2000), Košler et al.(2001), Nishio and Nakai(2002), Hall(2002), Bryant et al.(2003), Pistiner and Henderson(2003), Millot et al. (2004), Choi et al.(2010), Pogge von Strandmann et al.(2010), Phan et al.(2016), Lin et al. (2016), Henchiri et al.(2016), Weynell et al.(2017), Fries et al.(2019), Gou et al.(2019), Hindshaw et al.(2019), Murphy et al.(2019) and Pogge von Strandmann et al.(2019). . . . 68

4.6 Comparison between measured and simulated Ca composition of seawater. Shown are all available measured Ca concentrations and isotope ratios and the values of all ocean grid cells in the simulation, sorted by value from smallest to biggest. Mean concentrations and isotope ratios are indicated by horizontal lines, and shading indicates one standard deviation around the means. Data is taken from Fabricand et al.(1967), De Villiers(1999) and Fantle and Tipper(2014)...... 69

4.7 Transient changes in modelled Sr, Os, Li, Ca, composition of seawater and atmospheric CO2 and temperature following instant releases of 1000 Pg C and 5000 Pg C. Shown are changes a) in concentrations, and b) in isotopic composition of seawater...... 70

5.1 Total emissions in the simulations of hydrothermal events of different durations and intensities. For each element, the total amount artificially added to the ocean throughout the experiment is shown, each cross indicating the value for one simulation...... 81

xix LIST OF FIGURES

5.2 Transient changes in modelled Sr, Os, Li, Ca, composition of seawater and atmospheric

CO2 and temperature as a result of increased hydrothermal emissions. Shown are changes in concentrations (top row), and in isotopic composition of seawater (bottom row) for 100 kyr (left column) and 500 kyr (right column) of enhanced hydrothermal emissions. Shading indicates the strength (metal flux) of the emission event. Lines of different opacity show the evolution of a variable under different factors of hydrothermal emission increase: 2, 4, 6 and 10 pre-industrial emissions. In simulations represented by coloured lines, the modern-day × C:metal ratio is preserved. In simulations represented by dotted, gray lines, the C:metal ratio = 0, hence mantle-derived metals are released but no extra C is added to the ocean. Horizontal gray bands, where visible, indicate intervals of assumed analytical uncertainty (see section 5.2)...... 85

5.3 Transient changes in modelled Sr, Os, Li, Ca, composition of seawater and atmospheric

CO2 and temperature as a result of increased hydrothermal emissions with 2 modern-day × C:metal ratio. Shown are changes in concentrations (top row), and in isotopic composition of seawater (bottom row) for 100 kyr (left column) and 500 kyr (right column) of enhanced hydrothermal emissions. Lines of different opacity show the evolution of a variable under different amounts of hydrothermal emission increase: 2, 4, 6 and 10 pre-industrial emissions. × Within each panel, rows shows the timeseries of different proxy systems. In simulations represented by coloured lines, the C:metal of excess hydrothermal emissions is 2 that of × modern-day hydrothermal systems. In simulations represented by dotted, gray lines, the C:metal = 0, hence more mantle-derived metals are released but no extra C is added to the ocean. Horizontal gray bands indicate intervals of assumed analytical uncertainty (see section 5.2)...... 87

5.4 Separation of contributions of exogenic (’no C forcing’), continental (difference between ’full C forcing’ and ’no climate response’) and sedimentary (difference between ’no climate response’ and ’no C forcing’) metal injections to the simulated metal isotope excursions in the scenario of 10 pre-industrial hydrothermal emissions, sustained over 500 kyr, with × 2 modern-day C:metal. Horizontal gray bands indicate intervals of assumed analytical × uncertainty (see section 5.2)...... 88

5.5 Amplitude of isotopic excursions as a function of the cumulative amount of excess hy- drothermal metal emission for 187Os/188Os, 87Sr/86Sr, δ88Sr, δ7Li, δ44Ca in all simulations. Different marker colours show excursion maxima in simulations with different C:metal of the hydrothermal forcing. Markers of different shape indicate the duration of enhanced high-temperature hydrothermal activity...... 90

xx LIST OF FIGURES

5.6 Time span of 187Os/188Os, 87Sr/86Sr, δ88Sr, δ7Li, δ44Ca and δ13C peak excursions in simulations of (a) a quadrupling and (b) a 10-fold increase of modern day hydrothermal inputs with different C:metal over 500 kyr. Each coloured line shows the temporal persistence of isotope values peak excursion + typical analytical uncertainty. See table 5.4 for values ≤ of the assumed analytical uncertainties. The vertical line indicates the end of the simulated igneous forcing...... 91

5.7 Marine Li reservoir perturbation due to hydrothermal input and enhanced weathering with reduced terrestrial clay formation. The former is the simulation of 10-fold pre-industrial hydrothermal input with 2 C:Metal previously discussed. The latter contains the same × forcing, but 4 [Li] in continental run-off and riverine δ7Li=2%...... 92 ×

5.8 Comparison of simulated recoveries of Sr, Os, Li, Ca, compositions of seawater, atmospheric

CO2 and temperature after a 100-kyr high-temperature hydrothermal emissions event with and without enhanced low-temperature basalt alteration. Each row shows the results of simulations with a different low-temperature alteration rate. The upper row shows differences between experiments with low-temperature alteration increases proportional to preceding hydrothermal fluxes (see section 5.2.2) and the previously discussed experiments without increased low-temperature alteration (same as in figures 5.2 and 5.3). The panels in the second row compare recoveries of marine reservoirs in simulations with (dotted lines) and without (coloured lines, same as in fig 5.3) quadrupled pre-industrial low-temperature alteration following 100 kyr lasting high-temperature hydrothermal emissions with 2 C:Metal. Red × and gray vertical areas show phases of active enhanced high-temperature hydrothermal fluxes and low-temperature hydrothermal fluxes, respectively. Horizontal gray bands indicate intervals of assumed analytical uncertainty (see section 5.2)...... 94

5.9 ’Proxy potential’ of seawater 187Os/188Os, 87Sr/86Sr, δ88Sr, δ7Li, δ44Ca changes across the simulated hydrothermal events for all tested forcing strengths. Each proxy system is represented by a different marker shape. Colours indicate if a measurable (considering a theoretical analytic error) isotopic excursion is directly attributable to exogenic (mantle- derived) metal emissions, continental input due to enhanced weathering, carbonate dissolution or whether more than one of these processes shape the excursion. The assumed analytical uncertainties are: 0.02 (187Os/188Os), 0.0001 (87Sr/86Sr), 0.01% (δ88Sr), 0.1% (δ7Li) and 0.05% (δ44Ca)...... 100

5.10 Conceptualization of contributions of mantle emissions and C-cycle dynamics to the recorded excursion amplitudes in (a) radiogenic (e.g. 187Os/188Os and 87Sr/86S) and (b) stable (e.g. δ88Sr, δ7Li,δ44Ca) isotope proxy systems...... 102

xxi LIST OF FIGURES

6.1 Composite figure of reported Os isotopes (a) before and during OAE 1a and (b) before, during and after OAE 2. The presented data is taken from Tejada et al.(2009); Bottini et al.(2012); Adloff et al.(2020) for OAE 1a and Du Vivier et al.(2015) for OAE 2. In (a), ’background’ refers to the Aptian (all available data points) before the transient radiogenic Os isotope excursion, which is represented by ’pre-OAE’ values. In (b) ’pre-OAE’ and ’post-OAE’ each represent approximately 500 kyr before/after the unradigenic Os isotopic excursion during OAE 2...... 111

6.2 Published relationships between [Os] and [O2] from different ocean basins (East Pacific: 1Woodhouse et al.(1999), 2Chen and Sharma(2009), 3Gannoun and Burton(2014); North Atlantic: 4Gannoun and Burton(2014); Indian Ocean: 5Levasseur et al.(1998)) and measured with different methods. The figure is based on a similar figure in Woodhouse et al.(1999) . 112

6.3 Comparison between the observed and simulated relationship between dissolved Os and O2 concentrations in seawater. Shown are values of all ocean grid cells in the simulation and published observations from different ocean basins (East Pacific: 1Woodhouse et al.(1999), 2Chen and Sharma(2009), 3Gannoun and Burton(2014); North Atlantic: 4Gannoun and Burton(2014); Indian Ocean: 5Levasseur et al.(1998))...... 117 6.4 Comparison between the observed and simulated vertical profile of [Os] in seawater. Shown are the average profile in each simulation, as well as regional simulation results and published observations (East Pacific: 1Woodhouse et al.(1999), 2Chen and Sharma(2009), 3Gannoun and Burton(2014); North Atlantic: 4Gannoun and Burton(2014); Indian Ocean: 5Levasseur et al.(1998))...... 118

6.5 Marine O2 inventory and POC flux as a function of nutrient abundance in cGENIE (a), as well as the corresponding marine residence time of Os (b)...... 119 6.6 Deviations in spatial 187Os/188Os homogeneity in seawater versus different environmental conditions relative to today for the LGM, late Paleocene, late Cenomanian and Aptian. Estimates for differences in marine oxygenation are taken from Kaiho(1991); Jaccard and Galbraith(2012); Monteiro et al.(2012); Adloff et al.(2020); Remmelzwaal et al.(2019), in productivity from Thomas et al.(2000); Maher et al.(2010); Monteiro et al.(2012); Adloff

et al.(2020), and in atmospheric CO 2 from Yiou et al.(1991); Monteiro et al.(2012); Gehler et al.(2016); Naafs et al.(2016a)...... 120

187 188 87 86 88 7 44 13 7.1 Os/ Os, Sr/ Sr, δ Sr, δ Li, δ Ca, δ C and atmospheric CO2 in simulations with step changes in different boundary conditions (see section 7.3.1). Every symbol style represents a different boundary condition that was changed and symbol colors indicate the different degrees of change that were tested. Arrows connect the results of simulations with modern-day boundary conditions and the biggest tested boundary condition change, pointing in the direction of an increase in the respective condition. The reconstructed composition of Aptian seawater (see table 7.1) with error margins is indicated where available...... 132

xxii LIST OF FIGURES

7.2 Changes in metal and C reservoirs and the marine carbonate system due to different boundary condition changes (see section 7.3.1). Each symbol represents a boundary condition change. The size of the symbols represents the relative size of the simulated change. Values in the present-day spin-up are indicated by horizontal dotted lines. Dashed lines indicate reconstructed values for the Aptian, where available. Symbols highlighted in orange show results for simulations with unequal temperature dependencies of Ca and alkalinity inputs (equal dependencies in grey)...... 134

7.3 Modelling stages to produce proxy-consistent spin-ups of Early Aptian C and metal cycles. In stage 1 ("Physical boundary conditions"), I equilibrate the model with the physical input

fields representative of the Aptian and 840 ppm atmospheric CO2 concentration. In stage 2

("Carbon cycle"), I set up for different C cycles which stabilize atmospheric CO2 at 840 ppm. In stage 3 ("Metal cycles"), I set up two different versions of proxy-consistent metal cycles for each C cycle configuration and tuned the isotopic composition of continental run-off to achieve proxy-consistent marine metal reservoirs...... 139

7.4 Time-series of target isotope values in the final version of the simulation with 2xpre-

industrial CO2 degassing, 2xpre-industrial CaCO3:CaSiO3 and 1xpre-industrial hydrothermal

emissions (2xCO2PI , CaCO3, 1xHYDPI in figure 7.3). This is an example of the residual isotopic drift after iteratively tuning the composition of continental run-off for all simulations. Shaded areas indicate the uncertainty interval, which is includes measurement uncertainties and differences between Early Aptian isotopic values from different locations (see table 7.1 for references)...... 142

7.5 Sizes of marine metal reservoirs in simulations of the Early Aptian and marine pH in different C cycle configurations. Dotted horizontal lines indicate pre-industrial values. . . . 143

7.6 Isotopic composition of continental run-off in the different Early Aptian configurations as a result of the tuning process. Dotted horizontal lines indicate pre-industrial values...... 144

8.1 Isotopic record of OAE 1a from Resolution Guyot, North Pacific (Jenkyns et al., 1995; Blättler et al., 2011; Lechler et al., 2015) and Cismon, Italy (Tejada et al., 2009). Black vertical lines delineate the ’Selli level’, or OAE 1a interval. The dark and light gray areas mark the negative and positive δ13C excursions, respectively...... 150

8.2 Isotopic response to the highest atmospheric CO2 concentrations reconstructed by (Naafs et al., 2016a) across the C isotope excursions associated with OAE 1a. Shown are timeseries of isotopic changes in seawater assuming that the δ13C record analyzed by Naafs et al. (2016a) represents a period of a) 1 Myr and b) 3 Myr. c) compares the simulated and measured metal isotope excursion amplitudes...... 158

xxiii LIST OF FIGURES

8.3 Comparison of average estimated metal fluxes derived in the previous sections of this chapter (a) and their relative potential to shift the isotopic composition of seawater (b). This potential was estimated by multiplying estimated fluxes with estimated isotopic offsets between seawater and the respective metal source or sink. Whiskers indicate the range between minimum and maximum estimates due to uncertain original volume and composition of OJP basalt, event duration and differences between the tested metal and C cycle configurations. In b), whiskers additionally include uncertainties about the isotopic offset between seawater and marine metal sources in the Early Aptian. Since it is unknown how secondary mineral formation changes affected riverine δ7Li and δ44Ca during the C cycle perturbation, their uncertainty ranges on the potential isotopic forcing from weathering fluxes include the possibilities of any run-off composition between fully congruent and present-day weathering regimes...... 163 8.4 Comparison of estimated C sources and sinks during the C cycle perturbation associated

with OAE 1a. Simulations of the biggest reconstructed atmospheric CO2 concentration change and corresponding weathering flux changes resulted in estimates of the combined atmospheric and marine C sink and C sequestration due to weathering flux changes. This is compared to reconstructions of C emissions during the emplacement of the OJP and C sequestration during its weathering, and estimates of C emissions from sill intrusions at the High Arctic Large Igneous Province (HALIP Polteau et al., 2016). The ’missing flux’ term quantifies the C flux which would be required to achieve C flux balance. Whiskers indicate the range between minimum and maximum estimates due to differences between the tested metal and C cycle configurations and event duration, as well as the uncertain original volume and composition of OJP basalt...... 169

A.1 Bathymetry prescribed for the simulations in the present study. This is the regridded version of the bathymetry used in Donnadieu et al.(2006a). The paleo-location of the Cau site is indicated by a black star...... 183 A.2 Size of the negative δ13C excursion measured in bulk carbonate of OAE 1a sediment records. The same 5-point smoothing was applied to all data sets and excursion amplitudes were calculated by subtracting the mean of stage C2 values from the most negative δ13C value during the excursion in the smoothed data set. Due to this calculation method, only records providing values for segments C2 and C3 could be considered. Additionally, these two stages had to be distinguishable in the records. This figure draws on data from Italy: Calabianca (Bellanca et al., 2002), Pusiano (Keller et al., 2011), Coppitella (Luciani et al., 2006), Cismon (Erba et al., 1999), north-central Tunisia (Heldt et al., 2008), Spain: Madoz (Millán et al., 2011), Carbonero, Cau and Puentenansa (Quijano et al., 2012), Aralar, Igaratza and Iribas (Millán et al., 2009), Cuchía and La Florida (Najarro et al., 2011b), France: La Bédoule (Lorenzen et al., 2013), Slovakia: Rochovika (Michalík et al., 2008), Oman (Immenhauser et al., 2005) and the southern USA (Phelps et al., 2014)...... 184

xxiv LIST OF FIGURES

A.3 Comparison between model forcing and simulation results: continuous lines represent model 13 forcings (atmospheric CO2 concentration changes (a) and the atmospheric δ C excursion 13 13 (b) offset by the difference between oceanic DIC δ C and atmospheric CO2 δ C (c)) and dashed lines show simulation results...... 185

A.4 Rate and isotopic signature of carbon emissions according to scenario 3, starting from 3 and

4 times pre-industrial CO2 concentrations...... 186

A.5 Rate and isotopic signature of carbon emissions required to produce pCO2 changes as prescribed in scenario 3 together with the measured CIE, starting from 0.5 and 1 times pre-industrial oceanic nutrient inventory...... 186

A.6 Rate and isotopic signature of carbon emissions required to produce pCO2 changes as prescribed in scenario 3 together with the measured CIE, starting from an initial surface ocean carbonate saturation state of 4.5 (’low alk’) and 5.3 (’high alk’)...... 187

A.7 Rate and isotopic signature of carbon emissions required to produce pCO2 changes as prescribed in scenario 3 together with the measured CIE, with and without temperature dependent biology. Weathering fluxes are adjusted to achieve the same baseline surface ocean saturation state in both simulations...... 187

A.8 Rate and isotopic signature of carbon emissions required to produce the measured CIE and

pCO2 changes as prescribed in scenario 3 and in a new, more extreme pCO2 change scenario (’scenario 6’)...... 188

A.9 Surface ocean calcite saturation Ωsur f ace changes across the simulations in different pCO2 change scenarios and duration estimates for the OAE 1a negative CIE...... 190

A.10 Spatial pattern of surface ocean calcite saturation Ωsur f ace in our spin up for the Aptian (a),

and changes in simulations of different pCO2 change scenarios and event durations (b-e).

The changes are calculated by subtracting the baseline Ωsur f ace values from the Ωsur f ace values at the end of the respective simulation...... 191

A.11 Spatial pattern of sea surface temperatures (SST) in our spin up for the Aptian (a), and

changes in simulations of different pCO2 change scenarios and event durations (b-e). The changes are calculated by subtracting the baseline SST values from the SST values at the end of the respective simulation...... 192

A.12 Spatial pattern of proxy evidence for and against bottom water dysoxia before OAE 1a (see table A.2) overlying the model bathymetry...... 193

xxv LIST OF FIGURES

B.1 Comparison of measured Sr, Li, Os and Ca profiles in seawater. Shown are composites of all available profiles of measured concentrations and isotopic compositions. Data are taken from Angino et al.(1966), Fabricand et al.(1967), Bernat et al.(1972), Brass and Turekian (1974), De Villiers(1999), Mokadem et al.(2015) and Wakaki et al.(2017) for Sr, Angino and Billings(1966), Fabricand et al.(1967), Chan(1987), Chan and Edmond(1988), You and Chan(1996), Moriguti and Nakamura(1998), Tomascak et al.(1999), James and Palmer (2000), Košler et al.(2001), Nishio and Nakai(2002), Hall(2002), Bryant et al.(2003), Pistiner and Henderson(2003), Millot et al.(2004), Choi et al.(2010) and Lin et al.(2016) for Li, Levasseur et al.(1998), Woodhouse et al.(1999) and Gannoun and Burton(2014) for Os and Fabricand et al.(1967) and De Villiers(1999) for Sr/Ca and Ca...... 198 B.2 Comparison between measured and simulated Sr profiles in seawater. Shown are composites of all available measured Sr concentration and isotope ratio profiles and all profiles in the simulation. Data is taken from Angino et al.(1966), Fabricand et al.(1967), Bernat et al. (1972), Brass and Turekian(1974), De Villiers(1999) and Mokadem et al.(2015)...... 199 B.3 Comparison between measured and simulated Os vertical profiles in seawater. Shown are composites of all available measured Os concentration and isotope ratio profiles and all profiles in the simulation. Data is taken from Levasseur et al.(1998), Woodhouse et al. (1999) and Gannoun and Burton(2014)...... 200 B.4 Comparison between measured and simulated Li profiles in seawater. Shown are composites of all available measured Li concentration and isotope ratio profiles and all profiles in the simulation. Data is taken from Angino and Billings(1966), Fabricand et al.(1967), Chan (1987), Chan and Edmond(1988), You and Chan(1996), Moriguti and Nakamura(1998), Tomascak et al.(1999), James and Palmer(2000), Košler et al.(2001), Nishio and Nakai (2002), Hall(2002), Bryant et al.(2003), Pistiner and Henderson(2003), Millot et al.(2004), Choi et al.(2010) and Lin et al.(2016)...... 200 B.5 Comparison between measured and simulated Ca and Sr/Ca profiles in seawater. Shown are composites of all available measured concentration profiles and all profiles in the simulation. Data is taken from Fabricand et al.(1967), De Villiers(1999) and Fantle and Tipper(2014). 201 B.6 Comparison between measured and simulated Sr concentrations and isotopic composition in surface waters. Measurements are shown as symbols on the map, the colour indicating the respective value. Data is taken from Angino et al.(1966), Fabricand et al.(1967), Bernat et al.(1972), Brass and Turekian(1974), De Villiers(1999), Mokadem et al.(2015) and Wakaki et al.(2017)...... 202

C.1 Comparison between the observed and simulated vertical profile of [Os] in seawater. Shown are the average profile in each simulation, as well as regional simulation results and published observations (East Pacific: 1Woodhouse et al.(1999), 2Chen et al.(2009), 3Gannoun and Burton(2014); North Atlantic: 4Gannoun and Burton(2014); Indian Ocean: 5Levasseur et al.(1998))...... 204

xxvi ihhg nri eg otnna c hes okwahrn,vniaino h epoen a be can ocean) deep the of ventilation weathering, rock sheets, ice continental (e.g. inertia high with ,adatrdhbtt n iigcniin o raim costepae (e.g. planet the across organisms for conditions living and habitats altered and 2013), al., et (Stocker h at scretyeprecn abn()cceprubto asdb h ees feoei C exogenic of release the by caused perturbation cycle (C) carbon a experiencing currently is Earth The nphto hi yais eie,smlto eut eoeicesnl neti ihtelnt of length the with uncertain increasingly short become a results contains simulation only of Besides, record mechanisms dynamics. observational their the the of instances, as snapshot most uncertain still in Yet, are processes emissions. studies responding extreme for slowly considered of these be scenarios to or need impacts processes processes these long-term However, of of future. Changes near the 2016). of al., simulations et in (Lord neglected Myr 1 the to from up recovery system take Earth might full which the injection simulate However, C to centuries. anthropogenic expensive few next computationally the too over are emissions models the C elucidate these human to of grids consequences resolved local high and and increasingly regional atmosphere on global, of run simulations are cycles Numerical community. biogeochemical research and physics climate ocean the C exogenic of of priority consequences key the a of is skills emissions civilization, predictive human accurate and and ecosystems understanding the affects profound that system a impacts atmosphere-ocean developing wide-ranging C the and additional in complex of C these of strength through accumulation and is observed it effect Since the thus 2013 ). altering , al. capacities, and et reservoir (Stocker accumulation C emissions C and initial fluxes these the C of on Many influence feedbacks 2019). return, causing al., in et many, Piao and 2011 ; inter-connected Hoegh-Guldberg, are etc, impacts greening global reefs, coral of cryosphere demise the and cycle hydrological the water patterns, and weather air in in changes rise the associated global affected with a measurably causing temperatures by has prominently centuries most and environment, chemical decades accumulation and past The biological the physical, 1996 ). over system (Joos, ocean atmosphere-ocean and the atmosphere in the C in of C light isotopically of accumulation the through and e.g. ways, numerous in CO detected atmospheric been rising has perturbation This system. atmosphere-ocean the into 2 2015 ) al., et Lauvset ( pH ocean surface decreased 1996 ), (Joos, concentration 1 Introduction

C h a p t e r 1 CHAPTER 1. INTRODUCTION the simulated time period as the simulated circulation and elemental cycles increasingly deviate from present-day conditions which serve as a reference for model calibrations (Knutti and Sedláček, 2013). A different approach to learn about the long-term response of the Earth system to exogenic C injections has been to study previous C injection events, since the geological record is full of evidence of past carbon cycle perturbations: Abrupt changes in the carbon isotopic composition of sediments hint at upheavals in superficial carbon reservoirs, and warming and ocean acidification events have been reconstructed for several intervals of Earth’s history (Dickens, 2009; Hönisch et al., 2012). These events provide valuable insight into the sensitivity to C injections of the various parts of the Earth system in diverse settings. Although none of these events can serve as a full analogue for the present-day C cycle disruption in terms of emission rates (Zeebe et al., 2016), reconstructed total emissions for several of these events are similar or larger than the anticipated total amount of anthropogenic C release by the end of this century ( 1000 Pg C, e.g. Gutjahr et al., 2017). The geological record can thus provide more case ≥ studies of possible Earth system responses to such large C releases than the observational record, and in particular offers the opportunity to study natural carbon source and sink dynamics, threshold behaviour and tipping points (Lenton, 2011) on longer timescales. For example, paleoclimate research revealed the non-linear response of the North Atlantic current to warming-induced melt water addition (Bond et al., 1992) and highlighted the potential of thawing methane clathrates to exacerbate the impacts of exogenic C emissions (e.g. Kennett et al., 2003). An impressive example of a long-term negative feedback to exogenic C emissions in the last 250 Myrs are ’Oceanic Anoxic Events’ (OAEs, Jenkyns, 2010; Robinson et al., 2017). OAEs were periods of wide-spread preservation of organic matter in marine sediments in the Mesozoic and Paleozoic. These events are interpreted as recurring phases of low marine oxygen concentrations, hence their name (OAEs, Schlanger and Jenkyns, 1976). This first interpretation was later supported by the discovery that the cycling of many other redox-sensitive elements was dramatically perturbed during OAEs (Jenkyns, 2010). The high amount of preserved organic matter and the fact that these geological events were accompanied by large changes in the stable C isotopic composition in marine sediments (Robinson et al., 2017) indicate that marine sediments repeatedly turned into a large, transient C sink and balanced the C cycle during periods of warm background climates. Based on a synchronicity of OAEs with the emplacement of large igneous provinces (LIPs, e.g. Jones and Jenkyns, 2001; Percival et al., 2015), volcanism and/or the associated emission of mantle-derived CO2 have been suggested as likely triggers of OAEs. In particular, the C isotopic record of the Early Aptian OAE 1a ( 121 Ma, Olierook et al., ∼ 2019) suggests that exogenic C release preceded the phase of enhanced organic C burial (Menegatti et al., 1998). A link between volcanism and OAEs was further supported by the discovery of shifts in the isotopic composition of sedimentary Strontium (Sr) and Osmium (Os) towards very unradiogenic (mantle-like) values at the onset of OAEs (Jones and Jenkyns, 2001; Tejada et al., 2009; Bottini et al., 2012). OAEs are particularly relevant case studies for understanding the present-day C cycle perturbation because they feature enhanced exogenic C emissions, as well as increased nutrient supply to the oceans.

2 In fact, the increased nutrient supply was a key factor for OAE formation and duration (Jenkyns, 2010; Monteiro et al., 2012), but the origin of the added nutrients is still uncertain. Possible origins are: emission from submarine volcanism or related sediment metamorphism (Snow et al., 2005), sedimentary release in response to decreased marine oxygenation (Arndt et al., 2009), or indirect supply via enhanced

weathering rates resulting from an increase in atmospheric CO2 concentration (Poulton et al., 2015). At the moment, marine oxygen minimum zones are expanding in response to rising temperatures (Oschlies et al., 2018). Improved understanding of the external forcings during OAE formation might elucidate how further marine deoxygenation can be prevented in the future. More than 40 years of research on OAEs have improved our understanding of the temporal and geographic extent of these events, as well as the range of affected biogeochemical cycles (Robinson et al., 2017; Jenkyns, 2018; Svensen et al., 2019). Yet, the roles of volcanism and Earth system feedbacks for the supply and burial of C and nutrients remain uncertain. This hampers the use of OAEs as case studies for Earth system feedbacks in two major ways: Firstly, without better knowledge of the relevance of volcanism for nutrient release, it is not clear whether the onset of OAEs was primarily carbon-, oxygen- or nutrient-driven, i.e. whether OAEs should be regarded as feedbacks to sustained warming (weathering-related nutrient supply), marine deoxygenation (sedimentary nutrient release) or as a reaction to increased exogenic nutrient supply (nutrient addition from the mantle). The relative roles of climate-driven and volcanic nutrient supply has direct implications for the necessity of external nutrient sources (e.g. LIP emplacement) to trigger OAEs, and the question whether such a perturbation of marine biogeochemistry can develop without exogenic C emissions. Or in the present-day context: Will limiting climate change via the internationally agreed C emission cuts (Paris Agreement, 2015) prevent deterioration of marine ecosystems or is there a risk that, without a global strategy to also regulate anthropogenic nutrient outputs, the currently temperature-driven deoxygenation becomes nutrient-driven in the future, regardless of limited climate change? Secondly, knowing the origin of exogenic C additions is crucial for estimating C emission rates

and the total amount of injected C during OAEs. In the absence of direct pCO2 proxies for most OAE intervals, quantification of past C fluxes relies heavily on their C isotopic fingerprint (Kump and Arthur, 1999). This fingerprint, however, is more complicated to interpret in the case of OAEs than shorter C cycle perturbations (e.g. Cenozoic hyperthermals) because of their long duration. The wide-spread organic C burial would have had the opposite isotopic effect on seawater than exogenic C emissions, with invoked C emissions sources typically adding isotopically light C to the atmosphere-ocean system, while organic C burial preferentially removes isotopically light C. During long-lasting OAEs, periods of exogenic C emissions and enhanced C burial likely overlapped temporarily. Hence, only the net isotopic change of both processes is preserved in the rock record and needs to be disentangled to obtain the pure isotopic signal of C inputs or burial. The ambiguity resulting from this temporal overlap for the study of the recorded isotopic excursions during OAEs is illustrated by the fact that two fundamentally different interpretations of the C isotope excursions are possible: If the isotopic compositions of emitted and buried C were the same (i.e. an organic C source and sink), the preserved net C isotope excursions would

3 CHAPTER 1. INTRODUCTION indicate fluctuations in the size of the marine C reservoir and thus C flux imbalances, during the OAE interval. If, instead, the emitted C was isotopically different from the buried C, a net isotopic excursion could have developed in a balanced C cycle by shifts in the isotopic composition of C inputs or outputs. Similarly, depending on the nature of the dominant C source different C masses were required to drive the observed negative C isotope excursion, since volcanic C has a smaller isotopic offset from seawater than organic C (Vervoort et al., 2019). In order to circumvent the ambiguous C isotope record of OAEs, several studies attempted to estimate C fluxes based on metal isotope systems which are sensitive to igneous processes and climate change (e.g. Lechler et al., 2015; Bauer et al., 2017a). This approach can only be used to reconstruct C fluxes from specific sources (i.e. volcanism) or to specific sinks (i.e. enhanced weathering and carbonate burial), and the relevance of the estimated C fluxes depends on the role of this specific process in the overall C cycle perturbation. Thus, identifying the dominant C source is key to disentangling forcings and feedbacks during OAEs and to quantifying exogenic C fluxes. Knowing the amount of emitted C will make it possible to compare OAE onsets quantitatively to other C cycle perturbations, including the current one, and to assess the role of OAEs for the Earth system’s sensitivity to C injections.

Finally, understanding the role of volcanism for OAE formation can also shed light on the environ- mental impacts of LIP emplacements. LIPs are massive basalt accumulations at Earth’s surface, which were created during episodes of extensive volcanism throughout Earth’s history (Ernst, 2014). These events were very likely responsible for the biggest cumulative releases of greenhouse gasses prior to humans and coincided with climatic changes and often mass extinctions (Ernst, 2014; Rampino and Self, 2015; Jones et al., 2016). Ocean plateaus are the largest LIPs in terms of basalt volume, yet the environmental impact of their emplacements appears to have been smaller than that of less voluminous continental flood basalts (Ganino and Arndt, 2009). In particular, improved radiometric dating has established that the largest volcanic structure on Earth’s surface, the Ontong Java plateau (OJP), was emplaced in close temporal proximity or coincident with the early Aptian OAE 1a and likely was the dominant volcanic source of C emissions at that time (Tejada et al., 2009). In that context, OAE 1a is enigmatic, not because of its intensity, but, on the contrary, the fact that it was not significantly more intense or longer than other OAEs, and that it was not associated with a mass-extinction event despite having coincided with the largest LIP emplacement. Additionally, other volcanic events have been put forward as potential sources of C emissions around OAE 1a, further challenging the impact strength of OJP emplacement. It has been theorized that Mesozoic biota might have been more resilient in the face of, and the global C cycle more buffered against, environmental perturbations due to extensive shallow shelf areas and the equitable climate at the time (Weissert, 2019), while other studies suggest that the carbon cycle is better buffered against sudden CO2 releases at present than in past warm periods due to increased erosion and continental denudation (Rugenstein et al., 2019) but a consensus is yet to be reached and will require quantitative knowledge of C fluxes during OAE 1a.

4 1.1. IDENTIFYING AND QUANTIFYING PAST C EMISSIONS

1.1 Identifying and quantifying past C emissions

The C cycle connects C reservoirs of different sizes, turn-over times and environmental sensitivities through a complex network of C fluxes (Sharp, 2017). While radioactive C is generated and decays through β-decay, the vast majority of the C on Earth, stable C, is neither produced nor destroyed. Hence, on a planetary scale, the size of any C reservoir is fully determined by the balance of fluxes into and out of it. In order to change the size of a reservoir, this balance needs to be altered, which requires external forcing. The non-lithological surficial C cycle (atmosphere, ocean, ecosystems, soils and sediments), in contrast, is not closed because C is exchanged between Earth’s interior, crust and surface. Thus, surficial C reservoir sizes can change because of a net change in the amount of C circulating at Earth’s surface (net C gain or loss from/to lithospheric C reservoirs, e.g. volcanism or lithological C sequestration) or because of externally-driven changes of the partitioning of a constant amount of C between surficial C reservoirs (e.g. orbital, evolutionary or climatic changes). The present-day C cycle disruption and, possibly OAEs are examples of the former. Among Earth’s C reservoirs, the atmospheric C reservoir has the shortest residence time and atmospheric C has the largest impact on the global environment because it directly affects the radiation balance of the planet, and thus climate (Tyndall, 1861; Arrhenius, 1896). Variations in the size and composition of the atmospheric C reservoir are thus prime indicators of an unbalanced C cycle. In fact, although scientists had been aware of anthropogenic C emissions from fossil fuel buring since the 19th century and speculated about their impact on the environment, it was the observation of increasing

atmospheric pCO2 which proved that these emissions were substantial enough to cause a global C cycle perturbation (Callendar, 1938; Revelle and Suess, 1957; Crawford, 1996; Harris, 2010). Through climate-sensitive exchanges between the atmospheric and other C reservoirs, the C cycle provides important stabilizing feedbacks to Earth’s climate. At the same time, the radiative forcing of atmospheric C enables C cycle imbalances to cause climate change. However, because of the large number of reservoirs in constant exchange with the atmosphere and the climate sensitivity of exchange fluxes, variations in

the amount of atmospheric CO2 cannot easily be attributed to a triggering mechanism for changes in

atmospheric pCO2. In particular, knowledge of the scale of the atmospheric C reservoir change alone is not enough to differentiate between exogenic C fluxes, i.e. C fluxes to/from reservoirs that are not

influenced by atmospheric CO2, and endogenic C flux changes, i.e. an alteration in the exchange between the atmosphere and another C reservoir because of a climatic change. This differentiation between exogenic C fluxes versus C cycle feedbacks in a C cycle perturbation requires knowledge about the

isotopic composition of atmospheric CO2, or the origin/sink of in-flowing/sequestered C. Size and origin of an unbalanced C flux can be assessed directly via changes in the emission rate of its source or indirectly via changes in the sizes and isotopic compositions of affected C reservoirs. The feasibility and accuracy of these methods depend on the nature of the emission source (e.g. emissions from point sources can be assessed more accurately than from area sources) and the scale of the impact on other C reservoirs. In the following sections, I describe common approaches for direct and indirect assessments of past C fluxes.

5 CHAPTER 1. INTRODUCTION

1.1.1 Indirect reconstruction of C emissions based on C isotopes

C fluxes entering or leaving a C reservoir can noticeably change the size of that reservoir, which can be used to infer the amount of transferred C. Direct evidence of size changes in the marine or atmospheric C reservoirs is not available beyond the instrumental and ice core record (Royer et al., 2001). However, indirect evidence of size changes in those reservoirs are preserved throughout the geological record: Since the amount of dissolved C in the ocean affects the stability of CaCO3, evidence of CaCO3 accumulation changes or dissolution hints at size changes of the marine C reservoir. The isotopic composition of dissolved boron is pH dependent, thus B isotopic shifts provide a more easily quantifiable indication of marine C reservoir size changes (Sanyal et al., 1995). The size of the atmospheric C reservoir is more difficult to constrain because there is no recorder of the composition of the air similar to sediments in the marine realm. Instead, physiological changes of plant leaves have been used to infer atmospheric

CO2 changes (Woodward, 1987). An approach to reconstruct the concentration of dissolved C in the surface ocean exploits the difference in isotopic composition of organic and inorganic sedimentary C (Dean et al., 1986). C has two stable isotopes, 12C and 13C, the relative abundance of which is expressed relative to a standard, commonly VPDB, in the δ13C signature (%):

13C ( 12 ) 13 C sample (1.1) C ( 13 1) 1000 = ( C ) − · 12C standard

12C is slightly lighter than 13C and thus requires less energy to be built into organic compounds. Organisms preferentially take up 12C and therefore cause isotopic fractionation between dissolved C in seawater and organic matter. This fractionation is dependent on the concentration of dissolved C in seawater, with larger fractionation occurring when more dissolved C is available. C in biogenic CaCO3, also produced in the surface ocean, has an isotopic composition equal to dissolved C in seawater. Tracking the difference of the isotopic composition of C in organic and inorganic components of sediments thus provides a means to infer changes in the concentration of dissolved C in the surface ocean and by extension CO2 partial pressure in the air, assuming that the surface ocean was in thermodynamic balance with the atmosphere (Freeman and Hayes, 1992). If the isotopic signature of a C flux is different to the reservoir it enters or leaves, shifts in the isotopic composition of that C reservoir can be used to derive the size of the C flux. Thus, while C fluxes themselves are transient and cannot be recorded, they can leave record-able imprints in the geologic record. Inversely, if the origin of of a C flux is known, its size can be derived from the isotopic change of the reservoirs involved. Commonly, isotope mixing models have been used to derive an envelope of possible C fluxes based on isotope excursions in the sedimentary record (e.g. Beerling et al., 2002). In order to reduce the width of the resulting C flux envelope, constraints from C reservoir size changes have been added: Assuming source isotopic compositions, forward-modelling of C injections have been 13 used to reproduce δ C excursion amplitudes and the extent of recorded CaCO3 dissolution and thus estimate the amount and origin of emitted C (e.g. Panchuk et al., 2008; Zeebe et al., 2009). However,

6 1.1. IDENTIFYING AND QUANTIFYING PAST C EMISSIONS

with this method, the match of the simulated and recorded C cycle perturbation still depends on two variables, the δ13C and magnitude of C inputs. With increasingly accurate and highly resolved isotope measurements and Earth system models, inversion methods, simplified but similar to those commonly used to trace carbon fluxes and reservoir changes in today’s Earth system (e.g. Jacobson et al., 2007), have also been applied to past carbon cycle perturbations. Cui et al.(2011) eliminated the emission rate as a variable by inverting the recorded δ13C excursion with the Earth system and dynamic C cycle model cGENIE. Thus, rather than guessing the amount of C required to produce the observed δ13C excursion, the latter is calculated by the model taking into account the effect of C cycle feedbacks. Adding reconstructions of size changes in the marine C reservoir, Gutjahr et al.(2017) also eliminated the need to prescribe the δ13C of the C flux, making it possible to reconstruct C flux size and composition. Since C reservoirs vary in their δ13C signature, the isotopic composition of a C flux contains information about the reservoir it originated from. The reservoir of origin, in turn, reveals the role C cycle feedbacks played for the C emission: If the emitted C was of organic origin, than the C emission was likely caused by destabilized surficial C. If, instead, the Earth’s mantle was the origin of the C emission, the recorded C cycle changes were predominantly the result of exogenic C input. Inversion experiments with fully coupled C cycle models can thus extract substantial quantitative information from δ13C records of past C cycle disruptions. The most important limitation of this inversion technique is that it only reconstructs the net C forcing. For example, exogenic C emissions would be underestimated in the case of simultaneously enhanced C sequestration. OAEs were events of enhanced C emissions and sequestration, which restricts the applicability of δ13C inversions across OAE intervals.

1.1.2 Direct reconstruction of C fluxes based on metal isotopes

A different approach to assess past C fluxes is to constrain the strength of C sources and sinks directly. This approach exploits the fact that variations in C sources and sinks commonly also perturb other biogeochemical cycles which are less ambiguous to interpret in the geological record than δ13C. In particular, radiogenic Os and Sr isotopes and stable Li and Ca isotopes have been used to reconstruct enhanced volcanism and continental weathering, respectively because the processes which control the C cycle on long timescales also shape those metal cycles (extensive descriptions of individual metal cycles are provided in chapter4): Continental weathering is a major source of dissolved metals and also a long-term C sink. Volcanic eruptions deliver C and metals to Earth’s surface and the main sinks of Sr, Ca and Os are linked to sedimentary C burial. The isotopic compositions of these metals in seawater, old crust, young crust and the mantle are very different, which enables the identification of the dominantly perturbed reservoir for Sr, Os, Li and Ca isotope excursions. These metals have long residence times in today’s ocean and they are well-mixed between ocean basins, meaning that changes in their global marine abundance can be reconstructed even if only a small number of well-preserved sedimentary successions is available. Isotopic excursions of these metal systems recorded in ancient marine sediments have been used to identify variations of volcanic input or continental weathering (e.g. Jones et al., 1994; Tejada et al., 2009; Kısakűrek et al., 2005a; Kasemann et al., 2005), and isotope-mixing models have been

7 CHAPTER 1. INTRODUCTION employed to quantify those variations based on the recorded isotope record (e.g. Blättler et al., 2011; Von Strandmann et al., 2013; Lechler et al., 2015; Bauer et al., 2017a). The results of these modelling studies have further been used to derive 1st-order estimates of C fluxes, assuming a constant quantitative link between these metal fluxes and C fluxes, neglecting C cycle feedbacks on metal release (e.g. Blättler et al., 2011; Bauer et al., 2017a). To my knowledge, the model by François and Walker(1992) and Goddéris and François(1995) is the only box model with coupled dynamic C and metal (Sr and Ca) cycles and has not been applied to transient C cycle perturbations. Although Os, Sr, Li and Ca isotope excursions have the previously stated advantages for the reconstruction of C cycle changes, they, too, have limitations: A general difficulty for the quantitative interpretation of these metal isotope records with isotope mixing models is that the continental end-member composition is variable through time, and cannot be reconstructed: The composition of metals supplied from the continents depends on the type of rock that is weathered and sedimentation processes en route to the open ocean. Radiogenic metal isotopes are the product of radioactive decay, and their abundances in the host rock thus vary with age in addition to lithology. Stable metal isotopes are fractionated during mineral formation in soils and freshwater systems, causing offsets between their abundances in continental run-off and the host rock (e.g. Hathorne and James, 2006). The long residence time of dissolved Os, Sr, Li and Ca in the ocean further limit their application to large-scale, long-term C-cycle changes and bears the risk that the isotopic response to several, individual forcing events might be blended in the isotopic record. Furthermore, although their perturbations are linked to the same processes that shape long-term carbon cycle change, these links are poorly understood and quantified, even for the modern, well-documented Earth system state. Finally, the usefulness of this approach for understanding the C cycle disruption during OAEs, depends on whether igneous forcings were dominant drivers of OAEs and whether metal flux changes correspond to C flux changes. The latter is sometimes assumed without giving a mechanistic justification (e.g. Bauer et al., 2017a). However, the quantitative link between C and metal input depends on the form of igneous forcing which, particularly in the case of LIP emplacement, is complex and requires a more detailed discussion.

1.2 Carbon and metal fluxes during the emplacement of Large Igneous Provinces

Large Igneous Provinces (LIPs) represent the largest accumulations of mafic rock at Earth’s surface, forming vast oceanic plateaus and continental flood basalts (Bryan and Ernst, 2008). The oldest evidence of LIP emplacement stems from the Archean (Shimizu et al., 2005) and the emplacement of the youngest LIP (Columbia River Flood Basalts) ended 6 Ma (Swanson et al., 1979). The 1783-1784 Laki flood basalt eruption is regarded as the most recent volcanic event comparable to - but significantly smaller than - previous LIP emplacements (Thordarson and Self, 2003). The formation of LIPs occurred in geologically short pulses ( 1 Myr), involving large-scale volcanic eruptions and sediment intrusions, in < some cases causing severe climate and environmental perturbations (see Bryan and Ernst, 2008, for full definition of LIPs). The emplacement of LIPs enhanced elemental fluxes from the mantle into the

8 1.2. CARBON AND METAL FLUXES DURING THE EMPLACEMENT OF LARGE IGNEOUS PROVINCES

ocean-atmosphere system and also affected elemental cycling between surficial reservoirs. The elemental and isotopic fluxes caused by LIP emplacement are thus varied, and fluxes of different compositions likely overlapped spatially and temporally, rendering their identification in the sedimentary record and their quantification difficult. In the following sections, I review the different LIP-related matter fluxes which will form the basis for the discussion of the isotopic record of OAE 1a in the subsequent chapters. LIP eruptions affect the Earth system in multiple ways. The physical presence of the new plateau affects the Earth system through changes in mass distribution and ocean currents or winds, but their biogeochemical impacts are most relevant for global environmental change and its sedimentary imprint.

Magma is supersaturated in CO2, so a lot of CO2 exsolves during an eruption, as well as other short-lived radiation-relevant volatiles. Consequent erosion of highly-weatherable fresh basalt adds metals and other elements to the ocean.

1.2.1 Emission of mantle-derived substances via volcanic eruptions, hydrothermal venting and alteration of fresh basalt

The composition and quantity of material directly emitted from the LIP depends on its magma source. LIPs are linked to mantle plumes (Ernst, 2014), which move material from the deep mantle with relatively

low concentrations of gasses to Earth’s surface. These gasses, predominantly water, CO2, SO4,H2 and

CH4 degas during an eruption (Jones et al., 2016). The amount of degassing depends on the ambient pressure at the location of magma surfacing (subaerial/submarine, ocean depth) and the velocity of magma ascent, which can prohibit complete degassing by quenching. Subducted oceanic crust can constitute an additional magma source of different composition and can substantially increase the amount of volatiles emitted during LIP eruptions (Sobolev et al., 2011). There are no direct measurements of volatile composition and quantity from LIP eruptions but several attempts have been made to estimate them based on the geochemical composition of LIP basalt (see chapter8 for further discussion). In submarine settings, mantle-derived matter can also enter the ocean without explosive eruptions, through hydrothermal activity. Seawater penetrating porous oceanic crust reacts with unaltered basalts and magma intrusions, gathering mantle-derived ions (Humphris, 1977). Because these reactions are temperature-dependent, hydrothermal activity at high temperatures (presently found near mid-ocean

ridges and magmatic hotspots, where intruding seawater can be heated up to 400◦C, Parson et al., 1995), > delivers mantle-derived ions at a higher rate than low-temperature (<60◦) interactions between seawater and ocean crust basalt. Today, magma only gets close enough to a small percentage of the seafloor to allow for high-temperature hydrothermal activity while low-temperature oceanic crust alterations happen over vast areas, which are mostly unexplored (e.g. Staudigel et al., 1996). On land, element release from LIP basalts depends on physical and chemical erosion rates which, on a global scale, are predominantly governed by temperature and run-off (Dessert et al., 2001; Huh, 2003; Johansson et al., 2018). As a result, continental LIP-related elemental fluxes are also a function of latitude (Donnadieu et al., 2006a). Finally, chemical alteration of LIP basalt also constitutes a sink for substances in the atmosphere-

9 CHAPTER 1. INTRODUCTION

ocean system, in particular CO2, to an extent where LIP emplacement can represent a net source for one element and a net sink for another (Jones et al., 2016; Johansson et al., 2018).

1.2.2 Emissions of surface-derived substances via sediment intrusions, contact metamorphism and Earth system feedbacks

Large-scale eruptions of magma do not only release mantle material, but can also mobilize substances in dormant superficial reservoirs. For example, magma intruding and heating marine sediments changes the speed and nature of local chemical reactions, potentially resulting in the activation of dormant sedimentary reservoirs, e.g. of C (Ganino and Arndt, 2009; Jones et al., 2016). Additionally, environmental change caused by LIP emplacement has been suggested as a trigger for Earth system feedbacks involving the alteration of substance fluxes (e.g. release of thermogenic methane or nutrient supply from enhanced weathering, Svensen et al., 2004; Jenkyns, 2010). The LIP-related net substance fluxes and environmental forcing then depends on local lithology and the sensitivity of Earth system feedbacks. It has been argued that these processes accompanying LIP emplacement can have larger effects on the environment than the LIP emplacement itself (Ganino and Arndt, 2009). One main argument for this is that, while most LIPs coincided with major biotic crises (Ernst, 2014), there is no correlation between the scale of those crises and the amount of emplaced basalt (Ganino and Arndt, 2009).

1.3 Oceanic Anoxic Event 1a: window into OAE formation and metal cycle perturbation during LIP emplacements

The previous sections introduced OAEs as past examples of exogenic C and nutrient release events which resulted in unusually large sedimentary organic C burial and substantially altered marine biochemical cycles for up to millions of years. I stated that quantification of C emissions and sequestration during OAEs can improve our knowledge of the Earth system’s sensitivity to external C addition. Furthermore, I argued that a better understanding of the role of volcanism in their formation is required to determine whether OAEs were the Earth system’s response to igneous forcing or a negative feedback to sustained climate warming. Simultaneously, the previous discussion highlighted the challenges for studying C fluxes during OAEs, in particular the overlapping isotopic effects of C emissions and sequestration and the complex igneous forcing from LIP emplacements. Another difficulty is the age and scarcity of OAE sediments. OAEs have not occured since the Mesozoic, limiting the number of locations with non-diagenetically altered sediments and the resolution of isotope records. The scarce preservation of un-altered OAE sediments and increasingly limited quantitative constraints on the Earth system state further back in time mean that the youngest OAEs (the Mesozoic Toarcian OAE, OAE 1a and OAE 2) are the best studied OAEs. And while more sedimentary records are available for the Toarcian OAE and OAE 2 (Robinson et al., 2017), OAE 1a might be the Mesozoic OAE which provides the best opportunity to assess C fluxes in the face of mentioned challenges. C flux estimates based on the inversion of the δ13C record require a temporal offset between exogenic C emissions and enhanced organic C burial, which is

10 1.3. OCEANIC ANOXIC EVENT 1A: WINDOW INTO OAE FORMATION AND METAL CYCLE PERTURBATION DURING LIP EMPLACEMENTS suggested for the OAE 1a onset by an initial negative δ13C excursion that precedes wide-spread organic matter preservation. The use of metal isotope records for the reconstruction of exogenic C sources is also easier for OAE 1a than for other OAEs because the emplacement of the best studied ocean plateau in terms of basalt composition, the Ontong-Java Plateau (OJP) is suggested to be the dominant volcanic event of that time, providing constraints on the elemental and isotopic forcing from Earth’s mantle (Fitton and Godard, 2004; Svensen et al., 2019).

Black shale 13 δ C C2 C3 C4 C5 C6 C7

Cooling δ18O Warming

Δ13C

Nannoconid abundance Time

Figure 1.1: Schematic of the proxy behaviour during OAE 1a. δ13C and the definition of C-segments is based on Menegatti et al.(1998), δ18O is an approximation of data presented in Jenkyns(2018), ∆13C is based on Naafs et al.(2016a) and nannoconid abundance on Erba et al.(2010).

OAE 1a occurred about 121 Ma in the Early Aptian and has originally been identified as one of several transient periods of quasi-global increased organic matter preservation in marine sediments (Schlanger and Jenkyns, 1976; Olierook et al., 2019). OAE 1a stands out in the sediments of the Early Cretaceous because of the many indications of a severely perturbed oceanic system, including reducing conditions in sediments and a characteristic double C isotope excursion. Records of this event from all

11

CHAPTER 1. INTRODUCTION major ocean basins have been correlated using C isotope stratigraphy (see fig 1.1). The isotopic changes related to OAE 1a are characterized by a sudden negative δ13C excursion in C isotope stage C3, followed by a sustained positive excursion starting in C isotope stage C4. OAE 1a sediments contain indications of several transient Earth system changes, which are described in the following. See also Jenkyns(2010) and Erba et al.(2015) for extensive reviews.

1.3.1 The Early Aptian, the paleogeographic and -climatological context of OAE 1a

Figure 1.2: Reconstructed Early Aptian (120 Ma) geography and locations of sites with isotope records spanning OAE 1a (different symbols indicate different component of sediments analysed) and potentially active large igneous province emplacement (dashed circles, ’HALIP’ = High Arctic Large Igneous Province, ’OJMHP’ = Ontong-Java-Manihiki-Hikurangi Plateau). The elevation data was taken from Scotese(2018). Indicated carbonate records are from Erba et al.(1999); Jenkyns and Wilson(1999); Bellanca et al.(2002); Immenhauser et al.(2005); Luciani et al.(2006); Heldt et al.(2008); Michalík et al.(2008); Millán et al.(2009); Keller et al.(2011); Millán et al.(2011); Najarro et al.(2011b); Quijano et al.(2012); Lorenzen et al.(2013); Phelps et al.(2014) and records of sedimentary organic matter re from Menegatti et al.(1998); Takashima et al.(2004); Dumitrescu and Brassell(2006); van Breugel et al.(2007a); Millán et al.(2009); Najarro et al.(2011b); Stein et al.(2011, 2012); Quijano et al. (2012); Gaona-Narvaez et al.(2013); Pauly et al.(2013); Westermann et al.(2013); Schlak et al.(2016).

In this thesis, I use the term ’Early Aptian’ to refer to the beginning of the Aptian age in the Early Cretaceous. This term is not strictly delineated in time because there is substantial uncertainty over the age of the stratigraphic boundary between the Barremian and the Aptian (likely 123.8 – 121.8 Ma, Olierook et al., 2019). Instead, I use ’Early Aptian’ to discuss the environmental context of the onset of OAE 1a. There is an ongoing debate about the presence of polar ice sheets in the Early Cretaceous but

12 1.3. OCEANIC ANOXIC EVENT 1A: WINDOW INTO OAE FORMATION AND METAL CYCLE PERTURBATION DURING LIP EMPLACEMENTS

the Early Aptian was likely ice free (Jenkyns et al., 2012; Bodin et al., 2015). At the time of OAE 1a, long-term environmental change was likely dominated by plate tectonics and large igneous province eruptions (Haq, 2014; Patruno et al., 2015). Plate tectonics were dominated by continental break-ups rather than collisions, with Gondwana and Laurasia continuing to disintegrate (Svensen et al., 2018). Figure 1.2 shows that the North Atlantic was a medium-depth semi-detached ocean basin at that time, potentially comparable to the modern-day Mediterranean in terms of its water masses (Steinig et al., 2020), while the South Atlantic had just started to open, becoming the scene of large-scale evaporite deposition (Evans, 1978). Sea levels were higher than today by 50 – 200 m with fluctuations of up to 100 m over 1 – 2 Myr around the Barremian-Aptian boundary (Haq, 2014). Submersed continental ∼ shelves were locations of wide-spread carbonate production and preservation, while dysoxic episodes caused repeated local organic matter burial events in marginal seas (Stein et al., 2011; Fu et al., 2020). Pulsed volcanic eruptions of the High Arctic large igneous province, the Ontong-Java, Manihiki and Hikurangi plateaus and potentially also the Songliao Basin in modern-day China might have caused disruptions of ecosystems prior to OAE 1a, including changes to the Tethyan nannoconid assemblage and carbonate platform drowning at the North Tethyan margins (Erba et al., 2010; Huck et al., 2011; Najarro et al., 2011a; Patruno et al., 2015; Wang et al., 2016; Olierook et al., 2019).

1.3.2 Lithological expression

In pelagic sections, OAE 1a is associated with organic-rich shale production (Erba et al., 1999; Ando et al., 2008; Stein et al., 2011; Erba et al., 2015). Apart from a few Tethyian pelagic records which consist of black shale throughout the negative carbon isotopic excursion, and even before and after (Quijano et al., 2012), black shales appear towards the end of the negative carbon isotopic excursion, in segment C4 (Menegatti et al., 1998; Westermann et al., 2013). In the abundant neritic seas of the northern and southern Tethys the negative δ13C shift is marked by drowning-related hardground formations with lithological hiatusses and drastic changes in producer communities, respectively (Huck et al., 2010; Amodio and Weissert, 2017).

1.3.3 Temperature

Temperature proxy behaviour across OAE 1a has only been examined at a few sections which is not sufficient to reconstruct global climate changes. However, similar patterns at the studied sites can be used

to identify regional temperature changes, which are tentatively represented in figure 1.1. TEX86, pollen analysis and δ18O data at sections in the western Tethys and the central Pacific indicate that regional temperatures rose at the beginning of OAE 1a, shortly after the initial decline in δ13C(Menegatti et al., 1998; Bellanca et al., 2002; Keller et al., 2011; Kuhnt et al., 2011; Mutterlose et al., 2014; Bodin et al., 2015; Naafs and Pancost, 2016; O’Brien et al., 2017). The local amplitude of the initial warming has

been estimated to have been on the order of 3 – 6 ◦C(Mutterlose et al., 2014; Naafs and Pancost, 2016). The Tethyan Serre Chatieu section is the only one that offers indications of non-variant climate zones through the event, based on pollen of climate sensitive terrestrial vegetation (Heimhofer et al., 2004).

13 CHAPTER 1. INTRODUCTION

18 TEX86 data from the Pacific and the Southern Ocean and Tethyian δ O data suggest that the warming trend was interrupted by a short cooling episode of uncertain extent, before the return to pre-event temperatures in stages C5 or C6 (Jenkyns et al., 2012; Naafs and Pancost, 2016; Jenkyns, 2018). After OAE 1a, towards the end of the Aptian age, a well-documented cold spell occurred, with evidence of an active cryosphere (Bodin et al., 2015; Rodríguez-López et al., 2016; O’Brien et al., 2017).

1.3.4 CO2 concentrations

Reconstructions of CO2 concentrations across OAE 1a are sparse (Erba et al., 2015). Naafs et al.(2016a) published the most detailed reconstruction of CO2 changes across the OAE 1a interval yet, which, in accordance with reconstructions from the Tunisian Serdj Djerbel section, suggest a slow and moderate 13 CO2 increase of 1500 ppm and 1000 ppm, respectively, throughout the initial negative δ C excursion, starting from 3 – 4 pre-industrial CO2 concentrations and culminating at 10 pre-industrial CO2 × ∼ × concentrations in stage C4. Based on the δ13C record of the neritic Tethyan section Serre Chatieu stable 13 CO2 concentrations of 3 – 4 pre-industrial values were obtained for most of the positive δ C excursion × (Heimhofer et al., 2004). Using isotope mixing models to reconcile the initial isotopic shifts in δ13C 187 188 and Os/ Os at two pelagic sites, Bauer et al.(2017a) calculated much higher CO 2 changes across the onset of OAE 1a (increase of 3000 ppm). However, they assumed a linear relationship between hydrothermal CO2 outgassing and simultaneous Os emissions, which is poorly constrained, and that 13 the negative δ C excursion was driven entirely by addition of mantle-derived CO2. Assuming instead that the initial negative δ13C excursion was entirely driven by methane emissions with δ13C = -60%, mass balance calculations by Beerling et al.(2002) resulted in a much lower 600ppm CO 2 concentration increase at the onset of OAE 1a.

