PERUVIAN MOLLUSK SHELLS AS MULTI-PROXY ARCHIVES: LATE HOLOCENE

UPWELLING VARIATION AND EL NIÑO-INDUCED BIOMINERALIZATION

EFFECTS ON TRACE ELEMENTS

by

MIGUEL F. ETAYO-CADAVID

A DISSERTATION

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy

in the Department of Geological Sciences in the Graduate School of

The University of Alabama

TUSCALOOSA, ALABAMA

2010

Copyright Miguel F. Etayo-Cadavid 2010 ALL RIGHTS RESERVED

ii

ABSTRACT

The purpose of this research is to characterize Peruvian upwelling during the late

Holocene (last 2000 years) using molluscan proxies. Peruvian upwelling is a key component of

El Niño/Southern Oscillation (ENSO) cycle, an important factor introducing interannual

variability to Earth’s weather. Thus by studying Peruvian paleoupwelling a better picture of past

ENSO conditions can be inferred.

High resolution sampling for radiocarbon and stable oxygen isotopes in modern pre-

bomb Donax obesulus and Protothaca asperrima shells revealed sub-seasonal variations in

Peruvian upwelling. Based on the shells’ radiocarbon data a new reservoir effect correction (∆R)

was calculated for the Peruvian coast. ∆R, the radiocarbon age difference between global and

local marine reservoirs, is also a qualitative proxy for deep water upwelling.

A Trachycardium procerum shell that survived the 1982-1983 El Niño revealed that

biomineralization changes induced by this event likely affected trace element incorporation into

molluscan aragonite. Detected variations in mollusk biomineralization linked to El Niño suggest

the need for coupled structural and chemical analyses in environmental proxy studies.

Comparison between modern pre-bomb and archaeological ∆R obtained from D.

obesulus shells revealed similar upwelling rates in northern Peru for the 20th and 16th centuries

and lower rates for the 6th century. Low upwelling rates in northern Peru in the 6th century are in

agreement with reported Mega- El Niño events that contributed to the political decline of Moche

society.

iii

DEDICATION

I want to dedicate this dissertation to my parents, brother, wife, and daughter. My

family’s love and affection as well as economical support contributed to the successful

completion of my PhD degree. Fernando, Olga, Victor, Johana, and Amalia thank you for

believing in me and giving me hope of better times to come.

iv

LIST OF ABBREVIATIONS AND SYMBOLS

ACC Amorphous calcium carbonate

AD Anno Domini

AMS Accelerator mass spectroscopy

BP Before Present

Ba Barium

BSE Backscatter electron microscopy

14C Radiocarbon

CAF Center for Analytical Facilities

Ca Calcium

Concytec Consejo Nacional de Ciencia, Tecnología, e Innovación Tecnológica

DIC Dissolved inorganic carbon

δ13C delta notation (per mil) for carbon fractionation where 10001 ×

−=

std

sample

R

Rδ

and where 12

13

C

CR = for sample and standard (std)

δ18O delta notation (per mil) for oxygen fractionation where 10001 ×

−=

std

sample

R

Rδ

and where 16

18

O

OR = for the sample and the standard (std)

v

∆14C Radiocarbon difference in per mil where 10001 ×

−=∆

std

sample

R

R and

where 13

14

C

CR = for the sample and the standard (std)

∆R Difference between modeled global ocean age and measured local ocean age

ENSO El Niño/Southern Oscillation

EEP Eastern equatorial Pacific

FMNH Florida Museum of Natural History

HCL Hydrochloric acid

HNO3 Nitric acid

ICDD International Center for Diffraction Data

ICP-MS Inductively coupled plasma mass spectrometer

ICP-OES Inductively coupled plasma optical emission spectroscopy

IRSM Isotope ratio mass spectrometer

k Growth rate constant

L Shell length at capture

L∞ Shell length at infinite time

LCS Lagrangian Coherent Structures

LIA Little Ice Age

Mg Magnesium

µg Micrograms

MINT Center for Materials for Information Technology

mm Millimeters

ms Mean state

vi

NBS National Bureau of Standards

NIST National Institute of Standards and Technology

NSF National Science Foundation

p Probability associated with the occurrence under the null hypothesis of a value as

extreme as or more extreme than the observed value

pMC Percent modern carbon

RS Raman spectroscopy

RSD Relative standard deviation

SEM Scanning electron microscopy

SST Sea surface temperature

Sr Strontium

t Calendrical age

TP Trachycardium procerum

VPDB Vienna Pee Dee Belemnite

VBGF Von Bertalanffy Growth Function

XRD X-Ray diffraction

yrs Years

‰ Per mil

σ Standard deviation

> More than

< Less than

= Equal to

vii

ACKNOWLEDGMENTS

I am pleased to have this opportunity to thank the people from the Department of

Geological Sciences of the University of Alabama for their contribution to my PhD completion. I

can not forget Ana I. Landeros, Victor O. Ramírez, and Diana M. Durán friendship and help

during my early years in Tuscaloosa. I am most indebted to Dr. Fred Andrus, the chairman of

this dissertation, for giving me the opportunity to come to Department of Geological Sciences.

He shared his expertise and wisdom regarding paleoclimate and archaeology with me lavishly.

My gratitude goes to my committee members Dr. Paul Aharon, Dr. Greg Hodgins, Dr. Alberto

Perez-Huerta, and Dr. Amy Weislogel who greatly contributed to my academic progress. In

particular, Dr. Alberto Perez-Huerta deserves a special recognition for his friendship and

contribution to my dissertation completion. Additionally, I would like thanking Daniel H.

Sandweiss, Maria del Carmen Sandweiss, Kevin B. Jones, Kurt Rademeker, David Reid, Greg

Hodgins, and Fred Andrus for their camaraderie and support during 2006-2007 field seasons in

Peru. I am in debt to Joe Lambert for his generous friendship and teachings about laboratory

techniques. I should notice the immense impact that knowing Dr. Ernest A. Mancini had for me

during my time in the Department of Geological Sciences. Finally, I would like to thank the

National Science Foundation, Geological Sciences Advisory Board, the Philip E. and Bunnie

LaMoreaux Foreign Geology Student Scholarship Fund, and my parents for the financial support

required while completing my research.

viii

CONTENTS

ABSTRACT................................................................................................ ii

DEDICATION........................................................................................... iii

LIST OF ABBREVIATIONS AND SYMBOLS ...................................... iv

ACKNOWLEDGMENTS ........................................................................ vii

LIST OF TABLES..................................................................................... xi

LIST OF FIGURES .................................................................................. xii

1. INTRODUCTION ...................................................................................1

2. SUBSEASONAL VARIATIONS IN MARINE RESERVOIR AGE FROM PRE-BOMB DONAX OBESULUS AND PROTOTHACA

ASPERRIMA SHELL CARBONATE .......................................................11

2.1. Abstract ...............................................................................................11

2.2. Introduction.........................................................................................12

2.3. Material and Methods .........................................................................14

2.4. Results.................................................................................................19

2.5. Discussion ...........................................................................................22

2.6. Conclusions.........................................................................................30

2.7. Acknowledgements.............................................................................32

2.8. References...........................................................................................33

ix

2.9. Appendix 1..........................................................................................37

3. EL NIÑO INDUCED BIOMINERALIZATION CHANGES: REPERCUSSIONS FOR MOLLUSCAN PROXIES ...............................43

3.1. Abstract ...............................................................................................43

3.2. Introduction.........................................................................................43

3.3. Species Description and Collection Site .............................................44

3.4. Previous studies ..................................................................................46

3.5. Results.................................................................................................49

3.6. Discussion ...........................................................................................52

3.7. Conclusions.........................................................................................54

3.8. Methodology.......................................................................................55

3.9. Acknowledgements.............................................................................56

3.10. References.........................................................................................57

3.11. Appendix 2........................................................................................64

4. RESERVOIR EFFECT VARIATION IN DONAX OBESULUS SHELLS FROM NORTHERN PERU: EVIDENCE FOR MEGA-EL NIÑO IN THE LATE HOLOCENE.......................................77 4.1. Abstract ...............................................................................................77

4.2. Introduction.........................................................................................77

4.3. Materials and Methodology ................................................................80

4.4. Results.................................................................................................83

4.5. Discussion ...........................................................................................85

4.6. Conclusions.........................................................................................90

4.7. Acknowledgements.............................................................................90

4.8. Laboratory methods ............................................................................91

x

4.9. References...........................................................................................92

4.10. Appendix 3........................................................................................97

5. CONCLUSIONS..................................................................................107

xi

LIST OF TABLES

1. El Niño events 1525 to 2010 AD...........................................................10 2. Radiocarbon data for P. asperrima and D. marincovichi ......................20 3. ∆R statistical data for the three studied periods within the late Holocene ....................................................................................................88 4. Radiocarbon data for D. obesulus showing calibrated AD ages............89

xii

LIST OF FIGURES

1. Schematic representation of ENSO conditions........................................4 2. Donax obesulus and Protothaca asperrima collection sites..................16 3. Donax obesulus and Protothaca asperrima shells.................................17 4. Stable isotope and radiocarbon profiles for D. obesulus shells .............23 5. Stable isotope and radiocarbon profiles for P. asperrima shells ...........25 6. Box plots of ∆R value distributions of the four analyzed shells............27 7. Molluscan intra-shell ∆R and ∆R weighted average at different latitudes along the Peruvian coast..............................................................31 8. Images of T. procerum shells.................................................................45 9. T. procerum shell collection site............................................................47 10. T. procerum trace element, stable isotope and radiocarbon data.........48 11. SEM images of T. procerum shell .......................................................50 12. Raman spectra analyses along T. procerum shell ontogeny................51

xiii

13. Modern and ancient Donax obesulus shells collection site .................81 14. Donax obesulus ∆R ranges and weighted ∆R averages ......................84 15. Donax obesulus δ18O averages and ranges..........................................86

1

1. INTRODUCTION

This dissertation is composed of three papers to be published in peer-reviewed journals.

These papers focus on modern pre-bomb Peruvian reservoir effect correction (∆R) obtained from

mollusk shells, biomineralization and chemical changes in the shells of Trachycardium procerum

that survived 1982-83 El Niño event, and ∆R changes through the late-Holocene along the

Peruvian coast as recorded by archaeological Donax obesulus shells.

The main goal in these three papers is to improve the understanding of Holocene

Peruvian upwelling. This objective will be accomplished by generating a modern pre-bomb ∆R

benchmark against which ∆R values obtained from archaeological sites will be compared. If

differences exist between modern and archaeological ∆R those disparities may be consequence

of different oceanic conditions in ancient and modern times. This work will complement the

research published by Jones et al. (2007, 2009, and 2010) and it will give more direct qualitative

high-resolution radiocarbon proxy information about Holocene Peruvian upwelling than has yet

been published. Additionally, the biomineralization study of bivalves surviving El Niño events

may contribute to have a better understanding of the way trace elements are incorporated into

molluscan carbonate under stress. Molluscan high resolution radiocarbon and biomineralization

studies are novel approaches for understanding dynamic upwelling systems and the proxies used

to characterize them in the past.

Many general inferences about Peruvian upwelling have been made by studying past El

Niño/southern oscillation (ENSO) conditions obtained by different proxies such as molluscan

2

assemblages (Sandweiss et al., 1996, 1997, 2001), coral elemental and stable isotope profiles

(Gagan et al., 1998; Cobb et al., 2003; Koutavas et al., 2006), and sedimentation rates (Rodbell

et al., 1999; Haug et al., 2001; Rein et al., 2005). Such inferences are important because they

provide insight into upwelling conditions through the Holocene. However, molluscan

radiocarbon content allows a closer and direct measure of marine upwelling conditions. This is

because mollusk shells precipitate carbonate directly from dissolved inorganic carbon (DIC) in

water (McConnaughey and Gillikin, 2008; Poulain et al., 2010). Deep water is depleted in

radiocarbon due to radioactive decayment and the time this water has been isolated from the

atmosphere (Dickin, 2005). Thus, different radiocarbon concentrations in molluscan carbonates

may be related to upwelling changes in an area.

Upwelling is the movement of deep sea water to the ocean surface (Pidwirny, 2006).

Upwelling along the Peruvian coast changes as a consequence of wind direction and speed, and

thermocline depth variation sometimes associated with ENSO events (Huyer et al., 1987). Wind

direction and speed control the volume of upwelling water and thermocline depth controls

whether the upwelled water is from the warm, nutrient-depleted, tropical mixed layer or cold

nutrient-enriched, deep water (Huyer et al., 1987).

ENSO, a prominent source of interannual variation in weather and climate around the

world (Trenberth 1997; Trenberth and Caron, 2000), is defined as a coupled oceanic and

atmospheric interaction (Trenberth 1997). El Niño, La Niña, and normal conditions constitute

ENSO oceanic phases (Philander, 1985; Trenberth 1997) while the Southern Oscillation is the

atmospheric component of ENSO. Southern Oscillation normal conditions are defined by high

atmospheric pressure in Tahiti and low atmospheric pressure in Darwin (Allan et al., 1991). El

Niño oceanic conditions are defined by a five-month sea surface temperature (SST) moving

3

average in the El Niño 3.4 region (5°N–5°S,120°–170°W) that positively exceeds the calculated

1950-1979 SST mean by at least 1σ for six months or more (Trenberth 1997). La Niña

conditions are defined by SST lower than the 1950-1979 SST mean by at least -1σ for six

months. Normal ENSO conditions are defined by the temperatures falling within ±1σ of 1950-

1979 SST mean. El Niño, La Niña and Normal ENSO conditions described further in the text

refers to these descriptions of Pacific oceanic conditions. The suffix ms is added to El Niño, La

Niña or Normal when one of these phases is the ENSO Pacific “mean state”.

During normal ENSO conditions trade winds drive Eckman flow, removing coastal

surface water off the coast of Peru, in turn triggering upwelling of deep cold water (figure 1).

This contributes to cooler SST’s in this region than in the western Pacific (Oliver and Hidore,

2002). During La Niña, SST’s are colder than usual in the eastern Pacific due to intensification

of trade winds (Philander, 1985). Trade wind intensification during La Niña is caused by

northward movement of the intertropical convergence zone (ITCZ) (Philander, 1985). During El

Niño, reversal or weakening of trade winds by southward ITCZ movement, allows the incursion

of warm water from the western to eastern Pacific (Philander, 1985)(figure 1). The Eastern

Pacific thermocline changes from ~40 m depth during normal/La Niña conditions to ~80 m depth

during El Niño (Huyer et al., 1987; Pidwirny, 2006).

El Niño conditions in the eastern Pacific occur about every 3 to 7 years (Ortlieb and

Macharé, 1993, Rodbell et al., 1999), and they typically persist from 6 to 18 months (Barber and

Chavez, 1983). El Niño has catastrophic consequences around the world due to its marked

influence in local and regional weather/climate conditions (Barber and Chavez, 1983; Ortlieb

and Macharé, 1993). In South America, El Niño generates rains in the Bolivian Altiplano,

southern Ecuador, and the coast of Peru, while it triggers droughts in Colombia and Venezuela.

4

Figure 1 Schematic representation of Normal (left) and El Niño (right) ENSO conditions. Observe trade winds reverse and thermocline deepening in the Peruvian coast during El Niño. Notice that Peru upwelling depth remains stable but its source change from deep (blue) to surface (red) water.

5

La Niña conditions have the opposite effect in these regions (Rodbell et al., 1999; Baker et al.,

2001; Haug et al., 2001; Rein et al., 2005; Poveda et al., 2006).

In the following paragraphs I review what is known about Holocene ENSO conditions as

recorded by multiple proxies. I start my review from the base of the Holocene and progress until

modern times.

South American climate during the early-Holocene seems warm and humid, compared to

modern conditions, based on proxies from different continental locations. In Colombia marked

increases in pollen from high humidity-adapted vegetation is found in the sedimentary record

from high altitude lakes (van der Hammen and Hooghiemstra, 1996; Velez et al., 2006).

Venezuela Cariaco basin sediments show increase in Fe and Ti content due to high riverine input

related to augmented rains (Haug et al, 2001; Petersen and Haug, 2006). Lake Titicaca sediments

from the Bolivian Altiplano show fresh-water planktonic diatom domination suggesting a

constant water supply (Baker et al., 2001). In the Ecuadorian mountains, Lake Pallcacocha

shows high amounts of rain-related light-colored clastic laminas in its sediment record (Rodbell

et al., 1999). Peruvian offshore cores reveal high sediment accumulation rates attributed to

increased coastal flood frequency (Rein et al., 2005). Based on reported continental widespread

humidity and a more northerly (than current) ITCZ position for the early-Holocene (Clement et

al., 2000; Haug et al., 2001; Martínez et al., 2006; Vélez et al., 2006; Pettersen and Haug, 2006)

it may be possible to suggest that Normal-ms conditions existed for this period. However, high

Bolivian Altiplano and Peruvian coastal humidity is inconsistent with observed climatic

conditions in those areas during Normal-ms in the Pacific (Baker et al., 2001; Rein et al., 2005).

Thus, water abundance on those regions registered in proxy data may be explained by Andean

icecap melt once the El Abra stadial ended (van der Hammen and Hooghiemstra, 1996).

6

ENSO conditions are more difficult to interpret from proxy data between 9000 and 5000

14C cal years BP, in a period sometimes known as the Holocene ‘thermal maximum’ (Haug et al.,

2001). This is because different proxy data suggest simultaneous El Niño-ms and La Niña-ms for

the eastern Pacific during this period. Sandweiss et al. (1996) analyzed warm-water molluscan

assemblages from archaeological sites (north of 10ºS), suggesting that between 8000 and 5000

14C years BP, El Niño-ms existed in the Pacific. However, Devries et al. (1997) and Wells and

Noller (1997) contradicted the Sandweiss et al. (1996) conclusions, pointing out evidence

suggesting La Niña conditions during the same time interval. Each argued that warm-water

molluscan assemblages were found in warm-water embayments. However, Sandweiss et al.

(1996) considered embayments open consequently reflecting warm oceanic conditions for the

Peruvian coast north of Lima. Meanwhile, Wells and Noller (1997) considered warm water

embayments restricted and cold waters dominating Peruvian oceanic conditions. Supporting the

idea of cold oceanic conditions for the area, Wells and Noller (1997) pointed out thick sequences

of eolian dunes and remarkable preserved human/vegetal remains as evidence for hyperaridity of

the Peruvian coast between 7000 and 5000 14C cal yrs BP.

Further support for Pacific El Niño-ms during the Holocene ‘thermal maximum’ came

from coral-derived δ18O and Sr/Ca SST temperatures showing that western Pacific warm pool

was 1ºC warmer than current conditions (Gagan et al., 1998). Also, SST records derived from

fish otolith δ18O data showed Northern Peru had significantly warmer than current annual SST’s,

and central Peru had warmer than present summers (Andrus et al., 2002; Andrus et al., 2003). In

Ecuador, Lake Pallcacocha sediments indicated low El Niño frequency for the ‘thermal

maximum,’ suggesting generally warmer conditions in the EEP (Rodbell et al., 1999). Low El

Niño frequency for the period was supported by lake sediment records from Galapagos Islands

7

(Riedinger et al., 2002), reports about undisturbed well preserved organic-rich fine sediments in

southern Peru (Fontugne et al., 1999), and low sediment input in Peruvian offshore cores (Rein et

al., 2005). Additionally, Huascaran icecap δ18O data show that the warmest Andean tropospheric

temperatures occurred during the Holocene ‘thermal maximum’ (Thompson et al., 1995). The

warm ‘thermal maximum’ temperatures were a consequence of high atmospheric moisture

content that may be linked to EEP SST rise (Diaz and Graham, 1996). Higher than present EEP

SST’s for the Holocene ‘thermal maximum’ are inferred from high productivity benthic

foraminifera taxa low abundance in marine cores (Loubere, 1999).

Conversely, evidence supporting La Niña-ms during the Holocene ‘thermal maximum’

can be summarized as follows. Foraminifera-derived Mg/Ca thermometry from a Galapagos

Islands core record (in the cold tongue region) suggest colder than current SST (Koutavas et al.,

2002, 2006). This is supported by high abundance of upwelling-prone foraminifera and

coccolithophor assemblages in Colombian Pacific cores associated to seasonally stronger

southeast trade winds (Martínez et al., 2006). Reduced water level in Lake Titicaca, inferred

from the abundance of fresh-water diatoms and stable isotope data from cores, show very dry

conditions in the area between 8500 and 5000 14C years BP (Baker et al., 2001; Theissen et al.,

2006). The wettest period in 14000 14C cal yrs for northern South America registered in Cariaco

basin Ti and Fe sediment content (Haug et al., 2001). Molluscan-derived δ18O records showing

cooler (2-3ºC) than current mean SST during the Holocene ‘thermal maximum’ for southern

Peru (Carré et al., 2005).

Less debate exists in the literature about ENSO conditions after the Holocene “thermal

maximum” between 5000 and 1200 14C cal years BP. Notable preservation of soft non-

carbonized materials north of 10ºS after 5000 14C cal years BP (Sandweiss et al., 1997) and cold-

8

water marine species dominance in archaeological coastal middens (Sandweiss et al., 2004,

Andrus et al., 2008) suggest that Normal-ms conditions were in place in the Pacific. However,

there is proxy evidence for El Niño frequency increase in this period (Ortlieb and Macharé,

1993; Rodbell et al., 1999; Haug et al., 2001; Baker et al., 2001). Evidence for increased El Niño

episodes is found in high frequency rain-related sediment deposition found in Pallcacocha Lake

cores (Rodbell et al., 1999), and a succession of beach ridges formed by flooding in northern

Peru (Ortlieb and Macharé, 1993). Cariaco basin rain-related Ti and Fe records show marked

amplitude increase between wet and dry events recorded after 5000 14C cal years BP (Haug et al.,

2001). Successive dry and wet periods in the Bolivian Altiplano region are recorded in Lake

Titicaca sediment cores (Baker et al., 2001). In the dissertation I report data from archaeological

shells form ca. 1300 BP in northern Peru, thus, by using high resolution radiocarbon proxies on

those shells I will evaluate upwelling conditions in northern Peru during this period.

ENSO conditions between 1200 14C cal years BP and today are defined by both proxy

and historical data (see table1), and can be summarized as dominated by Pacific Ocean La Niña

conditions and more frequent El Niño (Quinn et al., 1987; Ortlieb and Macharé, 1993;

Thompson et al., 1995; Sandweiss et al., 1997; Rodbell et al., 1999; Haugh et al., 2001; Moy et

al., 2002; Cobb et al., 2003; Rein et al., 2005; Langton et al., 2008). Proxy data such as coral

δ18O signals (Cobb et al., 2003), South American ice cap δ18O records (Vimeux et al., 2009), and

Cariaco basin Ti content in sediments (Peterson and Haug, 2006) suggest La Niña-ms conditions

for the Pacific during Little Ice Age (LIA; ~390-100 yrs BP). A western-eastern SST gradient

reduction in the Pacific Ocean during LIA is suggested as well (Cobb et al., 2003). Tropical

Pacific modeling considering solar and volcanic forcing suggests El Niño-ms conditions during

LIA (Mann et al., 2005) in opposition to proxy data. These proxies are especially relevant to this

9

dissertation because radiocarbon analyses on archaeological shells from this period (372 yrs BP)

in northern Peru are reported. These data provide upwelling information that may contribute to

better define ENSO oceanic conditions during the LIA.

Data concerning ENSO conditions through the Holocene, even though numerous, are still

fragmentary. Sometimes data collected form different sources and regions support each other,

but are contradictory in other instances. It may be that local factors interfere or obscure ENSO

signals obtained from proxy data. The most direct, complete and reliable instrumental

information about Holocene ENSO conditions is unfortunately very short (about a 60 yr record).

Thus, local proxy analyses on ENSO oceanic conditions are necessary for periods of time older

than 60 years ago. Despite being fragmentary, my research as explained in the following pages

gives direct qualitative proxy information about Holocene oceanic conditions prior to 1950 AD,

and examines, from a biomineralization perspective, the limitation molluscan trace elements as

paleoenvironmental proxies.

10

Very strong El Niño events Strong El Niño events Moderate El Niño events 1578 1525-1526 1806-1807 1728 1531-1532 1812 1791 1539-1541 1817 1828 1552 1819

1877-1878 1567-1568 1821 1891 1574 1824

1925-1926 1591-1592 1832 1982-1983 1607 1837 1997-1998 1614 1850

- 1618-1619 1854 - 1624 1857-1858 - 1634 1860 - 1652 1866 - 1660 1867-1868 - 1671 1874 - 1681 1880 - 1687-1688 1887-1889 - 1696 1896-1897 - 1701 1902 - 1707-1708 1905 - 1714-1715 1907 - 1720 1914 - 1747 1918-1919 - 1761 1923 - 1775 1930-1931 - 1785-1786 1939 - 1803-1804 1943 - 1814 1951 - 1844-1845 1953 - 1864 1965 - 1871 1976 - 1884 1987 - 1899-1900 2002-2003 - 1911-1912 2006-2007 - 1917 2009-2010 - 1932 - - 1940-1941 - - 1957-1958 - - 1965-1966 - - 1972-1973 - - 1986-1987 - - 1991-1993 -

Table 1 El Niño events 1525 to 2010 AD ranking Quinn et al. (1987), Ortlieb and Macharé (1993), and Wolter and Timlin (1998).

11

2. SUBSEASONAL VARIATIONS IN MARINE RESERVOIR AGE FROM PRE-BOMB DONAX OBESULUS AND PROTOTHACA ASPERRIMA SHELL CARBONATE 2.1. Abstract

Two Donax obesulus and two Protothaca asperrima shells collected prior to 1950’s

nuclear testing were micromilled at sub-seasonal resolution, and the samples were analyzed for

radiocarbon to produce new ∆R estimates for coastal Peru. We report ∆R estimates of 117±9.5

and 99±9.2 yrs for northern (4º4’S to 8º14’S) and central (13º52’S) Peru based on D. obesulus

and P. asperrima shells, respectively. Intra-shell ∆R variability of up to 400 14C yrs was detected

over periods of time as short as 40 days. Those sub-seasonal ∆R shifts were not mirrored by

changes in δ18O as was expected based on the close relationship between deep water upwelling

and cool water temperature. These rapid shifts in ∆R and the lack of a consistent relationship

between ∆R and δ18O in molluscan carbonate are consistent with Lagrangian modeling of

Peruvian upwelling. This type of modeling considers upwelled water as a dynamic combination

of filament-like Lagrangian coherent structures that may have different radiocarbon content from

one another and/or acquire different temperatures through time. Sub-seasonal radiocarbon

analyses may therefore serve as a proxy for past spatial and temporal heterogeneity in upwelling

systems. Additionally, these data suggest radiocarbon dating of short-lived mollusks in such

regions may not reflect inter-annual mean ∆R.

12

2.2. Introduction

Upwelling along the Peruvian coast is largely a function of wind and thermocline depth

variation often associated with El Nino/southern oscillation (ENSO) events (Huyer et al., 1987).

Changes in these parameters influence radiocarbon concentration in sea water by controlling

vertical mixing. Wind direction and speed control the volume of upwelling water, and

thermocline depth controls whether upwelled water is from the warm, nutrient-depleted, tropical

mixed layer or cold, nutrient-enriched, deep water (Huyer et al., 1987). Cold deep water

upwelling reduces radiocarbon concentration in surface seawater while warm water upwelling

makes surface water radiocarbon content closer to atmospheric levels. Radiocarbon depletion in

deep water is a consequence of isolation from atmosphere during circulation and the radiocarbon

decay process (Toggweiler et al., 1991; Dickin, 2005; Jones et al., 2007).

Vertical mixing is a spatially and temporarily heterogeneous turbulent flow populated by

several physical oceanic structures, such as eddies or plumes, that influence where and when

water moves (Rossi et al., 2009). Because of its complexity, vertical mixing is considered as a

dynamic or Lagrangian fluid flux system (Shadden et al., 2005). In Lagrangian systems fluid flux

is described by different particle (or groups of particles) trajectories through finite time periods.

By defining trajectory boundaries, called Lagrangian coherent structures (LCS) which separate

the different paths of water bodies, general flux movement can be described accurately (Shadden

et al., 2005). LCS have a filament-like shape (see Shadden et al., 2005). For that reason in this

paper, LCS will be called water “filaments” for simplicity. Thus, vertical mixing can be

envisioned as a “spaghetti bowl” where individual water filaments change position through time.

Even though vertical mixing is described by many different water trajectories in finite-time

periods there is always a final average flux in the system (in this case an average upwelling rate).

