Radiocarbon, Vol 65, Nr 5, 2023, p 1139–1159 DOI:10.1017/RDC.2023.95
© The Author(s), 2023. Published by Cambridge University Press on behalf of University of Arizona. This
is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://
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AUSTRALIAN MARINE RADIOCARBON RESERVOIR EFFECTS: ΔR ATLAS AND
ΔR CALCULATOR FOR AUSTRALIAN MAINLAND COASTS AND NEAR-SHORE
ISLANDS

Sean Ulm1* • Damien O’Grady1,2 • Fiona Petchey3,1 • Quan Hua4,5 •

Geraldine Jacobsen4 • Lauren Linnenlucke1,4 • Bruno David6 •

Daniel Rosendahl7 • Magdalena M E Bunbury1 • Michael I Bird8 • Paula J Reimer9

1ARC Centre of Excellence for Australian Biodiversity and Heritage, College of Arts, Society and Education, James
Cook University, PO Box 6811, Cairns, Queensland 4870, Australia
2NGIS, Level 22, 120 Spencer Street, Melbourne, Victoria 3000, Australia
3Radiocarbon Dating Laboratory, Division of Health, Engineering, Computing and Science, University of Waikato,
3240, New Zealand
4Australian Nuclear Science and Technology Organisation, Locked Bag 2001, Kirrawee DC, New South Wales 2232,
Australia
5School of Social Science, The University of Queensland, Brisbane, Queensland 4072, Australia
6ARC Centre of Excellence for Australian Biodiversity and Heritage, Monash Indigenous Studies Centre, Monash
University, Clayton, Victoria 3800, Australia
7College of Arts, Society and Education, James Cook University, PO Box 6811, Cairns, Queensland 4870, Australia
8ARC Centre of Excellence for Australian Biodiversity and Heritage, College of Science and Engineering, James Cook
University, PO Box 6811, Cairns, Queensland 4870, Australia
9The 14CHRONO Centre for Climate, the Environment and Chronology, Geography, Archaeology and
Palaeoecology, School of Natural and Built Environment, Queen’s University Belfast BT7 1NN, United Kingdom

ABSTRACT. Studies of pre-bomb mollusks live-collected around the Australian coastline have concluded that near-
shore marine radiocarbon reservoir effects are small and relatively uniform. These studies are based on limited samples
of sometimes dubious quality representing only selective parts of Australia’s lengthy coastline. We systematically
examine spatial variability in the marine radiocarbon reservoir effect (ΔR) through analysis of 292 live-collected
mollusk samples across the Australian mainland coasts and near-shore islands subject to strict selection criteria. This
study presents 233 newΔR values combined with an evaluation of 59 previously published values. Results demonstrate
significant spatial variability in marine radiocarbon reservoir effects across the study region. ΔR values range from
68 ± 24 14C years off the Pilbara region of Western Australia to –337 ± 46 14C years in the southern Gulf of Carpentaria
in Queensland. Most sets of local values exhibit internal consistency, reflecting the dominant influence of regional
oceanography, including depletion inΔR values southwards along the eastern Australian coastline coincident with the
East Australian Current. Anomalous values are attributed to inaccurate documentation, species-specific relationships
with the carbon cycle and/or short-term fluctuations in marine radiocarbon activities. To account for the heterogeneous
distribution of marine 14C, we recommend using a location specific ΔR value calculated using the Australian ΔR
Calculator, available at: https://delta-r-calc.jcu.io/.

KEYWORDS: marine 14C, marine radiocarbon reservoir effects, mollusks, MRE, radiocarbon, ΔR.