1.3.5 Biological impact

In Tethyian as well as boreal sections, significant variations in size and shape of planktonic carbonate shell producers have been discovered throughout the OAE 1a interval (Erba et al., 2010; Lübke and Mutterlose, 2016). The interval is also characterized by the Tethyan ‘nannoconid crisis’, the disappearance of nannoconid fossils during the negative carbon isotopic excursion at the onset of OAE 1a (Erba, 1994). Reef building communities on southern Tethyan carbonate platforms saw changes in ecosystem structure from phototrophic to heteotrophic rudist communities (Immenhauser et al., 2005). Most of these processes started before the onset of OAE 1a, but many culminated during the prominent carbon isotopic excursions (Erba et al., 2010; Huck et al., 2010; Malinverno et al., 2010; Huck et al., 2011; Erba et al., 2015). Typical membrane lipids of cyanobacteria are abundant in OAE 1a sections and were interpreted as cyanobacteria blooms across the event (Kuypers et al., 2004).

14 1.3. OCEANIC ANOXIC EVENT 1A: WINDOW INTO OAE FORMATION AND METAL CYCLE PERTURBATION DURING LIP EMPLACEMENTS

1.3.6 Marine oxygenation

The first indication for oxygen-poor bottom waters during OAE 1a was the widespread presence of strata with unusually high percentage of preserved organic matter in pelagic sediments (Schlanger and Jenkyns, 1976). Also, benthic foraminifera communities decreased in variability or disappeared altogether during the deposition of these black shales (Premoli Silva et al., 1999; Friedrich, 2010). However, while widespread anoxic conditions did not develop in shallow shelf areas of the Tethys (Westermann et al., 2013), the abundance of redox-sensitive trace metals increased in OAE 1a strata at several pelagic sites (see review in Jenkyns, 2010),

1.3.7 Euxinia

There is evidence for local photic zone euxinia during OAE 1a. Pancost et al.(2004) discovered bacteriochlorophyll degradation products in the Tethyan Gorgo a Cerbara section which suggest euxinic conditions in the photic zone. Likewise, the presence of pyrite framboids as well as specific biomarkers in OAE 1a black shales indicate euxinic conditions on the Russian platform (Bushnev, 2005; Zorina et al., 2017). Euxinic conditions are also suggested for parts of the OAE 1a interval at the Pacific Shatsky Rise (Dumitrescu and Brassell, 2006).

1.3.8 Weathering

Stein et al.(2012) interpreted the appearance of kaolinite at the Tethyan La Bédoule section before OAE 1a as an indication of increased terrestrial runoff and terrestrial weathering. Wortmann et al.(2004) interpreted the appearance of quartz sandstones during the negative carbon isotopic excursion at several locations in the Tethys as the result of increased terrestrial influx and weathering. Quantitative estimates of weathering flux changes have been made based on isotopic shifts in the OAE 1a record: Using a dynamical isotope mixing model to simultaneously reproduce the measured negative excursions in 87Sr/86Sr and δ44/40Ca, Blättler et al.(2011) calculated that basalt weathering rates might have tripled at the onset of OAE 1a. Following a similar approach but using Li isotopes instead of Ca, Lechler et al.(2015) concluded that a 2.5 fold increase in basalt weathering at the onset of the negative carbon isotopic excursion can explain the negative shifts in δ7Li and 87Sr/86Sr. Finally, a synthesis of δ34S and 87Sr/86Sr also resulted in an estimated three-fold increase of the terrestrial weathering flux (Mills et al., 2017b). While the quantitative approaches based on various isotope systems yielded very similar results, the assumed baseline weathering fluxes differ and are the result of tuning the isotopic composition of seawater to Early Aptian values under different assumptions. No study considered C cycle dynamics, elaborated whether the estimated weathering flux changes are consistent with records of warming or discussed uncertainties arising from assumed initial weathering fluxes.

15 CHAPTER 1. INTRODUCTION

1.3.9 Duration

One major obstacle in understanding the processes that led to, sustained and terminated OAE 1a is that a coherent age model is still missing. Existing time estimates for OAE 1a and different phases of its distinct carbon isotopic excursions were achieved via cyclostratigraphy from pelagic sections (Li et al., 2008; Malinverno et al., 2010; Hu et al., 2012) as well as carbonate shelf sections (Graziano and Raspini, 2018; Beil et al., 2020). The absolute ages of these strata remain difficult to establish, and several of these sections are condensed. Especially the speed of the δ13C decrease in the beginning of the event and its recovery varies widely between age models (see table 1.1).

Table 1.1: Segments of the carbon isotopic excursions associated with OAE 1a and their estimated durations. Underlying cyclostratigraphic studies are Li et al.(2008); Malinverno et al.(2010); Stein et al. (2011); Hu et al.(2012); Li et al.(2016); Graziano and Raspini(2018); Beil et al.(2020).

Segment Duration estimates (kyr) C3 27 – 560 C4 50 – 388 C5 220 – 570 C6 200 – 630 C7 900 – 1600

1.3.10 The role of volcanism in the formation of OAE 1a

A causal link between enhanced volcanism and Cretaceous environmental change, particularly transgres- sions, has since long been suggested - first in the form of enhanced ocean crust formation, followed by chemical changes in relation to unknown short-lived, tectonic events (e.g. Schlanger and Jenkyns, 1976). Enhanced volcanism was soon also indirectly regarded as a potential explanation of Cretaceous OAEs, through volcanically forced transgressions and the good correlation of Cretaceous OAEs and trangression periods (Arthur et al., 1987; Weissert, 1989). With the recognition of the stratigraphic and environmental importance of volcanic plateau formation, theories of direct volcanic drivers of OAEs were published

(e.g. CO2 emissions, nutrient-releasing weathering events, magmatic micro-nutrient pulses Kerr, 1998). In particular, emission of mantle-derived C during volcanic eruption was proposed as the cause of negative δ13C excursions in Cretaceous sediments (Grocke et al., 1999), though other C sources (e.g. methane clathrates) were later suggested (Beerling et al., 2002). A direct link between large volcanic events and OAEs was further suggested by the emerging temporal coincidence of several OAEs and Large Igneous Plateau (LIP) emplacements, although direct attribution of OAEs to LIP emplacements was still hampered by large uncertainties of age models of the OAEs and LIP emplacement phases and missing volcanic markers in OAE strata (Courtillot and Renne, 2003; Percival et al., 2015). Additionally, it remained unclear whether volcanic CO2 degassing could have been substantial enough to disrupt the global C cycle to the extent evidenced by proxy data of OAE strata (Caldeira et al., 1990; Self et al.,

16 1.4. SCOPE AND STRUCTURE OF THIS THESIS

2006). Evidence for a coincidence between phases of LIP emplacement and OAEs were eventually provided by the accumulation of unradiogenic metal isotopes in OAE strata, including OAE 1a and its initial negative δ13C excursion (Jones et al., 1994; Tejada et al., 2009). However, it is still debated whether volcanic emissions can account for the negative δ13C excursion, and if and how they are related to increased organic C burial.

1.3.11 Published C flux reconstructions for OAE 1a

The δ13C changes across OAE 1a, preserved in marine sediments and terrestrial organic matter (van Breugel et al., 2007a), suggest that the marine and atmospheric C reservoirs underwent external C addition and enhanced C sequestration. The scale of these changes has been estimated using recorded isotopic excursions during OAE 1a. The first estimate of exogenic C addition ( 0.6 Gt/yr for up to 5 ∼ Myr), was based on the unradiogenic Sr isotope excursion (Jones and Jenkyns, 2001). However, most C flux reconstructions used the initial negative δ13C excursion to estimate C inputs. Depending on the assumed dominant C source, C release rates over the OAE onset (100 kyr) were estimated to be between 0.003 Gt/yr (assuming biogenic methane emissions and Beerling et al., 2002) and 0.42 Gt/yr (assuming volcanic emissions Bauer et al., 2017a). The latter estimate is also consistent with the recorded radiogenic Os isotope excursion. The positive δ13C excursion, on the other side, was interpreted as the burial of 0.02 – 0.08 Gt C/yr over at least 500 kyr (Tsandev and Slomp, 2009). At the same time, the combined excursions of Sr, Ca and Li have been interpreted as a 0.2 Gt/yr strong sequestration of C due to enhanced continental weathering (Blättler et al., 2011; Lechler et al., 2015). Although these previous C flux estimates use diverse geochemical proxy data, none considered implications of C emissions and sequestrations on the evolution of metal isotope systems, or the consistency between weathering rate or hydrothermal emission changes derived from metal isotopes with reconstructions of the C cycle perturbation.

1.4 Scope and structure of this thesis

The aim of this thesis is to re-evaluate and quantify the role of volcanic activity and C cycle feedbacks during the early Aptian OAE 1a, using C and metal isotope records. This will contribute to ongoing scientific discussions about:

• The Earth system response to past C injection events;

• The nutrient sources for OAEs;

• The environmental impacts of OJP volcanism.

Chapter2 will provide an introduction to the intermediate-complexity Earth system model cGENIE and the different set-ups applied in this thesis. Chapters3–8 present my original pieces of research, some of which are published in, submitted to, or in preparation for submission to peer-reviewed scientific

17 CHAPTER 1. INTRODUCTION journals. A disclaimer before each chapter will clarify the state of publication. In chapter3, I assess the size and origin of exogenic C fluxes during the negative C isotope excursion of OAE 1a based on newly available reconstructions of pCO2 changes across that interval from Naafs et al.(2016a). I complement this approach with an in-depth analysis of the potential to reconstruct C fluxes during LIP volcanism with previously suggested metal isotope tracers of volcanism and climate change (Os, Sr, Li and Ca). For the latter, I add a new tracer system, Os, into the intermediate complexity Earth system model cGENIE which already contains isotope-enabled cycling of C, Ca, Sr and Li. After validating the model with observed present-day seawater composition in chapter4, I explore the isotopic fingerprint of simultaneous C and metal emissions in chapter5. I also investigate the implications of the observed association of sedimentary Os with organic matter for the use of Os isotopes as tracers of global environmental change during OAEs (chapter6). Lastly, I develop model set-ups which reproduce reconstructed Early Aptian seawater composition (chapter7) and explore implications for the interpretation of the Early Aptian C and metal isotope record in chapter8. A discussion of the findings in the context of my research aims will conclude the thesis.

18 idfils(eoiisadsrse)adpaeayabd.Fnt ieecsaeue oapproximate to used are differences Finite albedo. planetary and stresses) and (velocities fields wind computation increased of benefit the for complexity physical reduced of model ocean dynamic a is which hscatrdsrbsgnrlmtoooia hie neligm vrl praht h research the to approach overall my underlying choices methodological general describes chapter This e-c yais h oe swaeta ersnigwn-rvnoencruaino cl smaller scale on and circulation ocean ocean for wind-driven used representing one at the weakest from is differ model can The step dynamics. time sea-ice atmospheric and the ocean that the so component, asynchronous, atmospheric is the sea-ice between surface coupling 2D The ocean, equations. differential coastal in the derivatives to land a over bathymetry, ocean precipitated and freshwater mask re-rout land-sea to a map are run-off fields thickness terrestrial input sea-ice sea-ice, Required with temperature. covered cell surface grid sea-ice a and of area humidity, velocities, and ocean temperature 3D salinity, air temperature, 16 are ocean to variables up Prognostic layers. with ocean grid vertical horizontal stretched, equal-area logarithmically 36x36 adjustable an on operates 2005), C-GOLDSTEIN Marsh, efficiency. and (Edwards C-GOLDSTEIN from taken is Earth sea-ice) physical energy- dynamic the atmospheric balance, of mixing, moisture representation diffusive and and Its circulation atmosphere. ocean 2D hydrostatic a geostrophic, marine (frictional and of system ocean range 3D a a simulates model) in system cycles Earth biogeochemical Integrated ENabled Grid carbon-centric (the cGENIE model cGENIE The 2.1 8). – 3 (chapters chapter be research as will each isotopes of designs Ca beginning experimental and the and Li at Os, methodologies described Sr, Chapter-specific of perturbations. use cycle the C into provides for investigation chapter my proxies chapter this of Besides, this outline thesis. experimental in my and detail the throughout rationale of used in a set-ups use described different the is of on overview which predominantly an cGENIE, relies alongside model work system My Earth introduction. complexity the of intermediate end the at presented questions 19

Methods C h a p t e r 2 CHAPTER 2. METHODS than 10,000 km, but it reproduces surface ocean gyres and large-scale thermohaline circulations with similar skill as CMIP models with more complex physics (Edwards and Marsh, 2005).

C-GOLDSTEIN was extended by several modules to enable the simulation of biogeochemical cycles on seasonal - geological time scales, resulting in cGENIE. The BIOGEM (marine biogeochemistry) and ATCHEM (atmospheric chemistry) modules form the core of the biogeochemical component (Ridgwell et al., 2007) and, alongside the sediment dynamics module SEDGEM (Ridgwell and Hargreaves, 2007), are based on the SUE model of marine biogeochemistry and air-sea gas exchange (Ridgwell, 2001), which simulates vertical and horizontal distribution of C, O, P, S, N, Si, Ca and Fe in the ocean through the solubility, soft tissue, carbonate and microbial pumps. Dependent on temperature, wind fields, sea-ice coverage, surface water density and the concentration gradient, gasses are exchanged at the air-sea interface, and dissolved into the surface ocean water. Particulate elements enter the ocean via prescribed continental run-off or dust fluxes. Dissolved inorganic C (DIC) speciation is determined 2 2 based on local pH, while local abundances of CO3− and Ca + set the carbonate saturation. Biology is simulated implicitly, though elemental fluxes representing biological processes. Conversion of dissolved inorganic C and P into organic matter under O2 production in the surface ocean is parameterized based on Michaelis-Menten-type kinetic limitation with a prescribed upper limit for nutrient uptake, and is a function of nutrient and DIC availability, sea-ice cover, latitudinal and seasonal insolation and, optionally, on temperature. The relative uptake of dissolved elements during primary production follows the Redfield ratio (Redfield, 1963) and Anderson and Sarmiento(1994). A fixed portion of this organic matter is transported by the physical ocean model as dissolved organic C and P (DOC and DOP) and is remineralized at a prescribed rate. The remainder sinks through the water column as particulate C and P (POC and POP) and decays with depth at a constant rate or following an empirical remineralization function. Organic matter reaching the seafloor is remineralized at the sediment-water interface. Wherever 2 organic matter is remineralized, C and P are released and O2,N2O or SO4− is consumed, affecting local alkalinity, pH and redox conditions. Where carbonate saturation is 1, CaCO3 is produced in > the surface ocean at a ratio to POC and POP that follows a quadratic function and has been tuned to reproduce modern-day seafloor CaCO3 accumulation (Ridgwell and Hargreaves, 2007). Like particulate organic matter, it sinks through the water column, dissolving according to a prescribed decay function. Otherwise, it is added to the surface sediments. The parameterization of sediment dynamics in SEDGEM accounts for different depositional environments which are prescribed through an input field. Pelagic sediments are represented by a dynamic stack of sediment layers, which store CaCO3 fallen to the seafloor and grow or decrease depending on the balance of CaCO3 accumulation and dissolution in its surface layer. Neritic sediments, on the contrary, are not layered but CaCO3 can grow in-situ, depending on the local carbonate saturation. Finally, grid cells marked as ’muds’ do not accumulate CaCO3. In all environments, a prescribed, constant addition of detrital material occurs every time step to simulate the sediment components other than CaCO3. SEDGEM can run at a different spatial resolution than the ocean modules. In that case, an interface scales fluxes between ocean and sediments according to the resolution difference to assure mass preservation. BIOGEM uses the same resolution as the physical

20 2.1. THE CGENIE MODEL ocean modules. However, it is asynchronously coupled to the ocean physics, meaning that the time stepping of biogeochemical processes can be different to that of the ocean physics. Throughout the biogeochemical pathways, the model can track the abundances of the C isotopes 13C and 14C. If the isotope tracers are switched on, prescribed C input fluxes need to be assigned a δ13C signature, which the model translates into absolute abundances and than returns again as δ13C values in the model output. Tracing each isotope individually makes it possible to use the same transport functions as for other conservative tracers. Isotopic fractionation occurs during air-sea gas exchange, speciation changes of

DIC, biological primary production of organic matter and CaCO3 formation. The fractionation factors are temperature-sensitive and are calculated locally. The model is capable of successfully reconstructing the present-day distribution of PO4 except for overestimations in areas with wind-driven upwelling (Ridgwell et al., 2007), and DIC δ13C(Holden et al., 2013).

Colbourn et al.(2013) added ROKGEM, a module to calculate climate-sensitive weathering of terrestrial silicates and carbonates. ROKGEM requires the provision of a terrestrial elevation map, and optionally a map of terrestrial lithologies. Based on the land topography, ROKGEM calculates the size and outflow direction of drainage basins and, if a map of lithology is given, its mineralogy. Furthermore, this module alters the prescribed weathering fluxes according to environmental conditions which can be chosen by the model user: air temperature, CO2 concentration and/or run-off. Dynamic pelagic sediments and climate-sensitive terrestrial weathering take substantially longer to equilibrate to a given climatic condition than marine biogeochemistry (Lord et al., 2016). In order to improve the model efficiency when simulating processes with such divers time scales, Lord et al.(2016) added the module GEMLITE with which the calculation of continental run-off and sediment dynamics can be periodically decoupled from the other modules. In the coupled phase, all model components interact, while marine output to the sediments is kept constant during de-coupled periods, so that biogeochemical and physical ocean dynamics do not need to be calculated at each time step. Recently, project-specific isotope enabled cycles of Sr and Li, as well as Ca isotope tracers, have been added to BIOGEM, SEDGEM and ROKGEM but have not been described or validated consistently. As part of the work for this thesis, I evaluated the implemented cycles and tuned the free parameters to match the present-day composition of dissolved Sr, Li and Ca in seawater (see chapter4 for more information). Furthermore, I added, evaluated and tuned parameterizations for isotope-enabled cycling of Os which also described in chapter4.

The described modules can be added or omitted in the compilation of cGENIE. Its modular structure, together with the reduced spatial resolution and physical complexity, the asynchronous coupling of the modules and the accelerated time-stepping method provided by GEMLITE make cGENIE a very efficient fully coupled Earth system model for ensemble experiments and simulations of long time scales. It is flexible in its application to geographies, climates and biogeochemical conditions different to the present-day and has been employed to simulate C cycle dynamics throughout geologic time (Hülse et al., 2017). The range of dynamic biogeochemical cycles and Earth system processes simulated by cGENIE and its efficiency and flexibility make it the right tool to investigate my research questions. In particular, I employed cGENIE for three main purposes (not in order of presentation in this thesis):

21 CHAPTER 2. METHODS

Firstly, I used the model to experimentally constrain the sizes and isotopic composition of metal fluxes in the present-day system so that cGENIE simulates marine metal reservoirs that are consistent with observations of their present-day composition and size (chapters4 and6). Secondly, I used cGENIE to explore the behaviour of the previously set-up metal cycles under various boundary conditions and forcings in order to understand dynamic relationships between the isotopic composition of dissolved metals and other biogeochemical cycles, in particular C and O2 (chapters5,6 and7). Finally, I made use of the flexible boundary conditions to produce specific set-ups representative of the Early Aptian Earth system state and OAE 1a (chapters3,7 and8). These purposes require different configuration choices, which are described in the following sections and at the beginning of each chapter for which a particular set-up was employed.

2.2 cGENIE set-ups

In this thesis, I used two previously published cGENIE set-ups to simulate the pre-industrial Earth system state to evaluate and tune metal cycle parameterizations and to explore their interactions with the C cycle. I also developed new set-ups for simulations of the Aptian period to run simulations with specific focus on OAE 1a. In the following subsections, I describe the boundary conditions for each of these set-ups. Further information and evaluations of the spin-ups are also provided and discussed as part of chapters3,4 and7.

2.2.1 Pre-Industrial

I used two pre-industrial set-ups of cGENIE for validation experiments for the existing and newly added metal isotope systems based on previously published C cycle solutions: the one used by Archer et al. (2009) and the one used by Ridgwell and Hargreaves(2007). Specific physical parameters and input fields are described in detail and compared to higher resolution models in Marsh et al.(2011) and Marsh et al.(2009), respectively. The main difference between the two physical set-ups is the different vertical resolution of the ocean grid, 16 versus 8 layers, which requires different bathymetries and diffusivities to achieve similar physical transport. The different vertical resolutions also have implications for the set-ups of biogeochemical cycles: The increased vertical resolution in the first set-up is more accurate at simulating processes in the photic zone, which is only one grid cell layer thick in the lower resolution set-up, and remineralization profiles. This is particularly relevant for simulated fields of O2, nutrients and organic matter. The lower resolution of the second set-up, however, is faster to compute which is essential for the equilibration of isotope systems with dynamic sediments and climate-sensitive continental weathering. Hence, I employ the first set-up to study redox-sensitive marine sinks of Os in equilibrium climates (chapter6), while I use the latter to simulate metal isotope dynamics with long equilibration times (chapters4 and5).

22 2.2. CGENIE SET-UPS

2.2.2 Aptian

Prior to the first publication of my PhD project, a published cGENIE set-up for the Aptian did not exist. A physical set-up for the Aptian, however, had already been prepared for an unpublished study by my supervisor Fanny Monteiro (personal communications). For the Aptian simulations in this thesis, I used this physical set-up but I had to produce set-ups for the Aptian C and metal cycles which cater for the specific requirements of my experiments, in particular by involving climate-sensitive continental rock weathering and marine sediment dynamics. In the following, I investigate the unpublished physical set-up of Monteiro and describe my approach to simulating Aptian biogeochemical cycles.

2.2.2.1 Physical boundary conditions

To produce a physical state of the Early Aptian, I used input fields derived from the palaeotopography and -bathymetry as well as atmospheric and ocean circulations of simulations with the more highly-resolved GCM FOAM (Donnadieu et al., 2006b). While pre-industrial input fields, climate and biogeochemical cycles are well constrained, they are uncertain for the Aptian. Thus, rather than simply applying input fields from (Donnadieu et al., 2006b), the effect of their application on biogeochemical cycling in cGENIE and the consistency of the resulting simulated climate with proxy-data and other modelling studies needs to be tested. In order to assess the implications of Early Aptian physical boundary conditions and their uncertainty on the simulation results, I show here sensitivity experiments where I implemented the Aptian boundary

conditions step-wise to observe the changes in the simulated surface temperature and atmospheric CO2 concentration. I started from the modern-day set-up of Ridgwell and Hargreaves(2007) altered the simulation set-up step-wise until simulating the full Early Aptian configuration (see table 2.1). At each step, I ran a 20 kyr-long simulation of an interactive climate and atmospheric and marine C-cycles with closed carbonate system (i.e. weathering input is not driven by climate, but artificially restores the

marine Ca reservoir after carbonate burial). All simulations were run from initial pre-industrial CO2 1 concentrations (278 ppm) and with an effective CO2 outgassing rate of 6 Tmol yr− .

Table 2.1: Step-wise alteration of physical boundary conditions to achieve an Early Aptian spin-up.

Steps Varied conditions 1 Aptian topography and bathymetry Changed ocean diffusivity to 2 account for sub-grid changes in ocean circulation 3 Re-gridded surface wind fields 4 Reduced solar constant 5 Reduced salinity 6 Adapted planetary albedo 7 Increased air-sea gas exchange

23 CHAPTER 2. METHODS

Figure 2.1: Changes in atmospheric CO2 concentration and land-surface temperature under the stage change application of physical Aptian boundary conditions (see table 2.1). Arrows indicate the effect of adding an additional boundary condition change to the previous set-up. The respective additional boundary condition change is written in black text next to the arrow. The complete pre-industrial and Aptian set-ups are annotated with blue writing.

Figure 2.1 shows the simulated relationship of atmospheric CO2 and land surface temperature at different steps of the transition from pre-industrial to Aptian physical boundary conditions (table 2.1). At each step, an additional boundary condition, annotated next to the respective arrow, is added to the previous set-up. Atmospheric CO2 concentration and land-surface temperatures change relatively independently because climate-sensitive weathering, an important temperature-related negative feedback on CO2 concentration changes, is not considered in these simulations. The largest land-surface temperature change results from applying a planetary albedo and radiation adjustment based on (Donnadieu et al.,

2006b). The biggest CO2 concentration change is caused by the correction of the air-sea gas exchange coefficient. This correction is required because by default, cGENIE calculates the piston velocity of

CO2 based on the empiric equations by Wanninkhof(1992), which assume modern-day long-term average wind-speeds. Overall, the changed physical boundary conditions result in a 5 ◦C higher average ∼ land-surface temperature and a 45 ppm decrease in atmospheric CO2 concentration. This temperature ∼ range is comparable to the thermodynamic effect of introducing Cenomanian (late Cretaceous) land surface, palaeogeography and solar constant found by Laugié et al.(2020) with a more physically complex GCM.

24 2.2. CGENIE SET-UPS

a) Pohl et al. 2020 b) this study c) Farnsworth et al. 2019

d) Land, ocean and global mean surface temperatures

Figure 2.2: Comparison of simulated Aptian surface temperatures in studies with FOAM (Pohl et al., 2020), HadCM3L (Farnsworth et al., 2019) and cGENIE (this study). Shown are the spatial pattern of surface temperatures in the three models under 1120 ppm atmospheric CO2 concentrations and minimum TEX86 temperatures (Steinig et al., 2020, , upper row) and below average temperatures for ocean, land, non-polar land (-60 – 60◦N) and the globe under different CO2 concentrations.

Figure 2.1 shows that the average land-surface temperature is significantly larger in the Aptian configuration due to a lower planetary albedo, while decreased C uptake by the ocean leads to higher atmospheric CO2 concentrations. While Aptian planetary albedo and air-sea gas exchange dominate the impacts of physical boundary condition changes on the C-cycle, their Aptian values are poorly constrained. In fact, the applied albedo correction results predominantly from changed cloud characteristics, removal of ice sheets and the assumption of an omnipresent deciduous forest in the GCM simulation from which my simulation set-up is derived (Donnadieu et al., 2006b). Apart from low ice coverage, these changes are dependent on model resolution and parameterization. More recent GCM simulations of the Early Aptian, one with an improved version of FOAM (Pohl et al., 2020) and one with the higher-resolution HadCM3L (Farnsworth et al., 2019) yield slightly lower global mean surface temperatures than my cGENIE set-up

(fig. 2.2). Average land temperatures are lower by several degrees in these simulations (-5◦C and -2◦C for Pohl et al.(2020) and Farnsworth et al.(2019), respectively) because of colder polar continents than in my set-up. The average temperature of non-polar land, arguably more relevant for global weathering fluxes because of higher temperatures and run-off, in my set-up with an atmospheric CO2 concentration of 1120

25 CHAPTER 2. METHODS ppm are similar to those simulated by Farnsworth et al.(2019). The main reason for the difference in polar temperatures is a more positive polar energy balance in my set-up because radiation parameters were tuned to the warmer Maastrichtian simulation of (Donnadieu et al., 2006b) rather than the Aptian one. Differences in palaeogeography, in particular the assumed southward extent of Antarctica and the cut-off Arctic sea, might add to this discrepancy. However, currently available sea surface temperature proxy data is not sufficient to rule out any of the simulated temperature distributions. While palaeobotanical and geological records indicate that the polar regions were likely ice free in periods of the Cretaceous with [CO2] 1000 ppm, which climate models fail to reproduce (Chumakov et al., 1995; Hay and > Floegel, 2012; Hay et al., 2019), these records are sparse and reconstructions of palaeotopography and -seasonality are uncertain. In the context of uncertain Early Aptian land surface temperatures, my set-up results in an upper-limit continental warming scenario which is consistent with ice-free polar land. The weathering fluxes simulated with my comparatively high Aptian surface temperatures will be higher than they would be in other models, yet within uncertainty of our limited understanding of the Early Aptian climate. The climate sensitivity in my set-up is in-between those simulated by Pohl et al.(2020) and Farnsworth et al.(2019).

2.2.2.2 Biogeochemical cycles representative of the Aptian

The previous discussion suggested that the physical set-up choices affect the weathering environment on land, air-sea gas exchange and carbonate burial and hence the cycling of C and metals at Earth’s surface. However, choices about the strength of sources and sinks of biogeochemical cycles in the Aptian are equally as relevant. For my first Aptian experiments (chapter3), my choices about C sinks and sources are primarily motivated by constraints on Aptian atmospheric CO2 concentration and marine carbonate chemistry. In particular, I tuned volcanic CO2 outgassing, terrestrial weathering rates and carbonate saturation state to achieve reconstructed levels of surface ocean export and a proxy-consistent atmospheric CO2 concentration (a more detailed description is part of my published manuscript, included in this thesis as chapter3). The introduction of metal isotopes in chapters4–8 adds more direct constraints on geological C and metal sources and sinks because their seawater values are sensitive to the relative strength of sedimentary versus igneous C sources and sinks. This enables a more systematic, process based construction of the Early Aptian C cycle. Thus, rather than tuning the lithological C cycle to indirect constraints on surface ocean export which also depends on marine biogeochemistry and ecosystems, I use tectonic reconstructions and the isotopic composition of dissolved metals in Aptian seawater to constrain C and Ca fluxes between the lithosphere and the atmosphere-ocean system. In this way, I also improve the representation of Early Aptian metal cycles relative to previously published work (e.g. Blättler et al., 2011; Lechler et al., 2015) because, while these studies provide proxy-consistent solutions for some Aptian metal cycles, they were not conceived with the C or other biocheochemical cycles in mind, and thus are not always compatible with reconstructions of the Aptian C cycle or other metal cycles (see discussion in chapter7). However, the Aptian state of most biogeochemical cycles is under-constrained because existing uncertainty and gaps in proxy data of Aptian seawater composition

26 2.3. C FLUX INVERSIONS IN CGENIE allow for non-unique solutions. Instead of choosing one biogeochemical set-up that is consistent with the available proxy data, I therefore systematically explored a range of such proxy-consistent set-ups in chapter7. This approach provides an improved understanding of the certainty of Aptian C and metal cycle simulations with direct implications for quantitative studies of recorded isotope excursions which I will discuss in chapter8.

2.3 C flux inversions in cGENIE

Another benefit of using cGENIE is that the model has previously been used for C flux inversions to study geological C cycle perturbations. cGENIE was first used for ’single inversions’, which deduce C fluxes from a recorded δ13C excursion based on an assumed composition of the C influx (Cui et al., 2011, 2013; Kirtland Turner and Ridgwell, 2013; Vervoort et al., 2019). This approach was further developed into a ’double inversion’ by constraining simulated C fluxes by records of two proxies (pH reconstructions based on δ11B and δ13C of the surface ocean, Gutjahr et al., 2017). In chapter3, I used 13 a newly implemented, similar double inversion constrained by reconstructed atmospheric δ C and CO2 concentration. The C flux inversion functions are located in the BIOGEM module and require input of a DIC or atmospheric δ13C record and a prescribed δ13C signature of exogenic C input (single inversion) or a marine pH or atmospheric CO2 concentration record (double inversion). In the case of a single inversion, the globally averaged simulated DIC or atmospheric δ13C signature is compared to the provided record 13 at the start of each BIOGEM timestep and DIC or CO2 with prescribed δ C is added to or removed from the ocean or atmosphere to such an extent that simulated and recorded δ13C values match. In the case of a double inversion, the model determines first the mass of C that needs to be injected in order to 13 comply with the provided atmospheric CO2 or ocean pH record, and establishes then the δ C signature of that C flux required to match the provided δ13C record. In both cases, the model outputs the mass of injected C and its isotopic composition. Applied to observed and reconstructed atmospheric CO2 concentration and δ13C changes over 1765 – 2010 (Meinshausen et al., 2011), this double inversion results in cumulative emissions of 379 Pg C with average δ13C = -18% which is consistent with the

CO2 emissions from fossil fuel burning (375 30 Pg C between 1750 – 2011, Ciais et al., 2014). ±

2.4 Interpreting Sr, Os, Li and Ca isotope excursions as indicators of C cycle perturbations

My work with Sr, Os, Li and Ca isotopes started with reviewing and evaluating the existing, unpublished isotope-enabled cycles of Sr, Li and Ca in cGENIE, and implementing isotope-enabled cycling of Os (see chapter4). To my knowledge, this is the first dynamical coupling of all four isotope-enabled metal cycles with the C cycle in a 3D fully-coupled Earth system model, which provides new opportunities to investigate their transient behaviour under changing boundary conditions and external forcings. One

27 CHAPTER 2. METHODS significant unknown in the quantitative interpretation of geological metal isotope excursions is the initial marine abundance of a metal. Sr and Ca abundances varied substantially throughout the Phanerozoic (see review in Turchyn and DePaolo, 2019), but the variability of Os and Li abundances over time are largely unknown. While it has already been suggested that a present-day abundance of marine Li is incompatible with Li isotope excursions observed during OAEs (Von Strandmann et al., 2013), in the absence of observational constraints it is commonly assumed that Os was as prevalent in past oceans as it is today (Turgeon and Creaser, 2008; Tejada et al., 2009; Bauer et al., 2017a), despite a potentially significant redox-sensitive sink (Lu et al., 2017). The implementation of a dynamic Os cycle in cGENIE makes it possible, for the first time, to test implications of such a redox-sensitive Os sink for the distribution of dissolved Os in the present-day ocean and under different biogeochemical conditions. This exploration is done in chapter6, using compilations of measured vertical abundance profiles of dissolved Os in the present-day ocean and the reconstructed isotopic homogeneity of Os at selected times in the past, including OAEs. With the resulting knowledge, I discuss the implications of a reduced oxygenation of the Aptian ocean on the marine residence time, and hence the reactivity of the marine Os isotope system to external perturbations. A second advantage of the Sr, Os, Li and Ca tracers in cGENIE is that the continental metal supply is climate-sensitive. Interpretations of metal isotope excursions with isotope mixing models are commonly derived by varying one metal flux at a time (e.g. Tejada et al., 2009; Blättler et al., 2011; Von Strandmann et al., 2013; Bauer et al., 2017a), assuming that metal input fluxes are independent of each other. In the case of igneous events, this assumption is only valid if climate changes are minimal or the weathering regime does not change with climate. For OAEs, however, environmental proxies suggest both, climate change and weathering changes (see review in the introduction). In chapter5, I use the extended model to examine potential impacts of sustained C emissions on dynamic Sr, Os, Ca, Li and C cycles. With an ensemble of different igneous emission scenarios I test how C emission duration and emission rate affect the drivers of isotopic change in seawater. These effects are modulated by the initial state of metal and C fluxes and reservoirs. In order to apply the gained knowledge to OAE 1a, I set up a separate simulation ensemble with varying boundary conditions and explore which combination of boundary condition changes relative to pre-industrial metal and C cycles produces a seawater composition representative of the Aptian background state (chapter 7). Finally, I discuss published metal isotope records and their ability to constrain the OAE 1a C cycle perturbation in the context of the findings from the previous chapters and simulations of the isotopic effect of the weathering response to reconstructed CO2 concentration changes across OAE 1a (chapter8).

28 uhrcnrbtosaddeclaration: and contributions Author l rvosynmdclaoaoscnrbtdt h nlmnsrp et h td a ocie by conceived was study The text. manuscript final the to contributed collaborators named previously All aa .Gen,FnyM otioadB ai .Naafs. A. David B. and Monteiro M. Fanny A . Greene, E. Appendix Sarah in inventory nutrient marine Fanny Aptian Jímenez. Early Castro the Manuel of José reconstruction by Preston the provided Will were performed and which Monteiro Parkinson samples J. M. from Ian Andy data draft. and isotope manuscript Lunt Os the Dan the wrote Naafs, produced and A. figures David the B. produced the Greene, also performed E. I and Sarah Ridgwell. simulations Monteiro, the M. ran Fanny and from designed advice I with analysis 2020). , al. et (Adloff Letters Science Planetary CO negative initial the during medn notethesis: the into Embedding 2 (2016a). al. et Naafs by reconstructed changes concentration naeln h ore fcro msin tteostof onset the at emissions carbon of sources the Unravelling δ 13 hscatrpeet eosrcino xgncCflxsadsources and fluxes C exogenic of reconstruction a presents chapter This xuso fOE1 ae nteCiooercr n atmospheric and record isotope C the on based 1a OAE of excursion C hscatri ulse sa ril ntejunlErhand Earth journal the in article an as published is chapter This 29 cai nxcEet(A)1a (OAE) Event Anoxic Oceanic

C h a p t e r 3 CHAPTER 3. UNRAVELLING THE SOURCES OF CARBON EMISSIONS AT THE ONSET OF OCEANIC ANOXIC EVENT (OAE) 1A

Abstract

The early Aptian Oceanic Anoxic Event (OAE) 1a represents a major perturbation of the Earth’s climate system and in particular the carbon cycle, as evidenced by widespread preservation of organic matter in marine settings and a characteristic negative carbon isotopic excursion (CIE) at its onset, followed by a broad positive CIE. The contemporaneous emplacement of a large igneous province (LIP) is invoked as a trigger for OAE 1a (and OAEs in general), but this link and the ultimate source of the carbon perturbation at the onset of OAEs is still debated. In this study, we simultaneously assimilate an atmospheric pCO2 reconstruction along with a δ13C record from the Spanish Cau section in an Earth system model to obtain a novel transient reconstruction of emission rates and identify the primary carbon-emitting sources across the negative CIE interval at the onset of OAE 1a. We reconstruct carbon emissions of 4,300 - 29,200 Pg from a mixture of carbon sources. This estimate is a lower bound, as contemporaneous organic carbon burial is not accounted for. Carbon was first released at slow rates from a 13C-depleted reservoir (e.g. thermo- and/or biogenic methane from sill intrusions). Towards the end of the negative CIE the rate of emissions increased and they became more 13C-enriched, likely from a dominantly volcanic source (e.g. LIPs). New osmium isotope (187Os/188Os) measurements, from the same section as the 13 pCO2 reconstruction and δ C data, reveal a shift to less radiogenic values coinciding with the change towards mantle-derived carbon emissions as indicated by our modelling results, lending further support to our interpretation. These results highlight that geologically triggered carbon emissions were likely driving the OAE onset.

3.1 Introduction

The early Aptian Oceanic Anoxic Event (OAE) 1a ( 121 Ma, Olierook et al., 2019) represents one ∼ of the largest perturbations of the climate system during the last 200 Myr (Jenkyns, 2010). Although OAEs, including OAE 1a, were first identified in the 1970s (Schlanger and Jenkyns, 1976), it is still unclear exactly how the oceanic system evolved into such an extreme state. Increasing nutrient supply to the photic zone and, to a lesser extent, climate warming may have played a crucial role (Larson and Erba, 1999; Jenkyns, 2010; Monteiro et al., 2012), driving increased productivity and subsurface oxygen demand, and reduced oxygen solubility, respectively. The resulting reduced oceanic oxygen concentrations would have led to enhanced preservation and burial of organic matter (Jenkyns, 2010; Monteiro et al., 2012). However, the driver of this warming and increased nutrient delivery is debated. While all OAEs are associated with a positive carbon isotopic excursion (CIE), interpreted as reflecting an interval of enhanced burial of organic matter, the onset of OAE 1a is characterized by a distinct negative CIE prior to the positive CIE (Menegatti et al., 1998). Because of the broad temporal coincidence of OAE 1a with the emplacement of the Ontong-Java Plateau, the negative CIE could have resulted from carbon input from (submarine) volcanism initiating the OAE by warming the climate and releasing nutrients to the ocean (e.g. Weissert, 1989). A phase of increased volcanism during the onset of OAE 1a (and other OAEs) is further highlighted by the observed perturbations of the marine osmium

30 3.1. INTRODUCTION cycle (Tejada et al., 2009; Bottini et al., 2012). However, it is not certain whether volcanic emissions could have caused the negative CIE, so destabilization of methane hydrates has been proposed as an alternative, more 13C-depleted carbon source (Beerling et al., 2002; van Breugel et al., 2007b; Méhay et al., 2009; Malinverno et al., 2010). Constraining the carbon source for OAE 1a is crucial as it has implications for the mass and rate of carbon emissions and hence extent of the perturbation estimated from the carbon isotope record. The size of a negative CIE is a function of the mass of emitted carbon and its isotopic composition (e.g.

Kirtland-Turner and Ridgwell, 2016), a predominantly volcanic carbon source (CO2), relatively enriched in 13C compared to organic carbon sources, requires massive carbon emissions to match the negative

CIE, resulting in high atmospheric CO2 concentrations (e.g. 3000 ppm pCO2 increase (Bauer et al.,

2017b)). In contrast, the estimated emissions, and hence CO2 concentrations, are much lower if the carbon originated predominantly from more 13C-depleted sources (e.g. 600 ppm for methane emissions (Beerling et al., 2002)). The nature of the dominant carbon source is important to determine the role of Earth system feedbacks in triggering OAE formation in the Aptian and its sensitivity to carbon injections. For instance, predominant volcanic CO2 emissions suggest OAE formation was primarily a response to external forcing while a dominant biogenic methane source would indicate a major role for feedbacks between surface carbon reservoirs and an increased sensitivity to carbon emissions. This could have broader implications for our understanding of the formation of other Mesozoic OAEs since negative CIEs are also known from OAE 1b and the Toarcian OAE, and the presence of a suppressed negative CIE before OAE 2 is discussed (Jenkyns, 2010).

Recently, a continuous pCO2 proxy record across OAE 1a (Naafs et al., 2016b) together with a 13 δ Ccarb record from the same site provides an opportunity to identify the carbon source and quantify 13 emissions rates across OAE 1a. The pCO2 record, based on compound-specific and bulk δ Ccarb from the hemipelagic Tethyan Cau section, shows a gradual pCO2 increase during the negative CIE starting around 800-1000 ppm and reaching maximum values of 2000 1200 ppm before the recovery of the ± negative CIE. This estimate is within the range of previously reconstructed pCO2 values during the

Early Cretaceous of 200-2000 ppm (see Wang et al., 2014, for a compilation) and is between pCO2 values predicted for a pure methane and a purely volcanic source. At the same time as the pCO2 increase, organic proxies indicate a 2-5 ◦C increase in local sea-surface temperature (SST) during the negative CIE (Mutterlose et al., 2014; Naafs and Pancost, 2016). Global temperature changes of this magnitude are consistent with a doubling to quadrupling of pCO2, depending on assumptions about the initial pCO2 and the climate sensitivity of the Early Cretaceous. At the same time, biological turn-over and carbonate platform drowning, key features of OAE 1a, have been interpreted as being the results of surface ocean acidification due to increased pCO2 (Wissler et al., 2003; Erba et al., 2010). However, it is debated whether the relative timing, the amount, and the rate of emitted carbon explain the observed changes (Gibbs et al., 2011; Naafs et al., 2016b).

In this study, we assimilate the observed negative CIE and reconstructed pCO2 changes from the

31 CHAPTER 3. UNRAVELLING THE SOURCES OF CARBON EMISSIONS AT THE ONSET OF OCEANIC ANOXIC EVENT (OAE) 1A

Cau section in the Earth system model cGENIE (Ridgwell et al., 2007) to constrain carbon emissions across the onset of OAE 1a and to understand their implications for the dominant carbon sources. We also assess the effect of the pCO2 changes on Earth’s climate, as well as quantifying the implications of uncertainties in pCO2 change estimates and duration of the OAE onset for reconstructing the carbon cycle perturbation. Finally, we compare our simulation results to a newly-generated osmium isotope record from the same section, which allows us to reconsider the relationship between the negative CIE and environmental perturbations at the onset of OAE 1a.

3.2 Methods

3.2.1 The Cau section

The studied succession belongs to the Almadich Formation, made of a cyclic succession of hemipelagic marls and marsltones of late Barremian- Aptian p.p. age (Aguado et al., 1999; Castro et al., 2008). The interval considered in this study is located in the upper part of the lower member of the Almadich Formation, of Early Aptian age (Desayesites forbesi ammonite zone, B. blowi planktonic foraminifera, see Naafs et al., 2016b). The lithologies present are dominant grey marls (beds 0.5 – 2.5 m thick) alternating with marly limestones (beds 0.3 – 0.6 m thick), with two levels of dark marls (ca. 0.4 m thick) containing small pyrite nodules. The samples used for Os analyses were taken from the marly limestone levels, that have a CaCO3 content between 36 and 70% wt and TOC contents ranging from 0.7 to 2.4% wt. We assume stratigraphic continuity and a constant sedimentation rate as there is no < sedimentological evidence for interruption of sedimenation (hard/soft-ground or erosive surfaces). Also biostratigraphy and nannofossils associations are consistent with a continuous record, at the scale of the resolution available (Aguado et al., 1999; Naafs et al., 2016b).

3.2.2 Model setup and experiment design cGENIE is the carbon cycle centric version of the Grid ENabled Integrated Earth system model (GENIE), which couples a 3D ocean with a 2D zonally-averaged atmosphere (Edwards and Marsh, 2005), accounting for the biogeochemical cycles of carbon, phosphorus, sulphur, oxygen and stable carbon isotopes (Ridgwell et al., 2007). cGENIE can be run with a vertically-integrated sediment module which builds up deep sea sediments with varying CaCO3 content and carbon isotopic composition, resolving for CaCO3 burial and dissolution (Ridgwell and Hargreaves, 2007) and with a terrestrial weathering module (Colbourn et al., 2013) hence closing the geological carbon cycle. Its design also allows for inversion (data assimilation) experiments (e.g. Cui et al., 2011; Gutjahr et al., 2017, see below). Here we ran the model on a 36x36 grid with 16 vertical levels in the ocean, and included modules for weathering and marine sediments by which alkalinity is added to or removed from the ocean. In our model set-up, carbon emissions affect temperature, weathering rates, ocean solubility of gases, and ocean circulation. Wind fields are fixed and prescribed as boundary conditions and hence do not change in response to changing atmospheric CO2 concentration and greenhouse warming.

32 3.2. METHODS

We configured cGENIE for the early Aptian using paleogeography and bathymetry (see Appendix A), wind fields, and planetary albedo from the Aptian modelling setup of Donnadieu et al.(2006b). Temperature effects on biogeochemical production were included, and remineralization profiles adapted to a warmer ocean (John et al., 2014). We spun up the model in a first step (20 kyr) to equilibrate to an

atmospheric CO2 concentration of 840 ppm (as reconstructed for the start of the negative CIE in Naafs et al.(2016b)) and atmospheric δ13C value of -6 %, which is at the upper limit of measured values of the modern atmospheric composition (Craig, 1953). Carbonate production is set up as in Ridgwell and Schmidt(2010) to represent a warm, ice-free world. We assume that organic carbon burial did not play a major role for the marine carbon cycle during the interval that we simulate here (see Discussion section), but in order to equilibrate oceanic δ13C in the absence of organic carbon burial, we set the carbon isotopic composition of the weathering flux to 6.2 %. Initial calcium ion supply from terrestrial weathering is set 1 to 34 Pmol yr− , resulting in an average surface calcite saturation state (4.3) within the reconstructed range for the Early Cretaceous (Ridgwell and Zeebe, 2005). The initial oceanic nutrient inventory was 3 1 set to 1.06 µmol PO4− kg− ocean water, equalling half of the preindustrial oceanic phosphate inventory. This is based on a model-data comparison of pre-OAE 1a anoxia extents, following Monteiro et al. 2012 (see appendixA). However, sensitivity experiments showed that the initial phosphate inventory has little effect on our results (see fig. A.5 in the AppendixA). During the second spin up stage (500 kyr), the model was run as an open system so that volcanic outgassing, riverine input of solutes to the ocean, and carbonate burial in marine sediments could reach equilibrium.

To constrain carbon fluxes and their isotopic composition across OAE 1a onset, we used a double data assimilation approach. Similar studies with single assimilations used the size of negative CIEs to constrain emission rates associated with other major carbon cycle events such as the Paleocene-Eocene Thermal Maximum (PETM, e.g. Cui et al., 2011; Turner and Ridgwell, 2013) making assumptions about the δ13C signature of the carbon source. Here however, we intend to reconstruct both the mass and provenance (i.e. isotopic composition) of the emitted carbon. Knowing that a given isotopic excursion can be produced by adding a small mass of very 13C-depleted carbon or a large mass of less 13C-depleted carbon (e.g. Kirtland-Turner and Ridgwell, 2016) this constitutes a problem with two unknowns (mass and composition), the solution for which requires an additional constraint to the CIE size. We hence 13 combined estimates of atmospheric δ C changes with estimates of pCO2 changes (Naafs et al., 2016b) to reconstruct carbon emissions across the onset of the OAE 1a negative CIE.

Each time step, cGENIE adds the mass of carbon needed to reach the prescribed pCO2 target to the atmosphere, and then calculates the required isotopic signature of that carbon addition to create the 1 13 right CIE. We allow a maximum carbon emission rate of 10 Pg yr− with a δ C not more negative than 13 -100 %. We used the Naafs et al.(2016b) pCO2 estimates based on ∆ C, the offset between compound 13 13 13 specific δ C in organic matter and bulk carbonate δ C(δ Ccarb)(Popp et al., 1998). We assumed 13 13 that the evolution of δ Ccarb reflects marine and atmospheric δ C changes (see AppendixA). For this, we correct sedimentary δ13C measurements from the Cau section by applying a 7.7 % offset to 13 account for different baseline δ C values between atmosphere and biogenic CaCO3. We smooth these

33 CHAPTER 3. UNRAVELLING THE SOURCES OF CARBON EMISSIONS AT THE ONSET OF OCEANIC ANOXIC EVENT (OAE) 1A a) Reconstructed atmospheric carbon across OAE 1a b) Model forcing for stage C3

Figure 3.1: Reconstructed properties of the surficial carbon reservoir during OAE 1a (segments after 13 Naafs et al.(2016b)) and pCO2 forcings used in this study. a) Reconstruction of bulk carbonate δ C variation and pCO2 across OAE 1a based on proxy data from Cau (Naafs et al. 2016a): b) Zoom into the 13 13 onset of the negative CIE, showing δ C changes and the 5 pCO2 scenarios we tested in cGENIE. δ C 13 values are given as offsets from the highest value in the smoothed δ Ccarb data series prior to the start of OAE 1a.

data by applying a running mean over 7 data points (see fig. 3.1) to minimize the effect of short-term fluctuations. This smoothed sedimentary δ13C is characterized by an averaged 1.3 % negative excursion (maximum value 1.6 %), which is similar to most other measured negative CIE amplitudes for OAE 1a (see AppendixA). This dual data assimilation exercise is analogous to Gutjahr et al.(2017)’ assessment 13 of the PETM carbon cyle perturbation, except here taking pelagic δ Ccarb as a measure of atmospheric rather than surface ocean (DIC) δ13C changes, and we directly constrain the rate of emissions using a pCO2 reconstruction rather than surface pH. We additionally address a number of uncertainties in the data and its interpretation. Firstly, implications of uncertainties in the pCO2 reconstruction are explored by using an ensemble of 5 simulations with different pCO2 trajectories within the uncertainty envelope reconstructed by Naafs et al.(2016b) (fig.

3.1). This uncertainty envelope accounts for uncertainties in the calibration of the pCO2 reconstruction method to Cretaceous organisms and due to the fluctuability of the 13C curve in Cau outcrop data.

Secondly, the duration of the negative CIE at the OAE 1a onset is poorly constrained. We run every pCO2 scenario with a duration of 100 kyr, but since durations between 20 and 300 kyr have been suggested for the onset of the negative CIE interval (e.g. van Breugel et al., 2007b; Li et al., 2008; Malinverno et al., 2010; Hu et al., 2012), we repeat some simulations with three different assumed durations: 20 kyrs,

34 3.2. METHODS

40 kyrs and 300 kyrs. In total, we run 20 inverse modelling simulations, exploring 5 different pCO2 trajectories and 4 different assumptions about durations. Additional sensitivity experiments were run to investigate the sensitivity to boundary conditions (see AppendixA).

3.2.3 Osmium isotope analysis

Osmium (Os) isotopes and Os and Rhenium (Re) concentrations were determined at the School of Earth Sciences, University of Bristol. Samples were digested in Carius tubes using techniques slightly modified from Shirey and Walker(1995). 0.3-0.5 g of powder was added to the Carius tubes. As the rock contained a significant amount of carbonate (46 m - 62 m of the Cau section consist of a succession of marl and marly limestone, see Quijano et al.(2012) and Naafs et al.(2016b) for more information on the lithologies) the powder was decarbonated with a small amount of concentrated HCl prior to sealing. Appropriate amounts of 190Os and 185Re spikes were added to the Carius tubes along with additional

HCl and HNO3 to make up 12 ml of inverse aqua regia. The samples were then digested at 230 ◦C for 48 hours. This technique recovers hydrogenic Os and Re without dissolving any detrital material. Os and Re separation chemistry and mass spectrometry follows methods recently described in detail elsewhere (Josso et al., 2019). For Os isotope analyses the purified Os was analysed on a ThermoFisher Triton thermal ionisation mass spectrometer (TIMS) in N-TIMS mode, with instrumental mass fractionation corrected for using the exponential mass fractionation law and a 192Os/188Os ratio of 3.08271. Os concentrations were determined by isotope dilution and the isotope data were spike-stripped to yield the sample 187Os/188Os ratio. Total procedural blanks were determined for each dissolution batch and yielded Os concentrations of 0.31 and 1.46 pg, with 187Os/188Os ratios of 0.1783 0.0347 and ± 0.1745 0.0557 respectively. All data were corrected for the procedural blank with blank corrections ± usually less than 1.5 % (range 0.04 to 4 %) on the concentration and usually less than 1 % (range 0.02-3.5 %) on the 187Os/188Os ratio depending on sample size and Os concentration. A DTM solution standard was run during the analytical period and yielded a 187Os/188Os ratio of 0.17396 39 (2sd, n=12), within ± error of previous determinations of the standard (e.g. Birck et al., 1997). Precision on the standard and samples is similar because they were both run at comparable beam intensity, with the exception of one sample, which has a precision of 12 %. Re isotopes were measured by multi-collector inductively plasma source mass spectrometry (MC-ICP- MS) on a ThermoFisher Neptune using a SEM and corrected for instrumental mass fractionation using the exponential mass fractionation law and a 191Ir/193Ir ratio of 0.59418. Total procedural blanks were determined for each dissolution batch and yielded Re concentrations of 5 2 pg, with Re concentrations ± determined by isotope dilution and blank corrected using the appropriate procedural blank. Blank corrections for the Re concentrations are less than 2 % (range 0.14-4.1 %). A 9 ppt solution of the NIST SRM3134 Re standard, doped with Ir, was run during the analytical period and yielded a 187Re/185Re ratio within error of previous determinations of the standard (Miller et al., 2009). One sample (Cau-21) was fully duplicated, because it had elevated Re concentrations, low Os concentrations and gave a low initial 187Os/188Os ratio at a key part of the section. The duplicate analyses gave initial 187Os/188Os ratios

35 CHAPTER 3. UNRAVELLING THE SOURCES OF CARBON EMISSIONS AT THE ONSET OF OCEANIC ANOXIC EVENT (OAE) 1A just outside of analytical uncertainty, but confirming that there is significant drop in initial 187Os/188Os ratio in the section at this time.

3.3 Results a) carbon mass fluxes across stage C3 b) δ13C of carbon fluxes

c) carbon masses with different C3 duration estimates d) δ13C with different duration estimates

Figure 3.2: Carbon fluxes and their isotopic signatures across the onset of the negative CIE as calculated by cGENIE. (a) and (b) show differences due to different pCO2 change scenarios (see fig. 3.1), all assuming a CIE onset duration of 100 kyr. (c) and (d) show the influence of a different CIE onset duration (20-300 kyr) examplarily for scenario 3. The results are averaged over 1m depth equivalent.

The model simulations provide estimates of carbon emission rates and the isotopic composition of the emitted carbon for the onset of the Aptian negative CIE under different pCO2 change scenarios (fig. 3.2a-b) and onset durations (fig. 3.2c-d). In our simulations, total emissions ranged between 1 4,300-29,200 Pg C with emission rates between 0.01 and 0.7 Pg C yr− . The uncertainty in our carbon emission estimates is almost equally attributable to uncertainties in the duration of the event and the pCO2 reconstruction (10,300 Pg C and 13,700 Pg C respectively). Alternative assumptions on initial atmospheric CO2 concentrations, oceanic nutrient inventory and surface ocean saturation state add

36 3.3. RESULTS only minor additional uncertainty to emission rates (see sensitivity studies in AppendixA). The model results imply isotopically light carbon input (mean composition across all scenarios = -42 %) at the start of the negative CIE (46 - 50 m) for all scenarios. Toward the peak of the negative CIE, our model results indicate a shift towards the input of less 13C-depleted carbon with a mean composition of -6 % between 55.5 - 60.0 m. Additional sensitivity studies (see AppendixA) demonstrate that the necessity for 13C-depleted carbon at the start of the negative CIE is a robust result considering uncertainties in initial atmospheric CO2 concentration, initial oceanic nutrient inventory, initial carbonate saturation state, and different biological production schemes (temperature-dependent or -independent production). In our simulations the calcite saturation state (Ω) of the surface ocean only decreases appreciably 1 in experiments with carbon emission rates of at least 0.1 Pg C yr− (see fig. A.9 in AppendixA). In scenarios with slower carbon emissions, surface ocean Ω stays constant or increases slightly. The total Ω change and the associated uncertainty intervals vary between locations and are largest in the tropics (up to -2.5 in the most extreme experiments, see fig. A.10 in AppendixA). Sea surface temperature (SST) ∼ changes are more variable with pCO2 change scenario than assumed CIE onset duration, and are largest around Antarctica (see fig. A.11 in AppendixA).

187 188 Figure 3.3: Os concentration and Os/ Os(i) between meters 39 and 65 of the Cau section. The onset of the negative CIE is marked by blue shading. Uncertainties on data are smaller than the symbols.