13

Changes in vertical mixing alter radiocarbon concentrations in surface water where

organisms grow carbonate skeletons. Thus, a radiocarbon age offset is observed when

contemporaneous samples from marine and terrestrial reservoirs are dated. This radiocarbon age

offset is known as reservoir effect R(t), and it is not constant in time or space; local reservoir

effects R’(t) also exist (Stuiver and Braziunas, 1993). The modern pre-bomb global R (1830)

value is 402 yrs (Stuiver and Braziunas, 1993). The difference between global R(t) and local

R’(t) is known as the reservoir effect correction (∆R) (Stuiver and Braziunas,1993). ∆R is also a

qualitative proxy for vertical mixing in an area (Andrus et al., 2005).

We studied modern pre-bomb mollusk shells collected along the Peruvian coast during

the first part of the 20th century in order to detect changes in ∆R. The aim of this study was to

understand how vertical mixing is recorded in sub-seasonal time-series data from mollusks in the

eastern Pacific prior to anthropogenic atmospheric radiocarbon contamination. Continuous time-

series records such as those provided by corals are useful to monitor ∆R changes in oceanic

water (e.g. Druffel, 1981, 1982, 1987, 1997; Druffel and Griffin, 1993; Moore et al., 1997;

Guilderson et al., 1998, 2000, 2002). However, the use of corals as proxies for Peruvian

upwelling is not possible because water temperatures are too cold for them to grow there. Thus a

molluscan radiocarbon proxy may serve as an alternative for assessing upwelling variations

along this coast.

Aquatic mollusks precipitate their shells’ carbonate primarily from dissolved inorganic

carbon (DIC), with a lesser, variable contribution from metabolic sources (McConnaughey and

Gillikin, 2008; Poulain et al., 2010). Thus a growing mollusk shell records radiocarbon

concentrations in local water through time. A shells’ radiocarbon concentration is less likely to

be greatly affected by metabolic carbon because its contribution to carbonate is usually below

14

12% (Lorrain et al., 2004; McConnaughey and Gillikin, 2008; Poulain, et al., 2010).

Furthermore, as filter-feeders (primary consumers) bi-valved mollusks’ metabolic carbon has

values isotopically close to that of water’s DIC (McConnaughey and Gillikin, 2008; Poulain, et

al., 2010). Mollusk shell radiocarbon concentrations have been successfully used as upwelling

proxies in modern post-bomb and pre-bomb times (e.g. Andrus et al., 2005; Jones et al., 2007).

In this paper we present new modern pre-bomb ∆R values obtained from molluscan carbonate

from two common inhabitants of the Peruvian coast. This information complements the available

modern pre-bomb data for the region (Taylor and Berger, 1967; Jones et al., 2007).

2.3. Materials and Methods

2.3.1. Shell collection and archival sites

Two D. obesulus shells were collected in Puerto Pariñas (4º40’S, 1929) and Puerto

Salaverry (8º13’S, 1926), northern Peru and two P. asperrima shells were collected in Paracas

(13º52’S), central Peru. The locations of the collection sites can be seen in figure 2. After

collection, samples were archived in the Smithsonian Institution Museum of Natural History (D.

obesulus) in Washington D.C. and the Florida Museum of Natural History (P. asperima) in

Gainesville, Florida until they were loaned for this research.

2.3.2 Species description

2.3.2.1. Donax obesulus

The surf clam D. obesulus (figure 3, left) sensu Carstensen et al. (2009) (formerly D.

marincovichi and D. peruvianus, Coan, 1983) lives in the intertidal zone of sandy beaches

(Paredes and Cardozo, 2001) where it can be found buried in sediments in water depths of up to

20 cm (Carstensen et al., 2007). An interesting aspect of the Donax genus is its ability to migrate

with the tide (Ansel, 1983). D. obesulus is found from Nicaragua to Chile (Keen, 1958; Guzman

15

et al., 1998) being able to survive at comparatively wide range of water temperatures. Its shell is

made of aragonite based on unpublished X-ray diffraction (XRD) data measured at The

University of Alabama Department of Geological Sciences (see appendix 1). The clams used in

this study reached a maximum length of 25 mm, but this species can reach up to 33.2 millimeters

in Peru (Talledo, 1980).

2.3.2.2. Protothaca asperrima

The infaunal P. asperrima (figure 3, right) is a subtidal clam that lives in mud flats from

Magdalena Bay, Lower California to Peru (Keen, 1958). This is a medium-size bivalve that

grows up to 44 mm in length (Keen, 1958). Its shell is made of aragonite according to

unpublished XRD data from The University of Alabama Department of Geological Sciences (see

appendix 1). In Ilo Bay, Southern Peru, this species is found at depths up to 12 m (personal

communication with local shell divers).

2.3.3. Radiocarbon and stable isotope shell sampling

One valve from each shell was mounted intact onto a glass slide and affixed using

Crystalbond adhesive. The outer 10 µm of the shell was milled off prior to taking radiocarbon

and stable isotope samples to avoid possible surface contamination. The mounted valves were

sub-sampled with a Merchantek/New Wave Micromill or a slow speed hand drill (shell

220557A) using carbide milling bits. Radiocarbon samples were milled with a 0.10 mm diameter

bit, and ~5 mg of carbonate was obtained per sample. Samples for stable isotope analysis were

milled using 0.08 mm bits and averaged about 70 µg/sample. Samples were milled in a series of

continuous transects along the shell’s growth lines from umbo to edge. The maximum overall

milling depth was 150 micrometers. After collection, the carbonate powder was weighed and

16

Figure 2 Map showing the location of Donax obesulus and Protothaca asperrima collection sites, denoted by stars.

17

Figure 3 Shells of Donax obesulus (left) and Protothaca asperrima (right). White bars represent 1 cm.

18

stored in aluminum foil (radiocarbon) or glass vials (stable isotopes) for their subsequent

digestion with phosphoric acid.

2.3.4. Radiocarbon analyses

Samples for radiocarbon analyses (shells 368497, 424416, and 220557B) were

hydrolyzed using orthophosphoric acid and heated under vacuum to reduce reaction time. The

resultant CO2 was sealed in glass vials and sent to the University of Arizona for accelerator mass

spectrometry (AMS) analysis. Two 14C-dead samples were processed with shell samples for

quality control. δ13C values used for 14C correction were measured at the National Science

Foundation (NSF) University of Arizona AMS facility and are available in table 2. The CO2 was

converted into graphite following the methodology of Slota et al. (1987) and analyzed at the NSF

University of Arizona AMS facility. Samples for radiocarbon analysis from shell 220557A were

reduced to graphite using an iron catalyst following the method of Vogel et al. (1984) and

analyzed at the University of Georgia AMS Laboratory at the Center for Applied Isotope

Studies. δ13C values used for 14C correction of those samples are also available in table 2.

2.3.5. Stable isotopes analyses

Carbonate samples for stable isotopes were analyzed on a Thermo GasBench II coupled

to a Thermo Delta Plus isotope ratio mass spectrometer (IRMS). Stable isotope samples from

shell 220557A were cryogenically purified in a micro-extraction line following the McCrea

(1950) procedure before dual-inlet IRMS analysis. The mean precision (1σ) of the measurements

is 0.11 per mil for oxygen based on multiple NBS 19 analyses in each sample run.

2.3.6. Reservoir correction calculations

R’(t), the local 14C marine reservoir age obtained from mollusk shells can be expressed as

)()()(' tAtMtR m −=

19

Where Mm(t) is the measured radiocarbon age for the mollusk shell, and A(t) is the atmospheric

radiocarbon age obtained from a terrestrial calibration curve (Jones et al., 2007), in this case

IntCal04 (Reimer et al., 2004).

Peruvian ∆R was calculated by using the formula (Jones et al., 2007):

)()()( tMtMtR calibm −=∆

where Mcalib(t) is obtained from the Marine04 calibration curve (Hughen et al., 2004).

Weighted averages for R’(t) and ∆R(t) were calculated following the method of Long and

Rippeteau (1974). In this method, (used with data series known to be of the same age such as

ours), radiocarbon measurements with higher analytical precision (smaller σ) are given more

weight within the calculation of the average. Thus, the weighted average improves the analytical

precision of the resultant R’(t) and ∆R(t) means.

2.4. Results

All calculated shell R’(t) and ∆R (t) data are presented in table 2. Each shell’s weighted

average for R’(t) and ∆R (t) is included. Stable oxygen and carbon isotope data profiles are

plotted in figures 4 and 5 in comparison to ∆R.

2.4.1. 368497 D. obesulus collected in Salaverry -8º14’S- 1926 (Smithsonian)

The weighted average for ∆R in this shell is 136 ±18 years (table 2). The maximum ∆R is

237±60 yrs and the minimum is 46±75 yrs, and the range is 191 years (see figures 4a and 6).

δ18O oscillates along the shell’s ontogeny with a range of 2.6‰ (see figure 4a). δ18O oscillations

do not parallel ontogenic changes in ∆R.

20

Lab

#

Sample

#

Lat

Date

mm

from

umbo

δδδδ13C

(‰)

14C

content

(pMC)

14C Age

(BP)

R’(t)

yrs a

∆∆∆∆R(t)

yrsb

AA57252 220557A-01 13º52'S

20.7 0.4 93.35±0.47 553±40 354±41 84±47 AA57253 220557A-02 1948 20.4 0.4 93.22±0.77 564±65 365±66 95±69 AA57254 220557A-03 20.0 0.4 92.67±0.38 612±32 413±33 143±40 AA57255 220557A-04 19.3 0.4 93.18±0.38 567±32 368±33 98±40 AA57256 220557A-05 18.8 0.4 93.58±0.52 533±44 334±45 64±50 AA57257 220557A-06 18.2 0.4 93.42±0.46 547±38 348±39 78±45 AA57258 220557A-07 18.0 0.4 93.81±0.64 514±54 315±55 45±59 AA57259 220557A-08 16.7 0.4 93.84±0.50 511±42 312±43 42±48 AA57260 220557A-09 15.9 0.4 94.22±0.47 479±39 280±40 10±46 AA57261 220557A-10 14.9 0.4 94.20±0.45 482±37 283±38 13±44 AA57262 220557A-11 13.8 0.4 93.47±0.34 542±29 343±30 73±38 AA57263 220557A-12 12.6 0.4 92.64±0.63 614±53 415±54 145±58 AA57264 220557A-13 11.0 0.4 92.49±0.37 627±31 428±32 158±39 AA57265 220557A-14 9.6 0.4 93.96±0.50 500±42 301±43 31±48 AA57266 220557A-15 8.4 0.4 92.60±0.69 617±59 417±60 148±64 AA57267 220557A-16 6.8 0.4 93.42±0.49 547±41 348±42 78±48 AA57268 220557A-17 4.8 0.4 93.08±0.44 576±37 377±38 107±44 AA57269 220557A-18 2.9 0.4 92.55±0.36 622±30 423±31 153±38 AA57270 220557A-19 0.5 0.4 92.98±0.35 585±29 386±30 116±38

weighted average 362±9 91±10

AA72855 220557B-01 13º52’S

0.0 0.8 94.80±0.97 422±82 223±82 -47±85 AA72850 220557B-02 1948 3.0 0.6 92.50±0.51 621±44 422±42 152±50 AA72857 220557B-03 4.4 0.7 93.30±0.64 662±55 463±56 193±60 AA72853 220557B-04 6.0 0.9 93.80±0.43 511±36 312±37 42±43 AA72856 220557B-05 8.9 1.0 93.00±0.43 583±36 384±37 114±43 AA72848 220557B-06 9.0 1.3 92.74±0.48 605±42 406±43 136±48 AA72852 220557B-07 10.2 1.3 92.00±0.65 549±55 350±56 80±60 AA72846 220557B-08 12.0 1.2 91.93±0.71 676±62 477±63 207±66 AA72849 220557B-10 13.6 1.0 90.27±0.73 822±65 623±66 353±69 AA72858 220557B-11 13.9 1.6 92.60±0.42 611±36 412±37 142±43 AA72847 220557B-13 16.0 1.0 93.45±0.48 544±41 345±42 75±48

weighted average 391±15 125±17

AA69002 368497-01 8º14'S 11.4 0.9 92.74±0.43 605±36 473±37 154±43 AA69003 368497-02 1926 10.3 0.4 93.09±0.62 575±53 443±53 124±58 AA69004 368497-03 9.2 0.3 94.00±0.83 497±71 365±71 46±75 AA69005 368497-04 8.2 0.8 92.32±0.54 642±46 510±47 191±51 AA69006 368497-05 7.3 1.0 92.99±0.61 584±53 452±53 133±58 AA69007 368497-06 5.8 0.5 93.06±0.58 578±50 446±50 127±55 AA69008 368497-07 4.7 0.4 93.16±0.80 569±69 437±69 118±73 AA69009 368497-08 3.8 0.6 92.78±0.89 602±77 470±77 151±80 AA69010 368497-09 2.5 0.6 93.72±0.41 521±34 389±35 70±41

21

AA69011 368497-10 1.3 0.9 91.80±0.65 688±55 556±55 237±60 weighted average 450±16 136±18

AA72025 424416-01 4º40'S 0.0 1.8 92.96±0.46 586±40 434±41 132±46 AA72026 424416-02 1929 2.2 1.6 93.37±0.38 551±31 399±32 97±39 AA72027 424416-03 4.2 1.5 93.37±0.38 551±31 399±32 97±39 AA72028 424416-04 5.6 1.6 93.37±0.39 551±33 399±34 97±40 AA72029 424416-05 6.9 1.5 92.73±0.37 606±32 454±33 152±39 AA72030 424416-06 7.8 1.4 94.51±0.47 454±39 302±40 0±45 AA72031 424416-07 8.3 1.6 93.16±0.37 569±31 417±32 115±39 AA72032 424416-09 10.7 1.6 93.08±0.37 576±31 424±32 122±39 AA72033 424416-10 11.2 1.8 93.07±0.37 577±31 425±32 123±39 AA72034 424416-11 11.6 1.7 93.15±0.38 570±32 418±33 116±39 AA72035 424416-12 13.0 1.5 92.98±0.39 585±33 433±34 131±40 AA72037 424416-14 14.1 1.3 92.96±0.37 586±31 434±32 132±39

Weighted average 414±10 111±12

Table 2 Radiocarbon data for P. asperrima and D. marincovichi samples, with calibrated ages, resulting marine reservoir ages, and reservoir effect correction ages with 1σ errors reported for all samples. Weighted average (Long and Rippeteau 1974) for samples in each shell are shown in bold. R(t) calculations use atmospheric radiocarbon ages from IntCal04 (Reimer et al., 2004) of 132±7 yrs for 1926, 152±7 yrs for 1929, and 199±9 yrs for 1948. ∆R calculations use mixing marine modeled layers radiocarbon ages from Marine04 (Hughen et al., 2004) of 451±23 yrs for 1926, 454±23 yrs for 1929, and 469±24 yrs for 1948.

22

2.4.2. 424416 D. obesulus collected in Puerto Pariñas -4º4’S- 1929 (Smithsonian)

The weighted average for ∆R in this shell is 111±12 yrs (table 2). The maximum ∆R is

152±39 yrs and the minimum is 0±45 yrs, and the range is 152 years (see figures 4b and 6). δ18O

range is 1.2‰ (see figure 4b). Toward the edge δ18O profile becomes more negative. However,

δ18O trend does not correspond to ontogenic ∆R changes.

2.4.3. 220557A P. asperrima collected in Paracas -13º52’S- 1948 (FMNH)

The weighted average for ∆R in this shell is 91±10 years (table 2). The maximum ∆R is

158±39 yrs and the minimum is 10±46 yrs, and its range is 148 years (figures 5a and 6). δ18O

oscillates along the shell’s ontogeny with a range of 2.1‰ (figure 5a). There is no evident

correspondence between δ18O and ∆R values along the shell’s ontogeny.

2.4.4. 220557B P. asperrima collected in Paracas -13º52’S- 1948 (FMNH)

The weighted average for ∆R in this shell is 125±17 yrs (table 2). The maximum ∆R is

353±69 yrs and the minimum is -47±85 yrs. The range within the shell is 400 years (figure 5b

and 6). δ18O changes along the shell’s ontogeny within a range of 1.4‰ (figure 5b). There is no

evident correspondence between δ18O and ∆R.

2.5. Discussion

Knowledge of shell age and growth rate improves interpretation of time-series

sclerochonological data. D. obesulus’ life span was calculated using the Von Bertalanffy growth

function (VBGF)

)1( KTeLL −−∞=

based on the Artnz et al. (1987) growth rate constant (K= 1.17 yr-1) and Talledo-Cornejo’s

(1980) maximum reported length for the species in Peru (33.2 mm). Here L is the length of the

shell at capture (25.0 mm), L∞ is the length of the shell at an infinite time or the maximum

23

a. Shell #368497 b. Shell #424416 Salaverry (8º 14' S), 10 Oct. 1926 Puerto Pariñas (4º 40' S), 1929

Figure 4 Stable isotope and radiocarbon profiles for D. obesulus shells. Black triangles represent δ18O. Stable isotope values are plotted versus VPDB in parts per mil (‰) on the right y-axis. Black diamonds represent ∆R values in years as compared to the left y-axis. δ18O has 1σ (smaller than symbols) of 0.11 based on repeated analyses of NBS-19. Error bars in black diamonds represent 1σ in years. The x-axis represents distance from umbo in mm corrected for shell curvature.

24

shell’s length recorded for species (33.2 mm), K is the growth constant, and T represents time in

years. T was adjusted until L and L∞ were within one standard deviation of each other. Based on

this iteration D. obesulus will reach a maximum length similar to the one reported by Talledo-

Cornejo (1980) in 4.6 years. Other Donax species around the world have been reported having

similar life spans for example: D. hanleyanus (Marko et al., 2009) lives for about three years, D.

serra (Laudien, 2002) lives up to five years, while D. vittatus and D. deltoides (Marko et al.,

2009; references within) live for 3.5 years. Applying the VBGF we calculated that a 25 mm long

D. obesulus specimen lived for approximately 1.2 years. Oxygen isotope profiles from the

analyzed shells (figure 4) also support that both D. obesulus specimens lived for about a year or

less.

The typical lifespan for P. asperrima has been calculated as 2.4 years in warm waters,

where a shell can reach 38 mm in seven months (Palacios-Villegas et al., 1986). Specimens used

here for analysis reached 24 mm in length, and oxygen isotope analyses (figure 5) suggested that

they lived for about one year and a half. Differences between previously reported length-age

values (Palacios-Villegas et al., 1986) and the one reported here may be explained by different

water temperature in their habitats. It is not uncommon for individuals of the same species to

grow slower in cold water areas than in warm ones (Marko et al., 2009).

These age estimates for the D. obesulus and P. asperrima shells (~1 and 1.5 years

respectively) permit assessment of sample time averaging and resolution. Sampling resolution

for ∆R can be obtained by dividing the specimen’s lifespan by the number of samples taken from

them (assuming a constant growth rate). D. obesulus shell 368497’s ten samples average ∆R in

periods of 1.2 months, and shell 424416’s twelve samples average ∆R in periods of 1 month. P.

asperrima shell 220557A’s nineteen samples average ∆R in intervals of 0.95 months, and shell

25

a. Shell #220557A b. Shell #220557B Paracas (13º 52' S), 1948 Paracas (13º 52' S), 1948 Figure 5 Stable isotope and radiocarbon profiles for P. asperrima shells. Black triangles represent δ18O. Stable isotope values are plotted versus VPDB in parts per mil (‰) on the right y-axis. Black diamonds represent ∆R values in years as compared to the left y-axis. δ18O has 1σ (smaller than symbols) of 0.11 based on repeated analyses of NBS-19. Error bars in black diamonds represent 1σ in years. The x-axis represents distance from umbo in mm corrected for shell curvature.

26

220557B’s eleven samples average ∆R in intervals of 1.6 months. Therefore, sampling resolution

ranged between ~1 and 1.6 months. The average sampling resolution for both species shells is

about 40 days. The ∆R values in these shells therefore represent a sub-seasonal scale.

Statistically significant (based on analytical precision 1σ) ∆R shifts between consecutive

samples ranged between 145 and 167 14C yrs for D. obesulus shells, while ∆R shifts for

consecutive samples in P. asperrima shells ranged between 127 and 211 14C yrs (see figures 4

and 5). ∆R ranges in D. obesulus were of 191 14C yrs for shell 368497 and of 152 14C yrs for

shell 424416, while in P. asperrima ∆R ranges were of 148 14C yrs for shell 220557A and of 400

14C yrs for shell 220557B. A box plot representation, (figure 6) shows ∆R distributions and

ranges for the four different shells. From the box plot it can be observed that ∆R ranges for D.

obesulus and one P. asperrima shell are similar, and that the ∆R range for P. asperrima 220557B

shell is twice as big as any of the others. These data suggest that ∆R signals recorded in mollusk

shells significantly change (as defined by analytical precision 1σ) along a shell’s ontogeny.

Additionally our data suggest that each individual shell records unique ∆R shifts. The shells’ ∆R

variability may be interpreted as a qualitative measure for upwelling mixing at different

locations. Thus, our molluscan data may represent the first report of sub-seasonal scale variation

and local stirring rates for marine ∆R in the southeastern Pacific.

Rossi et al. (2009) modeled and described upwelling along the Pacific coasts or Peru-

Chile, among others, as a Lagrangian system. According to their modeling different upwelling

zones along the Peruvian coast have variable intensities of water stirring. Lagrangian upwelling

systems may be divided into fast and slow mixing sub-systems depending on their water stirring

activity (Rossi et al., 2009). Filament movement for fast mixing sub-systems ranges between 40

27

Figure 6 Box plots of ∆R value distributions of the four analyzed shells. Y-axis represents ∆R in radiocarbon years. X-axis denotes shell identification codes.

28

and 90 days, while for slow mixing sub-systems movement ranges between 65 and 530 days

(Rossi et al., 2009). These movement rates, especially in fast mixing sub-systems, are similar to

our sub-seasonal molluscan ∆R variability and suggest that the rapid radiocarbon variation

measured in the shells is a product of filament movement. Thus, statistically significant ∆R

differences along bivalve shells may be the product of distinct water filaments, or small groups

of filaments time averaged together to produce the different measured profiles. This finding

opens the possibility to detect past spatial and temporal heterogeneity of different Lagrangian

upwelling systems (Rossi et al., 2009) using molluscan carbonate radiocarbon analyses.

Additionally, it suggests caution in using short-lived organisms for radiocarbon dating, as this

may introduce uncertainty greater than the overall mean inter-annual ∆R.

Andrus et al., (2005) found a correspondence between δ18O and ∆R changes in mollusk

shells collected in Peru. The correspondence between molluscan δ18O and ∆R is in agreement

with studies showing an inverse relationship between temperature and radiocarbon concentration

in upwelled water (Huyer et al., 1987; Toggweiler et al., 1991; Dickin, 2005). Nevertheless, we

found that sub-seasonal δ18O and ∆R changes are not clearly related (figures 4 and 5). This lack

of correspondence has been seen before (Jones et al. 2007, 2009). Jones et al. (2007) attributed

this lack of correspondence to low sampling resolution, or (Jones et al. 2009) upwelled water

parcels changing temperature faster (~one month to match observed values) than radiocarbon

concentration can change (~10 years atmospheric equilibration time). We refine Jones et al.

(2009) original idea suggesting that the lack of δ18O/∆R correspondence is caused by water

filament movement. Filaments may increase in temperature relatively quickly, but their

radiocarbon content will not change as rapidly, even if they travel for thousands of kilometers

(Toggweiler et al., 1991). Conversely, it may also be possible for water filaments with different

29

radiocarbon concentrations to have the similar temperatures. Consequently, water filament

temperature may rise or fall (recorded as carbonate δ18O shifts) while radiocarbon concentrations

in DIC remains comparatively stable. The lack of correspondence between δ18O and ∆R may be

common for shells growing in intense upwelling areas and may be function of stirring in the

system. Shells inhabiting areas with low intensity upwelling environments may not display this

phenomenon to the same degree.

Modern pre-bomb D. obesulus weighed ∆R averages of 136 ±18 years (368497) and 111

±12 years (424416) are statistically indistinguishable within one standard deviation. However,

modern pre-bomb P. asperrima weighed ∆R averages of 125 ±17 years (220557A) and 91 ±10

years (220557B) are statistically different at one sigma level. The small difference (7 years)

disappears when values are compared at the two sigma level. This difference between weighed

∆R averages at one sigma in P. asperrima shells is difficult to explain. It may be caused by

different factors such as sampling strategies impacting time-averaging and aliasing, filament

movement, different habitat location, dissimilar growing times, or different combinations of

those factors.

Previously reported modern pre-bomb Peruvian ∆R values are 243±49 yrs (~10ºS in

Strombus peruvianus ) and 670±44 years (~14ºS in Oliva peruviana) from Taylor and Berger

(1967) as reprocessed in Jones et al., (2007). The O. peruviana ∆R is considered as an outlier

(Owen, 2002; Jones et al., 2007). Jones et al. (2007) analyzed Argopecten purpuratus, yielding

weighted ∆R averages of 189±23 yrs (5º45’S), 165±24 yrs (8º14’S), 183±18 and 194±23 yrs

(12º24’S). Our ∆R means are younger than any other modern pre-bomb mean ∆R previously

reported for the area (Taylor and Berger, 1967; Jones et al., 2007). However, our individual

samples are within the range of previously reported intra-shell data (Jones et al., 2007) as is

30

shown in figure 7, left. These differences in mean ∆R may be in part caused by their seasonal

shell growth preferences (Jones et al., 2010). For example, Mesodesma donacium grows most

rapidly in cold water, biasing its average recorded radiocarbon signal toward older ages when

compared to year-round growing species like A. purpuratus (Jones et al., 2010). Similar

differences in seasonal growth may exist in the species described here, though there are no

published data concerning seasonal growth preferences in D. obesulus, P. asperrima, S.

peruvianus, or O. peruviana with which to compare. Latitudinal variation in upwelling does not

seem to explain these differences as similar weighted ∆R averages were measured between the

collection locations for D. obesulus and P. asperrima (figure 7, right). This was also seen in

weighted ∆R averages for A. purpuratus from northern and central Peru (Jones et al., 2007).

2.6. Conclusions

Based on our multiple 14C data obtained from D. obesulus and P. asperrima shells, we

report modern pre-bomb ∆R values of 117±9.5 and 99±9.2 yrs for northern (4º4’S to 8º14’S) and

central (13º52’S) Peru respectively. High spatial and temporal vertical mixing variability, during

finite-time periods, characterizing Peruvian upwelling (Rossi et al., 2009) is registered in high

resolution molluscan ∆R and δ18O profiles. Shells contained ∆R variations of up to 400 14C yrs,

and those changes were not necessarily paralleled by δ18O. Molluscan ∆R profile variability may

be used as a qualitative proxy for vertical mixing in an area and give insight into the intensity of

spatial and temporal heterogeneity in upwelling systems. Molluscan mean ∆R may be influenced

by species growth preferences. Different factors, or combination of factors, such as filament

movement, sampling strategies, and/or location may introduce additional variability to mean ∆R

values, even within shells of the same species. Caution should be exercised when interpreting

31

Figure 7 Molluscan intra-shell ∆R (left) and ∆R weighted average (right) at different latitudes along the Peruvian coast. ∆R from D. obesulus, A. purpuratus (from Jones et al., 2007), and P.

asperrima shells is represented by grey open diamonds, black circles, and grey open circles respectively. Vertical grey and black lines represent 1σ in for individual and weighted ∆R values in both plots.

32

radiocarbon dates from short-lived mollusks as sub-seasonal upwelling variability may yield

anomalous data when compared to longer-term mean ∆R in a variable upwelling environment.

2.7. Acknowledgements

We are grateful to the staff of Invertebrate Zoology at the National Museum of Natural

History, Smithsonian Institution, Washington DC and Florida Museum of Natural History for

loan of specimens and permission to take samples. Also, we would like to thank Joe Lambert

from the Department of Geological Sciences Stable Isotope Laboratory at The University of

Alabama and the staff of the NSF-Arizona AMS facility for their help in the stable isotope and

radiocarbon analyses. The corresponding author of this paper would like to thank Daniel

Carstensen from the Alfred Wegner Institute for Polar and Marine Research (Germany) and Juan

Tarazona from Concytec (Peru) for providing valuable references about D. obesulus shells. This

research was funded by National Science Foundation (NSF) grant ESH - OCE-0502533 PI’s

Andrus, Hodgins, and Sandweiss.

33

2.8. References

Andrus CFT, Hodgins GWL, Sandweiss HD, Crowe DE. 2005. Molluscan radiocarbon as a proxy for El Niño-related upwelling variation in Peru. Geological Society of America Special Paper. 395:13-20.