INTRODUCTION

Radiocarbon (14C) ages obtained on contemporaneous terrestrial and marine samples are not
directly comparable. On average, Holocene subtropical marine samples are ca. 400 14C years
older than contemporaneous terrestrial samples (Stuiver et al. 1986; Bard 1988). The difference
is caused by marine radiocarbon reservoir effects (MRE) that reflect the different residence
time of carbon in marine versus atmospheric reservoirs. While 14C produced in the upper
atmosphere is rapidly and relatively evenly incorporated throughout the atmosphere, long
residence times for carbon in the deep ocean and uneven mixing of upwelling deep ocean waters
cause significant spatial variability in global MRE (Mangerud 1972). A range of other factors

*Corresponding author. Email: sean.ulm@jcu.edu.au

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can impact local MRE, including local upwelling along with temperature, wave, wind, and
current regimes influencing air-sea gas exchange (Alves et al. 2018). Local differences can be
particularly marked in estuaries and lagoons where local geology, terrestrial freshwater inputs,
and incomplete exchange with the open ocean can accentuate MRE (Little 1993; Ulm 2002;
Ulm et al. 2009; Petchey et al. 2023).

Successive marine calibration curves (Marine04, Marine09, Marine13, Marine20) have
modeled global-scale surface ocean 14C activity (Hughen et al. 2004; Reimer et al. 2009, 2013;
Heaton et al. 2020). The difference between local and modeled global-scale surface ocean ages
is expressed asΔR (Stuiver et al. 1986). NegativeΔR values reflect lower MRE for the studied
region compared with the global marine model and vice versa. Local ΔR values can be
determined from a variety of approaches (the most common include 14C dating known-age
marine samples; 14C dating paired contemporaneous marine/terrestrial samples; and paired
14C/U-series dating of corals) (Stuiver and Braziunas 1993; Hua et al. 2020). To avoid
ambiguity, here we use the term ΔR when discussing local correction values in general and
ΔRXX when denoting offsets to a specific calibration curve (i.e., ΔR20 when referring to a ΔR
value derived from and for use with the Marine20 marine calibration curve) (see Heaton et al.
2023). ΔR and ΔR variability are usually small in areas where surface waters are well-mixed
(e.g., east coast of Australia) but can be large and highly variable in areas with strong upwelling
of deep waters with long residence times (e.g., Southern California, Antarctica) (e.g., Culleton
et al. 2006; Hall et al. 2010).

To date, relatively fewMRE studies have been undertaken in Australia compared with other areas
of the globe (see Reimer and Reimer’s 2001 14CHRONO Centre Marine Reservoir Correction
Database, http://calib.org/marine/). This is at least partly attributable to the enduring impact of
Gillespie’s (1975, 1977; Gillespie and Temple 1977; Gillespie and Polach 1979) pioneering studies
that demonstrated relatively little variability in MRE based on the dating of six marine shell
specimens from four locations around the Australian coastline. Subsequent studies proposed only
minor deviations based on local studies that largely supported the values proposed by Gillespie
(e.g., Rhodes et al. 1980; Bowman and Harvey 1983; Gill 1983; Head et al. 1983; Bowman 1985a,
1985b). For decades it was a common practice in Australia to adjust 14C ages on marine samples
for MRE by simply subtracting 450 or 450 ± 35 14C years to make them comparable to coeval
terrestrial samples. These ages were often reported as “corrected shell dates” (e.g., Godfrey 1989;
O’Connor 1989; Bird and Frankel 1991; Sim 1998). Conventional radiocarbon ages (cf. Stuiver and
Polach 1977) were often not listed, making the use of the published marine shell 14C ages and their
calibration problematic. Despite several studies suggesting variability in MRE (e.g., Hughes and
Djohadze 1980; Woodroffe et al. 1986; Woodroffe and Mulrennan 1993; Murray-Wallace 1996;
Spennemann andHead 1996; Ulm 2002; Ulm et al. 2009), no systematic study of AustralianMRE
has been undertaken (cf. Ulm 2006).