The new Os data from Cau (see fig. 3.3) show a low concentration of Os with a slight trend towards

37 CHAPTER 3. UNRAVELLING THE SOURCES OF CARBON EMISSIONS AT THE ONSET OF OCEANIC ANOXIC EVENT (OAE) 1A more radiogenic values ( 1) towards the start of the negative CIE (40-45 m). This is followed by increasing Os concentration during the CIE, its isotopic composition shifting to less radiogenic values ( 0.4). A < brief excursion back to low concentrations of very radiogenic Os ( 1.2) half way through the negative > CIE onset ( 55 m) is based on two data points. All data can be found in AppendixA. ∼

3.4 Discussion

Our inverse modelling suggests that the addition of 13C-depleted carbon during the start of the negative CIE (Phase A in fig. 3.4), followed by sustained input of carbon with a largely volcanic isotopic signature (Phase B, typically between -5 and -8 % away from subduction zones (Javoy et al., 1986)), reconciles 13 the measured δ Ccarb and reconstructed pCO2 at Cau (Naafs et al., 2016b). Our method results in required ‘net’ carbon fluxes and their isotopic compositions. While we cannot exclude mixes of sources (and sinks) that sum to the right ‘net’ values, this provides information about the dominant carbon 13 source. The requirement for initial carbon emissions more C-depleted than volcanic CO2 across our simulations indicates that contribution from organic carbon sources (typically between -10 and -30 % (e.g. Meyers, 1994)) and methane, the only surficial carbon with a δ13C < -40 %, was necessary to drive the CIE at the OAE 1a onset (see fig. 3.2b,d and AppendixA). Predominant methane emissions, however, are only required in scenarios with minimal pCO2 rise during the CIE onset. All scenarios require the most 13C-depleted carbon input between 48 m and 52 m. The isotopic composition of the carbon input predicted by cGENIE between 52 m and 58 is consistently less depleted (around or above -10 % for most simulations) almost regardless of uncertainty in reconstructed pCO2 or duration. This is consistent only with an appreciable contribution from a volcanic source. The shift in source from sedimentary organic carbon to volcanism occurs relatively rapidly, within 4 m at Cau or 25 kyr assuming a negative CIE onset duration of 100 kyr and a constant sedimentation rate. Importantly, this difference in isotopic composition between strata below and above 52 m is a robust feature in all simulations and suggests that Earth’s system transitioned from predominant input from an isotopically light carbon source to a heavier 13 one. Scenarios with low pCO2 increase require another pulse of biogenic CO2 to reach the lowest δ C values at the end of our simulations, while the isotopic signature of carbon inputs in scenarios with higher emission rates remains close to mantle values. A shift to a more mantle-like source is supported by published Os isotope data which have been used to infer changes in volcanic activity across OAEs, given that the main source of unradiogenic Os is mantle material (Turgeon and Creaser, 2008; Bottini et al., 2012; Du Vivier et al., 2014). Published OAE 1a Os isotope records from pelagic sections show a shift towards unradiogenic (mantle-like) values during the negative CIE at the onset of OAE 1a (Bottini et al., 2012), suggesting a strengthened Os flux from the mantle. While a direct comparison between Os records from Cau and other sites is hampered by uncertainties in age models and missing stratigraphic ties, records from all sites show similar features. The consistent shift to very unradiogenic Os-isotope values in the Cau record (fig. 3.4) is similar to that recorded in other sections and adds confidence to the assumption that strengthened volcanism

38 3.4. DISCUSSION

Figure 3.4: Osmium isotopic changes (left) and reconstructed δ13C signature of emissions based on carbon isotopes (right) at Cau. The two shaded sections show phases of least (A) and most prominent (B) volcanic activity.

was the primary control on Os isotope changes recorded across the negative CIE at Cau, even more so given the small amount of preserved organic matter preserved and its platform setting. Similar to other Tethyan sections, the Os record at Cau shows a shift back to radiogenic values before stagnating at unradiogenic values (in phase B in fig. 3.4, Jenkyns(2018)). Since this excursion is not evident in records from all OAE 1a sections, it might represent a local or regional change with little implications for the reconstructed volcanic strength. In that case the shifts from less to more mantle-like compositions of Os and carbon coincide at Cau (fig. 3.4). If the radiogenic excursion at 55 m in the Cau section ∼ reflects a global change of Os fluxes, the resolution of the pCO2 reconstruction is either too coarse to evidence a short-term decline in volcanic carbon emissions, or the relationship between carbon and Os isotopic changes during the onset of LIP emplacement is more complex. At this moment, we cannot test this relationship at other sites because combined records of Os isotope and inferred pCO2 changes are not available at the required resolution. Emissions of carbon from an organic matter reservoir are needed to explain carbon isotopic changes at Cau regardless of the pCO2 scenario or assumed duration of CIE onset. However the exact mechanism of its release at the onset of OAE 1a is not clear. It is unlikely that depleted carbon was emitted due to feedback mechanisms in response to a warming climate (e.g. destabilized methane hydrates), given the small changes in atmospheric pCO2 at that time. There is, however, evidence in support of geologically-triggered emissions of 13C-depleted organic carbon during the onset of OAE 1a. Polteau et al.(2016) showed that magma intrusions into overlying sediments during the formation of the Barents

39 CHAPTER 3. UNRAVELLING THE SOURCES OF CARBON EMISSIONS AT THE ONSET OF OCEANIC ANOXIC EVENT (OAE) 1A

Sea Sill Complex in the early Aptian could have destabilized a considerable mass of organic carbon and led to thermogenic methane emissions. OAE 1a happened at a time of high magmatic activity, including the emplacement phases of the Ontong-Java Plateau LIP (e.g. Larson and Erba, 1999). We therefore suggest that at the start of the negative CIE magmatic activity increased under thin crust,intruding into organic-rich marine sediments and causing small releases of 13C-depleted thermogenic gases. This initial phase of increased mantle activity was then followed by a more eruptive phase of LIP emplacement, when large-scale submarine volcanism dominated exogenic carbon emissions and delivered large amounts of new mantle material to the ocean floor. This increased the flux of unradiogenic Os into the ocean through hydrothermal vents as well as weathering of fresh basalt and released vast amounts of mantle-sourced carbon to the atmosphere. Thus, the initial δ13C decrease and the excursions in Os isotopes and ∆13C are consistent with a scenario in which the recorded CIE and pCO2 change occured independently: The

first through release of sedimentary organic carbon, and the latter through volcanic CO2 emissions.

13 Our results based on records of atmospheric pCO2 and δ C are consistent with published model interpretations of Os isotope profiles, which also find that volcanism was the primary carbon source during OAE 1a (Bauer et al., 2017b). The mass of emitted carbon in our results is however different from that reconstructed by Bauer et al.(2017b) using Os isotopes. The biomarker-based estimate suggests an increase in pCO2 of 200-1700 ppm (Naafs et al., 2016b), whereas the model interpretation of 187 188 Os/ Os implies that pCO2 rose by about 3,000 ppm (Bauer et al., 2017b). We tested the implications for carbon sources assuming a continuous CO2 concentration increase of 3000 ppm, which resulted in 1 increased carbon emissions (0.32 Pg C yr− assuming a 100 kyr duration, see fig. A.8 in the Appendix A) compared to our scenarios, with isotopic compositions between -20 and -3 %. This is still consistent with a predominantly volcanic source, but reduced the need for more 13C-depleted organic carbon release. Temperature proxy records across OAE 1a (Mutterlose et al., 2014; Naafs and Pancost, 2016) are consistent with regional temperature changes of 1-5 ◦C produced by scenarios based on the Naafs et al.(2016b) pCO2 reconstruction. The higher (Os based) pCO2 changes result in a temperature rise of

7 ◦C globally in cGENIE, equivalent to 5 – 6 ◦C in the Tethys which is at the upper end of reconstructed temperature change.

Organic carbon burial is not simulated by our model, meaning that we have to assume that organic carbon burial did not strengthen significantly during the negative CIE onset. Although carbon contents at Cau and at other locations only increase during the recovery of the negative CIE and start of the positive CIE (generally referred to as segments C4-C6 Menegatti et al., 1998; Quijano et al., 2012; Erba et al., 2015), it is unknown to what degree the marine carbon and Os cycles were influenced by organic matter burial locally and/or globally. Widespread organic carbon burial would shorten the residence time of Os and carbon in the ocean and create a sink for 12C, increasing carbon emission rates needed to produce the observed environmental changes. The results from our experiments should thus be regarded as a low-end estimate of the mass of emitted carbon. However, our experiments indicate that the transition from more 13 depleted organic carbon input (potentially from sill intrusions) to mantle-sourced carbon (volcanism) is robust against changes in emission rate and total mass of emitted carbon and hence should

40 3.5. CONCLUSION be detectable despite changes in the amount of organic matter burial. In terms of timing, high-resolution temperature records (based on palynology and δ18O) at the expanded pelagic section of Pusiano and the shelf section at La Bédoule (Keller et al., 2011; Lorenzen et al., 2013) indicate a time lag between the start of the negative CIE and the main period of warming. This would be consistent with our reconstructed emissions scenarios. At pelagic sections lower sediment accumulation rates and coarser sampling resolutions (e.g. Cismon, Roter Sattel, Pacific DSDP site 463 and Atlantic DSDP site 398), likely prevented the identification of such time lag between temperature proxies and negative CIE (Menegatti et al., 1998; Ando et al., 2008; Naafs and Pancost, 2016).

Major changes in the marine nannofossil community, including dwarfism, and a decline in CaCO3 burial rates, have been observed during the negative CIE and interpreted as an indicator for a decline in calcite surface ocean saturation state due to large carbon emissions (Weissert and Erba, 2004; Erba et al., 2010). The widespread occurrence of surface ocean acidification during OAE 1a as driver of biological turn-over is contested (Gibbs et al., 2011; Naafs et al., 2016b). Our simulations show that only scenarios with a large carbon source or short event duration result in an appreciable Ω decline (∆Ω 0.5), globally > and locally. A decrease in saturation state could have imposed significant stress onto calcifiers (Weissert and Erba, 2004). At Cau, the pCO2 changes and the decline in Ω (around 54 m) began well after the onset of the nannofossil decline, which starts at 43 m. In our longer simulations ( 100 kyr) increased ≥ weathering and continental runoff eventually counteract the CO2 dissolution effect, which leads to a recovered or even increased calcite saturation state at the end of these experiments, despite ongoing carbon emissions. Further quantitative comparison of the impact of carbon emissions onto the surface ocean carbonate chemistry in our simulations is hampered by remaining uncertainties. For example, the carbonate system of the pre-OAE 1a Aptian surface ocean is poorly constrained. Particularly the mass of emitted carbon needed to cause appreciable Ω changes and the position of the carbonate compensation depth depend largely on these initial conditions. The slow carbon emission rates predicted by our model are also a function of the duration of the negative CIE onset. Unless the onset took 20 kyr (Malinverno et al., 2010, the smallest current estimate) or less, it is unlikely that carbon emissions could have outpaced the weathering feedbacks that stabilize the surface ocean saturation state (Hönisch et al., 2012). As such, estimated onset durations and the temporal decoupling between changes in calcite saturation state and nannoconid crisis make it unlikely that this major perturbation of the marine nanno-calcifier community was a direct result of carbon emissions driving the negative CIE.

3.5 Conclusion

13 We used transient model simulations based on combined pCO2 and δ C records to identify dominant carbon sources and quantify associated emission rates. The simulations show that carbon emission rates 1 of 0.043-1.46 Pg C yr− reconcile the negative CIE and pCO2 estimates, with the exact rate depending on the assumed duration of OAE onset. Assuming a baseline pCO2 of 850 ppm this is consistent with estimates of moderate temperature change from diverse proxy data. Our results suggest that an initial

41 CHAPTER 3. UNRAVELLING THE SOURCES OF CARBON EMISSIONS AT THE ONSET OF OCEANIC ANOXIC EVENT (OAE) 1A input of predominantly 13C-depleted carbon was responsible for the negative CIE associated with OAE

1a, but had little effect on atmospheric pCO2. This carbon could have originated from sill intrusions into marine organic rich sediments, potentially releasing thermogenic and/or biogenic methane. Following this initial phase, volcanic (less 13C-depleted) carbon emissions sustained the stagnant part of the negative

CIE and fuelled most of the recorded atmospheric pCO2 increase. Our results indicate that organic 13 carbon emissions in form of methane and/or CO2, despite shaping the δ C curve, did not increase the atmospheric carbon reservoir appreciably. Importantly, this demonstrates that the scale and nature of the Earth system perturbation at the onset of OAE 1a cannot be determined based on the existence of a negative CIE or its size alone. This may also be the case for other negative CIEs in the geological record. Our results further imply the possibility of a time lag between the carbon isotopic excursion and the major phase of carbon emissions, but highly resolved records from other sections are necessary to corroborate this finding. Uncertainties in the amount of atmospheric pCO2 change and duration of the OAE onset create proportionally large uncertainties on carbon emission rates and their initial isotopic composition. Increased accuracy in duration and pCO2 change estimates are needed to narrow down our estimates of carbon flux magnitudes and origins. However, the shift from more to less 13C-depleted carbon emissions is robust against these uncertainties, as are the pure volcanic-like carbon fluxes towards the peak of the negative CIE. We conclude that mantle activity increased in the early Aptian, heating organic-rich marine sediments and releasing thermogenic methane before sustained mantle eruptions led to OAE formation.

42 uhrcnrbtosaddeclaration: and contributions Author o tadant vi lgaimsuspicions. plagiarism avoid to Strandmann von eeomn icsin xetfrscin426weeIrprsdsnecsaddb hlp Pogge Philipp Model by Geoscientific added in sentences version rephrased the I to where identical 4.2.6 is section chapter for except this contributed Discussions of Greene Development text E. The Sarah text. and previously manuscript Monteiro All final M. Fantle. the Fanny S. to supervisors Matthew my and as Strandmann well von as Sr, Pogge collaborators, cGENIE Philipp named the from implemented advice Ridgwell with Andy cycles Ca manuscript. and draft Alex Li the Parkinson, wrote produced J. output, and model Ian figures the and validated from simulations data, advice observational the the with compiled cycle also I Os Ridgwell. Andy cGENIE and the Dickson implemented and conceived (https://doi.org/10.5194/gmd-2020- I discussion 233). under currently is and Development Model Geoscientific the provides O This and cycles. C C cycles, and metal metal these pre-industrial of the of co-evolution and spin-up the cGENIE investigate a into to as cycles tools well their as of code, implementation added the throughout the presents weathering of chapter evaluation continental This and and event. volcanism Li the Sr, of of Os, evolution body of the the excursions reconstruct isotopic to Instead, used burial. been C have organic because Ca marine onset, increased event by The the dominated beyond onset. then event fluxes is the C exogenic it during about source information C provide dominant not the does however, as record, volcanism established and 1a OAE of record thesis: the into Embedding nlso fasieo eteigtaesi h GNEEarth cGENIE the in tracers weathering of suite a of Inclusion h rvoscatrrcntutdeoei ue ae nthe on based fluxes C exogenic reconstructed chapter previous The ytmMdl-mfi ees v.0.9.10 release muffin - Model System hscatrwssbitda natcet h journal the to article an as submitted was chapter This 43 2 ntefloigchapters. following the in

C h a p t e r 4 δ δ 13 13 C C CHAPTER 4. INCLUSION OF A SUITE OF WEATHERING TRACERS IN THE CGENIE EARTH SYSTEM MODEL - MUFFIN RELEASE V.0.9.10

Abstract

The metals strontium (Sr), lithium (Li), osmium (Os) and calcium (Ca) and their isotopes are important tracers in the study of changes in weathering rates and volcanism, two main processes which shape the long-term cycling of carbon and other biogeochemically important elements at the Earth’s surface. Traditionally, isotopic shifts of these four elements in the geologic record are interpreted with isotope- mixing, tracer-specific box models because of their long residence times in the ocean. However, these models often lack mechanistic links between the cycling of the four metals and other geochemically relevant elements, particularly carbon. Here we develop and evaluate the implementation of Sr, Li, Os and Ca isotopes into the Earth system model cGENIE. The model has the potential to study these metal systems at equilibrium and under perturbations alongside other biogeochemical cycles. We provide examples of how to apply this new model to investigate Sr, Li, Os and Ca isotope dynamics and responses to environmental change.

4.1 Introduction

The evolution of life and climate on Earth is intrinsically linked to the dynamics of carbon, oxygen and nutrients at the Earth’s surface. While complex interactions on a range of spatial and temporal scales determine the distribution of these elements between surficial (non-lithological) reservoirs like oceans, atmosphere, biomass and soils, the total amount and isotopic distribution of these elements are ultimately governed by the balance between crust weathering, marine sediment deposition and mantle inputs during oceanic crust formation. Geological records show that the abundance of these elements at Earth’s surface varied on time scales of thousands to millions of years. For example, the changing composition of mantle fluxes into the ocean and nutrient supply during weathering of large mountain ranges were potentially drivers of the accumulation of surficial oxygen during the Archean and Proterozoic (e.g. Kump and Barley, 2007; Campbell and Allen, 2008). Likewise, the supply of particulate iron from airborne grounded rock to the oceans of the Quaternary is invoked as a mechanism to drive glacial-interglacial carbon cycle dynamics (e.g Martin, 1990; Martínez-Garcia et al., 2011; Loveley et al., 2017; Hooper et al., 2019). The emplacement of large igneous provinces (LIPs) repeatedly led to climatic and biotic crises by increasing the supply of mantle-derived carbon and nutrients to the oceans, e.g. during oceanic anoxic events (e.g. Erba et al., 2010; Jenkyns, 2010; Bottini et al., 2012; Monteiro et al., 2012; Percival et al., 2015). Increased basalt weathering in the Cenozoic could have led to a continuous decline in CO2 concentrations, contributing to the reconstructed long-term cooling trend (e.g. Kent and Muttoni, 2013; Mills et al., 2014). Mass fluxes between the lithosphere and Earth’s dynamic surface are thus important drivers of environmental processes on the Earth’s surface over geological time scales, but our ability to measure these fluxes directly is limited by their long evolution times and large spatial extents. Instead, records of variations in the content and isotopic composition of trace metals like strontium (Sr), osmium (Os), lithium (Li) and calcium (Ca), preserved in marine sediments, are used to study lithological processes. The dynamics of these metals are controlled by processes that also

44 4.2. OBSERVATIONAL CONSTRAINTS

shape the long-term carbon and nutrient cycles, namely continental and oceanic weathering and direct mantle emissions, but variations in their isotopic compositions can be linked more directly to changes in these processes since radioactive decay and mass-dependent fractionation form isotopically distinct lithological metal reservoirs. The residence time of these metals in the ocean is generally assumed to be greater than the mixing time of the ocean and therefore their distribution is comparably homogeneous (e.g. Faure and Mensing, 2005). While laboratory methods to measure and reconstruct the evolving trace metal composition of seawater have become increasingly precise, our ability to interpret these records is limited by our incomplete mechanistic understanding of the cycling of these metals and their isotopes. Quantifying reservoir sizes and fluxes constitute particular challenges under varying chemical conditions and marine productivity over geological time. Mass balances and box models have been most commonly used to interpret geological records of trace metal variations (e.g. Tejada et al., 2009; Misra and Froelich, 2012; Kristall et al., 2017; Them et al., 2017). They however rely on assumed fluxes and residence times based on today’s ocean which might not always be applicable throughout the geological record. Mechanistic Earth system models are useful tools to test our conceptual and mathematical understand- ing of processes against observations, and to explore characteristics and processes of biogeochemical cycling beyond modern observational data. The Earth system model of intermediate complexity cGENIE has been used successfully to study marine biogeochemical cycles (including C and Ca) under various boundary conditions and external forcings (e.g. Ridgwell and Zeebe, 2005; Ridgwell et al., 2007; John et al., 2014; Death et al., 2014; Kirtland-Turner and Ridgwell, 2016; Hülse et al., 2019). Implementing isotope enabled cycling of Sr, Os, Li and Ca in cGENIE allows us to test the influence of different assumptions about source and sink mechanisms, and efficiencies, on metal distributions in the ocean and their behaviour under environmental perturbations. Here, we present our implementation of the marine cycling of Sr, Os, Li and Ca in cGENIE. We evaluate the model’s performance by comparing simulations of pre-industrial trace metal distributions in the oceans to seawater measurements, and study their equilibration times to imposed geochemical perturbations compared to estimated seawater residence times for these elements.

4.2 Observational constraints

We first provide a brief review of the systematics of Sr, Os, Li and Ca cycling in the ocean, as well as their observed concentrations and isotopic compositions. This discussion provides the theoretical basis for our model implementation, and the data compilations for the model evaluation at the end of this study.

4.2.1 Strontium

Of the four metals modelled in this study, Sr has the second highest marine concentration (3 – 4 times more abundant than Li and more than one billion times more abundant than Os, Broecker and Peng, 1982). The main source for marine Sr is continental weathering, replenishing the ocean reservoir through rivers and potentially groundwater discharge (Basu et al., 2001; Beck et al., 2013). Smaller sources are

45 CHAPTER 4. INCLUSION OF A SUITE OF WEATHERING TRACERS IN THE CGENIE EARTH SYSTEM MODEL - MUFFIN RELEASE V.0.9.10 hydrothermal input of mantle-derived Sr and refluxes from diagenetic alteration of carbonates at the sea floor. The chemical and physical similarity of Sr to Ca leads to its substitution in aragonite and, to a lesser degree, calcite (Fietzke and Eisenhauer, 2006; Rüggeberg et al., 2008; Böhm et al., 2012; Stevenson et al., 2014). Angino et al.(1966) argue that biological uptake is the dominant driver of spatial gradients in Sr concentrations in today’s oceans, and Krabbenhöft et al.(2010) predict that marine carbonate burial could be the most important sink of seawater Sr. The concentration of Sr incorporated into biogenic carbonates depends on the mineralogy and the growth rate with higher Sr/Ca ratios in aragonite precipitated at fast growth rates (Rickaby et al., 2002; Stevenson et al., 2014). By contrast, direct effects of temperature on elemental fractionation during the formation of calcite, the major carbonate buried in marine sediments, are small (Tang et al., 2008). Assuming rivers to be the only supply of continental Sr to the oceans, Hodell et al.(1989) estimates the marine residence time of Sr to be 1.9 – 3.45 Myr. Considering the potentially appreciable Sr influx from groundwater, the actual residence time might be at or below the lower end of this estimate. Strontium has four stable isotopes (0.56% 84Sr, 9.87% 86Sr, 7.04% 87Sr, 82.53% 88Sr) (Veizer, 1989), although 87Sr is also the product of β-decay of 87Rb (half-life 4.88 1010 yr (Faure and Mensing, 2005). · Radiogenic Sr isotope ratios are reported as 87Sr/86Sr ratios whereas stable Sr isotope ratios are reported as δ88/86Sr, which is the per mille (%) deviation in the 88Sr/86Sr relative to the NBS987 standard 88 86 88/86 ( Sr/ Sr)sample (δ Sr = ( 88 86 - 1) 1000, Fietzke and Eisenhauer, 2006). Elemental fractionation during ( Sr/ Sr)std · magmatic processes creates different Rb/Sr ratios that over time generate reservoirs with distinct Sr isotopic signatures with the continental crust being considerably more radiogenic than the mantle (Faure and Mensing, 2005). Dust and rainwater isotopic signatures, both radiogenic and stable, are generally lower than modern day seawater values (Pearce et al., 2015). Volcanic material brings unradiogenic particulate Sr into sediments and can over time significantly affect the radiogenic composition of dissolved Sr in the sediment column while having little effect on the isotopic composition of dissolved Sr in seawater (Elderfield and Gieskes, 1982; Pearce et al., 2015). Changes in isotope abundances caused by kinetic and mass-dependent fractionation during carbonate formation are much smaller, and one can thus assume that the 87Sr/86Sr of seawater and deposited carbonates is only controlled by inputs to the ocean (Krabbenhöft, 2011). By contrast, variations in δ88/86Sr are only controlled by fractionation during chemical processes, biogenic carbonate formation being the most important one in the ocean (e.g. Krabbenhöft et al., 2010). There is no evidence for a generic dependence of δ88/86Sr fractionation during biogenic carbonate formation on environmental conditions, although temperature and growth rate effects were observed in some calcifying species (Fietzke and Eisenhauer, 2006; Böhm et al., 2012; Stevenson et al., 2014; Vollstaedt et al., 2014).

46 4.2. OBSERVATIONAL CONSTRAINTS

Table 4.1: Estimates of pre-industrial Sr fluxes between surface reservoirs and their isotopic composition. Process Flux (Gmol/yr) 87Sr/86Sr δ88/86Sr (%) Reference Pearce et al.(2015) hydrothermal input flux 3-4 0.7035-0.70387 0.328-0.422 Kristall et al.(2017) input from diagenesis 3-5 0.7035-0.7084 0.27 Kristall et al.(2017) Allègre et al.(2010) Peucker-Ehrenbrink et al.(2010) dissolved riverine input 20.2-47 0.7111-0.7136 0.32 Pearce et al.(2015) Kristall et al.(2017) Allègre et al.(2010) particulate riverine input 5.2 0.7136 uncertain Peucker-Ehrenbrink et al.(2010) < Kristall et al.(2017) Basu et al.(2001) groundwater discharge 7.1-16.6 0.7089 0.354 0.028 ± Beck et al.(2013) dust flux and rainwater uncertain 0.7075 - 0.7191 0.05 - 0.31 Pearce et al.(2015) Krabbenhöft et al.(2010) pelagic Sr burial Stevenson et al.(2014) in carbonates 12.5 - 174 seawater 0.20 Kristall et al.(2017) neritic Sr burial in carbonates 19 seawater 0.21 Krabbenhöft et al.(2010) Sr burial in Menzies and Seyfried Jr(1979) uncertain seawater seawater sea floor alteration Kristall et al.(2017)

4.2.2 Osmium

Osmium is a siderophile and chalcophile element which led to its accumulation in the Earth’s core (Goldschmidt, 1922) and is also compatible during mantel melting. As a result, it is one of the rarest elements in the Earth’s crust and the oceans. Because of its low concentrations, the ability to measure Os in seawater only developed in the past few decades, limiting the number of observations of marine Os concentrations and isotopic compositions. The cycling of Os at the Earth’s surface is similar to that of radiogenic Sr in many aspects. Oxidative weathering of sediments is currently the most important natural source of Os to the oceans (Peucker- Ehrenbrink and Ravizza, 2000; Lu et al., 2017). The estimated annual input of such Os to the oceans via aeolian and riverine transport and groundwater discharge is about 5 times larger than all other natural inputs combined (Lu et al., 2017). Hydrothermal inputs constitute the next biggest source of oceanic Os with high and low temperature systems being of roughly equal importance (Georg et al., 2013). The high temperature hydrothermal source can be split into a basaltic and a peridotitic source (Burton et al., 2010). Unlike for Sr, cosmic and terrestrial dust are significant sources of marine Os, as well as volcanic aerosols, though field observations do not suggest that the latter significantly contributes to the oceanic inventory (Sharma et al., 2007a). Os is removed from the ocean by deposition at the seafloor, predominantly under suboxic water masses and in ferro-manganese nodules (Lu et al., 2017). Os incorporation into biogenic carbonates constitutes an additional minor sink (Burton et al., 2010).

47 CHAPTER 4. INCLUSION OF A SUITE OF WEATHERING TRACERS IN THE CGENIE EARTH SYSTEM MODEL - MUFFIN RELEASE V.0.9.10

The marine residence time of Os is inherently uncertain given the uncertainty in Os fluxes, although estimates range from 3 – 50 kyr (Sharma et al., 1997; Levasseur et al., 1998; Oxburgh, 2001). Os has seven naturally occuring isotopes (0.02% 184Os, 1.59% 186Os, 1.51% 187Os, 13.29% 188Os, 16.22% 189Os, 26.38% 190Os, 40.98% 192Os). 186Os has such a long half-life that it can also be treated as stable over geological times, whereas 187Os is radiogenic due to the beta decay of 187Re (Faure and Mensing, 2005). The isotopic composition of Os in marine sediments provides insight into changing fluxes between different Os reservoirs, particularly weathering related Os fluxes from the continents and mantle derived fluxes from volcanic activity. During partial melt in the upper mantle Os is compatible and rhenium (Re) is incompatible, leading to an increased Re/Os ratio in continental crust relative to the mantle (D˛abek and Halas, 2007), and therefore elevated 187Os/188Os ratios in the continental crust compared to the mantle. No mass-dependent fractionation has been observed during Os uptake into macroalgae (Racionero-Gómez et al., 2017) and is not assumed to occur during other fluxes between surface reservoirs.

Table 4.2: Estimates of pre-industrial Os fluxes between surface reservoirs and their isotopic composition. Process flux estimate (kg/yr) 187Os/188Os reference Sharma et al.(2007a) riverine input (corrected for estuaries) 267-284 1.2-1.5 Georg et al.(2013) groundwater discharge 182 1.2-1.5 Lu et al.(2017) terrogenous and cosmic dust 35-88 0.12-0.60 Lu et al.(2017) Sharma et al.(2007a) high-temperature hydrothermal input 30 0.13 Georg et al.(2013) Sharma et al.(2007a) low-temperature hydrothermal input 19-56 0.88 Georg et al.(2013) burial in biogenic carbonates 4-5.3 ppt Os/Ca seawater Burton et al.(2010) oxic burial in marine sediments 2-372 seawater Lu et al.(2017) suboxic burial in marine sediments 458-2802 seawater Lu et al.(2017)

4.2.3 Lithium

Lithium is the 25th most abundant element in the Earth’s crust, and it is more concentrated in continental crust than in oceanic crust (Baskaran, 2011). Weathering, in particular of silicate rocks, releases dissolved Li to rivers and soils where it is partially bound during clay formation (Kısakűrek et al., 2005a; Dellinger et al., 2015; Pogge von Strandmann et al., 2017). The remaining dissolved Li is transported to the oceans via rivers and groundwater. Aeolian transport only contributes a minor flux of Li to the oceans (Baskaran, 2011). Li is also added to the oceans by hydrothermal vents and submarine weathering, but the size of this flux is more uncertain (Chan et al., 1992; Hathorne and James, 2006). Removal from the ocean happens predominantly via Li adsorption onto clay minerals, with a minor proportion buried with Li-containing biogenic calcite (Hathorne and James, 2006). These removal fluxes are dependent on the abundance of inorganic carbon and pH (Hall and Chan, 2004; Marriott et al., 2004), and are not uniform (Hathorne

48 4.2. OBSERVATIONAL CONSTRAINTS and James, 2006). The residence time of Li in the ocean is estimated to be 0.3 – 3 Ma (Stoffyn-Egli and Mackenzie, 1984) with more recent estimates closer to 1 Ma (Vigier and Goddéris, 2015). Li has two stable isotopes (7.52% 6Li and 92.48% 7Li, Penniston-Dorland et al., 2017). Changes in the abundance of Li isotopes on Earth are related to mass-dependent fractionation processes. The isotopic composition of Li is expressed as δ7Li, which is the % deviation of the 7Li/6Li ratio from the 7 6 7 ( Li/ Li)sample L-SVEC standard (δ Li = ( 7 6 - 1) 1000). While earlier studies suggest considerable variation ( Li/ Li)std · in seawater δ7Li (Carignan et al., 2004), recent studies suggest that seawater is remarkably homogeneous in its δ7Li (Hall et al., 2005; Rosner et al., 2007; Penniston-Dorland et al., 2017) consistent with its long residence time. Mass-dependent isotope fractionation has been observed during clay formation, adsorption onto minerals and incorporation of Li into calcite shells (Pistiner and Henderson, 2003; Rudnick et al., 2004; Dellinger et al., 2015; Hindshaw et al., 2019), while kinetic fractionation occurs in magmatic systems due to diffusion (Parkinson et al., 2007; Penniston-Dorland et al., 2017), and potentially in aqueous solutions (Richter et al., 2006). Isotopic differences in weathered lithologies and post-weathering formation of secondary minerals in rivers and soils result in a large spatial and temporal variability of the δ7Li of continental run-off (Huh et al., 1998; Pistiner and Henderson, 2003; Pogge von Strandmann and Henderson, 2015). Temporal variations in the amount of secondary mineral formation on land have the potential to drive shifts in seawater δ7Li over geological time (Misra and Froelich, 2012; Pogge von Strandmann and Henderson, 2015). Fractionation during biogenic carbonate formation results in carbonate δ7Li values that are a few % lower than seawater, but this offset seems to be carbonate producer-dependent Hathorne and James(2006).

Table 4.3: Estimates of pre-industrial Li fluxes between surface reservoirs and their isotopic composition. 1 7 Process flux estimate (Gmol yr− ) δ Li (%) reference Hathorne and James(2006) continental run-off 8-16 23 Misra and Froelich(2012) Hathorne and James(2006) hydrothermal vents 3-15 8.3 Misra and Froelich(2012) subduction reflux 6 15 Misra and Froelich(2012) loss to sea spray 0.1 sea water Stoffyn-Egli and Mackenzie(1984) Hathorne and James(2006) secondary mineral formation 3.5-37 16 Misra and Froelich(2012) Hathorne and James(2006) sea floor alteration 1-12 16 Misra and Froelich(2012) Rollion-Bard et al.(2009) neritic carbonate burial 1.7 - 81.3 µmol/mol Li/Ca 20 - 40 Dellinger et al.(2018) pelagic carbonate burial 10.4 - 14.5 µmol/mol Li/Ca 27.1 - 31.4 Hathorne and James(2006)

4.2.4 Calcium

Calcium cycling is closely linked to the C cycle, both shaping and shaped by the size of C reservoirs and C fluxes at the Earth’s surface. Similar to Sr, Os and Li, the dominant Ca source for today’s oceans

49 CHAPTER 4. INCLUSION OF A SUITE OF WEATHERING TRACERS IN THE CGENIE EARTH SYSTEM MODEL - MUFFIN RELEASE V.0.9.10 is weathering-derived dissolved and particulate Ca in continental runoff. Input through hydrothermal vents near ocean ridges is on the order of 20% of the riverine flux (e.g. Milliman, 1993; DePaolo, 2004). Unlike Sr, Os, and Li, Ca plays an important role in many biological systems, predominantly as an electrolyte and building block for biogenic minerals (e.g. shells, exoskeletons, bones and teeth). In the ocean, Ca ions are incorporated into biogenic minerals (e.g. foraminiferal tests and calcareous nannoplankton), or form hydrogenetic or authigenic minerals (Fantle et al., 2020) if waters are highly saturated (Ω=aCa2 aCO2 /Ksp). The resulting minerals are dissolved in undersaturated conditions, or + · 3− buried, compacted, and lithified. Carbonate formation creates the biggest long-term Ca and C sinks in today’s oceans, and marine carbonate accumulation and dissolution constitute a significant buffer mechanism to stabilize marine and atmospheric pCO2 during periods of enhanced exogenic C input. The residence time of Ca in seawater is estimated to be 0.5-1.3 million years (Milliman, 1993; Sime et al., 2007; Griffith et al., 2008). Ca has 6 stable isotopes (96.941% 40Ca, 0.647% 42Ca, 0.135% 43Ca, 2.086% 44Ca, 0.004% 46Ca, 0.187% 48Ca). 48Ca has such a long half-life time that it can be treated as a stable isotope, whereas a small 40 40 component of the Ca in a rock mineral is radiogenic (via decay of K; t1/2= 1.248 Ga) and accumulates in continental crust over geological time scales (Fantle and Tipper, 2014). The isotopic composition of Ca is reported as either δ44/40Ca or δ44/42Ca, which are the % deviations in δ44/40Ca and δ44/42Ca, respectively, from NIST SRM-915a, SRM-915b, or modern seawater (see Fantle and Tipper, 2014, for 44 40 44 42 44/40 ( Ca/ Ca)sample 44/42 ( Ca/ Ca)sample discussion): (δ Ca = ( 44 40 - 1) 1000 and δ Ca = ( 44 42 - 1) 1000). We use ( Ca/ Ca)std · ( Ca/ Ca)std · the δ44/40Ca notation in this study, from now on shortened to δ44Ca, with NIST SRM-915a as standard. Dissolution of carbonates and silicates, as well as the precipitation of secondary silicate minerals controls the Ca isotopic composition in soil pore fluids, lakes and rivers (Farkaš et al., 2007; Tipper et al., 2008; Hindshaw et al., 2013; Fantle and Tipper, 2014; Kasemann et al., 2014; Perez-Fernandez et al., 2017). Both, biotic and abiotic precipitation of carbonates fractionate Ca isotopically, generating minerals with 44 2 low δ Ca values relative to aqueous Ca +. The isotopic fractionation factor is most strongly a function of precipitation rate (and thus and solution chemistry, e.g. DePaolo, 2011) and is close to one (∆ 0) in ∼ the marine sedimentary column (see reviews in Blättler et al., 2012; Fantle and Tipper, 2014). In the ocean, species-dependent fractionation has been observed for several groups of calcifiers, with a small dependence on temperature (e.g. Nägler et al., 2000).

50 4.2. OBSERVATIONAL CONSTRAINTS

Table 4.4: Estimates of pre-industrial Ca fluxes between surface reservoirs and their isotopic composition. δ44/40Ca are given relative to NIST SRM915a (offset by +1.8825 0.07 from seawater (Holmden et al., ± 2012)) 1 44/40 Process flux (Tmol yr− ) δ Ca (%) reference Berner and Berner(2012) Zhu and Macdougall(1998) hydrothermal input flux 2-20 0.93 0.05 ± Holmden et al.(2012) Tipper et al.(2016) Berner and Berner(2012) input from diagenesis 0.92 0.6 0.77 ± Fantle and Tipper(2014) Berner and Berner(2012) riverine input 13.72 0.88 0.5 Holmden et al.(2012) ± Fantle and Tipper(2014) Berner and Berner(2012) groundwater discharge 5.24 - 13.22 0.58 - 0.85 0.23 Holmden et al.(2012) ± Fantle and Tipper(2014) Fantle et al.(2012) dust flux 0.05 - 2.25 0.72 0.6 ± Fantle and Tipper(2014) Holmden et al.(2012) Ca burial in carbonates 23.95 - 31.94 0.58 - 0.78 Fantle and Tipper(2014)

4.2.5 Metal distributions in seawater

51 CHAPTER 4. INCLUSION OF A SUITE OF WEATHERING TRACERS IN THE CGENIE EARTH SYSTEM MODEL - MUFFIN RELEASE V.0.9.10

Strontium Lithium Osmium Calcium

Figure 4.1: Sr, Li, Os and Ca contents of seawater. Shown are composites of all published measured concentrations and isotope ratios with reported errors. From these, we calculated mean concentrations and isotope ratios which are indicated by horizontal lines. Shading indicates one standard deviation around the means. Data are taken from Angino et al.(1966), Fabricand et al.(1967), Bernat et al.(1972), Brass and Turekian(1974), De Villiers(1999), Pearce et al.(2015), Mokadem et al.(2015) and the compilation of Wakaki et al.(2017) for Sr, Angino and Billings(1966), Fabricand et al.(1967), Chan (1987), Chan and Edmond(1988), You and Chan(1996), Moriguti and Nakamura(1998), Tomascak et al.(1999), James and Palmer(2000), Košler et al.(2001), Nishio and Nakai(2002), Hall(2002), Bryant et al.(2003), Pistiner and Henderson(2003), Millot et al.(2004), Choi et al.(2010), Pogge von Strandmann et al.(2010), Phan et al.(2016), Lin et al.(2016), Henchiri et al.(2016), Weynell et al. (2017), Fries et al.(2019), Gou et al.(2019), Hindshaw et al.(2019), Murphy et al.(2019) and Pogge von Strandmann et al.(2019) for Li, Levasseur et al.(1998), Woodhouse et al.(1999) and Gannoun and Burton(2014) for Os and Fabricand et al.(1967), De Villiers(1999) and Fantle and Tipper(2014) for Ca.

1 Dissolved Sr, Os, Li and Ca are largely homogeneous in sea water, which is illustrated in figure 4.1 by sorting all seawater measurements - independent of location and depth - by their measured value. Measurements of a perfectly homogeneous seawater property would appear as a horizontal line in this plot, since the same value would be measured everywhere in the ocean. Most trace metal measurements have a difference of less than one standard deviation from the respective mean, suggesting very small spatial heterogeneities. In particular, most measured isotopic compositions are analytically indistinguishable from the standard deviation of the overall data population. Larger differences between lowest and highest measured metal concentrations indicate heterogeneity (potentially horizontal and/or vertical gradients)

52 4.2. OBSERVATIONAL CONSTRAINTS in metal abundances or are an artefact of the small number of sub-surface measurements. One possible example is Sr, which is reportedly less abundant in surface waters and waters in the North Atlantic than in deeper waters and sites outside the North Atlantic (see fig. B.1). Higher Li concentrations in the surface ocean compared with deeper waters are only reported in one study, Angino and Billings(1966), while no vertical gradients are apparent in Fabricand et al.(1967) and Hall(2002). These differences suggest that the spread in Li concentrations in fig. 1 could be the result of analytical uncertainty rather than real gradients in dissolved Li. Os concentrations vary between sites, but only a few sub-surface measurements are available and there is considerable variation in Os concentration between measurement techniques (Gannoun and Burton, 2014). Ca profiles show no apparent spatial patterns.

4.2.6 Application of Sr, Os, Li and Ca isotopes as proxies of weathering and mantle emissions

The isotopic differences between Sr, Os, Li and Ca in the ocean and exogenic reservoirs allows these metals to be used as proxies for mass exchange between the surficial Earth system and the mantle, continental crust (all four) and extra-terrestrial material (Os). However, they record different geochemical pathways because they behave differently in water and have different predominant host lithologies. Sr and Os are used as proxies for the balance between the weathering of old continental crust and juvenile basalt or direct mantle emission (e.g. Hodell et al., 1990; Goddéris and François, 1995; Tejada et al., 2009; Finlay et al., 2010; Bottini et al., 2012; Dickson et al., 2015). The fact that carbonates are the biggest source of continental Sr but not of Os (which resides predominantly in shales and evaporites), means differences in these records can be used to infer changes in weathered lithology (e.g. Peucker-Ehrenbrink et al., 1995). Li is orders of magnitude more abundant in silicates than in carbonates and thus is discussed as the most direct proxy for silicate weathering (Kısakűrek et al., 2005a; Millot et al., 2010). The isotopic composition of dissolved Li is also not affected by plant growth (Lemarchand et al., 2010; Clergue et al., 2015) or phytoplankton growth (Pogge von Strandmann et al., 2016). Instead, the light Li isotope (6Li) is preferentially taken up by secondary minerals (clays, oxides, zeolites) formed during weathering, enriching residual waters in isotopically heavy Li. Hence, the δ7Li of continental run-off is controlled by the weathering congruency, which is a measure for the ratio of primary rock dissolution to secondary mineral formation (Misra and Froelich, 2012; Pogge von Strandmann and Henderson, 2015) and can act as a tracer of weathering intensity (that is, the ratio of the weathering rate to the denudation rate, Dellinger et al., 2015; Pogge von Strandmann et al., 2017; Murphy et al.,

2019; Gou et al., 2019). This also relates to the efficiency of CO2 drawdown, as cations retained on the continents in secondary minerals do not end up in the oceans to assist carbon sequestration (Pogge von Strandmann and Henderson, 2015; Pogge von Strandmann et al., 2017). It has been suggested that Ca isotopes can also be used to identify weathering flux changes in the geologic record (Kasemann et al., 2005; Farkaš et al., 2007; Kasemann et al., 2008; Blättler et al., 2011; Holmden et al., 2012; Fantle and Tipper, 2014; Kasemann et al., 2014), but they are also crucial proxies for changes in marine carbonate burial (Pogge von Strandmann et al., 2019). Because of its tight links with the marine carbonate system,

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Ca also serves as a constraint on CO2 concentration. Furthermore, Ca isotopes have been considered as a potential temperature proxy (e.g. Nägler et al., 2000), but this application might be complicated by the strong control of aqueous chemistry on Ca fractionation (DePaolo, 2011). Likewise, changes in the Sr/Ca ratio in calcifiers reflects ecosystem shifts, carbonate mineralogy and calcification rate (Stoll and Schrag, 2001), and stable Sr isotopes in calcifiers correlate with growth rate, mostly influenced by temperature and pCO2 (Stevenson et al., 2014; Müller et al., 2018). While each system individually gives valuable insight into Earth system dynamics, in concert, these trace metal systems can provide information on feedbacks and event durations, as well as improve the accuracy of our reconstructions (e.g. Kasemann et al., 2008).

4.3 Model implementation

We implemented the marine cycling of Sr, Os and Li and Ca isotopes in the Earth system model ’cGENIE’. cGENIE is a modular model, comprising modules for ocean physics (’GOLDSTEIN’ Edwards and Marsh, 2005), marine biogeochemistry (’BIOGEM’ Ridgwell et al., 2007), continental weathering and run-off (’ROKGEM’ Colbourn et al., 2013), sea-floor sediment formation (’SEDGEM’ Ridgwell and Hargreaves, 2007), atmospheric chemistry (’ATCHEM’) and atmospheric energy balance (’EMBM’ Ridgwell et al., 2007). As a whole, cGENIE includes a 3D ocean combined with a 1D atmosphere which capture the cycling of carbon and a range of other elements relevant for biogeochemical studies of the ocean water column and at the sea-sediment and sea-air interfaces, as well as climate-sensitive continental run-off and explicit sedimentary carbonate burial.

54 4.3. MODEL IMPLEMENTATION

Figure 4.2: Processes included in the cGENIE trace metal implementation and the number of the subsection containing their explanation. Hashed arrows indicate processes during which isotopic fractionation occurs in the model.

Figure 4.2 shows a conceptual model of the Sr, Os, Li and Ca cycles in cGENIE with arrows of different colours showing mass fluxes of different metals. The implementation of these processes involves code additions to the modules ROKGEM, BIOGEM and SEDGEM that are described in the following sections.

4.3.1 Continental weathering and run-off

Continental weathering is the main source for marine Sr, Os, Li and Ca today and changes in the weathered lithology or weathering intensity are invoked as major drivers of the evolution of trace metal concentrations and their isotopic compositions in seawater over time (e.g. Misra and Froelich, 2012; Kristall et al., 2017). ROKGEM, the weathering module of cGENIE, provides a framework for calculating climate- and CO2-dependent additions of Ca, Mg and alkalinity from carbonate weathering (following Berner, 1994) and silicate weathering (following Brady, 1991) to the ocean (see Colbourn et al., 2013, for a full description of the weathering module). The module calculates a drainage map based on a prescribed continental topography and determines the coastal locations where this input is added to the ocean. Depending on the primary source rock, we tied the rate M of Sr, Os or Li ion delivery to the ocean to Ca and magnesium (Mg) input rates from weathering of carbonates (CaCaCO3 ) and/or silicates

(CaCaSiO3 ), related by a constant ratio k (see table 4.5):

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(4.1) MCaCO kCaCO CaCaCO MCaSiO kCaSiO CaCaSiO 3 = 3 · 3 3 = 3 · 3

ROKGEM allows for different CaSiO3 weathering schemes, including one which separates the contribution from CaSiO3 weathering into contributions from granite and basalt weathering (’Wallmann’). For this case, we imposed individual parameters for Sr weathering for each lithology. The model does not consider secondary mineral formation on land, which should be taken into account by setting the parameters for terrestrial Li input based on run-off data rather than source rock composition. The amount and isotopic composition of weathering-derived Os is mostly dependent on organic matter content (Jaffe et al., 2002; Georg et al., 2013; Dubin and Peucker-Ehrenbrink, 2015). ROKGEM does not contain an explicit representation of organic matter weathering, and a differentiation between carbonate and silicate derived Os would not capture the lithology dependence of weathering derived Os appropriately. Hence, we decided not to differentiate the source lithology of Os in the model, but to prescribe the net abundance and isotopic composition of Os in continental run-off.

Table 4.5: Model parameters setting weathering-related trace metal fluxes. Parameter name default value unit description rg_par_weather_fracOs 0.0 mol/mol Os:[Ca+Mg] ratio in continental weathering

rg_par_weather_CaSiO3_fracLi 10.00E-6 mol/mol Li:[Ca+Mg] ratio in continental silicate weathering

rg_par_weather_CaSiO3_fracSr 0.00532 mol/mol Sr:[Ca+Mg] ratio in continental silicate weathering

rg_par_weather_CaSiO3b_fracSr 0.0057471 mol/mol Sr:[Ca+Mg] ratio in continental basalt weathering

rg_par_weather_CaSiO3g_fracSr 0.0050847 mol/mol Sr:[Ca+Mg] ratio in continental granite weathering

rg_par_weather_CaCO3_fracSr 0.002 mol/mol Sr:[Ca+Mg] ratio in continental carbonate weathering

4.3.2 Hydrothermal inputs

Mantle-derived metal input via hydrothermal vents is parameterised in the SEDGEM module. To represent the vast range of chemical conditions and reaction rates at the sediment-water interface in the ocean efficiently, three biogeochemically distinct depositional environments are represented in SEDGEM: (1) dynamic shallow seas with reef-building biota (’reef’), (2) organic rich sediments depleted in oxygen (’muds’), and (3) plankton-derived carbonate deposition in the open ocean (’deep sea’). CaCO3 deposition and dissolution as well as elemental fluxes across the sediment-water interface are parameterised differently in each of these environments, using masks to distinguish the different environments. Hydrothermal inputs of elements into bottom waters occurs only in grid cells which

56 4.3. MODEL IMPLEMENTATION represent ’deep sea’. We parameterised this flux such that a global total input flux can be prescribed, which is distributed equally across ’deep sea’ grid cells. There is no differentiation between seafloor areas with predominant high- or low-temperature hydrothermal venting in our implementation. Hence, we suggest to prescribe total hydrothermal metal fluxes with an average isotopic composition in cGENIE to account for both temperature regimes.

Table 4.6: Model parameters setting hydrothermal metal input. Parameter name default value unit description 1 sg_par_sed_hydroip_fOs 0.0 mol yr− global hydrothermal Os flux 1 sg_par_sed_hydroip_fLi 0.0 mol yr− global hydrothermal Li flux 1 sg_par_sed_hydroip_fSr 3.1E9 mol yr− global hydrothermal Sr flux 1 sg_par_sed_hydroip_fCa 0.0 mol yr− global hydrothermal Ca flux

4.3.3 Aeolian inputs

To account for inputs at the air-sea interface (only assumed to be relevant for Os, as described in the scientific background section), we added the option to prescribe a uniform or spatially explicit field of annual input into the surface ocean (or technically anywhere into the water column). This implementation follows the same equations of flux forcings for other marine tracers (e.g. oxygen) and is calculated as part of the BIOGEM module.

4.3.4 Metal export in carbonates

Ca export from the surface ocean is linked to the export of particulate organic carbon (POC) by a constant CaCO3:POC ratio (rain ratio) (see Ridgwell et al., 2007, for a description of POC export simulation in cGENIE). We parameterise the incorporation of Os, Li and Sr into carbonates by scaling their export in carbonates to the Ca export. This can be done by setting either a constant Sr/Li/Os-to-Ca ratio (rM/Ca) or a constant scaling factor α which links the local Sr/Li/Os-to-Ca ratio in seawater to the Sr/Li/Os-to-Ca ratio in the precipitate (following e.g. Tang et al., 2008):

(4.2) exportmetal k exportCa = ·

(4.3) k rM/Ca α [Metal]water/[Ca]water = + · The Sr/Li/Os-to-Ca ratio of the precipitate is then used to calculate the metal consumption during carbonate formation, as well as metal release during carbonate dissolution. To reflect the different Sr/Li/Os-to-Ca ratios in pelagic compared to reef carbonates, a separate factor can be set for reef production. Reef CaCO3 immediately contributes to surface sediments, while pelagically formed CaCO3 sinks through the water-column, and might be dissolved before reaching the ’deep sea’ sediment-water interface as a result of local chemical equilibria. cGENIE also calculates Li export by abiotically precipitated carbonates.

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Table 4.7: Model parameters setting the Os, Li and Sr contents of calcite shells. Parameter name default value unit description bg_par_bio_red_CaCO3_OsCO3 0.0 mol/mol pelagic Os:Ca ratio bg_par_bio_red_CaCO3_OsCO3_alpha 0.0 unit-less pelagic partition coefficient between Os and Ca bg_par_bio_red_CaCO3_LiCO3 0.0 mol/mol pelagic Li:Ca ratio bg_par_bio_red_CaCO3_LiCO3_alpha 1.0 unit-less pelagic partition coefficient between Li and Ca sg_par_bio_red_CaCO3_LiCO3 0.0 mol/mol benthic Li:Ca ratio sg_par_bio_red_CaCO3_LiCO3_alpha 0.005 unit-less benthic partition coefficient between Li and Ca bg_par_bio_red_CaCO3_SrCO3 0.0 mol/mol pelagic Sr:Ca ratio bg_par_bio_red_CaCO3_SrCO3_alpha 1.0 unit-less pelagic partition coefficient between Sr and Ca

4.3.5 Scavenging from the water-column

To test implications of Os burial with particulate organic carbon, we included an option for [O2]-sensitive scavenging from the water column. In the surface ocean, organic carbon is produced as a function of 3 the concentration of inorganic carbon, light, nutrient availability (PO4− in our set up), sea ice cover and temperature (Ridgwell, 2001). The produced organic carbon is split into dissolved and particulate organic carbon (DOC and POC) at an adjustable ratio. DOC is advected and diffused in the ocean and remineralized depending on a prescribed lifetime, while POC is instantly exported to deeper water layers and remineralized following a decay function tuned to POC flux measurements (Ridgwell, 2001). O2 is exchanged between the atmosphere and the ocean at the air-water interface, depending on the solubility of O2 in water. In the ocean, O2 is released during primary production in the surface ocean and consumed during remineralization of DOC and POC under oxic conditions. Following the example of existing scavenging parameterization schemes in cGENIE, we implemented this process by scaling the flux of scavenged Os (fscav) to the local concentrations of Os and POC:

(4.4) fscav k [Os] [POC] = · ·

Since there is evidence that Os needs to be reduced in order to be burried, we include a switch to use the scavenging code only where [O2] is below an adjustable threshold.

Table 4.8: Model parameters setting Os scavenging. Parameter name default value unit description bg_ctrl_Os_scav_O2_dep .false. N/A switch to turn on [O2]-dependency 1 bg_par_scav_Os_O2_threshold 5E-9 mol kg− [O2] threshold for [O2]-dependency 1 bg_par_bio_remin_kOstoPOMOS 0.0 1 mol− scaling factor for Os scavenging

58 4.3. MODEL IMPLEMENTATION

4.3.6 Clay formation

The model calculates Li burial during clay formation f Li clay locally at the sea-sediment interface, which is scaled to the concentrations of Li in the deepest grid box of the water column and the detrital flux into the sediments:

(4.5) f Li clay k [det] [Li] = · ·

Table 4.9: Model parameters for weathering-related trace metal fluxes. Parameter name default value unit description sg_par_sed_clay_fLi_alpha 0.0 kg/mol scaling factor relating Li burial to detrital flux and [Li]

4.3.7 Recrystallization

Recrystallization of SrCO3 is an additional source of Sr to the water column (see above). Its parameteri- sation is similar to that of hydrothermal inputs, except that elemental fluxes from recrystallization only occur in bottom waters of grid cells labelled as ’reef’. The size and rate of this Sr flux can be either set as a total global or an area-weighted value.

Table 4.10: Model parameters for Sr recrystallization. Parameter name default value unit description sg_par_sed_SrCO3recrystTOT 0.0 mol yr 1 Prescribed global SrCO3 − recrystlization rate

sg_par_sed_SrCO3recryst 0.0 mol cm 2 yr 1 Prescribed SrCO3 − − recrystlization rate

4.3.8 Rock alteration and metal deposition at the sea floor

We include the burial of Sr and Li into seafloor sediments due to seafloor weathering by scaling the metal flux into the uppermost sediment layer (f Metal) to the metal concentration of the overlying ocean gridbox ([Metal]):

(4.6) f Metal k [Metal] = · This burial occurs in all grid cells that are labelled as ’deep sea’. In the absence of better constraints on depositional mechanisms, we include a mathematically similar sink for Os. For a desired global burial 1 2 rate B (mol s− ), the value of k can be estimated by considering the total area of ’deep sea’ Adeep (m ) 1 and equilibrium metal concentration [Metal] (mol kg− ):

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B/Adeep (4.7) k = [Metal]

Table 4.11: Model parameters for metal deposition in sediments. Parameter name default value unit description 2 1 sg_par_sed_lowTalt_fLi_alpha 0.0 kg m− s− Li low temperature alteration sink rate 2 1 sg_par_sed_lowTalt_fSr_alpha 0.0 kg m− s− Sr low-T alteration sink rate 2 1 sg_par_sed_Os_dep 0.0 kg m− s− burial rate for Os

4.3.9 Isotopes

The isotopic composition of Sr, Os, Li and Ca sources to the ocean is prescribed, in delta notation for stable isotopes and ratios for radiogenic isotopes. Once in the ocean, cGENIE tracks isotopes in total molar abundances rather than delta notation or ratios so that they can be advected and diffused like any other tracer. For this approach, prescribed isotopic compositions of marine inputs are converted into molar isotope abundances which requires a standard for each isotope. The hard-coded standards are listed in table 4.12, and are either international standards or observations of modern-day sea water. Li isotopes are implemented similarly to stable C isotopes (Ridgwell, 2001). Sr, Os and Ca are different, because they have more than two principal stable isotopes. We chose to reduce the number of traced isotopes to three for Sr and Os and two for Ca, because these subsets contain the most abundant isotopes of the respective element (Sr) and/or are most relevant for their application as seawater proxies (Sr, Os and Ca). Calcium isotopes are thus treated similarly to Li isotopes. To track three isotopes rather than two, we track two isotopes explicitly and one implicitly with the bulk abundance of the trace metal. In the case of Sr, abundances of 87Sr and 88Sr are tracked explicitly. The abundance of 86Sr is then taken as the difference between the abundances of the two explicitly tracked isotopes and the bulk Sr abundance, since 84Sr can be neglected. Os has more than two stable isotopes, but only two of them, 187Os and 188Os, are currently used as a proxy system and so these two isotopes are tracked explicitly and the bulk Os abundance contains all remaining stable isotopes. To account for isotopic fractionation during chemical reactions, the amount f I of an isotope I transferred to the product-side of the reaction is calculated by multiplying the amount of Sr, Li or Ca involved in the reaction, f M, with the relative abundance k of I in the reaction product:

(4.8) f I k f M = ·

k is derived from the prescribed relative abundance of I in the reaction product in standard sea water, usually the observed isotopic signature of the respective reaction product in today’s ocean, and the difference between the local, simulated relative abundance of I in cGENIE and standard sea water.

60 4.3. MODEL IMPLEMENTATION

The model parameters required to set isotopic fractionation of Os, Li and Sr are listed in table 4.13. Given the current lack of evidence for Os isotopic fractionation outside of the lithosphere (e.g. Nanne et al., 2017) we do not include a fractionation factor for marine Os sinks. For Sr and Li, we include isotopic fractionation during carbonate and secondary mineral formation. We simplify the model by assuming constant fractionation factors as the influence of environmental factors on isotope partitioning is still debated. Growth rate-dependent fractionation factors could be implemented in the future by using the ecosystem module ECOGEM (Ward et al., 2018), but this will significantly increase computational costs.

Table 4.12: Isotopic standards in cGENIE. Isotope ratio standard value standard material/reference 87Sr/86Sr 0.709175 Mokadem et al.(2015) 88Sr/86Sr 8.375209 NBS987 187Os/188Os 1.05 Lu et al.(2017) 188 189 190 192 Os/ + + Os 0.159 D˛abekand Halas(2007) 7Li/6Li 12.33333 L-SVEC 44Ca/40Ca 0.021229 NIST SRM915aHeuser et al.(2002)

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Table 4.13: Model parameters for the representation of isotopes and isotopic fractionation. Parameter name default value unit description rg_par_weather_187Os_188Os 0.0 187Os/188Os of input from weathering 188 rg_par_weather_188Os_192Os 0.0 proportional Os abundance in input from weathering sg_par_sed_hydroip_fOs_187Os_188Os 0.0 187Os/188Os of hydrothermal input 188 sg_par_sed_hydroip_fOs_188Os_192Os 0.0 proportional Os abundance in hydrothermal input 7 bg_par_d7Li_LiCO3_epsilon 4.0 % δ Li fractionation for pelagically formed carbonate 7 sg_par_d7Li_LiCO3_epsilon -2.0 % δ Li fractionation for neritically formed carbonate

sg_par_sed_hydroip_fLi_d7Li 4.0 % δ7Li of hydrothermal input sg_par_sed_lowTalt_7Li_epsilon -15.0 % δ7Li of sea floor alteration sink sg_par_sed_clay_7Li_epsilon -15.0 % δ7Li of clay 7 rg_par_weather_CaSiO3_Li_d7Li 0.0 % δ Li of input from silicate weathering 88/86 bg_par_d88Sr_SrCO3_epsilon -0.236 % δ Sr fractionation for pelagically formed carbonate 88/86 sg_par_d88Sr_SrCO3_epsilon 0.9 % δ Sr fractionation for neritically formed carbonate sg_par_r87Sr_SrCO3recryst 0.70838 87Sr/86Sr of input from recrystallization

sg_par_d88Sr_SrCO3recryst 0.172 % δ88/86Sr of input from recrystallization sg_par_sed_hydroip_fSr_r87Sr 0.7025 87Sr/86Sr of hydrothermal input

sg_par_sed_hydroip_fSr_d88Sr 0.24 % δ88/86Sr of hydrothermal input rg_par_weather_CaSiO3_r87Sr 0.714 87Sr/86Sr of silicate weathering 87 86 rg_par_weather_CaSiO3b_r87Sr 0.705 Sr/ Sr of basaltic silicate weathering 87 86 rg_par_weather_CaSiO3g_r87Sr 0.719 Sr/ Sr of granitic silicate weathering rg_par_weather_CaCO3_r87Sr 0.7077 87Sr/86Sr of carbonate weathering

rg_par_weather_CaSiO3_d88Sr 0.36 % δ88/86Sr of silicate weathering 88/86 rg_par_weather_CaSiO3b_d88Sr 0.36 % δ Sr of basaltic silicate weathering 88/86 rg_par_weather_CaSiO3g_d88Sr 0.36 % δ Sr of granitic silicate weathering

rg_par_weather_CaCO3_d88Sr 0.16 % δ88/86Sr of carbonate weathering rg_par_weather_CaCO3_d44Ca 0.8 % δ44Ca of carbonate weathering rg_par_weather_CaSiO3_d44Ca 0.8 % δ44Ca of silicate weathering sg_par_sed_hydroip_fCa_d44Ca 0.9 % δ44Ca of hydrothermal input 44 sg_par_d44Ca_CaCO3_epsilon -1.07 % δ Ca fractionation 62 for neritically form carbonates 44 bg_par_d44Ca_CaCO3_epsilon -1.09 % δ Ca fractionation for pelagically form carbonates 4.4. MODEL CONFIGURATION AND VALIDATION

4.4 Model configuration and validation

Box models are important tools to investigate the global balance of elemental and isotopic fluxes and essential to estimate elemental residence times as well as to identify missing sinks and sources (e.g. Stoffyn-Egli and Mackenzie, 1984). They are usually validated with observed average seawater compositions (e.g. Krabbenhöft et al., 2010; Misra and Froelich, 2012; Pearce et al., 2015). The three-dimensional grid of cGENIE allows for comparison of the spatial pattern produced by the simulated set of processes to observations, which can further bolster or refute the accuracy of our assumptions about global trace metal cycling on diverse time scales. Here we set up the model to represent the pre-industrial state of trace metal cycling, and compare the model output to measured modern seawater profiles.