Ansel AD. 1983. The Biology of the Genus Donax, in A. McLachlan, and T. Erasmus eds. Sandy

beaches as ecosystems: The Hague. Junk Publishers. 607-635. Arntz WE, Brey T, Tarazona J, Robles A. 1987. Changes in the Structure of Shallow Sandy

Beach Community in Peru During and El Niño Event. South African Journal of Marine Sciences. 5:645-658.

Cartensen D, Soto R, Sotil G, Mendo J, Tarazona J, Laudien J. 2007. Population Dynamics and

Reproduction Biology of Donax marincovichi (Coan 1983) from “Playa Jahuay” (Peru). Congreso Latinoamericano de Ciencias del Mar XII COLACMAR.

Carstensen D, Laudien J, Leese F, Arntz W, Held C. 2009. Genetic Variability, Shell and Sperm

Morphology Suggest that the Surf Clams Donax marincovichi and D. obesulus are one species: Journal of Molluscan Studies. 75:381-390.

Coan EV.1983. The Eastern Pacific Donacidae. The Veliger 25(4): 273-298. Culleton BJ, Kennet DJ, Ingram, B.L., Erlandson JM, Southon, JR. 2006. Intrashell Radiocarbon

Variability in Marine Mollusks: Radiocarbon. 48(3):387-400. Dickin AP. 2005. Radiogenic Isotope Geology. Cambridge University Press, 508 p. Druffel ERM. 1981. Radiocarbon in annual coral rings from the eastern tropical Pacific Ocean.

Geophysical Research Letters. 8:59-63. Druffel ERM. 1982. Banded Corals: Changes in oceanic carbon-14 during the Little Ice Age.

Science. 218:13-20.

Druffel ERM. 1987. Bomb radiocarbon in the Pacific: Annual and seasonal timescale variations. Jounal of Marine Research. 45:667-698.

Druffel ERM, Griffin S. 1993. Large variations of surface ocean radiocarbon: Evidence of

circulation changes in the southwestern Pacific. Journal of Geophysical Research. 98: 20249-20269.

Druffel ERM. 1997. Geochemistry of corals: Proxies of past ocean chemistry, ocean circulation,

and climate. Proceedings of the National Academy of Sciences of the United States of America. 94:8354-8361.

34

Huyer A, Smith RL, Paluszkiewicz T. 1987. Coastal Upwelling off Peru during normal and El Niño times, 1981-1984. Journal of Geophysical Research-Oceans 92(C13):14297-14307.

Guilderson TP, Schrag DP, Kashgarian M, Southon JR. 1998. Radiocarbon variability in the

western equatorial Pacific inferred from a high-resolution coral record from Nauru Island. Journal of Geophysical Research-Oceans. 103:24641-24650.

Guilderson TP, Schrag DP, Goddard E, Kashgarian M, Wellington GM, Linsley BK. 2000.

Southwest subtropical Pacific surface water radiocarbon in a high resolution coral record. Radiocarbon. 42: 249-256.

Guilderson TP, Kashgarian M, Schrag DP. 2002. Biogeochemical proxies in scleractinian corals used to reconstruct ocean circulation, Study of Environmental Change using Isotope Techniques. I. A. E. Agency. 130-139.

Guzmán N, Saá S, Ortilieb L. 1998. Catálogo descriptivo de los molúscos litorales (Gastropoda y Pelecypoda) de la zona de Antofagasta, 23º S (Chile). Estudios Oceanológicos. 17:17-86.

Hughen KBM, Bard E, Beck JW, Bertrand CJ, Blackwell PG, Buck CE, Burr GS, Cutler KB, Damon PE, Edwards RL, Fairbanks RG, Friedrich M, Guilderson TP, Kromer B, McCormac FG, Manning S, Bronk Ramsey C, Reimer PJ, Reimer RW, Remmele S, Southon J, Stuiver M, Talamo S, Taylor FW, van der Plicht J, Weyhenmeyer CE. 2004. Marine04 marine radiocarbon age calibration, 0–26 cal kyr BP. Radiocarbon. 46:1959-1086.

Jones KB, Hodgins GWL, Dettman DL, Andrus CFT, Nelson A, Etayo-Cadavid MF. 2007.

Seasonal variation in Peruvian Marine Reservoir Age from Pre-Bomb Argopecten purpuratus Shell Carbonate. Radiocarbon 49(2): 877-888.

Jones KB, Hodgins, GWL, Andrus, CFT, Etayo-Cadavid, MF. 2010. Modeling Molluscan Marine Reservoir Ages In A Variable-Upwelling Environment. Palaios. 25:126-131.

Keen M. 1958. Sea Shells of Tropical West America: Marine mollusks from Baja California to

Peru. Stanford University Press. 1064p.

Laudien J. 2002. Population dynamics and ecology of the surf clam Donax serra (Bivalvia, Donacidae) inhabiting beaches of the Benguela upwelling system. Fachbereich 2 (Biologie/Chemie). Bremen. Universitat Bremen. 112p.

Long A, Rippeteau B. 1974. Testing contemporaneity and averaging radiocarbon dates.

American Antiquity. 39:3509-3520. Lorrain A, Paulet YM, Chauvaud L, Dunbar R, Mucciarone D, Fontugne M. 2004. δ13C variation

in scallop shells: Increasing metabolic carbon contribution with body size? Geochimica et Cosmochimica Acta. 68(17):11.

35

McConnaughey TA, Gillikin DP. 2008. Carbon isotopes in mollusk shell carbonates. Geo-Marine Letters 28:287-299.

McCrea JM. 1950. On the Isotopic Chemistry of Carbonates and a Paleotemperature Scale. The Journal of Chemical Physics. 18(6):849-857.

Marko H, Carstensen D, Fischer S, Laudien J, Penchaszadeh PE, Arntz W.E. 2009.Population

structure, growth, and production of the wedge clam Donax hanleyanus (Bivalvia: Donacidae) from northern Argentinean beaches (Report). Journal of Shellfish Research. 28(3):511-527.

Moore MD, Schrag DP, Kashgarian M. 1997. Coral radiocarbon constraints on the source of the

Indonesian throughflow. Journal of Geophysical Research-Oceans. 102:12359-12365. Ortilieb L, Macharé J. 1993. Former El Niño events: records from western South America.

Global and Planetary Change. 7:181-202.

Owen BD. 2002. Marine carbon reservoir age estimates for the far south coast of Peru. Radiocarbon. 44:701-708.

Paredes C, Cardozo F. 2001. El Género Donax en la costa peruana (Bivalvia: Tellinoidea):

Revista Peruana de Biología. 8:1-12. Poulain C, Lorrain A, Gillikin DP, Dehairs F, Robert R, Paulet Y-M. 2010. Experimental shift of

diet and DIC stable carbon isotopes: Influence on shell δ13C values in the Manila clam Ruditapes philippinarum. Chemical Geology. 272:75-82.

Quinn HW, Neal VT, Antunez de Mayolo SE. 1987. El Niño Occurrences Over the Past Four

and a Half Centuries. Journal of Geophysical Research. 92(13):14449-14461.

Shadden SC, Lekien F, Marsden JE. 2005. Definition and properties of Lagrangian coherent structures from finite-time Lyapunov exponents in two-dimensional aperiodic flows. Physica D. 212:271-304.

Talledo-Cornejo CR. 1980. Algunas consideraciones Bioecológicas de Donax peruvianus, Deshayes 1855. Universidad Nacional Pedro Ruiz Gallo. Lambayeque. 54 p.

Taylor RE, Berger R. 1967. Radiocarbon content of Marine Shells from the Pacific Coast of Central and South America. Science 158:1180-1182.

Reimer PJ, Baillie M, Bard E, Bayliss A, Beck JW, Bertrand CJH, Blackwell PG, Buck CE, Burr

GS, Cutler KB, Damon PE, Edwards RL, Fairbanks RG, Friedrich M, Guilderson TP, Hogg AG, Hughen KA, Kromer B, McCormac G, Manning S, Bronk Ramsey C, Reimer RW, Remmele S, Southon JR, Stuiver M, Talamo S, Taylor FW, van der Plicht J, Weyhenmeyer CE. 2004. IntCal04 terrestrial radiocarbon age calibration, 0–26 cal kyr BP. Radiocarbon 46(4):1029-1058.

36

Rossi V, López C, Hernández-García E, Sudre J, Garçon V, Morel Y. 2009. Surface mixing and

biological activity in the four Eastern Boundary Upwelling Systems: Nonlinear Processes in Geophysics. 16:557-568.

Slota PJ, Jull AJT, Linick TW, Toolin LJ. 1987. Preparation of small samples for 14C accelerator targets by catalytic reduction of CO. Radiocarbon. 29(2):303-306.

Stuiver MP, Gordon W, Braziunas TF. 1986. Radiocarbon age calibration of marine samples

back to 9000 cal yr BP. Radiocarbon. 28(2b):980-1021. Stuiver M, Braziunas TF. 1993. Modeling Atmospheric 14C influences and 14C Ages of Marine

Samples to 10,000 BC. Radiocarbon 35(1): 137-189.

Toggweiler JR, Dixon K, Broecker WS. 1991. The Peru Upwelling and the Ventilation of the South-Pacific Thermocline. Journal of Geophysical Research-Oceans. 96:20467-20497.

Vogel JS, Southon JR, Nelson DE, Brown TA. 1984. Performance of catalytically condensed

carbon for use in accelerator mass spectrometry: Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms. 5:289-293.

37

2.9. Appendix 1

Supplementary figure 1 XRD pattern identification of Donax obesulus shell carbonate as aragonite (upper), compare to ICDD 00-41-1475 aragonite (CaCO3) pattern (bottom). X-axis is in 2 theta (θ) values and Y-axis is in intensity (counts per second).

38

Supplementary figure 2 XRD pattern identification of Protothaca asperrima shell carbonate as aragonite (upper), compare to ICDD 00-41-1475 aragonite (CaCO3) pattern (bottom). X-axis is in 2 theta (θ) values and Y-axis is in intensity (counts per second).

39

Sample δδδδ13

C (‰ VPBD) δδδδ18

O (‰ VPBD) Distance from umbo (mm)

368497-001 0.9 0.3 6.2 368497-002 0.3 -1.2 6.0 368497-003 1.1 0.1 5.9 368497-004 1.3 0.6 5.7 368497-005 1.2 0.3 5.6 368497-006 0.9 -0.5 5.4 368497-007 0.7 -0.3 5.3 368497-008 1.0 -0.4 5.1 368497-009 0.8 -0.6 5.0 368497-010 0.5 -0.9 4.8 368497-011 0.8 0.0 4.7 368497-012 0.3 -1.0 4.5 368497-013 0.6 -0.8 4.4 368497-014 0.9 -0.3 4.2 368497-015 0.6 -0.8 4.1 368497-016 0.7 -0.5 3.9 368497-017 0.6 -0.4 3.8 368497-018 1.0 0.0 3.6 368497-019 0.6 -0.8 3.5 368497-020 0.7 -2.0 3.3 368497-021 0.4 -0.9 3.2 368497-022 0.7 -0.7 3.0 368497-023 0.9 -0.6 2.9 368497-024 0.6 -0.8 2.7 368497-025 0.7 -1.1 2.6 368497-026 1.2 0.5 2.4 368497-027 0.8 -0.4 2.3 368497-028 0.9 0.0 2.1 368497-029 0.4 -1.2 2.0 368497-030 0.7 -1.7 1.4 368497-031 0.9 -0.9 1.2 368497-032 1.0 -1.0 1.1 368497-033 1.3 -0.2 0.9 368497-034 0.6 -0.9 0.8 368497-035 0.6 -0.8 0.6 368497-036 0.4 -0.6 0.5 368497-037 1.1 -0.3 0.3 368497-038 0.2 -1.2 0.1 368497-039 1.5 -0.8 0.0

Supplementary table 1 Stable carbon and oxygen data for D. obesulus shell (368497) collected in Salaverry (8º 14' S) during 1926. Stable isotopes are reported in parts per mil (‰) VPDB. Distance from umbo in mm uncorrected for shell curvature.

40

Sample δδδδ13

C (‰ VPBD) δδδδ18

O (‰ VPBD) Distance umbo (mm)

424416-001 0.8 -0.9 12.0 424416-002 0.8 -0.5 11.5 424416-003 0.9 -0.3 11.0 424416-004 0.9 0.1 10.2 424416-005 1.0 -0.1 9.8 424416-006 1.0 -0.4 9.5 424416-007 1.1 0.1 9.2 424416-008 1.3 0.2 8.8 424416-009 1.0 0.1 8.2 424416-010 0.8 -0.3 7.4 424416-011 0.7 0.0 7.0 424416-012 1.0 0.2 6.5 424416-013 1.0 0.1 5.9 424416-014 1.0 0.1 5.4 424416-015 1.0 0.3 5.0 424416-016 0.9 0.1 4.5 424416-017 1.1 0.3 4.1 424416-018 1.0 0.2 3.5 424416-019 1.1 0.0 3.0 424416-020 0.9 0.1 2.5 424416-021 0.8 0.1 2.1 424416-022 0.9 0.2 1.7 424416-024 0.9 0.2 0.6 424416-025 0.8 0.1 0.0

Supplementary table 2 Stable carbon and oxygen data for D. obesulus shell (424416) collected in Salaverry (4º 40' S) during 1929. Stable isotopes are reported in parts per mil (‰) VPDB. Distance from umbo in mm uncorrected for shell curvature.

41

Sample δδδδ13

C (‰ VPBD) δδδδ18

O (‰ VPBD) Distance umbo (mm)

220557A-001 1.0 0.0 12.0 220557A-002 1.1 0.1 11.9 220557A-003 0.8 0.2 11.3 220557A-004 0.8 0.0 10.8 220557A-005 1.3 1.0 10.6 220557A-006 0.5 0.2 10.2 220557A-007 0.4 0.3 9.4 220557A-008 0.5 -0.2 9.1 220557A-009 0.3 0.4 8.7 220557A-010 0.1 0.1 8.3 220557A-011 0.2 0.2 8.2 220557A-012 0.3 0.3 8.1 220557A-013 0.0 0.4 7.8 220557A-014 0.0 0.2 7.4 220557A-016 0.2 -0.3 6.9 220557A-017 0.2 -0.5 6.5 220557A-018 0.6 -0.4 6.3 220557A-019 0.6 -0.4 5.6 220557A-020 0.6 -0.5 5.5 220557A-021 0.7 -0.7 5.2 220557A-022 0.9 -0.7 5.0 220557A-023 0.6 -0.9 4.8 220557A-024 0.5 -0.5 4.5 220557A-025 0.7 -1.1 4.1 220557A-026 0.8 -1.0 3.9 220557A-027 0.9 -0.9 3.2 220557A-028 1.1 -0.9 3.2 220557A-029 0.7 -0.9 2.8 220557A-030 0.7 -0.3 2.7 220557A-031 0.5 -0.7 2.4 220557A-034 0.6 -0.7 1.8 220557A-035 0.4 -1.0 1.3 220557A-036 0.4 -0.8 1.2 220557A-037 1.2 -0.7 1.0 220557A-038 1.3 -0.4 0.8 220557A-039 1.4 -0.4 0.5 220557A-040 1.2 -0.8 0.4 220557A-041 1.1 -1.1 0.1 220557A-042 1.3 -1.1 0.0

Supplementary table 3 Stable carbon and oxygen data for P. asperrima shell (220557A) collected in Salaverry (13º 52' S) during 1948. Stable isotopes are reported in parts per mil (‰) VPDB. Distance from umbo in mm uncorrected for shell curvature.

42

Sample δδδδ13

C (‰ VPBD) δδδδ18

O (‰ VPBD) Distance umbo (mm)

220557B-001 0.6 -0.3 17.6 220557B-002 0.5 -0.4 16.9 220557B-003 0.3 0.0 16.2 220557B-004 0.7 -0.1 15.5 220557B-005 0.8 -0.4 14.7 220557B-006 0.2 -0.2 13.9 220557B-007 0.5 0.0 13.3 220557B-008 1.0 0.1 12.6 220557B-009 0.2 -0.2 12.1 220557B-010 1.0 -0.1 11.4 220557B-011 0.3 0.2 10.6 220557B-012 0.5 0.5 10.0 220557B-013 0.5 0.2 9.0 220557B-014 0.1 0.0 8.4 220557B-015 0.1 0.2 7.7 220557B-016 -0.1 -0.3 7.1 220557B-017 -0.4 -0.3 6.3 220557B-018 0.2 -0.2 5.4 220557B-019 -0.5 -0.8 4.5 220557B-020 0.5 -0.7 3.7 220557B-021 0.2 -0.9 3.0 220557B-022 0.4 -0.9 2.2 220557B-023 0.7 -0.6 1.6 220557B-024 0.3 -0.9 0.8 220557B-025 0.7 -0.7 0.0

Supplementary table 4 Stable carbon and oxygen data for P. asperrima shell (220557B) collected in Salaverry (13º 52' S) during 1948. Stable isotopes are reported in parts per mil (‰) VPDB. Distance from umbo in mm uncorrected for shell curvature.

43

3. EL NIÑO INDUCED BIOMINERALIZAION CHANGES: REPERCUSSIONS FOR MOLLUSCAN PROXIES 3.1. Abstract

A Trachycardium procerum valve from a set of samples surviving the1982-83 El Niño

was analyzed to study trace elements potential as marine environmental proxies. High resolution

Ba/Ca, Sr/Ca, and Mg/Ca ontogenic profiles were obtained. Elemental data were compared to

previously generated ontogenic ∆14C, δ13C and δ18O profiles. Despite Sr/Ca and Mg/Ca

correspondence with ∆14C and δ18O profiles, SEM and Raman analyses revealed marked

biomineralization differences in the shell prior to and after the onset of the El Niño event. Thus

elemental profiles may be partially a consequence of dual biomineralization processes and may

not reflect environmental signals. Shell biomineralization should be considered whenever

elements are used as environmental proxies in order to avoid erroneous conclusions.

3.2. Introduction

Environmental variation associated with the 1982-83 El Niño triggered biomineralization

changes in Trachycardium procerum shells in coastal Peru. Bivalve shells like these are

increasingly used as sources of geochemical data in paleoclimate studies to reconstruct

environmental conditions (Gillikin, 2005; Freitas et al., 2005). Such molluscan proxies are

interpreted assuming stable biomineralization processes during the lifetime of an organism

(Freitas et al., 2009). However, biomineralization changes in collected T. procerum shells

44

influence trace elemental and isotopic chemical data and must be considered when interpreting

molluscan-derived geochemical records for paleoenvironmental information.

El Niño events in coastal Peru subject marine organisms to significant and sudden

changes in their living environments. During El Niño, changes in the southeastern trade winds

(Philander, 1985) trigger a massive west-east warm water displacement, deepening the eastern

Pacific thermocline and changing upwelling conditions offshore Peru from cold nutrient-rich

deep water to warm nutrient-depleted surface water (Wyrtki, 1985; Huyer et al., 1987). Rainfall

greatly increases in the commonly hyperarid Peruvian coastal region triggering destructive

floods (Quinn et al., 1987). These events disrupt fisheries and bivalve populations in the area

causing migration or death of many species (Quinn et al., 1987; Rollins et al., 1987). T.

procerum is one of the comparatively few mollusc species that continue to grow during these

changes.

3.3. Species Description and Collection Site

The infaunal T. procerum is a large, up to 10 cm long, subtidal cardioidean bivalve with a

ribbed aragonite shell (Olson, 1961; Andrus et al., 2005) (figure 8). Its shell is formed by

crossed-lamellar microstructures common to all cardioideans (Schneider and Carter, 2001). T.

procerum is found in the Pacific from Mexico to Peru (Andrus et al., 2005), with the Peruvian

coast as the coldest part of its range. This species lives in littoral and embayed sandy substrate

environments (Olsson, 1961). The temperature distributions of its range suggest that T. procerum

may grow better in warm waters, although it is capable of living in cold waters. Samples of this

species were collected after the 1982-83 El Niño along the Peruvian coast from Tumbes to

Paracas (Rollins et al., 1986, 1987) (figure 9). This shell collection has been analyzed

45

Figure 8 Images of T. procerum shells. Scale represents 4 cm and white arrow indicates the location of the scar associated to El Niño onset.

46

extensively with research beginning by the study of macroscopically observable growth patterns

variation generated during El Niño (Rollins et al., 1986, 1987).

Studies were expanded then to include sequential analysis of radiocarbon, stable carbon and

oxygen isotopes (Andrus et al., 2005). We analyzed the microstructure and geochemistry of one

shell (2TP4-2) (Andrus et al., 2005) that contains the same macroscopic growth patterns present

in the overall collection.

3.4. Previous Studies

Previous studies revealed that physiological stress associated with the 1982-1983 El Niño

sea surface temperature (SST) anomaly affected the way T. procerum forms its shell (Rollins et

al., 1986). Optical microscopy showed a transgressive crossed-lamellar development in the part

of the shells precipitated during El Niño (Rollins et al., 1987). This anomalous crossed-lamellar

development caused a change in the angle of inclination of the valve surface prior to and after

the onset of El Niño (~35º to ~10º respectively) (Rollins et al., 1987). This angle difference is

macroscopically observable in the shell as a scar (figure 8). High resolution radiocarbon and

stable isotope ontogenic analyses in shell 2TP4-2 showed significant variation in ∆14C and δ18O

(figure 10) prior to and after the onset of El Niño (Andrus et al., 2005), meanwhile δ13C did not

show significant differences (Andrus et al., 2005) (figure 10). ∆14C enrichment after the onset of

El Niño (figure 10) was related to higher radiocarbon content in surface waters displacing deep

water upwelling, while δ18O depletion (figure 10) during the event was related to water’s higher

SST. Thus, combined ∆14C and δ18O data were suggested as El Niño proxy indicators.

47

Figure 9 Location of T. procerum shell collection marked by red stars. Los Chimus is the area where shell 2TP4-2 was collected (Rollins et al., 1986).

48

Figure 10 Trace element, stable isotope (δ18O and δ13C in ‰ versus VPDB) and radiocarbon (versus pMC) data in profiles from the umbo toward the edge of the shell. Vertical dashed line shows the location of the scar associated with the onset of El Niño event.

49

3.5. Results

Our scanning electron microscopy (SEM) and Raman spectroscopy (RS) data show that

shell microstructure and biomineralization markedly differ prior to and after El Niño onset for T.

procerum shells. SEM observations reveal that prior to El Niño fine crossed-lamellar

microstructures form three layers (figure 11) with evident growth lines. Detailed observations by

backscatter electron microscopy (BSE) reveal that fine crossed-lamellar microstructures, dark

and light, are made of a mixture of aragonite and organic matter. Dark microstructures have a

sheet-like shape while light microstructures are composed of well defined nacre tablets. After El

Niño onset, fine crossed-lamellar microstructures are replaced by coarse ones with a transition

from three to only two discernible shell layers (figure 11). Growth lines disappear completely

and crossed-lamellar microstructures appear transgressive towards the shell surface (Rollins et

al., 1987). Coarse crossed-lamellar microstructures are mainly made of aragonite with a

significant reduction of organic components. Dark microstructures have a “flaky” shape while

light microstructures are composed of irregular aragonite “spears”. RS analyses along the shell’s

ontogeny reveals organic content differences prior and after the onset of El Niño (figure 12).

Data shows that prior to El Niño, the RS aragonite peak at 1085 cm-1(A) is accompanied by a

broad organic peak at 1140 cm-1 (B)(Addadi et al., 2003). After El Niño onset, peak B

disappears, revealing a more pure aragonite phase. A 41% reduction inorganic matter is

documented after the onset of the El Niño, as compared to shell grown earlier in ontogeny.

High resolution Ba/Ca, Sr/Ca, and Mg/Ca profiles were generated along the shell to test

their potential utility as proxies for upwelling and other environmental changes associated with

El Niño (figure 10). Ba2+, Sr2+, and Mg2+ were chosen because they have been previously

50

Figure 11 SEM images of T. procerum shell in longitudinal section showing shell regions precipitated before El Niño ( top left), the scar associated with El Niño onset (top center), and shell precipitated during El Niño (top right). BSE images showing detailed crossed lamellar structures prior (bottom left) and after (bottom right) El Niño.

51

Figure 12 Raman spectra analyses along T. procerum shell ontogeny. Shell precipitated before El Niño showing a typical aragonite peak (A) accompanied by a peak revealing an organic phase (B). Raman data analyses in the part of the shell precipitated during El Niño shows the disappearance of peak B indicating a reduction in organic matter content (bottom graph).

52

assessed as environmental proxies in mollusc shells (Vander Putten et al., 2000; Gillikin et al

2006; Freitas et al., 2006). We used the Mann-Whitney similarity test (Hammer et al., 2001) with

a rejection level of 95% to detect different elemental means prior to and after the onset of El

Niño within profiles. Ba/Ca mean values prior (0.28 mmol/mol) and after (0.19 mmol/mol) El

Niño are indistinguishable (p=0.212, p>0.05) as well as Sr/Ca mean values (p=0.195, p>0.05),

despite a marked peak after El Niño. However, Mg/Ca mean values prior (78 mmol/mol) and

after (145 mmol/mol) El Niño onset are significantly different (p=0.001, p<0.05) (figure 10).

Sr/Ca and Mg/Ca profiles superficially seem promising as proxies for SST changes due to their

variation linked to El Niño. Since Ba/Ca is not changing along the shell it appears to be a less

useful proxy for El Niño-related events.

3.6. Discussion

The current biomineralization paradigm (Weiner, 2008) may help to explain why these

elemental profiles may not be simply reflecting environmental conditions after all. This

paradigm states that many organisms, such as mollusks (Addadi et al., 2006), form their

skeletons by precipitating crystals not from saturated solutions but from highly disordered

colloidal phases (Weiner, 2008). The colloidal phase from which mollusc shells are formed is

known as amorphous calcium carbonate (ACC) (Addadi et al., 2003). Commonly, ACC

precipitates into aragonite by water expulsion and the addition of proteins and double-charged

ions (e.g. Mg+2 and Sr+2) (Addadi et al., 2006). Formation of well-defined aragonite

biostructures, such as nacre tablets, is achieved by sodium addition into aragonite (Pokroy et al.,

2004). In the absence of protein, aragonite can be precipitated by incorporation of double charge

ions such as Mg+2 into ACC (Addadi et al., 2003; Soldati et al., 2008). Thus, molluscs may be

able to precipitate their aragonite shells by two different mechanisms: 1) addition of both

53

proteins and doubled charged ions into ACC; 2) doubly charged ions without the addition of

protein into ACC.

T. procerum shells likely used these different biomineralization mechanisms for

precipitating aragonite before and during El Niño. The shell’s dual-biomineralization may

partially explain its elemental profiles. However, molluscan trace element variations have been

previously attributed to kinetic effects (Gillikin et al., 2006; Freitas et al., 2006), calcification

rates (Lorrain et al., 2005; Carré et al., 2006), and metabolic effects (Carré et al., 2006). We can

not rule out those factors contribution to elemental variability in mollusk shells. Nevertheless,

based on our observations in T. procerum we present a new factor affecting trace element

incorporation into shells, biomineralization. If biomineralization change is considered the only

factor affecting trace element incorporation into T. procerum shell, observed variation can be

explained as follows. Prior to El Niño onset, Sr+2 may have been actively involved in aragonite

precipitation as the main double-charged ion associated to proteins (organic matter) for ACC

stabilization (Addadi et al., 2003) (figures 10 and 12). After El Niño, Sr+2 incorporation into

aragonite may have changed from the lattice to crystalline faces by sorption (Menadakis et al.,

2009). Constant Sr+2 concentrations are expected for aragonite (Pokroy et al., 2004). Meanwhile,

the Mg/Ca profile prior to El Niño suggests that relatively low quantities of Mg+2 may have been

incorporated into aragonite associated with proteins (Addadi et al., 2003, 2006) (figures 10 and

12). After El Niño onset, a stressed shell perhaps adapted to reduced protein availability by

increasing Mg+2 incorporation into ACC in order to precipitate aragonite rapidly (Nebel and

Epple, 2008) (figures 10 and 12). RS data and SEM images (figures 11 and 12) confirm organic

matter reduction, including proteins, during El Niño event. Rapid aragonite precipitation may be

54

responsible for crossed-lamellar microstructures thickening and the disappearance growth line in

the shell (figure 10).