Studies in Australian coastal archaeology and geomorphology are highly dependent on 14C
ages obtained on marine samples, particularly mollusks. Mollusk remains are the dominant
component of many coastal deposits, often with limited or no representation of other material
(e.g., charcoal) suitable for radiocarbon dating. Mollusks may be preferred for dating owing to
their relatively short lifespan and often larger surface area, limiting movement in deposits. In
contrast, charcoal samples (where available) may have potentially large in-built ages (e.g.,
“old-wood effect” for charcoal, see Schiffer 1986), and even “short-lived” plant materials might
have inbuilt age of 50–150 years (Anderson 1991; Allen and Wallace 2007). Individual small
charcoal pieces can also move more readily across the matrix, distorting local chronologies.

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Mollusks are represented in archaeological deposits in Australia dating from at least 42,000 cal
BP (Veth et al. 2017), making marine mollusk samples central to the chronology-building that
underpins our understanding of the human history of the continent. The SahulArch dataset
(Saktura et al. 2023) hosted on the Octopus database (Codilean et al. 2022) indicates that more
than 23% of ages from archaeological deposits across the continent are on marine mollusk
samples (26.4% of ages from Holocene archaeological deposits). Determining ΔR values and
developing an understanding of ΔR variability through space and time is therefore crucial to
refining chronologies in Quaternary science.

This study specifically examines spatial variability in ΔR around the Australian coastline
measured in mollusks live-collected between AD 1841 and AD 1956. By providing a large-scale
assessment ofΔR values and variability across the continent, this study improves the calibration
of radiocarbon ages based on marine materials, which is essential for assessing the antiquity of,
and changes in, Aboriginal and Torres Strait Islander social practices, cultures, and technologies
through the archaeological record and the impacts of coastal change on human populations (e.g.,
Williams et al. 2018). Results also have implications for geomorphology, providing new
information on modeling rates and impacts of sea-level change (e.g., Sloss et al. 2018), coral reef
development and evolution of reef islands (e.g., Chivas et al. 1986; Woodroffe et al. 2007), as well
as the evolution of the Australian coastline and the impact of environmental change on coastal
landscapes. The results and their application have important implications for coastal
management and conservation efforts, as understanding the history of coastal environments
is crucial for making informed decisions about their protection and management.

METHODS

Synthesis of Previous Studies

A systematic review was undertaken of all previously publishedΔR values available from live-
collected mollusks around the Australian coast using the 14CHRONO Centre Marine
Reservoir Correction Database (Reimer and Reimer 2001) as well as an extensive literature
search to achieve comprehensive data collection (Tables S1–2). This review is restricted to
mollusks, which are the most commonly 14C-dated materials in Australian coastal
archaeological and geomorphological studies. There are a small number of studies of recent
marine radiocarbon reservoir effects based on coral records that are not included here (Druffel
and Griffin 1993, 1999; Squire et al. 2013; Hua et al. 2015; Komugabe-Dixson et al. 2016; Wu
et al. 2021). However, a comparison between the ΔR values based on mollusks reported here
and those based on these corals within the time frame of our study is presented in Results and
Discussion below.

A total of 59 ΔR values obtained on live-collected mollusks have been published prior to the
current study (Table S2; Figure 1). Full details are presented in Table S1. Laboratory reports
were checked, where available, and original primary publications were accessed to confirm
details for legacy ages.

Identification of Samples in Museum Collections

To expand the geographical coverage of live-collected mollusk samples, all major Australian
museum malacology collections were systematically evaluated for appropriate samples,
including the Australian Museum, Queensland Museum, Western Australian Museum, South
Australian Museum and Museums Victoria.

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Evaluation of museum collections commenced with a review of mollusks identified on museum
databases as live-collected in or before AD 1950. These specimens were then located in
collections and visually inspected for suitability against the sample selection criteria (see
below). Many of these specimens were rejected at this stage, typically because no physical or
documentary evidence clearly demonstrated live-collection. Often accession or donation dates
were recorded on museum databases rather than live-collection dates. Another limitation of
relying on museum database searches to identify samples stems from the large proportion of
materials held in museum malacology collections that are not accessioned. Furthermore, much
of the critical information recorded in documentary material accompanying specimens or on
hand-written museum accession registers has not been migrated to online databases.