4.4.1 Pre-industrial configuration

We initialised cGENIE with a modern-day geography on a 36x36 grid with up to 8 depth layers in

the ocean (following Ridgwell and Hargreaves, 2007) and with a pre-industrial CO2 concentration of 278 ppm. Marine biological productivity is simulated using a single nutrient scheme as outlined in

Ridgwell et al.(2007) but with a constant CaCO 3:POC rain ratio set to 0.043 (Panchuk et al., 2008).

Burial and dissolution of CaCO3 in deep-sea sediments follows Ridgwell and Hargreaves(2007). This 1 configuration results in a pelagic CaCO3 burial rate of 0.125 GtC yr− , close to the observationally

calibrated CaCO3 sink of Ridgwell and Hargreaves(2007). In addition to the pelagic environment, covering 350.6 million km2, we simulated reef deposition on shelfs, which covers 5.5 million km2 in our set up. The sediment model bathymetry was derived from ETOPO51. Reefal deposition was simulated in

grid cells representing marine sediments shallower than 1000 m and not further pole-wards than 41.8◦ N/S, on the basis that reefal carbonate deposition is predominantly a tropical and subtropical process. We 1 prescribe a reefal CaCO3 sink of 0.04 GtC yr− . Temperature dependent terrestrial silicate and carbonate

weathering (Lord et al., 2016) were included with the baseline temperature and rates of CaCO3 and 1 1 CaSiO3 weathering set to 8.48◦C, 8.4 Gmol yr− and 6.0 Gmol yr− , respectively. Silicate weathering

was split into weathering of CaSiO3 (2/3) and MgSiO3 (1/3). We balanced the Ca cycle by including 1 an exchange between sedimentary Ca and dissolved Mg of 2.0 Gmol yr− at the seafloor. To close the 1 13 long-term carbon cycle, we prescribed a fixed rate of organic C burial of 2.57 Gmol yr− with δ C = 1 13 -30 % as well as a total exogenic carbon flux of 8.57 PgC yr− with δ C = -6 %. This net input can be 1 13 regarded as the result of 8.57 PgC yr− sub-aerial outgassing with δ C = -4.6 % (Mason et al., 2017), 1 13 hydrothermal emissions of 1.5 PgC yr− with δ C = -6 % at mid-ocean ridges and consumption of 1.5 1 13 PgC yr− with δ C = 2 % during seafloor weathering (Cocker et al., 1982). Table 4.14 summarizes the trace metal fluxes we prescribe to simulate the pre-industrial trace metal cycling. Note that the prescribed hydrothermal metal fluxes are net fluxes of high- and low-temperature hydrothermal activity.

1Data Announcement 88-MGG-02, Digital relief of the Surface of the Earth. NOAA, National Geophysical Data Center, Boulder, Colorado, 1988.

63 CHAPTER 4. INCLUSION OF A SUITE OF WEATHERING TRACERS IN THE CGENIE EARTH SYSTEM MODEL - MUFFIN RELEASE V.0.9.10

By applying the chosen model parameters for our spin-up with modern boundary conditions and running the model to steady state, we assumed that metal fluxes are currently in equilibrium. This is a common assumption when modelling weathering tracer isotopes and their perturbations in the geologic record (e.g. Misra and Froelich, 2012; Bauer et al., 2017a). However, given the long residence time estimates in today’s ocean, it is likely that at least the Sr, Li and Ca cycles are not fully in steady state today (i.e. Derry, 2009). Constant Os isotopic compositions of seawater over the last millennia suggest that Os has reached steady state since the last deglaciation, but residence time estimates of >20 kyr based on modern day Os fluxes put this into question (Oxburgh, 2001). The newly implemented tracers in cGENIE can be used to study different equilibria and transient adaptations of the marine metal reservoirs to new boundary conditions. As an example, we simulated two different steady states for Sr under pre-industrial boundary conditions: One with a best estimate of pre-industrial Sr fluxes (hereafter referred to as FLUXES) and one tuned to best fit the spatial mean of observations (TUNED).

Table 4.14: Metal fluxes for pre-industrial spin up. 1 Flux size (mol yr− ) isotopic composition Strontium 87Sr/86Sr δ88/86Sr (%) weathering FLUXES 34.0x109 0.7122 0.318 TUNED 31.0x109 0.7097 0.256 hydrothermal input 3.1x109 0.7038 0.261 diagenetic input FLUXES 3.4x109 0.708 0.385 TUNED 3.4x109 0.7087 0.256 carbonate sink FLUXES 40.5x109 seawater seawater - 0.18 TUNED 37.5x109 seawater seawater - 0.18 Osmium 187 188 188 189 190 192 Os/ Os Os/ + + Os weathering 2605.26 1.2 0.159 hydrothermal input 526.32 0.5625 0.159 aeolian input 157.89 0.2 0.159 sediment deposition 3289.47 seawater seawater carbonate sink 0.0 seawater seawater Lithium δ7Li (%) weathering 8x109 23.0 hydrothermal input 6x109 8.3 secondary mineral formation sink 4x109 seawater -15.0 sea floor alteration sink 9.5x109 seawater -15.0 carbonate sink 0.5x109 seawater - 4 Calcium δ44Ca (%) weathering 12.4x1012 0.9 hydrothermal input 2x1012 0.93 carbonate sink 14.4x1012 seawater - 1.1

64 4.4. MODEL CONFIGURATION AND VALIDATION

The spin up was done in three stages to improve computational efficiency. The first stage (20 kyr) was run with a closed marine carbonate system, where the marine C and alkalinity reservoirs are artificially restored by balancing losses through CaCO3 burial with external inputs to the ocean. During this stage, the climate and ocean dynamics adjust to the physical boundary conditions and ocean-atmosphere C exchanges balance. In the second phase (500 kyr) the marine carbonate system was open so that prescribed inputs from terrestrial weathering and the mantle and marine burial dynamically adjusted to balance. During the third stage (15 Myr), when ocean dynamics, C, nutrient and Ca cycles were already equilibrated, the prescribed Sr, Os and Li sources were added and the model was run until metal concentrations and their isotopic composition in the ocean were at steady state. The model calculations were accelerated during the last two stages of the spin up using the time-stepping method introduced by Lord et al.(2016).

4.4.2 Comparison between simulated and observed trace metal contents of seawater

One advantage of simulating trace metal cycles within a 3D earth system model is that we can test, for the first time, simulated metal concentrations and isotopes against observed spatial patterns. In the following sections, the simulated pre-industrial distribution of each metal is compared against observational data shown in section 4.2.5.

4.4.2.1 Strontium

65 CHAPTER 4. INCLUSION OF A SUITE OF WEATHERING TRACERS IN THE CGENIE EARTH SYSTEM MODEL - MUFFIN RELEASE V.0.9.10

Figure 4.3: Comparison between measured and simulated Sr composition of seawater. Shown are measured Sr concentrations and isotope ratios and the values of all ocean grid cells from the model simulations, sorted by value from smallest to biggest. Mean concentrations and isotope ratios are indicated by horizontal lines, and shading indicates one standard deviation around the means. Data is taken from Angino et al.(1966), Fabricand et al.(1967), Bernat et al.(1972), Brass and Turekian(1974), De Villiers(1999), Mokadem et al.(2015) and Wakaki et al.(2017).

Figure 4.3 compares Sr concentrations and isotopic compositions in our simulation with observations. Standard deviations tend to be smaller in the model simulations than in observations. This is particularly true for Sr concentrations which are more homogeneous in the simulations than in observations. Measured isotopic compositions of Sr in seawater are very homogeneous, which is matched by the model simulations. The FLUXES simulation, in which we constrain2 fluxes rather than the marine reservoir with observations, results in higher than observed Sr concentrations in seawater, and a more radiogenic and isotopically heavy composition. Uncertainties in size and isotopic composition of pre-industrial Sr fluxes are big enough to allow for realistic combinations that lead to equilibrated Sr concentrations close to observations (TUNED simulation) but continental input needs to be less radiogenic than the average of today’s rivers to yield a steady state marine 87Sr/86Sr close to observations (in agreement with e.g.

Pearce et al., 2015). The observed fractionation factor for stable Sr isotopes during biogenic CaCO3 formation is too big to equilibrate the model at the observed low δ88Sr, even if we assume that all Sr sources only provide mantle-like light Sr (δ88Sr = 0.256%, TUNED simulation). Corroborating the conclusion of e.g. Vance et al.(2009), this suggests that the isotopic composition of marine dissolved Sr

66 4.4. MODEL CONFIGURATION AND VALIDATION is currently not at equilibrium. The simulations capture the homogeneous distribution of Sr concentrations observed at most site (see figures B.1 and B.2 in the SI). However modelled Sr concentrations are higher than observed in some studies of North Atlantic water. Given that the low North Atlantic values come from one of the first studies measuring Sr concentrations in seawater (Angino et al., 1966), and that other studies of North Atlantic seawater yielded higher Sr concentrations (e.g. De Villiers, 1999), this difference could be partially the result of analytical errors or seasonal/inter-annual variability.

4.4.2.2 Osmium

Figure 4.4: Comparison between measured and simulated Os composition of seawater. Shown are all available measured Os concentrations and isotope ratios and the values of all ocean grid cells in the simulation, sorted by value from smallest to biggest. Mean concentrations and isotope ratios are indicated by horizontal lines, and shading indicates one standard deviation around the means. Data is taken from Levasseur et al.(1998), Woodhouse et al.(1999) and Gannoun and Burton(2014).

Os concentrations and isotopes are generally more homogeneous in the simulation than in the observations. While the model captures the range of 80% of the measured Os concentrations and isotopic compositions well, it fails to reproduce the lowest 20% of measurements, especially with respect to Os concentrations. The low Os concentrations not captured by the model are observations from surface and intermediate waters from the East Pacific (fig. B.3, Woodhouse et al., 1999; Gannoun and Burton, 2014). Since the depletion of Os in Pacific surface waters is a robust feature against measurement methods, this indicates that some processes affecting Os distribution in that region might be missing in our model. For example, Woodhouse et al.(1999) suggested that Os could bind onto organic matter in the water column under low oxygen conditions. cGENIE provides the necessary framework to investigate this and other assumptions, which should be the subject of a separate study. Our aim here is to focus on reproducing the basin-scale distribution in trace metals. Observations from other sites show no vertical Os concentration gradients, which is well-reproduced by our simulation set-up. The isotopic Os composition shows a uniform vertical distribution in the simulations, which is consistent with observations at all sites (see figures B.3b). 3

67 CHAPTER 4. INCLUSION OF A SUITE OF WEATHERING TRACERS IN THE CGENIE EARTH SYSTEM MODEL - MUFFIN RELEASE V.0.9.10

4.4.2.3 Lithium

Figure 4.5: Comparison between measured and simulated Li composition of seawater. Shown are all available measured Li concentrations and isotope ratios and the values of all ocean grid cells in the simulation, sorted by value from smallest to biggest. Mean concentrations and isotope ratios are indicated by horizontal lines, and shading indicates one standard deviation around the means. Data is taken from Angino and Billings(1966), Fabricand et al.(1967), Chan(1987), Chan and Edmond(1988), You and Chan(1996), Moriguti and Nakamura(1998), Tomascak et al.(1999), James and Palmer(2000), Košler et al.(2001), Nishio and Nakai(2002), Hall(2002), Bryant et al.(2003), Pistiner and Henderson(2003), Millot et al.(2004), Choi et al.(2010), Pogge von Strandmann et al.(2010), Phan et al.(2016), Lin et al. (2016), Henchiri et al.(2016), Weynell et al.(2017), Fries et al.(2019), Gou et al.(2019), Hindshaw et al.(2019), Murphy et al.(2019) and Pogge von Strandmann et al.(2019).

Similar to Sr and Os, the model simulates more homogeneous Li concentrations and isotopic compositions than is observed for most of the ocean (see fig. 4.5). The simulated standard deviation around the spatial mean of Li concentrations is only 8% of that observed. The lowest and highest 20% of observed Li concentrations is not reproduced by our simulation set-up. Similarly, there are no spatial gradients in the simulated isotopic composition of dissolved Li, while observations show some spread. Given relatively large analytical uncertainty, it is more likely that this results from measurement inconsistencies rather than unknown processes affecting the isotopic composition of dissolved Li. The high concentrations which are underrepresented in our simulation were mostly measured in the upper water column (see fig. B.4). As shown in fig. B.1, these measurements all come from one study in the Caribbean Sea (Angino and Billings, 1966), a marginal4 ocean which is not representative of the open ocean and which can barely be resolved in the coarse grid of cGENIE. Additionally, Angino and Billings (1966) was one of the first studies measuring Li concentrations in seawater, and their measurements may be associated with much larger uncertainties than reported. Were these measurements excluded, the spatial mean of observed Li concentrations would be lower, and the model could be re-tuned by prescribing slightly lower Li fluxes in- and out of the ocean which are permissible given the current range of flux estimates (see table 4.3). Only one measured vertical profile of Li isotopes is available in the literature (Hall, 2002), and it shows no vertical δ7Li variation which is reproduced by our simulation. The simulated 7Li is offset from the profile reported by Hall(2002) since we tuned the model to the average of reported seawater 7Li

68 4.4. MODEL CONFIGURATION AND VALIDATION measurements but the profile in Hall(2002) contains some of the most 7Li enriched published seawater values.

4.4.2.4 Calcium

Figure 4.6: Comparison between measured and simulated Ca composition of seawater. Shown are all available measured Ca concentrations and isotope ratios and the values of all ocean grid cells in the simulation, sorted by value from smallest to biggest. Mean concentrations and isotope ratios are indicated by horizontal lines, and shading indicates one standard deviation around the means. Data is taken from Fabricand et al.(1967), De Villiers(1999) and Fantle and Tipper(2014).

Simulated concentrations of dissolved Ca and its homogeneous isotopic composition closely resemble the observations. Similar to the average Ca concentration in seawater, the uniform vertical distribution is well captured by the model simulation (see fig. B.5). Likewise, no vertical Sr/Ca gradients are observed or simulated. Observed Sr/Ca ratios are in between simulation results with tuned and un-tuned marine Sr reservoir. This is an artefact of the tuning to mean observed Sr concentrations which is lower than the mean Sr concentrations of the sites shown in figure B.5 because it includes the unusually depleted samples from the North Atlantic. This mismatch is another indication that the Sr measurements reported in Angino et al.(1966) might be associated with a larger uncertainty than reported.

4.4.3 Transient perturbation experiments

Another advantage of the new metal cycles in cGENIE is that we can study their transient behaviour under external forcings in a fully coupled system, including effects from ocean circulation and primary productivity changes, climate-sensitive weathering and marine carbonate accumulation and dissolution. 5 Here we present one example, where we instantly release either 1000 Pg C or 5000 Pg C into the atmosphere to produce temporary weathering responses which re-equilibrate the model (similar to Lord et al., 2016). These scenarios allow us to showcase the sensitivity of the simulated metal systems and to discuss the Earth system processes that shape their transient evolution. Since our experiment are set up to understand model behaviour, it is of less concern here whether these scenarios cause isotopic perturbations beyond the analytical uncertainty of real-world measurements.

69 CHAPTER 4. INCLUSION OF A SUITE OF WEATHERING TRACERS IN THE CGENIE EARTH SYSTEM MODEL - MUFFIN RELEASE V.0.9.10

Table 4.15: Marine trace metal concentrations and residence times in our pre-industrial spin up compared to those reported in literature (see scientific background).

mean concentration simulated estimated Metal 1 (mol kg− ) residence time (kyr) residence time (kyr) 6 Strontium FLUXES 92.84 10− 2,100 1,900–3,450 × 6 ∼ Strontium TUNED 86.50 10− 1,960 1,900–3,450 × 15 ∼ Osmium 52.64 10− 21,5 3–50 × 6 ∼ Lithium 27.00 10− 2,600 300–3,000 × 3 ∼ Calcium 10.25 10− 960 500–1,300 × ∼

In our spin-up, the prescribed metal fluxes result in residence times within the range of published estimates (table 4.15). Li has the longest residence time in our simulations, and thus the largest inertia to external perturbations. Sr and Ca follow, with Os being the most responsive system.

a) Concentrations and temperature b) Isotopes in seawater

Figure 4.7: Transient changes in modelled Sr, Os, Li, Ca, composition of seawater and atmospheric CO2 and temperature following instant releases of 1000 Pg C and 5000 Pg C. Shown are changes a) in concentrations, and b) in isotopic composition of seawater.

Fig. 4.7 shows the modelled transient responses of Sr, Os, Li, Ca concentrations and isotopic 13 compositions, DIC δ C, atmospheric CO2 and temperature to an exogenic CO2 pulse. After the 13 instantaneous carbon release, atmospheric CO2 concentration increases and the δ C of seawater decreases on the timescale of years. The sudden increase in atmospheric CO2 concentrations replenishes the marine carbon reservoir, which decreases biogenic carbonate formation in the surface ocean and leads to the dissolution of pelagic carbonates. Over the next 10,000 yrs, this negative carbon cycle ∼ feedback removes the majority of the initial excess carbon (Lord et al., 2016). Increased atmospheric

70

6 4.4. MODEL CONFIGURATION AND VALIDATION

CO2 also enhances the greenhouse effect and thus leads to a rise in global mean air temperature, altering the hydrological cycle and speeding up reaction rates which result in increased rates of continental crust weathering. After a few ten thousands of years, increased continental weathering supplies enough alkalinity to the ocean to slow down carbonate dissolution and increase carbonate burial. Through enhanced silicate weathering and carbonate burial, the remaining excess carbon is sequestered over the timescale of 100,000 yrs after the emission. Over the same timescale, temperature, which due to ∼ Earth system feedbacks initially recovers more slowly than atmospheric CO2 concentrations, returns to pre-emissions values and ends the phase of enhanced weathering. Metal input from continental weathering (and marine carbonate dissolution for Sr and Ca) leads to a transient growth of marine metal reservoirs and isotopic excursions. Increased continental weathering increases the influx of radiogenic Sr and Os, driving the respective marine reservoirs to more radiogenic isotopic compositions. Continental crust is also depleted in heavy stable isotopes compared to seawater, and the increased weathering influx therefore reduces the δ88Sr, δ7Li and δ44Ca values of seawater. The isotopic composition of carbonates and silicates in continental crust is fixed in our set-up, but since carbonate and silicate weathering rates vary differently with climate, the isotopic composition of weathering-derived marine input varies for metals with different isotopic compositions in these lithologies. For example, the radiogenic Sr excursion in the ocean is amplified by a transient increase in 87Sr/86Sr of weathering-derived Sr. Since more 2 alkalinity than Ca + is derived from continental weathering in our set-up, the climate-driven increase in 2 weathering results in a transient imbalance between alkalinity and Ca + supplies which does not appear 2 in C cycle simulations without an igneous Ca + source at the seafloor (e.g. Lord et al., 2016; Vervoort et al., 2019). The imbalance is small (10% of the Ca input at its peak) but cumulatively the unbalanced alkalinity supply is large enough to causes a slight reduction of the steady-state marine Ca and Sr reservoirs (by 0.5% following the emission of 5000 Pg C). Our assumption of a climate-insensitive ∼ 2 Ca + source at the seafloor is a simplification since there is evidence that this flux depends on bottom water properties, in particular temperature (e.g. Krissansen-Totton and Catling, 2017). However, the 2 climate sensitivity of this Ca + flux is lower than that from continental weathering (Brady and Gíslason, 1997) and temperature change is dampened in the deep ocean. In our transient simulations this would 2 mean that Ca + supply from the seafloor would increase less than from the continent, were this climate sensitivity to be included in the model. Without this additional feedback, our set-up thus produces an 2 upper limit for a transient imbalance between alkalinity and Ca + supplies which is the consequence of 2 decoupled alkalinity and Ca + sources with different climate sensitivities.

In the presented simulations, only the radiogenic 87Sr/86Sr excursion amplitude is larger than measurement uncertainty in present-day seawater (see figures 4.3– 4.6). Stronger or prolonged climate change, or a more sensitive weathering regime, would be required to produce detectable weathering changes in the other isotope systems. However, our simulation results still illustrate the different responses of all five isotope systems to a sudden carbon injection. The timings of excursion peaks and minima differ strongly between the isotope systems. The radiogenic 187Os/188Os and negative δ88Sr and δ44Ca excursions peak a few tens of thousands of years after the C injection, while the radiogenic 87Sr/86Sr and

71 CHAPTER 4. INCLUSION OF A SUITE OF WEATHERING TRACERS IN THE CGENIE EARTH SYSTEM MODEL - MUFFIN RELEASE V.0.9.10 negative δ7Li excursions take hundreds of thousands of years to reach their full amplitude. These time lags result from different residence times and fractionation processes: With the shortest residence time, estimated both from present-day inventories and in our simulation (see table 4.15), Os is the first metal to re-equilibrate after the perturbation. The excursions in Os concentration and isotopes are only driven by enhanced weathering rates, and thus both recover within 300 kyrs once atmospheric temperature, and with it continental weathering rates, decrease sufficiently. The radiogenic 87Sr/86Sr excursion, however, continues to grow until weathering rates have fully returned to pre-event levels because concentration-dependent Sr sinks adapt more slowly to enhanced continental Sr input as a result of the longer residence time. The re-equilibration of the marine Sr reservoir is substantially slower than that of the Os reservoir for the same reason. However, the removal of marine Sr is also dependent on carbonate chemistry, since marine carbonate preservation constitutes the largest marine Sr sink. Biogenic carbonate preservation initially decreases because of the pH drop following the C injection, but it increases during the C cycle recovery as a result of enhanced weathering-related alkalinity input. The increased marine carbonate burial causes the marine Ca reservoir to re-equilibrate on a similar timescale to Os although Ca has a substantially longer residence time in our spin-up. The effect is not strong enough to stop the growth of the marine Sr reservoir but it reduces its growth rate. Isotopic fractionation of Ca and Sr during biogenic carbonate formation enhances the speed of the δ44Ca recovery and stops the δ88Sr excursion from growing, despite continued excess input of isotopically light continental Sr. Li has the longest residence time of the four metals in our simulations and Li burial is only dependent on the marine Li concentration and a constant detrital flux, not carbonate chemistry. Hence, the marine Li reservoir continues to grow until all excess weathering stops. Once more dissolved Li is buried than added to the ocean, i.e. the marine Li reservoir shrinks, the δ7Li trend is reverses because excess sources of isotopically light Li cease and isotopically light Li is preferentially buried during clay formation, enriching seawater in the heavier 7Li. In the longer term, stable isotope fractionation during the removal of excess Sr, Li and Ca from the ocean results in transient positive δ88Sr, δ7Li and δ44Ca excursions which, in the case of Sr and Li, last for several million years. In our simulations, the staggered timings of the 187Os/188Os and 87Sr/86Sr excursion peaks, as well as the δ44Ca and δ7Li excursion minima, are thus predominantly the result of different elemental residence times while enhanced carbonate burial is the main reason for the time lag between δ7Li and δ88Sr and the coincidence of the excursion minima of δ88Sr and δ44Ca.

4.5 Conclusion

Sr, Os, Li and Ca isotope records can help identify mantle activity and lithological responses to climate change in the geological record if processes governing their distribution in the ocean and their response to geological perturbations were well understood. Our implementation of the marine cycling of Sr, Os, Li and Ca in the Earth system model cGENIE allows us to investigate these processes and their consistency with observations. Simulating pre-industrial Sr, Os, Li and Ca distributions in the ocean, the model

72 4.5. CONCLUSION achieves slightly more homogeneous fields than observed, but consistent with the widely used assumption of homogeneous metal isotope distributions in a fully equilibrated state (e.g. Elderfield, 1986; Chan and Edmond, 1988). It reproduces the mostly homogeneous mean observed depth profiles of concentrations and isotopic compositions well, but partially deviates from local observations. This could be an artefact of measurement uncertainties, non-equilibrated cycles in today’s ocean or local processes not resolved or parameterised in cGENIE. We showed how the new cGENIE tracers thus provide an opportunity to investigate the consistency between reported metal compositions in the ocean and marine sources and sinks, and between different ocean basins. Further investigations of the differences between cGENIE simulations and observations have thus the potential to improve our understanding of present-day marine trace metal cycling. Furthermore, the new implementation can be used to study the response of these metal cycles to transient environmental change. As an example, we show how these systems react to a sudden CO2 release through perturbation to their input and output fluxes on different timescales. cGENIE thus becomes a valuable tool to improve our understanding of Sr, Os, Li and Ca isotopes and distributions in today’s ocean, and to quantitatively interrogate the environmental signals of these isotope systems as preserved in sedimentary records.

73

.Tefis ieteiec o ls temporal close a for evidence direct first The 2018). al., et Percival 1998; , Kerr 1989; Weissert, 1987; ocnceutosi h at hyas epdcntantesz ftecrepnigenvironmental corresponding the of size the constrain helped also They past. the in eruptions volcanic niain fevrnetlcag ntelte a eue osuyErhsse mat fps LIP past of impacts system Earth study to used globe, be the can across latter from it the records makes in sedimentary composition change in environmental metal emplacements of sedimentary LIP indications the localized Since of phases 2018). identify al., to et explored possible Percival been have (e.g. concentrations 2 purpose Hg OAE Recently, same and 2009). the 1a al., OAE for et the Tejada to 2008; volcanism Creaser, large-scale and of Os (Turgeon start radiogenic onsets the responsive connecting more in pseudo-global The pivotal 1994). the been al., have between et isotopes correlation (Jones excursions stratigraphic Sr the unradiogenic and was OAEs activities Mesozoic LIP al., and et OAEs (Arthur between strata OAE link Mesozoic and basalts LIP on reconstructions causal age suggested strata of OAE the in uncertainty prove markers the to volcanic of impossible without because Courtillot OAEs is projectiles, Mesozoic it and or example, volcanism ash For tectonic between 2015). (e.g. relationship al., LIP et the Percival to contain 2003; to related Renne , afield eruptions and far volcanic too often of sediments evidence marine physical are in change direct buried environmental instead for is tracers information containing This sediments preserved. environmental formation, rarely its LIP and event of volcanic location the the of At records impact: physical crucial between is mismatch composition spatial Igneous metal Large the sedimentary of of in because impact signals environmental volcanic global the of of preservation study The the (LIPs). Provinces in tools important them made big which of forcing fingerprints global and regional determine to used been have isotopes and concentrations Metal LIP during changes C-cycle of tracers as isotopes Metal 5.1 nepeigsrnim sim ihu n acu isotopic calcium and lithium osmium, strontium, Interpreting emplacements xusosdrn I emplacements LIP during excursions 75

C h a p t e r 5 CHAPTER 5. INTERPRETING STRONTIUM, OSMIUM, LITHIUM AND CALCIUM ISOTOPIC EXCURSIONS DURING LIP EMPLACEMENTS volcanism. For example, stable Li and Ca isotopes are used to identify periods of enhanced continental weathering (Blättler et al., 2011; Von Strandmann et al., 2013; Lechler et al., 2015), proposed to have been instrumental for the replenishment of the marine nutrient reservoir during periods of enhanced organic C burial (Jenkyns, 2010).

Based on the implied temporal coincidence of isotopically-distinct metal injections and igneous C emissions and weathering changes, metal isotope excursions have also been employed as indirect proxies on contemporaneous C-cycle perturbations: Assuming a quantitative link between C emissions, weathering change and metal inputs, they have been used as quantitative constraints on C degassing and the enchained environmental disruption (Tejada et al., 2009; Blättler et al., 2011; Von Strandmann et al., 2013; Lechler et al., 2015; Bauer et al., 2017a). However, the results of these studies are associated with large uncertainties. Firstly, these studies employ isotope mixing models to infer the size of excess metal fluxes from isotopic excursions. These models do not account for C-cycle changes which perturb metal isotope systems. For instance, although transient changes in metal inputs from continental crust depend on climate, and thus should respond to an injection of excess igneous C, decoupled isotope mixing models do not account for a quantitative relationship between magmatic and continental metal fluxes through the C-cycle. Instead, the strengths of metal fluxes from different sources in these models are independent. As a result, metal flux estimates are commonly produced by varying one metal flux until the observed excursion can be reproduced, while keeping all other fluxes constant. It can be argued that this is justifiable for short volcanic events because of the time lag between the isotopic forcing from the eruption and weathering changes caused by the slow response rate ( 10 – 100 kyr) of terrestrial weathering to ∼ climate change (e.g. Lord et al., 2016). However, both isotopic forcings - volcanism and weathering - affect seawater metal isotope composition on geological timescales during periods of extended igneous activity. For example, it was shown that, on time scales of millions of years, the size of unradiogenic Sr isotope excursions due to enhanced mantle emissions is limited by the isotopic effect of the continental weathering feedback (Goddéris and François, 1995). LIP emplacements happen on timescales of 100 kyr – 1 Myr, and thus volcanic forcing and environmental response might have overlapped temporally during these events. Significant isotopic forcings from excess mantle emissions and enhanced continental crust weathering is even more likely given the large estimated increases in continental weathering during OAE 1a and OAE 2 of up to 4 pre-event values (Blättler et al., 2011). Secondly, quantitative studies × based on metal isotope excursions assume fixed ratios of C emissions to metal release (C:Metal) during LIP emplacements, which are poorly constrained. The chemical composition of magmas, and thus their concentrations of CO2 and metals, depends on their location of origin in the mantle and their ascent history (Moore and Bodnar, 2019). However, unlike metal release, the degassing of CO2 also depends on ambient pressure. Hence, the C:metal ratio is expected to be different and temporarily variable for LIPs emplaced in different environments, even if the erupting magma has identical volatile concentrations. In particular, this might have resulted in very different volatile emissions for subaerial and subaqueous LIP emplacement (Jones et al., 2016). Depending on the composition of pre-existing lithology (country rock) at the site of LIP emplacement, intrusion and contact-metamorphism may volatilize additional C

76 5.2. METHODS or sedimentary metals (Ganino and Arndt, 2009), further complicating the relationship between C and metal release and altering the net isotopic composition of metals released by the igneous event. Thirdly, while C degassing is an immediate consequence of the surfacing of fresh magma, metal release predominantly happens during chemical alteration of fresh basalt. In the absence of recent LIP emplacements, basalt alteration at mid-ocean ridges and in ocean crust is arguably the closest observable analogue for submarine tholeiitic ocean plateau weathering (see methods below). In these settings, the rates of metal release from basalt alteration depend largely on ambient temperature and are very different to the quasi-instantaneous C release: While high-temperature alteration of fresh basalt emits metals within months of the emplacement, low-temperature alteration leads to mantle-like metal release over millions of years without further C emissions (see reviews in German and Von Damm, 2006; Coogan and Gillis, 2018). This long-term, post-eruption alteration of LIPs also depends on the weathering environment, with high alteration rates on land and in low latitudes and low (but potentially longer-lasting) alteration rates in submarine settings (Coogan and Gillis, 2018; Johansson et al., 2018). Basalt alteration is evident at various LIPs (e.g. Banerjee et al., 2004; Johansson et al., 2018) and it has been suggested that the resulting chemical transformation of seawater had sizeable impacts on marine C and metal reservoirs (Jones and Jenkyns, 2001; Johansson et al., 2018), including their isotopic composition (e.g. Goddéris et al., 2017). It is unclear if phases of high- and low-temperature alteration, and thus phases of C emission and C sequestration, can be distinguished in the metal isotope record (e.g. Jones and Jenkyns, 2001). The question thus arises whether and how the isotopic composition of metals in seawater can record C cycle changes during episodes of enhanced mantle emissions such as LIP emplacements. Metal isotope excursions resulting from LIP emplacement have previously been interpreted as isotopic fingerprints of igneous C emissions or weathering events, but the coupled metal- and C-cycles available in cGENIE (chapter4) enables the testing of the relative importance of these forcings on the evolution of metal isotope excursions for the first time. By analysing the simulated effects of coupled and de-coupled C and metal injections, I will discuss in this chapter how metal isotope excursions could facilitate qualitative and quantitative constraints on the C forcing resulting from a LIP emplacement and identify the biggest sources of uncertainty.

5.2 Methods

LIP emplacements occurred throughout geologic time (Ernst, 2014) in various geographic, tectonic and biogeochemical settings. Based on different source mantle regions and chemical histories of erupted magma, as well as physical and sedimentary eruption environments, the size and composition of elemental fluxes associated with LIP formation vary from one event to another. Here, I have not attempted to simulate a specific geologic event, but rather investigate the isotopic effects of sustained mantle emissions considering coupled cycling of C, Sr, Os, Li and Ca. For this purpose, I simplified the experimental design in two major ways: Firstly, I ran the experiments in the modern-day configuration, starting from the model spin-up developed in chapter4. The modern-day Earth system state provides geochemically

77 CHAPTER 5. INTERPRETING STRONTIUM, OSMIUM, LITHIUM AND CALCIUM ISOTOPIC EXCURSIONS DURING LIP EMPLACEMENTS consistent, data-supported metal- and C-cycles and climate. Although the Earth system state will have been different for every LIP emplacement, currently no other, similarly robust and internally consistent set-up of the considered metal- and C-cycles is available. Instead, the background C- and metal cycles of past periods are poorly constrained and extensive sensitivity testing and proxy-model comparisons would be required to produce a justifiable alternative to the modern-day set-up (see chapter7). While the use of modern-day constraints limits the direct applicability of quantitative simulation results to specific events (see discussion in 5.4), using a modern-day background state still enables the study of the implications of a dynamic C-cycle for metal isotope excursions under exogenic forcing. Secondly, I simulated LIP emplacement as periods of increased submarine emissions of mantle-derived C and metals with relative metal abundances based on the measured Sr:Os:Li:Ca of present-day hydrothermal alteration of Mid-Ocean Ridge Basalts (MORB), the biggest present-day accumulation of fresh basalt. The high-temperature settings at Mid-Ocean Ridges (MOR) are known to be sources of mantle C to the ocean, and high-temperature interactions between water and fresh basalt are a rich source of metals with mantle-like isotopic composition (see references in table 5.2). Less observed, and thus constrained, is the role of low-temperature (<60◦) alteration of MORB. Penetrating seawater dissolves basalt at lower rates, acquiring isotopic compositions between pure mantle and pure seawater values. Low-temperature alteration constitutes a net source of dissolved Sr and Os (Krabbenhöft et al., 2010; Georg et al., 2013, and references therein), while Li is predominantly stripped out of seawater in low-temperature environments during the formation of secondary clays (Seyfried Jr et al., 1984). Furthermore, Ca is leached from basalts, creating a sink for C (e.g. Brady and Gíslason, 1997; Alt and Teagle, 1999). In addition to the different isotopic forcings of high- and low-temperature alteration of fresh basalt, I tested a range of durations of alteration events, of C:Metal ratios in emissions from high-temperature alteration, as well as different strengths of low-temperature alteration, to account for the aforementioned uncertainty in the duration of LIP emplacements, past C degassing rates, and different volumes of altered basalt or alteration efficiencies. An overview of all simulations is provided in table 5.1, and in the following subsections, I explain the set-ups for each simulation in more detail.

78 5.2. METHODS

Table 5.1: List of experiment set-ups for this study. HT = high-temperature hydrothermal emissions, LT = low-temperature hydrothermal emissions. In ’pure C’ simulations I only increased the CO2 degassing while the release of metal from the mantle stays constant. In ’no clay’ simulations, I assumed fully congruent weathering on land, i.e. continental run-off contains 4 times more Li and has a δ7Li = 2% (see description in the text). ’no Clim’ simulations were run without simulating the climate change resulting from excess CO2 emissions.

duration of high-temperature C:Metal of special Exp. ID recovery high-temperature emissions increase factor excess emissions settings HT 1, 10, 100, 500 kyr 2, 4, 6, 10 0, 1, 2 no LT none pure C 1, 10, 100, 500 kyr 2, 4, 6, 10 no LT none ∞ 4 [Li]runof f no clay 500 kyr 10 2 no LT 7 × δ Lirunof f =2% no radiative no Clim 500 kyr 10 2 no LT forcing of CO2

proportional 100 kyr 2, 4, 6, 10 1 LT proportional none LT to HT strong 100 kyr 2, 4, 6, 10 1 4 LTPI none LT ×

For most elements, the model cGENIE contains prescribed net hydrothermal inputs and outputs without differentiating between high- and low-temperature environments. In order to simulate the effect of changes in each alteration component individually, I divided the prescribed net hydrothermal fluxes prescribed for the pre-industrial spin up into values for high- and low-temperature regimes (see table 5.2).

79 CHAPTER 5. INTERPRETING STRONTIUM, OSMIUM, LITHIUM AND CALCIUM ISOTOPIC EXCURSIONS DURING LIP EMPLACEMENTS

Table 5.2: Hydrothermal fluxes in the pre-industrial configuration, differentiated between high- and low-temperature components.

high-temperature low-temperature Flux prescribed net value references component component Farley et al.(1995) Resing et al.(2004) 12 1 CO2 [10 mol yr− ] 0 +1.5 -1.5 Gillis and Coogan(2011) Burton et al.(2013) Mills et al.(2014) Cocker et al.(1982) δ13C [%] -2 -6 2 Mason et al.(2017) Schultz and Elderfield(1997) De Villiers(1999) 12 1 Ca [10 mol yr− ] +2 +0.5 +1.5 Schmitt et al.(2003) Amini et al.(2008) Antonelli(2018) Amini et al.(2008) δ44Ca [%] 0.93 0.9825 0.9125 Heuser et al.(2005) 9 1 Sr [10 mol yr− ] +3.1 +2.6 +0.5 Krabbenhöft et al.(2010) 87Sr/86Sr 0.7038 0.703 0.708 Krabbenhöft et al.(2010) δ88Sr [%] 0.261 0.256 0.29 Krabbenhöft et al.(2010) 9 1 Li [10 mol yr− ] - +6 -9.5 Hathorne and James(2006) δ7Li [%] - 8.2 seawater Hathorne and James(2006)

Os [mol yr 1] +520 +210 +310 Sharma et al.(2007b) − Georg et al.(2013)

187Os/188Os 0.5625 0.13 0.88 Sharma et al.(2007b) Georg et al.(2013)

5.2.1 High-temperature emission phase of LIP emplacement

The isotopic composition of high-temperature hydrothermal emissions is a reasonable analogue to LIP emplacement-related emissions (Banerjee and Muehlenbachs, 2003; Tejada et al., 2004, 2013; Sano and Nishio, 2015; Gales et al., 2020). However, MORB high-temperature hydrothermalism occurs during the formation of tholeiitic basalts, whereas LIPs have varying amounts of tholeiitic and calc-alkaline magma (e.g. Svensen et al., 2019, and references therein). Tholeiitic magmas contain less Ca and have a lower redox-potential than calc-alkaline magmas (Le Maitre et al., 2004). This means that the assumed Sr:Os:Li:Ca ratios might have been different during LIP emplacement-related emissions. However, since the cycles of Sr, Os, Li are entirely independent in the cGENIE model, and Sr only depends on the total marine Ca reservoir, which is substantially larger than any amount of metal emission that I simulated, the isotopic effect of emissions with different Sr:Os:Li:Ca ratios can be approximated by combining results of simulations with different emission rates (e.g. taking Os results from a simulated doubling of hydrothermal emissions and Ca results from a simulated quadrupling). The most variable component

80 5.2. METHODS of LIP eruption-related elemental fluxes that needs to be considered in these experiments to cover a wide range of LIP emplacements are overall emission rates and the relative amount of emitted C. I simulated emission events with different multiples of modern-day hydrothermal emission rates (2 , 4 , × × 6 , 10 ) and varied the ratio of emitted C to metals: no C emission (0 C:MetalHYD), 1 C:MetalHYD, × × × × 2 C:MetalHYD and pure C emissions ( C:MetalHYD). Additionally, I varied the duration of the × ∞× simulated emission event (1, 10 kyr, 100 kyr and 500 kyr) to account for uncertain durations of LIP emplacements. At the end of the given emissions, I set hydrothermal emission rates and compositions back to pre-industrial values and let marine metal and C reservoirs recover for 5 Myr. Overall, I produced 1 48 simulations (’HT’ and ’pure C’ in table 5.1) spanning CO2 emissions fluxes of 0 – 1.4 Pg yr− and the range of total elemental emissions shown in figure 5.1.

103

3 101 10 105 101

102

100 102 104 100

101

1 10 1 10 103 10 1

100 10 2 100 102

Os (Mmol) Sr (Pmol) Li (Pmol) Ca (Pmol) CO2 (Pg)

Figure 5.1: Total emissions in the simulations of hydrothermal events of different durations and intensities. For each element, the total amount artificially added to the ocean throughout the experiment is shown, each cross indicating the value for one simulation.

I repeated the simulation with the largest C cycle response, i.e. the one with the greatest total C emissions (10 modern-day hydrothermal emission rates, 2 C:MetalHYD, 500 kyr forcing duration), × × with altered settings to disentangle the effects of weathering changes and marine sediment dissolution, and to test the potential of isotopic shifts due to changes in freshwater clay formation. Firstly, I ran the simulations without climatic effect of increased atmospheric CO2 concentrations. In this set-up, only the biogeochemical component of the imposed C forcing affects the Earth’s system and metal fluxes (’no Clim’ in table 5.1). Secondly, I separately repeated the simulation with the largest total C emissions with

81 CHAPTER 5. INTERPRETING STRONTIUM, OSMIUM, LITHIUM AND CALCIUM ISOTOPIC EXCURSIONS DURING LIP EMPLACEMENTS

[Li] of continental run-off quadrupled and its and δ7Li reduced to 2% (Misra and Froelich, 2012) to simulate a terrestrial Li cycle without any effects of secondary clay formation (’no clay’ in table 5.1). In the absence of dynamic terrestrial clay formation in cGENIE, this simulation provides an upper limit on the potential effect of time-variant riverine Li composition on the marine Li reservoir (the lowest riverine δ7Li observed today is 6%, Kısakűrek et al., 2005b; Misra and Froelich, 2012). ∼

5.2.2 Low-temperature alteration of LIP basalts

The isotopic and chemical effects of low-temperature basalt alteration after the LIP emplacement are simulated by increasing the low-temperature component of the baseline hydrothermal flux (’LT’ simulations). In the previously described simulations, I changed elemental fluxes only during the active emplacement phase and let the model recover from this perturbation under pre-industrial C and metal fluxes. Here, I consider low-temperature alteration of the emplaced basalt during recovery. In a first set of simulations (’proportional LT’), I assumed that the scale of low-temperature alteration is proportionate to that of the preceding high-temperature hydrothermalism, i.e. assuming that the same increase in basalt volume is altered first in a high-temperature environment and during cooling after the active emplacement phase under low temperatures. To increase low-temperature alteration fluxes proportionately to high-temperature hydrothermal fluxes, I started by calculating the volume of basalt that corresponds to the excess high-temperature hydrothermal activity. I multiplied the mass of excess high-temperature input (1 , 3 , 5 , 9 ), the duration of the phase of increased high-temperature input × × × × (100 kyr) and the modern day rate of ocean crust production (3.45 km2/yr, Parsons, 1982). This gives the assumed area of excess basalt that caused enhanced high-temperature hydrothermal inputs (short-term). Adding this area to the area of oceanic crust being altered in the modern-day ocean ( 10.35 106 km2, ∼ × assuming that only crust aged 3 Myr is altered and that crust production rates were constant over the ≤ last 3 Myr, Parsons, 1982; Brady and Gíslason, 1997) and normalizing the sum by the latter, I obtained the corresponding factors for increased low-temperature alteration fluxes (table 5.3).

Table 5.3: Corresponding increase factors for elemental fluxes related to high-temperature and low- temperature alteration in simulations of a 100-kyr-long high-temperature hydrothermal event.

High-temperature increase factor Low-temperature increase factor 2 1.03 4 1.10 6 1.17 10 1.30

Starting from the end of the phase of increased high-temperature hydrothermal input in all 100-kyr experiments, I used the above low-temperature increase factors (table 5.3) to simulate alternative LIP emplacement recoveries. Enhanced low-temperature alteration is maintained for an exemplary duration of 200 kyr before all fluxes are set back to baseline value for another 5 Myr. In a second set of experiments (’strong LT’ in table 5.1), I simulated an alternative LIP emplacement

82 5.3. RESULTS

recovery for the 100-kyr simulations with 2 C:MetalHYD with a substantially larger low-temperature × alteration C sink by quadrupling baseline low-temperature-alteration-related fluxes.

5.2.3 Assumed analytical uncertainties

To ensure a meaningful discussion of the simulation results, I will consider an assumed analytical uncertainty (due to measurement technique) for each isotope system in the identification and interpretation of simulated isotopic excursions (see table 5.4). Thus, I will not discuss simulated isotope excursions within the baseline seawater composition analytical error because they would be undetectable in the ± sedimentary record. The assumed uncertainty only acknowledges analytical limitations, not detection difficulties arising from background variability in isotope records as the latter is more difficult to quantify because it varies spatially and temporally.

Table 5.4: Assumed analytical uncertainty for each simulated isotope system based on standard deviations during measurements of international carbonate standards (except for Os isotopes, which were measured on an internal standard) in recently published studies.

Isotope system analytical error references 187Os/188Os 0.0015 Percival et al.(2019) 87Sr/86Sr 0.000015 Chen et al.(2020) δ88Sr 0.04% Guibourdenche et al.(2020) δ7Li 0.5% Bénard et al.(2020) δ44Ca 0.035% Chen et al.(2020) δ13C 0.08% Yan et al.(2020)

5.3 Results

In the following, I present the results of simulations of high- and low-temperature alteration of fresh basalt with and without simultaneous C emissions and the resultant feedbacks.

5.3.1 High-temperature hydrothermal event

LIP emplacements happened likely through repeated, multi-annual lava flows over a total of tens to hundreds of thousands of years (Ernst, 2014). Depending on the setting of these flows and the composition of the lava, this period can be marked by outgassing of CO2 and metal release during quick alteration of the fresh mantle material.

83 CHAPTER 5. INTERPRETING STRONTIUM, OSMIUM, LITHIUM AND CALCIUM ISOTOPIC EXCURSIONS DURING LIP EMPLACEMENTS

Table 5.5: Ratio of initial marine reservoir size and hydrothermal and continental influxes for Sr, Os, Li, Ca and C (atmospheric reservoir).

reservoir size continental influx Element hydrothermal influx (kyr) hydrothermal influx Strontium 48 103 13 × Osmium 320 13 Lithium 6 103 1.3 × Calcium 28 103 25 × Carbon (atmosphere) 33 N.A. Carbon (ocean) 2 103 N.A. ×

84 5.3. RESULTS

a) 100 kyr event b) 500 kyr event Inventories Isotopes

Figure 5.2: Transient changes in modelled Sr, Os, Li, Ca, composition of seawater and atmospheric CO2 and temperature as a result of increased hydrothermal emissions. Shown are changes in concentrations (top row), and in isotopic composition of seawater (bottom row) for 100 kyr (left column) and 500 kyr (right column) of enhanced hydrothermal emissions. Shading indicates the strength (metal flux) of the emission event. Lines of different opacity show the evolution of a variable under different factors of hydrothermal emission increase: 2, 4, 6 and 10 pre-industrial emissions. In simulations represented by × coloured lines, the modern-day C:metal ratio is preserved. In simulations represented by dotted, gray lines, the C:metal ratio = 0, hence mantle-derived metals are released but no extra C is added to the ocean. Horizontal gray bands, where visible, indicate intervals of assumed analytical uncertainty (see section 5.2).

85 CHAPTER 5. INTERPRETING STRONTIUM, OSMIUM, LITHIUM AND CALCIUM ISOTOPIC EXCURSIONS DURING LIP EMPLACEMENTS

Figure 5.2 compares the results of all simulations with increased hydrothermal emissions assuming modern-day C:metal ratio (’HT’ with 1xC:Metal, full lines) and without simultaneous C emissions (’HT’ with 0xC:Metal, dotted lines) from the mantle. Increased mantle emissions start at time 0, and end either after 100,000 or 500,000 years (right and left columns of Figure 5.2). Under both tested emissions durations, the release of mantle-derived material increases metal concentrations in the ocean and drives the seawater isotopic composition to more mantle-like values. In simulations including C forcing, atmospheric CO2 concentration rises by 30 – 430ppm for the 100-kyr emission events (90 – 1360ppm for the 500-kyr emission events) with a peak at the end of the emissions. δ13C and temperature perturbations peak at the same time and, upon termination of the emissions phase, are restored on similar time scales as the atmospheric CO2 inventory. Os is the fastest metal system to respond because the ratio of initial reservoir size and hydrothermal influx is much smaller than for the other tested metal systems (see table 5.5). Detectable excursions (i.e. excursions larger than the analytical uncertainty) in concentration and isotopic composition appear faster in the marine Os reservoir than in the atmospheric C reservoir and climate (after 10 kyr), with and without C forcing. In both cases, Os concentration reaches ∼ 187 188 a maximum at the end of the hydrothermal event, similar to CO2. The Os/ Os excursion peak, on the other hand, only occurs simultaneously to peak in Os concentrations in simulations without C forcing. In simulations with simultaneous C emissions, the 187Os/188Os excursion peak occurs several 10 kyr before the end of the hydrothermal event and the peak C-cycle perturbation. Once excess hydrothermal emissions stop, marine Os concentration is restored at a pace similar to that of the atmospheric and marine C reservoirs while 187Os/188Os recovers substantially faster. The Ca reservoir remains almost unchanged in simulations without C forcing. With simultaneous C emissions, the Ca reservoir perturbation develops on similar timescales as the C cycle perturbation but δ44Ca peaks earlier than δ13C in the simulation with 500kyr-long increased hydrothermal activity. The recovery of the Ca reservoir differs from the C reservoir with a positive δ44Ca excursion after the end of the hydrothermal event and lower post-event steady state marine Ca concentration. The marine reservoirs of Li and Sr take substantially longer to respond to the increased hydrothermal emissions than the C reservoirs. Peak perturbations, both in Sr and Li concentrations and isotopes, are reached at the end of excess hydrothermal input, similar to the C-cycle. Their recoveries are slower than the restoration of the C reservoirs although simultaneous emission of C reduces the recovery timescale of 87Sr/86Sr, alongside the peak 87Sr/86Sr excursion amplitude. δ88Sr is the only proxy system for which no simulation resulted in excursions outside the tested analytical uncertainty.

86 5.3. RESULTS

a) 100 kyr event b) 500 kyr event Inventories Isotopes

Figure 5.3: Transient changes in modelled Sr, Os, Li, Ca, composition of seawater and atmospheric CO2 and temperature as a result of increased hydrothermal emissions with 2 modern-day C:metal ratio. × Shown are changes in concentrations (top row), and in isotopic composition of seawater (bottom row) for 100 kyr (left column) and 500 kyr (right column) of enhanced hydrothermal emissions. Lines of different opacity show the evolution of a variable under different amounts of hydrothermal emission increase: 2, 4, 6 and 10 pre-industrial emissions. Within each panel, rows shows the timeseries of × different proxy systems. In simulations represented by coloured lines, the C:metal of excess hydrothermal emissions is 2 that of modern-day hydrothermal systems. In simulations represented by dotted, gray × lines, the C:metal = 0, hence more mantle-derived metals are released but no extra C is added to the ocean. Horizontal gray bands indicate intervals of assumed analytical uncertainty (see section 5.2).

87 CHAPTER 5. INTERPRETING STRONTIUM, OSMIUM, LITHIUM AND CALCIUM ISOTOPIC EXCURSIONS DURING LIP EMPLACEMENTS

The differences between the perturbations and recoveries of C- and metal reservoirs are amplified when the C:metal of the hydrothermal input increases (figure 5.3). In simulations with C:metal of excess hydrothermal emissions twice that of modern-day hydrothermal systems, the C-cycle perturbation is substantially larger (CO2 changes by 100 – 1510 ppm and 260 – 4560 ppm for the 100- and 500-kyr events, respectively). Similarly, marine metal reservoirs grow larger in simulations with 2 C:metalmodern, in × the cases of Os, Sr and Ca up to a doubling. For all metal isotope systems, positive excursions are simulated during the recovery period, which, in the cases of radiogenic and stable Sr isotopes and Ca isotopes, exceed the respective analytical uncertainty in simulations of 500-kyr-long hydrothermal forcing. Excursion amplitudes of all stable isotope excursions, as well as positive radiogenic isotope excursions during the recovery period, are larger than in the 1 C:metalmodern simulations. Negative × radiogenic excursion sizes, on the contrary, are reduced in the 2 C:metalmodern simulations. × a) Inventories b) Isotopes

Figure 5.4: Separation of contributions of exogenic (’no C forcing’), continental (difference between ’full C forcing’ and ’no climate response’) and sedimentary (difference between ’no climate response’ and ’no C forcing’) metal injections to the simulated metal isotope excursions in the scenario of 10 × pre-industrial hydrothermal emissions, sustained over 500 kyr, with 2 modern-day C:metal. Horizontal × gray bands indicate intervals of assumed analytical uncertainty (see section 5.2).

Comparing these results with simulations of igneous C and metal injections without climate change, and thus with constant continental weathering rates, fig. 5.4 shows that other aspects of the C-cycle perturbation also drive the isotopic changes in marine metal reservoirs: Enhanced continental weathering is the dominant C-cycle change reducing the excursion amplitude of seawater 187Os/188Os and 87Sr/86Sr, but sediment dissolution and reduced carbonate burial is the dominant driver of the deepening of the negative δ88Sr excursion. Reduced carbonate burial has also a strong effect on δ44Ca, which is partially offset by enhanced weathering. Since δ44Ca of riverine input is isotopically lighter than seawater, it is not the delivery of continental Ca through which enhanced weathering partially offsets the isotopic

88 5.3. RESULTS

effect of reduced carbonate burial, but the delivery of alkalinity which increases the stability of CaCO3 in seawater.

89 CHAPTER 5. INTERPRETING STRONTIUM, OSMIUM, LITHIUM AND CALCIUM ISOTOPIC EXCURSIONS DURING LIP EMPLACEMENTS

a) 187Os/188Os b) 87Sr/86Sr

0.00 C:metal of emissions 0.0000 2×C:metalmodern

n 1×C:metalmodern o

0.05 n i o

s 0×C:metalmodern i 0.0001 r s u r c

0.10 Event duration (kyr) u x c

e 1 x

0.0002 e s 10

0.15 r O 100 S 8 8 500 6 1 8

/ 0.0003 / r s 0.20 S O 7 7 8 8

. 1 0.0004 0.25 g . e g n e

n k 0.30 0.0005 a k e a p e

p 0.35 0.0006

0 200 400 600 800 1000 0 2 4 6 8 10 12 cumulative hydrothermal Os emissions (106 mol) cumulative hydrothermal Sr emissions (1015 mol)

c) δ88Sr d) δ7Li

0

0.005 n n

o 2 i o i

s 0.000 s r r u u c c x x

e 0.005

e 4

r i S L 8 7 8

0.010 .

. g

g 6 e e n

n

0.015 k k a a e e p

p 8 0.020

0.025 10 0 2 4 6 8 10 12 0 5 10 15 20 25 cumulative hydrothermal Sr emissions (1015 mol) cumulative hydrothermal Li emissions (1015 mol)

e) δ44Ca

0.02 n

o 0.00 i s r u c

x 0.02 e

a C 4

4 0.04

. g e

n 0.06

k a e p 0.08

0.10 0.0 0.5 1.0 1.5 2.0 cumulative hydrothermal Ca emissions (1018 mol)

Figure 5.5: Amplitude of isotopic excursions as a function of the cumulative amount of excess hydrothermal metal emission for 187Os/188Os, 87Sr/86Sr, δ88Sr, δ7Li, δ44Ca in all simulations. Different marker colours show excursion maxima in simulations with different C:metal of the hydrothermal forcing. Markers of different shape indicate the duration of enhanced high-temperature hydrothermal activity.

90 5.3. RESULTS

To better illustrate the effect of C-cycle feedbacks on the metal isotope excursion amplitude, figure 5.5 shows the variability of metal isotope excursion amplitudes in experiments with different C forcings. An almost linear relationship between excursion amplitude and total excess hydrothermal emission for a given event duration and hydrothermal C:metal is apparent for all proxy systems except for δ7Li. δ7Li is also the only isotope system for which simulated excursion amplitudes do not vary with C forcing. C forcing modulates the excursion amplitudes most for 87Sr/86Sr and δ44Ca. For the latter, a small positive excursion is simulated without C forcing but larger, negative excursions are simulated with simultaneous C emissions. C emissions reduce the size of the negative 87Sr/86Sr excursions by up to 85%.

a) 4 HYDPI b) 10 HYDPI

s × s × O O 8 8 8 8 1 1

/ 2×C:metalmodern / 2×C:metalmodern s s

O 1×C:metalmodern O 1×C:metalmodern 7 7 8 8

0×C:metal 0×C:metal

1 modern 1 modern

r r

S S

6 6 8 8 / / r r S S 7 7 8 8 r r S S 8 8 8 8 i i L L 7 7 a a C C 4 4 4 4 C C 3 3 1 1

0 200 400 600 800 1000 1200 0 200 400 600 800 1000 1200 Simulation time (kyr) Simulation time (kyr)

Figure 5.6: Time span of 187Os/188Os, 87Sr/86Sr, δ88Sr, δ7Li, δ44Ca and δ13C peak excursions in simulations of (a) a quadrupling and (b) a 10-fold increase of modern day hydrothermal inputs with different C:metal over 500 kyr. Each coloured line shows the temporal persistence of isotope values peak excursion + typical analytical uncertainty. See table 5.4 for values of the assumed analytical ≤ uncertainties. The vertical line indicates the end of the simulated igneous forcing.