The dual-biomineralization processes in T. procerum calls into question the potential

application of Sr/Ca and Mg/Ca profiles as SST proxies. Even more, the Sr/Ca and Mg/Ca

increase during El Niño is an anomalous environmental response considering how surface

seawater contains less of those elements than deeper upwelled water (Bernat et al., 1972; de

Villiers and Nelson, 1999). These dual-biomineralization mechanisms may also affect molluscan

carbonate δ13C and δ18O signals (McConnaughey and Gillikin, 2008; Cusack et al., 2008). If

different biomineralization mechanisms involve dissimilar respiration rates, shell δ13C likely

reflect kinetic effects in addition to water dissolved inorganic carbon (DIC) (McConnaughey and

Gillikin, 2008). The δ18O signal in molluscan aragonite is mainly controlled by ambient δ18Owater

and temperature (Lécuyer et al., 2004). Nevertheless, it has been observed in other species that

aragonite with different crystal habits may introduce δ18O variability up to 0.4‰ (Cusack et al.,

2008). Radiocarbon data in molluscs is less likely to be affected by biomineralization changes

due to its cosmogenic origin (Dickin, 2005) and the δ13C corrections applied during analysis

(Donahue et al., 1990).

3.7. Conclusions

Our findings about variations in mollusc biomineralization linked to El Niño suggest the

need for coupled structural and chemical analyses in environmental proxy studies. If different

biomineralization processes are found to be occurring in a shell, environmental trace elements

concentrations and stable isotope variations should be interpreted with caution. This is especially

true of research focusing on extreme climatic events that may cause organisms to grow in an

anomalous manner. Knowledge of shell biomineralization processes helps to improve trace

55

element proxy interpretation and shell biomineralization changes themselves may be potentially

used as an environmental proxy.

3.8. Methodology

3.8.1. Samples

Shells of Trachycardium procerum were collected alive in Peru in 1984 after the El Niño

1982-1983 event (see figure 9) (Rodbell et al., 1986).

3.8.2. Shell Microstructure

Longitudinal shell sections were polished with a diamond paste, subsequently etched with

10% HCl for 2 minutes, and finally gold coated prior to analysis using a JEOL-7000 scanning

electron microscope in the Center for Analytical Facilities at The University of Alabama.

3.8.3. Raman Spectroscopy

Raman spectral analyses (see Supplementary table 5a-h) were carried out in longitudinal

shell sections using a Jobin–Yvon HR800UV Confocal Raman Microscope in the Center for

Materials for Information Technology of the Department of Chemistry at The University of

Alabama. A laser argon ion source (Ar+) with an excitation line of 488.01 nm (blue light)

coupled with an Olympus Microscope were used for the analyses. Raman data was detected by a

Peltier-cooled CCD detector using 600 grooves/mm holographic grating monochrometer.

3.8.4. Trace element chemistry

Samples for elemental analysis were milled from umbo to edge shell regions using a hand

drill with a carbide bit (80 µm diameter) following a previously established procedure (Andrus et

al., 2005). Milled powder was homogenized and split (~0.5 mg each one) to create original and

replicate data. Samples were dissolved in 50 ml polypropylene bottles containing 10 ml of 10 %

Optimatm HNO3 for trace element analyses (Patterson III et al., 1998). Samples were analyzed to

56

detect concentrations of Mg, Sr, Ba, Pb, Cd, Ni, and Mn using an ELAN 6000 ICP-MS. From the

analyzed elements only Mg, Sr, and Ba were above ICP-MS detection limits. Analytical

precision in RSD for these elements was 4.0% for Mg, 6% for Sr, and 2.6% Ba using CPI

International NIST traceable standard. Calcium samples were analyzed via Optima 3000DV

Inductively ICP-OES. Analytical precision for Ca was 0.9% in RSD using CPI International

NIST traceable standard. Results are reported as element/Ca ratios (See supplementary table 6 in

supplement) with and average Ca of 38 wt%.

3.9. Acknowledgements

The authors would like to thank Sidhartha Bhattacharyya, Ghanashyam Neupane, and

Betsy Graham from the Department of Geological Sciences of the University of Alabama for

their valuable help with trace elements analysis, Brian Flowers from the Center for Materials for

Information Technology (MINT) of The University of Alabama for helping with the Raman

spectra analysis, and Rich Martens, Johnny Goodwin and Rob Holler from the Central Analytical

Facility (CAF) at The University of Alabama for assisting with the SEM. CAF National Science

Foundation (NSF) DMR-0321180 supported the SEM work. This research was funded in part by

National Science Foundation grant ESH - OCE-0502533 PI’s Andrus, Hodgins, and Sandweiss.

57

3.8. References

Addadi L, Raz S, Weiner S. 2003. Taking advantage of Disorder: Amorphous Calcium

Carbonate and Its Role in Biomineralization. Advanced Materials. 15:959-970. Addadi L, Joester D, Nudelman F, Weiner S. 2006. Mollusc Shell Formation: A Source of New

Concepts for Understanding Biomineralization Processes. Chemistry a European Journal. 2:980-987.

Andrus CFT, Hodgins GWL, Sandweiss HD, Crowe DE. 2005. Molluscan radiocarbon as a

proxy for El Niño-related upwelling variation in Peru: Geological Society of America Special Paper 395:13-20.

Bernat M, Church T, Allegre CJ. 1972. Barium and Strontium Concentrations in Pacific and

Mediterranean Sea Water Profiles by Direct Isotope Dilution Mass Spectrometry. Earth and Planetary Science Letters. 16:75-80.

Carré M, Bentaleb I, Bruguier O, Ordinola E, Barret NT, Fontugne M. 2006. Calcification rate

influence on trace element concentrations in aragonitic bivalve shells: Evidences and mechanisms. Geochimica et Cosmochimica Acta. 79:4906-4920.

Cusack M, Parkinson D, Freer A, Perez-Huerta A, Fallick AE, Curry GB. 2008. Oxygen isotope

composition in Modiolus modiolus aragonite in the context of biological and crystallographic control. Mineralogical Magazine.72:569-577.

de Villiers S, Nelson BK. 1999. Detection of Low-Temperature Hydrothermal Fluxes by

Seawater Mg and Ca Anomalies. Science. 285:721-723. Dickin AP. 2005. Radiogenic Isotope Geology, Cambridge University Press. 508 p. Donahue DJ, Linick TW, Jull AJT. 1990. Isotope-ratio and Background Corrections for

Accelerator Mass Spectrometry Radiocarbon Measurements. Radiocarbon. 32:135-142. Freitas PS, Clarke LJ, Kennedy H, Richardson CA, Abrantes F. 2005. Mg/Ca, Sr/Ca, and stable-

isotope (δ18O and δ13C) ratio profiles from the fan mussel Pinna nobilis: Seasonal records and temperature relationships: Geochemistry Geophysics Geosystems. 6:1-16.

Freitas PS, Clarke LJ, Kennedy H, Richardson CA, Abrantes F. 2006. Environmental and

biological controls on elemental (Mg/Ca, Sr/Ca and Mn/Ca) ratios in shells of the king scallop Pecten maximus. Geochimica et Cosmochimica Acta 70:5119-5133.

Freitas PS, Clarke LJ, Kennedy H, Richardson CA. 2009. Inter- and intra-specimen variability

masks reliable temperature control on shell Mg/Ca ratios in laboratory- and field-cultured Mytilus edulis and Pecten maximus (bivalvia). Biogeosciences Discussions. 6:1267-1316.

58

Gillikin DP. 2005. Geochemistry of Marine Bivalve Shells: the potential for paleoenvironmental reconstruction. Vrije Universiteit Brussel. Brussels. 267 p.

Gillikin DP, Deharis F, Lorrain A, Steenmans D, Baeyens W, and André L. 2006. Barium uptake

into the shells of the common mussel (Mytilus edulis) and the potential for estuarine paleo-chemistry reconstruction. Geochimica et Cosmochimica Acta. 70:395-407.

Hammer Ø, Harper DAT, Ryan PD. 2001. PAST: Paleontological Statistics Software Package for Education and Data Analysis. Palaeontologia Electronica. 4(1):1-9. http://palaeo-electronica.org/2001_1/past/issue1_01.htm

Huyer A, Smith RL, Paluszkiewicz T. 1987. Coastal Upwelling off Peru during normal and El

Niño times, 1981-1984 Journal of Geophysical Research Oceans. 92:14297-14307. Lécuyer C, Reynard B, Martineau F. 2004. Stable isotope fractionation between mollusc shells

and marine waters from Martinique Island. Chemical Geology. 213:293-305. Lorrain A, Gillikin DP, Paulet Y-M, Chauvaud L, Le Mecier A, Navez J, André L. 2005. Strong

kinetic effects on Sr/Ca ratios in the calcitic bivalve Pecten maximus. Geology. 33:965-968.

Philander SGH. 1985. El Niño and La Niña. Journal of Atmospheric Sciences. 42:2652-2662. Menadakis M, Maroulis G, Koutsoukos. 2009. Incorporation of Mg2+, Sr2+, Ba2+ and Zn2+ into

aragonite and comparison with calcite. Journal of Mathematical Chemistry. 46:484-491. McConnaughey TA, Gillikin DP. 2008. Carbon isotopes in mollusc shell carbonates. Geo-

Marine Letters, 28:287-289. Nebel H, Epple M. 2008. Continuous Preparation of Calcite, Aragonite and Vaterite, and of

Magnesium-Substituted Amorphous Calcium Carbonate (Mg-ACC). Zeitschrift für anorganische und allgemeine Chemie. 634:1439-1443.

Olsson AA. 1961. Mollusc of the Tropical Eastern Pacific particularly from the southern half of

the Panamic-Pacific fauna province (Panama to Peru) Panamic-Pacific Pelecypoda. Ithaca. Paleontological Research Institute. 574 p.

Patterson III WF, Cowan Jr JH, Graham EY, Berry Lyons W.1998. Otolith Microchemical

Fingerprints of Age-0 Red Snapper, Lutjanus campechanus, from the Northern Gulf of Mexico: Gulf of Mexico Science. 16:83-91.

Quinn HW, Neal VT, Antunez de Mayolo SE. 1987. El Niño Occurrences over the Past Four and

a Half Centuries. Journal of Geophysical Research. 92:14449-14461. Pokroy B, Quintana JP, Caspi EN, Berner A, Zolotoyabko E. 2004. Anisotropic lattice

distortions in biogenic aragonite. Nature Materials. 3:900-902.

59

Rollins HB, Sandweiss DH, Rollins JC. 1986. Effect of the 1982-1983 El Niño on bivalve molluscs. National Geographic Research. 2:106-112.

Rollins HB, Sandweiss DH, Brand U, Rollins JC. 1987. Growth Increment and Stable Isotope

Analysis of Marine Bivalves: Implication for the Geoarchaeological Record of El Niño. Geoarchaeology. 2:181-197.

Schneider JA, Carter JG. 2001. Evolution and Phylogenetic Significance of Cardioidean Shell

Microstructure (Mollusca, Bivalvia): Journal of Paleontology. 75:607-643. Soldati AL, Jacob DE, Wehrmeister U, Hofmeister W. 2008.Structural characterization and

chemical composition of aragonite and vaterite in freshwater cultured pearls. Mineralogical Magazine. 72:579-572.

Vander Putten E, Dehairs F, Keppens E, Baeyens W. 2000. High resolution distribution of trace

elements in the calcite shell layer of modern Mytilus edulis: Environmental and biological controls. Geochimica et Cosmochimica Acta. 64:997-1011.

Weiner S. 2008. Biomineralization: A structural perspective: Journal of Structural Biology.

163:229-234. Wyrtki K. 1985. Water Displacements in the Pacific and the Genesis of El Niño Cycles. Journal

of Geophysical Research. 90:7129-7132.

60

3.11. Appendix 2

Point1 Point2 Point3 Point4 Point5

Wave# Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u)

1200.3 -12.47 1200.3 -7.59 1200.2 -16.93 1200.3 -1.34 1200.3 -18.37 1198.3 -15.38 1198.3 1.55 1198.3 2.41 1198.3 -7.05 1198.3 -11.00 1196.4 1.77 1196.4 13.24 1196.3 1.99 1196.4 9.69 1196.4 15.31 1194.4 3.11 1194.4 -8.55 1194.4 9.48 1194.4 12.61 1194.4 2.07 1192.5 21.00 1192.5 -0.53 1192.4 11.32 1192.5 7.88 1192.5 -2.41 1190.5 4.94 1190.5 0.71 1190.5 16.99 1190.5 19.00 1190.5 21.69 1188.6 -32.95 1188.6 -8.53 1188.5 -6.79 1188.6 -5.55 1188.6 7.58 1186.6 9.18 1186.6 -0.21 1186.6 -0.99 1186.6 17.62 1186.6 2.09 1184.7 -7.20 1184.7 -8.05 1184.6 -5.38 1184.7 0.55 1184.7 -2.97 1182.7 15.56 1182.7 10.21 1182.7 7.81 1182.7 12.40 1182.7 8.27 1180.8 1.15 1180.8 18.98 1180.7 -3.41 1180.8 6.95 1180.8 1.92 1178.8 8.17 1178.8 10.71 1178.8 3.26 1178.8 19.25 1178.8 21.85 1176.8 8.80 1176.8 18.35 1176.8 18.61 1176.8 15.92 1176.8 12.52 1174.9 12.27 1174.9 19.88 1174.8 28.29 1174.9 29.52 1174.9 30.48 1172.9 -14.84 1172.9 0.07 1172.9 -8.41 1172.9 -2.27 1172.9 -3.76 1171.0 26.64 1171.0 34.05 1170.9 0.70 1171.0 24.01 1171.0 21.19 1169.0 9.90 1169.0 21.63 1169.0 12.95 1169.0 26.66 1169.0 9.56 1167.1 19.37 1167.1 15.46 1167.0 13.95 1167.1 5.93 1167.1 -3.09 1165.1 24.14 1165.1 18.99 1165.0 0.83 1165.1 19.14 1165.1 9.78 1163.1 27.20 1163.1 3.40 1163.1 3.54 1163.1 7.94 1163.1 22.24 1161.2 20.41 1161.2 37.77 1161.1 14.82 1161.2 8.16 1161.2 13.86 1159.2 15.33 1159.2 27.45 1159.2 26.97 1159.2 26.25 1159.2 24.62 1157.3 10.53 1157.3 21.84 1157.2 -2.91 1157.3 7.03 1157.3 -2.35 1155.3 15.31 1155.3 32.38 1155.2 2.95 1155.3 31.57 1155.3 12.27 1153.3 18.66 1153.3 15.74 1153.3 -7.08 1153.3 11.62 1153.3 4.58 1151.4 25.16 1151.4 22.14 1151.3 -5.08 1151.4 6.25 1151.4 6.77 1149.4 17.77 1149.4 49.04 1149.4 -6.81 1149.4 9.34 1149.4 9.67 1147.4 55.98 1147.4 23.05 1147.4 16.99 1147.4 34.22 1147.4 14.73 1145.5 38.69 1145.5 32.34 1145.4 13.26 1145.5 19.39 1145.5 22.95 1143.5 34.88 1143.5 54.12 1143.5 24.89 1143.5 24.35 1143.5 13.23 1141.6 26.18 1141.6 21.05 1141.5 20.58 1141.6 -8.18 1141.6 13.12 1139.6 35.87 1139.6 47.74 1139.5 19.15 1139.6 23.66 1139.6 12.30 1137.6 18.53 1137.6 21.24 1137.6 14.12 1137.6 11.66 1137.6 21.54 1135.7 21.75 1135.7 11.11 1135.6 3.75 1135.7 12.74 1135.7 2.73 1133.7 22.52 1133.7 37.98 1133.6 -1.44 1133.7 4.03 1133.7 20.05 1131.7 12.77 1131.7 22.66 1131.7 6.91 1131.7 25.14 1131.7 23.83 1129.8 13.83 1129.8 36.60 1129.7 17.14 1129.8 25.36 1129.8 16.81 1127.8 -5.02 1127.8 16.35 1127.7 9.78 1127.8 9.43 1127.8 -11.14 1125.8 34.13 1125.8 48.34 1125.8 16.71 1125.8 3.44 1125.8 21.22 1123.9 36.07 1123.9 43.82 1123.8 14.25 1123.9 19.40 1123.9 25.02 1121.9 17.91 1121.9 32.79 1121.8 11.21 1121.9 13.98 1121.9 17.98 1119.9 2.05 1119.9 44.74 1119.9 6.44 1119.9 -0.55 1119.9 0.95 1118.0 -4.86 1118.0 14.74 1117.9 12.80 1118.0 5.16 1118.0 -4.23 1116.0 12.69 1116.0 39.87 1115.9 28.57 1116.0 18.11 1116.0 8.39 1114.0 -0.02 1114.0 26.78 1114.0 11.19 1114.0 13.11 1114.0 14.07

61

1112.0 13.64 1112.0 26.14 1112.0 6.84 1112.0 7.24 1112.0 14.98 1110.1 -0.39 1110.1 1.71 1110.0 -3.32 1110.1 -17.49 1110.1 0.94 1108.1 5.15 1108.1 -2.43 1108.1 0.87 1108.1 5.78 1108.1 -12.38 1106.1 8.52 1106.1 2.99 1106.1 5.65 1106.1 15.43 1106.1 12.61 1104.2 20.62 1104.2 18.73 1104.1 -0.75 1104.2 13.32 1104.2 9.45 1102.2 0.30 1102.2 28.10 1102.1 16.39 1102.2 15.57 1102.2 24.74 1100.2 -4.47 1100.2 4.01 1100.2 -0.78 1100.2 20.15 1100.2 3.25 1098.2 6.32 1098.2 25.75 1098.2 6.77 1098.2 -7.72 1098.2 4.59 1096.3 26.01 1096.3 7.02 1096.2 10.40 1096.3 8.36 1096.3 6.80 1094.3 6.53 1094.3 20.19 1094.2 24.23 1094.3 12.21 1094.3 5.08 1092.3 5.10 1092.3 28.26 1092.3 8.78 1092.3 15.49 1092.3 4.67 1090.3 10.81 1090.3 30.66 1090.3 14.31 1090.3 4.76 1090.3 2.21 1088.4 68.50 1088.4 191.30 1088.3 130.94 1088.4 57.08 1088.4 56.83 1086.4 211.13 1086.4 324.66 1086.3 274.15 1086.4 173.30 1086.4 106.84 1084.4 315.04 1084.4 247.14 1084.4 251.93 1084.4 266.56 1084.4 215.52 1082.4 208.49 1082.4 94.36 1082.4 103.19 1082.4 237.38 1082.4 196.65 1080.5 60.55 1080.5 35.78 1080.4 51.00 1080.5 77.94 1080.5 89.39 1078.5 8.48 1078.5 28.81 1078.4 9.72 1078.5 4.69 1078.5 23.58 1076.5 3.38 1076.5 18.02 1076.5 3.26 1076.5 18.67 1076.5 14.68 1074.5 6.77 1074.5 11.48 1074.5 6.47 1074.5 5.54 1074.5 4.30 1072.6 28.35 1072.6 20.91 1072.5 8.07 1072.6 15.43 1072.6 10.92 1070.6 23.39 1070.6 16.11 1070.5 12.16 1070.6 10.07 1070.6 16.23 1068.6 3.74 1068.6 38.18 1068.5 13.91 1068.6 17.62 1068.6 9.36 1066.6 13.16 1066.6 9.73 1066.6 -0.94 1066.6 0.35 1066.6 2.92 1064.6 20.82 1064.6 6.69 1064.6 24.48 1064.6 -4.30 1064.6 27.05 1062.7 -9.75 1062.7 11.58 1062.6 8.88 1062.7 8.41 1062.7 20.61

Supplementary table 5a Raman Spectra points 1 to 5 taken from T. procerum shell 2TP4-2. See figure 12 in the text for point location along shell ontogeny. Each point has two columns representing wavenumber in cm-1 and intensity in arbitrary units, respectively.

62

Point6 Point7 Point8 Point9 Point10

Wave# Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u)

1200.3 -15.09 1200.3 -8.22 1200.3 -5.50 1200.3 -6.34 1200.3 -18.05 1198.3 -14.75 1198.3 -3.88 1198.3 8.09 1198.3 20.75 1198.3 -8.36 1196.4 3.96 1196.4 -4.75 1196.4 19.01 1196.4 9.17 1196.4 -23.52 1194.4 10.25 1194.4 14.02 1194.4 -1.72 1194.4 23.58 1194.4 -13.39 1192.5 -1.69 1192.5 11.18 1192.5 3.97 1192.5 -8.39 1192.5 3.95 1190.5 23.28 1190.5 35.08 1190.5 20.15 1190.5 23.86 1190.5 31.37 1188.6 -7.65 1188.6 8.02 1188.6 -5.01 1188.6 -1.21 1188.6 5.00 1186.6 0.49 1186.6 11.68 1186.6 15.01 1186.6 10.11 1186.6 -3.54 1184.7 -18.30 1184.7 -0.67 1184.7 10.09 1184.7 -19.39 1184.7 -16.35 1182.7 29.85 1182.7 28.95 1182.7 16.23 1182.7 22.29 1182.7 -3.08 1180.8 -13.79 1180.8 9.21 1180.8 24.80 1180.8 10.79 1180.8 -1.14 1178.8 23.05 1178.8 22.11 1178.8 26.55 1178.8 26.83 1178.8 25.93 1176.8 23.84 1176.8 9.44 1176.8 16.37 1176.8 10.91 1176.8 12.53 1174.9 24.20 1174.9 22.65 1174.9 22.82 1174.9 18.71 1174.9 1.53 1172.9 8.34 1172.9 -7.11 1172.9 9.91 1172.9 -0.79 1172.9 -4.22 1171.0 -2.13 1171.0 15.49 1171.0 12.80 1171.0 29.23 1171.0 18.22 1169.0 24.86 1169.0 8.49 1169.0 18.83 1169.0 26.38 1169.0 19.02 1167.1 37.06 1167.1 10.46 1167.1 29.71 1167.1 19.67 1167.1 16.97 1165.1 16.74 1165.1 8.86 1165.1 27.34 1165.1 30.64 1165.1 19.20 1163.1 18.81 1163.1 25.25 1163.1 18.25 1163.1 38.20 1163.1 34.99 1161.2 16.60 1161.2 19.09 1161.2 2.87 1161.2 39.62 1161.2 33.80 1159.2 27.53 1159.2 14.21 1159.2 6.62 1159.2 44.34 1159.2 24.46 1157.3 -0.42 1157.3 -11.70 1157.3 -5.78 1157.3 -0.56 1157.3 41.99 1155.3 24.96 1155.3 16.45 1155.3 8.69 1155.3 31.03 1155.3 23.48 1153.3 5.85 1153.3 20.15 1153.3 16.18 1153.3 26.86 1153.3 44.47 1151.4 0.90 1151.4 14.82 1151.4 14.35 1151.4 42.89 1151.4 14.19 1149.4 8.41 1149.4 23.83 1149.4 13.53 1149.4 18.24 1149.4 22.58 1147.4 21.23 1147.4 29.54 1147.4 12.14 1147.4 49.48 1147.4 40.58 1145.5 4.08 1145.5 17.61 1145.5 30.40 1145.5 19.49 1145.5 35.93 1143.5 22.66 1143.5 26.05 1143.5 18.82 1143.5 36.70 1143.5 89.72 1141.6 16.84 1141.6 22.73 1141.6 20.30 1141.6 22.89 1141.6 48.02 1139.6 15.61 1139.6 30.04 1139.6 8.84 1139.6 45.87 1139.6 45.23 1137.6 34.52 1137.6 19.23 1137.6 27.14 1137.6 35.65 1137.6 64.01 1135.7 14.59 1135.7 -7.00 1135.7 -4.19 1135.7 22.11 1135.7 61.94 1133.7 18.68 1133.7 12.98 1133.7 21.32 1133.7 28.85 1133.7 67.50 1131.7 33.44 1131.7 15.97 1131.7 28.28 1131.7 32.72 1131.7 62.55 1129.8 29.34 1129.8 35.26 1129.8 8.72 1129.8 31.69 1129.8 65.52 1127.8 26.38 1127.8 7.40 1127.8 28.37 1127.8 4.55 1127.8 12.37 1125.8 30.05 1125.8 37.10 1125.8 23.80 1125.8 58.79 1125.8 62.52 1123.9 17.70 1123.9 34.91 1123.9 20.08 1123.9 40.44 1123.9 46.42 1121.9 37.85 1121.9 20.15 1121.9 19.11 1121.9 18.46 1121.9 59.79 1119.9 4.95 1119.9 -0.85 1119.9 24.06 1119.9 25.66 1119.9 66.08 1118.0 4.42 1118.0 5.04 1118.0 16.29 1118.0 27.08 1118.0 12.62

63

1116.0 38.50 1116.0 9.78 1116.0 20.52 1116.0 45.29 1116.0 9.19 1114.0 -2.43 1114.0 14.23 1114.0 22.73 1114.0 27.74 1114.0 40.96 1112.0 26.46 1112.0 22.89 1112.0 0.88 1112.0 27.86 1112.0 43.05 1110.1 0.13 1110.1 15.61 1110.1 5.55 1110.1 18.55 1110.1 2.50 1108.1 5.26 1108.1 21.23 1108.1 2.67 1108.1 20.98 1108.1 14.58 1106.1 6.76 1106.1 2.32 1106.1 9.38 1106.1 22.25 1106.1 13.16 1104.2 14.36 1104.2 11.57 1104.2 8.68 1104.2 8.27 1104.2 43.13 1102.2 9.18 1102.2 10.81 1102.2 9.29 1102.2 28.29 1102.2 -4.79 1100.2 5.45 1100.2 -8.29 1100.2 3.65 1100.2 16.18 1100.2 -15.10 1098.2 9.58 1098.2 12.33 1098.2 -4.33 1098.2 -4.53 1098.2 -21.64 1096.3 -7.56 1096.3 13.01 1096.3 17.97 1096.3 22.21 1096.3 12.31 1094.3 28.91 1094.3 24.78 1094.3 5.91 1094.3 19.70 1094.3 26.76 1092.3 1.70 1092.3 -14.77 1092.3 9.14 1092.3 21.11 1092.3 -3.24 1090.3 31.80 1090.3 10.70 1090.3 9.31 1090.3 -9.57 1090.3 -57.20 1088.4 47.63 1088.4 55.33 1088.4 52.84 1088.4 47.45 1088.4 13.00 1086.4 127.01 1086.4 117.10 1086.4 103.87 1086.4 151.57 1086.4 80.36 1084.4 269.19 1084.4 307.99 1084.4 279.04 1084.4 351.69 1084.4 257.85 1082.4 286.94 1082.4 322.45 1082.4 308.47 1082.4 392.49 1082.4 298.66 1080.5 158.82 1080.5 172.46 1080.5 167.32 1080.5 225.56 1080.5 149.74 1078.5 27.33 1078.5 47.33 1078.5 50.61 1078.5 57.56 1078.5 10.31 1076.5 13.03 1076.5 21.52 1076.5 22.82 1076.5 9.04 1076.5 9.15 1074.5 7.06 1074.5 -2.41 1074.5 1.75 1074.5 15.88 1074.5 -4.91 1072.6 13.85 1072.6 15.57 1072.6 26.41 1072.6 -7.64 1072.6 -25.30 1070.6 29.90 1070.6 19.64 1070.6 23.06 1070.6 19.74 1070.6 -13.27 1068.6 23.20 1068.6 19.45 1068.6 10.47 1068.6 20.86 1068.6 0.08 1066.6 21.48 1066.6 18.38 1066.6 -9.64 1066.6 22.87 1066.6 -16.08 1064.6 18.74 1064.6 24.07 1064.6 16.25 1064.6 6.21 1064.6 14.49 1062.7 9.23 1062.7 5.49 1062.7 10.83 1062.7 14.97 1062.7 -13.60

Supplementary table 5b Raman Spectra points 6 to 10 taken from T. procerum shell 2TP4-2. See figure 12 in the text for point location along shell ontogeny. Each point has two columns representing wavenumber in cm-1 and intensity in arbitrary units, respectively.