The duration of peak excursions in the simulated proxy systems is visualized in figure 5.6. C-cycle dynamics (green and orange lines) decrease the persistence of excursion peaks and reduce the simulation time required to reach peak excursion values. They also cause time lags between excursion peaks of different proxy systems. In fact, simulations without hydrothermal C emissions (blue lines) are the only ones in which peak negative excursions in Os, Sr and Li occur simultaneously, at the end of the hydrothermal event. In those simulations, only 187Os/188Os develops the excursion peak before the end of the hydrothermal event, meaning that excursions of the other proxy systems would have grown larger had the simulated hydrothermal event lasted longer. In simulations with 2 C:metalmodern, extending × the event duration beyond 400 kyr would not increase the amplitudes of the 187Os/188Os and 87Sr/86Sr excursions. In simulations with 2 C:metalmodern and high emissions rates (i.e. 10 HYDPI ), this is also × × the case for δ44Ca.

91 CHAPTER 5. INTERPRETING STRONTIUM, OSMIUM, LITHIUM AND CALCIUM ISOTOPIC EXCURSIONS DURING LIP EMPLACEMENTS

a) Inventory b) Isotopes

Figure 5.7: Marine Li reservoir perturbation due to hydrothermal input and enhanced weathering with reduced terrestrial clay formation. The former is the simulation of 10-fold pre-industrial hydrothermal input with 2 C:Metal previously discussed. The latter contains the same forcing, but 4 [Li] in continental × × run-off and riverine δ7Li=2%.

The previously presented simulation results show the isotopic effect of changed continental weathering rates. However, for Li another climate-sensitive driver of marine isotopic composition is the weathering congruency, i.e. the degree of secondary mineral (mostly clay) formation in terrestrial freshwater bodies relative to primary mineral dissolution (silicate weathering). Congruent weathering implies that all solutes derived from the weathered rock reach the open ocean in the aqueous phase while they are partially removed into secondary minerals in incongruent weathering regimes. In particular, Li isotopes have been interpreted as an indicator of weathering congruency, because Li isotopes are strongly fractionated during secondary mineral formation, resulting in isotopically heavier continental Li input under incongruent weathering (Misra and Froelich, 2012).

Figure 5.7 compares the perturbations of the marine Li reservoir due to enhanced mantle emissions and continental weathering for (1) a simulation assuming no change in riverine Li composition, and (2) a simulation assuming complete cessation of terrestrial clay formation. The resulting growth of the marine Li reservoir is more than twice as big in the extreme scenario of no terrestrial clay formation during the mantle emission phase. This is the result of quadrupled [Li] concentrations in continental run-off in the simulation without terrestrial clay formation. The abrupt end of enhanced Li emissions from the mantle and restoration of modern-day riverine Li concentrations at the end of the emission event causes a larger imbalance between marine Li sources and concentration-dependent Li sinks than in previously discussed simulations and thus to a substantially quicker recovery of the marine Li reservoir. Alongside the amount of dissolved Li in the ocean, the negative δ7Li excursion develops more rapidly and thus ends more abruptly than in the simulation with changed riverine Li composition. The excursion amplitude is twice as big as in the simulation with constant riverine Li composition.

92 5.3. RESULTS

5.3.2 Assessing the impact of low-temperature alteration during recovery

Beyond the active phases of LIP emplacement, alteration of the fresh basalt will continue to release mantle-like Os, Sr and Ca while sequestering Li and C.

93 CHAPTER 5. INTERPRETING STRONTIUM, OSMIUM, LITHIUM AND CALCIUM ISOTOPIC EXCURSIONS DURING LIP EMPLACEMENTS

Inventories Isotopes proportional basalt alteration extreme basalt alteration

Figure 5.8: Comparison of simulated recoveries of Sr, Os, Li, Ca, compositions of seawater, atmospheric CO2 and temperature after a 100-kyr high-temperature hydrothermal emissions event with and without enhanced low-temperature basalt alteration. Each row shows the results of simulations with a different low- temperature alteration rate. The upper row shows differences between experiments with low-temperature alteration increases proportional to preceding hydrothermal fluxes (see section 5.2.2) and the previously discussed experiments without increased low-temperature alteration (same as in figures 5.2 and 5.3). The panels in the second row compare recoveries of marine reservoirs in simulations with (dotted lines) and without (coloured lines, same as in fig 5.3) quadrupled pre-industrial low-temperature alteration following 100 kyr lasting high-temperature hydrothermal emissions with 2 C:Metal. Red and gray vertical areas × show phases of active enhanced high-temperature hydrothermal fluxes and low-temperature hydrothermal fluxes, respectively. Horizontal gray bands indicate intervals of assumed analytical uncertainty (see section 5.2).

94 5.4. DISCUSSION

Low-temperature basalt alteration during the recovery phase enhances the rate of the recoveries of atmospheric temperature and CO2 concentration and marine Ca and Sr concentrations. The low- temperature alteration effect on marine Os- and Li concentrations is positive in simulations of 6- and 10-fold increases of preceding high-temperature hydrothermal emissions, with a short drop in Os concentrations at the end of basalt alteration. In the long term, transient periods of increased low-temperature alteration raise marine concentrations of Ca and Sr. The isotopic effect of increased low- temperature alteration is largest for C. When low-temperature basalt alteration increases proportionately to the area of basalt that would correspond to the simulated high-temperature hydrothermal fluxes in modern-day MOR settings, its effects on elemental concentrations and isotopic compositions are negligible. However, quadrupling of pre-industrial low-temperature basalt alteration during the recovery phase alters this outcome significantly (second row of figure 5.8). CO2 is stripped out of the atmosphere- ocean system substantially faster than in previous simulations, resulting in a short-term cold spell with 13 atmospheric CO2 concentration below baseline values. The negative δ C excursion deepens further and its recovery is delayed by the duration of enhanced low-temperature alteration. Alongside atmospheric C, marine metal reservoirs shrink substantially faster in the second simulations because of the faster demise of above-baseline weathering fluxes and the provision of a sizable Li sink but minor Sr, Ca and Os sources. The reduction of the marine Li reservoir and δ7Li fractionation during incorporation into clay formation in altered basalts speeds up the recovery of seawater δ7Li while the reduced radiogenic weathering input and, to a smaller degree the additional unradiogenic Os and Sr input from basalt alteration, slow down the recovery of seawater 187Os/188Os and 87Sr/86Sr.

5.4 Discussion

The emplacement of LIPs is often associated with large C emissions and resulting environmental change (e.g. Bond and Wignall, 2014). However, neither can be unambigously assessed from the δ13C record alone. Nonetheless, the eruption of fresh mantle material and altered terrestrial and marine C fluxes should also impact dissolved metal reservoirs in the ocean, many of which have biogeochemical cycles that are easier to reconstruct than the C cycle, with its many intertwined processes. Therefore, sedimentary excursions of 187Os/188Os, 87Sr/86Sr, δ88Sr, δ7Li, δ44Ca have been used to identify, and more recently quantify, igneous emissions and their weathering responses. Based on the presented simulations of high- and low-temperature alteration of fresh basalt with and without simultaneous C emissions, I discuss in the following sections whether and how C emissions might manifest themselves in the trace metal isotope systems during fresh basalt alteration and how this affects the interpretation of excursions in the sedimentary record. First, I discuss C-cycle-related alterations of the isotopic response of the two main basalt alteration modes (high- and low-temperature alterations). Based on this, I discuss implications and strategies for using 187Os/188Os, 87Sr/86Sr, δ88Sr, δ7Li, δ44Ca excursions during LIP emplacements as quantitative constraints on metal and, by extension, C fluxes.

95 CHAPTER 5. INTERPRETING STRONTIUM, OSMIUM, LITHIUM AND CALCIUM ISOTOPIC EXCURSIONS DURING LIP EMPLACEMENTS

5.4.1 The effect of C release during high-temperature hydrothermal metal emissions

The model experiments show that during enhanced high-temperature hydrothermal activity, C emissions affect the shape of resulting metal isotope excursions: Injection of C alongside mantle-derived metals increases the amplitudes of stable isotope excursions of any sign, while it increases positive radiogenic isotope excursions and reduces the amplitude of negative ones. The radiogenic metal isotope systems are most sensitive to the mantle input. C emissions also change the timing of the isotopic excursion peak in radiogenic Os and Sr and in Ca isotopes. As a result, excursion peaks occur simultaneously at the end of excess hydrothermal activity for simulations without excess C emissions, but with temporal offsets when C is emitted alongside mantle-derived metals. Additionally, marine metal reservoirs grow substantially larger in simulations with excess C emissions. These differences in the isotopic response stem from the sensitivity of metal fluxes between continental, sedimentary and marine reservoirs to changes in the atmospheric and marine C reservoirs. The sensitivity of marine Os, Sr, Li and Ca reservoirs to continental weathering rates has been long recognized, and inspired the use of these isotope systems to trace changes in continental weathering fluxes (e.g. Gannoun et al., 2006; Blättler et al., 2011; Lechler et al., 2015). Enhanced weathering adds more continental-derived metals to the ocean, resulting in a shift towards continental-like values. The model shows that this can overlap with the isotopic effect of mantle metal emissions if the latter spans weathering-relevant timescales and coincides with C emissions. In that case, delivery of continental-like metal isotopes has the potential to stop the marine metal reservoir shifting towards a more mantle-like isotopic composition: In the model simulations, the two opposing processes, isotope input from the mantle and input from continental weathering result in reduced 187Os/188Os and 87 86 Sr/ Sr excursion amplitudes. In the 500-kyr simulations with 2 C:metalmodern, enhanced continental × input leads to the partial recovery of the initial negative isotopic excursion of these two systems, despite continued mantle emissions. Once mantle emissions stop, input from continents prevails and drives seawater composition back to pre-event values. In this way, enhanced weathering increases the speed of isotopic recovery and can lead to positive ’overshoot’ excursions after the emissions event. Heavy stable Sr, Li and Ca isotopes accumulate in seawater which is thus isotopically heavier than hydrothermal and continental inputs of these elements. In this constellation, the increased weathering input does not counter-act mantle emissions. Instead, enhanced continental weathering and dissolution of marine carbonates add to the tendency towards isotopically lighter seawater during the hydrothermal event. Since marine carbonate burial controls seawater δ88Sr and δ44Ca, changes in carbonate burial rates due to C emissions create an additional isotopic forcing on these systems. C injections reduce the stability of calcium carbonate in the ocean while the growth of the marine Sr and Ca reservoirs enhances stable isotope fractionation during burial. The former shapes δ88Sr and δ44Ca initially, before increased preferential removal of light Sr and Ca isotopes stops the negative tendency of seawater δ88Sr and δ44Ca. In the case of δ88Sr, hydrothermal C emissions increase the amplitude of the negative excursion caused by the emission of isotopically lighter Sr from the mantle because of reduced carbonate burial. In the studied set-up, hydrothermal Ca input is relatively unimportant for the marine Ca reservoir (see continental/hydrothermal influx ratio in table 5.5), which instead is entirely dominated by Ca fluxes

96 5.4. DISCUSSION from rock and sediment dissolution and formation. Hence, the simulated hydrothermal forcing alone is not sufficient to cause a negative shift in seawater δ44Ca. However, enhanced continental Ca input is not sufficient either. The presented model simulations suggest instead that marine carbonate burial rates are the dominant control on seawater δ44Ca. In this context, enhanced continental weathering influences the shape of the δ44Ca excursion more strongly by buffering the marine carbonate system than by the provision of isotopically light δ44Ca. During the recovery phase additional sources of light Sr and Ca cease and the marine carbonate system recovers with the atmospheric C reservoir, while enhanced burial-related isotopic fractionation continues until the mass balance between marine Ca and Sr inputs and outputs is restored. In simulations with sufficient accumulation of dissolved Sr and Ca during the hydrothermal event, this causes positive δ88Sr and δ44Ca excursions during the recovery phase. None of the presented model simulations produced δ88Sr excursions larger than the current analytical uncertainty. As of today, no record of δ88Sr across an LIP emplacement has been published, but future measurements may show if the forcings applied in this study were not strong enough to simulate LIP emplacements or whether isotopic effects not represented in the model (e.g. biological fractionation changes) played an important role. Continental and hydrothermal inputs are of equal importance for the marine Li reservoir (continen- tal/hydrothermal influx ratio close to 1). Here, increased weathering of silicate, which is the dominant host lithology for Li in the model set-up, results in substantially smaller additional Li fluxes than the hydrothermal forcing (the model simulates a maximum weathering increase factor of 4 in the scenario of a 10-fold increase in hydrothermal inputs). Thus, the hydrothermal forcing dominates the negative δ7Li excursions in the model simulations, and the C-cycle dynamics play a minor role. δ7Li of continental run-off is not climate-dependent in the presented model version, which is an important limitation for the simulation of seawater Li under climate change. The simulation of an extreme scenario in which the model assumes that terrestrial clay formation ceases entirely at the start of the hydrothermal event shows that variations of riverine δ7Li during the C-cycle perturbation have the potential to cause a similar isotopic perturbation of the marine Li reservoir as the most extreme hydrothermal emissions event I simulated. The isotopic effect of perturbing the terrestrial weathering system is thus potentially substantially underestimated in my simulation ensemble of hydrothermal events. However, this is only the case if the change in riverine δ7Li is substantial and is sustained for >100 kyr. Stable isotope fractionation during burial speeds up the recovery of the negative δ7Li excursion and causes the non-linear relationship between emitted hydrothermal Li and excursion amplitude in 500 kyr simulations with large hydrothermal forcings. The main Li sink is marine clays, the formation of which are not impacted by the C-cycle in our model. Hence, C-cycle changes also have little effects on the simulated recovery.

5.4.2 Negligible direct isotopic signal of enhanced low-temperature alteration effects

Emissions of mantle-like metal isotopes associated with C sequestration during low-temperature basalt alteration could jeopardize the use of mantle-like metal isotope excursions as indicators of C emissions. During LIP emplacements, large amounts of fresh basalt were evidently exposed to weathering under

97 CHAPTER 5. INTERPRETING STRONTIUM, OSMIUM, LITHIUM AND CALCIUM ISOTOPIC EXCURSIONS DURING LIP EMPLACEMENTS water and on land (Jones et al., 2016). Several published works on metal isotope excursions that look at these periods highlight the potential for the chemical alteration of this basalt to drive parts, or all, of the recorded seawater changes (Jones and Jenkyns, 2001; Blättler et al., 2011; Von Strandmann et al., 2013). The model results presented here indicate that significant increases in low-temperature basalt alteration and/or long lasting alteration increases ( 100 kyr) are necessary to cause isotopic >> excursions on the order of those produced by enhanced high-temperature hydrothermal inputs (see Results section 5.3.2). One reason for this is that basalt alteration is significantly stronger under high than low temperatures (Coogan and Dosso, 2015). Additionally, enhanced continental crust weathering in the wake of C emissions exerts a competing isotopic forcing to low-temperature basalt alteration. High-temperature alteration is constrained to a short time (Coogan et al., 2005, hours to days, e.g.[) after the eruption before the fresh basalt cools too much, while low-temperature alteration lasts for millions of years (e.g. Brady and Gíslason, 1997) after the basalt emplacement, on timescales more similar to that of the weathering feedback. The proportion of fresh basalt altered in a high-temperature environment compared to a low-temperature environment could have been different during LIP emplacements than in modern-day MOR settings. Reasons for this might include different cooling rates of LIP basalt compared to MORB or different penetration depths of hydrothermal systems. Low-temperature alteration also could have been strengthened by warming ocean water. There is sedimentary and chemical evidence that basalt alteration on land and at the seafloor is temperature-dependent (e.g. Coogan and Dosso, 2015; Li et al.,

2016). In our simulations temperature changes by 0 – 13◦C and 0 – 10◦C on land and in the deep ocean, respectively. In our model, only continental crust weathering is temperature dependent but there is no climate-sensitive sea floor weathering in general or alteration of fresh LIP basalt in particular. The latter two are instead represented by prescribed elemental fluxes in our simulations. Depending on the assumed temperature sensitivity, the simulated temperature changes could result in a doubling of elemental fluxes from basalt alteration (Coogan et al., 2005). However, even in simulations with prescribed quadrupled elemental fluxes from young basalt alteration, the dominant isotopic forcing of basalt alteration is indirect:

Changed continental crust weathering via enhanced CO2 burial. Since basalt alteration releases dissolved Ca and binds C, large increases in basalt alteration require sufficiently large marine and atmospheric C reservoirs and their continued replenishment. In our simulations substantial, and analytically resolvable, alteration increases can only be maintained for a few 100 kyr, until all excess C is removed from the atmosphere-ocean system, without continued exogenic C input. Since there is no negative climate feedback in fresh basalt alteration in our simulations, those simulations result in a depletion of marine and atmospheric C reservoirs below baseline values. While a climate-alteration-rate-coupling should exist in the real world (e.g. Coogan and Dosso, 2015), cold spells during the recovery of several LIP emplacements were reconstructed (Jenkyns, 2018). The emplacement of massive basalt structures could have led to temporary excess CO2 draw-down. During these cold spells, however, climate-sensitive basalt alteration must have been lowered, reducing the likelihood of long-lasting alteration increases above baseline values after the LIP emplacement. From these findings, it seems less likely that low-temperature alteration of fresh LIP basalts released enough mantle-derived metals to substantially perturb marine

98 5.4. DISCUSSION metal reservoirs without simultaneous C emissions. However, constituting a potent C sink, enhanced alteration of fresh basalt could have indirectly affected seawater metal isotope excursions through climate-driven reduction of continental crust weathering. In particularly, in simulations with the largest tested alteration-rate increase, the recovery of the negative 87Sr/86Sr was delayed by almost 1 Myr due to global cooling and the resulting temporary decrease of continental Sr inputs.

5.4.3 C-cycle driven timings of metal isotope excursion peaks

Enhancing exogenic and continental metal deliveries simultaneously in the simulations for this chapter influenced the timing and size of 187Os/188Os, 87Sr/86Sr, δ88Sr, δ7Li, δ44Ca excursions. This has important implications for the interpretation of the geochemical record during events of simultaneous C and metal emissions, particularly LIP emplacements. The first implication of these findings concerns the identification of hydrothermal events in the geologic record. The recognition of perturbation events and the establishment of interpretive links between different proxy systems rely on the identification of isotopic excursions and their contemporaneity. Our simulations show that C-cycle feedbacks affect the relative timing of 187Os/188Os, 87Sr/86Sr, δ88Sr, δ7Li, δ44Ca and δ13C, the duration of excursion peaks, and can indirectly cause isotope excursions during the recovery from the emissions event. Isotope excursions take 10s of thousands of years after the start of the simulated emissions event to become recognizable as excess exogenic C and metals build up in atmospheric and marine reservoirs. Without C-cycle feedbacks, all isotope systems, including δ13C, reach their excursion peaks at the end of the excess emissions phase. Simultaneous injection of C and mantle-derived metals can alter the duration and peak timing of several of these excursions, particularly for 187Os/188Os, 87Sr/86Sr and δ44Ca. The timing of the Os isotope excursion peak changes significantly if C-cycle feedbacks operate, resulting in peaks 10s of thousands of years earlier than without feedbacks. Depending on the C:metal ratio of the hydrothermal emissions, excursions can be masked in some isotope systems while they occur in others. Examples are the minor positive δ44Ca in simulations without C emissions and the strongly dampened 87 86 negative Sr/ Sr excursion in simulations with 2 C:metalmodern. Carbon draw-down via enhanced × low-temperature alteration, on the other hand, has the potential to create the opposite isotopic effects although my simulations suggest that a substantial increase of the amount of altered basalt is required. Finally, the isotopic effect of C-cycle changes on marine metal reservoirs can also persist for 100s kyr beyond the C-cycle disruption itself: Enhanced sediment dissolution and continental weathering lead to additional growth of marine metal reservoirs, the re-equilibration of which can create noticeable isotope excursions in the aftermath of the hydrothermal event, particularly in stable isotope systems. All of these findings show that the geochemical record of large hydrothermal events can be more complex than the coincidence of a negative δ13C and mantle- or continent-like metal isotope excursions, and that dynamic models of combined C and metal cycling are required to reconstruct the exogenic forcing.

99 CHAPTER 5. INTERPRETING STRONTIUM, OSMIUM, LITHIUM AND CALCIUM ISOTOPIC EXCURSIONS DURING LIP EMPLACEMENTS

a) 10 kyr b) 100 kyr187Os/188Os 87Sr/86S c)r 5008 kyr8Sr 7 44 187 188 87 86 88 7 44 Li Ca O18s7/ O18s8 Sr8/ 7 Sr86 Sr 88 Li Ca 187 188 87 86 88 187 188 87 86 88 Os/ Os Sr/ Sr Sr 7Li 44COas/ Os Sr/ Sr Sr 7Li 44COas/ Os Sr/ Sr Sr 7Li 44Ca

no no no no no Metal Metal

Metal mixed Metal Metal mixed mixed mixed mixed

2 carbonate carbonate carbonate carbonate 2 2 2 2 carbonate exogenic exogenic exogenic exogenic

1 exogenic 1 1 1 1 continental C:Metal of mantle emissions continental continental continental C:Metal of mantle emissions C:Metal of mantle emissions C:Metal of mantle emissions continental 0 C:Metal of mantle emissions

0 no reaction 0 0

2×HYDPI 4×HYDPI 6×HYDPI 10×HYDPI no reaction no reaction no reaction Emission rate 0 2×HYDPI 4×HYDPI 6×HYDPI 10×HYDPI 2×HYDPI 4×HYDPI 6×HYDPI 10×HYDPI 2×HYDPI 4×HYDPI 6×HYDPI 10×HYDPI no reaction Emission rate Emission rate Emission rate 2×HYDPI 4×HYDPI 6×HYDPI 10×HYDPI Emission rate 187Os/188Os 87Sr/86Sr 88Sr 7Li 44Ca

Figure 5.9: ’Proxy potential’ of seawaterno 187Os/188Os, 87Sr/86Sr, δ88Sr, δ7Li, δ44Ca changes across Metal

the simulated hydrothermal events for all tested forcing strengths. Each proxymixed system is represented by a different marker shape. Colours indicate if a measurable (considering a theoretical analytic error) isotopic excursion is directly attributable to exogenic (mantle-derived) metal emissions, continental input due to enhanced weathering, carbonate dissolution or whether more than one of these processes shape 187 188 87 86 the excursion. The assumed analytical2 uncertainties are: 0.02 ( Os/ Os),carbonate 0.0001 ( Sr/ Sr), 0.01% (δ88Sr), 0.1% (δ7Li) and 0.05% (δ44Ca). exogenic 187 188 87 86 88 7 44 5.4.4 The proxy-potential of 1 Os/ Os, Sr/ Sr, δ Sr, δ Li, δ Ca during igneous forcing continental C:Metal of mantle emissions Another implication of my findings concerns the quantitative reconstruction of past disruptions in the marine cycling of Os, Sr, Li and Ca. Isotopic excursions in marine Sr, Os, Li and Ca reservoirs have been 0

used to reconstruct the size of excess metal inputs (e.g. Jones and Jenkyns, no reaction 2001; Blättler et al., 2011;

Lechler et al., 2015; Von Strandmann2× etHY al.DPI, 20134×HY;D BauerPI 6×HY etDP al.I 1,0 2017a×HYDP).I Through assumptions about Emission rate the C:Metal of these inputs, some of these studies further used the metal isotope excursions to derive quantitative constraints on C fluxes. For this purpose, the provenance of the excess metal fluxes had to be assumed (exogenic or continental). For the first time, my ensemble of idealized metal emissions events of different durations, strength, and C:Metal offers the opportunity to diagnose the relative contribution of mantle-derived metal emissions, enhanced continental crust weathering and reduced carbonate burial to the resulting metal isotope excursions. For each simulation which produces a measurable metal isotope excursion in a proxy system (given current analytical uncertainties, see section 5.2), figure 5.9 shows the isotopically dominant source of the injected metal or indicates if exogenic, continental and

100 5.4. DISCUSSION sedimentary sources have no measurable impacts on the excursion. Because of long residence times, several proxy systems only show isotope excursions outside analytical uncertainty in simulations with substantial cumulative excess metal input, resulting from a long event duration or high emissions rate. Among the simulations which produce resolvable isotope excursions, only simulations of pure C or pure metal emissions or short duration events provide scenarios in which the nature of the dominant Os and Sr isotopic forcing can be identified unambiguously. Neither scenario is a likely analogues for LIP emplacements, given evidence for sustained, large-scale outpourings of magma with mantle-like isotopic composition and super-saturated in CO2 (e.g. Ernst, 2014) during LIP formation. However, they are comparable to other geological events: simulations of pure C emissions may represent any change in continental weathering regime that is not accompanied by metal emissions from the mantle, e.g. activation of dormant superficial C reservoirs (e.g. methane emissions from peat lands, permafrost or hydrates, degassing of marine C due to ocean circulation changes, expansion or shrinking of the biosphere etc.) or changes to the extent of terrestrial rock weathering through large-scale variations in the extent of glacial land cover, sea level fluctuations or similar. Asteroid impacts can be compared to simulations of short pure exogenic metal emissions, provided that no significant superficial C reservoir is perturbed by the impact and that no large-scale impact volcanism enchains. However C-neutral impacts of asteroids sufficiently large to provide enough metals to disturb the marine reservoirs of Os or Sr are arguably unlikely (Kamber and Petrus, 2019). Although C and metal emissions might have been decoupled temporarily (e.g. due to cryptic degassing, Black and Gibson, 2019), LIP emplacements as a whole were likely events during which Os and Sr isotope systems were shaped significantly by exogenic and continental metal inputs. According to my simulations, δ7Li excursions, which are least affected by simulated increased continental influx because of the small ratio of baseline fluxes from land and the mantle (see table 5.5), could have been predominantly driven by exogenic Li emissions during LIP emplacement. While this suggests that δ7Li could provide direct quantitative information on the scale of exogenic forcings, δ7Li is more complex than radiogenic Os and Sr isotopes and key isotope fractionation processes (i.e. secondary mineral and evaporite formation) are not simulated by cGENIE. In particular, my sensitivity study showed that large shifts in the composition of riverine Li can exert isotopic forcings similar to or larger than the simulated mantle emissions. Coupling of dynamic, isotope-enabled marine and terrestrial Li cycling would be required to assess the full proxy potential of δ7Li for scenarios of combined C and Li mantle emissions.

5.4.5 A new framework for metal-isotope-derived quantitative constraints on contemporaneous C-cycle perturbations

101 CHAPTER 5. INTERPRETING STRONTIUM, OSMIUM, LITHIUM AND CALCIUM ISOTOPIC EXCURSIONS DURING LIP EMPLACEMENTS

a) radiogenic isotope proxy b) stable isotope proxy

mantle emission only mantle emission recorded excursion recorded excursion only amplitude amplitude stable isotope ratio stable isotope radiogenic isotope ratio radiogenic isotope isotope effect isotope effect of C-cycle dynamics of C-cycle dynamics

event duration (kyr) event duration (kyr)

Figure 5.10: Conceptualization of contributions of mantle emissions and C-cycle dynamics to the recorded excursion amplitudes in (a) radiogenic (e.g. 187Os/188Os and 87Sr/86S) and (b) stable (e.g. δ88Sr, δ7Li,δ44Ca) isotope proxy systems.

The presented simulations show that enhanced exogenic and climate-driven, terrestrial metal fluxes influence the shapes and sizes of radiogenic isotope excursions, implying that they contain quantitative information on metal delivery from both processes. However, the signals of exogenic forcings and weathering changes cannot be distinguished directly from resulting radiogenic isotope excursions in seawater. The question is thus if and how the signals of mantle forcing and C-cycle feedbacks can be disentangled so that the true size of each can be determined. Previous studies of radiogenic Os and Sr excursions based their reconstructions of the exogenic forcing or weathering response on excursion amplitudes (Jones and Jenkyns, 2001; Bauer et al., 2017a). Our simulations suggest that the excursion amplitude in these proxies is not enough to constrain the C forcing, since C-cycle feedbacks which reduce the size of 187Os/188Os and 87Sr/86Sr excursion amplitudes caused by mantle emissions and increase the size of δ88Sr excursions during long-lasting and/or high-emission events most similar to LIP emplacements. In particular, if the reaction timescale of a proxy system is similar to or longer than the timescale of a relevant C-cycle feedback (like 87Sr/86Sr and continental weathering in our simulations), the real impact of exogenic forcing can be masked almost entirely. Figure 5.5 shows that, if we were to deduce the hydrothermal forcing from the size of 87Sr/86Sr excursions in simulations with hydrothermal C emissions, we would underestimate it by up to 85%. Rather, the scale of C-cycle disruption emerges from the difference between the recorded isotope excursion and the potential excursion without C-cycle changes. This is conceptualized in figure 5.10a. In the radiogenic isotope systems 187Os/188Os and 87Sr/86Sr, the isotopic excursion recorded in the geological record is the portion of the exogenic isotopic forcing which was not compensated by enhanced delivery of terrestrial metals. The recorded excursion in stable isotope systems (δ88Sr, δ7Li,δ44Ca), on the other hand, represents the added isotopic forcings of enhanced metal delivery from land, the mantle and carbonate burial. Interpreting radiogenic isotope excursions resulting from exogenic and continental metal emissions only as consequences of the former

102 5.4. DISCUSSION would underestimate of mantle-derived metal - and by extension C - input. Similarly, the interpretation of stable isotope excursions as pure weathering signals would overestimate the scale of weathering changes, particularly since disruptions to carbonate burial seem to be significant drivers of δ88Sr and δ44Ca excursions. The extent of this under- or overestimation depends on the C:Metal of exogenic emissions and the background state (see discussion below). Still, combining reconstructions based on radiogenic and stable isotope excursions could provide an envelope around the true sizes of excess igneous, continental and changed carbonate burial fluxes. The width of these envelopes can only be reduced by additional constraints on either of those fluxes (e.g. reconstructed C:Metal of igneous emissions or mass constraints from estimates of amount and composition of the emplaced basalt or independent evidence on the strength of climate feedbacks). The composition and geographic extent of LIPs could provide such additional constraints on the igneous forcing. For example, the Ontong-Java Plateau is one of the best studied LIPs on Earth and the chemical composition of its pristine basalts is well known (Fitton and Godard, 2004) and several reconstructions exist for its initial size (see review in Svensen et al., 2019). This information could be used to constrain the maximum isotopic forcing that could have resulted from the eruption of these basalts. The estimated maximum isotopic forcing could then be used to simulate maximum seawater isotope excursions in the absence of C emissions, which can be done with a conventional isotope-mixing model since C-cycle dynamics are not relevant. The difference between the simulated and the measured isotope excursions, both in terms of timing and amplitude, would then allow for the estimation of the isotopic forcing of C-cycle feedbacks. This would be a novel and more robust way to derive quantitative constraints on the hard-to-quantify strength of igneous forcing and weathering feedback during LIP emplacement.

5.4.6 The quantitative importance of the background state

All of the discussed simulations were run with modern-day initial values and boundary conditions which have implications for the direct applicability of the numeric results of this study to past events. In several ways, the impact of excess mantle emissions on marine metal reservoirs and their alteration through the C-cycle depend on the background state. The degree to which the latter can be constrained for past periods directly impacts uncertainties associated with the quantitative interpretation of metal isotope excursions. As previously discussed, the pre-event ratio of continental versus mantle-derived input of a metal dictates the sensitivity of its marine reservoir to C-cycle changes during enhanced igneous metal delivery. Today, this ratio is lowest for Li and largest for Ca which therefore show the smallest and biggest relative isotopic effect of enhanced weathering, respectively. Os and Sr have the same ratio of modern-day continental versus mantle-derived input. Yet the simulated behaviour of 187Os/188Os and 87Sr/86Sr under igneous forcing and the impacts of C-cycle changes are different. This is the result of vastly different initial marine reservoir sizes and residence times. Os has the smallest initial inventory and residence time of the studied metals. Hence, its marine reservoir shows measurable perturbations more quickly than those of other metals. In simulations of simultaneous mantle-derived metal and C emissions, most of the 187Os/188Os excursion builds up before the isotopic forcing of climate-driven increases in

103 CHAPTER 5. INTERPRETING STRONTIUM, OSMIUM, LITHIUM AND CALCIUM ISOTOPIC EXCURSIONS DURING LIP EMPLACEMENTS continental crust weathering manifests. Isotopic effects of igneous metal emissions and C-cycle changes are thus almost temporally separate in the resulting 187Os/188Os record, while they overlap, and in some simulations cancel each other, in the 87Sr/86Sr record because of the larger initial marine Sr reservoir and residence time. The strengths of continental and igneous isotopic forcings further depend on the isotopic offset between metals in the mantle and continental run-off and seawater. For stable Sr, Li and Ca isotopes, the initial role of the marine sink for the isotopic composition of seawater is an important control on the isotopic signal of the recovery of increased marine metal reservoirs. Finally, the potential for positive (e.g. C emissions independent of metal emissions) and negative C-cycle feedbacks (e.g. continental crust weathering, sediment dissolution, seafloor alteration, organic C burial) in the pre-event Earth system state affects the strength and speed of the manifestation of exogenic C emissions in metal isotope records.

5.5 Conclusions

Through an ensemble of simulations of transient increases in hydrothermal emissions over different durations, of different strengths, and with variable C:metal, I evaluated the potential to use excursions in seawater 187Os/188Os, 87Sr/86Sr, δ88Sr, δ7Li, δ44Ca as quantitative constraints on exogenic C emissions and C-cycle feedbacks during LIP emplacement. The simulations showed that all of those proxy systems are potentially influenced by the isotopic forcings of enhanced igneous and continental metal emissions and changed carbonate burial rates, and that the sensitivities to those processes depends on initial marine reservoir sizes, relative source strengths and isotopic fractionation during marine burial. In particular, 187Os/188Os and 87Sr/86Sr excursion amplitudes and timings are shaped by both enhanced metal delivery from the mantle and from land in simulations of long-lasting C emissions events with high emissions rate and simultaneous mantle-derived C and metal injections, scenarios most likely representing LIP emplacement volcanism. In these simulations, seawater δ44Ca is predominantly driven by the carbonate burial response and δ7Li by the igneous forcing, but simulating the effects of reduced terrestrial clay formation showed that the latter is likely due to limitations of the land surface representation in cGENIE. Since isotopic excursions of these metal systems record changes in igneous inputs and C-cycle changes, the latter need to be disentangled before they can be used to constrain the hydrothermal forcing and its environmental impacts during LIP emplacement. A first order approach can be the combination of radiogenic and stable isotope systems, since they provide opposite end-member constraints. However, quantitative interpretations of these isotope excursions remain uncertain in the absence of additional, independent data. Furthermore, establishing quantitative links between isotope excursion amplitudes and metal (and C) emissions requires assumptions about the background Earth system state (metal and C cycles). In particular, the reconstruction of the isotopic potential of the igneous forcing requires assumptions about the size of marine metal reservoirs, the ratio between initial marine sources of mantle- and land-derived metals and the isotopic offset between metals in seawater, runoff and mantle emissions. Thorough quantification of uncertainties introduced by these unknown parameters will be essential in

104 5.5. CONCLUSIONS any attempt to constrain past C-cycle dynamics with metal isotope excursions.

105

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C h a p t e r 6 CHAPTER 6. SIGNIFICANT VARIATIONS IN THE OCEAN RESIDENCE TIME OF OSMIUM WITH CHANGES IN BIOGEOCHEMISTRY

Abstract

Shifts in the isotopic composition of dissolved osmium (Os) in seawater, as preserved in the sedimentary record, reveal periods in Earth’s history with transient imbalances between mantle inputs and continental weathering, two major geologic processes shaping the long-term carbon cycle. The interpretation of these shifts in localized marine sediment successions as indicators for global change requires the assumption of a marine residence time of Os substantially longer than the ocean mixing time, which is often based on modern Os fluxes but is inconsistent with marine Os isotope changes over the last deglaciation. Currently deposited marine sediments indicate that ambient oxygen concentrations play an essential role on Os deposition rates. This raises the possibility of large variations in the residence time coupled to past variations in marine biochemistry which would have direct effects on the interpretation of isotopic shifts in ancient sediments. Yet, it has never been explored explicitly how large the range of possible past residence time variations is and what this implies for interpretations of the Os isotope record. Here we use the intermediate complexity Earth system model cGENIE to simulate the marine Os reservoir under different oxygen- and organic carbon export-dependent Os deposition rates. In two data-model comparison exercises we test the compatibility of oxygen- and organic carbon export-dependent Os deposition with observations of marine Os concentrations and explore Os residence time variability in the geologic record. I find that measurements of Os concentrations in present-day seawater are consistent with redox controls on Os deposition, and that seawater Os isotope heterogeneity reconstructed from the sedimentary record correlates with the degree of oxygenation and primary productivity of past oceans. I further show that, even if the redox state of seawater only plays a small role in Os deposition today, it could have reduced the marine residence time of Os below the ocean mixing time during periods of low oceanic oxygenation. This implies that marine Os concentrations might not have always been homogeneous across ocean basins and that local Os isotope variations might reflect regional rather than global Os flux changes during periods with small marine Os concentrations.

6.1 Introduction

Osmium (Os) is a rare, siderophile and chalcophile metal, which is cycled at Earth’s surface between the mantle, the continental crust and seawater. The ocean constitutes a transitory reservoir for Os, which is predominantly derived from weathered continental crust and hydrothermal inputs, and eventually buried in marine sediments. The isotope 187Os is the product of radioactive decay of 187Re (half-life 41.6x109 yr, Smoliar et al., 1996). The Rhenium (Re) to Os ratio of continental crust is considerably higher than that of the mantle, over time resulting in an elevated 187Os/188Os of continental crust compared to the mantle. The different isotopic ratios in old continental crust and young basalt allows us to distinguish the two main sources of marine Os - terrestrial weathering and hydrothermal alteration of mid-ocean ridge basalts, similar to other radiogenic elements like strontium (Sr) and neodymium (Nd). Fluctuations in the isotopic composition of Os and other metals in marine sediments thus provide valuable insight into the evolution of local and global metal sources, often related to environmental

108 6.1. INTRODUCTION change. The fraction of an element’s abundance in the ocean and the sum of annual inputs or outputs at equilibrium is commonly referred to as the marine residence or flushing time of this element, and is an important characteristic of metal cycles. Depending on the difference between the marine residence time of a metal and the ocean mixing time, the isotopic composition metals in seawater can be used to reconstruct ocean circulation (water mass tracers like Nd with residence times smaller than the ocean mixing time ( 1500 yr today Broecker and Peng, 1982)) or the balance between carbon emissions from ∼ the Earth’s mantle and absorption during weathering and marine sediment accumulation (weathering tracers like Sr with residence times much larger than the ocean mixing time). Both ocean circulation and weathering have varied over Earth’s history and affected global climate and its local expression. Ocean currents reflect sea ice extent, ocean basin connectivity, and sea level, which impact latitudinal heat transfer. The carbon exchange between Earth’s surface and the lithosphere affects the amount of carbon accumulating at the surface (in the atmosphere, oceans, biosphere), with warming events triggered by temporally unbalanced volcanic emissions (e.g. Tejada et al., 2009; Du Vivier et al., 2015) and cold periods governed by a surplus in silicate weathering (e.g. Kump et al., 2000; Misra and Froelich, 2012). Os is increasingly used to study mass exchange between the mantle and Earth’s surface because its residence time in today’s ocean is estimated to be sufficiently longer than the ocean mixing time to be spatially homogeneous, but shorter than the residence time of elements like Sr and lithium (Li), thus capturing more abrupt disturbances of oceanic metal cycles. As such, Os has been applied as indicator for periods of increased volcanic activity (e.g. Turgeon and Creaser, 2008; Tejada et al., 2009; Bottini et al., 2012), as well as phases of enhanced continental weathering (e.g. Burton et al., 2010; Finlay et al., 2010). Even though we have an incomplete knowledge of the chemical exchange reactions involved in the marine Os cycle and the scale of Os burial today, it is commonly assumed that the marine Os cycle behaved similarly in the past as it does today. This assumption enabled the interpretations of shifts in the isotopic composition of Os in localized sedimentary successions as records of global environmental change. However, a marine residence time of several 10 kyr is not reconcilable with the abrupt isotopic shifts from glacial to interglacial stages in the Quarternary, which instead suggest a residence time close to the ocean mixing time during that period (Oxburgh, 2001). Additionally, other evidence suggests that the isotopic composition of seawater, which is spatially invariable today, was more heterogeneous in the past (e.g. Paquay and Ravizza, 2012). This also indicates a substantially shorter ocean residence time of Os in the past. While these findings have been used to challenge our understanding of modern Os fluxes into the ocean (e.g. Oxburgh et al., 2007), the possibility that the marine residence time of Os could have varied over time has not been explored in detail. Given ample evidence for an important role of oxygen or organic matter concentrations for Os burial at present (Lu et al., 2017), we argue that fluctuations in the Os residence time in the past are likely, and that the implications for the interpretation of Os isotopic shifts require further investigation, particularly during phases of substantially different marine biogeochemistry compared to today.

109 CHAPTER 6. SIGNIFICANT VARIATIONS IN THE OCEAN RESIDENCE TIME OF OSMIUM WITH CHANGES IN BIOGEOCHEMISTRY

6.2 What is the evidence for a variable marine residence time of Osmium?

The isotopic composition of Os in present-day seawater is largely homogeneous, except for less radiogenic surface water which could result from anthropogenic Os emissions (Chen and Sharma, 2009). Os isotopic homogeneity in the ocean has long been interpreted as an indication for a marine residence time of Os considerably longer than the ocean mixing time (Oxburgh, 2001). Estimates of yearly Os inputs to the oceans support a residence time of several 10 kyr, although the Os flux from groundwater is poorly constrained (Oxburgh, 2001; Lu et al., 2017). However, the sedimentary record indicates that the spatial homogeneity of 187Os/188Os in seawater, and thus the marine residence time of Os, varied over time. For example, Oxburgh(1998) argues for global, abrupt isotopic shifts at glacial-interglacial transitions during the last 200 kyr. Unless it is assumed that weathering-derived Os fluxes more than doubled during deglaciation, these abrupt shifts can only be explained by a residence time on the order of a few thousand years, close to the ocean mixing time (Oxburgh, 2001). The global nature of these isotopic shifts was disputed by Paquay and Ravizza(2012), who instead argue that seawater was more heterogeneous than measurements of modern seawater suggest, at least between 10-30 ka, and that these shifts were local phenomena. While challenging previous conceptions of the Os cycle during deglaciation (e.g. Oxburgh et al., 2007), Paquay and Ravizza(2012)’s interpretation of the glacial Os isotope record also requires the assumption of a residence time close to or below the ocean mixing time, since there is no other known reason for geographical Os isotopic heterogeneity in seawater. The Os isotope record of recent glacial cycles thus implies that the residence of Os might have been much closer to the mixing time of the ocean during glacial phases than today. Another example for a period with reconstructed geographical Os isotope heterogeneity is the Late Cenomanian - Early Turonian (96-92 Ma). At the boundary between these stages, sustained large igneous province volcanism caused drastic changes in climate and the biogeochemistry of Earth’s surface, leading to widespread marine anoxia and a distinct, organic-rich horizon in the geological record, referred to as Oceanic Anoxic Event 2 (OAE 2, Jenkyns, 2010). Os isotope records across OAE 2 show a sharp excursion to mantle-like values at the onset of the characteristic positive carbon isotope excursion (Du Vivier et al., 2015). While the peak value of the unradiogenic 187Os/188Os excursion is very similar across all measured sedimentary successions, 187Os/188Os values before and after the excursion vary strongly between sites (fig. 6.1b, Du Vivier et al., 2015).

110 6.2. WHAT IS THE EVIDENCE FOR A VARIABLE MARINE RESIDENCE TIME OF OSMIUM?

a) OAE 1a b) OAE 2

Figure 6.1: Composite figure of reported Os isotopes (a) before and during OAE 1a and (b) before, during and after OAE 2. The presented data is taken from Tejada et al.(2009); Bottini et al.(2012); Adloff et al. (2020) for OAE 1a and Du Vivier et al.(2015) for OAE 2. In (a), ’background’ refers to the Aptian (all available data points) before the transient radiogenic Os isotope excursion, which is represented by ’pre-OAE’ values. In (b) ’pre-OAE’ and ’post-OAE’ each represent approximately 500 kyr before/after the unradigenic Os isotopic excursion during OAE 2.

A similar environmental perturbation to OAE 2, OAE 1a, occurred some 30 Myr earlier, in the early Aptian ( 120 Ma). Although fewer detailed Os isotope records are available for this time period, figure ∼ 6.1a shows that the available data indicate a large regional spread of Os isotopes in seawater before OAE 1a, similar to the late Cenomanian. Similar to OAE 2, seawater had a regionally homogeneous, mantle-like composition during OAE 1a but local records from the pre-OAE ocean and a transient radiogenic excursion just before the start of OAE 1a show clear regional differences. The inter-basin range of 187Os/188Os over these short time intervals could suggest geographical heterogeneity, which in turn implies a short marine residence time of Os. However, different sedimentation rates and sampling frequencies at each site mean that apparent inter-site 187Os/188Os discrepancies could in reality reflect temporal oscillations of the Os isotopic composition of seawater. Still, in this case the range of recorded 187Os/188Os values is so large that sufficiently big oscillations can hardly be envisaged in the absence of large environmental changes, for which there is no evidence during these periods, unless the residence time of Os was low and seawater 187Os/188Os volatile. Regardless of age model uncertainties, the reported inter-basin range of 187Os/188Os thus suggests that the marine residence time of Os might have been close to the ocean mixing time before and after OAE 2 and before OAE 1a, as has been suggested for records of recent deglaciation. By contrast, Os isotope record of the Paleocene-Eocene Thermal Maximum (PETM, 55.9 Ma) imply that 187Os/188Os was similarly homogeneous across ocean basins as today (Dickson et al., 2015), and thus a modern-like residence time in the late Paleocene and early Eocene. The geological 187Os/188Os record thus suggests that the heterogeneity of the Os isotopic composition

111 CHAPTER 6. SIGNIFICANT VARIATIONS IN THE OCEAN RESIDENCE TIME OF OSMIUM WITH CHANGES IN BIOGEOCHEMISTRY of seawater, i.e. the marine residence time of Os, varied over time. This variation could have resulted from changes in the strength of input or output fluxes of Os to and from the ocean. Today, dissolved Os is predominantly derived from products of continental crust weathering and supplied to the ocean through riverine discharge and aeolian transport. Smaller sources are hydrothermal vents at the sea floor and, to a lesser extent, extra-terrestrial meteoritic input. Marine Os sinks are poorly constrained, but they include oxic and anoxic marine sediments and estuaries, as well as ferromanganese nodules in the deep sea (Koide et al., 1991; Yamashita et al., 2007). It is assumed that most dissolved marine Os is in its highest oxidation state, while lower oxidation states prevail in compounds with metals or organic matter in sediments (Yamashita et al., 2007). Os sequestration from the dissolved state must therefore involve

Os reduction. Redox conditions in the ocean (i.e. availability of dissolved O2) have varied over geologic time, and if the transition from dissolved to sedimentary-bound Os involves changes in the redox-state of Os, this could have played a role in the variability of the marine Os reservoir.

Figure 6.2: Published relationships between [Os] and [O2] from different ocean basins (East Pacific: 1Woodhouse et al.(1999), 2Chen and Sharma(2009), 3Gannoun and Burton(2014); North Atlantic: 4Gannoun and Burton(2014); Indian Ocean: 5Levasseur et al.(1998)) and measured with different methods. The figure is based on a similar figure in Woodhouse et al.(1999)

A mechanistic link between concentrations of dissolved Os and O2 has been discussed based on vertical concentration profiles in different ocean basins: While no relationship between seawater [Os] and [O2] was observed in the Indian Ocean and North Atlantic, it has been suggested that the vertical profile of [Os] in the East Pacific might follow that of [O2](Woodhouse et al., 1999), potentially indicating redox-sensitivity in the water column (see figure 6.2). However, there remains considerable analytical uncertainty over the [Os] values in the East Pacific samples (Chen and Sharma, 2009; Gannoun and Burton, 2014), based on which the reliability of the reported relationship between [Os] and [O2] was questioned (Gannoun and Burton, 2014). Despite considerable analytical uncertainty related to measurement technique, figure 6.2 shows that a correlation between [Os] and [O2] might still be detectable in these samples because the lowest and highest [Os] occur in the most O2-depleted and -enriched samples, respectively. With the exception of studies with Teflon/Br2 treatment, all measurement series also show an almost linear relationship between [Os] and [O2]. Despite uncertain absolute dissolved Os

112 6.3. METHODS

concentrations, a relationship between [Os] and [O2] thus seems to be a robust feature of the East Pacific samples independent of measurement technique. Another line of evidence for an anti-correlation between

Os and O2 stems from the distribution of Os in marine sediments. Sedimentary Os concentrations are between 2-3 orders of magnitude higher in reducing, organic-rich sediments than in oxic sediments (Koide et al., 1991). The extensive compilation of Os concentrations in recent and ancient suboxic marine sediments by Lu et al.(2017) suggests that preservation of organic matter is a major, but not the only, factor influencing Os burial. While this accumulation of Os in reducing sediment successions could be related to Os enrichment in marine organic matter (up to 3 orders of magnitude larger in macroalgae than in seawater Racionero-Gómez et al., 2017), it has been found that [Os] is also elevated in reducing sediments poor in organic matter (Yamashita et al., 2007). However, missing evidence for a direct link between the amount of Os in seawater overlaying the sediments and the sediments themselves means that the mechanism and extent of suboxic Os deposition remain vague. In oxic sediments, Os accumulation rates are 1-4 orders of magnitudes lower than in suboxic sediments, with highest accumulation rates in metalliferous sediments and Fe-Mn crusts (Lu et al., 2017). Although Os is incorporated into biogenic calcite shells, its concentrations are too low for marine carbonate burial to constitute an important marine Os sink (Burton et al., 2010). Lu et al.(2017) estimated the total Os burial in suboxic sediments to be 450-2800 kg/yr, while oxic burial is estimated to be 2-370 kg/yr, suggesting that Os burial rates are redox-sensitive. In the following sections, I investigate whether a sizable redox-sensitive Os sink is compatible with the measured distribution of [Os] in present-day seawater, and how it would impact the marine Os reservoir and its residence time under different biogeochemical conditions.

6.3 Methods

I used cGENIE, a 3D Earth system model of intermediate complexity which now includes isotope-enabled cycling of Os (chapter4), to simulate the marine Os reservoir with different assumptions about sink mechanisms and under different biogeochemical conditions. The model results were compared to seawater [Os] measurements to assess which assumptions are compatible with observational evidence. Details of the model and the simulation set-ups are described below.

6.3.1 Organic matter, O2 and Os cycling in cGENIE cGENIE is a modular model, which in our set-up comprises modules for ocean circulation (advection and mixing), the biological pump and marine chemistry, sea-ice, atmospheric chemistry, atmospheric water- balance and the greenhouse effect, as well as climate-sensitive continental weathering and sedimentary

CaCO3 accumulation or dissolution (Ridgwell, 2001; Ridgwell et al., 2007; Ridgwell and Hargreaves, 2007; Colbourn et al., 2013). Simulated organic carbon export from the surface ocean depends on 3 light limitation, nutrient availability (PO4− in our set up), sea-ice cover and temperature (Ridgwell, 2001). The produced organic carbon is split into dissolved and particulate organic carbon (DOC and POC, respectively) at an adjustable ratio. DOC is transported by the physical model component and

113 CHAPTER 6. SIGNIFICANT VARIATIONS IN THE OCEAN RESIDENCE TIME OF OSMIUM WITH CHANGES IN BIOGEOCHEMISTRY remineralized depending on a prescribed lifetime, while POC is instantly exported to deeper water layers and remineralized following a decay function tuned to POC flux measurements. Our set-up does not allow for organic carbon burial in sediments, meaning POC reaching the water-sediment interface is entirely remineralized. O2 is exchanged between the atmosphere and the ocean at the air-sea interface, depending on the temperature-dependent solubility of O2 in water. In the ocean, O2 is released during primary production in the surface ocean and consumed during remineralization of DOC and POC under oxic conditions. Os has recently been added as a tracer to cGENIE (see chapter4). In cGENIE, Os enters the the ocean at a proportional rate to climate-sensitive terrestrial weathering, with prescribed 2 isotopic signature and Os:Ca + ratio, and through hydrothermal input with prescribed rate and isotopic composition. In the ocean, Os is distributed by the physical ocean module. Sink mechanisms can be turned on and off and include incorporation and burial of Os in biogenic carbonates, Os scavenging during POC export and concentration-dependent diffusion of Os from bottom waters into marine sediments. The model allows for two different diffusion rates of Os into the sediments, with an adjustable bottom water

[O2] threshold. This enables the model to simulate increased Os deposition under low [O2]. Additionally, the model can be configured such that Os scavenging only occurs below an adjustable [O2] threshold.

6.3.2 Simulation set-ups

We spun up the model with modern boundary conditions on a 36x36x16 grid following the set-up of Archer et al.(2009), first for 20 kyr with a closed carbonate system to equilibrate atmosphere and ocean, and then for 500 kyr with interactive weathering and sediments to equilibrate marine alkalinity and 2 [Ca +]. In a third step, we introduced Os to the ocean and equilibrated the marine Os cycle to reach an average concentration of 52.6 fmol/kg Os in seawater. In our set-up we prescribe an Os influx of 500 kg/yr with 187Os/188Os = 1.2 from land to the ocean, comprised of river and groundwater discharge and terrigeneous dust. Furthermore we add an Os input of 30 kg/yr with 187Os/188Os = 0.2 to the surface ocean representing cosmic dust and volcanic aerosols and an influx of 100 kg/yr with 187Os/188Os = 0.56 into the deep ocean, comprising contributions from hot and cold hydrothermal systems. To balance these input fluxes, the Os burial rate needs to be 630 kg/yr. To test the effects of different sink mechanisms on the distribution of Os in the ocean, we set up a set of simulations in which this burial flux is achieved through different sink mechanisms and combinations of oxic and anoxic burial (see table

7.2), for example: 630 kg/yr Os deposition under O2 independent diffusion at water-sediment interface (’DIFF’), 315 kg/yr Os deposition under anoxic and 315 kg/yr under oxic diffusion at water-sediment interface (’DIFF_R 50’), 315 kg/yr O2 independent Os scavenging by POC and 315 kg/yr Os deposition by O2 independent diffusion (’SCAV 50’) and 315 kgr/yr O2 dependent Os scavenging by POC and 315 kg/yr Os deposition by O2 independent diffusion (’SCAV_R 50’). We also tested different ratios of oxic to anoxic deposition in these configurations. Since burial in biogenic carbonates only constitutes a very minor Os flux to the sediments, we omit this sink in our simulations.

114 6.3. METHODS

Table 6.1: Compositions of marine Os sinks in our cGENIE simulations.

Percentage of Os burial Percentage of Os burial ID sink mechanisms dependent on [O2] dependent on POC

DIFF O2 independent deposition 0 0 DIFF_R 25 25 0 O2 dependent deposition DIFF_R 50 50 0

SCAV 25 O2 independent deposition & 0 25 O independent scavenging SCAV 50 2 0 50 SCAV_R 10 10 O2 independent deposition SCAV_R 25 & 25 SCAV_R 50 O2 dependent scavenging 50

To test the implications of different Os sink mechanisms on its marine residence time, we run a second set of simulations in which we use the previously tuned sink parameters and apply them to oceans with different nutrient availability and atmospheres with different [CO2] and thus climate.

6.3.3 The marine residence time and its dependence on the sink strength

For each simulation, we calculate the marine residence of Os. To do so, we divide the equilibrated, total marine Os reservoir M by the total annual input (In) or output (Out) of Os:

M M (6.1) τ = In = Out

Since we assume that the total Os output scales with the size of the marine Os reservoir (Out k M) = · with all tested sink mechanisms, the residence time is inversely proportional to the burial efficiency k:

M M 1 (6.2) τ = Out = k M = k · From the relationship between τ and k follows that τ can only change if k changes: For example, we can envisage two equilibrium states (designated with subscripts 1 and 2) with different marine reservoir sizes. By definition, annual input fluxes equal annual output fluxes in both cases:

(6.3) In1 Out1 k1 M1 In2 Out2 k2 M2 = = · = = ·

and equations 6.1 and 6.2 yield:

1 1 (6.4) τ1 τ2 = k1 = k2

115 CHAPTER 6. SIGNIFICANT VARIATIONS IN THE OCEAN RESIDENCE TIME OF OSMIUM WITH CHANGES IN BIOGEOCHEMISTRY

If the strength of marine Os sources is different in the two equilibrium states (In2 α In1) but = · the burial efficiency is the same (k2 k1), the marine Os cycle is still governed by the same τ in both = equilibrium states:

M2 M2 1 1 (6.5) τ2 τ1 = In2 = Out2 = k2 = k1 =

However, if the burial efficiency is different (k2 β k1), τ2 and τ1 differ proportionately: = · 1 1 1 (6.6) τ2 τ1 = k2 = β k1 = β · · This theoretical exploration illustrates that, when the strength of marine Os burial is proportional to the marine Os reservoir size, the Os residence time is not affected by altering Os input fluxes since M changes accordingly. The residence time can then only be changed by variations in the Os burial efficiency.

6.4 Results

6.4.1 Simulations of different Os sink mechanisms under pre-industrial conditions

116 6.4. RESULTS

a) DIFF b) DIFF_R 25

c) SCAV 25 d) SCAV_R 25

Figure 6.3: Comparison between the observed and simulated relationship between dissolved Os and O2 concentrations in seawater. Shown are values of all ocean grid cells in the simulation and published observations from different ocean basins (East Pacific: 1Woodhouse et al.(1999), 2Chen and Sharma (2009), 3Gannoun and Burton(2014); North Atlantic: 4Gannoun and Burton(2014); Indian Ocean: 5Levasseur et al.(1998)).

Figure 6.3 shows how the observed relationship between [Os] and [O2] (see also figure 6.2) compares to the simulation results. Without [O2]-dependent Os deposition (panels a and c), marine [Os] is very homogeneous and a relationship with [O2] is not distinguishable. If Os burial is limited to dysoxic water masses (panels b and d), a larger range of [Os] at low [O2] is simulated, matching observations more closely.

117 CHAPTER 6. SIGNIFICANT VARIATIONS IN THE OCEAN RESIDENCE TIME OF OSMIUM WITH CHANGES IN BIOGEOCHEMISTRY

a) global average b) Indian Ocean

c) North Atlantic d) East Pacific

Figure 6.4: Comparison between the observed and simulated vertical profile of [Os] in seawater. Shown are the average profile in each simulation, as well as regional simulation results and published observations (East Pacific: 1Woodhouse et al.(1999), 2Chen and Sharma(2009), 3Gannoun and Burton(2014); North Atlantic: 4Gannoun and Burton(2014); Indian Ocean: 5Levasseur et al.(1998)).

This, however, does not represent a global change in the distribution of dissolved Os, but rather is the result of local sensitivities to the inclusion of [O2] dependent sink mechanisms. Figure 6.4a shows that the effects of different sink mechanisms could hardly be distinguished in the globally averaged vertical distribution of dissolved Os given existing measurement uncertainties. Panels b, c and d of the same figure compare simulated and observed local [Os] distributions. Similarly, the global average and vertical [Os] profiles in the North Atlantic and Indian Ocean are not noticeably different under the various different sink mechanisms. By contrast, the vertical profile of [Os] varies substantially with sink mechanisms in the East Pacific, particularly when assuming Os scavenging in dysoxic waters (simulations SCAV_R). In that case, scavenging leads to a sharp [Os] decrease below the surface, the peak of which coincides with the most O2 depleted waters of the local Oxygen Minimum Zone (OMZ). Below the OMZ [Os] increases again, before it shows a small decline with further depth. These large local modulations of the [Os] profile due to Os scavenging has only a negligible effect on the distribution of Os isotopes, the

118 6.5. DISCUSSION profiles of which are almost indistinguishable between simulations with and without Os scavenging, locally and in the global average (see figure C.1).