64

Point11 Point12 Point13 Point14 Point15

Wave# Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u)

1200.3 9.76 1200.3 -13.20 1200.3 -17.43 1200.3 18.39 1200.3 -4.05 1198.3 19.36 1198.3 16.23 1198.3 2.86 1198.3 11.32 1198.3 -2.15 1196.4 15.55 1196.4 -2.49 1196.4 11.53 1196.4 12.29 1196.4 8.04 1194.4 7.64 1194.4 20.04 1194.4 -1.27 1194.4 -10.21 1194.4 36.34 1192.5 -7.93 1192.5 13.88 1192.5 35.70 1192.5 2.07 1192.5 8.38 1190.5 18.39 1190.5 37.87 1190.5 27.28 1190.5 51.29 1190.5 58.23 1188.6 -8.52 1188.6 54.08 1188.6 23.10 1188.6 13.90 1188.6 15.51 1186.6 34.12 1186.6 33.90 1186.6 15.51 1186.6 9.91 1186.6 32.69 1184.7 11.45 1184.7 21.49 1184.7 -16.34 1184.7 -13.79 1184.7 -8.82 1182.7 29.04 1182.7 26.80 1182.7 51.09 1182.7 14.96 1182.7 20.28 1180.8 8.74 1180.8 48.29 1180.8 20.36 1180.8 -0.12 1180.8 20.17 1178.8 27.49 1178.8 87.99 1178.8 42.86 1178.8 45.59 1178.8 16.36 1176.8 12.43 1176.8 54.68 1176.8 49.75 1176.8 14.87 1176.8 9.56 1174.9 51.68 1174.9 41.24 1174.9 38.73 1174.9 22.23 1174.9 42.86 1172.9 9.71 1172.9 24.79 1172.9 26.69 1172.9 7.83 1172.9 13.30 1171.0 29.07 1171.0 61.57 1171.0 61.35 1171.0 44.38 1171.0 25.71 1169.0 17.82 1169.0 54.80 1169.0 22.38 1169.0 33.11 1169.0 17.76 1167.1 25.08 1167.1 95.35 1167.1 43.96 1167.1 61.02 1167.1 22.92 1165.1 26.37 1165.1 88.30 1165.1 36.03 1165.1 28.62 1165.1 36.64 1163.1 38.64 1163.1 57.40 1163.1 58.35 1163.1 64.98 1163.1 33.10 1161.2 40.51 1161.2 64.74 1161.2 66.27 1161.2 40.26 1161.2 68.84 1159.2 51.66 1159.2 90.09 1159.2 91.63 1159.2 54.09 1159.2 38.30 1157.3 7.78 1157.3 112.75 1157.3 58.97 1157.3 68.94 1157.3 29.33 1155.3 35.80 1155.3 104.25 1155.3 74.63 1155.3 51.03 1155.3 43.94 1153.3 21.49 1153.3 131.24 1153.3 46.64 1153.3 37.26 1153.3 61.01 1151.4 33.52 1151.4 63.71 1151.4 58.15 1151.4 43.81 1151.4 61.63 1149.4 23.91 1149.4 81.10 1149.4 103.21 1149.4 40.48 1149.4 56.22 1147.4 30.36 1147.4 115.29 1147.4 115.34 1147.4 80.16 1147.4 58.99 1145.5 46.00 1145.5 123.40 1145.5 147.86 1145.5 55.32 1145.5 69.93 1143.5 36.81 1143.5 159.37 1143.5 114.22 1143.5 70.64 1143.5 94.82 1141.6 17.99 1141.6 115.78 1141.6 118.47 1141.6 46.48 1141.6 83.81 1139.6 12.95 1139.6 112.83 1139.6 143.14 1139.6 55.20 1139.6 81.42 1137.6 47.60 1137.6 134.61 1137.6 141.66 1137.6 56.02 1137.6 87.08 1135.7 39.11 1135.7 134.54 1135.7 148.95 1135.7 89.95 1135.7 81.95 1133.7 28.60 1133.7 115.17 1133.7 114.78 1133.7 50.03 1133.7 69.75 1131.7 36.37 1131.7 135.25 1131.7 140.36 1131.7 61.94 1131.7 59.56 1129.8 26.13 1129.8 137.34 1129.8 117.24 1129.8 59.59 1129.8 83.24 1127.8 26.26 1127.8 117.64 1127.8 126.69 1127.8 60.70 1127.8 67.56 1125.8 17.59 1125.8 148.15 1125.8 105.84 1125.8 54.01 1125.8 65.72 1123.9 19.88 1123.9 126.26 1123.9 127.00 1123.9 44.71 1123.9 52.32 1121.9 30.56 1121.9 103.76 1121.9 116.81 1121.9 69.80 1121.9 40.06 1119.9 37.92 1119.9 103.95 1119.9 85.64 1119.9 53.27 1119.9 53.82 1118.0 11.44 1118.0 56.52 1118.0 85.12 1118.0 9.51 1118.0 39.52 1116.0 39.93 1116.0 93.44 1116.0 48.82 1116.0 68.35 1116.0 49.67 1114.0 29.06 1114.0 118.24 1114.0 68.12 1114.0 37.87 1114.0 26.94 1112.0 27.45 1112.0 74.06 1112.0 43.22 1112.0 70.41 1112.0 45.21 1110.1 28.02 1110.1 45.50 1110.1 44.11 1110.1 16.69 1110.1 21.15

65

1108.1 25.97 1108.1 41.42 1108.1 47.03 1108.1 19.22 1108.1 27.39 1106.1 23.77 1106.1 61.74 1106.1 21.93 1106.1 15.21 1106.1 24.78 1104.2 18.09 1104.2 36.59 1104.2 38.35 1104.2 44.75 1104.2 31.18 1102.2 15.30 1102.2 46.31 1102.2 17.43 1102.2 28.25 1102.2 13.88 1100.2 5.53 1100.2 54.88 1100.2 30.08 1100.2 13.90 1100.2 7.48 1098.2 28.20 1098.2 44.96 1098.2 24.99 1098.2 3.47 1098.2 18.09 1096.3 25.85 1096.3 72.61 1096.3 24.41 1096.3 4.67 1096.3 30.03 1094.3 29.62 1094.3 35.59 1094.3 12.46 1094.3 57.61 1094.3 10.36 1092.3 22.02 1092.3 41.24 1092.3 43.22 1092.3 4.02 1092.3 31.05 1090.3 4.05 1090.3 16.40 1090.3 12.00 1090.3 15.14 1090.3 14.86 1088.4 69.99 1088.4 41.90 1088.4 49.36 1088.4 27.45 1088.4 42.15 1086.4 128.42 1086.4 132.57 1086.4 79.89 1086.4 63.13 1086.4 77.94 1084.4 322.84 1084.4 303.73 1084.4 217.88 1084.4 246.62 1084.4 200.00 1082.4 443.93 1082.4 399.48 1082.4 295.49 1082.4 321.37 1082.4 279.79 1080.5 209.59 1080.5 274.10 1080.5 195.55 1080.5 214.18 1080.5 175.17 1078.5 87.57 1078.5 64.53 1078.5 41.18 1078.5 71.73 1078.5 56.07 1076.5 36.60 1076.5 18.35 1076.5 34.73 1076.5 17.00 1076.5 11.40 1074.5 31.88 1074.5 50.98 1074.5 11.71 1074.5 -2.76 1074.5 4.20 1072.6 33.32 1072.6 30.84 1072.6 45.85 1072.6 4.15 1072.6 19.72 1070.6 35.35 1070.6 36.65 1070.6 18.70 1070.6 17.38 1070.6 36.59 1068.6 23.14 1068.6 37.76 1068.6 20.15 1068.6 26.51 1068.6 35.41 1066.6 22.52 1066.6 17.57 1066.6 14.10 1066.6 7.88 1066.6 -5.74 1064.6 29.70 1064.6 29.55 1064.6 36.86 1064.6 23.92 1064.6 26.43 1062.7 30.11 1062.7 15.81 1062.7 0.07 1062.7 8.21 1062.7 10.67

Supplementary table 5c Raman Spectra points 11 to 15 taken from T. procerum shell 2TP4-2. See figure 12 in the text for point location along shell ontogeny. Each point has two columns representing wavenumber in cm-1 and intensity in arbitrary units, respectively.

66

Point16 Point17 Point18 Point19 Point20

Wave# Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u)

1200.3 -9.39 1200.3 -9.65 1200.3 -12.22 1200.3 16.83 1200.3 -16.43 1198.3 -8.87 1198.3 -1.13 1198.3 -9.01 1198.3 9.22 1198.3 -21.73 1196.4 27.23 1196.4 0.49 1196.4 32.12 1196.4 26.33 1196.4 -25.19 1194.4 -2.37 1194.4 15.40 1194.4 12.51 1194.4 20.70 1194.4 -19.05 1192.5 17.64 1192.5 -16.08 1192.5 -19.86 1192.5 24.67 1192.5 -36.25 1190.5 34.13 1190.5 39.03 1190.5 20.90 1190.5 7.00 1190.5 16.59 1188.6 8.59 1188.6 19.15 1188.6 42.30 1188.6 20.17 1188.6 -18.45 1186.6 11.78 1186.6 29.71 1186.6 66.42 1186.6 31.65 1186.6 -21.80 1184.7 10.29 1184.7 -8.22 1184.7 20.80 1184.7 1.18 1184.7 -37.06 1182.7 36.04 1182.7 33.26 1182.7 29.88 1182.7 40.46 1182.7 -0.98 1180.8 7.45 1180.8 -1.73 1180.8 2.06 1180.8 42.89 1180.8 -9.01 1178.8 39.06 1178.8 11.97 1178.8 39.97 1178.8 57.24 1178.8 16.47 1176.8 31.47 1176.8 29.94 1176.8 73.09 1176.8 63.94 1176.8 14.40 1174.9 49.61 1174.9 36.55 1174.9 54.06 1174.9 55.42 1174.9 61.96 1172.9 15.12 1172.9 18.70 1172.9 64.31 1172.9 53.00 1172.9 19.08 1171.0 16.76 1171.0 33.99 1171.0 53.91 1171.0 37.63 1171.0 16.86 1169.0 23.67 1169.0 41.76 1169.0 82.12 1169.0 57.71 1169.0 34.30 1167.1 20.47 1167.1 9.62 1167.1 54.19 1167.1 70.11 1167.1 54.18 1165.1 28.81 1165.1 24.08 1165.1 97.83 1165.1 80.95 1165.1 24.87 1163.1 23.46 1163.1 50.27 1163.1 102.69 1163.1 90.38 1163.1 24.64 1161.2 45.96 1161.2 43.92 1161.2 92.70 1161.2 85.96 1161.2 44.83 1159.2 13.46 1159.2 56.00 1159.2 154.57 1159.2 133.70 1159.2 25.89 1157.3 22.97 1157.3 4.17 1157.3 79.53 1157.3 106.70 1157.3 46.24 1155.3 35.63 1155.3 35.98 1155.3 109.13 1155.3 135.61 1155.3 33.14 1153.3 21.10 1153.3 31.33 1153.3 108.12 1153.3 104.00 1153.3 29.04 1151.4 35.35 1151.4 38.55 1151.4 108.54 1151.4 113.02 1151.4 67.76 1149.4 56.06 1149.4 51.52 1149.4 124.58 1149.4 75.76 1149.4 15.94 1147.4 49.98 1147.4 71.53 1147.4 138.77 1147.4 177.00 1147.4 73.62 1145.5 66.00 1145.5 79.93 1145.5 137.62 1145.5 165.70 1145.5 56.18 1143.5 54.31 1143.5 84.47 1143.5 164.46 1143.5 142.75 1143.5 27.80 1141.6 73.79 1141.6 64.02 1141.6 177.11 1141.6 145.20 1141.6 61.31 1139.6 66.27 1139.6 96.59 1139.6 172.51 1139.6 127.96 1139.6 91.26 1137.6 50.83 1137.6 100.28 1137.6 152.23 1137.6 136.88 1137.6 102.12 1135.7 59.97 1135.7 61.80 1135.7 201.72 1135.7 136.59 1135.7 82.04 1133.7 62.36 1133.7 102.64 1133.7 188.91 1133.7 179.79 1133.7 115.36 1131.7 71.09 1131.7 90.92 1131.7 154.03 1131.7 128.65 1131.7 79.84 1129.8 67.72 1129.8 73.13 1129.8 172.03 1129.8 183.57 1129.8 89.56 1127.8 61.90 1127.8 66.14 1127.8 187.88 1127.8 149.97 1127.8 57.73 1125.8 53.61 1125.8 39.07 1125.8 127.08 1125.8 167.72 1125.8 102.94 1123.9 39.53 1123.9 56.17 1123.9 178.88 1123.9 140.99 1123.9 106.18 1121.9 63.01 1121.9 50.46 1121.9 168.73 1121.9 189.82 1121.9 59.12 1119.9 44.15 1119.9 41.41 1119.9 153.36 1119.9 138.64 1119.9 51.20 1118.0 45.09 1118.0 22.51 1118.0 148.39 1118.0 99.54 1118.0 43.98 1116.0 58.04 1116.0 26.03 1116.0 143.84 1116.0 112.23 1116.0 77.30 1114.0 42.18 1114.0 37.08 1114.0 106.97 1114.0 126.67 1114.0 73.27 1112.0 10.22 1112.0 30.32 1112.0 101.37 1112.0 86.62 1112.0 91.57 1110.1 20.27 1110.1 4.11 1110.1 86.47 1110.1 60.44 1110.1 38.23

67

1108.1 29.76 1108.1 16.33 1108.1 32.95 1108.1 100.41 1108.1 53.32 1106.1 16.46 1106.1 -6.28 1106.1 87.98 1106.1 76.53 1106.1 54.49 1104.2 30.60 1104.2 22.36 1104.2 82.92 1104.2 107.39 1104.2 54.06 1102.2 36.62 1102.2 2.34 1102.2 28.41 1102.2 68.94 1102.2 32.55 1100.2 41.91 1100.2 -6.51 1100.2 48.03 1100.2 58.38 1100.2 -23.31 1098.2 8.79 1098.2 6.17 1098.2 49.47 1098.2 16.93 1098.2 5.90 1096.3 17.86 1096.3 10.42 1096.3 39.85 1096.3 43.02 1096.3 17.52 1094.3 16.31 1094.3 39.45 1094.3 10.53 1094.3 72.34 1094.3 38.04 1092.3 34.29 1092.3 13.98 1092.3 44.46 1092.3 64.21 1092.3 26.07 1090.3 -9.28 1090.3 24.07 1090.3 24.88 1090.3 85.26 1090.3 40.34 1088.4 37.61 1088.4 40.89 1088.4 36.80 1088.4 101.21 1088.4 27.77 1086.4 59.14 1086.4 44.59 1086.4 173.19 1086.4 210.67 1086.4 159.65 1084.4 165.90 1084.4 165.94 1084.4 523.55 1084.4 559.35 1084.4 504.91 1082.4 286.38 1082.4 262.57 1082.4 727.19 1082.4 849.22 1082.4 792.65 1080.5 175.08 1080.5 171.43 1080.5 475.87 1080.5 606.95 1080.5 601.39 1078.5 57.79 1078.5 48.42 1078.5 187.05 1078.5 237.60 1078.5 268.46 1076.5 8.49 1076.5 9.93 1076.5 13.78 1076.5 94.74 1076.5 51.90 1074.5 30.66 1074.5 6.00 1074.5 39.93 1074.5 43.32 1074.5 33.40 1072.6 15.89 1072.6 6.31 1072.6 -7.37 1072.6 58.42 1072.6 38.50 1070.6 6.83 1070.6 29.95 1070.6 16.45 1070.6 25.99 1070.6 1.62 1068.6 1.87 1068.6 10.01 1068.6 38.10 1068.6 68.26 1068.6 -14.30 1066.6 9.54 1066.6 5.32 1066.6 -17.08 1066.6 19.49 1066.6 14.43 1064.6 25.30 1064.6 16.36 1064.6 10.73 1064.6 6.67 1064.6 -29.00 1062.7 4.46 1062.7 4.17 1062.7 -4.03 1062.7 50.32 1062.7 -21.14

Supplementary table 5d Raman Spectra points 16 to 20 taken from T. procerum shell 2TP4-2. See figure 12 in the text for point location along shell ontogeny. Each point has two columns representing wavenumber in cm-1 and intensity in arbitrary units, respectively.

68

Point21 Point22 Point23 Point24 Point25

Wave# Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u)

1200.3 -28.50 1200.3 -20.19 1200.3 -1.53 1200.3 -11.18 1200.3 -6.91 1198.3 12.68 1198.3 43.38 1198.3 12.73 1198.3 6.67 1198.3 4.80 1196.4 -12.48 1196.4 16.46 1196.4 33.93 1196.4 -1.81 1196.4 -2.46 1194.4 4.87 1194.4 32.33 1194.4 13.87 1194.4 19.37 1194.4 65.75 1192.5 -2.94 1192.5 -1.99 1192.5 16.71 1192.5 5.64 1192.5 59.35 1190.5 0.99 1190.5 30.03 1190.5 20.11 1190.5 54.46 1190.5 24.77 1188.6 -26.80 1188.6 3.17 1188.6 2.13 1188.6 11.98 1188.6 53.45 1186.6 -0.08 1186.6 21.06 1186.6 8.78 1186.6 25.84 1186.6 36.96 1184.7 -37.12 1184.7 3.94 1184.7 -13.06 1184.7 22.57 1184.7 71.20 1182.7 45.10 1182.7 47.38 1182.7 23.39 1182.7 55.60 1182.7 34.40 1180.8 15.56 1180.8 22.16 1180.8 12.88 1180.8 30.04 1180.8 47.95 1178.8 18.93 1178.8 52.60 1178.8 7.91 1178.8 20.08 1178.8 134.10 1176.8 21.60 1176.8 29.05 1176.8 32.34 1176.8 29.85 1176.8 99.53 1174.9 43.04 1174.9 52.27 1174.9 33.06 1174.9 48.89 1174.9 134.61 1172.9 23.23 1172.9 58.01 1172.9 12.28 1172.9 26.95 1172.9 64.55 1171.0 50.24 1171.0 31.58 1171.0 49.72 1171.0 82.44 1171.0 55.49 1169.0 50.79 1169.0 15.51 1169.0 69.82 1169.0 104.67 1169.0 69.08 1167.1 20.97 1167.1 55.73 1167.1 55.16 1167.1 74.45 1167.1 92.36 1165.1 30.19 1165.1 55.06 1165.1 48.18 1165.1 100.11 1165.1 105.55 1163.1 16.73 1163.1 31.55 1163.1 85.01 1163.1 75.55 1163.1 116.18 1161.2 19.97 1161.2 88.56 1161.2 81.03 1161.2 98.24 1161.2 173.23 1159.2 49.35 1159.2 61.32 1159.2 94.49 1159.2 120.09 1159.2 137.17 1157.3 67.47 1157.3 71.80 1157.3 57.34 1157.3 76.05 1157.3 151.54 1155.3 44.69 1155.3 82.00 1155.3 35.59 1155.3 72.88 1155.3 174.36 1153.3 88.03 1153.3 85.34 1153.3 63.93 1153.3 87.44 1153.3 134.50 1151.4 39.16 1151.4 126.65 1151.4 90.01 1151.4 122.08 1151.4 166.64 1149.4 78.24 1149.4 79.85 1149.4 64.23 1149.4 101.43 1149.4 217.45 1147.4 76.92 1147.4 90.64 1147.4 112.42 1147.4 111.15 1147.4 210.08 1145.5 91.24 1145.5 119.39 1145.5 84.90 1145.5 166.81 1145.5 200.99 1143.5 88.19 1143.5 106.96 1143.5 119.23 1143.5 134.08 1143.5 174.21 1141.6 92.47 1141.6 98.54 1141.6 111.36 1141.6 158.34 1141.6 200.42 1139.6 105.81 1139.6 146.31 1139.6 136.11 1139.6 168.54 1139.6 232.83 1137.6 96.73 1137.6 142.36 1137.6 148.95 1137.6 151.71 1137.6 184.15 1135.7 71.07 1135.7 98.38 1135.7 115.89 1135.7 151.27 1135.7 226.51 1133.7 96.37 1133.7 138.46 1133.7 127.00 1133.7 186.82 1133.7 183.08 1131.7 133.66 1131.7 132.76 1131.7 122.85 1131.7 145.90 1131.7 232.55 1129.8 111.01 1129.8 132.67 1129.8 157.34 1129.8 174.56 1129.8 192.67 1127.8 108.38 1127.8 126.09 1127.8 128.38 1127.8 203.55 1127.8 197.61 1125.8 113.83 1125.8 106.36 1125.8 134.04 1125.8 213.65 1125.8 224.78 1123.9 99.06 1123.9 154.06 1123.9 115.43 1123.9 139.27 1123.9 188.43 1121.9 119.25 1121.9 93.71 1121.9 98.97 1121.9 167.56 1121.9 210.56 1119.9 73.96 1119.9 69.73 1119.9 54.29 1119.9 130.36 1119.9 196.56 1118.0 47.41 1118.0 119.37 1118.0 68.73 1118.0 90.95 1118.0 195.56

69

1116.0 95.11 1116.0 82.06 1116.0 90.14 1116.0 97.38 1116.0 190.50 1114.0 49.57 1114.0 53.39 1114.0 72.61 1114.0 92.24 1114.0 132.41 1112.0 46.15 1112.0 76.28 1112.0 29.83 1112.0 72.15 1112.0 191.67 1110.1 30.84 1110.1 48.30 1110.1 32.83 1110.1 90.76 1110.1 109.13 1108.1 68.47 1108.1 3.59 1108.1 8.99 1108.1 77.46 1108.1 126.34 1106.1 25.70 1106.1 70.78 1106.1 35.50 1106.1 65.01 1106.1 127.89 1104.2 -1.29 1104.2 31.98 1104.2 35.16 1104.2 122.29 1104.2 114.02 1102.2 -3.15 1102.2 19.02 1102.2 40.21 1102.2 42.54 1102.2 45.77 1100.2 1.52 1100.2 1.09 1100.2 33.03 1100.2 59.28 1100.2 96.72 1098.2 28.18 1098.2 28.70 1098.2 1.98 1098.2 35.58 1098.2 121.66 1096.3 27.34 1096.3 61.43 1096.3 12.10 1096.3 36.75 1096.3 122.75 1094.3 51.42 1094.3 50.49 1094.3 50.36 1094.3 78.72 1094.3 69.04 1092.3 26.53 1092.3 32.68 1092.3 17.51 1092.3 32.52 1092.3 124.04 1090.3 15.03 1090.3 21.40 1090.3 2.71 1090.3 34.70 1090.3 75.95 1088.4 43.51 1088.4 55.52 1088.4 52.12 1088.4 81.12 1088.4 127.06 1086.4 128.12 1086.4 142.26 1086.4 129.93 1086.4 188.06 1086.4 210.96 1084.4 405.75 1084.4 389.57 1084.4 410.54 1084.4 470.06 1084.4 573.22 1082.4 584.98 1082.4 518.13 1082.4 634.59 1082.4 694.33 1082.4 789.21 1080.5 476.02 1080.5 413.60 1080.5 469.09 1080.5 442.88 1080.5 572.64 1078.5 149.81 1078.5 150.25 1078.5 145.57 1078.5 183.37 1078.5 226.97 1076.5 54.83 1076.5 48.75 1076.5 35.41 1076.5 42.50 1076.5 88.91 1074.5 4.72 1074.5 8.10 1074.5 26.25 1074.5 -7.50 1074.5 70.30 1072.6 4.14 1072.6 37.81 1072.6 3.30 1072.6 28.81 1072.6 27.75 1070.6 8.68 1070.6 -14.63 1070.6 8.94 1070.6 54.46 1070.6 65.42 1068.6 3.25 1068.6 20.38 1068.6 3.27 1068.6 -17.81 1068.6 62.90 1066.6 -12.78 1066.6 -15.68 1066.6 12.14 1066.6 -12.73 1066.6 37.59 1064.6 9.11 1064.6 28.93 1064.6 27.35 1064.6 15.13 1064.6 74.59 1062.7 -1.64 1062.7 45.93 1062.7 -15.83 1062.7 1.84 1062.7 89.41

Supplementary table 5e Raman Spectra points 21 to 25 taken from T. procerum shell 2TP4-2. See figure 12 in the text for point location along shell ontogeny. Each point has two columns representing wavenumber in cm-1 and intensity in arbitrary units, respectively.

70

Point26 Point27 Point28 Point29 Point30

Wave# Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u)

1200.3 -36.71 1200.3 -34.99 1200.3 3.95 1200.3 -1.70 1200.3 -22.08 1198.3 0.59 1198.3 4.54 1198.3 7.02 1198.3 1.52 1198.3 -53.91 1196.4 15.75 1196.4 25.78 1196.4 15.74 1196.4 -1.83 1196.4 31.92 1194.4 21.30 1194.4 -5.97 1194.4 -2.81 1194.4 34.25 1194.4 -24.38 1192.5 -6.24 1192.5 -5.65 1192.5 -35.54 1192.5 48.87 1192.5 -0.97 1190.5 49.69 1190.5 28.49 1190.5 8.98 1190.5 50.21 1190.5 -1.88 1188.6 32.74 1188.6 5.60 1188.6 22.38 1188.6 46.44 1188.6 -15.12 1186.6 62.96 1186.6 41.91 1186.6 20.08 1186.6 24.10 1186.6 -13.36 1184.7 56.64 1184.7 -8.37 1184.7 -3.79 1184.7 3.16 1184.7 -0.96 1182.7 18.79 1182.7 37.33 1182.7 22.54 1182.7 72.41 1182.7 56.98 1180.8 30.59 1180.8 27.02 1180.8 12.27 1180.8 41.95 1180.8 0.56 1178.8 38.14 1178.8 42.40 1178.8 24.00 1178.8 37.45 1178.8 63.54 1176.8 12.15 1176.8 47.70 1176.8 30.35 1176.8 62.78 1176.8 19.28 1174.9 82.97 1174.9 57.41 1174.9 35.28 1174.9 111.61 1174.9 72.94 1172.9 87.85 1172.9 30.00 1172.9 6.48 1172.9 35.83 1172.9 15.53 1171.0 110.81 1171.0 21.76 1171.0 61.37 1171.0 77.43 1171.0 114.95 1169.0 94.04 1169.0 20.79 1169.0 72.31 1169.0 88.17 1169.0 76.86 1167.1 50.59 1167.1 71.13 1167.1 47.32 1167.1 91.92 1167.1 109.13 1165.1 116.93 1165.1 65.61 1165.1 55.55 1165.1 93.55 1165.1 129.61 1163.1 92.98 1163.1 74.65 1163.1 44.65 1163.1 70.61 1163.1 129.55 1161.2 148.56 1161.2 88.97 1161.2 53.02 1161.2 97.78 1161.2 101.06 1159.2 110.30 1159.2 75.59 1159.2 70.11 1159.2 86.54 1159.2 98.40 1157.3 126.20 1157.3 70.05 1157.3 80.22 1157.3 97.73 1157.3 121.90 1155.3 85.44 1155.3 63.36 1155.3 80.61 1155.3 94.33 1155.3 129.11 1153.3 131.54 1153.3 71.83 1153.3 71.26 1153.3 106.11 1153.3 106.11 1151.4 169.81 1151.4 71.28 1151.4 75.50 1151.4 84.38 1151.4 162.87 1149.4 156.66 1149.4 91.23 1149.4 108.70 1149.4 118.66 1149.4 157.78 1147.4 202.15 1147.4 115.36 1147.4 89.59 1147.4 116.69 1147.4 190.53 1145.5 184.69 1145.5 140.67 1145.5 131.16 1145.5 144.72 1145.5 176.54 1143.5 185.15 1143.5 116.17 1143.5 128.55 1143.5 146.92 1143.5 217.08 1141.6 210.76 1141.6 132.45 1141.6 95.47 1141.6 137.20 1141.6 223.48 1139.6 217.85 1139.6 128.04 1139.6 109.08 1139.6 179.22 1139.6 189.05 1137.6 223.50 1137.6 159.88 1137.6 138.23 1137.6 193.96 1137.6 225.20 1135.7 207.56 1135.7 144.53 1135.7 96.60 1135.7 157.33 1135.7 278.08 1133.7 206.58 1133.7 154.09 1133.7 143.64 1133.7 160.40 1133.7 210.92 1131.7 263.52 1131.7 153.42 1131.7 125.74 1131.7 213.33 1131.7 246.84 1129.8 222.63 1129.8 188.65 1129.8 200.09 1129.8 188.03 1129.8 311.93 1127.8 206.06 1127.8 180.35 1127.8 119.44 1127.8 158.51 1127.8 217.10 1125.8 213.72 1125.8 181.71 1125.8 118.23 1125.8 202.43 1125.8 263.03 1123.9 223.55 1123.9 163.86 1123.9 133.34 1123.9 179.67 1123.9 221.34 1121.9 195.96 1121.9 163.18 1121.9 142.10 1121.9 169.45 1121.9 235.23 1119.9 154.45 1119.9 121.57 1119.9 123.26 1119.9 140.85 1119.9 146.76 1118.0 162.80 1118.0 87.30 1118.0 98.60 1118.0 129.58 1118.0 146.00 1116.0 220.97 1116.0 88.01 1116.0 43.36 1116.0 118.73 1116.0 185.78 1114.0 131.14 1114.0 62.50 1114.0 78.16 1114.0 85.98 1114.0 122.74 1112.0 146.16 1112.0 69.15 1112.0 50.38 1112.0 108.28 1112.0 155.58 1110.1 88.95 1110.1 51.28 1110.1 45.19 1110.1 74.47 1110.1 86.35

71

1108.1 94.37 1108.1 14.52 1108.1 54.65 1108.1 46.14 1108.1 99.75 1106.1 170.51 1106.1 77.63 1106.1 58.16 1106.1 110.27 1106.1 121.88 1104.2 92.71 1104.2 23.40 1104.2 44.82 1104.2 72.61 1104.2 132.83 1102.2 40.27 1102.2 11.13 1102.2 22.60 1102.2 68.93 1102.2 142.34 1100.2 6.53 1100.2 33.46 1100.2 52.43 1100.2 52.01 1100.2 76.36 1098.2 33.43 1098.2 29.90 1098.2 14.89 1098.2 49.61 1098.2 47.70 1096.3 64.30 1096.3 45.42 1096.3 76.64 1096.3 11.68 1096.3 69.99 1094.3 59.64 1094.3 23.50 1094.3 50.73 1094.3 70.17 1094.3 24.38 1092.3 30.92 1092.3 5.79 1092.3 31.79 1092.3 40.37 1092.3 51.91 1090.3 9.89 1090.3 6.57 1090.3 17.78 1090.3 53.27 1090.3 -14.49 1088.4 50.43 1088.4 40.50 1088.4 82.30 1088.4 130.85 1088.4 95.81 1086.4 126.37 1086.4 176.56 1086.4 170.69 1086.4 175.81 1086.4 148.39 1084.4 302.21 1084.4 506.43 1084.4 535.42 1084.4 498.21 1084.4 502.40 1082.4 461.14 1082.4 801.00 1082.4 864.88 1082.4 849.36 1082.4 772.57 1080.5 311.23 1080.5 597.10 1080.5 672.36 1080.5 648.40 1080.5 559.47 1078.5 91.00 1078.5 231.47 1078.5 232.03 1078.5 232.71 1078.5 269.54 1076.5 25.80 1076.5 43.10 1076.5 90.47 1076.5 94.58 1076.5 113.30 1074.5 -2.84 1074.5 16.93 1074.5 -19.59 1074.5 80.59 1074.5 -16.59 1072.6 -16.42 1072.6 -30.26 1072.6 40.19 1072.6 6.88 1072.6 12.63 1070.6 32.36 1070.6 -4.56 1070.6 62.19 1070.6 22.31 1070.6 67.87 1068.6 25.84 1068.6 50.23 1068.6 0.07 1068.6 40.98 1068.6 14.06 1066.6 -17.72 1066.6 10.62 1066.6 -24.22 1066.6 1.94 1066.6 23.95 1064.6 44.66 1064.6 10.95 1064.6 31.29 1064.6 42.97 1064.6 43.40 1062.7 -7.78 1062.7 -34.92 1062.7 13.02 1062.7 -1.43 1062.7 35.81

Supplementary table 5f Raman Spectra points 26 to 30 taken from T. procerum shell 2TP4-2. See figure 12 in the text for point location along shell ontogeny. Each point has two columns representing wavenumber in cm-1 and intensity in arbitrary units, respectively.