6.4.2 Simulations of the marine Os reservoir under varying environmental conditions

a) O2 and POC fluxes under different [PO4] b) corresponding changes in Os residence time

Figure 6.5: Marine O2 inventory and POC flux as a function of nutrient abundance in cGENIE (a), as well as the corresponding marine residence time of Os (b).

Figure 6.5 illustrates O2 inventories, POC fluxes and resulting marine residence times of Os in simulations with different nutrient availability and Os sink mechanisms. Variations of the marine PO4 inventory, and subsequent changes in O2 and POC fluxes, do not affect the residence time of Os in the simulation without Os scavenging or O2-sensitivity (DIFF). Simulations including the latter processes show a reduction and increase of the residence time under increased and reduced nutrient availability, respectively. This effect is particularly strong when Os deposition is redox sensitive (DIFF_R and SCAV_R).

6.5 Discussion

There are only few measurements of vertical [Os] seawater profiles and they are associated with large analytical uncertainties which complicate the assessment of a potential relationship between [Os] and

[O2]. Still, despite considerable uncertainty in absolute [Os] values, the East Pacific samples from

Woodhouse et al.(1999) show an anti-correlation between [Os] and [O 2] independent of analysis technique. Furthermore, there is ample observational evidence for increased Os sequestration under low

[O2] and/or high TOC. Our simulations showed that [O2]-dependent Os burial could explain observed features of the East Pacific vertical [Os] profile, in particular the Os depletion in surface waters compared to the deep ocean, and the concurrence of [Os] and [O2] minima in the OMZ. The simulations further showed that a missing correlation between [Os] and [O2] in the North Atlantic and Indian ocean does not

119 CHAPTER 6. SIGNIFICANT VARIATIONS IN THE OCEAN RESIDENCE TIME OF OSMIUM WITH CHANGES IN BIOGEOCHEMISTRY necessarily imply such relationship does not exist, since its effect on [Os] in well-oxygenated waters would be minimal. Our simulation results thus suggest that enhanced Os burial under dysoxic conditions is more compatible with, and cannot be ruled out based on, existing observations. Additional measurements of [Os] and [O2] in seawater and simulations with increased spatial resolution are necessary to further ascertain and quantify the dependence of [Os] on [O2].

Figure 6.6: Deviations in spatial 187Os/188Os homogeneity in seawater versus different environmental conditions relative to today for the LGM, late Paleocene, late Cenomanian and Aptian. Estimates for differences in marine oxygenation are taken from Kaiho(1991); Jaccard and Galbraith(2012); Monteiro et al.(2012); Adloff et al.(2020); Remmelzwaal et al.(2019), in productivity from Thomas et al.(2000); Maher et al.(2010); Monteiro et al.(2012); Adloff et al.(2020), and in atmospheric CO 2 from Yiou et al. (1991); Monteiro et al.(2012); Gehler et al.(2016); Naafs et al.(2016a).

Figure 6.6 shows how different geologic time periods compare in terms of reconstructed Os isotopic heterogeneity of seawater, average Os isotopic value, atmospheric CO2, marine O2 concentration and productivity. Increased seawater 187Os/188Os heterogeneity in geological records could be caused by strengthened fractionation processes which happen on time scales below the ocean mixing time, by a reduction of the marine residence time of Os to or below the ocean mixing time, or it could be an artefact of records from basins with restricted connectivity to the open ocean. The latter is of particular concern for events of the Mesozoic or older, for which open ocean sediments may be scarce. Though in the case of the events studied here, we can exclude this possibility. Several late Pleistocene records from open ocean settings show conflicting 187Os/188Os variations across the last glacial and deglaciation, thus suggesting seawater 187Os/188Os heterogeneity in the open ocean (Paquay and Ravizza, 2012). Likewise, open ocean records are available for the late Cenomanian and Aptian, and they confirm geographic heterogeneity of 187Os/188Os (Bottini et al., 2012; Du Vivier et al., 2015). Samples are corrected for

120 6.5. DISCUSSION mass fractionation effects, which means that also fractionation processes cannot affect the geographic pattern of 187Os/188Os. Consequently, we exclude restricted circulation and local fractionation processes as potential explanation for the recorded 187Os/188Os heterogeneity in seawater, which then has to be the result of variations in the residence time of Os. Today, this residence time is several 10 kyr. To create considerable 187Os/188Os heterogeneity in past seawater, the residence time must have been close to or below the ocean mixing time. The ocean mixing time has evidently varied in the past (e.g. Schmittner et al., 2015; Donnadieu et al., 2016; Kurahashi-Nakamura et al., 2017), but not by one order of magnitude as reconstructed for Os residence time. This variation in Os residence time can only be explained by a substantial change of the relative size of the marine Os reservoir to input and burial fluxes of Os. As previously established, the Os residence time can only be changed by changing the burial efficiency if we assume that the Os burial flux is a function of its concentration in seawater (see section 6.3.3). For a residence time reduction from several 10 kyr to a few thousand kyr, the total amount of Os buried would have to have varied by at least one order of magnitude. Our simulations show that Os residence time variations of this magnitude are conceivable across the Phanerozoic if Os burial varies with [O2], and, to a lesser extent, with POC export. A link between seawater 187Os/188Os homogeneity and marine 187 188 [O2] and POC exportmight be able to explain variations in Os/ Os homogeneity for different time periods in the geologic record (figure 6.6), although this compilation is only qualitative and thus cannot numerically confirm the dominant control on 187Os/188Os homogeneity through time. The degree of oxygenation of intermediate and deep ocean layers seems to be the strongest predictor of 187Os/188Os 187 188 homogeneity since the marine O2 inventory was lower than today in all periods with reduced Os/ Os homogeneity, while it was of similar size in the Paleocene and today, coincident with homogeneous 187Os/188Os in seawater. Marine nutrient availability was higher at the last glacial maximum and in the late Cenomanian than in the Paleocene and today, which also correlates with 187Os/188Os heterogeneity but it cannot explain reduced nutrient availability coincident with more heterogeneous seawater in the 187 188 Aptian. Atmospheric CO2 concentrations seem to be a weak predictor of Os/ Os homogeneity, since periods of more and less homogeneous seawater had higher CO2 concentrations than today, and more heterogeneous seawater prevailed at the LGM, when CO2 concentrations were lower than today. All geologic periods in our compilation had less radiogenic seawater 187Os/188Os, independent of how heterogeneous seawater 187Os/188Os was. This implies that the strength of Os sinks cannot be reconstructed based on the 187Os/188Os of seawater, consistent with isotopically neutral burial processes. Together with the results from our sensitivity studies of Os concentrations under different Os sink mechanisms, there is thus compelling indication that Os reduction under low [O2]/high POC export plays a role in the burial of dissolved Os and influences its marine residence time. Our simulations of Os cycling under different marine biogeochemical conditions suggest that the implications of [O2]/POC-sensitive Os sequestration would have implications for interpretations of the geological Os isotope record. If even a minor portion of marine Os burial today is mechanistically associated with ambient [O2] or POC export, the marine residence time of Os would have been significantly shorter at times of reduced marine

121 CHAPTER 6. SIGNIFICANT VARIATIONS IN THE OCEAN RESIDENCE TIME OF OSMIUM WITH CHANGES IN BIOGEOCHEMISTRY oxygenation and increased nutrient availability. While increased POC export is an important factor in this reduction of the residence time, the degree of ocean oxygenation seems more influential, with the potential of reducing the residence time of Os below the ocean mixing time even under moderate decreases of the marine O2 inventory (<30%). The reason for this is that the relative increase in dysoxic water masses is larger under increased nutrient availability than relative changes in POC export because dysoxic water masses are small in the present day ocean.

6.6 Conclusion

Os isotopes are valuable indicators of large external perturbations of the ocean/atmosphere system on time scales 100 kyr. Using Earth system model simulations, we demonstrated that remaining uncertainty < about marine Os sinks significantly affects the accuracy of identification and quantification of such events in the geological record. If the marine Os cycle is influenced by the abundance of oxygen or POC export, its marine residence time must have varied substantially in the past with implications for the interpretation of shifts in the sedimentary Os record. There is evidence for increased geographical heterogeneity of seawater 187Os/188Os during certain intervals of the sedimentary record, in particular the last glacial period, the late Cenomanian and the early Aptian. These periods were characterized by increased nutrient supply to the oceans and reduced oxygenation of the intermediate and deep ocean. In our simulations, we showed that these conditions could result in a significantly reduced marine residence 187 188 time of Os even if only small portion of Os burial is [O2]-dependent today. As such, Os/ Os records of these periods would likely reflect a more local signature than today’s sediments, and external additions of isotopically distinct Os could have more readily overwhelmed the marine Os reservoir at those times. The latter could explain the geographically uniform, mantle-like peak excursion values during OAE 2 and OAE 1a. Our results highlight the importance of an improved understanding of the marine and sedimentary cycling of Os today for unlocking the full potential of Os as a paleo-proxy. Depending on the geographic heterogeneity of Os isotopes, 187Os/188Os could be interpreted as a weathering or water-mass tracer and provide an indication of the degree of marine deoxygenation and/or organic matter deposition. Furthermore, they underline the relevance of reconstructing past residence times of Os and obtaining multiple records from different ocean basins for an accurate assessment of an Os perturbation in sediments.

122 . Introduction 7.1 ). 8 (chapter a chapter following of the basis in the 1a form OAE will system during results Earth excursions These the isotope uncertainties. reconstruct metal associated to of discuss re-evaluation further and data-derived used how perturbation, be show a can to cycles to example metal prior an and state as C of Aptian seawater the Early oxigenated on the less constraints use the numerical I in and chapter, time present residence the reduced In a Aptian. experiments had Early sensitivity have the the could size, Os reservoir that showed Os 6 marine chapter Aptian in Early dissolved the of marine of mechanism of reconstruction burial variability the the the prevents about explored knowledge Os 6 missing Chapter Although perturbation. time. the through to to concentrations key Os prior thus cycles is metal it and perturbations, C cycle the about metal knowledge reconstruct past requires interpreting fluxes Before C cycles. on metal constraints contemporaneous quantitative in the as peaks use excursion their between of and time-lags amplitude systems of proxy and interpretation different timing the the particular, In influence of peaks. feedbacks excursion offset internal resulting isotopic and the and input size exogenic relative by the addition, caused In fluxes reservoirs. metal flux metal C on surficial forcing exogenic of the scale of The impact seawater. needs CO or ambient perturbation air to that of larger response composition the in isotopic changes and the longer the change the in appreciably perturbation, is to a element be of an to start abundant the at more ocean The the system: influenced or Earth ways atmosphere several the in of are configuration shifts contemporaneous isotopic the resulting by the that of showed emplacement also the study accompanied this However, likely during LIPs. which particularly perturbations the surface, have Earth’s biochemical large-scale sediments at and variations marine sustained flux in the mass metals into of insight composition quantifiable isotopic provide the to in potential fluctuations that found I , 5 chapter In iuaigpoycnitn rtcossaae composition seawater Cretaceous proxy-consistent Simulating 2 ocnrto aitosas eemnstesz fteisotopic the of size the determines also variations concentration 123

C h a p t e r 7 CHAPTER 7. SIMULATING PROXY-CONSISTENT CRETACEOUS SEAWATER COMPOSITION

7.2 The Early Aptian Earth system state

The chemical composition of marine sediments deposited in the Early Aptian prior to OAE 1a indicates that the isotopic and elemental compositions of seawater, and hence the climate and biogeochemical cycles which control them, of that time were different than today. Here, I review the reconstructed composition of the Aptian air and seawater as well as their suggested geophysical and geochemical drivers. This will be followed by an overview of model set-ups that have been used in previous studies to simulate Early Aptian C and metal cycling.

7.2.1 Seawater composition of the Early Aptian

Table 7.1 lists published reconstructions of seawater isotopic composition of the Early Aptian. These studies commonly assume that metal isotopes were as homogeneously distributed in Early Aptian seawater as they are today. This assumption allows for the derivation of the isotopic composition of the Early Aptian seawater from a small number of sediment records. Still, offsets between different records exist, and are included as error ranges on the derived global values in table 7.1. Ca and Sr are the only metals studied here for which detailed reconstructions of Early Aptian concentration exist. Investigation of ancient evaporites revealed that Ca concentrations were up to 3 times higher in the early Cretaceous 2 2 ( 120 Ma) than today, and that the [Mg +]/[Ca +] ratio was considerably lower (Vollstaedt et al., 2014; Turchyn and DePaolo, 2019). In combination with an Aptian Sr/Ca similar to today (Coggon et al., 2010), observations suggest that Sr concentrations might have increased in proportion to Ca in the Early Aptian. A 3 larger marine Sr reservoir in the Cretaceous is also supported by higher Sr concentrations in ocean × crust that was altered at that time (Coogan, 2009). Similar estimates are not available for dissolved Li or Os concentrations in Aptian seawater. However, considerably lower Li concentrations in the late Cretaceous are supported by the abrupt onset and large amplitude of the negative Li isotopic excursion during OAE 2 (von Strandmann 2012). If the size of the marine Os reservoir is sensitive to marine oxygenation and productivity, as suggested by the accumulation of Os in organic-rich sediments (see chapter6), it is also possible that there was less dissolved Os in the Early Aptian ocean than there is today.

Table 7.1: Isotopic composition of seawater today and reconstructed for the Early Aptian.

Proxy Modern seawater Aptian seawater References 187Os/188Os 1.05 0.6 0.2 Tejada et al.(2009); Bottini et al.(2012) ± 87Sr/86Sr 0.70918 0.7075 0.0001 Jenkyns et al.(1995) ± δ88Sr 0.39% 0.4% Vollstaedt et al.(2014) δ7Li 31.5% 24 1% Lechler et al.(2015) ± δ44Ca 0.01% 2.2 0.1% Blättler et al.(2011) ± [Sr] 92.8 µmol/kg 278.4 92.8 µmol/kg Coogan(2009) ± [Ca] 10.25 mmol/kg 30.75 10.25 mmol/kg Turchyn and DePaolo(2019) ±

124 7.2. THE EARLY APTIAN EARTH SYSTEM STATE

7.2.2 Atmosphere and Climate of the Early Aptian

Atmospheric CO2 concentrations were perhaps 2 – 4 the pre-industrial value (Foster et al., 2017). × Temperature proxies suggest that Aptian sea-surface and intermediate-depth temperatures were globally higher, consistent with increased atmospheric CO2 concentrations (O’Brien et al., 2017; Steinig et al., 2020).

7.2.3 Tectonics, spreading rates and weathering regimes

The increased concentrations of dissolved Sr (and, to a lesser extent, Ca) in the Aptian ocean were likely linked to variations of major marine Sr (Ca) sources. A major cause for the higher Sr is probably related to the enhanced terrestrial carbonate weathering and enhanced hydrothermal Sr emissions (Tripati et al., 2009).

Reconstructions of the increased total length of Aptian mid-ocean ridges and subduction margins suggest that CO2 degassing related to plate tectonics was 1.5 – 2 the present-day value (Van Der Meer × et al., 2014). In addition, because basalt alteration is arguably temperature-sensitive, hydrothermal venting of ocean crust could have provided significantly more Sr (and Ca) to the bottom waters in a warmer ocean (e.g. Coogan and Dosso, 2015). A strengthened relative importance of seafloor alteration 2 2 compared to continental silicate weathering could explain the substantially lower [Mg +]/[Ca +] of the Cretaceous ocean compared to today (Hain et al., 2015). At the same time, there is evidence for enhanced biological Ca burial. Numerical simulations of oceans with extended shelf areas and enhanced CO2 degassing indicate that neritic carbonate burial could have reached its Cretaceous apex in the Aptian, 4-10 higher than today (Pohl et al., 2020). × The reconstructed climatic conditions of the Early Aptian favoured enhanced continental crust weathering. With higher atmospheric CO2 concentration, higher air temperatures and a more dynamic biosphere with flourishing vegetation even in high latitudes (Harland et al., 2019), frequent wildfires (Brown et al., 2012) and higher run-off (simulations suggest 1 – 2 preindustrial values, Donnadieu × et al., 2006a; Hayes, 2019), the Early Aptian probably featured a more corrosive and erosive terrestrial environment than today. However, these factors by themselves do not prove that terrestrial weathering fluxes were actually increased. Besides erosion rates, carbonate weathering is also a function of rock exposure (Donnadieu et al., 2006a) and silicate weathering must additionally be balanced by CO2 emissions on long time scales. While the climate could have supported higher-than-pre-industrial weathering fluxes with pre-industrial rock exposure, reduced land surface area due to high sea level stands (see compilation in Turchyn and DePaolo, 2019) and no major orogenic events could have limited the amount of exposed, weatherable rock in the Early Aptian. It it is thus not clear how different the overall weathering rate in the Aptian were compared to today.

125 CHAPTER 7. SIMULATING PROXY-CONSISTENT CRETACEOUS SEAWATER COMPOSITION

7.2.4 Model representations of the Early Aptian Earth system state

Previous model simulations of the Early Aptian considered different combinations of the aforementioned reconstructed geophysical and geochemical conditions, but never included all of them. Instead, the number of boundary conditions considered in the previous model simulations depends on which elemental cycle the study focused.

Simulations of the Aptian C cycle either restored atmospheric CO2 concentrations disregarding of required C fluxes (e.g. Farnsworth et al., 2019), or chose terrestrial silicate weathering rates deliberately so that assumed CO2 degassing fluxes result in desired atmospheric CO2 concentrations (Pohl et al.,

2020). Similarly, I simulated higher atmospheric CO2 concentrations and increased marine carbonate burial in my Aptian set-up for chapter3 by increasing atmospheric CO 2 outgassing and terrestrial weathering.

In simulations of combined C- and metal cycles, assumptions about baseline C- and metal fluxes were notably unrelated. For example, Bauer et al.(2017a) achieved Early Aptian seawater 187Os/188Os by increasing unradiogenic hydrothermal Os input by a factor of 6 but assumed no change to pre-industrial ∼ C degassing or weathering fluxes. Blättler et al.(2011) modeled proxy-consistent seawater 87Sr/86Sr by increasing pre-industrial hydrothermal Sr input by a factor of 10 while leaving pre-industrial ∼ hydrothermal Ca inputs unchanged. The only other change to Sr and Ca cycles in that study was a reduced Ca burial efficiency to achieve a 2.5 larger marine Ca reservoir, while the present-day Sr × reservoir size remained unchanged. The most complex modelling of Early Aptian metal cycles was done by Lechler et al.(2015) who coupled dynamical models of Sr-, Os-, Li- and Ca-cycles and simulated the Early Aptian background state by increasing the mid-ocean ridge hydrothermal input for all elements and tuning the composition of continental run-off to achieve proxy-consistent seawater composition. However, they did not consider effects of C cycle changes.

The quantitative implications of these choices for the results of perturbation experiments are rarely discussed or even assessed. Not knowing the sensitivity to boundary condition choices underestimates the true uncertainty on reconstructed metal and C fluxes, can result in biogeochemical inconsistencies within one set-up and create difficulties with multi-study comparisons. Here, I take a more systematic approach to reconstructing the Early Aptian background state with associated conceptual and quantitative uncertainties. For this, I exploit the ability of cGENIE to simulate coupled C and metal cycle states, which provides a novel opportunity to investigate how Earth system changes affect the isotopic composition of seawater and to identify Earth system configurations which are consistent with multiple lithological proxies of a particular time period. I first simulate the effects of different boundary conditions on seawater composition to assess the range of scenarios consistent with Early Aptian proxy data. I then simulate Early Aptian background states by iteratively varying boundary conditions from the present-day model set-up and assess how well they align with Early Aptian reference proxy data. The following sections describe the modelling set-up and results for each of these two parts.

126 7.3. IMPACT OF BOUNDARY CONDITION CHANGES ON THE SEAWATER COMPOSITION

7.3 Impact of boundary condition changes on the seawater composition

In the first part of this chapter, I investigate how changes in prescribed boundary conditions affect the simulated steady state isotopic composition of seawater. This investigation helps identify the processes with the largest potential to produce the reconstructed composition Early Aptian seawater, as the biogeochemically relevant differences between the present-day and the Aptian Earth system states are still poorly constrained. Instead of choosing a pre-defined subset of boundary condition changes for simulations of the Early Aptian ocean based on conceptual models, I can thus base my choice on quantitative considerations.

7.3.1 Methods

The first set of simulations is aimed at identifying which possible boundary condition changes move the present-day seawater composition closer to that reconstructed for the Early Aptian. Starting from the present-day configuration developed in chapter4, I set up a series of simulations in which I changed individual boundary conditions and let the model re-balance the biogeochemical cycles over a 20 Myr period. The only modification to the previously used model set-up is a slight alteration of the Ca cycle: Here, I combined the Ca input from hydrothermal sources and silicate weathering so that marine Ca and alkalinity inputs vary synchronously with temperature. This is required to stabilize the carbonate system on long time-scales in the absence of temperature-dependent ocean crust alteration and a full, dynamical Mg cycle. Once a new equilibrium was reached, I compared the resulting isotopic signature of seawater and residence times of dissolved metals with the modern-day set up as described in chapter4 and the previously presented reconstruction of Early Aptian seawater (see table 7.1). The tested variations in boundary conditions are described in the following paragraphs, and are summarized in table 7.2.

127 CHAPTER 7. SIMULATING PROXY-CONSISTENT CRETACEOUS SEAWATER COMPOSITION

Table 7.2: Overview of my simulations and respective variations in boundary conditions relative to the prescribed values in the pre-industrial set-up (see chapter4).

Simulation name Varied boundary condition Range of relative changes

CO2 CO2 outgassing 50% - 400% CaCO3 continental carbonate weathering rate 10% - 400% CaSiO3 continental silicate weathering rate 10% - 200% WEATH total continental weathering rate 50% - 200% LT-HYD low-temperature hydrothermal activity 50% - 200% HT-HYD high-temperature hydrothermal activity 50% - 400% HYD total hydrothermal activity 50% - 200% PO4 marine nutrient reservoir size 50% - 200% REEF amount of reefal carbonate burial 50% - 200%

PICPOC ratio of CaCO3 to POC export 50% - 200% CONG isotopic effect of terrestrial clay formation 0%-100% AGE isotopic effect of weathering unradiogenic crust 0%-100%

7.3.1.1 CO2 outgassing

There is ample evidence that the net flux of CO2 from the mantle into the surficial Earth system varies over time, sustaining periods of warm climate and repeatedly causing pulses of transient warming (Mills et al., 2017a). Through climate-sensitive rock weathering and the stability of carbonates in the ocean, variations in the amount of atmospheric and marine C also affect the cycling of Sr, Os, Li and Ca. Here,

I tested the implications of different CO2 outgassing rates relative to the pre-industrial baseline (8.58 1 Gmol yr− , simulations ’CO2’), simulating from colder, more CO2-depleted to warmer, CO2-enriched Earth systems: 90%, 150%, 200% and 400% of the value in the pre-industrial set-up (8.57 Tmol/yr), covering the full range of reconstructed Phanerozoic degassing rates (100% – 300% the pre-industrial value, Mills et al., 2017a).

7.3.1.2 Continental crust weathering

The continental crust is the dominant source of marine Sr, Os, Li and Ca today and variations in the isotopic composition of these marine metal reservoirs have repeatedly been used to infer the amount of rock weathering (e.g. Hodell et al., 1990; Ravizza et al., 2001; Blättler et al., 2011; Lechler et al., 2015).

Variations in weathering also strongly influence surficial carbon cycling through CO2 sequestration and delivery of alkalinity to the ocean (e.g. Goddéris and François, 1996). However, variations in continental crust weathering are not just climate-driven, as in the simulations of varied CO2 outgassing, but they are also influenced by sea level, mountain uplift, paleogeography and the size of biosphere (see review in Penman et al., 2020). I thus tested scenarios of non-climatic weathering changes by changing continental crust weathering rates: 10%, 150% and 200% of the pre-industrial spin up. Further, to study the effects

128 7.3. IMPACT OF BOUNDARY CONDITION CHANGES ON THE SEAWATER COMPOSITION of carbonate versus silicate weathering, I produced three different sets of experiments, two in which I change the rates for only one of the two rock weathering types (’CaSiO3’ and ’CaCO3’ in table 7.2), and one in which weathering rates of both were changed in tandem (’WEATH’ in table 7.2). This range of silicate weathering changes results in atmospheric CO2 concentrations of 100 – 2000 ppm, which covers long-term atmospheric CO2 concentration estimates for at least the past 300 Myr (e.g. Goddéris et al., 2014).

7.3.1.3 Hydrothermal activity

Interactions between seawater, oceanic crust and mantle magma affect the composition of seawater (e.g. Seyfried Jr and Mottl, 1982). Depending predominantly on the ambient temperature and geological setting, seawater circulating through the seafloor can lose or gain elements to reactions with the host rocks. The amount of C and metals thus released into the ocean varies with the production and cooling rates of oceanic crust. To capture these effects, I changed the magnitude of individual and joint contributions of high- and low-temperature hydrothermal emissions (simulations ’HYD’, ’HT-HYD’ and ’LT-HYD’ in table 7.2) within a range which is consistent with estimated spreading rate variations over the past 150 Myr (Jones and Jenkyns, 2001).

7.3.1.4 Biological productivity and carbonate deposition

To investigate further metal sinks, I studied the isotopic variations due to changes in biogenic carbonate deposition rates. The latter constitutes the dominant sink for dissolved Sr and Ca in today’s ocean, and stable isotope fractionation occurs for Sr, Ca and Li during the formation of biogenic carbonates. In cGENIE, the rate of biological carbonate production is proportional to primary production of organic matter. Primary productivity and carbonate deposition vary in all previously described simulations, because they depend on temperature, seawater pH and alkalinity. However, such variations can also be caused by environmental changes independent of climate and alkalinity supply, for example variations in the availability of nutrients in the ocean, ecosystem structure or extent of shallow ocean deposition due to sea-level changes (e.g. Berger et al., 1989). To simulate the isotopic effects of variations in the biological pump and biogenic carbonate deposition independent of climate and alkalinity supply, I explored the effect of the size of the marine nutrient inventory (simulations ’PO4’ in table 7.2) and reefal carbonate deposition (simulations ’REEF’ in table 7.2), both of which I changed by 50%, 150% and 200% relative to the baseline values in the pre-industrial spin up. In both cases, this covers values reconstructed for the Cretaceous (Monteiro et al., 2012; Pohl et al., 2020). I also ran simulations with 50% and 200% of the pre-industrial PIC:POC ratio in biogenic export from the surface ocean (’PICPOC’), however, the extent of past PIC:POC changes is poorly constrained.

7.3.1.5 Composition of continental run-off

For my final sensitivity analysis, I varied the composition of continental run-off to account for factors other than the total amount of weathered rock and the ratio of silicate versus carbonate weathering. A

129 CHAPTER 7. SIMULATING PROXY-CONSISTENT CRETACEOUS SEAWATER COMPOSITION range of lithological, climatological and chemical controls on the isotopic composition of terrestrial run-off have been identified: Radiogenic Os and Sr isotopes in rivers are strongly influenced by the radiogenic signature of the weathered rock which is dependent on the mineralogy of the rock and its age. Sulphide and organic-rich rocks contain significantly more radiogenic Os than igneous rock (Esser and Turekian, 1993; Georg et al., 2013). Similarly, the radiogenic Sr isotope ratio varies between granites, basalts and carbonates (e.g. Goldstein, 1988). The mineralogy of the weathered rock also determines its stable Sr, Ca and Li isotope composition (Teng et al., 2004; Tipper et al., 2008; Pearce et al., 2015). However, the δ88Sr, δ7Li, δ44Ca values of run-off into the ocean are often dominated by the amount of dissolution and secondary mineral formation in terrestrial waters (Tipper et al., 2008; Pearce et al., 2015). As in other metal cycle models (e.g. Tejada et al., 2009; Misra and Froelich, 2012; Blättler et al., 2011), none of these processes are simulated by the cGENIE version used for the presented simulations, which arguably constitutes one of the biggest simplifications in the simulations of these metal cycles. In the absence of mechanistic constraints in the present and previous studies, the isotopic composition of past run-off is prescribed strategically to close the isotopic balance in such a way that a proxy-consistent seawater composition is achieved. To investigate the isotopic effect of changes in continental run-off composition, I ran one simulation in which I set 187Os/188Os and 87Sr/86Sr of continental run-off equal to the composition of fresh basalt (’AGE’). In another simulation, I quadrupled the [Li] of run-off and set its δ7Li=2% of run-off to simulate a fully congruent weathering regime to test the effect of changed rates terrestrial clay formation (Misra and Froelich, 2012) (’CONG’ in table 7.2). In that simulation, I also set the δ88Sr to pure basaltic values to test the maximum strength of erosion- and lithology-driven changes in riverine δ88Sr (Pearce et al., 2015).

7.3.2 Results

The results of the simulated boundary condition changes are presented in this section.

130 7.3. IMPACT OF BOUNDARY CONDITION CHANGES ON THE SEAWATER COMPOSITION

Table 7.3: Atmospheric CO2 and seawater composition changes as a result of variations in boundary conditions in my pre-industrial model set-up. The table presents isotopic and concentration shifts from the most extreme boundary changes that I tested (see table 7.2). Negative and positive changes outside of measurement uncertainty are highlighted in blue and red, respectively. Colour shading indicates the scale of the change relative to the maximum change across all simulations.

Proxy 187Os/188Os 87Sr/86Sr δ88Sr (%) δ7Li (%) δ44Ca (%) δ13C (%) CO (ppm) Sr (µmol/kg) Ca (mmol/kg) Simulation 2 CO2 -10% = -0.0002 -0.01 -0.33 -0.02 +0.45 -77.0 +22.63 +3.78 CO2 -10% Ca adj. = -0.0002 = -0.5 = +0.45 -78.0 = = CO2 +300% +0.06 +0.0024 +0.02 -7.16 -0.02 -3.62 +5685.0 -82.4 -9.53 CO2 +300% Ca adj. +0.07 +0.0026 +0.02 +3.0 +0.02 -3.87 +6730.0 +69.08 +2.54 HYD -50% +0.05 +0.0006 +0.02 +2.46 +0.01 = +102.0 -30.59 -4.02 HYD -50% Ca adj. +0.05 +0.0005 = +1.58 = +0.72 +107.0 = = HYD +100% -0.11 -0.0013 -0.03 -3.67 -0.04 -0.14 -147.0 +39.87 +8.11 HYD +100% Ca adj. -0.1 -0.0012 = -3.65 +0.02 +0.51 -146.0 = = HT-HYD -50% +0.03 +0.0002 = +1.62 -0.01 +0.4 -47.0 = +1.09 HT-HYD +100% -0.14 -0.0005 +0.02 -6.8 +0.04 -1.63 +351.0 -32.14 -5.38 HT-HYD +100% Ca adj. -0.13 -0.0005 = -6.25 = -1.65 +381.0 +22.05 = LT-HYD -50% +0.02 +0.0004 +0.02 -4.53 +0.02 = +161.0 -13.86 -2.81 LT-HYD +100% -0.02 -0.0003 = -0.13 -0.03 = -124.0 = +1.73 LT-HYD +100% Ca adj. -0.06 -0.0002 = +2.08 +0.03 +0.13 -185.0 = = WEATH -50% -0.02 +0.0005 = +0.25 -0.04 +0.43 +933.0 = = WEATH +100% +0.02 -0.0004 = -0.27 +0.02 -0.15 -183.0 = = CaSiO3 -50% +0.01 -0.0003 = -0.1 -0.02 +0.32 +933.0 +10.08 = CaSiO3 -90% Ca adj. +0.02 -0.0014 -0.02 -1.68 -0.05 +1.06 +11109.0 +15.73 +2.63 CaSiO3 +100% -0.02 +0.0005 = +0.16 +0.03 = -183.0 = = CaSiO3 +100% Ca adj. = +0.0009 = +1.06 +0.03 -0.11 -150.0 +10.94 = CaCO3 -90% -0.08 +0.0018 +0.03 +0.55 = +0.42 = = = CaCO3 +300% +0.06 -0.0017 -0.03 -1.59 = -0.21 = = = REEF -50% = = = -0.14 = -0.13 = +24.58 = REEF +100% = = = +0.29 -0.02 +0.27 = -27.65 = PICPOC -50% = = = -0.11 +0.01 = = +28.45 = PICPOC +100% = = = -0.16 = -0.15 = +22.23 = CONG 100% = = -0.05 -14.0 = = = = = AGE 0% -0.49 -0.0057 ======

131 CHAPTER 7. SIMULATING PROXY-CONSISTENT CRETACEOUS SEAWATER COMPOSITION

a) 187Os/188Os vs 87Sr/86Sr b) 187Os/188Os vs δ7Li 400 400 35.0 0.712 350 350 32.5

300 300 0.710 30.0

250 250 ) r 27.5 S

6 0.708 8 ( / 200 200 i r Aptian L S

7 25.0 7 8 0.706 150 Aptian 150 22.5

100 100 0.704 20.0 50 50 17.5 Boundary condition setting (% of pre-industrial) Boundary condition setting (% of pre-industrial) 0.702 0 0 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 187Os/188Os 187Os/188Os

87 86 44 87 86 7 c) Sr/ Sr vs δ Ca d) Sr/ Sr vs δ Li 400 400 400 35.0 2.30 0.712 350 350 350 2.25 32.5

300 300 300 30.00.710 2.20 Aptian ) 250 250 2.15 ) 27.5 250 ( r

S a (

200 200 6 i C 0.708 8 0 L /

4 2.10 200

7 25.0 / r

4 Aptian S 4 150 Aptian 150 7 2.05 8 22.5 0.706 150 100 100 2.00 20.0 100 50 50 1.95 17.50.704 Boundary condition setting (% of pre-industrial) Boundary condition setting (% of pre-industrial) 0 0 50 0.702 0.704 0.706 0.708 0.710 0.712 0.702 0.704 0.706 0.708 0.710 0.712 87Sr/86Sr 87Sr/86Sr Boundary condition setting (% of pre-industrial) 0.702 0 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 187 188 87 86 88 44 Os/88 Os 13 e) Sr/ Sr vs δ Sr f) δ Ca vs δ Sr g) [CO2] vs δ C 400 400 400

0.52 0.52 350 350 350 6

0.50 300 0.50 300 300 ) ) ) 7 0.48 250 0.48 250 250 ( ( (

r r

200 m 200 200 t S S

a Aptian 6 0.46 6 0.46 8 8 8 C / / 3 8 8 1 8 150 8 150 150 0.44 0.44 9 100 100 100 0.42 0.42 50 5010 50 0.40 0.40 Boundary condition setting (% of pre-industrial) Boundary condition setting (% of pre-industrial) Boundary condition setting (% of pre-industrial) 0 0 0 0.702 0.704 0.706 0.708 0.710 0.712 1.95 2.00 2.05 2.10 2.15 2.20 2.25 2.30 102 103 104 87 86 44/40 Sr/ Sr Ca ( ) [CO2, atm] (ppm)

187 188 87 86 88 7 44 13 Figure 7.1: Os/ Os, Sr/ Sr, δ Sr, δ Li, δ Ca, δ C and atmospheric CO2 in simulations with step changes in different boundary conditions (see section 7.3.1). Every symbol style represents a different boundary condition that was changed and symbol colors indicate the different degrees of change that were tested. Arrows connect the results of simulations with modern-day boundary conditions and the biggest tested boundary condition change, pointing in the direction of an increase in the respective condition. The reconstructed composition of Aptian seawater (see table 7.1) with error margins is indicated where available.

132 7.3. IMPACT OF BOUNDARY CONDITION CHANGES ON THE SEAWATER COMPOSITION

Table 7.3 illustrates which boundary condition changes result in notable shifts in the size or isotopic composition of atmospheric C and marine metal reservoirs, as well as the direction and maximum simulated amplitude of these shifts. All tested boundary condition changes affect more than one reservoir, highlighting the wide-ranging impact of the tested boundary condition changes. Apart from decreased reef carbonate deposition and increased PIC:POC of pelagic primary production, there is no tested boundary condition change that shifts all reservoirs in the same direction. The majority of the tested boundary condition changes thus result in a unique fingerprint in those reservoirs. Further to table 7.3, figure 7.1 shows the size of the isotopic shifts from all experiments along with observed proxy values for the Early Aptian. The size of the modelled shifts depends on the strength of the boundary condition change. Most isotopic effects appear to be linearly related to the extent of boundary 44 condition change, although there are exceptions (e.g. the effect of increased CO2 degassing on δ Ca). The fact that the majority of these lines are not parallel to the plot axes mirrors my previous result that most isotopic shifts do not occur in isolation. End-member compositions of run-off, representative of unradiogenic rock weathering and substantially less clay formation in rivers, result in the largest isotopic shifts and come closest to Early Aptian values in all metal isotope systems except for δ44Ca. However, the extent of run-off composition changes which produce the observed offset between present-day and Early Aptian seawater is different for each metal system. For instance, simulating data-consistent seawater 187Os/188Os requires the average age of weathered crust to be much younger than what is necessary to reproduce Early Aptian 87Sr/86Sr. Increased hydrothermal fluxes shift all isotope systems towards Early Aptian values, but the size of these shifts in all metal isotope systems except 87Sr/86Sr is insufficient.

Increasing CO2 degassing alone, a common approach in simulations of the Cretaceous C cycle, results in enhanced continental weathering which shifts seawater δ7Li in accordance with proxy constraints but also causes 187Os/188Os and 87Sr/86Sr shifts towards more continental values, as opposed to the less radiogenic values recorded in Aptian sediments. Non-climate-driven increases in weathering of sedimentary rock have the potential to reproduce Aptian 87Sr/86Sr, but cause an insufficient shift towards lower δ7Li and increases, rather than decreases, in 187Os/188Os. No single tested boundary condition change can reproduce a data-consistent seawater δ44Ca. The largest implication of adjusted Ca input is a reversal in the sign of Ca and Sr concentration changes in scenarios of climate-driven or prescribed silicate weathering changes. In cases where the 2 supply of alkalinity to the ocean is entirely climate-sensitive while a portion of the Ca + supply is 2 invariant, atmospheric CO2 increase and the induced warming cause an imbalance in the delivery of Ca + 2 and alkalinity, which results in a temporal outpacing of Ca + supply by enhanced CaCO3 burial, and thus a reduction of marine Ca concentrations. Since Sr is strongly related to Ca burial, Sr concentrations also decrease in these cases. On the contrary, if the increased alkalinity supply is matched by an increased 2 Ca + delivery, both marine Ca and Sr reservoirs can grow.

133 CHAPTER 7. SIMULATING PROXY-CONSISTENT CRETACEOUS SEAWATER COMPOSITION

Figure 7.2: Changes in metal and C reservoirs and the marine carbonate system due to different boundary condition changes (see section 7.3.1). Each symbol represents a boundary condition change. The size of the symbols represents the relative size of the simulated change. Values in the present-day spin-up are indicated by horizontal dotted lines. Dashed lines indicate reconstructed values for the Aptian, where available. Symbols highlighted in orange show results for simulations with unequal temperature dependencies of Ca and alkalinity inputs (equal dependencies in grey).

Figure 7.2 shows simulated changes of the reservoir sizes and selected parameters of the carbonate system due to boundary condition changes in comparison Early Aptian reconstructions (where available, see table 7.1). Reconstructions of marine and atmospheric elemental reservoir sizes are much more uncertain than reconstructions of their isotopic compositions. However, scenarios that fail to reproduce at least the sign of reconstructed reservoir size changes can be regarded as less realistic than those which do. The simulations suggest that considerable growth of the marine Ca and Sr reservoir sizes requires large increases in CO2 degassing or hydrothermal emissions, as well as temporary offsets between alkalinity and Ca supply. Whether Ca and alkalinity input changes are proportional or not also affects the direction of changes in the marine reservoirs of Ca and Sr (via the impacts on carbonate burial and the C cycle). My simulations of a climate-insensitive submarine Ca source (gray symbols in fig. 7.2) show that climate-related variations in the relative abundance of Ca and alkalinity supply to the oceans result in seawater composition changes that are opposite of those expected from simulations with fully coupled Ca and alkalinity supply (yellow symbols). If the Ca and alkalinity sources have equal climate-dependencies, Ca fluxes are always balanced by alkalinity fluxes, which is a common assumption in simulations of the long-term C cycle (e.g. Ridgwell and Hargreaves, 2007; Colbourn et al., 2013). However, my simulation results show that this simplification might lead to misrepresentation of metal reservoir changes on geological timescales, given that concepts of more complex weathering

134 7.3. IMPACT OF BOUNDARY CONDITION CHANGES ON THE SEAWATER COMPOSITION

fluxes in various environments are emerging (e.g. Coogan and Dosso, 2015; Hilton and West, 2020). There is evidence that there are multiple temperature-dependent sources of Ca and alkalinity which are uncoupled or release Ca and alkalinity at different ratios than Ca-bearing silicate and carbonate weathering (e.g. weathering of non-Ca-bearing carbonates or silicates and evaporites as well as seafloor alteration, Coogan and Dosso, 2015). No simulation achieved Sr and Ca concentrations reconstructed for the Early Aptian. The offset between reconstructed Early Aptian values and simulation end-members is particularly stark for marine Ca concentrations although marine Ca concentrations vary substantially more under imbalanced Ca and alkalinity supplies.

7.3.3 Discussion

Several boundary conditions between the present-day and the Early Aptian have been reconstructed (see section 7.2), but others are still uncertain or unknown. The isotopic composition of dissolved metals in Early Aptian seawater is comparatively more certain than the strength of geological processes in the Early Aptian. The reconstructed seawater composition therefore provides additional constraints on the Early Aptian Earth system state if the isotopic effect of boundary condition changes is known, since marine metal reservoirs respond to a range of Earth system changes. In this section, I will discuss the simulated effects of boundary condition changes on the seawater composition and consequences for the construction of a proxy-consistent cGENIE Early Aptian configuration. No single tested boundary condition change shifted all proxy systems to Early Aptian values, in terms of direction and size (see table 7.3). While several of the tested boundary condition changes have large transient effects on seawater, the simulations show that a change in any boundary condition needs to be substantial enough to cause steady-state seawater composition changes similar to the reconstructed offset between pre-industrial and the Early Aptian. Out of all tested boundary condition changes, only a substantially more unradiogenic average 187Os/188Os of terrestrial run-off, and thus weathered rock, has the potential to produce the reconstructed offset between Early Aptian and pre-industrial seawater 187Os/188Os. The required change in the average 187Os/188Os of weathered rock could be achieved by a younger average age of the rock or a reduced weathering of organic-rich sediments or evaporites. This paucity of steady state options to achieve the reconstructed seawater 187Os/188Os contrasts with 87Sr/86Sr and δ7Li, the reconstructed Early Aptian values of which can be reproduced in multiple ways: lower average 87Sr/86Sr of weathered rock, enhanced carbonate weathering or increased hydrothermal emissions and lower δ7Li of terrestrial run-off, increased high-temperature hydrothermal emissions or increased CO2 outgassing, respectively. The fact that none of the presented simulations reproduce Aptian seawater δ44Ca is consistent with the suggestion that fractionation in the marine Ca sinks (not accounted for in my simulations) control the long-term evolution of δ44Ca rather than imbalances in Ca input fluxes (Gussone et al., 2020). In particular, based on the isotopic offset between aragonite and calcite it has been predicted that calcite-dominated carbonate deposition in the Mesozoic, including the Aptian, could have depleted the marine 44Ca reservoir below the present-day aragonite-dominated deposition regime (Gussone et al., 2020).

135 CHAPTER 7. SIMULATING PROXY-CONSISTENT CRETACEOUS SEAWATER COMPOSITION

Another important uncertainty relates to the simulated size changes of the marine reservoirs of Sr, Li, Os and Ca. The isotopic shifts of these metals that can be caused by external perturbation fundamentally depend on the contemporary size of their marine reservoirs. Indeed, if a marine reservoir is small, a small addition of isotopically distinct material is sufficient to appreciably shift the isotopic composition of seawater compared with when the marine reservoir is large. Several previous quantitative interpretations of metal isotope excursions assumed that the marine reservoir size of some of the metals in question did not vary significantly over time, and that isotopic changes in past seawater can thus be interpreted as if they happened in the modern ocean (e.g. Blättler et al., 2011; Bauer et al., 2017a).

Where metal reservoir variations have been considered, these assumptions were usually done independently of C flux changes (e.g. Blättler et al., 2011; Lechler et al., 2015). This is a critical simplification, the associated implications of which can be explored with the previously presented simulation results. While the evolution of marine concentrations of these metals have barely been investigated (with the exception of Ca and Sr Coogan, 2009; Vollstaedt et al., 2014; Turchyn and DePaolo, 2019), there is no evidence to preclude substantial changes in marine reservoir sizes and residence times for each of these metals since the Cretaceous. The suite of boundary conditions explored in my simulations produce marine metal reservoirs that differ from the modern by up to 175% for Ca and Sr, 280% for Os, and 300% for Li. These changes, however, are not caused by the same boundary condition variation. Thus, boundary condition changes also affect the relative proportion of metal reservoirs by causing bigger variations in some reservoir sizes than in others. Given that the reservoir size influences the timescale on which isotopic excursions evolve under exogenic forcing and their amplitude (see chapter5), these results highlight the necessity to consider reservoir size changes in the interpretation of past multi-metal isotope excursions. Furthermore, it suggests that, if past boundary conditions are not well constrained, uncertain initial reservoir sizes can be a considerable error source in metal and C flux reconstructions worth quantifying.

Finally, the results of the ensemble show that variations in the amount of alkalinity in the ocean can have a larger influence on the evolution of marine Ca and Sr concentrations, and pH, than changes in 2 Ca + delivery or atmospheric CO2 concentration. If changes in the influx of alkalinity are matched by 2 changed Ca + delivery, they should be pH neutral in the long-term since carbonate saturation creates a 2 negative feedback on the pH-effect of changed alkalinity and Ca + supply. In this case, atmospheric

CO2 concentrations dominate changes in marine carbonate chemistry and predictions of lower pH 2 and increased dissolved Ca + under higher atmospheric CO2 concentrations are reproduced by the 2 model simulations (my experiments with adjusted Ca + supply). If, however, the Ca:alkalinity ratio of marine inputs or outputs is variable (e.g. due to Mg-bearing silicate weathering), CaCO3 burial changes result in a relative depletion or accumulation of Ca or alkalinity in the ocean, which can strongly affect pH and marine Ca and Sr concentrations. Simulations with unsteady Ca:alkalinity ratio of marine sources or sinks produce the opposite pH and Ca concentration changes than what is predicted purely by the atmospheric CO2 concentration. If the Ca cycle is simplified to inputs from weathering of Ca-bearing silicates and carbonates and outputs via carbonate burial (typical for models designed for

136 7.3. IMPACT OF BOUNDARY CONDITION CHANGES ON THE SEAWATER COMPOSITION sub-geological time-scales e.g. most published configurations of cGENIE and LOSCAR, Ridgwell and Hargreaves, 2007; Zeebe, 2012; Lord et al., 2016), simulations of seawater chemistry changes feature constant Ca:alkalinity ratios of marine sources/sinks by design. In contrast, models of geological-scale biogeochemical change contain independent, climate-sensitive sources and sinks of Ca and alkalinity (e.g. hydrothermal vents and weathering of Mg-bearing silicates, Wallmann, 2001; Berner, 2006; Arvidson et al., 2014). As a result, atmospheric CO2 and pH are less closely related in these models than in models with constant Ca:alkalinity (Wallmann, 2001; Ridgwell, 2005; Arvidson et al., 2014; Zeebe and

Tyrrell, 2019). However, even in those models, atmospheric CO2 concentration remains the dominant driver for pH changes, unlike in my simulations without Ca adjustment. This is corroborated by the fact that proxy-based, independent reconstructions of pH and atmospheric CO2 for the Cenozoic show a strong inverse relationship between atmospheric CO2 concentrations and pH (e.g. Krissansen-Totton and Catling, 2017; Zeebe and Tyrrell, 2019), suggesting that my simulations without Ca adjustment result in more extreme decoupling of Ca and alkalinity fluxes than what would be representative of 2 Cenozoic or Mesozoic seawater composition change. One reason for amplified differences of Ca + and alkalinity balances in my simulations is that low-temperature hydrothermal activity is currently not temperature-sensitive in cGENIE. However, despite considerable evidence that this is the case (e.g. Krissansen-Totton and Catling, 2017). The different results of simulations with and without Ca adjustment highlight that atmospheric CO2 concentrations only dominate marine pH changes when climate-sensitive Earth system processes maintain a close-to-constant Ca:alkalinity ratio of marine inputs and outputs. It is interesting to note that one consequence of alkalinity-driven pH changes is a larger variability of marine Ca concentrations and that the simulated boundary condition changes cannot achieve size variations of the marine Ca reservoir close to reconstructions of the Early Aptian with Ca adjustment (see figure 7.2). The inability to simulate a substantially larger marine Ca reservoir suggests that processes relevant for the dynamic production of the Early Aptian marine Ca reservoir are missing from the current cGENIE version. It could be interesting to explore if shifts in the Ca:alkalinity of marine sources or sinks could have contributed to the formation or cessation of ’calcite seas’, periods of high marine Ca concentrations and predominant calcite precipitation like the Early Aptian. However, dynamic Mg and Ca cycling across the seafloor-seawater interface is likely a more relevant process, the absence of which could explain the observed discrepancies between the simulated and reconstructed Ca reservoir variability. cGENIE has a Mg tracer but processes are missing to balance Mg sinks and sources dynamically. In the pre-industrial model set-up described in chapter4, a portion of the continental silicate weathering flux is derived from Mg-bearing silicates. The Mg and Ca cycles are balanced through a fixed exchange of dissolved Mg for dissolved Ca at the seafloor, simulating elemental fluxes during ocean crust alteration. Since silicate weathering is climate-sensitive in cGENIE while the Mg-Ca exchange in the deep ocean is fixed, simulations of climate-driven weathering flux changes result in a growing marine Mg reservoir, while the marine Ca reservoir is depleted because continued supply of terrestrial alkalinity is not matched by increased Ca supply. Overall, this results in increased seawater Mg/Ca, which is the opposite of the reduced Mg/Ca reconstructed for the Early Aptian. In simulations without

137 CHAPTER 7. SIMULATING PROXY-CONSISTENT CRETACEOUS SEAWATER COMPOSITION

Mg/Ca exchange at the seafloor and pure weathering of Ca-bearing silicates on land, the Mg/Ca ratio changes little because the marine Mg reservoir is static and the growth of the marine Ca reservoir is inhibited by increased carbonate burial. In order to achieve proxy-consistent higher Mg/Ca and a tripling of the marine Ca reservoir, cGENIE needs to be initialized accordingly.

7.4 Simulations of the Early Aptian Earth system

The set of simulations discussed in this chapter show that shifts in metal isotope compositions can be used to fingerprint boundary condition changes, but also that no single tested boundary condition change matched all Early Aptian proxy data. In the absence of a single boundary condition change which shifts pre-industrial seawater composition to Early Aptian values, I set up combinations of boundary condition changes to simulate proxy-consistent Early Aptian seawater. For this, I focused on the four boundary condition changes which showed the largest effect on multiple isotope systems: CO2 degassing rate, proportion of carbonate to silicate weathering on land, hydrothermal activity and the isotopic composition of continental run-off. I then tuned related model parameters so that a proxy-consistent seawater composition is achieved. The exact combination of processes which produced the Early Aptian seawater composition and their relative importance remains unknown. In order to quantify the effect of these uncertainties in the combination and scaling of boundary condition changes on the simulated C and metal cycles, I establish a range of configurations in which the seawater composition is consistent with the proxy data. In the following section, I describe the resulting model configurations.

7.4.1 Methods

I produced steady state simulations of Early Aptian C and metal fluxes following three stages. In the first stage, I equilibrated the ocean dynamics and air-sea gas exchange to Early Aptian paleogeography, solar insulation and atmospheric CO2 with Early Aptian input fields (see description in chapter2).

Atmospheric CO2 concentration was restored to 850 ppm throughout the 20 kyr-long simulation and marine alkalinity and Ca concentrations were artificially kept constant by coupling continental input to carbonate burial rates. The only difference compared with the spin-up strategy in chapter3 is that I initialize the marine Ca and Mg concentrations with 0.03075 mol/m3 and 0.0328 mol/m3 respectively, yielding Mg/Ca = 1.07, consistent with reconstructions (Turchyn and DePaolo, 2019). In the second stage, I equilibrated the marine carbonate system under prescribed CO2 outgassing rates, allowing the dynamical adjustment of the weathering module. In the final stage, I added isotope-enabled cycling of Ca, Sr, Os and Li. The order of simulations is shown in figure 7.3. A description of the physical set-up (stage 1) is provided in chapter2 and the procedures for stages 2 and 3 are described in more detail below.

138 7.4. SIMULATIONS OF THE EARLY APTIAN EARTH SYSTEM

Physics Carbon cycle Metal cycles

stabilizing atmospheric CO2 tuning isotopic composition of continental run-off

1x pre-industrial 1xHYDPI +CaCO3 hydrothermal fluxes 2x pre-industrial 2x pre-industrial CaCO3:CaSiO3 2xHYDPI

2x pre-industrial 1xHYDPI 2xCO2PI CO2 outgassing Aptian 2xHYDPI physics 1x pre-industrial 1xHYDPI 1xCO2PI CO2 outgassing 2xHYDPI 1xHYD 2x pre-industrial CaCO3:CaSiO3 1x pre-industrial PI +CaCO3 hydrothermal fluxes

2x pre-industrial 2xHYDPI

Figure 7.3: Modelling stages to produce proxy-consistent spin-ups of Early Aptian C and metal cycles. In stage 1 ("Physical boundary conditions"), I equilibrate the model with the physical input fields representative of the Aptian and 840 ppm atmospheric CO2 concentration. In stage 2 ("Carbon cycle"), I set up for different C cycles which stabilize atmospheric CO2 at 840 ppm. In stage 3 ("Metal cycles"), I set up two different versions of proxy-consistent metal cycles for each C cycle configuration and tuned the isotopic composition of continental run-off to achieve proxy-consistent marine metal reservoirs.

7.4.1.1 Early Aptian C cycle set-up

In the second stage of the Early Aptian spin ups, I ran the model from the first stage ("Physical" step) with an open carbonate system (weathering inputs of Ca and alkalinity are independent of marine carbonate burial) and without artificially restoring the atmospheric C reservoir. In order to explore implications of

uncertainties in Early Aptian CO2 outgassing fluxes and the ratio of carbonate to silicate weathering,

I ran a total of four simulations, with either 1 or 2 pre-industrial CO2 outgassing (’1xCO2PI ’ and × × ’2xCO2PI ’) and 1 or 2 pre-industrial carbonate:silicate weathering (’+CaCO3’). Each simulation was × × run for a total of 200 kyr. To improve the computational efficiency of simulations, I periodically (every 10 years) decoupled the marine biochemistry module for 90 years (as in the spin-up for chapter3, see Lord et al., 2016). Higher Aptian land-surface temperatures (see model evaluation and discussion in section 2.2.2.1) result in a more efficient weathering of continental crust. In fact, if pre-industrial weathering fluxes are extrapolated into Aptian conditions assuming temperature sensitivity tuned to the pre-industrial climate (Colbourn et al., 2013), the higher land-surface temperatures of the Aptian configuration result

in substantially increased continental weathering and thus CO2 draw-down. In this scenario, twice the

amount of pre-industrial CO2 outgassing, consistent with reconstructed Early Aptian seafloor spreading

rates, is already required to stabilize pre-industrial atmospheric CO2 concentrations in the Aptian

set-up, let alone raise them to Aptian levels. However, atmospheric CO2 concentration reconstructions

139 CHAPTER 7. SIMULATING PROXY-CONSISTENT CRETACEOUS SEAWATER COMPOSITION for the Early Aptian indicate a larger atmospheric C reservoir than at pre-inudstrial, requiring higher

CO2 outgassing. With the high continental weathering rates, an approximate 8-fold increase of the pre-industrial CO2 outgassing would be required to stabilize the model at 850 ppm, but this is inconsistent with reconstructions of tectonic forcings (e.g. Jones and Jenkyns, 2001). Instead, I was able to stabilize the model with Early Aptian-like CO2 concentrations within the reconstructed range of CO2 outgassing fluxes by assuming either that less rock was exposed to weathering in the Early Aptian than today, or a weaker sensitivity of Early Aptian weathering rates to climate. With the assumption of 28% and 54% of modern-day weathered rock exposure in the Early Aptian, I was able to stabilize proxy-consistent atmospheric CO2 concentrations of 850 ppm with 1 and 2 pre-industrial CO2 outgassing fluxes, × × respectively. It is important to mention that CO2 outgassing rates only constrain silicate weathering rates.

Carbonate weathering does not control atmospheric CO2 on long timescales, but instead depends entirely on climate and rock exposure. Given different climate and rock exposure during the Early Aptian, the ratio of silicate to carbonate weathering could have been different than today. I tested the implications of the unknown silicate to carbonate weathering rates for Early Aptian metal with the simulations with doubled carbonate:silicate weathering ratios.

7.4.1.2 Early Aptian metal cycle set-ups

In the final and third spin-up stage, I added concentration and isotope tracers for Ca, Sr, Os and Li which I initialized with reconstructed values of Early Aptian seawater and, in the absence of values of the Early Aptian, present-day concentrations. In order to test uncertainties in Aptian metal fluxes, I also simulated two different metal cycle set-ups, starting from each C-cycle spin-up (see figure 7.3). The first set-up is identical to the set-up of metal cycles presented in chapter4, except for varied isotopic composition of weathering inputs. Changing the isotopic composition of terrestrial run-off was previously used to achieve proxy-consistent seawater of past times (e.g. Von Strandmann et al., 2013; Lechler et al., 2015). Thus, results of this first set-up can be compared more easily to these previous studies. The second set-up is a combination of increased input of mantle- relative to continent-derived metals and changes of the run-off composition. In this case, I assumed a doubling of seafloor production (Eldholm and Coffin, 2000) and thus C emissions and metal leaching from high-temperature hydrothermal systems. High C and Ca concentrations in Mesozoic ocean crust (up to 5 times higher than in currently altered crust, Gillis and Coogan, 2011) imply increased C burial and metal leaching from off-axis, low-temperature basalt alteration in the Early Cretaceous. The isotopic signature of metals released from off-axis systems would have been more similar to those released from on-axis systems in the Early Aptian because of a smaller offset between seawater and MORB (Kristall et al., 2017). Given the difference in C concentrations, increased carbonate precipitation in off-axis ocean crust alteration could have constituted a significant C sink, which could have compensated, potentially even over-compensated, the increased C degassing from increased seafloor spreading rates. However, seafloor weathering did not entirely replace continental crust weathering as the dominant alkalinity source because otherwise

140 7.4. SIMULATIONS OF THE EARLY APTIAN EARTH SYSTEM the Early Aptian seawater 87Sr/86Sr could not have been more radiogenic than ocean floor basalt as indicated by proxy data. Sizable radiogenic Sr input is required to explain the reconstructed offset by 0.005. This radiogenic Sr could not have come from weathered sediments, given that seawater 87Sr/86Sr reached a local maximum in the Early Aptian with higher values than recorded since the late Triassic (McArthur et al., 2012). Instead, the reconstructed 87Sr/86Sr of seawater indicates that ancient igneous rock must have been weathered to some extent in the Early Aptian. In order to allow for a 87Sr/86Sr offset between seawater and ocean crust and to keep the C cycle balanced, I assumed that high-temperature hydrothermal fluxes and low-temperature alteration changed proportionately, both twice the size of the pre-industrial values, while maintaining the silicate weathering rates tuned to stabilize CO2 outgassing in spin-up stage 2. All simulations were initialized with the Aptian seawater composition suggested by proxy data (table 7.1) and run repeatedly for 1 Myr, iteratively changing the isotopic composition of run-off until the metal isotope cycles were balanced: If the seawater composition drifted away from proxy-consistent values during the simulation, I would re-run the simulation with adapted isotopic composition of weathering fluxes and repeated this procedure until the drift disappeared. In order to avoid geologically unreasonable isotopic run-off compositions, I only tested compositions within lithological end-members (see table 7.4). Similar to the simulations in stage 2, all simulations in stage 3 were run with temporally decoupled marine biochemistry for computational efficiency.

Table 7.4: Range of isotopic run-off values which I considered geologically reasonable during the tuning of Early Aptian metal cycles.

Isotope system Considered run-off composition Reference

187Os/188Os 0.15 (fresh basalt) Dubin and Peucker-Ehrenbrink(2015) – 2.2 (pure organic-rich sediment) Lu et al.(2017) 0.702 (fresh basalt) 87Sr/86Sr Capo et al.(1998) – 0.716 (continental crust) 0.13 – 0.57% δ88Sr Pearce et al.(2015) (river measurements) 2%(fully congruent) δ7Li Misra and Froelich(2012) – 23%(present river average) 0 – 2 % δ44Ca Fantle and Tipper(2014) (presently weathered rocks)

7.4.2 Results

141 CHAPTER 7. SIMULATING PROXY-CONSISTENT CRETACEOUS SEAWATER COMPOSITION

Figure 7.4: Time-series of target isotope values in the final version of the simulation with 2xpre-industrial CO2 degassing, 2xpre-industrial CaCO3:CaSiO3 and 1xpre-industrial hydrothermal emissions (2xCO2PI , CaCO3, 1xHYDPI in figure 7.3). This is an example of the residual isotopic drift after iteratively tuning the composition of continental run-off for all simulations. Shaded areas indicate the uncertainty interval, which is includes measurement uncertainties and differences between Early Aptian isotopic values from different locations (see table 7.1 for references).

Through iterative tuning of the isotopic composition of continental runoff, I obtained parameter sets which maintain seawater composition within reconstruction uncertainty (measurement uncertainty and inter-site variability) of the Early Aptian. As an exemplar, figure 7.4 shows the stability of the simulated isotopic composition of dissolved metals in one simulation. Table 7.5 shows the consistency of the simulated seawater composition with proxy data in all model configurations. The iterative tuning process reproduced the reconstructed isotopic composition of Early Aptian seawater in all simulations. Consistent with the previous perturbation experiments, no configuration could produce the reconstructed substantially larger marine Sr and Ca reservoirs. On the contrary, the simulated sizes of these reservoirs are more similar to pre-industrial times than the Early Aptian.

142 7.4. SIMULATIONS OF THE EARLY APTIAN EARTH SYSTEM

Table 7.5: Proxy-consistency of my early Aptian simulations. Gray ’=’ signs indicate that the simulation result is within uncertainty of the reconstructed Aptian value. Analytical uncertainty of the proxy and uncertainty in the Aptian value are considered. Blue colouring indicates if the simulated value is smaller than the reconstructed Aptian value. The shading of the colours blue and red indicate how far off the simulated value is: the darker the colour, the bigger the offset.

187 188 87 86 88 7 44 Os/ Os Sr/ Sr δ Sr (%) δ Li (%) δ Ca (%) CO2 (ppm) Sr (µmol/kg) Ca (mmol/kg) Aptian proxy data 0.6 0.11 0.70755 0.0002 0.4 0.11 24 1.1 2.2 0.11 840 260 ppm 278.4 102.8 30.8 11.25 ± ± ± ± ± ± ± ± 1xCO2PI +2HYD = = = = -0.05 = = = 1xCO2PI +CaCO3+2HYD = = = = -0.06 = = = 2xCO2PI +2HYD ======2xCO2PI +CaCO3+2HYD ======1xCO2PI = = = = -0.04 = = = 1xCO2PI +CaCO3 = = = = -0.06 = = = 2xCO2PI ======2xCO2PI +CaCO3 ======

Figure 7.5: Sizes of marine metal reservoirs in simulations of the Early Aptian and marine pH in different C cycle configurations. Dotted horizontal lines indicate pre-industrial values.

Table 7.5 shows that reconstructed Early Aptian seawater composition could be achieved in almost all tested model configurations despite differences in total weathering, carbonate burial and hydrothermal fluxes because the isotopic composition of continental run-off was tuned accordingly in each configuration. The only exception is δ44Ca, reconstructed Early Aptian values of which were only reproduced in configurations with doubled CO2 outgassing and thus CaCO3 burial. Similarly to the isotopic composition of seawater, the concentrations of dissolved Sr and Ca are similar in all simulations because the model was initialized with Mg, Ca and Sr concentrations and burial fluxes to achieve a tripling of the marine Sr and Ca reservoirs in all configurations. Contrary to Sr and Ca, sizes of the marine Os and Li reservoirs are not similar, or even pushed in the same direction, in all configurations. Most simulations result in

143 CHAPTER 7. SIMULATING PROXY-CONSISTENT CRETACEOUS SEAWATER COMPOSITION increased Os and Li reservoirs. In particular, increased weathering fluxes and hydrothermal inputs lead to a doubling of Os concentrations. However, some simulations also decreased the Os and Li reservoirs. It is important to note that, despite equal atmospheric CO2 concentrations, surface ocean pH varies across the 2 configurations as a result of changing alkalinity and Ca + fluxes. Higher continental weathering fluxes reduce the effect of higher Early Aptian atmospheric CO2 concentrations on pH, while it is increased by 2 higher net hydrothermal Ca + input.

Figure 7.6: Isotopic composition of continental run-off in the different Early Aptian configurations as a result of the tuning process. Dotted horizontal lines indicate pre-industrial values.

Figure 7.6 shows the resulting run-off composition for each configuration. Early Aptian run-off generally has to be isotopically lighter to achieve proxy-consistent seawater composition, apart from δ44Ca values which need to be larger then at present in all configurations except those with the highest

CaCO3 burial rates. The extent to which the isotopic value of run-off has to be changed from pre-industrial conditions to achieve proxy-consistent seawater varies largely with the configuration of the C cycle and hydrothermal emissions: For radiogenic Sr and Os isotopes, simulations with high hydrothermal inputs require smaller changes in run-off isotopic composition, while largest changes are required for simulations of higher-than-pre-industrial weathering rates, particularly of silicates in the case of Sr. Stable isotope ratios in seawater are strongly influenced by isotopic fractionation during burial, which varies across the simulation set-ups. Increased low-temperature hydrothermal alteration enhances the amount of Li burial, and thus fractionation, which reduces the requirement for isotopically light run-off. Increased continental weathering enhances delivery of isotopically heavy Sr, which thus requires even lower δ88Sr of weathered rock. Hydrothermal Sr input, on the other hand, is isotopically light and compensates for the isotopically heavy continental input. Simulating the reconstructed 44Ca-enrichment of Early Aptian

144 7.4. SIMULATIONS OF THE EARLY APTIAN EARTH SYSTEM seawater requires increased Ca isotope fractionation in the ocean or isotopically heavier continental run-off. In configurations with pre-industrial CO2 outgassing rates, it was not possible to achieve the reconstructed Early Aptian seawater δ44Ca with run-off δ44Ca within the range of present-day weathered rocks (see table 7.4).

7.4.3 Discussion

The simulation results of the Early Aptian configurations presented above show that a seawater composition consistent with reconstructions for the Early Aptian can be simulated with cGENIE, but also that existing uncertainties about the size and isotopic composition of metal sources and the C cycle in the Early Aptian still permit multiple proxy-consistent configurations. This introduces an ambiguity to the configuration choice when interpreting the metal isotopic record of OAE 1a. Here, I discuss solutions for the Early Aptian Earth system in the context of this ambiguity and assess resulting uncertainties for reconstructing metal cycles. Previously published simulations of Early Aptian metal cycles commonly altered the hydrothermal activity and the isotopic composition of run-off to achieve proxy-consistent marine reservoirs for that time period (e.g. Jones and Jenkyns, 2001; Tejada et al., 2009; Blättler et al., 2011; Bauer et al., 2017a). The isotopic composition of run-off is variable over time but cannot be directly reconstructed for past time periods. Thus, tuning the isotopic composition of run-off is an easy way to simulate various seawater compositions. However, since the isotopic composition of run-off affects the isotopic effect of weathering flux changes on seawater, its assumed value has implications for the identification and quantification of weathering flux changes based on metal isotope excursions. Figure 7.6 shows that one boundary condition that influences the degree of required run-off tuning is the strength of hydrothermal activity. This is to be expected because the isotopic composition of hydrothermal fluids is very different compared to continental run-off. Variations in the proportion of these two marine inputs can shift the isotopic composition of seawater without changes in the composition of run-off. Thus, run-off composition changes would only need to account for the remaining offset between simulated and reconstructed seawater. Figure 7.6 also shows that the configuration of the terrestrial C cycle, in particular the rates of silicate and carbonate weathering, are equally influential. Increased weathering

fluxes in simulations of higher-than-pre-industrial CO2 outgassing rates enhance the supply of metals with continental isotopic composition and drive the isotopic composition of seawater towards more continental values (see simulation results of higher CO2 outgassing in table 7.3 and figure 7.1). For Sr, variations in the proportion of carbonate to silicate weathering also changes the isotopic composition of run-off, because of the different isotopic compositions of sedimentary and igneous rock. The δ44Ca of seawater is largely influenced by the amount of CaCO3 burial, since the latter involves fractionation of Ca isotopes. Tuning the isotopic composition of continental run-off for different combinations of these boundary conditions for the Early Aptian resulted in plausible values for all isotope systems except δ44Ca. The failed attempt to stabilize cGENIE at the reconstructed Early Aptian seawater δ44Ca with observed

145 CHAPTER 7. SIMULATING PROXY-CONSISTENT CRETACEOUS SEAWATER COMPOSITION

run-off compositions under pre-industrial CaCO3 burial and CO2 outgassing rates suggests that those rates must have been higher, or that Ca isotope fracitonation during marine carbonate burial was increased. The four simulations which produced a proxy-consistent seawater composition are the first self-consistent configurations of Early Aptian C and metal cycles. Yet, the range of remaining uncertainty because of missing constraints is considerable, and the true range of uncertainty of the Early Aptian run-off composition is likely larger than suggested by figure 7.6. More numerical combinations of the tested boundary conditions are imaginable and other boundary conditions could have been different, affecting the isotopic composition of seawater (see table 7.3 and fig. 7.1). I also did not explore the uncertainty in the reconstructed seawater composition itself. However, the only other study which quantified uncertainties in Early Aptian run-off composition reports a similar 87Sr/88Sr range (Kristall et al., 2017, 0.708 – 0.709). This uncertainty range indicates the maximum accuracy with which shifts in the isotopic composition of seawater under environmental change can be predicted, which directly translates into the error margin on quantitative interpretations of metal isotope excursions. Reconstructions of metal fluxes during metal cycle disruptions are only meaningful in the context of this error margin. In essence, it is unlikely that metal flux perturbations can be better constrained than the baseline state of the metal cycle. Reconstructing boundary conditions for pre-excursion metal cycles from independent constraints can reduce this margin, but the latter is likely to remain comparatively large for periods as old as the Early Aptian. Besides the isotopic composition of seawater, the C and metal cycle configurations also affect the sizes of marine metal reservoirs (see figure 7.5). The tested Early Aptian configurations predominantly led to increased marine metal reservoirs. In particular, in the configuration with maximal weathering and hydrothermal inputs (’2xCO2PI +CaCO3, 2xHYDPI ’), the marine Os reservoir is roughly twice as large as in the pre-industrial spin-up. The size of a reservoir prior to its perturbation determines how much input or output fluxes need to be disrupted to cause a noticeable shift, and how quickly this shift evolves. Uncertainty over past metal reservoir sizes thus adds to the error margin on quantitative interpretations of metal isotope excursions, and constraining pre-excursion reservoir sizes can improve the accuracy of such interpretations. Size changes in marine metal reservoirs, in particular of Ca, also affect the charge balance of seawater, which is an important control on pH changes on geological time scales, alongside atmospheric CO2 (see Halevy and Bachan, 2017, for a review). As a result, the tested

Early Aptian configurations produced different surface ocean pH values despite equal atmospheric CO2 concentrations (fig. 7.5). The sizes of all simulated marine metal reservoirs are affected by the differences between pre- industrial and Early Aptian model set-ups but reconstructions for the Early Aptian only exist for Sr and Ca (see table 7.1. The simulated variations of dissolved Ca and Sr under a wide range of boundary condition changes is substantially smaller than that suggested by geological record. In order to achieve the large Early Aptian marine Sr and Ca reservoirs indicated by proxy data, I had to initialize the model with bigger reservoirs and reduce the abundance of dissolved Mg. In the case of Sr, this hints at Sr cycle changes that are currently not dynamically simulated by cGENIE. One such change could be the dominant burial of

146 7.5. CONCLUSIONS calcite in the Early Aptian, while aragonite is predominantly buried at present (Sandberg, 1983). Sr is predominantly incorporated into aragonite (e.g. Terakado and Masuda, 1988), meaning that less aragonite burial in the Early Cretaceous could have reduced the marine Sr sink and led to an accumulation of dissolved Sr. At the same time, increased Sr burial by calcite producers like coccolithophores could have stripped the ocean of proportionately more isotopically light Sr (Stevenson et al., 2014). Sr burial and isotopic fractionation in cGENIE do not distinguish between CaCO3 mineralogies. Instead, I prescribed different sink strength and fractionation coefficient to mimic the effects of reduced aragonite burial on the marine Sr reservoir and to reproduce the reconstructed Early Aptian marine Sr reservoir. Similarly, the mismatch between the simulated and reconstructed marine Ca reservoirs is likely the result of processes unaccounted for in my simulation set-up. Ca is removed from the ocean alongside alkalinity during carbonate burial. The alkalinity cycle is both influenced by and regulates atmospheric CO2 concentrations and climate. Through this link with the C cycle, unlike Sr, Os and Li, changes in the burial rate of Ca cause a negative feedback on its dominant source, continental weathering. The simulations of long-term boundary condition changes showed that, if all Ca and alkalinity fluxes are coupled, this negative feedback stabilizes the marine Ca reservoir and prevents large deviations in reservoir size. Decoupled fluxes of alkalinity or Ca are required to simulate noticeable reservoir size changes. Another factor affecting the variability of Ca concentrations is the charge balance of seawater. Sr, Os and Li are trace metals in seawater and changes in their concentrations have negligible effects on the total amount 2 of cations in the ocean. Ca +, in contrast, is one of the principle positive charges in seawater (Pilson, 2012) and sustained changes in its concentration require compensatory changes in the concentrations of other ions. The substantially larger-than-present-day Early Aptian marine Ca reservoir size was most 2 likely sustainable because of reduced Mg + concentrations (see the review of Turchyn and DePaolo, 2019). The replacement of Mg by Ca as the second most abundant dissolved metal in Early Cretaceous seawater cannot yet be achieved dynamically with cGENIE because the model does not currently have a dynamic Mg cycle. Instead, the model had to be initialized with the desired Mg/Ca ratio.

7.5 Conclusions

In this chapter, I explored how to simulate an evidence-based, proxy-consistent Early Aptian background state in cGENIE. To this end, I started by reviewing the steady state marine isotopic composition produced by changes in boundary conditions and identified CO2 degassing, the ratio of continental carbonate to silicate weathering, hydrothermal activity and the isotopic composition of continental run-off as the governing boundary conditions for the studied metal isotope systems. Starting with a spin-up with Early Aptian physics (see Methods), I produced eight different model set-ups to simulate proxy-consistent

Early Aptian atmospheric CO2 concentrations and steady-state isotopic composition of marine metal reservoirs through different combinations of variations in these boundary conditions. The resulting spin-ups are used to investigate implications of uncertainties in reconstructed Early Aptian C and metal cycles for the quality of quantitative interpretations of metal isotope excursions during OAE 1a in the

147 CHAPTER 7. SIMULATING PROXY-CONSISTENT CRETACEOUS SEAWATER COMPOSITION subsequent chapter8. The approach to reconstruct metal and C cycles prior to OAE 1a is more extensive than previous attempts to simulate Early Aptian seawater and it enables the quantification and exploration of error margins around baseline C and metal fluxes. The applied changes to the pre-industrial C cycle affected metal fluxes and reservoirs but did not result in proxy-consistent seawater isotope values. In order to close the gap between simulations and observations, I tuned the isotopic composition of continental run-off which is largely independent of environmental conditions in cGENIE. The Early Aptian run-off composition and average composition of weathered rock are unconstrained by proxy-data and cGENIE does not contain fractionation processes in terrestrial freshwater systems and soils which are influenced by climate (e.g. Rugenstein et al., 2019). At the same time, variations in the isotopic composition of run-off have large effects on the isotopic composition of seawater (see figure 7.1). Missing observational and mechanistic constraints and large influence on the composition of seawater render tuning the isotopic composition of run-off a justifiable and efficient way of closing isotope cycles, achieving proxy-consistent seawater composition and testing whether C and metal cycle configurations are geologically plausible. The tuned run-off compositions could provide avenues to explore the terrestrial environment in the Early Aptian, though it would be challenging to disentangle the manifold of processes (e.g. weathered lithologies, biogeochemistry of freshwater systems and river deltas, vegetation and soils) that govern the run-off composition. Inversely, it would be interesting to test the tuned run-off compositions with predictions from land-surface models. Improved quantitative understanding and numerical representation of environmental controls on the composition of run-off, e.g. stable isotope abundances as a function of erosive strength or radiogenic Os and C release from oxidative organic-rich shale weathering, have the potential to substantially improve our understanding of metal cycle variations and environmental change in the past. The reconstructed sizes of the Early Aptian marine Sr and Ca reservoirs could not be achieved dynamically by my simulation set-ups but had to be prescribed, because implications of the dominantly buried CaCO3 mineralogy, sea floor alteration dynamics and Mg cycle changes for marine metal abundances and the charge balance are currently not captured by cGENIE. Currently, Mg fluxes and fluxes related to seafloor alteration are invariant and prescribed in the simulation set-up. Similar to the isotopic composition of run-off, uncertainties introduced by the missing representation of these processes could be reduced by comparison with other models or further development of cGENIE.

148 steol vdnefraboi rss ugsieo limited of suggestive crisis, biotic a for evidence only the is - 1994) (Erba, crisis nannoconid the - .Rdoei sadS stpstedtwrsmore towards trend isotopes Sr and Os Radiogenic 2017). Föllmi, and (Charbonnier decrease identified OJHMP, were the to proximity relative in deposited sediments, Pacific in isotopes (Pb) lead Aptian, Ontong-Java, on reconstructions Age volcanism. from emissions C substantial more of result the was .Dsietepeec fteevolcanic these of presence the Despite 2020). , al. et Adloff 2012; al., et Bottini 2009; al., et (Tejada soe htijcino rai ieycue h negative the caused likely C organic of injection that showed 3 chapter in inversion flux C The niomna irpinfo h ocncevent. volcanic the from disruption environmental nannoplankton calcifying of disappearance prolonged The emissions. C perturbation) of environmental reconstruction of inverse scale the the positive thus the (and during emissions especially elusive, C volcanic remain of flux and mass the indicators, enrichments negative the (Hg) with Mercury coincident values relative mantle-like strata, same the In 2011). al., et (Kuroda values OJHMP-like to within happened emplacement their that ± indicate basalts (OJHMP) plateaux Manihiki CO and atmospheric Hikurangi reconstructed the of most that but 1a, OAE of onset 1a? the OAE at of shift evolution the in volcanism of role the was What 8.1 n eeecsteen.I h early the In therein). references and 2017 , Föllmi, and (Charbonnier 1a OAE of onset the of Myr 1 eitrrtn h stp eodo A 1a. OAE of record isotope the Re-interpreting δ δ 13 13 149 xuso rcdn nacdbaksaeformation shale black enhanced preceding excursion C xuso hnwd-pedCbra complicates burial C wide-spread when excursion C 2 ocnrto change concentration

C h a p t e r 8 δ 13 C CHAPTER 8. RE-INTERPRETING THE ISOTOPE RECORD OF OAE 1A.

a) Resolution Guyot b) Cismon APTICORE

Figure 8.1: Isotopic record of OAE 1a from Resolution Guyot, North Pacific (Jenkyns et al., 1995; Blättler et al., 2011; Lechler et al., 2015) and Cismon, Italy (Tejada et al., 2009). Black vertical lines delineate the ’Selli level’, or OAE 1a interval. The dark and light gray areas mark the negative and positive δ13C excursions, respectively.

Metal isotope ratios that are sensitive to igneous forcing show negative excursions during OAE 1a (figure 8.1). Consistent across records from different locations, the negative excursions of 187Os/188Os and δ7Li peaked during the negative δ13C excursion. On the other hand δ44Ca seems to have peaked during the positive δ13C excursion, and 87Sr/86Sr at the end of it. A relatively short, transient return to more radiogenic values occurred in the 187Os/188Os record at the peak of the negative δ13C excursion, just before the unradiogenic peak. The timing of excursion onsets and ends is less certain than the isotopic trends. All trace metal systems seem to have commenced their trends towards more mantle-like values before the start of the negative δ13C excursion (Jones and Jenkyns, 2001; Tejada et al., 2009; Blättler et al., 2011; Bottini et al., 2012; Lechler et al., 2015). While this tendency has been interpreted as an early onset of increased seawater-basalt interaction for some proxy systems (e.g. Tejada et al., 2009, suggested a time lag of up to 200 kyr between the onset of the 187Os/188Os and δ13C excursions), the isotopic variations of others (e.g. 87Sr/86Sr and δ44Ca) are within the range of background variability. Apart from 87Sr/86Sr, which started to recover at the end of the positive δ13C excursion, the recovery timescale of these isotope excursions is also uncertain as records of the recovery vary between sites (δ44Ca and δ7Li) or are not available (187Os/188Os). Previously, metal isotope records across OAE 1a have been attributed to either igneous forcing (Os and Sr) or enhanced continental weathering fluxes (Li and Ca). The co-occurence of the negative excursion peaks of 187Os/188Os and δ13C was interpreted as a fingerprint of increased volcanism (Tejada et al., 2009; Bottini et al., 2012, , see also chapter3), while the co-occurence of the negative excursion

150 8.2. CONSTRAINING C AND METAL FLUXES DURING OAE 1A

peaks of δ7Li and δ13C and the radiogenic 187Os/188Os excursion was explained with enhanced silicate weathering through C release-induced climate change (Lechler et al., 2015). Tejada et al.(2009) and Bottini et al.(2012) interpreted the early start of the unradiogenic 187Os/188Os excursion as an early onset of OJ volcanism, which they used to explain C emission-induced environmental changes (enhanced continental weathering, nannoconid crisis). The amplitudes of these excursions have been used to estimate respective flux size changes. However, the discussion in chapter5 showed that a direct attribution of metal isotope excursions to either igneous forcing or weathering flux changes is not possible if an igneous C and metal source persisted for more than

100 kyr, which was likely the case during OAE 1a, given that elevated atmospheric CO2 concentrations and unradiogenic metal isotope excursions persisted for millions of years (Jones and Jenkyns, 2001; Li et al., 2008; Naafs et al., 2016b). It is then likely that the amplitudes of the recorded metal isotope excursions resulted from a combination of igneous forcing and continental weathering changes. The isotopic impact of these processes need to be disentangled before metal flux imbalances can be quantified. To my knowledge, Von Strandmann et al.(2013) and Lechler et al.(2015) are the only studies that attempted to disentangle the different isotopic effects of LIP emplacement using a combination of all four metal isotope systems. In the present chapter, I will revise their and other published interpretations of the isotopic record of OAE 1a in order to determine the scale of the associated C cycle perturbation and the role volcanism had in it. My interpretation of the isotope records will be based on a detailed review of existing constraints on igneous and continental metal and C fluxes in the Early Aptian and will apply the knowledge gained in the previous chapters that explored metal cycle perturbations and the Early Aptian background state numerically (chapters5 and7). First, I will evaluate the potential of the OJP emplacement and resulting weathering changes to cause isotopic shifts in Early Aptian seawater. I will then use the gained knowledge to discuss the recorded isotope excursions and propose an updated model of environmental change during OAE 1a.

8.2 Constraining C and metal fluxes during OAE 1a

Interpreting the observed isotopic excursions requires knowledge about the sizes and isotopic compositions of exogenic metal fluxes during OAE 1a. Previously proposed transient metal sources during OAE 1a include the emplacement of the Greater Ontong Java Plateau (e.g. Tejada et al., 2009), ocean crust formation (Jones and Jenkyns, 2001), volcanism related to the High Arctic LIP (Polteau et al., 2016) and enhanced continental crust weathering (Blättler et al., 2011; Lechler et al., 2015). The C and metal fluxes from each of these sources are uncertain. Instead, envelopes of C and metal flux sizes and isotopic compositions which could have caused the observed isotopic shifts in seawater have to be reconstructed. Because of the diverse nature of the potential C and metal sources and sinks during OAE 1a, different reconstruction methods with different degrees of accuracy have to be employed for this. In the following sections, I assess the potential of the two most prominently-discussed transient metal sources during OAE 1a to have caused isotopic shifts in Early Aptian seawater: the emplacement of the Greater OJP and

151 CHAPTER 8. RE-INTERPRETING THE ISOTOPE RECORD OF OAE 1A. climate-driven increases in continental crust weathering. For each process, I will quantify envelopes of possible total C and metal fluxes and their isotopic signatures, and discuss remaining uncertainties. There is no guarantee that OJP volcanism and weathering were the only relevant external C and metal reservoirs during OAE 1a, though, and the implications of this will be discussed during the re-evaluation of the isotopic record of OAE 1a.

8.2.1 Reconstruction of elemental fluxes during the emplacement of the Ontong-Java-Hikurangi-Manihiki Plateau

8.2.1.1 Geological context

The OJP is the largest LIP on Earth’s surface with an area of 2 106 km2, a thickness of up to 43 km and × an estimated volume of 4-8 107 km3 (depending on whether emplacement took place on- or off-axis) and × with related giant radiating dyke swarms and flood volcanism in surrounding basins (Neal et al., 1997; Mochizuki et al., 2005; Kerr and Mahoney, 2007; Svensen et al., 2019). Based on magma compositions and tectonic reconstructions, previous studies suggested that the OJP might have been emplaced together with the Manihiki and Hikurangi plateaus as one ’super-LIP’ (Taylor, 2006; Hochmuth et al., 2015). In this case, the magma volume could have been twice as large as estimated for OJP alone, covering a total surface area of 5 106 km2 (Taylor, 2006). The OJP consists predominantly of tholeiitic basalt. Two ∼ × emplacement pulses have been recognized through 40Ar/39Ar geochronology: One major pulse at 122 ∼ Ma and a less voluminous pulse at 90 Ma (Mahoney and Spencer, 1991; Mahoney et al., 1993). The ∼ OJP is situated in the South-West Pacific, at the boundary between the Australian and Pacific plates. In the early Cretaceous, this location was at or in vicinity of the intersection between the Pacific, Farallon and Phoenix plates. The OJP was thus emplaced into or onto basaltic oceanic crust of Jurassic age, isotopically and chemically identical to MORB (Mahoney et al., 1998; Ishikawa et al., 2005; Ganino and Arndt, 2009; Ishikawa et al., 2011; Hochmuth et al., 2015). Apart from localized evidence for subaerial volcanism, the emplacement happened predominantly below water, at a reconstructed depth between 1-3 km (Roberge et al., 2004; Thordarson, 2004). The submarine emplacement of this large LIP has sparked debate whether a mantle plume or impact volcanism are at its origin (Ingle and Coffin, 2004; Tejada et al., 2004; Jones et al., 2005). While the subaerial emplacement goes counter to model-derived estimates of thermal and dynamic uplift during the eruption of a deeply-rooted mantle plume, the isotopic composition of OJP basalts resembles that of the lower mantle and as of now no impact-related global elemental spikes have been identified (e.g. Roberge et al., 2004).

8.2.1.2 Composition of pre-eruptive OJP magma

Drilling into the OJP revealed that the chemical composition of OJP basalts emplaced during the early Aptian are fairly homogeneous (Fitton and Godard, 2004). Elemental analysis revealed that the dominant compositional Kwaimbaita-type basalt likely derived from the parental Kroenke type (Fitton and Godard, 2004). Glass samples of the latter contain metals at concentrations listed in table 8.1. These can be

152 8.2. CONSTRAINING C AND METAL FLUXES DURING OAE 1A

regarded as reasonably unaltered (Fitton and Godard, 2004), which is also suggested by the relatively low Li concentration. The concentrations of Li and CaO in Kroenke-type basalt glasses are similar to modern day MORB glasses, while Kroenke-type basalt is somewhat depleted in Sr ( 0.65 MORB). ∼ × Since mantle melting exhausted sulphides during Kroenke-type magma formation (Reekie et al., 2019), much higher Os concentrations in Kroenke-type basalt than in MORB would be expected as a result of a substantially lower melt fraction. However, fractionation because of crystallization during or after eruption could have efficiently removed a substantial amount of the Os present in the melt. Additionally, sulfide saturation of Kwaimbaita-type basalts, which make up the majority of the OJP, suggests that low-pressure differentiation of Kroenke-type magma prior or during eruption could have reduced the concentration of siderophile elements in erupting OJ magma (Reekie et al., 2019). In fact, measured Os concentrations in Kroenke- and Kwaimbaita-type basalts are substantially lower (118-174 ppt and 11-51 ppt, respectively Tejada et al., 2013) than values of > 10,000 ppt which would be expected for the mobilization of the entire mantle Os fraction during 30% melting. Thus, the amount of emitted Os > per unit of Kroenke-type basalt volume is more uncertain, but likely higher than during hydrothermal alteration of MORB given 1-1000 larger Os concentrations in OJP basalt than in MORB glasses × (Gannoun et al., 2007).

Table 8.1: Elemental composition of sample 1187-8 (hole 1187A, core section 10R-1, interval 114-118cm) of fresh glass in Kroenke-type basalt and MORB glasses as reported by Ryan and Langmuir(1987); Chan et al.(1992); Verma(1992); Kushiro(1998); Fitton and Godard(2004).

Sr (ppm) Li (ppm) Ba (ppm) CaO (wt%) Kroenke-type basalt 81.6 4.0 13.46 12.39 MORB glasses 126 3 – 6 5 – 100 11.5 – 13.5 >

While it can be assumed that the composition of most incompatible metals does not vary substantially

between pre-eruptive magma and fresh glass, this assumption is not applicable to volatiles like CO2, the evasion of which can happen on faster time scales than quenching upon magma ascent (Lowenstern,

2001). However, initial CO2 contents can still be extrapolated from the concentration of non-volatile

elements with similar partition coefficients in basaltic magma (e.g. Barium (Ba) for CO2, Hirschmann,

2018; Le Voyer et al., 2019). Le Voyer et al.(2019) assumed an average CO 2/Ba value of undegassed MORB of 81.3 based on a large compilation of undegassed basalts. However, Pacific MORB is enriched

in C and has an unusually high CO2/Ba = 134 23 (Le Voyer et al., 2019). Because Kroenke-type ± basalt resembles the enriched Pacific MORB (both have Th/La > 0.07), it might have had similarly higher C contents compared with average MORB (Shimizu et al., 2016). Together with the measured

Ba concentration in Kroenke-type basalt (table 8.1), these estimates of undegassed CO2/Ba result in

pre-eruptive CO2 concentrations of 1094 ppm and 1804 310 ppm, respectively. ± 153 CHAPTER 8. RE-INTERPRETING THE ISOTOPE RECORD OF OAE 1A.

8.2.1.3 Elemental fluxes during OJ eruption

Since the OJP erupted into oceanic crust basalt, carbon emissions from sediment intrusions or contact metamorphism can be neglected (Ganino and Arndt, 2009). The dominant carbon source should have been direct mantle emissions during the emplacement. Carbon emissions during OJ volcanism can be estimated by calculating the difference between pre-eruptive and post-eruptive CO2 concentrations in basalt. Roberge et al.(2004) measured a remaining CO 2 fraction of 30 – 137 ppm in OJP glasses.

Considering the full range of uncertainty in pre-eruptive CO2 concentrations, this implies that 957 –

2074 ppm CO2, 87 – 98%, degassed during eruption. This is similar or somewhat smaller than the average CO2 loss of degassing MORB (1470 – 2100 ppm, Le Voyer et al., 2019). MORB degassing 0.77 12 3 results in an annual CO2 emission of 1.32+ 10 mol/yr for 16.5 km /yr of erupted magma, which 0.85× − 12 is substantially less than the reconstructed CO2 fluxes from the sub-aerial Laki eruption (6.91 10 mol × for 14.7 km3 of magma erupted over 5-8 months Hartley et al., 2014). Assuming that the entire OJP was emplaced in a single emission pulse, this flux is equivalent to total CO2 emissions as given in table 8.2. Evidence for biological modification of basaltic OJP glass means that the latter might have lighter δ13C values now than the CO2 that degassed during OJP emplacement (Banerjee and Muehlenbachs, 2003). Since biological alteration cannot be excluded for any OJP glasses, the δ13C during eruption was likely similar to or heavier than δ13C = -9.5%, the heaviest measured sample. During the active emplacement phase, metals were most likely emitted from increased high- temperature hydrothermal venting of the newly emplaced basalts. Sr and Os release from the intruded MORB-like Jurassic crust is assumed to be negligible because emplaced OJP basalt was up to 10 times more voluminous than ocean crust (Svensen et al., 2019). Though measurements suggest it could have had a (small) isotopic effect (Tejada et al., 2013). By contrast, crust alteration leads to substantial enrichments in Li (Chan et al., 1992), which means that heating and intrusion of old, altered oceanic crust could have caused significant Li release. Hence, assuming no contribution of crust-derived metals yields an upper limit for the C:metal ratios during OJP emplacement, particularly for Li. Assuming that the relative loss of metals during high-temperature hydrothermal activity in OJP basalts was the same as in MORB today, and using estimates of modern metal inputs from high-temperature hydrothermal systems (Schultz and Elderfield, 1997; Hathorne and James, 2006; Krabbenhöft et al., 2010; Georg et al., 2013; Antonelli, 2018), I estimated C and metal fluxes for the OJP emplacement in table 8.2. I assumed that the isotopic composition of emitted metals resembles the composition of surveyed OJP basalt. The only exception is Li, which could have been slightly isotopically fractionated during high-temperature hydrothermal activity (Sano and Nishio, 2015). Table 8.3 shows the reconstructed isotopic compositions of all elemental fluxes.

154 8.2. CONSTRAINING C AND METAL FLUXES DURING OAE 1A

Table 8.2: Estimated total emissions during OJP emplacement. Upper-limit estimates for Os fluxes result from the assumption that Os concentrations in erupting OJ magma were 1000 those in MORB × melt, based on measurements (see section 8.2.1.2). Given missing controls on the extent of pre-eruptive differentiation and Os fractionation into crystals, these values could have been much higher.

17 14 5 14 17 CO2 (10 mol) Sr (10 mol) Os (10 mol) Li (10 mol) Ca (10 mol) OJP only 11.3 – 102.4 40.4 – 82.5 5040 – 10.29 106 144 – 294 12.0 – 24.5 × ’super-LIP’ 23.0 – 204.8 82.5 – 165 10290 – 20.58 106 294 – 588 24.5 – 49.0 ×

Table 8.3: Isotopic composition of fluxes during OJP emplacement. Measured isotopic compositions are taken from Banerjee and Muehlenbachs(2003); Tejada et al.(2004, 2013); Sano and Nishio(2015).

δ13C (%) 87Sr/86Sr 187Os/188Os δ7Li (%) δ44Ca (%) -9.5 0.70363 0.129 0.025 4 – 6 unknown ≥ ±

8.2.1.4 Elemental fluxes during the weathering of OJP basalts

Once emissions stopped and the newly emplaced basalt cooled, it was altered at low temperatures in a similar way to off-axis MORB today (Banerjee et al., 2004). At present, low-temperature basalt alteration creates a sink for dissolved C and Li and a source for Sr, Os and Ca. Assuming that only oceanic crust with an age 3 Myr undergoes such alteration (Brady and Gíslason, 1997) and that oceanic crust ≤ production rates were constant at 3.45 km2/yr (Parsons, 1982) over the last 3 Myr, 10.35 106 km2 of ∼ × oceanic crust are presently altered. Based on the the ratio of elemental concentrations in OJP basalt and MORB (see table 8.1), estimates of annual elemental fluxes of present-day crust alteration (Schultz and Elderfield, 1997; Hathorne and James, 2006; Krabbenhöft et al., 2010; Georg et al., 2013; Antonelli, 2018) and initial OJP surface areas of 2 106 km2 (’OJ alone’) and 5 106 km2 (’super-LIP’) I estimated × × the annual elemental fluxes due to OJP weathering given in table 8.4.

Table 8.4: Estimated annual elemental emissions (+) and sequestration (-) during OJP weathering.

12 9 9 12 CO2 (10 mol/yr) Sr (10 mol/yr) Os (mol/yr) Li (10 mol/yr) Ca (10 mol/yr) ’OJ only’ -0.29 0.06 60 – 59,900 -1.8 0.29 ’super-LIP’ -0.72 0.16 150 – 150,000 -4.6 0.72

Assuming the young OJP was weathered for 3 Myr in this way, a total of 10 – 20 1017 mol C could × have been sequestered, which is at the lower end of my estimates of C emitted during emplacement.

8.2.1.5 Timeline of OJP emplacement

40Ar-39Ar-dating of different basalt layers of the OJP revealed no statistically significant age difference, meaning that the majority of the OJP was likely emplaced on timescales faster than the analytical uncertainty of the applied 40Ar-39Ar analysis ( 3 Myr, Tejada et al., 2002). This results in minimum ± 155 CHAPTER 8. RE-INTERPRETING THE ISOTOPE RECORD OF OAE 1A. magma emission rates of 1 – 20 km3/yr, depending on assumptions of the initial size of the OJP. Eruption rates of 200 km3/yr have been observed in recent flood basalt eruptions of much smaller size (Laki ∼ eruption 1783-1784, Inoue et al., 2008). Eruptions of high and low effusivity have been reconstructed for the OJP (Inoue et al., 2008) but the Laki eruption rates imply that the OJP could have been emplaced within 30 – 600 kyr, again dependent on the assumed initial OJP volume. However, it is more likely that the OJP was not emplaced by a single, long-lasting eruption, but rather by a series of high-volume eruptions, each lasting a few decades to centuries (Self et al., 2015). Taken together, the cumulative active phase of emplacement might not have been longer than 100 kyr (Self et al., 2015). ∼

8.2.2 Estimating the isotopic forcing of continental weathering flux changes during OAE 1a

Continental crust weathering constitutes the biggest source of dissolved Sr, Os, Li and Ca for the present-day ocean. The distinct isotopic composition of continental run-off (isotopically heavier than fresh mantle sources) pushes the isotopic composition of seawater towards continental values. At present, seawater is isotopically more heavy than in the Early Aptian with respect to Sr, Os and Li, and lighter with respect to Ca (see table 7.1). Assuming a present-day composition of weathered rock, the increased offset in 187Os/188Os, 87Sr/86Sr and 44/40Ca between seawater and continental run-off would mean that climate-driven weathering increases had a lager potential to affect the isotopic composition of seawater. Early Aptian seawater 7Li (24%), on the contrary, was close to present-day run-off (23%), which would have diminished the potential of increased weathering to shift 7Li in seawater. However, my discussion in chapter7 showed that the different isotopic composition of seawater is an indication for a different set-up of C and metal cycles in the Early Aptian, likely involving weathering conditions that were different than today. Continental crust weathering is the only source of radiogenic Os and Sr isotopes and the substantially more unradiogenic Early Aptian seawater implies that this source was weaker, either in absolute terms or relative to sources of unradiogenic Os and Sr. Reduced weathering fluxes or weathering of less radiogenic material could have caused a weaker source of radiogenic isotopes. Increased hydrothermal sources of unradiogenic isotopes could have reduced the relative importance of the continental Os and Sr supply. While there are still too few constraints to identify a single most-likely constellation, I concluded in chapter7 that the reconstructed higher Early Cretaceous seafloor spreading rates did not create a sufficiently strong source to shift 187Os/188Os and 87Sr/86Sr under present-day radiogenic input from continental weathering. Thus, the supply of radiogenic isotopes from the continents was most likely smaller in the Early Aptian than today, either because of less continental crust weathering overall or because less radiogenic source rocks. In either case, this suggests a decreased potential for climate-driven increases in radiogenic metal supply from the continent. In particular, the range of tuned run-off compositions in chapter7 is close to Early Aptian seawater which implies that large changes in continental weathering fluxes would have been required to shift 187Os/188Os and 87Sr/86Sr of seawater. Stable metal isotope ratios are higher in present-day seawater than in continental run-off because isotopic fractionation during metal sequestration governs the isotope abundance in seawater.

156 8.2. CONSTRAINING C AND METAL FLUXES DURING OAE 1A

While the simulations in chapter5 showed that continental run-off changes can cause transient and long-term stable isotope shifts, the possibility that differences between present-day and early Aptian stable isotope ratios in seawater could have resulted from changes in metal sources or sinks complicates the reconstruction of weathering-related inputs of stable metal isotopes. Yet, this reconstruction is crucial for the application of stable isotope ratios as weathering proxies. Depending on the strength of marine metal sinks and isotopic fractionations in the Early Aptian, the reconstructed seawater composition is consistent with isotopically light or heavy continental run-off which have different implications for which weathering regime changes could have driven the observed stable isotopic excursions. Sufficiently large offsets between the isotopic compositions of seawater and continental run-off are required for isotopic excursions caused by climate-driven weathering flux size changes. This means that continental run-off must have been isotopically light if the negative stable isotope excursions observed during OAE 1a were caused by transiently increased weathering fluxes. At the same time, climate-driven changes in erosion rates and secondary mineral formation in terrestrial freshwater systems would have had the largest effect on the isotopic composition of seawater if the baseline continental run-off was isotopically heavy.

8.2.2.1 Simulating the metal isotopic response to increased weathering during the OAE 1a onset

The climate-sensitive metal cycles in cGENIE enable the simulation of the metal isotopic response to climate change within the limits of existing knowledge about Early Aptian boundary conditions and climate-sensitivity of continental weathering. In an attempt to estimate the maximum impact of weathering changes during OAE 1a on the isotopic composition of seawater, I used the C flux inversion method described in chapter3 to reproduce the maximum atmospheric CO 2 concentration changes reconstructed by Naafs et al.(2016a) in cGENIE, assuming present-day climate sensitivity of weathering

fluxes. I used four Early Aptian spin-ups (’2xCO2PI ’) that were developed in chapter7 as starting points for the simulations. These four configurations include increased volcanic CO2 outgassing and yield isotopic seawater compositions consistent with preserved sediments, including δ44Ca.

157 CHAPTER 8. RE-INTERPRETING THE ISOTOPE RECORD OF OAE 1A.

a) Timeseries b) Timeseries (assuming 1 Myr duration) (assuming 3 Myr duration)

c) Excursion amplitudes

Figure 8.2: Isotopic response to the highest atmospheric CO2 concentrations reconstructed by (Naafs et al., 2016a) across the C isotope excursions associated with OAE 1a. Shown are timeseries of isotopic changes in seawater assuming that the δ13C record analyzed by Naafs et al.(2016a) represents a period of a) 1 Myr and b) 3 Myr. c) compares the simulated and measured metal isotope excursion amplitudes.

Figure 8.2 shows that the enhanced continental weathering resulting from the maximum atmospheric

CO2 concentration increase as reconstructed by Naafs et al.(2016a) affects all metal isotope systems, though the magnitude of its isotopic effect varies from metal to metal and between model configurations. The simulated isotopic effects from increased weathering, relative to the observed excursion sizes, are largest for δ44Ca and smallest for δ7Li. 187Os/188Os and 87Sr/86Sr are only moderately affected because of the small isotopic offset between continental run-off and seawater in the configurations of continental metal input developed in the previous chapter (chapter7). Without substantially larger hydrothermal Os inputs than suggested by reconstructed seafloor production rates, achieving proxy-consistent 187Os/188Os of seawater requires run-off to be isotopically almost indistinguishable from Early Aptian seawater, particularly in scenarios with high weathering input. As a result, climate-driven increases in weathering-

158 8.2. CONSTRAINING C AND METAL FLUXES DURING OAE 1A derived Os supply have only minor effects on the isotopic composition of seawater and the simulated seawater 187Os/188Os stagnates at a relatively small excursion amplitude early into the weathering event. The tuned pre-event offset between 87Sr/86Sr of continental run-off and seawater is larger. The simulated weathering flux increase therefore has a bigger effect on the isotopic composition of seawater 87Sr/86Sr.

The configuration with the most radiogenic run-off (1 CaCO3:CaSiO3PI with ’1xHYDPI ’) presents × the largest change in weathering-induced radiogenic 87Sr/86Sr. The simulations in chapter5 showed that, in the present-day set-up, the change in weathering flux size has little influence on seawater δ7Li, which is instead more affected by igneous Li input and changed weathering congruency. Since the δ7Li offset between continental run-off and seawater is lower in the Aptian set-ups than in the present-day configuration, the simulated weathering-flux-related δ7Li excursions should be small as well. In the present-day configuration, the changes in weathering flux result in small, negative δ44Ca excursions (see chapter5). In the Early Aptian simulations, weathering-related minor negative δ44Ca excursions are only simulated in the two configurations that have larger-than-pre-industrial isotopic offsets between continental run-off and seawater. In the other two configurations, enhanced continental weathering results in a positive δ44Ca excursion because the smaller isotopic offset between continental run-off and seawater decreases the potential of increased weathering flux to cause negative δ44Ca excursions.

Figure 8.2 also shows that, while the amplitude of the weathering-driven excursion increases with the event duration for 87Sr/86Sr and δ44Ca, the simulated 187Os/188Os, δ88Sr and δ7Li excursions are of similar size whether a duration of 1 Myr or 3 Myr is assumed. This can be explained by differences between the individual metal cycles. The different sensitivity to the event duration of 187Os/188Os and 87Sr/86Sr is explained by the size difference between the marine Os and Sr reservoirs, which render seawater 187Os/188Os much more reactive to external forcing than 87Sr/86Sr. Stable isotope abundances in seawater are affected by stable isotope supply and isotopic fractionation during metal sequestration. The longer enhanced weathering fluxes persist, the more metal accumulates in the ocean, increasing metal burial fluxes. At some point, the isotopic effect of additional metal burial matches that of increased supply of isotopically light metals from land, and even compensates for it, resulting in the recovery of negative stable isotope excursions despite persisting enhanced weathering fluxes. These opposing effects of long-term weathering changes on stable isotope abundances in seawater limit the amplitude of weathering-driven negative excursions.

Strikingly, none of the simulations reproduces similar isotopic excursions to those measured in OAE 1a sediments. The weathering-related increased inputs of radiogenic Os and Sr cannot cause the observed unradiogenic 187Os/188Os and 87Sr/86Sr excursions. The latter must have instead been caused by an excess input of unradiogenic Os and Sr, most likely from Earth’s mantle. It is important, though, to point out the degree to which strengthened continental weathering could counteract the isotopic effect of large-scale volcanism. The small reconstructed 187Os/188Os offset between continental run-off and seawater likely prevented continental weathering changes from substantially altering the isotopic shifts caused by igneous Os supply. In contrast, the presented simulations suggest that the unradiogenic 87Sr/86Sr excursion could have been up to 1.5 times larger had there been no changes in continental

159 CHAPTER 8. RE-INTERPRETING THE ISOTOPE RECORD OF OAE 1A.

crust weathering. The measured negative δ7Li and δ44Ca excursions were previously interpreted as the result of changed weathering fluxes. This interpretation is not supported by the simulations of this chapter. Similar to 187Os/188Os and 87Sr/86Sr, the considerable difference between the simulated and measured δ7Li and δ44Ca excursions during OAE 1a could indicate substantial igneous Li and Ca supplies. However, this difference could also result from the model configuration or processes not parameterized in cGENIE. Previous studies suggested a reduced marine Li reservoir in the Early Aptian (Lechler et al., 2015), which would increase the potential of weathering flux changes to affect seawater δ7Li. Additionally, changes in weathering congruency rather than weathering flux could have caused the measured negative δ7Li (Lechler et al., 2015, , see chapter5). The potential of weathering flux 44 changes to affect seawater δ Ca depends largely on the assumed background rate of CaCO3 burial. 44 Chapter7 showed that the more CaCO 3 was buried during the Early Aptian, the larger the δ Ca offset between continental run-off and seawater could have been. This is because isotopic fractionation during

CaCO3 burial balances the effect of adding isotopically lighter continental Ca to the ocean. In the two configurations with the largest initial CaCO3 burial rates, the increase in weathering flux produces a 44 negative δ Ca excursion, even though this excursion is minimal. Assuming even larger CaCO3 burial rates in the Early Aptian, an isotopic offset between run-off and seawater could have been large enough to allow for weathering-driven δ44Ca shifts similar to measurements. However, this would also require larger baseline weathering fluxes, which were likely limited by high sea-level stands and the absence of significant orogens.

Table 8.5: Estimated total weathering-related metal emissions during OAE 1a and the CO2 emissions required to maintain the reconstructed atmospheric CO2 concentrations during weathering-related C sequestration. The given range of values represents the spread of simulation results due to different assumptions about event duration and initial C and metal cycle configurations.

18 16 9 16 19 Event duration CO2 (10 mol) Sr (10 mol) Os (10 mol) Li (10 mol) Ca (10 mol) 1 Myr 4.72 – 6.30 2.86 – 3.32 2.00 – 2.36 1.07 1.04 – 1.28 3 Myr 15.4 – 18.40 10.15 7.5 3.29 3.91

Table 8.5 shows the range of total amounts of weathering-related metal supply to the ocean in the simulations of the scenario of maximum atmospheric CO2 concentration changes reconstructed by Naafs et al.(2016a), and the C emissions that is required to achieve these CO 2 concentrations despite enhanced continental weathering. The unknown duration of OAE 1a is a considerably larger source of uncertainty for total fluxes than the model configuration.

8.2.2.2 Accuracy of the presented weathering flux estimates

The applied method to estimate weathering fluxes has two main advantages over previously published weathering flux estimates based on metal isotope records. Firstly, the isotopic forcing on all four metal isotope systems during the perturbation is consistent with estimated CO2 concentration changes and

160 8.2. CONSTRAINING C AND METAL FLUXES DURING OAE 1A reconstructed metal and C cycles prior to the perturbation. Secondly, with this method it is possible to assess the impact of different sources of uncertainty. The simulations of the weathering response during OAE 1a showed that the unknown duration of the C cycle perturbation associated with OAE 1a is clearly a main obstacle in determining precise weathering fluxes and their isotopic effect on seawater. However, there are also other sources of substantial uncertainty, which are explored in this subsection. The isotopic offset between seawater and continental run-off is key in determining whether the increase in weathering fluxes during OAE 1a could have caused isotopic shifts in the ocean. The isotopic composition of seawater prior to OAE 1a is well constrained by Early Aptian sedimentary composition within analytical and diagenetic uncertainty. The isotopic composition of continental run-off is substantially more uncertain since it cannot directly be reconstructed from preserved sediments. The values that were used for the presented simulations resulted from an effort to configure the pre-OAE 1a C and metal cycles in ways that are consistent with the reconstructed Early Aptian seawater composition (chapter7). Specifically, they resulted from tuning run-off composition to close the marine isotopic budget and achieve a proxy consistent seawater composition. As such, they depend largely on the assumptions made about the C and metal cycles, and therefore inherit uncertainties accompanying these choices. For radiogenic isotope systems, the dominant uncertainties are the strength of unradiogenic metal sources and the scale of continental metal supply. Bigger offsets between 187Os/188Os and 87Sr/86Sr, and thus a larger potential for weathering-driven isotopic excursions, is possible if unradiogenic Os and Sr inputs (predominantly from the mantle, but potentially also cosmic Os) were substantially larger than assumed based on reconstructions of Early Aptian seafloor spreading rates (see chapter7) or if Os and Sr concentrations in Early Aptian continental run-off were significantly lower than assumed (either because of weathering of Os and Sr-poor rock or retention of dissolved Os and Sr, e.g. by river deltas). The opposite of these scenarios would result in reduced 187Os/188Os and 87Sr/86Sr offsets between seawater and continental run-off, which would lower the potential for continental weathering flux increases to shift the radiogenic signature of seawater. In any case, the minor differences between simulations with different run-off compositions in figure 8.2 shows that any configuration changes need to be large to noticeably change the results, which would require a strong physico-chemical argument. The tuned stable isotopic signature of continental run-off is more ambiguous, because it does not just depend on other marine stable isotope sources and the size of the continental weathering flux, but also on the strength of marine sinks and the strength of the associated isotopic fractionation. These additional, poorly reconstructed processes add uncertainty to the presented simulation results. However, since a low potential of weathering flux increases to shift the stable isotopic composition of seawater also emerged in simulations with larger, present-day stable isotope signature offsets between seawater and continental run-off (see chapter5), it is unlikely that configuration changes of Early Aptian stable isotope cycles can significantly increase the sensitivity of the marine stable isotope signature to weathering flux changes. Besides the isotopic composition of continental run-off, uncertainties arise from the assumed atmospheric CO2 concentration changes (Naafs et al., 2016a), the assumed Early Aptian climate

161 CHAPTER 8. RE-INTERPRETING THE ISOTOPE RECORD OF OAE 1A.

sensitivity to atmospheric CO2 concentration change, the assumed duration of the event and the assumption that global weathering fluxes responded in the same way to climate change in the Early Aptian as in the present-day Earth system state. Larger climate changes, a longer event duration and a higher climate-sensitivity of the Early Aptian weathering system would have amplified isotopic excursions caused by weathering flux changes as long as the isotopic compositions of seawater and continental run-off were distinguishable. Unlike the isotopic composition of run-off, the latter causes of uncertainty have direct implications for the assumed potential for weathering-related atmospheric CO2 draw-down and required exogenic C injections.

8.3 Discussion: Re-evaluating the isotopic record of OAE 1a

Similar to previous studies, I found that the OAE 1a interval must have coincided with large igneous forcing, at least on metal cycles, because of the co-incident unradiogenic Os and Sr excursions (Jones and Jenkyns, 2001; Tejada et al., 2009; Bottini et al., 2012). At the same time, there is evidence for substantial atmospheric CO2 increase and climate change (e.g. Naafs et al., 2016a; Jenkyns, 2018), suggesting that the igneous forcing also affected the C cycle. Metal isotope records should have therefore been affected by both, mantle-derived metal additions and changes in continental metal supply. The simulations and discussion in chapter5 showed that, in such a case, the isotopic effect of at least one of these processes (igneous forcing or weathering feedbacks) has to be constrained in order to derive the scale of the other.

162 8.3. DISCUSSION: RE-EVALUATING THE ISOTOPIC RECORD OF OAE 1A

a) Metal fluxes b) Isotopic forcing potential

Figure 8.3: Comparison of average estimated metal fluxes derived in the previous sections of this chapter (a) and their relative potential to shift the isotopic composition of seawater (b). This potential was estimated by multiplying estimated fluxes with estimated isotopic offsets between seawater and the respective metal source or sink. Whiskers indicate the range between minimum and maximum estimates due to uncertain original volume and composition of OJP basalt, event duration and differences between the tested metal and C cycle configurations. In b), whiskers additionally include uncertainties about the isotopic offset between seawater and marine metal sources in the Early Aptian. Since it is unknown how secondary mineral formation changes affected riverine δ7Li and δ44Ca during the C cycle perturbation, their uncertainty ranges on the potential isotopic forcing from weathering fluxes include the possibilities of any run-off composition between fully congruent and present-day weathering regimes.

Figure 8.3a compares total estimates of unbalanced metal fluxes during the C cycle perturbation associated with OAE 1a as previously derived in this chapter. Based on these estimates, the reconstructed ranges of Early Aptian seawater, and the isotopic offset between continental run-off (chapter7) and OJP basalt (see discussion above), figure 8.3b shows the relative potential of each flux to perturb the isotopic composition of Early Aptian seawater. Most fluxes and their potential to cause isotopic excursions remain very uncertain, as shown by long whiskers, and the uncertainties considered in this assessment are by no means exhaustive. Improved constraints on the composition and release rates of each metal source are required to yield more precise metal flux estimates. Yet, a few interesting, tentative observations can be made. Firstly, according to this assessment, high-temperature alteration of OJP basalt had a much higher potential to affect the isotopic composition of seawater than low-temperature alteration, although the low-temperature alteration of ocean crust is likely more important for Os, Ca and Li cycling than high-temperature alteration of MORB at present. The reason for this lies in the different time-scales of high- and low-temperature basalt alteration and in the differences of the formation processes of ocean crust and the OJP. High-temperature alteration is more efficient at leaching metals from basalt, but ends relatively quickly as the basalt cools within decades to centuries (Schultz and Elderfield, 1997). Low-temperature alteration has much lower metal release rates but happens on longer timescales, ranging from decades to millions of years after the emplacement (Brady and Gíslason, 1997). At present,

163 CHAPTER 8. RE-INTERPRETING THE ISOTOPE RECORD OF OAE 1A. the amount of freshly formed basalt is small compared to the vast area of seafloor that is altered at low temperatures. The emplacement of the OJP, however, might have provided more opportunity for high-temperature alteration. The OJP was emplaced with consecutive lava pulses, witnessed by its different basalt layers, and is considerably thicker than ocean crust (Svensen et al., 2019). Hence, I assume here that most of the basalt volume was accessible for high-temperature hydrothermal alteration between lava pulses, while the surface of the final plateau that could have been altered at lower temperatures over an extended period was small compared to its volume.

Secondly, despite huge uncertainty, the potential of igneous Os release to have caused 187Os/188Os in an Early Aptian setting dwarfs that of the other Os sources considered. This is because there was potentially an enormous Os release from the OJP emplacement and a larger 187Os/188Os offset between Early Aptian seawater and OJP basalt than continental run-off. With slightly less certainty, continental run-off is the most likely Ca source to have affected the observed Early Aptian seawater δ44Ca. To interpret this result, it is important to mention that the isotopic effect of increased CaCO3 burial due to enhanced continental weathering has not been considered in figure 8.3b. The previously discussed simulation results (fig. 8.2) showed that the latter likely prevented a weathering-driven negative δ44Ca excursion, unless the isotopic offset between seawater and continental run-off was substantially larger than assumed in the simulations. The option of lighter continental run-off due to changed Ca fluxes on land during the C cycle perturbation is included in the uncertainty interval on the isotopic forcing potential of weathering changes in figure 8.3b. Another possibility is that Ca fractionation during CaCO3 burial or the extent of authigenic CaCO3 formation (Fantle and Ridgwell, 2020), changed during the C cycle perturbation. In any case, figure 8.3b shows that igneous Ca supply, which has a much smaller potential to affect the isotopic composition of seawater due to its smaller magnitude, is unlikely to have caused the observed negative δ44Ca excursion.

Finally, figure 8.3 shows that the interpretation of the recorded negative 87Sr/86Sr and δ7Li excursions during OAE 1a are ambiguous because continental weathering changes and the OJP emplacement could have both affected the isotopic composition of Sr and Li in seawater, and at an unknown proportion. For 87Sr/86Sr, the existence of the unradiogenic (negative) excursion during OAE 1a proves that igneous Sr supply dominated, because it is the only process that could have lowered seawater 87Sr/86Sr to such an extent. Yet, as previously discussed, weathering-related additions of continental radiogenic Sr could have masked a larger of the igneous forcing. Based on this, it is impossible to establish whether interactions with OJP basalt or climate-driven changes in the δ7Li of continental run-off dominated the observed δ7Li excursion during OAE 1a.