72

Point31 Point32 Point33 Point34 Point35

Wave# Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u)

1200.3 7.85 1200.3 -17.65 1200.3 4.90 1200.3 -29.15 1200.3 -0.37 1198.3 46.66 1198.3 -11.34 1198.3 43.61 1198.3 -25.04 1198.3 12.55 1196.4 12.04 1196.4 39.91 1196.4 33.21 1196.4 10.30 1196.4 6.56 1194.4 52.44 1194.4 55.72 1194.4 12.32 1194.4 9.06 1194.4 5.49 1192.5 64.87 1192.5 6.62 1192.5 39.36 1192.5 17.29 1192.5 27.20 1190.5 78.03 1190.5 79.75 1190.5 35.00 1190.5 14.63 1190.5 0.95 1188.6 69.52 1188.6 51.84 1188.6 32.05 1188.6 -23.73 1188.6 -1.26 1186.6 64.83 1186.6 30.83 1186.6 24.70 1186.6 15.10 1186.6 20.47 1184.7 52.19 1184.7 59.56 1184.7 12.95 1184.7 12.56 1184.7 10.04 1182.7 99.97 1182.7 22.21 1182.7 65.15 1182.7 41.65 1182.7 37.62 1180.8 41.89 1180.8 64.30 1180.8 49.00 1180.8 77.31 1180.8 10.85 1178.8 108.60 1178.8 64.83 1178.8 46.74 1178.8 68.26 1178.8 17.01 1176.8 69.64 1176.8 105.85 1176.8 38.21 1176.8 43.13 1176.8 22.74 1174.9 127.34 1174.9 113.50 1174.9 43.90 1174.9 39.58 1174.9 20.79 1172.9 102.13 1172.9 93.83 1172.9 76.34 1172.9 66.77 1172.9 2.33 1171.0 146.38 1171.0 84.66 1171.0 96.15 1171.0 88.28 1171.0 63.01 1169.0 102.63 1169.0 52.40 1169.0 86.48 1169.0 140.60 1169.0 27.17 1167.1 163.60 1167.1 104.20 1167.1 109.87 1167.1 82.91 1167.1 58.71 1165.1 112.66 1165.1 140.24 1165.1 64.24 1165.1 60.39 1165.1 44.64 1163.1 131.88 1163.1 168.31 1163.1 154.44 1163.1 80.22 1163.1 23.84 1161.2 128.98 1161.2 148.28 1161.2 88.78 1161.2 132.49 1161.2 52.28 1159.2 189.52 1159.2 141.22 1159.2 93.92 1159.2 104.08 1159.2 67.46 1157.3 152.47 1157.3 142.31 1157.3 117.08 1157.3 168.44 1157.3 58.21 1155.3 179.32 1155.3 172.00 1155.3 119.08 1155.3 109.53 1155.3 41.22 1153.3 114.58 1153.3 189.13 1153.3 121.66 1153.3 76.47 1153.3 91.06 1151.4 182.83 1151.4 197.39 1151.4 76.39 1151.4 110.25 1151.4 92.10 1149.4 247.01 1149.4 190.75 1149.4 187.01 1149.4 112.82 1149.4 81.83 1147.4 254.45 1147.4 142.93 1147.4 149.75 1147.4 160.71 1147.4 89.17 1145.5 308.12 1145.5 164.51 1145.5 153.77 1145.5 142.22 1145.5 81.46 1143.5 211.64 1143.5 239.81 1143.5 142.28 1143.5 159.02 1143.5 113.79 1141.6 239.62 1141.6 228.41 1141.6 114.68 1141.6 146.24 1141.6 95.59 1139.6 310.46 1139.6 213.54 1139.6 201.19 1139.6 189.50 1139.6 93.74 1137.6 296.08 1137.6 230.59 1137.6 152.88 1137.6 260.29 1137.6 120.52 1135.7 262.82 1135.7 222.32 1135.7 172.86 1135.7 140.45 1135.7 112.93 1133.7 270.42 1133.7 203.81 1133.7 157.59 1133.7 172.54 1133.7 78.25 1131.7 250.21 1131.7 227.06 1131.7 127.74 1131.7 231.47 1131.7 135.17 1129.8 271.79 1129.8 207.65 1129.8 190.27 1129.8 209.29 1129.8 117.04 1127.8 251.12 1127.8 210.73 1127.8 168.76 1127.8 202.95 1127.8 90.65 1125.8 285.71 1125.8 279.19 1125.8 213.91 1125.8 206.12 1125.8 156.62 1123.9 277.00 1123.9 222.35 1123.9 206.25 1123.9 222.87 1123.9 119.97 1121.9 255.98 1121.9 190.44 1121.9 173.86 1121.9 130.80 1121.9 115.36 1119.9 216.44 1119.9 154.88 1119.9 159.51 1119.9 147.09 1119.9 64.75 1118.0 116.35 1118.0 210.43 1118.0 133.12 1118.0 156.01 1118.0 77.74 1116.0 186.84 1116.0 205.95 1116.0 119.87 1116.0 127.43 1116.0 101.75 1114.0 89.65 1114.0 139.75 1114.0 146.01 1114.0 126.06 1114.0 40.46 1112.0 172.23 1112.0 157.54 1112.0 146.09 1112.0 96.55 1112.0 65.92 1110.1 139.45 1110.1 104.13 1110.1 85.38 1110.1 64.83 1110.1 53.55

73

1108.1 47.57 1108.1 94.04 1108.1 102.39 1108.1 65.73 1108.1 45.81 1106.1 102.67 1106.1 72.18 1106.1 97.78 1106.1 98.42 1106.1 48.22 1104.2 70.21 1104.2 129.03 1104.2 96.50 1104.2 32.20 1104.2 6.45 1102.2 107.06 1102.2 152.66 1102.2 66.72 1102.2 64.32 1102.2 65.39 1100.2 39.35 1100.2 113.17 1100.2 79.09 1100.2 67.38 1100.2 3.94 1098.2 45.06 1098.2 33.75 1098.2 74.58 1098.2 56.46 1098.2 22.33 1096.3 65.20 1096.3 87.35 1096.3 64.97 1096.3 56.75 1096.3 16.41 1094.3 76.47 1094.3 110.98 1094.3 75.74 1094.3 76.70 1094.3 30.01 1092.3 -28.17 1092.3 95.13 1092.3 92.65 1092.3 21.88 1092.3 8.34 1090.3 -18.71 1090.3 86.68 1090.3 28.74 1090.3 76.83 1090.3 70.82 1088.4 50.90 1088.4 91.37 1088.4 70.74 1088.4 90.84 1088.4 47.53 1086.4 66.70 1086.4 178.58 1086.4 212.11 1086.4 226.24 1086.4 168.53 1084.4 305.24 1084.4 564.19 1084.4 433.44 1084.4 567.86 1084.4 504.66 1082.4 563.22 1082.4 857.66 1082.4 793.80 1082.4 859.57 1082.4 733.69 1080.5 400.37 1080.5 716.32 1080.5 609.38 1080.5 715.73 1080.5 527.96 1078.5 118.30 1078.5 233.23 1078.5 193.71 1078.5 274.35 1078.5 170.90 1076.5 27.36 1076.5 99.70 1076.5 121.52 1076.5 119.44 1076.5 61.29 1074.5 -34.66 1074.5 107.74 1074.5 46.01 1074.5 -5.31 1074.5 -11.23 1072.6 -32.82 1072.6 85.57 1072.6 40.96 1072.6 22.75 1072.6 26.46 1070.6 19.50 1070.6 60.15 1070.6 30.47 1070.6 61.71 1070.6 25.60 1068.6 -11.67 1068.6 27.65 1068.6 29.21 1068.6 37.12 1068.6 -2.00 1066.6 -30.10 1066.6 40.79 1066.6 18.84 1066.6 -3.07 1066.6 -9.65 1064.6 23.48 1064.6 58.21 1064.6 13.45 1064.6 58.72 1064.6 19.89 1062.7 -16.57 1062.7 23.28 1062.7 -3.87 1062.7 39.08 1062.7 -9.09

Supplementary table 5g Raman Spectra points 31 to 35 taken from T. procerum shell 2TP4-2. See figure 12 in the text for point location along shell ontogeny. Each point has two columns representing wavenumber in cm-1 and intensity in arbitrary units, respectively.

74

Point36 Point37 Point38 Point39

Wave# Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u) Wave#

Int

(a.u)

1200.3 -3.29 1200.3 -5.61 1200.3 -7.16 1200.3 -9.15 1198.3 7.93 1198.3 -42.18 1198.3 -2.12 1198.3 -7.21 1196.4 20.44 1196.4 -10.83 1196.4 10.79 1196.4 -3.15 1194.4 -5.08 1194.4 26.20 1194.4 -14.04 1194.4 -52.81 1192.5 -50.57 1192.5 -0.66 1192.5 17.96 1192.5 11.19 1190.5 24.47 1190.5 -11.14 1190.5 24.24 1190.5 12.00 1188.6 -3.37 1188.6 -23.47 1188.6 16.36 1188.6 -50.64 1186.6 15.67 1186.6 -27.18 1186.6 14.98 1186.6 -17.56 1184.7 -24.83 1184.7 1.85 1184.7 37.71 1184.7 5.49 1182.7 14.64 1182.7 -21.57 1182.7 65.56 1182.7 19.47 1180.8 20.80 1180.8 -6.13 1180.8 51.71 1180.8 11.76 1178.8 -16.23 1178.8 36.46 1178.8 65.26 1178.8 36.84 1176.8 -11.09 1176.8 21.67 1176.8 65.74 1176.8 50.44 1174.9 22.36 1174.9 45.69 1174.9 24.26 1174.9 31.34 1172.9 26.10 1172.9 23.05 1172.9 82.20 1172.9 65.86 1171.0 53.48 1171.0 32.57 1171.0 89.38 1171.0 86.75 1169.0 28.60 1169.0 61.90 1169.0 79.89 1169.0 45.54 1167.1 46.60 1167.1 35.23 1167.1 59.97 1167.1 55.17 1165.1 44.94 1165.1 78.72 1165.1 99.24 1165.1 52.12 1163.1 20.00 1163.1 33.90 1163.1 58.32 1163.1 55.34 1161.2 50.30 1161.2 81.99 1161.2 104.05 1161.2 71.98 1159.2 25.47 1159.2 75.84 1159.2 134.96 1159.2 61.63 1157.3 33.64 1157.3 68.96 1157.3 96.56 1157.3 56.13 1155.3 61.56 1155.3 83.68 1155.3 82.57 1155.3 62.21 1153.3 72.05 1153.3 110.44 1153.3 63.99 1153.3 71.30 1151.4 38.42 1151.4 80.49 1151.4 85.34 1151.4 128.09 1149.4 65.10 1149.4 94.09 1149.4 47.52 1149.4 86.48 1147.4 60.40 1147.4 92.49 1147.4 120.80 1147.4 91.29 1145.5 95.58 1145.5 85.00 1145.5 143.65 1145.5 109.59 1143.5 41.49 1143.5 102.63 1143.5 76.06 1143.5 122.30 1141.6 82.01 1141.6 82.64 1141.6 118.30 1141.6 98.10 1139.6 87.64 1139.6 102.44 1139.6 157.14 1139.6 132.38 1137.6 113.99 1137.6 100.25 1137.6 161.21 1137.6 75.36 1135.7 82.37 1135.7 49.26 1135.7 125.84 1135.7 108.07 1133.7 109.17 1133.7 114.15 1133.7 92.30 1133.7 90.13 1131.7 82.83 1131.7 109.21 1131.7 126.59 1131.7 104.01 1129.8 123.65 1129.8 109.60 1129.8 156.02 1129.8 93.68 1127.8 84.30 1127.8 78.11 1127.8 115.50 1127.8 55.49 1125.8 111.59 1125.8 134.92 1125.8 131.66 1125.8 105.74 1123.9 101.94 1123.9 96.32 1123.9 108.70 1123.9 77.77 1121.9 89.52 1121.9 83.40 1121.9 138.17 1121.9 98.89 1119.9 44.11 1119.9 93.74 1119.9 114.88 1119.9 91.98 1118.0 30.05 1118.0 77.18 1118.0 80.72 1118.0 72.32 1116.0 65.33 1116.0 60.45 1116.0 83.14 1116.0 79.72 1114.0 61.26 1114.0 47.46 1114.0 76.72 1114.0 93.05 1112.0 5.71 1112.0 60.84 1112.0 104.07 1112.0 55.53 1110.1 57.14 1110.1 62.91 1110.1 68.20 1110.1 65.09

75

1108.1 6.31 1108.1 41.91 1108.1 101.52 1108.1 47.08 1106.1 53.88 1106.1 69.96 1106.1 95.38 1106.1 49.97 1104.2 28.55 1104.2 35.71 1104.2 98.52 1104.2 55.17 1102.2 24.13 1102.2 17.56 1102.2 71.57 1102.2 63.14 1100.2 18.83 1100.2 49.28 1100.2 69.32 1100.2 6.24 1098.2 14.39 1098.2 58.03 1098.2 69.38 1098.2 48.68 1096.3 33.97 1096.3 41.88 1096.3 2.16 1096.3 50.97 1094.3 1.99 1094.3 53.99 1094.3 67.76 1094.3 62.88 1092.3 40.98 1092.3 37.82 1092.3 54.40 1092.3 37.91 1090.3 16.98 1090.3 25.41 1090.3 69.47 1090.3 4.30 1088.4 94.84 1088.4 65.26 1088.4 108.21 1088.4 54.88 1086.4 182.59 1086.4 226.24 1086.4 232.73 1086.4 199.72 1084.4 622.80 1084.4 581.63 1084.4 682.58 1084.4 555.93 1082.4 880.29 1082.4 886.55 1082.4 941.09 1082.4 873.64 1080.5 646.58 1080.5 681.16 1080.5 728.74 1080.5 587.41 1078.5 231.19 1078.5 238.33 1078.5 304.13 1078.5 273.47 1076.5 80.18 1076.5 62.49 1076.5 118.40 1076.5 97.88 1074.5 -11.36 1074.5 31.55 1074.5 89.44 1074.5 67.20 1072.6 15.94 1072.6 1.60 1072.6 59.11 1072.6 51.29 1070.6 6.29 1070.6 13.44 1070.6 43.72 1070.6 22.74 1068.6 -13.51 1068.6 43.64 1068.6 64.28 1068.6 37.17 1066.6 -14.68 1066.6 21.57 1066.6 35.35 1066.6 -4.21 1064.6 32.23 1064.6 0.35 1064.6 25.20 1064.6 33.16 1062.7 -26.43 1062.7 -22.81 1062.7 75.34 1062.7 11.58

Supplementary table 5h Raman Spectra points 36 to 39 taken from T. procerum shell 2TP4-2. See figure 12 in the text for point location along shell ontogeny. Each point has two columns representing wavenumber in cm-1 and intensity in arbitrary units, respectively.

76

Samples Distance from umbo (mm) Ba/Ca Sr/Ca Mg/Ca

29 67.9 0.16 217.03 92.7 28 66.7 0.08 179.40 93.5 27 64.5 0.03 177.72 60.9 26 57.2 0.15 174.88 69.0 25 54.4 0.49 194.99 81.6 24 51.3 0.30 188.42 74.4 23 50.1 0.40 201.15 81.1 22 48.8 0.39 199.69 77.9 21 46.5 0.45 206.95 69.2 20 44.1 0.41 207.18 74.7 19 42.3 0.32 201.39 67.1 18 40.3 0.33 197.26 70.5 17 37.4 0.33 202.44 73.0 16 35.9 0.30 196.43 91.3 15 33.9 0.25 187.99 72.9 14 31.6 0.61 200.19 95.9 13 28.4 0.35 175.66 86.4 12 25.6 0.14 171.00 74.1 11 21.3 0.13 163.51 81.2 10 19.2 -0.01 166.85 72.5 9 15.7 0.12 176.46 85.8 8 13.6 0.17 195.37 114.3 7 12 0.16 205.10 145.3 6 9.9 0.06 212.84 215.9 5 8 0.28 218.00 214.8 4 6.7 0.35 207.25 140.3 3 4.4 0.40 215.73 215.7 2 2.3 0.15 184.96 105.7 1 0 0.06 170.83 70.6

Supplementary table 6 Trace elements as ratios to calcium (millimoles/mole) in T. procerum shell. Samples were taken replicating Andrus et al. (2005) methodology.

77

4. RESERVOIR EFFECT VARIATION IN DONAX OBESULUS SHELLS FROM NORTHERN PERU: EVIDENCE FOR MEGA-EL NIÑO IN THE LATE HOLOCENE

4.1. Abstract

Modern pre-bomb and archaeological shells from the surf clam Donax obesulus were

analyzed for radiocarbon reservoir effect (∆R) and stable oxygen isotopes (δ18O) to characterize

late Holocene coastal upwelling conditions in northern Peru (8º14’S). Mean ∆R values from

these shells suggest that modern upwelling conditions in this region may have been established

between 539 and 1578 AD. Upwelling conditions at the 6th century seem less intense when

compared to present day. High frequency strong El Niño events or quasi stable El Niño-like

conditions may have caused the observed radiocarbon enrichment in coastal waters. These ∆R-

inferred marine conditions are in agreement with proposed “mega-El Niño” activity in proxy and

archaeological records ca. 475-530 AD. Mega-El Niño conditions have been linked to political

destabilization, societal transformation, and collapse of the Moche civilization in northern Peru.

4.2. Introduction

Vertical mixing off coastal Peru is a defining component of El Niño/Southern Oscillation

(ENSO). Upwelling of deep, cold water contributes to coastal aridity and exceptionally

productive marine ecosystems (Barber and Chavez, 1983). However, El Niño occurrences every

3 to 7 years reduce and replace deep cold water with nutrient-depleted warm surface water

(Barber and Chavez, 1983; Philander, 1990; Ortlieb and Macharé, 1993). Warm water along the

Peruvian coast leads to more humidity and rains (Barber and Chavez, 1983; Philander, 1990;

78

Ortlieb and Macharé, 1993). During normal and/or La Niña conditions, upwelling is sub-

thermocline, but during El Niño it becomes supra-thermocline (Huyer et al., 1987; Jones et al.,

2009). The depth of source water typically remains at 50 to 100 m despite different ENSO

conditions (Huyer et al., 1987). Since deep waters are depleted in radiocarbon (due to ventilation

age) and surface waters are enriched in it (due to greater atmospheric equilibration), upwelling

rates in an area can be inferred from water’s radiocarbon concentration (Toggweiler et al., 1991).

Materials precipitated from dissolved inorganic carbon (DIC), such as mollusk shells, record

ambient water radiocarbon concentration (Andrus et al., 2005; Jones et al., 2007, 2009;

McConnaughey and Gillikin, 2008; Poulain et al., 2010). Additionally, shell δ18O provides a

qualitative assessment of water temperature associated with upwelling (Andrus et al., 2005;

Jones et al., 2007, 2009).

∆R represents the 14C age difference (in 14C years) between regional and modeled-

global surface marine waters (see Stuiver and Braziunas, 1993; Ascough et al., 2005). ∆R is a

function of local vertical mixing in water of different ventilation ages at a particular moment in

time (Stuiver and Braziunas, 1993; Jones et al., 2007). Thus, positive ∆R values represent a local

reduction in water’s radiocarbon content associated with increases in cold-deep water upwelling

(Toggweiler et al., 1991; Andrus et al., 2005; Ascough et al., 2005; Jones et al., 2007, 2009).

Meanwhile, negative ∆R values represent a local enrichment in radiocarbon content associated

with reductions in cold-deep water upwelling (Toggweiler et al., 1991; Andrus et al., 2005;

Ascough et al., 2005; Jones et al., 2007, 2009). Assessment of ∆R change through time may

contribute to reconstructions of paleoupwelling conditions in coastal areas such as northern Peru.

Northern Peruvian coastal upwelling variations during the 20th century have been

determined from modern pre-bomb ∆R data (Jones et al., 2007, 2009; Chapter 1 in this

79

dissertation). However, proxy reconstructions of late Holocene upwelling rely on other ENSO

characteristics such as water temperature (e.g. Hendy et al., 2002; Cobb et al., 2003) or rain (e.g.

Rodbell et al., 1999; Haug et al., 2001; Moy et al., 2002; Rein et al., 2005) from which general

upwelling conditions are inferred. Molluscan ∆R data more directly assess late Holocene

upwelling. We selected D. obesulus clams for analysis based on their ability to survive El Niño

SST conditions (Arntz et al., 1987; Chapter 1), and its abundance in modern and archaeological

record (Arntz et al., 1987; Roselló et al., 2001; Sandweiss et al., 2001).

ENSO reconstruction may provide crucial information about the relationship between

climate and human behavior. Environmental changes contributed to upheaval in complex

societies, such as the Akkad, Mayan, and the Moche (deMenocal, 2001; Dillehay et al., 2004).

The Moche were an economically and politically complex culture organized in competing

polities that dominated the northern Peruvian coast ca. 100 to 750 AD south of the Sechura

desert (deMenocal, 2001; Dillehay and Kolata, 2004). ENSO-related torrential rains may have

disrupted the Moche’s environment so drastically that it motivated political reorganization

around 600 AD (deMenocal, 2001; Dillehay et al., 2004; Uceda-Castillo, 2006) For example, the

Moche constructed two monumental adobe structures having religious and political functions in

the Moche valley of coastal northern Peru, Huaca de la Luna and Huaca del Sol (Shimada et al.,

1991; deMenocal, 2001; Uceda-Castillo, 2006). Political power shifts caused abandonment of

Huaca de la Luna which preceded the Moche political collapse ca. 800 AD (deMenocal, 2001;

Dillehay and Kolata, 2004; Dillehay et al., 2004; Uceda-Castillo, 2006). A new political order

was achieved in the Moche Valley with the Chimu emergence ca. 1100 (Dillehay and Kolata,

2004; Dillehay et al., 2004). Later, the Chimu were politically assimilated into the Inca (late 15th

century) and Spanish (16th century) Empires (Gomez-Cumpa, 2002; Dillehay and Kolata, 2004).

80

The Moche example shows how unforeseen climatic events affecting environmental condition

under which a society has flourished may trigger profound political transformations severing

elite political control over the general public. Our analysis of samples from Huaca de la Luna

adds more data to these reconstructions.

4.3. Materials and Methodology

All of our shells were captured or excavated near the Moche Valley region (8º14’S figure

13). We calculated the shells’ ∆R values by subtracting modeled global ocean radiocarbon ages

(Hughen et al., 2004) from the shells measured radiocarbon age at shells’ true calendrical age

(see Jones et al., 2007; chapter 1 this dissertation). Modeled global ocean ages (Hughen et al.,

2004) used for calculating ∆R values depend on independent knowledge of the true calendrical

age of the shell. ∆R values for the studied intervals were calculated by averaging (following

Long and Rippeteau, 1974) several individual ∆R values obtained from single (modern pre-

bomb) or multiple (archaeological) D. obesulus shells. The shells’ high resolution ∆R analyses

were done in order to detect sub-seasonal upwelling variation (see Jones et al., 2007; chapter 1

this dissertation).

One modern pre-bomb D. obesulus was collected on October 19th 1926 and archived in

the Smithsonian Institution until it was lent for analyses. This shell lived mostly through Normal

ENSO conditions based on its age at capture (see Chapter 1); the shell started growing after a

brief but very strong El Niño occurring in early 1925 (Glynn, 1988). Because this shell lived 24

years BP, a modeled global marine age of 451±23 14C years (see Hughen et al., 2004) was used

to calculate its ten ∆R values. From these ∆R values a weighted average, equivalent to a whole

shell analysis ∆R (Jones et al., 2007), was calculated for 1926 AD.

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Figure 13 Map showing field area where modern and ancient Donax obesulus shells were collected (denoted by star).

82

Two 16th century archaeological shells came from the wall of a trench directly above

flood deposits dated from the 1578 El Niño separating pre-Columbian and colonial remains in

the early Spanish settlement of Magdalena de Cao Viejo (Daniel H. Sandweiss personal

communication, 2010). An AMS radiocarbon date obtained from a tobacco sample places the

settlement occupation between 1390 and 1640 cal 14C years AD (see

http://140.247.102.177/mcv/Other%20Artifacts.htm). This date is supported by historical data

showing that Magdalena de Cao Viejo was an important regional Spanish settlement between

1560 to ca. 1650 AD (Gomez-Cumpa, 2002). Based on shells stratigraphical position and

settlement radiocarbon and historical data we estimate their calendrical age as between 1578 and

1640 AD. The 1625 AD global marine age of 708±23 14C years (see Hughen et al., 2004) was

used for calculating both shells’ internal ∆R values. A total of nine ∆R values produced the

reported 1625 AD weighted ∆R average.

The 6th century archaeological shells were excavated from tombs inside Huaca de la Luna

(see Uceda-Castillo, 2006; Zabaleta-Paredes, 2006). A total of six shells associated with human

remains were analyzed (three shells per tomb). The burials and their contents were left as

offerings by the Moche to signify the importance of a sacred enclosure renovation (Zabaleta-

Paredes, 2006). The tombs’ stratigraphic positions place them between 500 and 600 AD, likely

in the earlier time of the interval (Uceda-Castillo personal communication, 2009). Further age

constraint was made by AMS radiocarbon dating of short-lived plant material (canes) associated

with the shells in the tombs. Two statistically undistinguishable (1σ) radiocarbon ages (1653±45

and 1627±39 14C years) obtained from cane remains were calibrated using the Calib 6.0 program

(Stuiver and Reimer, 1993). Calibrated ages (2σ) were 340-539 and 321-474 AD. The

intersection of this dates plus archaeological time constrains for the tombs allow us to estimate

83

the calendrical age of the shells to between 474 and 539 AD. A value of 1899±26 14C years for

515 AD (see Hughen et al., 2004), representing the mean modeled global marine age for the

period, was used for calculating shells’ twelve ∆R values. Those twelve values were used for

calculating a weighted ∆R average for 515 AD. Different period shells were sampled at high

resolution from umbo to edge for δ18O. See appendix for detailed laboratory methods.