Having established the potential metal fluxes due to the emplacement of the Greater Ontong Java Plateau and climate-driven increases in continental weathering fluxes, as well as the associated uncertainties, it is now possible to interpret the metal isotope excursions accompanying OAE 1a and to discuss the quantitative constraints they provide on C cycle dynamics during the event.

164 8.3. DISCUSSION: RE-EVALUATING THE ISOTOPIC RECORD OF OAE 1A

8.3.1 Reconstructing the processes that affected C and metal fluxes during OAE 1a

While the Early Aptian δ13C record suggests that environmental perturbations culminating in OAE 1a started abruptly with the negative CIE (e.g. Beerling et al., 2002; Bottini et al., 2012; Adloff et al., 2020), the record of size, shape and abundance changes of nanno-calcifiers and variations in reef ecosystems have been used to argue that the onset of environmental perturbations preceded the negative CIE (Erba et al., 2010; Huck et al., 2010, 2011). Besides, there is no clear start to the perturbations of the metal isotope systems. The records of 187Os/188Os, δ7Li and δ44Ca contain indications for tendencies towards lower-than-background values before the negative CIE, but the distinction between ’background’ and ’perturbation’ for these systems is ambiguous since they might have never reached equilibrium, given their potentially slow reaction times. In any case, there is no evidence for unbalanced, isotopically distinct 13 C fluxes prior to the CIE (constant δ C of sediments and constant atmospheric CO2 concentrations, Malinverno et al., 2010; Naafs et al., 2016a), suggesting that the pre-OAE 1a tendencies in metal isotopes did not result from a large disruptions of the C cycle. Instead, they could indicate tectonic changes that were slow enough for associated C flux changes to be balanced, or were not accompanied by any C flux changes. Additional isotope records from the interval prior to the negative CIE are required to better constrain the nature, scale and onset of preceding environmental perturbations. New 187Os/188Os and δ7Li data could also help elucidate the state of marine Os and Li reservoirs prior to the negative CIE. 187Os/188Os and δ7Li records prior to the negative CIE recovered from different locations show relatively large heterogeneity. Although pre-OAE 1a δ7Li values were only recovered from two sections, they differ by 4% (Lechler et al., 2015), twice as much as 80% of observations from the present-day ocean ∼ (see figure 4.1). Pre-OAE 1a 187Os/188Os, recovered from four sites, also shows a significant spread (see figure 6.1). The spatial heterogeneity of both proxies decreased during OAE 1a but re-appeared after the event for δ7Li with a maximum difference of 7%. 187Os/188Os values post-OAE 1a are not available. This heterogeneity could indicate that the Early Aptian marine Os and Li reservoirs were substantially smaller than today. Chapter6 already showed that small increases in the global marine burial flux of organic matter can significantly reduce marine Os concentrations. Dissolved Li might have been more scarce in the Early Aptian ocean because of enhanced evaporite deposition during the opening of the southern Atlantic, which also caused substantial reductions in a range of other dissolved 2 2 ions (e.g. Mg +,SO4− Horita et al., 2002; Wortmann and Chernyavsky, 2007). Reduced marine concentrations of Os and Li prior to OAE 1a could explain the complex 187Os/188Os and δ7Li records during the negative and positive CIEs of OAE 1a, which show abrupt shifts while the negative 87Sr/86Sr and δ44Ca excursions continue relatively featureless throughout the CIEs, before recovering after the return to pre-OAE 1a δ13C values. In fact, Lechler et al.(2015) had to assume a substantially lower initial marine Li inventory in order to reproduce the scale and short duration of the negative δ7Li excursion. The negative excursions of both δ7Li and 187Os/188Os reached their full amplitude during the negative CIE. Lechler et al.(2015) interpreted the negative δ7Li excursion as the result of climate-driven weathering flux increases and increased weathering congruency. A distinct radiogenic 187Os/188Os excursion at the start of the negative CIE has also been interpreted as a sign of

165 CHAPTER 8. RE-INTERPRETING THE ISOTOPE RECORD OF OAE 1A. increased continental weathering (Tejada et al., 2009; Bottini et al., 2012). However, the weathering flux changes needed to cause the observed isotopic shifts take tens of thousands of years to develop, requiring sustained C emissions and climate change. This is incompatible with CO2 concentration reconstructions (Naafs et al., 2016a), temperature proxies (Kuhnt et al., 2011; Mutterlose et al., 2014; O’Brien et al., 2017) and the abrupt start and cessation of the radiogenic 187Os/188Os excursion itself: While the cause of the radiogenic excursion must have been a transient increase of radiogenic Os influx to the ocean or a transient decrease in the supply of unradiogenic Os, the simulations in chapter5 showed that a weathering-driven radiogenic 187Os/188Os excursion takes tens of thousands of years to develop, mainly due to the long timescale of weathering changes and particularly if the isotopic offset between continental run-off and seawater is small. However, the recovery from an injection of unradiogenic Os can be quicker, especially if baseline weathering fluxes are large. If the underlying trend to more unradiogenic dissolved Os in seawater was caused by additional mantle-derived Os input, the short radiogenic excursion most likely represents a transient cessation of this input. The sudden termination of the radiogenic excursion could then indicate resumed emissions of unradiogenic Os. Another possible cause of a transient radiogenic 187Os/188Os spike is the sudden mobilization of radiogenic Os from an additional reservoir that was previously disconnected from the ocean. The High-Arctic LIP intruded organic-rich sediments in the Early Aptian (Polteau et al., 2016) and the simulations and discussion in chapter3 showed that thermogenic methane emissions related to an active phase of the High-Arctic LIP could have caused the initial, characteristic δ13C drop measured in OAE 1a sediments. Organic-rich sediments contain large amounts of radiogenic Os (Lu et al., 2017), which could have been released during High-Arctic LIP activity. However, the radiogenic Os spike appears slightly later than the onset of the negative CIE, at least at Cau (chapter3). Given the abruptness of the radiogenic 187Os/188Os excursion and slow reaction rates of weathering fluxes, it seems more likely that the radiogenic 187Os/188Os excursion at the start of the negative CIE represents a break in mantle-derived Os emissions or mobilization of sedimantary radiogenic Os rather than a sudden spike in weathering fluxes.

At the negative excursion peak seawater reached mantle-like 187Os/188Os values. Such an isotopic shift can be caused by the addition of unradiogenic Os or reduced supply of radiogenic Os. However, since seawater reaches the isotopic composition of the unradiogenic end-member, Os supply from continental crust weathering would have had to become negligible compared to mantle-derived input at the excursion peak (and throughout OAE 1a) in order for reduced supply of radiogenic Os to cause such an excursion. Given evidence of global warming during OAE 1a, which is generally thought to increase weathering rates of continental crust, it is hard to imagine a physical mechanism that could explain a complete halt in Os delivery from continental crust weathering during OAE 1a. Thus, the addition of mantle Os is the most likely interpretation of the observed isotopic shift. Previously, Tejada et al.(2009); Bottini et al. (2012); Bauer et al.(2017a) explained the unradiogenic excursion with an influx of mantle-derived Os related to the emplacement of the OJP. As previously established, OJP emplacement would have also released light Sr, Li and Ca isotopes, which could explain the coincident negative excursions of 87Sr/86Sr, δ7Li and δ44Ca. The experiments in chapter3 further showed that a large volcanic C source during

166 8.3. DISCUSSION: RE-EVALUATING THE ISOTOPIC RECORD OF OAE 1A

13 the negative CIE is reconcilable with the δ C record. Rising atmospheric CO2 concentrations and the resulting climate change would have likely enhanced continental crust weathering, which could have reduced the amplitude of the negative 87Sr/86Sr excursion and added to the excursion amplitudes of δ7Li and δ44Ca if they were accompanied by changed terrestrial erosion and secondary mineral formation rates (figure 8.2).

During the positive CIE, the δ13C record was likely dominated by organic C burial (Jenkyns, 2010), preventing its use for the identification of exogenic C emissions. It is unknown how Os reservoir size changes due to enhanced organic C burial would have affected 187Os/188Os values, but organic C burial and redox-state changes have no direct effects on the other three metal systems. These metal systems can thus help reconstruct the evolution of LIP activity and continental weathering throughout the OAE and its recovery. The unradiogenic 87Sr/86Sr trend continued almost linearly over a period of several million years - to the end or beyond the positive δ13C excursion - before it reversed sharply and rose to pre-event values substantially faster than the preceding unradiogenic trend. The latter has been interpreted as the result of increased Sr release from volcanism or fresh basalt weathering (Blättler et al., 2011). While both processes move 87Sr/86Sr in the same direction, they have opposite effects on the marine and atmospheric C reservoirs. If the additional unradiogenic Sr was derived from high-temperature hydrothermal activity of fresh LIP basalt, it would have most likely been accompanied by an excess in C emissions. If it was instead derived from low-temperature LIP basalt alteration, then the unradiogenic Sr supply would indicate C sequestration. Neither of those C-cycle impacts could have been sustained for 5 Myr, the duration of the unradiogenic 87Sr/86Sr excursion. Instead, the 87Sr/86Sr excursion likely ∼ reflects a combination of both. Alteration of cold OJP basalts might have also affected the timing of peak excursions. My simulations in chapter5 showed that alteration of fresh basalt reduces the duration of the δ7Li excursion, because it sequesters Li, enriching the ocean in 7Li. At the same time, however, it releases unradiogenic Sr which extends the duration of the unradiogenic 87Sr/86Sr excursion. The latter could thus have been the result of an interplay of high- and low-temperature alteration. In this case, low-temperature basalt alteration likely happened more extensively than assumed in figure 8.3. Thus, possible scenarios to explain the long duration of the unradiogenic 87Sr/86Sr excursion are: a) A balance between C fluxes resulting from high- and low-temperature hydrothermal activity, organic C burial and increased continental weathering which could have been sustained for long time periods, or b) Continental weathering fluxes were reduced for millions of years, shifting the dominant marine Sr source from continental rocks to fresh LIP basalt. While these scenarios would be indistinguishable in the 87Sr/86Sr record, they would result in different impacts on the marine Li reservoir. Continental crust weathering and high-temperature basalt alteration are sources of isotopically light Li, while secondary mineral formation creates a sink for isotopically light Li during low-temperature alteration of basalt. The former two are consistent with the initial negative δ7Li excursion, but not with the δ7Li recovery during the positive CIE. Lechler et al. (2015) interpreted this recovery as the end of enhanced continental weathering but it would also be

167 CHAPTER 8. RE-INTERPRETING THE ISOTOPE RECORD OF OAE 1A. consistent with increased low-temperature basalt alteration. In summary, the 87Sr/86Sr and δ7Li records show continued seawater-basalt interaction throughout OAE 1a. While active and inactive phases of OJP emplacement are indiscernible in the 87Sr/86Sr record, their opposing isotopic effects on the δ7Li record indicate fluctuations in the relative strength of high-temperature and low-temperature basalt alteration. At the end of the positive CIE all metal isotope systems recovered, indicating that the igneous forcing and any enhanced continental metal source had ceased.

8.3.2 Quantitative constraints on C fluxes from metal isotope excursions

It is difficult to quantify carbon fluxes from metal isotope records during OAE 1a because most of their features are poorly understood. However, the reconstructions of igneous and weathering-related metal fluxes in the previous sections of this chapter can be used to contextualize existing C flux quantifications. Excursions of radiogenic isotope systems for which weathering-related metal flux changes had negligible impacts on the isotopic signature of seawater can be interpreted as direct indicators of igneous metal addition. In all simulations shown in figure 8.2, this is the case for Os, which was likely very susceptible to volcanic forcing (figure 8.3) in the Early Aptian. Furthermore, the isotopic composition of mantle Os surfacing in the Early Aptian is well constrained, both for shallow-mantle derived material erupting at mid-ocean ridges (Ishikawa et al., 2011) and Os derived from deep mantle convection during the emplacement of the OJP (Tejada et al., 2007), facilitating the inversion of the igneous Os flux from the measured isotopic excursion. This suggests that igneous Os emissions could be reconstructed from the 187Os/188Os record with isotope mixing models, although uncertainties related to the age model of OAE 1a and the initial marine Os reservoir size remain. However, the extrapolation to derive C fluxes from reconstructed igneous Os release remains highly uncertain. The Os:C ratio of elemental release from the OJP is very poorly constrained (see table 8.2). Options span several orders of magnitude, because it is uncertain how much Os was contained in the erupting lava. Although the 187Os/188Os record of OAE 1a is an important indicator for igneous activity, it can therefore not provide close constraints on exogenic C fluxes based on current knowledge. The unknown isotopic effect of changes in continental weathering complicate the reconstruction of Sr, Li and Ca fluxes from their respective isotope records. If increased continental weathering fluxes during OAE 1a are not accounted for, the scale of igneous Sr emission would be underestimated when reconstructed purely from the amplitude of the observed 87Sr/86Sr excursion. This has not been considered in previous reconstructions of OAE 1a-related C cycle changes. Both Lechler et al.(2015) and Blättler et al.(2011) recognized that negative excursions in stable isotope systems can be caused by increased igneous and continental input but assumed that 87Sr/86Sr is only influenced by the igneous forcing. Thus, they argued that the radiogenic Sr excursion limits the permissible scale of hydrothermal metal release because its relatively small excursion amplitude would be incompatible with strong igneous forcing. The difference between the simulated igneous effect on δ7Li and δ44Ca and their recorded

168 8.3. DISCUSSION: RE-EVALUATING THE ISOTOPIC RECORD OF OAE 1A excursions was then interpreted as the C cycle response - increased weathering - despite the fact that this could have affected 87Sr/86Sr, too. Since the recorded 87Sr/86Sr excursion represents the part of the igneous forcing that was not compensated by the isotopic effect of enhanced weathering, the former is more suitably interpreted as the minimal igneous forcing (assuming no weathering response at all). This means that Lechler et al.(2015) and Blättler et al.(2011)’s approach to reconstruct continental Li and Ca flux changes would result in maximum estimates. However, neither study quantified error ranges based on the uncertain δ7Li and δ44Ca of Early Aptian continental run-off, which are largely unconstrained. Like for 187Os/188Os, the amount of existing uncertainty means that the records of 87Sr/86Sr, δ7Li and δ44Ca provide only qualitative constraints on the igneous forcing and changes in continental weathering during OAE 1a, while they are of limited use for quantitative reconstructions of metal and C flux changes.

Figure 8.4: Comparison of estimated C sources and sinks during the C cycle perturbation associated with OAE 1a. Simulations of the biggest reconstructed atmospheric CO2 concentration change and corresponding weathering flux changes resulted in estimates of the combined atmospheric and marine C sink and C sequestration due to weathering flux changes. This is compared to reconstructions of C emissions during the emplacement of the OJP and C sequestration during its weathering, and estimates of C emissions from sill intrusions at the High Arctic Large Igneous Province (HALIP Polteau et al., 2016). The ’missing flux’ term quantifies the C flux which would be required to achieve C flux balance. Whiskers indicate the range between minimum and maximum estimates due to differences between the tested metal and C cycle configurations and event duration, as well as the uncertain original volume and composition of OJP basalt.

While uncertainties are large, the previously gathered constraints on C fluxes enable a tentative stock-taking of the possible range of C fluxes during the C cycle perturbation associated with OAE 1a. Overall, the reconstruction of the potential igneous forcing and weathering response during OAE 1a showed that elemental input from the OJP emplacement likely dominated environmental changes and provided the largest C source. However, figure 8.4 shows that the estimated total C release from the OJP is on the same order of magnitude as the amount of C needed in cGENIE to maintain the reconstructed elevated atmospheric CO2 concentrations during enhanced continental weathering. C emissions from sill intrusions associated with the HALIP emplacement and low-temperature alteration of OJP basalts are less relevant for the C flux balance. The sum of the average C flux estimates requires a small additional

169 CHAPTER 8. RE-INTERPRETING THE ISOTOPE RECORD OF OAE 1A.

C source, though large uncertainties about the extent of C sequestration through continental weathering and volcanic C emissions mean that direct and size of C fluxes not accounted for in this assessment are poorly unconstrained. The main uncertainties are the validity of assumed present-day climate-sensitivity and temperature sensitivities of continental weathering fluxes, the scale of initial weathering fluxes and the proportion of silicate weathering, the event duration, the quality of reconstructed atmospheric CO2 changes and the reconstruction of C degassing during OJP formation.

In reality, volcanic C emissions must have over-compensated weathering-related C sequestration because wide-spread marine organic C burial constituted an additional C sink, which has not yet been quantified for OAE 1a. However, numerical experiments with a model combining marine cycling of phosphorus (P), organic C and O2 by Tsandev and Slomp(2009) showed that increased continental P supply consistent with the weathering flux changes calculated in the present study could have resulted in 1.9 – 4.8 1018mol organic C burial over 300 – 500 kyr in the Cretaceous ocean. This is roughly × half of the estimated C flux into the ocean-atmosphere system and sedimentary carbonates, but does not account for non-continental nutrient sources and other marine sinks for P. Depending on the role of igneous nutrient supply and LIP basalt weathering for the P cycle, these estimates could be lower or upper end-members. Estimates of the effect of organic C burial of this scale on the δ13C record and consideration of Early Aptian marine oxygenation and productivity could improve the accuracy of these values for OAE 1a.

In any case, these estimates of organic C burial suggest that volcanism must have released substantially more C than was sequestered by marine carbonate burial. Higher volcanic emissions than estimated could have resulted from underestimated CO2 degassing of OJP basalt or the presence of other igneous sources, e.g. related to the HALIP. A smaller total C sink from continental weathering during OAE 1a would also be possible, with alternative explanations for the high δ44Ca of Early Aptian seawater to high initial weathering fluxes, a short event duration or smaller changes in atmospheric CO2 concentration than assumed in the above simulations. If the scale of organic C burial depended on weathering-derived nutrients, reduced C sequestration through less weathering would also lower the amount of C buried as sedimentary organic matter. The offset between volcanic emissions and weathering-related C sequestration would have had to be even larger if I underestimated C removal by OJP basalt alteration, as suggested by the 87Sr/86Sr record. The long duration of the unradiogenic Sr isotopic excursion (peak 5 – 7 Myr after ∼ the onset of the excursion, Jones and Jenkyns, 2001) furthermore suggests that unradiogenic metals kept being emitted for much longer than a C cycle imbalance can be maintained. Combined with reconstructed elevated atmospheric CO2 levels from the onset of OAE 1a through stage C7, this implies that there was a phase of dynamic adjustment between exogenic C inputs and enhanced sequestration that maintained high atmospheric CO2 concentrations and enhanced continental and/or submarine basalt weathering for millions of years. In this case, the C cycle perturbation associated with OAE 1a would have been driven and sustained by igneous C emissions. These emissions would have commenced during the negative CIE, but must have persisted for the majority of the positive CIE, isotopically masked by enhanced marine organic C burial in the δ13C record.

170 8.4. CONCLUSION

8.4 Conclusion

In this chapter, I estimated potential elemental and isotopic fluxes from the OJP and climate-driven continental weathering increases to inform the interpretation of metal isotope excursions during OAE 1a and their applicability as C flux proxies. While these reconstructions suggest that OJP emplacement could have dominated elemental fluxes during OAE 1a, they also revealed diverse and proxy-system specific sources of uncertainty that prevent accurate reconstructions of metal or C fluxes by inverting the observed metal isotope excursions. These uncertainties could be reduced by improved mechanistic understanding of elemental release and isotopic fractionation during hydrothermal alteration of fresh

basalt, a more accurate age model of OAE 1a, reduced error margins on the estimate of atmospheric CO2 concentration change and additional constraints on the Early Aptian terrestrial weathering environment and marine metal sinks. Although the uncertainties on C fluxes reconstructed based on the metal isotope record of OAE 1a remain large, the simulations and discussions in chapters5–8 demonstrated that the synopsis of radiogenic and stable metal isotope excursions, as well as δ13C, provides a valuable tool to constrain past weathering fluxes, igneous and lithological processes involved in past environmental perturbations as well as the relative importance of igneous forcing versus C cycle feedbacks. This analysis provides new insight into the potential processes that shaped the isotopic record of OAE 1a and remaining uncertainties in their reconstruction. In particular, it shows that volcanic C emissions likely sustained the C cycle perturbation associated with OAE 1a. The tentative balance of possible C fluxes suggests that more volcanic C emissions than those estimated for the OJP emplacement must have occurred, or less C sequestration by continental weathering than estimated in this assessment, in order to reconcile the presented C flux estimates with the presence of wide-spread organic C burial.

171

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The second aim of this thesis was then to assess the accuracy of metal flux reconstructions and derived C flux estimates for OAE 1a. To this end, I first evaluated the performance of existing, though unpublished metal cycles in cGENIE by comparing simulated metal concentrations and isotopic compositions in seawater to present-day observations and added parameterizations for the isotope-enabled cycling of Os (chapter4). I then used this new version of cGENIE to study the isotopic effects of LIP emplacement, the most likely large-scale volcanic C source during OAE 1a and other OAEs, on the aforementioned geochemical proxies. Running an ensemble of various combinations of igneous metal and C emissions, I tested different scenarios of how changes in volcanism and the C cycle can affect the isotopic composition of seawater while accounting for marine sediment dynamics and climate-sensitive terrestrial weathering (chapter5). I found that corrosion of marine sediments and climate-driven increases in continental weathering reduce the excursion amplitude of radiogenic isotope systems while increasing the amplitudes of stable isotope excursions. Furthermore, enhanced weathering and sediment dissolution fluxes cause an earlier excursion peak of 187Os/188Os, 87Sr/86Sr and δ44Ca if igneous metal release is accompanied by C emissions. The main result of these experiments was that the contemporaneous and opposing influences igneous to continental forcings exert on the isotopic composition of seawater make disambiguation a challenge if the igneous C and metal emissions persist for more than 100 kyr, i.e. the probable timescale of LIP emplacements and OAEs, unless the reaction time of these isotope systems was smaller than the response time of continental weathering to climate change. Instead, the recorded metal isotopic excursions of such events likely resulted from a combination of isotopic effects of metal release from the mantle and the continents. Further constraints are thus required to disentangle these metal sources in the isotope record and subsequently to estimate C fluxes based on metal isotopes. However, the new

174 framework allows for meaningful interpretations of metal isotope excursions during LIP emplacement by consequently accounting for the isotopic effects of both igneous forcing and C cycle feedbacks for the first time. After establishing that C cycle changes and igneous metal release can affect the isotope records of LIP emplacements, I went on to investigate how, and how accurately, 187Os/188Os, 87Sr/86Sr, δ7Li and δ44Ca records of OAE 1a can constrain the scale of volcanism and continental weathering changes. To answer this question, I first reconstructed the background state of the metal and C cycles in the Early Aptian. Previous studies suggested that the marine reservoirs of Sr and Ca were substantially larger in the Early Aptian than today, and that the volatility of the δ7Li record hints at a reduced marine Li reservoir. The variability of the marine Os reservoir across the geologic record, however, has not been explored before. In chapter6, I thus explored the rate of Os burial under varying marine oxygenation and nutrient availability. Small reductions in dissolved oxygen have a disproportionate effect on marine Os concentrations because of the strong association of Os and organic matter observed in today’s marine sediments. Thus, the ocean residence time of Os might have fluctuated over geologic time, potentially dropping below the ocean mixing time during periods of low marine oxygenation. If the ocean contained 187 188 less O2 prior to OAE 1a than today, it is likely that seawater Os/ Os could have responded to unradiogenic Os release from the OJP emplacement before continental weathering changes added more radiogenic Os. In this case, it should be possible to extrapolate the scale of igneous Os emission directly from the 187Os/188Os record. Besides the sizes of marine metal reservoirs, the reconstructed isotopic composition of seawater was also markedly different in the Early Aptian than today. These differences indicate that metals and C cycled differently through the surficial Earth system prior to OAE 1a than at present. In order to identify the processes behind these changes, I first simulated steady state marine isotopic composition caused by a range of possible boundary condition changes in chapter7. While it was not possible to identify a unique proxy-consistent solution, I found that proxy-consistent biogeochemical configurations of the

Early Aptian can be achieved by altering the strength of hydrothermal metal fluxes and volcanic CO2 degassing and the composition of continental run-off. In the final chapter, I used proxy-constrained model configurations of the Early Aptian to estimate the potential of continental weathering changes to noticeably affect the isotopic composition of seawater during OAE 1a (chapter8). These model experiments revealed that the offset between 187Os/188Os of seawater and continental run-off was likely much smaller than at present (chapter7), resulting in a weak weathering signal in 187Os/188Os regardless of the size of the marine Os reservoir (chapter 8). The 187Os/188Os record of OAE 1a is therefore very likely to reflect predominantly an igneous isotopic forcing, but the unknown initial marine Os concentrations prevent a precise reconstruction of igneous Os emissions. Smaller isotopic offsets between continental run-off and seawater also rendered 87Sr/86Sr and δ7Li less sensitive to weathering flux changes during OAE 1a than today and the resulting isotopic signal was likely concealed by the isotopic forcing from LIP emplacement. According to my

175 CHAPTER 9. CONCLUSIONS

reconstruction, δ44Ca might have therefore been the only one out of the five considered metal isotope proxies that was more sensitive to continental weathering changes prior to OAE 1a than today. However, the unknown isotopic effect of climate-driven changes in freshwater chemistry during OAE 1a make my reconstructions of the weathering signal in the δ7Li and δ44Ca records uncertain. While not causing prominent features in the isotopic record, continental weathering changes still had the potential to affect δ7Li, δ44Ca and 87Sr/86Sr, in a way that hinders the quantification of igneous metal fluxes from the recorded excursion amplitudes. It is therefore unlikely that the isotopic effects of either, the igneous forcing or the continental weathering response, can be reconstructed with sufficient accuracy to quantify metal fluxes from the isotopic record of OAE 1a. C fluxes derived from metal flux reconstructions are even more ambiguous, given the poorly constrained quantitative and temporal link between C and metal emissions during the OJP emplacement and remaining uncertainties about the size of weathering fluxes and the isotopic composition of continental run-off. The scaling factor between C and Os emissions is particularly uncertain, preventing accurate reconstructions of volcanic C emissions from the 187Os/188Os record despite the later probably provides the closest constraints on metal release from the OJP.

While existing uncertainties are too large to produce a detailed C flux reconstruction for OAE 1a based only on metal isotope records, the metal isotope constraints on the Early Aptian background state, combined with reconstructed atmospheric CO2 concentration and volume and composition of erupting lava during the formation of the OJP are sufficient to produce rough estimates of C fluxes associated with the OJP emplacement and continental weathering changes in chapter8. Uncertainties remain large, and an interpretation of these C fluxes ranges can only be tentative. Yet, the resulting inventory provides a summary of existing C flux constraints and the scale and origin of remaining uncertainty. Given current constraints, total estimated C emissions related to the OJP emplacement and the potential for CO2 sequestration through enhanced continental weathering are on the same order of magnitude (10 1018mol 10 1018mol). Improved accuracy of these flux estimates combined with better × ± × quantification of marine organic C burial during OAE 1a would allow for the assessment of whether additional sources of igneous C other than the OJP might have been active or whether the terrestrial weathering response was weaker than at present.

Overall, the exploration of metal and C cycle dynamics performed in this thesis demonstrates that it is possible to develop a model of the role of igneous forcing and Earth system feedbacks during OAE 1a (chapter8): A short phase of extensive volcanism followed by a weathering response cannot explain the long duration of reconstructed unradiogenic Sr supply and elevated CO2 concentrations during OAE 1a. Unradiogenic Sr release is associated with either C emission or sequestration (basalt emplacement or alteration), both of which have to be balanced on long timescales to avoid a run-away climate change, of which there is no evidence during OAE 1a. Instead, it seems that igneous C emissions related to LIP emplacement were compensated by a combination of increased continental crust weathering, OC burial and LIP basalt alteration, potentially in varying proportions, which established a long-lasting dynamic equilibrium and limited the accumulation of atmospheric CO2 and climate change. This thesis also concluded that C emissions rates are only constrained during the initial negative δ13C excursion,

176 9.1. IMPLICATIONS FOR THE INTERPRETATION OF ISOTOPIC RECORDS OF OTHER OAES AND LIP EMPLACEMENTS which likely only constituted a small portion of total C emissions throughout OAE 1a. The substantial uncertainty over the scale of the contribution of OC burial to, and thus the role of nutrient supply in, the resulting dynamic C flux equilibrium shows that the importance of OC burial for the biogeochemical recovery from sustained C emissions during the OJP emplacement remains unknown. Uncertainties over the scale of igneous and continental solute fluxes furthermore complicate estimates of exogenic nutrient release. While constraints on C and nutrient fluxes sufficiently close to understand the C cycle changes during OAE 1a mechanistically are yet to be found, my assessment provided a first balance of total C fluxes which is based on self-consistent C and metal cycle reconstructions and indicates dominant sources of remaining uncertainty.

9.1 Implications for the interpretation of isotopic records of other OAEs and LIP emplacements

The last quasi-global OAE occurred in the late Cretaceous (OAE 2, Robinson et al., 2017), with little evidence for comparable wide-spread marine OC burial events in the Cenozoic. Different theories exist to explain why OAEs have not developed in the Cenozoic, citing either paleogeographic predispositions, which would have made Paleozoic and Mesozoic oceans more susceptible to widespread anoxia, or the fact that exogenic forcings on the scale of LIP emplacements have not happened since the early Cenozoic (LIP emplacement and sea-floor spreading rates have decreased since the Mesozoic, Eldholm and Coffin, 2000). Geochemical proxies can help to understand the nature and role of exogenic forcing during different biogeochemical perturbations. My analysis indicates that the scale of environmental forcing from the emplacement of the OJP likely overshadowed other biogeochemical changes in the Early Aptian and can be considered as the driver of OAE 1a. This is supported by the observation that metal and C isotope systems recovered once the source of unradiogenic Sr ceased. Despite the large volume of material (including C and trace metals) added to the ocean-atmosphere system during the emplacement of the OJP in the Early Cretaceous, this did not overwhelm the climate system. Instead, the reconstructed

CO2 concentration changes and missing evidence for a major evolutionary catastrophe indicate that negative feedbacks were strong enough to prevent a large impact on biodiversity (to my knowledge, no loss of genera has been identified during OJP emplacement Rohde and Muller, 2005). The question then remains how the exogenic forcing due to the OJP emplacement compared with other LIP emplacement events and why this balance between external forcing and negative feedbacks was possible during the emplacement of the OJP but not at the time of other LIP emplacements, several of which caused drastic climate changes and mass extinctions, often alongside OAEs (e.g. Siberian Traps and Karoo Igneous Province). Possible reasons are different rates of LIP emplacement and associated C emissions, the fact that the OJP emplacement did not re-mobilize large sedimentary C and S reservoirs or additional external forcings or feedbacks during the other events, which did not occur in the Early Aptian (e.g. large bolide impacts Ganino and Arndt, 2009; Ernst and Youbi, 2017).

177 CHAPTER 9. CONCLUSIONS

Similar to the OJP emplacement, LIP emplacements associated with other OAEs caused negative δ44Ca, δ7Li and 87Sr/86Sr excursions during negative CIEs and trends to more radiogenic 87Sr/86Sr during/after positive CIEs (Hesselbo et al., 2007; Payne et al., 2010; Brazier et al., 2015; Song et al., 2015; Sun et al., 2018; Fantle and Ridgwell, 2020). The latter indicates that seawater-basalt interaction was a larger Sr source than continental weathering during OAEs. Assuming constant ratios of Sr and other metals released from igneous and terrestrial sources, negative δ44Ca and δ7Li excursions therefore likely also reflect the release of isotopically light Ca and Li from the mantle, although more information is required to account for the isotopic effects of climate-driven changes in terrestrial and marine sequestration of these metals.

While the Ca, Li and Sr records show similar features for different LIP emplacement events, 187Os/188Os records are less consistent across these events, with unradiogenic excursions during some (OAE 1a, OAE 2, Turgeon and Creaser, 2008; Tejada et al., 2009) and radiogenic excursions during other igneous C emission phases (Toarcian OAE, PETM, Ravizza et al., 2001; Wieczorek et al., 2013; Them et al., 2017). The variable residence time of Os in the ocean (chapter6) and the varying temporal resolution of these records mean that there is a possibility of sampling bias, i.e. that not all unradiogenic 187Os/188Os excursions might have been preserved or discovered. However, in that case, the unradiogenic 187Os/188Os excursions during the Toarcian OAE and the PETM must have been significantly shorter than the excursions during OAE 1a and OAE 2 which lasted for 1 Myr. The 187Os/188Os records of these ≥ events could thus hint at either substantial differences in the weathering response to exogenic C emission events or a sporadic source of radiogenic Os. An example of the latter could be reducing sediments that have high concentrations of Os and Re, and become the most radiogenic Os reservoirs at Earth’s surface as they age (Lu et al., 2017). Pending further investigation of the mechanisms and requirements for sedimentary Os release during LIP emplacement, the 187Os/188Os record could become an essential tool to evaluate the role of organic-rich sediment mobilization during past C cycle disruptions.

Another consideration for the differential environmental impact of LIP emplacement during Earth’s history are variations in the strength of negative C cycle feedbacks. Three main transient C sinks can be identified in the synthesis of the isotopic record of OAE 1a in chapter8: enhanced marine organic C burial, increased continental crust weathering and weathering of the freshly emplaced OJP basalt. If these processes were indeed the stabilizing forces during OAE 1a, why did they not operate similarly during other OAEs to mitigate biological disturbance? Were more drastic environmental changes during other LIP emplacements possible because they were overwhelmed by even larger external forcing in these instances or because the potential of these processes to counter igneous C emissions was reduced? The latter case would imply strong variability of the Earth system’s sensitivity to exogenic C emissions. The discussions in this thesis showed that such variations cannot simply be discovered by comparing isotopic excursion amplitudes for different LIP emplacements because exogenic forcings and Earth system feedbacks likely affected the isotopic composition of seawater on similar timescales and because the strength of their impacts depends largely on the sizes and isotopic compositions of elemental reservoirs and fluxes prior to the perturbation. Detailed reconstructions of biogeochemical

178 9.2. HOW DOES ANTHROPOGENIC ENVIRONMENTAL FORCING COMPARE TO LIP EMPLACEMENTS? cycles before LIP emplacements, as well as the elemental fluxes related to the LIP emplacement itself, could substantially improve the recovery of the isotopic signals related to exogenic forcing or Earth system feedbacks and allow for a more informative comparison of different events. While this requires a big interdisciplinary effort, involving analysis of a range of different proxy-systems in sedimentary and igneous rocks from diverse periods of Earth’s history and depositional settings, as well as process-based and global modelling, such reconstructions would provide the opportunity to constrain the strength of negative Earth system feedbacks to exogenic C injection with unprecedented accuracy and thus to improve our understanding of their variability through time and Earth system state-dependency.

9.2 How does anthropogenic environmental forcing compare to LIP emplacements?

It is important to highlight that improved understanding of the factors that determine the strength of negative or positive Earth System feedbacks to exogenic C injections is not just useful for studying past environmental changes but also for projecting the long-term evolution of the anthropogenic C cycle disruption. Depending on the total size of anthropogenic C emissions (including positive C cycle feedbacks), reactions with sediments and exposed rock are expected to remove 20 – 64% of excess C (Lord et al., 2016). These estimates are based on the assumption that C release is the only external environmental forcing and climate sensitivity of long-term negative C cycle feedbacks. In reality, this climate sensitivity is uncertain (Penman et al., 2020) and could be altered by human activity as it affects all biogeochemical cycles and the structure of Earth’s surface (e.g. Raymond and Hamilton, 2018). The transient intensification of organic C burial during OAEs is a good example to illustrate how the evolution of negative C cycle feedbacks depends on the state of other biogeochemical cycles (e.g. S, P and O2 Jenkyns, 2010; Monteiro et al., 2012; Hülse et al., 2019). LIP emplacements might provide some analogy to the present-day biogeochemical perturbation in terms of the co-occurrence of enhanced C and nutrient release, despite the long timescales of LIP emplacement. While the timescale of the anthropogenic biogeochemical imbalance is much shorter than Cretaceous and Mesozoic LIP emplacements, the rates of change are likely larger today, possibly resulting in similar order of magnitude of total excess C emissions. The fact that a combination of transiently enhanced C sinks might have stabilized the C cycle under continued exogenic C emissions during OAE 1a thus poses questions about the strength of CO2 drawdown in the future. How does the strength of net negative C cycle feedbacks today compare with that of the Early Aptian, and will it vary in the future under human influence? It is commonly assumed that silicate weathering will increase in the future (e.g. Lord et al., 2016), although it is unknown how this increase will compare to that during past global warming events. As discussed earlier, marine organic C burial likely played an important role in balancing sustained volcanic C emissions during OAE 1a. The main reason for this transient C sink was probably enhanced nutrient supply to the oceans, but the geographic configuration of ocean basins might have pre-conditioned regions of low dissolved O2 concentrations (Trabucho Alexandre et al., 2010; Monteiro et al., 2012). The source of the nutrients

179 CHAPTER 9. CONCLUSIONS that sustained OAEs is still unknown but it is commonly suggested that it resulted from biogeochemical feedbacks to climate change or the provision of large amounts of highly-weatherable mantle material during LIP emplacements (Snow et al., 2005; Arndt et al., 2009; Poulton et al., 2015). In the former case, similar nutrient sources could become active due to human-driven climate change. However, human activity also releases a range of bio-limiting nutrients to the oceans (see review in Ciais et al., 2014), and how the anthropogenic nutrient source compares to weathering of fresh LIP basalt has, to my knowledge, not been explored. Widespread burial of organic matter in marine sediments is not considered in the previously mentioned simulations of the Earth system recovery after anthropogenic C emissions, although it could be possible under sustained anthropogenically increased nutrient fluxes (Watson et al., 2017). If widespread organic C burial was an important C sequestration mechanisms during OAEs but due the continental configuration or nutrient limitations cannot develop in the future, would this difference reduce the capacity of the Earth system to balance large disruptions of the C and nutrient cycles? Finally, how important was the provision of fresh, highly-weatherable basalt for the recovery of the climate changes during OAE 1a, and could similar effects be achieved by artificial enhancements of basalt weatherability (e.g. Beerling et al., 2020)? The geological record shows that the recovery from a C cycle perturbation takes 104 – 106yr, a timescale that is impossible to investigate based on historic climate observations alone. Instead, continued study of past environmental perturbations like LIP emplacements might provide some answers to these questions and help predict the long-term consequences of the current anthropogenic environmental forcing.

9.3 Directions for future work

The results presented in this thesis open a wide range of possible pathways for future research. Firstly, further exploration of metal isotope systems, both in field and lab work and through numerical simulations could improve the use of metal isotopes as tracers of environmental changes. In particular, the dynamics of metal sinks and associated isotopic fractionation are often based on few measurements and thus poorly understood, though critical to estimate the size and isotopic composition of marine metal reservoirs prior to perturbations. For example, chapter6 showed that understanding the role of marine oxygenation for Os burial at present is necessary to estimate the volatility of the size of the marine Os reservoir over time, and to determine whether recorded Os isotope ratios are representative of the local or global environment. Besides marine sinks, the terrestrial transport and cycling of Os, Sr, Li and Ca need to be explored and considered in the interpretation of metal isotopic records. Once dissolved from the host lithology, metal ions pass through soils and freshwater systems that host a multitude of physical, chemical and biological processes, which are climate-sensitive and affect the composition of terrestrial run-off. Developing model frameworks that combine representations of terrestrial and marine transport and biogeochemistry as well as the atmospheric C reservoir has large potentials to advance our understanding of how run-off composition reacts to external forcing, and how this might be recorded by the isotopic composition of marine sediments. Another aspect of metal cycles that requires more attention are igneous

180 9.3. DIRECTIONS FOR FUTURE WORK and sedimentary sources and the conditions under which metals are released into seawater so that all active metal reservoirs during LIP emplacement can be identified and quantified. Secondly, the multi-proxy approach applied in this thesis to estimate C fluxes and assess biogeo- chemical cycling under past boundary conditions could be extended to further elucidate the impact of C emissions during OAEs. In particular, including records of temperature change and redox-state variations before and across the event could provide additional constraints on the scale of climate change and the potential for organic C burial. It would be interesting to explore numerically how records of

CO2 concentration and temperature change and marine deoxygenation can be reconciled with measured δ13C, δ18O and TEX86 in marine sediments. In addition, another proxy system that would be worth exploring in the geologic record and cGENIE is sulphur (S). Large δ34S variations have been measured during OAE 1a and other OAEs, which provide additional constraints on scenarios of igneous forcing and deoxygenation (e.g. Lechler et al., 2014). Furthermore, the δ34S record could be combined with that of δ7Li to investigate the past extent of evaporite formation and associated changes in the ion balance of seawater. Finally, it would be interesting to do a similar, joint exploration of C and metal isotope records for other periods of environmental change in the past. Comparing proxy behaviour during different occurrences of similar perturbations or under different environmental forcings could be used to understand how the reaction to and recovery from Earth system perturbations depends on boundary conditions and the nature of the external forcing. Besides periods of environmental change, reconstructions of biogeochemical balances during periods in the past could inform us about the potential of feedback systems to stabilize or destabilize the Earth system varied over time. It would be exciting to see if large changes in the weathering system, for example, occurred over time and if they play a role in the absence of OAEs in Cenozoic strata.

181

. ag fmaue A angtv I amplitudes CIE negative 1a OAE measured of Range A.2 simulations our for used bathymetry Aptian A.1 .Teplolcto fteCust sidctdb a by indicated is site Cau the of paleo-location version The regridded (2006a). the al. is et star. This Donnadieu study. black in present used the bathymetry in the simulations of the for prescribed Bathymetry A.1: Figure 183 pedxfrcatr3 chapter for Appendix

A p p e n d i x A APPENDIX A. APPENDIX FOR CHAPTER 3

Figure A.2: Size of the negative δ13C excursion measured in bulk carbonate of OAE 1a sediment records. The same 5-point smoothing was applied to all data sets and excursion amplitudes were calculated by subtracting the mean of stage C2 values from the most negative δ13C value during the excursion in the smoothed data set. Due to this calculation method, only records providing values for segments C2 and C3 could be considered. Additionally, these two stages had to be distinguishable in the records. This figure draws on data from Italy: Calabianca (Bellanca et al., 2002), Pusiano (Keller et al., 2011), Coppitella (Luciani et al., 2006), Cismon (Erba et al., 1999), north-central Tunisia (Heldt et al., 2008), Spain: Madoz (Millán et al., 2011), Carbonero, Cau and Puentenansa (Quijano et al., 2012), Aralar, Igaratza and Iribas (Millán et al., 2009), Cuchía and La Florida (Najarro et al., 2011b), France: La Bédoule (Lorenzen et al., 2013), Slovakia: Rochovika (Michalík et al., 2008), Oman (Immenhauser et al., 2005) and the southern USA (Phelps et al., 2014).

A.3 Comparison between model forcing and output

184 A.4. SENSITIVITY STUDIES

a) atmospheric CO2 concentration change

b) δ13C of atmospheric carbon c) δ13C of DIC

Figure A.3: Comparison between model forcing and simulation results: continuous lines represent model 13 forcings (atmospheric CO2 concentration changes (a) and the atmospheric δ C excursion (b) offset 13 13 by the difference between oceanic DIC δ C and atmospheric CO2 δ C (c)) and dashed lines show simulation results.

A.4 Sensitivity studies

185 APPENDIX A. APPENDIX FOR CHAPTER 3

a) carbon mass fluxes across stage C3 b) δ13C of carbon fluxes

Figure A.4: Rate and isotopic signature of carbon emissions according to scenario 3, starting from 3 and 4 times pre-industrial CO2 concentrations.

a) carbon mass fluxes across stage C3 b) δ13C of carbon fluxes

Figure A.5: Rate and isotopic signature of carbon emissions required to produce pCO2 changes as prescribed in scenario 3 together with the measured CIE, starting from 0.5 and 1 times pre-industrial oceanic nutrient inventory.

186 A.4. SENSITIVITY STUDIES

a) carbon mass fluxes across stage C3 b) δ13C of carbon fluxes

Figure A.6: Rate and isotopic signature of carbon emissions required to produce pCO2 changes as prescribed in scenario 3 together with the measured CIE, starting from an initial surface ocean carbonate saturation state of 4.5 (’low alk’) and 5.3 (’high alk’).

a) carbon mass fluxes across stage C3 b) δ13C of carbon fluxes

Figure A.7: Rate and isotopic signature of carbon emissions required to produce pCO2 changes as prescribed in scenario 3 together with the measured CIE, with and without temperature dependent biology. Weathering fluxes are adjusted to achieve the same baseline surface ocean saturation state in both simulations.

187 APPENDIX A. APPENDIX FOR CHAPTER 3

a) atmospheric CO2 forcing

b) resulting carbon mass fluxes across stage c) δ13C of carbon fluxes

Figure A.8: Rate and isotopic signature of carbon emissions required to produce the measured CIE and pCO2 changes as prescribed in scenario 3 and in a new, more extreme pCO2 change scenario (’scenario 6’).

188 A.5. OS DATA TABLE

A.5 Os data table

Table A.1: Rhenium and Osmium isotopic data for Cau samples. Uncertainties on Re and Os concentrations and measured (abbreviated as m. in the table header) 187Os/188Os and 187Re/188Os ratios incorporate analytical uncertainties and propagated uncertainties from the blank correction. Uncertainties on initial 187Os/188Os ratio include propagation of uncertainties on measured 187Os/188Os and 187Re/188Os ratios, 11 1 age (121.5 1.7 Ma; Parkinson et al.(2001)) and decay constant (l = 1.666x10 − a− ; Smoliar et al. ± (1996)). Full duplicate analysis of sample. ∗ 187 188 187 188 187 188 Sample Depth (m) Re (ppt) 2 s.e. Os (ppt) 2 s.e. Os/ Os m. 2 s.e. Re/ Os m. 2 s.e. Os/ Osi 2 s.e. Cau 10-35 64.5 2089 12.5 304.7 0.73 0.46511 0.00229 33.099 0.214 0.39805 0.00260 Cau 10-33 62.7 438 6.0 1204.9 2.25 0.25256 0.00080 1.707 0.024 0.24911 0.00080 Cau 10-13B 60.0 563 4.9 944.2 13.49 0.34595 0.00822 2.833 0.048 0.34021 0.00822 Cau 10-28 58.7 2996 10.9 1677.7 6.29 0.33373 0.00203 8.473 0.044 0.31656 0.00206 Cau 10-26 56.1 446 4.0 151.0 0.39 1.35155 0.00441 15.889 0.149 1.31935 0.00446 Cau 10-25 55.1 286 4.2 124.4 0.09 1.03418 0.00201 11.903 0.175 1.01007 0.00208 Cau 10-24 54.0 685 4.0 1256.4 1.57 0.30735 0.00057 2.579 0.016 0.30212 0.00058 Cau 10-21 51.5 7130 40.8 99.5 0.10 1.24317 0.00287 380.585 2.211 0.47202 0.01430 Cau 10-21 51.5 7148 32.2 95.5 0.35 1.23290 0.00571 397.013 2.301 0.42846 0.01569 ∗ Cau 11-07 47.1 345 4.0 84.2 0.42 1.02537 0.00777 21.230 0.267 0.98235 0.00783 Cau 10-11 44.0 956 5.9 93.3 0.18 1.11788 0.00606 53.669 0.349 1.00914 0.00638 Cau 10-10 43.5 331 4.0 113.5 0.38 1.03920 0.00390 15.107 0.191 1.00859 0.00396 Cau 10-08 42.9 223 4.3 94.3 0.37 1.02803 0.00448 12.264 0.241 1.00318 0.00452 Cau 11-03 41.0 258 4.0 97.2 0.38 0.96283 0.00464 13.609 0.217 0.93526 0.00468 Cau 10-03 39.75 614 12.6 52.8 0.07 1.04583 0.00393 60.370 1.239 0.92350 0.00512

A.6 Simulated surface ocean calcite saturation and temperature changes

189 APPENDIX A. APPENDIX FOR CHAPTER 3

a) pCO2 change scenarios b) duration estimates

Figure A.9: Surface ocean calcite saturation Ωsur f ace changes across the simulations in different pCO2 change scenarios and duration estimates for the OAE 1a negative CIE.

190 A.6. SIMULATED SURFACE OCEAN CALCITE SATURATION AND TEMPERATURE CHANGES

a) steady state Ωsur f ace

Ωsur f ace changes b) scenario 1, 20 kyr CIE onset c) scenario 5, 20 kyr CIE onset

d) scenario 1, 300 kyr CIE onset e) scenario 5, 300 kyr CIE onset

Figure A.10: Spatial pattern of surface ocean calcite saturation Ωsur f ace in our spin up for the Aptian (a), and changes in simulations of different pCO2 change scenarios and event durations (b-e). The changes are calculated by subtracting the baseline Ωsur f ace values from the Ωsur f ace values at the end of the respective simulation.

191 APPENDIX A. APPENDIX FOR CHAPTER 3

a) steady state SST

SST changes b) scenario 1, 20 kyr CIE onset c) scenario 5, 20 kyr CIE onset

d) scenario 1, 300 kyr CIE onset e) scenario 5, 300 kyr CIE onset

Figure A.11: Spatial pattern of sea surface temperatures (SST) in our spin up for the Aptian (a), and changes in simulations of different pCO2 change scenarios and event durations (b-e). The changes are calculated by subtracting the baseline SST values from the SST values at the end of the respective simulation.

192 A.7. MODEL-DATA RECONSTRUCTION OF OCEANIC PHOSPHATE INVENTORY FOR PRE-OAE 1A

A.7 Model-data reconstruction of oceanic phosphate inventory for pre-OAE 1a

To assess the oceanic inventory of phosphate for pre-OAE 1a, we compared our model seafloor oxygen level with compiled evidence of bottom water oxygenation from the available literature data (table A.2 and figure A.12). Following Monteiro et al.(2012), the presence of benthic fauna, bioturbation, and total organic carbon (TOC) content 1% were assumed to reflect oxic bottom waters, while the < absence of benthic fauna and bioturbation (presence of laminations), TOC content 1%, and elevated > concentrations of redox sensitive elements were assumed to reflect dysoxic bottom waters ([O2] ≤ 1 10 µmol l− ). Pre-OAE 1a evidence were associated with conditions just preceding OAE 1a (roughly corresponding to carbon isotope segments C1-C2 as defined by Menegatti et al.(1998)).

Figure A.12: Spatial pattern of proxy evidence for and against bottom water dysoxia before OAE 1a (see table A.2) overlying the model bathymetry.

We ran the model with different amounts of oceanic phosphate (0.25-2 times preindustrial value)

assuming an atmospheric CO2 of 4 times preindustrial values, and calculated a score (Ψ) of the model agreement with the observations for each model experiment. We took uncertainties in the paleogeographic reconstruction into account by weighing the score of the surrounding grid points for each observation (see details below).

µP ¶ i Nobs AiWi (A.1) Ψ P= 1 /2 = i Nobs Wi + = Nobs is the number of observations for pre-OAE 1a seafloor oxygenation evidence (Nobs = 20). Ai is the agreement between the model and the observation i, set to 1 in case of agreement and -1 in case

of disagreement. We then rescaled the score to be between (0-1). Wi is the weight of observation i, set to 1 for non-questionable evidence and 0.5 for questionable evidence (as indicated by a question mark in table A.2). We also added to the score the surrounding ocean grid points for each observation i,

193 APPENDIX A. APPENDIX FOR CHAPTER 3

Table A.2: Proxy evidence of pre-OAE 1a seafloor oxygenation

Locations Low oxygen Evidence Paleocoordinate References Santa Rosa Canyon × 0.5% TOC 24N, 50W Bralower et al.(1999); Li et al.(2008) << (Mexico) Southern Iberian Paleomargin • 4.8% TOC at La Frontera 28N, 5.5E Quijano et al.(2012) ≤ (La Frontera, Carbonero, Cau) Vigo Seamount •? 0.5-2% TOC 33.5N, 3E Bralower et al.(1994); Li et al.(2008) (DSDP site 398, ODP site 641) Bay of Biscay × 1% TOC 35.5N, 2E Bralower et al.(1994); Millán et al.(2009); < (DSDP site 402, and sections Quijano et al.(2012) Puentenansa, Igaratza and Iribas) Roter Sattel ×? 2% TOC, bioturbated 37N, 17E Menegatti et al.(1998) < (Switzerland) Umbria-Marche sections × 1% TOC, low concentration of 30N, 20E Danelian et al.(2004); Bralower et al. < (Apecchiese Road, Cismon, Gorgo redox-sensitive trace metals (1994); Erba et al.(1999); Hochuli et al. a Cerbara, Poggio le Guaine) (1999); Li et al.(2008); Menegatti et al. (1998); van Breugel et al.(2007b); Wester- mann et al.(2013) Tunisian sections × 0.4% TOC 20N, 14.5E Heldt et al.(2008); Elkhazri et al.(2013) < (Djebel Serdj and Jebel Ammar) Falkland plateau • 2-6% TOC 50.5S, 12.5W Bralower et al.(1994); Jenkyns et al.(2012) (DSDP site 511) Shatsky Rise ×? 0.61-2.44% TOC 0.5S, 159.5W Dumitrescu and Brassel (2005, 2006), (ODP sites 1207 and 1213, DSDP Sliter (1989), Check Scientific report site 305) Permanente Quarry × 0.1% TOC 36N, 71W Robinson et al.(2008); Sliter(1989) ≤ (USA) Mid-Pacific Mountains × 0.5% TOC 17.5S, 140W Baudin and Berthou(1996); Bralower et al. < (DSDP site 463, ODP site 866) (1994); Sliter(1989); van Breugel et al. (2007b) Hoheneggelsen •? 0.5-2.5% TOC 40N, 21E Heldt et al.(2012); Hild and Brumsack (Germany) (1998) Ul’yanovsk ×? 1-1.5% TOC, poorly dated 43.5N, 49.5E Gavrilov et al.(2002) (Russia) Kuh-e-Sefid × 1% TOC 1.5S, 42.5E (Moosavizadeh et al., 2014, , this study) < (Iran) Yenicesihlav × 0.2% TOC 3.5N, 40.5E Hu et al.(2012) < (Turkey) Yezo Group × 1.1% TOC 50N, 144E Ando et al.(2002); Takashima et al.(2004) < (Japan) Rochovica × 1% TOC 39.5N, 26.5E Michalík et al.(2008) < (Slovakia) Casabianca ×? 0.5-3% TOC, low V/Al ratio 22.5N, 16E Bellanca et al.(2002) (Sicily) Curití section (Columbia) × 1% TOC, abundant bivalves 53.52N, 18.92W Gaona-Narvaez et al.(2013) < weighting the agreement in the model-data comparison by 0.25 for non-questionable evidence and 0.125 for questionable evidence. We present here the scores for evidence from seafloor anoxia (table A.3). It shows that oceanic phosphate inventories for pre-OAE1a condition were 0.5 preindustrial value. ≤ ×

194 A.7. MODEL-DATA RECONSTRUCTION OF OCEANIC PHOSPHATE INVENTORY FOR PRE-OAE 1A

Table A.3: Model-data scores for pre-OAE 1a seafloor oxygenation

Atmosphere 4 CO2 × 0.25 PO4 0.81 × 0.5 PO4 0.81 × 1 PO4 0.72 Ocean × 2 PO4 0.37 ×

195

. bevdadsmltdmtldsrbtosi h ae column water the in distributions metal simulated and Observed B.1 197 pedxfrcatr4 chapter for Appendix

A p p e n d i x B APPENDIX B. APPENDIX FOR CHAPTER 4

Strontium Lithium Osmium

Sr/Ca Calcium

Figure B.1: Comparison of measured Sr, Li, Os and Ca profiles in seawater. Shown are composites of all available profiles of measured concentrations and isotopic compositions. Data are taken from Angino et al.(1966), Fabricand et al.(1967), Bernat et al.(1972), Brass and Turekian(1974), De Villiers(1999), Mokadem et al.(2015) and Wakaki et al.(2017) for Sr, Angino and Billings(1966), Fabricand et al. (1967), Chan(1987), Chan and Edmond(1988), You and Chan(1996), Moriguti and Nakamura(1998), Tomascak et al.(1999), James and Palmer(2000), Košler et al.(2001), Nishio and Nakai(2002), Hall (2002), Bryant et al.(2003), Pistiner and Henderson(2003), Millot et al.(2004), Choi et al.(2010) and Lin et al.(2016) for Li, Levasseur et al.(1998), Woodhouse7 et al.(1999) and Gannoun and Burton(2014) for Os and Fabricand et al.(1967) and De Villiers(1999) for Sr/Ca and Ca.

198 B.1. OBSERVED AND SIMULATED METAL DISTRIBUTIONS IN THE WATER COLUMN

Figure B.2: Comparison between measured and simulated Sr profiles in seawater. Shown are composites of all available measured Sr concentration and isotope ratio profiles and all profiles in the simulation. Data is taken from Angino et al.(1966), Fabricand et al.(1967), Bernat et al.(1972), Brass and Turekian (1974), De Villiers(1999) and Mokadem et al.(2015).

8

199 APPENDIX B. APPENDIX FOR CHAPTER 4

Figure B.3: Comparison between measured and simulated Os vertical profiles in seawater. Shown are composites of all available measured Os concentration and isotope ratio profiles and all profiles in the simulation. Data is taken from Levasseur et al.(1998), Woodhouse et al.(1999) and Gannoun and Burton (2014).

Figure B.4: Comparison between measured and simulated Li profiles in seawater. Shown are composites of all available measured Li concentration and isotope ratio profiles and all profiles in the simulation. Data is taken from Angino and Billings(1966), Fabricand et al.(1967), Chan(1987), Chan and Edmond (1988), You and Chan(1996), Moriguti and Nakamura(1998), Tomascak et al.(1999), James and Palmer (2000), Košler et al.(2001), Nishio and Nakai(2002), Hall(2002), Bryant et al.(2003), Pistiner and Henderson(2003), Millot et al.(2004), Choi et al.(2010) and Lin et al.(2016). 9

200 10 B.2. SITE SPECIFIC MODEL-DATA COMPARISON

Figure B.5: Comparison between measured and simulated Ca and Sr/Ca profiles in seawater. Shown are composites of all available measured concentration profiles and all profiles in the simulation. Data is taken from Fabricand et al.(1967), De Villiers(1999) and Fantle and Tipper(2014).

B.2 Site specific model-data comparison

11

201 APPENDIX B. APPENDIX FOR CHAPTER 4

Figure B.6: Comparison between measured and simulated Sr concentrations and isotopic composition in surface waters. Measurements are shown as symbols on the map, the colour indicating the respective value. Data is taken from Angino et al.(1966), Fabricand et al.(1967), Bernat et al.(1972), Brass and Turekian(1974), De Villiers(1999), Mokadem et al.(2015) and Wakaki et al.(2017).

12

202 . iuae n bevdvria rfie of profiles vertical observed and Simulated C.1 203 pedxfrcatr6 chapter for Appendix 187 Os/ 188 Os A p p e n d i x C a) global average b) Indian Ocean

c) North Atlantic d) East Pacific

Figure C.1: Comparison between the observed and simulated vertical profile of [Os] in seawater. Shown are the average profile in each simulation, as well as regional simulation results and published observations (East Pacific: 1Woodhouse et al.(1999), 2Chen et al.(2009), 3Gannoun and Burton(2014); North Atlantic: 4Gannoun and Burton(2014); Indian Ocean: 5Levasseur et al.(1998)). Bibliography

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