4.4. Results

D. obesulus’ ∆R range during 515 AD is almost three times wider than 1625 AD range

and twice as wide as 1926 AD range (figure 14 and table 3). Overlapping positive ∆R values are

observable for the three ranges (figure 14 and table 3). ∆R range for 1926 AD encompasses

completely the data from 1625 AD (figure 14). 515 AD is the only period showing negative ∆R

values (figure 14 and table 3). Mean weighted ∆R values for 1926 AD and 1625 AD are

indistinguishable within analytical precision (p=0.9983, p>0.05) (figure 14 and table 4). Marked

differences in weighted ∆R averages within analytical precision are observable for 1926/1625

and 515 AD periods (p=0.000135, p<0.05) (figure 14 and table 4). The widest δ18O ranges are

presented in 20th century shells while the narrowest is presented by a shell from 515 AD (figure

15). Shells with the most positive δ18O ranges are from the 16th century, while the most negative

δ18O ranges are from the 20th century (figure 15). A tendency toward more negative δ18O values

is observed toward the present (figure 15). However, there are similarities among mean δ18O

values from shells of different periods (figure 15).

84

Figure 14 Individual Donax obesulus ∆R (grey open diamonds) ranges and weighted ∆R average (solid black diamonds) for the late Holocene in Moche Valley northern Peru. Horizontal grey and black lines represent ∆R standard deviation in 14C years. X axis scale is in years AD, and Y axis scale is in 14C years.

85

4.5. Discussion

For the Moche Valley, comparisons of average ∆R for the 20th and 16th centuries revealed

closely matching ∆R magnitudes (figure 14). We thus infer similar deep water upwelling

conditions in northern Peru for these two periods. The similarity between modern and 16th

century upwelling rates suggest dominance of “Normal” ENSO conditions, as defined for the

twentieth century, for at least these two intervals within the last 400 yrs. This ENSO mode is

supported by coral δ18O records from the Great Barrier Reef (Hendy et al., 2002) and Palmyra

Island (Cobb et al., 2003) suggesting long term stability in evaporation rates and SST for the

western Pacific after the 16th century. El Niño frequency/intensity reduction registered in

sediment cores across the Pacific between 1500 and 1900 AD (Rodbell et al., 1999; Moy et al.,

2002; Reidinger et al; 2002; Rein et al; 2005; Langton et al., 2008) may be expressions of this

ENSO mode stability. Interestingly, δ18O range comparison suggests a generally colder SST for

16th than for 20th century (figure 15). Since similar upwelling conditions are inferred for both

centuries, colder SST during the 16th century may be consequence of other factors such as

reduced solar insolation (Steinhilber et al., 2009).

The early 6th century was characterized by 14C enrichment in coastal waters in the Moche

Valley (see negative ∆R in figure 13 and tables 3 and 4). This may be explained by two, possibly

related, mechanisms: 1: Deep water upwelling reduction generated by quasi-stable El Niño

conditions and 2: Higher than modern El Niño frequency generating radiocarbon enrichment of

surface water. Both mechanisms may have caused torrential rains and flooding as is recorded in

the archaeological record (Meggers, 1994; Bourget, 1998; Dillehay and Kolata, 2004; Dillehay et

al., 2004; Uceda-Castillo, 2006) and associated with a Mega-El Niño event (Wells, 1990;

Mörner, 1993; Meggers, 1994; Uceda-Castillo, 2006).

86

Figure 15 Donax obesulus δ18O averages (solid black triangles) and ranges (grey boxes) for the late Holocene in Moche Valley northern Peru. Middle, upper, and lower box lines represent δ18O median, 75th, and 25th percentiles respectively. Measured δ18O individual values (not shown) for each shell had 1σ of 0.10 based on repeated analyses of NBS-19. Vertical grey and black lines are δ18O series standard deviation in VPDB per mil (‰). δ18O range for 2006 shell is from Etayo-Cadavid unpublished data (see appendix 3). X axis scale is in years AD, and Y axis scale is in VPDB ‰.

87

Based on the tombs’ archaeological context (Zabaleta-Paredes, 2006), and the molluscan

assemblages indicative of cold waters (Roselló et al., 2001; Zabaleta-Paredes, 2006) we think it

is unlikely for the analyzed shells to have lived during an El Niño event resembling those seen in

the 20th century. This is supported by D. obesulus 6th century δ18O data (figure 15) that do not

show the extreme negative values associated with 20th century El Niño events (Andrus et al.,

2005). Thus, our ∆R and δ18O data (figures 14 and 15) may be indicative of “Normal” ENSO

conditions associated with “Mega-El Niño’s” described to have occurred in the 6th century.

Based solely on molluscan ∆R and δ18O (figures 14 and 15) it is extremely difficult to

differentiate which one of the proposed mechanisms (quasi-stable/high frequency) may be the

main factor behind 6th century Mega-El Niño. However, other Pacific proxy data for El Niño

may help pinpoint which cause is the most likely.

Mega-El Niño-related disruptions to Moche life are evident in flood-derived fine grained

sediments covering irrigation channels that fed cultivation areas (Shimada et al., 1991; Dillehay

and Kolata, 2004; Dillehay et al., 2004), and erosional surfaces found in residential and

ceremonial structures in northern Peru (Shimada et al., 1991; Meggers, 1994; Dillehay and

Kolata, 2004; Dillehay et al., 2004). These adverse environmental conditions may have

stimulated internal social conflict and even warfare within the Moche society (Shimada et al.,

1991; Dillehay and Kolata, 2004; Dillehay et al., 2004). Finally, social upheaval triggered Moche

political reorganization resulting in the abandonment of coastal ceremonial areas such as Huaca

de la Luna (Bourget, 1998; Shimada et al., 1991; Dillehay et al., 2004; Uceda-Castillo, 2006).

Our negative ∆R value is the first paleoupwelling evidence for potential Mega-El Niño oceanic

conditions directly associated to the Moche political collapse and may additionally suggest

diminishment of coastal productivity that may have further contributed to difficult economic and

88

1926 AD 1625 AD 515 AD

Average Range Average Range Average Range

Age 14

C yrs 582±16* 191 840±15* 135 1824±12* 380

∆∆∆∆R 14

C yrs 136±18* 191 136±17* 135 -82±14* 380

Table 3 ∆R statistical data for the three studied periods within the late Holocene. Asterisk indicates weighted average calculated by Long and Rippeteau (1974) method.

89

Lab # Sample # Years AD mm δδδδ13

C 14

C Age ∆∆∆∆R AA69002 368497-01 1926 11.4 0.89 605±36 154±43 AA69003 368497-02 10.3 0.45 575±53 124±58 AA69004 368497-03 9.2 0.27 497±71 46±75 AA69005 368497-04 8.2 0.80 642±46 191±51 AA69006 368497-05 7.3 1.00 584±53 133±58 AA69007 368497-06 5.8 0.50 578±50 127±55 AA69008 368497-07 4.7 0.44 569±69 118±73 AA69009 368497-08 3.8 0.59 602±77 151±80 AA69010 368497-09 2.5 0.64 521±34 70±41 AA69011 368497-10 1.3 0.94 688±55 237±60 AA87662 Doebic1-01 1625 14.3 0.47 831±35 123±42 AA87663 Doebic1-02 10.7 0.40 875±64 167±68 AA87664 Doebic1-03 8.2 0.90 878±47 170±52 AA87665 Doebic1-04 5.2 0.90 822±65 114±69 AA87666 Doebic1-05 3.6 0.80 818±67 110±71 AA87667 Doebic2-01 15.6 0.51 830±31 122±39 AA87668 Doebic2-02 11.6 0.46 779±44 71±50 AA87669 Doebic2-03 9.2 0.40 820±71 112±75 AA87670 Doebic2-04 6.7 0.80 914±40 206±46 AA87680 Dohlt35-1.01 515 13.3 0.81 1881±51 -18±57 AA87681 Dohlt35-1.02 10.9 0.71 1782±36 -117±44 AA87682 Dohlt35-1.03 8.4 0.48 1701±57 -198±63 AA87683 Dohlt35-2.02 12.3 0.87 1592±41 -307±49 AA87684 Dohlt35-2.03 10.2 0.97 1697±42 -202±49 AA87687 Dohlt35-3.01 11.6 0.91 1893±36 -6±44 AA87688 Dohlt35-3.02 9.2 1.10 1972±37 73±45 AA87689 Dohlt35-3.03 3.5 1.04 1963±36 64±44 AA87678 Dohlt34-1.01 12.3

0.80 1674±51 -225±57

AA87679 Dohlt34-2.01 12.3

0.98 1669±37 -230±45 AA87685 Dohlt34-3.01 11.8 0.04 1920±37 21± 45 AA87686 Dohlt34-3.02 5.3 1.40 1915±41 16±49

Table 4 Radiocarbon data for D. obesulus showing calibrated AD ages for the shells, each sample collection distance from the umbo in millimeters, δ13C correction values for each radiocarbon sample, uncalibrated radiocarbon ages, and reservoir effect correction ages. Uncalibrated and reservoir effect correction ages are reported with 1σ errors. ∆R calculations use mixing marine modeled layers radiocarbon ages from Marine04 (Hughen et al., 2004) of 451±23 yrs for 1926, 708±23 yrs for 1625 AD, and 1899±26 yrs for 515 AD.

90

political conditions at this time. Our ∆R data slightly pre-date other Mega-El Niño proxy

evidence and may suggest that Mega-El Niño started earlier than originally believed.

4.6. Conclusions

Vertical mixing rates for northern Peru between the early 20th (1926 AD) and 16th (1625

AD) centuries are similar. Diminished upwelling conditions existed here during the 6th (515 AD)

century. Negative ∆R values, local archaeological evidence, and proxy data from different

Pacific locations suggest Mega-El Niño conditions for the early 6th century. More molluscan ∆R

data are necessary to provide a more detailed picture of upwelling changes through time,

nevertheless our data suggest that modern upwelling conditions in northern Peru were

established somewhere in between 539 and 1578 AD.

4.7. Acknowledgements

We are grateful to the staff of Invertebrate Zoology at the National Museum of Natural History,

Smithsonian Institution, Washington DC for loan of modern pre-bomb specimens and permission

to take samples. We are grateful as well to Santiago Uceda from Universidad Nacional de

Trujillo and Jeffrey Quilter from Harvard University for loan of archaeological material and

permission to take samples. Also, we would like to thank Joe Lambert from the Department of

Geological Sciences Stable Isotope Laboratory at The University of Alabama and the staff of the

NSF-Arizona AMS facility for their help in the stable isotope and radiocarbon analyses. The

corresponding author of this paper would like to thank Kelley Rich and Robin Cobb from

Department of Geological Sciences at The University of Alabama for work done during the

project. Commentaries from Daniel H. Sandweiss and Alberto Pérez-Huerta helped in the

improvement of the earlier manuscript. The corresponding author wants to thank the Etayo-

91

Cadavid fund for financial support. This research was funded by National Science Foundation

(NSF) grant ESH - OCE-0502533 PI’s Andrus, Hodgins, and Sandweiss.

4.8. Laboratory methods

Shells were milled for radiocarbon from umbo to edge previous removal of first 10 µm of

shell to avoid contamination (see Jones et al., 2007; chapter 1 this dissertation). Radiocarbon

samples were reacted in orthophosphoric acid (1926 shell see chapter 1 this dissertation) or

hydrophosphoric acid (archaeological shells) under vacuum, resultant CO2 was converted into

graphite following the methodology of Slota et al. (1987) and analyzed at the National Science

Foundation (NSF) University of Arizona AMS facility. D. obesulus uncalibrated radiocarbon

ages were converted into ∆R values following Jones et al., (2007) methodology.

Samples for stable isotope analysis were milled using 0.08 mm bits and averaged about

70 µg/sample. Samples were milled in a series of continuous transects along the shell’s growth

lines from umbo to edge. The maximum overall milling depth was 150 micrometers. After

collection, the carbonate powder was weighed and stored in glass vials for their subsequent

digestion with phosphoric acid. The samples were analyzed on a Thermo GasBench II coupled to

a Thermo Delta Plus isotope ratio mass spectrometer (IRMS). The mean precision (1σ) of the

measurements is 0.1 per mil for oxygen based on multiple NBS 19 analyses in each sample run.

See appendices 1 and 3 for data.

92

4.9. References

Andrus, C.F.T., Hodgins, G.W.L., Sandweiss, H.D. and Crowe, D.E, 2005, Molluscan

radiocarbon as a proxy for El Niño-related upwelling variation in Peru: Geological Society of America Special Paper 395, p. 13-20.

Ascough, P., Cook, G., and Dugmore, A., 2005, Methodological approaches to determining the

marine radiocarbon reservoir effect: Progress in Physical Geography, v. 29, p. 532-547. Arntz, W.E., Brey, T., Tarazona, J., and A. Robles, 1987, Changes in the Structure of Shallow

Sandy-Beach Community in Peru During an El Niño Event: South African Journal of marine Sciences, v. 5, p. 645-658.

Barber, R.T., and Chavez, F.P., 1983, Biological consequences of El Niño: Science, v. 222, p.

1203-1210. Bourget, S., 1998, Practiques Sacrificielles et Funéraires au site Moche de La Huaca de La Luna,

Côte nurd du Pérou Bull. l'Institut Français d'Études Andines, v. 27, p. 41-74. Cobb, K.M., Charles, C.D., Cheng, H., and Edwards, R.L., 2003, El Niño/Southern Oscillation

and tropical Pacific climate during the last millennium: Nature, v. 424, p. 271-276.

Conroy, J.L., Overpeck, J.T., Cole, J.E., Shanahan, T.M., and Steinitz-Kannan, M. , 2008, Holocene changes in eastern tropical Pacific climate inferred from a Galápagos lake sediment record: Quaternary Sciences Reviews, v. 27, p. 1166-1180.

deMenocal, P.B., 2001, Cultural response to Climate Change During the Late Holocene: Science, v. 292, p. 667-673.

Dillehay, T., and Kolata, A.L., 2004, Long-term human response to uncertain environmental conditions in the Andes: Proceedings of the National Academy of Sciences, v. 101, p. 4325-4330.

Dillehay, T., Kolata, A.L., and Pino Q, M., 2004, Pre-industrial human and environment interactions in northern Peru during the late Holocene: The Holocene, v. 14, p. 272-281.

Gomez-Cumpa, J., 2002, Una economía Regional en el Norte del Peru: El obispado de Truxillo del Perú entre los siglos XVI-XVIII Revista de Educación, Cultura y Sociedad, v. 2, p. 77-92.

Grossman, E.L., Ku, T-L, 1986, Oxygen and carbon isotope fractionation in biogenic aragonite:

Temperature effects Chemical Geology, v. 59, p. 59-74.

Haug, G.H., Hughen, K.A., Sigman, D.M., Peterson, L.C., and Röhl, U., 2001, Southward Migration of the Intertropical Convergence Zone Through the Holocene Science, v. 17, p. 1304-1308.

93

Helama, S., Meriläinen, J., and Tuomenvirta, H., 2009, Multicentennial megadrought in northern Europe coincided with a global El Niño–Southern Oscillation drought pattern during the Medieval Climate Anomaly: Geology, v. 37, p. 175-178.

Hendy, E.J., Gagan, M.K., Alibert, C.A., McCulloch, M.T., Lough, J.M., and Isdale, P.J., 2002, Abrupt Decrease in Tropical Pacific Sea Surface Salinity at the End of Little Ice Age: Science, v. 295, p. 1511-1514.

Hughen K, B.M., Bard E, Beck JW, Bertrand CJ, Blackwell PG, Buck CE, Burr GS, Cutler KB, Damon PE, Edwards RL, Fairbanks RG, Friedrich M, Guilderson TP, Kromer B, McCormac FG, Manning S, Bronk Ramsey C, Reimer PJ, Reimer RW, Remmele S, Southon J, Stuiver M, Talamo S, Taylor FW, van der Plicht J, Weyhenmeyer CE., 2004, Marine04 marine radiocarbon age calibration, 0–26 cal kyr BP: Radiocarbon, v. 46, p. 1059-1086.

Huyer, A., Smith, R.L, Paluszkiewicz, T, 1987, Coastal Upwelling off Peru during normal and El

Niño times, 1981-1984: Journal of Geophysical Research Oceans, v. 92, p. 14297-14307.

Jones, P.D., Osborn, T,J., and Briffa, K.R. , 2001, The Evolution of Climate Over the Last Millenium: Science, v. 292, p. 662-667.

Jones, K.B., Hodgins, G.W.L., Dettman, D.L., Andrus, C.F.T., Nelson, A. Etayo-Cadavid, M.F.,

2007, Seasonal variation in Peruvian Marine Reservoir Age from Pre-Bomb Argopecten purpuratus Shell Carbonate: Radiocarbon, v. 49, p. 877-888.

Jones, K.B., Hodgins, G.W.L., Etayo-Cadavid, M.F., and Andrus, C.F.T., 2009, Upwelling

signals in radiocarbon from early 20th-century Peruvian bay scallop (Argopecten

purpuratus) shells: Quaternary Research, v. 72, p. 452-456. Koutavas, A., Lynch-Stieglitz, J., Marchitto Jr, T.M., and Sachs, J.P., 2002, El Niño–Like

Pattern in Ice Age Tropical Pacific Sea Surface Temperature: Science, v. 297, p. 226-230.

Langton, S.J., Linsley, B.K., Robinson, R.S., Rosenthal, Y., Oppo, D.W., Eglinton, T.I., Howe, S.S., Djajadihardja, Y.S., and Syamsudin, F., 2008, 3500 yr record of centennial-scale climate variability from the Western Pacific Warm Pool: Geology, v. 36, p. 795-798.

Long, A., and Rippeteau, B., 1974, Testing contemporaneity and averaging radiocarbon dates: American Antiquity, v. 39, p. 10.

Mann, M.E., Cane, M.A., Zebiak, S.E., and Clement, A. , 2005, Volcanic and Solar Forcing of the Tropical Pacific over the Past 1000 Years: Journal of Climate, v. 18, p. 447-456.

McConnaughey, T.A., and Gillikin, D.P., 2008, Carbon isotopes in mollusk shell carbonates: Geo-Mar-Lett, v. 28, p. 287-299.

94

Meggers, B.J., 1994, Arqueological evidence for the impact of Mega-El Niño events on Amazonia during the past two millennia. Climatic change, v. 28, p. 321-338.

Mörner, N.-A., 1993, Present El Niño-ENSO events and Past Super ENSO-events: Bulletin l'Institut Français d'Études Andines, v. 22, p. 3-12.

Moy, C.M., Seltzer,G.O., Rodbell, D.T., Anderson, D.M, 2002, Variability of El Niño/Southern

Oscillation activity at millennial timescales during the Holocene epoch: Nature, v. 420, p. 162-165.

Ortilieb, L., Fournier, M., and Macharé, J., 1993, Beach-ridges series in northern Peru:

chronology, correlation, and relationship, with major late Holocene El Niño events Bulletin l'Institut Français d'Études Andines, v. 22, p. 191-212.

Ortilieb, L., and Macharé, J, 1993, Former El Niño events: records from western South America:

Global and Planetary Change, v. 7, p. 181-202.

Philander, S.G.H., 1985, El Niño and La Niña: Journal of Atmospheric Sciences, v. 42, p. 2652-2662.

Poulain, C., Lorrain, A., Gillikin, D.P., Dehairs, F., Robert, R., and Paulet, Y.-M., 2010, Experimental shift of diet and DIC stable carbon isotopes: Influence on shell δ13C values in the Manila clam Ruditapes philippinarum: Chemical Geology, v. 272, p. 75-82.

Quinn, H.W., Neal, V.T, and Antunez de Mayolo, S.E., 1987, El Niño Occurrences Over the Past Four and a Half Centuries: Journal of Geophysical Research, v. 92, p. 14449-14461.

Rein, B., Lückge, A., Reinhardt, L., Sirocko, F., Wolf, A., and Dullo, W-C., 2005, El Niño

variability off Peru during the last 20,000 years: Palaeogeography, v. 20, p. 1-17.

Rein, B., 2007, How do the 1982/83 and 1997/98 El Niños rank in a geological record from Peru?: Quaternary International, v. 161, p. 56-66.

Rodbell, D.T., Seltzer, G.O., Anderson, D.E., Abbott, M.B., Enfield, D.B., and Newman, J.H.,

1999, A 15,000 year record of El Niño-driven alluviation in sothwestern Ecuador: Science, v. 283, p. 516-520.

Roselló, E., Vásquez, V., Morales, A., Rosales, T., 2001, Marine Resources from an Urban

Moche (470-600 A.D.) Area in the 'Huacas del Sol y de la Luna' Archaeological Complex (Moche Valley, Peru): International Journal of Osteoarchaeology, v. 11, p. 72-81.

Sandweiss, D.H., Richardson III, J.B., Reitz, E.J., Rollins, H.B., and Maasch, K.A. , 1996, Geoarcheological Evidence from Peru for a 5000 years B.P. Onset of El Niño Science, v. 273, p. 1531-1533.

95

Sandweiss, D.H., Richardson III, J.B., Reitz, E.J., Rollins, H.B., and Maasch, K.A.. 1997, Determining the Early History of El Niño: Science, v. 276, p. 965-967.

Sandweiss, D.H., Maasch, K.A., Burger, R.L., Richardson III, J.B., Rollins, H.B., and Clement,

A., 2001, Variation in Holocene El Niño frequencies: Climate records and cultural consequences in ancient Peru: Geology, v. 29, p. 603-606.

Sandweiss, D.H., Maasch, K.A., Chai, F., Andrus, C.F.T., Reitz, E.J., 2004, Geoarchaeological

evidence for multidecadal natural climatic variability and ancient Peruvian fisheries: Quaternary Research, v. 61, p. 330-334.

Shindell, D.T., Schmidt, G.A., Mann, M.E., Rind, D., and Waple, A., 2001, Solar Forcing of Regional Climate Change During the Maunder Minimum: Science, v. 294, p. 2149-2152.

Shimada, I., Shaaf, C.B., Thompson, L.G., Mosley-Thomson, E., 1991, Cultural Impacts of

Severe Droughts in the Prehistoric Andes: Application of a 1,500-Year Ice Core Precipitation Record: World Archaeology, v. 22, p. 247-270.

Sicart, J.E., Ribstein, P., Francou, B., Pouyaud, B., and Condom, T, 2007, Glacier mass balance

of tropical Zongo glacier, Bolivia, comparing hydrological and glaciological methods: Global and Planetary Change, v. 59, p. 27-36.

Slota, P.J., Jull, A.J.T., Linick, T.W., Toolin, L.J., 1987, Preparation of small samples for 14C

accelerator targets by catalytic reduction of CO: Radiocarbon v. 29, p. 303-306. Steinhilber, F., Beer, J., and Fröhlich, C, 2009, Total solar irradiance during the Holocene:

Geophysical Research Letters, v. 36. Stuiver, M., Pearson, Gordon W., Braziunas, Thomas F 1986, Radiocarbon age calibration of

marine samples back to 9000 cal yr BP.: Radiocarbon, v. 28, p. 980-1021.

Stuiver, M., and Reimer, P.J., 1993, Extended 14C Data Base and Revised CALIB 3.0 14C Age Calibration Program: Radiocarbon, v. 35, p. 215-230.

Thompson, L.G., Mosley-Thompson, E., Bolzan, J.F., Koci, B.R., 1985, A 1500-Year Record of Tropical Precipitation in Ice Cores from the Quelccaya Ice Cap, Peru: Science, v. 229, p. 971-973.

Trenberth, K.E., 1997, The Definition of El Niño: Bulletin of the American Meteorological Society, v. 78, p. 2771-2777.

Toggweiler, J.R., Dixon, K., Broecker, W.S., 1991, The Peru Upwelling and the Ventilation of the South-Pacific Thermocline: Journal of Geophysical Research-Oceans v. 96, p. 20467-20497.

96

Uceda-Castillo, S., 2006, Huacas del Sol y de La Luna: Cien años después de los Trabajos de Max Uhle in Uceda, S., and Morales, R., ed., Proyecto Arqueológico Huaca de la Luna: Moche Valley, Universidad Nacional de Moche Valley, p. 581.

Zabaleta-Paredes, L.E., 2006, Investigaciones en la Unidad 16 en Huaca de la Luna, in Uceda, S., and Morales, R,, ed., Proyecto Arqueológico Huaca de la Luna: Moche Valley, Universidad Nacional de Moche Valley, p. 581.

Wells, L.E., 1990, Holocene History of the El Niño phenomenon as recorded in flood sediments of northern coastal Peru: Geology, v. 18, p. 1134-1137.

97

4.10. Appendix 3

Sample δδδδ

18O

VPBD

(‰)

Dist

umbo

(mm)

Sample δδδδ

18O

VPBD

(‰)

Dist

umbo

(mm)

Sample δδδδ

18O

VPBD

(‰)

Dist

umbo

(mm)

D06-001 -0.6 0.0 D06-035 -1.0 5.1 D06-069 -1.6 10.2 D06-002 -0.8 0.2 D06-036 -1.0 5.3 D06-070 -1.4 10.4 D06-003 -1.7 0.3 D06-037 -0.9 5.4 D06-071 -1.2 10.5 D06-004 -1.4 0.5 D06-038 -0.6 5.6 D06-072 -1.7 10.7 D06-005 -1.0 0.6 D06-039 -1.1 5.7 D06-073 -1.2 10.8 D06-006 -1.2 0.8 D06-040 -1.1 5.9 D06-074 -1.0 11.0 D06-007 -1.2 0.9 D06-041 -0.9 6.0 D06-075 -1.4 11.1 D06-008 -1.1 1.1 D06-042 -1.5 6.2 D06-076 -1.0 11.3 D06-009 -1.4 1.2 D06-043 -1.0 6.3 D06-077 -0.6 11.4 D06-010 -1.1 1.4 D06-044 -1.2 6.5 D06-078 -1.1 11.6 D06-011 -1.1 1.5 D06-045 -1.2 6.6 D06-079 -0.6 11.7 D06-012 -1.0 1.7 D06-046 -1.1 6.8 D06-080 -1.2 11.9 D06-013 -0.9 1.8 D06-047 -1.1 6.9 D06-081 -1.1 12.0 D06-014 -0.9 2.0 D06-048 -1.0 7.1 D06-082 -0.8 12.2 D06-015 0.0 2.1 D06-049 -1.1 7.2 D06-083 -1.1 12.3 D06-016 -1.1 2.3 D06-050 -1.4 7.4 D06-084 -0.8 12.5 D06-017 -1.2 2.4 D06-051 -1.4 7.5 D06-085 -0.9 12.6 D06-018 -1.0 2.6 D06-052 -1.4 7.7 D06-086 -0.7 12.8 D06-019 -1.2 2.7 D06-053 -1.5 7.8 D06-087 -0.4 12.9 D06-020 -0.9 2.9 D06-054 -1.4 8.0 D06-088 -0.4 13.1 D06-021 -1.3 3.0 D06-055 -1.7 8.1 D06-089 -0.4 13.2 D06-022 -0.2 3.2 D06-056 -1.6 8.3 D06-090 -0.2 13.4 D06-023 -0.9 3.3 D06-057 -1.3 8.4 D06-091 -0.1 13.5 D06-024 -1.0 3.5 D06-058 -1.7 8.6 D06-092 -0.1 13.7 D06-025 -1.1 3.6 D06-059 -1.8 8.7 D06-093 -0.3 13.8 D06-026 -1.2 3.8 D06-060 -2.3 8.9 D06-094 0.2 14.0 D06-027 -1.1 3.9 D06-061 -2.2 9.0 D06-095 -0.2 14.1 D06-028 -1.4 4.1 D06-062 -2.0 9.2 D06-096 -0.3 14.3 D06-029 -1.3 4.2 D06-063 -1.9 9.3 D06-097 0.1 14.4 D06-030 -1.5 4.4 D06-064 -1.8 9.5 D06-098 -0.3 14.6 D06-031 -0.3 4.5 D06-065 -2.0 9.6 D06-099 -0.1 14.7 D06-032 -0.9 4.7 D06-066 -1.8 9.8 D06-100 -0.3 14.9 D06-033 -0.9 4.8 D06-067 -1.8 9.9 - - -

D06-034 -0.9 5.0 D06-068 -1.8 10.1 - - -

Supplementary table 7 Stable oxygen data for D. obesulus shell collected in Huanchaquito (8º 14' S) during 2006. Stable isotope is reported in parts per mil (‰) VPDB. Distance from umbo in mm uncorrected for shell curvature.

98

Sample δδδδ

13C

VPBD (‰)

Dist

umbo

(mm)

Sample δδδδ

13C

VPBD (‰)

Dist

umbo

(mm)

Sample δδδδ

13C

VPBD (‰)

Dist

umbo

(mm)

D06-001 0.8 0.0 D06-035 0.9 5.1 D06-069 0.4 10.2 D06-002 1.0 0.2 D06-036 0.8 5.3 D06-070 0.4 10.4 D06-003 0.6 0.3 D06-037 0.9 5.4 D06-071 0.3 10.5 D06-004 0.8 0.5 D06-038 1.0 5.6 D06-072 0.0 10.7 D06-005 0.7 0.6 D06-039 0.8 5.7 D06-073 0.2 10.8 D06-006 0.4 0.8 D06-040 0.8 5.9 D06-074 0.3 11.0 D06-007 0.4 0.9 D06-041 0.8 6.0 D06-075 0.2 11.1 D06-008 0.5 1.1 D06-042 0.2 6.2 D06-076 0.2 11.3 D06-009 0.5 1.2 D06-043 0.4 6.3 D06-077 0.3 11.4 D06-010 0.7 1.4 D06-044 0.1 6.5 D06-078 0.0 11.6 D06-011 0.7 1.5 D06-045 0.1 6.6 D06-079 0.3 11.7 D06-012 0.7 1.7 D06-046 0.1 6.8 D06-080 0.1 11.9 D06-013 0.8 1.8 D06-047 0.0 6.9 D06-081 0.2 12.0 D06-014 0.7 2.0 D06-048 0.2 7.1 D06-082 0.3 12.2 D06-015 1.4 2.1 D06-049 0.0 7.2 D06-083 0.2 12.3 D06-016 0.9 2.3 D06-050 0.0 7.4 D06-084 0.1 12.5 D06-017 1.0 2.4 D06-051 0.1 7.5 D06-085 0.0 12.6 D06-018 1.1 2.6 D06-052 0.4 7.7 D06-086 -0.1 12.8 D06-019 0.9 2.7 D06-053 0.8 7.8 D06-087 0.0 12.9 D06-020 0.9 2.9 D06-054 1.2 8.0 D06-088 0.0 13.1 D06-021 0.6 3.0 D06-055 1.1 8.1 D06-089 0.1 13.2 D06-022 1.0 3.2 D06-056 1.3 8.3 D06-090 0.1 13.4 D06-023 0.8 3.3 D06-057 1.5 8.4 D06-091 0.3 13.5 D06-024 0.9 3.5 D06-058 1.2 8.6 D06-092 0.3 13.7 D06-025 1.2 3.6 D06-059 1.0 8.7 D06-093 0.3 13.8 D06-026 1.4 3.8 D06-060 0.7 8.9 D06-094 0.6 14.0 D06-027 1.6 3.9 D06-061 0.7 9.0 D06-095 0.3 14.1 D06-028 1.0 4.1 D06-062 0.8 9.2 D06-096 0.1 14.3 D06-029 0.6 4.2 D06-063 0.8 9.3 D06-097 0.3 14.4 D06-030 0.2 4.4 D06-064 0.8 9.5 D06-098 0.1 14.6 D06-031 0.8 4.5 D06-065 0.6 9.6 D06-099 0.3 14.7 D06-032 0.4 4.7 D06-066 0.5 9.8 D06-100 0.2 14.9 D06-033 0.7 4.8 D06-067 0.3 9.9 - - -

D06-034 0.8 5.0 D06-068 0.3 10.1 - - -

Supplementary table 8 Stable carbon data for D. obesulus shell collected in Huanchaquito (8º 14' S) during 2006. Stable isotope is reported in parts per mil (‰) VPDB. Distance from umbo in mm uncorrected for shell curvature.

99

Sample δδδδ13

C (‰ VPBD) δδδδ18

O (‰ VPBD) Distance umbo (mm)

Dob-1.001 0.7 -0.1 16.0 Dob-1.002 0.6 0.4 15.4 Dob-1.003 0.6 0.4 14.9 Dob-1.004 0.3 0.3 14.3 Dob-1.005 0.1 0.0 13.8 Dob-1.006 0.2 0.3 13.3 Dob-1.007 0.1 0.3 12.7 Dob-1.008 0.1 -0.1 12.2 Dob-1.009 0.3 0.5 11.4 Dob-1.010 0.2 0.4 10.7 Dob-1.011 0.3 0.3 10.1 Dob-1.012 0.4 0.8 9.5 Dob-1.013 0.4 0.6 8.7 Dob-1.014 0.6 0.7 8.1 Dob-1.015 0.6 0.6 7.5 Dob-1.016 0.7 0.6 6.8 Dob-1.017 0.8 0.4 6.1 Dob-1.018 1.0 0.5 5.3 Dob-1.019 1.1 0.6 4.7 Dob-1.020 0.7 0.2 4.0 Dob-1.021 0.9 0.4 3.2 Dob-1.022 1.0 0.6 2.4 Dob-1.023 0.9 0.3 1.8 Dob-1.024 0.8 0.3 1.0 Dob-1.025 1.0 0.4 0.0

Supplementary table 9 Stable carbon and oxygen data for D. obesulus shell excavated from Magdalena de Cao Viejo (8º 14' S). Stable isotopes are reported in parts per mil (‰) VPDB. Distance from umbo in mm uncorrected for shell curvature.

100

Sample δδδδ13

C (‰ VPBD) δδδδ18

O (‰ VPBD) Distance umbo (mm)

Dob-2.001 0.8 0.2 16.5 Dob-2.002 0.4 0.2 15.7 Dob-2.003 0.1 0.3 14.9 Dob-2.004 0.4 0.5 14.2 Dob-2.005 0.3 0.5 13.4 Dob-2.006 0.2 0.3 12.8 Dob-2.007 0.3 0.2 12.2 Dob-2.008 0.3 0.2 11.6 Dob-2.009 0.3 0.3 10.9 Dob-2.010 0.4 0.1 10.4 Dob-2.011 0.5 0.7 9.7 Dob-2.012 0.6 0.7 9.2 Dob-2.013 0.6 0.7 8.6 Dob-2.014 0.5 0.4 8.0 Dob-2.015 0.5 0.4 7.5 Dob-2.016 0.5 0.4 6.9 Dob-2.017 0.5 0.8 6.1 Dob-2.018 0.6 0.9 5.3 Dob-2.019 0.6 0.7 4.6 Dob-2.020 0.6 0.9 4.0 Dob-2.021 0.7 0.9 3.2 Dob-2.022 0.8 1.0 2.5 Dob-2.023 0.5 0.5 1.6 Dob-2.024 0.8 1.0 0.9 Dob-2.025 0.8 0.8 0.0

Supplementary table 10 Stable carbon and oxygen data for D. obesulus shell excavated from Magdalena de Cao Viejo (8º 14' S). Stable isotopes are reported in parts per mil (‰) VPDB. Distance from umbo in mm uncorrected for shell curvature.

101

Sample δδδδ13

C (‰ VPBD) δδδδ18

O (‰ VPBD) Distance umbo (mm)

Do34-1.001 1.0 -0.6 14.2 Do34-1.002 0.3 -0.6 13.6 Do34-1.003 0.3 -0.6 13.3 Do34-1.004 0.5 -0.8 13.0 Do34-1.005 0.6 -0.5 12.2 Do34-1.006 0.7 -0.3 11.6 Do34-1.007 0.3 -0.3 11.2 Do34-1.008 0.6 -0.2 10.5 Do34-1.009 0.7 -0.1 9.9 Do34-1.010 0.8 -0.1 9.4 Do34-1.011 0.8 0.1 8.8 Do34-1.012 0.8 0.2 8.2 Do34-1.013 0.9 0.1 7.6 Do34-1.014 0.7 -0.1 7.2 Do34-1.015 0.6 0.0 6.6 Do34-1.016 0.8 -0.1 6.0 Do34-1.017 1.0 -0.3 5.4 Do34-1.018 0.8 0.4 4.9 Do34-1.019 1.0 0.4 4.1 Do34-1.020 1.1 0.7 3.5 Do34-1.021 0.9 0.2 2.8 Do34-1.022 0.9 0.2 2.2 Do34-1.023 1.1 0.4 1.6 Do34-1.024 1.0 0.2 0.7 Do34-1.025 0.7 -0.1 0.0

Supplementary table 11 Stable carbon and oxygen data for D. obesulus shell excavated from Huaca de la Luna -tomb 34- (8º 14' S). Stable isotopes are reported in parts per mil (‰) VPDB. Distance from umbo in mm uncorrected for shell curvature.

102

Sample δδδδ13

C (‰ VPBD) δδδδ18

O (‰ V-PBD) Distance umbo mm

Do34-2.001 0.9 -0.7 13.4 Do34-2.002 0.6 -0.5 12.9 Do34-2.003 0.4 -0.5 12.4 Do34-2.004 0.7 -0.8 11.9 Do34-2.005 1.0 -0.8 11.3 Do34-2.006 0.9 -0.4 10.8 Do34-2.007 0.9 -0.5 10.3 Do34-2.008 0.4 -0.1 9.7 Do34-2.009 0.4 -0.3 9.3 Do34-2.010 0.5 -0.1 8.7 Do34-2.011 0.8 -0.4 8.1 Do34-2.012 0.8 0.1 7.7 Do34-2.013 0.7 -0.2 7.1 Do34-2.014 0.7 0.0 6.5 Do34-2.015 1.0 -0.2 6.0 Do34-2.016 0.7 -0.2 5.6 Do34-2.017 0.9 0.1 5.1 Do34-2.018 0.9 0.0 4.5 Do34-2.019 0.7 -0.1 3.9 Do34-2.020 0.8 -0.1 3.4 Do34-2.021 0.9 0.2 2.7 Do34-2.022 0.8 0.4 2.1 Do34-2.023 0.7 0.4 1.5 Do34-2.024 0.8 0.0 0.8 Do34-2.025 1.3 0.2 0.0

Supplementary table 12 Stable carbon and oxygen data for D. obesulus shell excavated from Huaca de la Luna -tomb 34- (8º 14' S). Stable isotopes are reported in parts per mil (‰) VPDB. Distance from umbo in mm uncorrected for shell curvature.

103

Sample δδδδ13

C (‰ VPBD) δδδδ18

O (‰ VPBD) Distance umbo (mm)

Do34-3.001 0.8 0.2 12.2 Do34-3.002 0.8 0.1 11.5 Do34-3.003 1.1 0.5 10.9 Do34-3.004 1.2 0.5 10.2 Do34-3.005 1.1 0.4 9.6 Do34-3.006 1.2 0.5 8.9 Do34-3.007 1.1 0.5 8.3 Do34-3.008 1.1 0.5 7.7 Do34-3.009 1.2 0.3 7.2 Do34-3.010 1.3 0.5 6.7 Do34-3.011 1.3 0.5 6.2 Do34-3.012 1.2 0.6 5.6 Do34-3.013 1.3 0.5 5.1 Do34-3.014 1.3 0.6 4.5 Do34-3.015 1.3 0.6 3.9 Do34-3.016 1.4 0.6 3.3 Do34-3.017 1.4 0.4 2.7 Do34-3.018 1.3 0.1 2.0 Do34-3.019 1.6 0.3 1.4 Do34-3.020 1.7 0.2 0.8 Do34-3.021 1.7 -0.1 0.0

Supplementary table 13 Stable oxygen data for D. obesulus shell excavated from Huaca de la Luna -tomb 34- (8º 14' S). Stable isotope is reported in parts per mil (‰) VPDB. Distance from umbo in mm uncorrected for shell curvature.

104

Sample δδδδ13

C (‰ VPBD) δδδδ18

O (‰ VPBD) Distance umbo (mm)

Do35-1.001 0.5 -0.5 14.9 Do35-1.002 0.4 -0.2 14.3 Do35-1.003 0.5 0.0 13.7 Do35-1.004 0.5 -0.1 13.1 Do35-1.005 0.7 0.3 12.6 Do35-1.006 0.8 0.2 12.0 Do35-1.007 0.6 -0.1 11.4 Do35-1.008 0.8 0.0 10.8 Do35-1.009 0.7 0.1 10.2 Do35-1.010 0.7 0.1 9.6 Do35-1.011 0.5 0.3 8.9 Do35-1.012 0.5 0.4 8.3 Do35-1.013 0.4 0.0 7.7 Do35-1.014 0.3 -0.4 7.1 Do35-1.015 0.3 0.0 6.5 Do35-1.016 0.2 0.1 6.0 Do35-1.017 0.2 -0.3 5.4 Do35-1.021 0.5 -0.1 3.0 Do35-1.022 0.4 0.3 2.4 Do35-1.023 0.5 0.4 1.6 Do35-1.024 0.4 0.0 0.9 Do35-1.025 0.5 0.0 0.0

Supplementary table 14 Stable oxygen data for D. obesulus shell excavated from Huaca de la Luna -tomb 35- (8º 14' S). Stable isotope is reported in parts per mil (‰) VPDB. Distance from umbo in mm uncorrected for shell curvature. Samples 18 to 20 were lost.

105

Sample δδδδ13

C (‰ VPBD) δδδδ18

O (‰ VPBD) Distance umbo (mm)

Do35-2.001 0.7 -0.2 15.5 Do35-2.002 0.8 -0.5 14.7 Do35-2.003 0.6 -0.1 13.8 Do35-2.004 0.8 0.2 13.0 Do35-2.005 0.9 0.3 12.3 Do35-2.006 0.5 0.2 11.5 Do35-2.007 0.8 0.5 10.6 Do35-2.008 0.7 0.3 10.1 Do35-2.009 0.6 0.2 9.5 Do35-2.010 0.9 0.2 8.9 Do35-2.011 0.8 0.2 8.5 Do35-2.012 0.8 -0.1 8.0 Do35-2.013 0.8 0.2 7.5 Do35-2.014 0.6 0.5 6.9 Do35-2.015 0.5 0.5 6.4 Do35-2.016 0.3 -0.1 5.7 Do35-2.017 0.5 0.4 4.9 Do35-2.018 0.2 -0.5 4.3 Do35-2.019 0.4 -0.3 3.6 Do35-2.020 0.5 0.1 3.0 Do35-2.021 0.5 0.5 2.5 Do35-2.022 0.5 0.7 1.7 Do35-2.023 0.8 0.8 1.1 Do35-2.024 0.7 0.7 0.6 Do35-2.025 0.6 0.5 0.0

Supplementary table 15 Stable oxygen data for D. obesulus shell excavated from Huaca de la Luna -tomb 35- (8º 14' S). Stable isotope is reported in parts per mil (‰) VPDB. Distance from umbo in mm uncorrected for shell curvature.

106

Sample δδδδ13

C (‰ VPBD) δδδδ18

O (‰ VPBD) Distance umbo (mm)

Do35-3.001 0.9 -0.8 12.0 Do35-3.002 0.5 -0.5 11.3 Do35-3.003 0.7 -0.7 10.7 Do35-3.004 0.6 -0.3 10.0 Do35-3.005 0.6 -0.7 9.4 Do35-3.006 0.5 -0.6 8.8 Do35-3.007 0.4 -0.6 8.2 Do35-3.008 0.7 -0.8 7.6 Do35-3.009 1.0 -0.7 7.0 Do35-3.010 0.8 -0.7 6.4 Do35-3.011 0.8 -0.6 5.7 Do35-3.012 0.9 -0.3 5.1 Do35-3.013 0.9 -0.4 4.4 Do35-3.014 1.0 -0.3 3.8 Do35-3.015 0.8 -0.3 3.1 Do35-3.016 1.0 -0.2 2.5 Do35-3.017 1.1 -0.2 1.9 Do35-3.018 1.0 -0.4 1.3 Do35-3.019 1.1 -0.1 0.6 Do35-3.020 1.0 -0.1 0.0

Supplementary table 16 Stable oxygen data for D. obesulus shell excavated from Huaca de la Luna –tomb 35- (8º 14’ S). Stable isotope is reported in parts per mil (‰) VPDB. Distance from umbo in mm uncorrected for shell curvature.

107

5. CONCLUSIONS

Sclerochronology, the study of physical and chemical variations in the accretionary hard

tissues of organisms through time (Oschmann, 2009), is a valuable tool for obtaining paleo-

environmental information. In areas where long lived carbonate-secreting organisms such as

corals are not available for sclerochronological studies mollusks become a valuable alternative.

In this research we studied mollusk shells to obtain proxy information about late Holocene

coastal upwelling.

The utility of using mollusk shells as multi-proxies archives was demonstrated by the use

of radiocarbon, stable oxygen, trace elements, and biomineralization processes to characterize

Peruvian upwelling and El Niño events. High resolution ∆R analyses registered high temporal

and spatial heterogeneity of upwelling systems. Peruvian upwelling is dynamic, being populated

by different structures such as filaments, eddies, and plumes that move ocean water along the

coast at different rates. Discovering that molluscan-recorded upwelling signals may be

influenced by water structures movement (e.g. filaments), depend on sampling strategies, and

species-specific growth preferences contributes to a better awareness of proxy limitations. New

∆R corrections were produced for northern and central Peru will help geologists and

archaeologist to correct radiocarbon dates based on marine carbonates, expanding the available

data for the region.

Contributions to the development of new molluscan proxies was achieved by showing

how biomineralization changes may affect trace element (Ba+2, Sr+2, and Mg+2) content in

108

molluscan aragonite. Knowledge of the effects of biomineralization changes in trace element

content may produce more accurate environmental interpretations of this potential proxy data.

Additionally, biomineralization changes themselves may become proxies for extreme

environmental conditions in a region.

Upwelling changes through the late Holocene were outlined using D. obesulus ∆R in

northern Peru. 20th and 16th centuries seem to have similar upwelling regimes. However ∆R data

suggest that the 6th century had a marked reduction in deepwater upwelling. This upwelling

reduction may be the first oceanic evidence for Mega-El Niño events in northern Peru 1400 yrs

BP. This data supports Mega-El Niño evidence previously detected by other proxies (e.g.

flooding sedimentary deposits) and linked to political destabilization and power shift in ancient

Peruvian cultures.

109

References

Allan RJ, Nicholls N, Jones PD, Butterworth I .1991. A Further Extension of the Tahiti-Darwin SOI, Early ENSO Events and Darwin Pressure. Journal of Climate. 4:743-739.

Andrus CFT, Crowe DE, Sandweiss DH, Reitz EJ, Romanek CS. 2002. Otolith δ18O record of

Mid-Holocene Sea Surface Temperatures in Peru. Science. 295:1508-1510. Andrus CFT, Crowe DE, Sandweiss DH, Reitz EJ, Romanek CS. 2003. Response to Comment

on “Otolith δ18O Record of Mid-Holocene Sea Surface Temperatures in Peru”: Science. 299:203.

Andrus, CFT, Hodgins GWL, Sandweiss HD, Crowe DE. 2005. Molluscan radiocarbon as a proxy for El Niño-related upwelling variation in Peru. Geological Society of America Special Paper 395:13-20.

Andrus C.F.T., Sandweiss HD, Reitz EJ. 2008. Climate change and Archaeology: The Holocene

History of El Niño on the Coast of Peru, in Reitz EJ, Scarry CM, and Scudder, SJ, ed., Case Studies in Environmental Archaeology. London. Springer Science Business Media.

Baker PA, Seltzer GO, Fritz SC, Dunbar RB, Grove MJ, Tapia PM, Cross SL, Rowe HD, Broda

JP. 2001. The History of South American Tropical Precipitation for the Past 25,000 Years. Science. 291:640-643.

Barber RT, Chavez FP.1983. Biological consequences of El Niño. Science. 222:1203-1210.

Clement AC, Seager R, Cane MA. 2000. Suppression of El Niño during mid-Holocene by changes in Earth's orbit. Paleogeography. 15:731-737.

DeVries TJ, Ortlieb L, Diaz A, Wells LE, Hillaire-Marcel Cl. 1997. Determining the early

history of El Niño. Science. 276:965-967. Diaz HF, Graham NE. 1996. Recent changes in tropical freezing heights and the role of sea

surface temperature. Nature. 383:152-155.

Dickin AP. 2005. Radiogenic Isotope Geology. Cambridge University Press. 508 p. Donnelly JP, Woodruff JD. 2007. Intense hurricane activity over the past 5,000 years controlled

by El Niño and the West African monsoon. Nature. 447:465-468. Fontugne M, Usselmann P, Lavallée D, Julien M, and Hatté C. 1999. El Niño Variability in the

Coastal Desert of Southern Peru during the Mid-Holocene. Quaternary Research. 52:171-179.

110

Gagan MK, Ayliffe LK, Hopley D, Cali JA, Mortimer GE, Chappell J, McCulloch MT, Head MJ. 1998. Temperature and surface-ocean water balance of the mid-Holocene tropical Western Pacific. Science. 279:1014-1018.

Haug GH, Hughen KA, Sigman DM, Peterson LC, Röhl U. 2001. Southward Migration of the

Intertropical Convergence Zone through the Holocene. Science.17:1304-1308. Huyer A, Smith RL, Paluszkiewicz T. 1987. Coastal Upwelling off Peru during normal and El

Niño times, 1981-1984. Journal of Geophysical Research Oceans. 92:14297-14307. Jones KB, Hodgins GWL, Dettman DL, Andrus CFT, Nelson A, Etayo-Cadavid, MF. 2007.

Seasonal variation in Peruvian Marine Reservoir Age from Pre-bomb Argopecten purpuratus Shell Carbonate. Radiocarbon. 49:877-888.

Jones KB, Hodgins GWL, Etayo-Cadavid MF, Andrus CFT. 2009. Upwelling signals in

radiocarbon from early 20th-century Peruvian bay scallop (Argopecten purpuratus) shells. Quaternary Research.72:452-456.

Jones KB, Hodgins GWL, Andrus CFT, Etayo-Cadavid MF. 2010. Modeling Molluscan Marine

Reservoir Ages In A Variable-Upwelling Environment. Palaios. 25:126-131. Koutavas A, Lynch-Stieglitz J, Marchitto Jr TM, Sachs JP. 2002. El Niño–Like Pattern in Ice

Age Tropical Pacific Sea Surface Temperature. Science. 297:226-230. Koutavas A, DeMenocal P B, Olive GC, Lynch-Stieglitz J. 2006. Mid-Holocene El Niño–

Southern Oscillation (ENSO) attenuation revealed by individual foraminifera in eastern tropical Pacific sediments. Geology. 34:993-996.

Langton SJ, Linsley BK, Robinson RS, Rosenthal Y, Oppo DW, Eglinton TI, Howe SS,

Djajadihardja YS, Syamsudin F. 2008. 3500 yr record of centennial-scale climate variability from the Western Pacific Warm Pool. Geology. 36:795-798.

Loubere P. 1999. A multiproxy reconstruction of biological productivity and oceanography in

the eastern equatorial Pacific for the past 30,000 years. Marine Micropaleontology. 37:173-198.

Martinez I, Rincon D, Yokoyama Y, Barrows T. 2006. Foraminifera and coccolithophorid

assemblage changes in the Panama Basin during the last deglaciation: Response to sea-surface productivity induced by a transient climate change. Palaeogeography, Palaeoclimatology, Palaeoecology. 234:114-126.

McConnaughey TA, Gillikin DP. 2008. Carbon isotopes in mollusk shellCarbonates. GeoMarine

Letters. 28:287-299. Oliver JE, Hidore JJ. 2002. Climatology: An Atmospheric Science. Delhi. Pearson Education,

Inc. 410 p.

111

Ortlieb L, and Macharé J. 1993. Former El Niño events: records from western South America:

Global and Planetary Change. 7:181-202. Oschmann W. 2009. Schlerochronology: editorial International Journal of Earth Sciences (Geol

Rundsch). 98:1-2. Philander SGH.1985. El Niño and La Niña: Journal of Atmospheric Sciences. 42:2652-2662. Peterson LC, Haug HH. 2006. Variability in the mean latitude of the Atlantic Intertropical

Convergence Zone as recorded by riverine input of sediments to the Cariaco Basin (Venezuela). Palaeogeography, Palaeoclimatology, Palaeoecology. 234:97-113.

Pidwirny M. 2006. Fundamentals of Physical Geography, in M. Pidwirny, ed.University of

British Columbia Okanagan. Poveda G, Waylen PR, Pulwarty RS. 2006. Annual and inter-annual variability of the present

climate in northern South America and southern Mesoamerica: Palaeogeography, Palaeoclimatology, Palaeoecology. 234:3-27.

Poulain C, Lorrain A, Gillikin DP, Dehairs F, Robert R, and Paulet Y.-M. 2010. Experimental

shift of diet and DIC stable carbon isotopes: Influence on shell δ13C values in the Manila clam Ruditapes philippinarum. Chemical Geology. 272:75-82.

Quinn HW, Neal VT, Antunez de Mayolo SE. 1987. El Niño Occurrences over the Past Four and

a Half Centuries. Journal of Geophysical Research. 92: 14449-14461. Riedinger MA, Steinitz-Kannan M, Last WM, Brenner M. 2002. A ~6100 14C yr record of El

Niño activity from the Galápagos Islands. Journal of Paleolimnology. 27:1-7. Rein B, Lückge A, Reinhardt L, Sirocko F, Wolf A, Dullo W-C. 2005. El Niño variability off

Peru during the last 20,000 years. Palaeogeography. 20:1-17. Rodbell DT, Seltzer GO , Anderson DE, Abbott MB, Enfield DB, Newman JH. 1999. A 15,000

year record of El Niño-driven alluviation in sothwestern Ecuador. Science. 283:516-520. Sandweiss DH, Richardson III JB, Reitz EJ, Rollins HB, Maasch KA. 1996. Geoarcheological

Evidence from Peru for a 5000 years B.P. Onset of El Niño. Science. 273:1531-1533. Sandweiss DH, Richardson III JB, Reitz EJ, Rollins HB, Maasch KA. 1997. Determining the

Early History of El Niño. Science. 276:965-967. Sandweiss DH, Maasch KA, Burger RL, Richardson III JB, Rollins HB, Clement A. 2001.

Variation in Holocene El Niño frequencies: Climate records and cultural consequences in ancient Peru. Geology.29:603-606.

112

Sandweiss DH, Maasch KA, Chai F, Andrus CFT, Reitz EJ. 2004. Geoarchaeological evidence for multidecadal natural climatic variability and ancient Peruvian fisheries. Quaternary Research. 61:330-334.

Sandweiss DH, Solís RS, Moseley ME, Keefer DK, Ortloff CR. 2009. Environmental change and economic development in coastal Peru between 5,800 and 3,600 years ago. Proceedings of the National Academy of Sciences. 106:1359-1363.

Thompson LG, Mosley-Thompson E, Davis ME, Lin P-N, Henderson KA, Cole-Dai J, Bolzan

JF, Liu K-B. 1995. Late Glacial Stage and Holocene Tropical Ice Core Records from Huascaran, Peru. Science. 269:46-50.

Trenberth KE. 1997. The Definition of El Niño. Bulletin of the American Meteorological

Society.78:2771-2777. Trenberth KE, Caron JM. 2000. The Southern Oscillation Revisited: Sea Level Pressures,

Surface Temperatures, and Precipitation. Journal of Climate. 13:4358-4365.

Van der Hammen T, Hooghiemstra H. 1996. The El Abra Stadial, a Younger Dryas equivalent in Colombia. Quaternary Sciences Reviews. 14:841-851.

Vélez MI, Hooghiemstra H, Metcalfe S, Wille M, Berrío JC. 2006. Late Glacial and Holocene

environmental and climatic changes from a limnological transect through Colombia, northern South America. Palaeogeography, Palaeoclimatology, Palaeoecology. 234:81-96.

Vimeux F, Ginot P, Schwikowski M, Vuille M, Hoffman G, Thompson LG, Schottere U. 2009.

Climate variability during the last 1000 years inferred from Andean ice cores: A review of methodology and recent results. Palaeogeography, Palaeoclimatology, Palaeoecology. 281: 229-241.

Wells LE, Noller JS. 1997. Determining the early history of El Niño. Science. 276:965-967. Wolter K, Timlin MS. 1998. Measuring the strength of ENSO events: How does 1997/98 rank?

Weather. 53:315-324.