The second stage involved a systematic visual examination of all holdings and associated
documentation of taxa (especially bivalves) targeting taxa commonly selected in radiocarbon
dating of archaeological deposits. Williams et al. (2014) report that Anadara spp./Tegillarca
spp., Ostrea spp./Saccostrea spp. and Latona spp. (syn. Donax spp., Plebidonax sp.) are the

Figure 1 Map of Australia showing locations ofΔR samples discussed in this study. Black dots representΔR values
reported in previous studies. Red dots represent new values reported in this study. (See online version for color figures.
See Tables S1–3 for full details and Figures S1–18 for full-size figures.)

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dominant marine bivalves dated in Australian archaeology. Where no suitable target taxa were
identified, the evaluation was broadened to include taxa well-represented in museum
collections guided by curatorial and collection management staff.

Selection Criteria

Expanding and refining the criteria outlined in O’Connor et al. (2010), rigorous sample
protocols were developed and implemented for use in this study. Samples had to meet all these
conditions to be included in subsequent analyses. The test for inclusion was applied
sequentially down the list 1–9 below (i.e., a sample might be excluded on the basis of multiple
criteria, but was listed as excluded on the basis of its highest-ranked criterion for exclusion).

1. Phylum: Mollusca. Class: Bivalvia: Samples must be bivalves. Mollusks are the most dated
marine materials in archaeology and Quaternary studies in Australia (Williams et al. 2014;
Saktura et al. 2023). This study excludes values based on gastropods and non-molluscan
marine exoskeletal material (e.g., coral). Gastropods have been shown to be more problematic
for MRE studies as their detrital, carnivorous, herbivorous, algal grazing and/or omnivorous
feeding systems provide pathways for the incorporation of non-dissolved inorganic carbon
(non-DIC) sources into mollusk shell structures (Tanaka et al. 1986). 14C activity in suspension-
feeding (or filter-feeding) bivalves should reflect dissolved inorganic carbon (DIC) of the
ambient waters in which they lived (Petchey et al. 2013).

2. Live-Collected: Samples must have been collected as live specimens. Many specimens in
museum dry collections exhibit bleaching, edge-rounding, marine growth on inside surfaces
and/or bore holes indicating a time-lag between death and collection. Only specimens with
definitive evidence of live-collection, such as unambiguous documentation, the retention of the
desiccated animal or the presence of residual ligament, muscle and/or periosteum were
accepted for this study.

3. Live-Collected ≤AD 1950: Samples must have collection dates before or in AD 1950.
Atmospheric nuclear weapon testing resulted in enriched atmospheric and oceanic 14C levels
after this time. This ‘bomb effect’ has been detected in coral cores from the Pacific Ocean and
Indonesian Throughflow from c.AD 1954 (e.g., Andrews et al. 2016; Wu and Fallon 2020).
Ascough et al. (2005) recommend use of samples live-collected before AD 1890 to avoid the
combined effects of atmospheric nuclear weapon tests and the Suess effect caused mainly by
industrial-scale burning of fossil fuels. Unfortunately, very few live-collected specimens in
Australian museum collections (and only five samples in this study) pre-date AD 1890.
Although this is an important consideration for the calculation of the marine reservoir age,ΔR
values are calculated from the offset with the marine calibration curve which is modeled with
atmospheric 14C as input thereby including the Suess effect (Heaton et al. 2020).

4. Collection Date Known to Within ≤1 Year: Samples must have specified collection dates that
confine their collection to a single calendar year. Many of the amateur mollusk collectors who
donated to museums collected over decades and often collections were acquired by the
museums many years subsequent to their collection (e.g., after the death of the collector). In
some cases, the date of specimen collection can only be confidently bracketed by the active
collecting years of a particular collector. For example, Bowman (1985a) used samples from the
Bernard Bardwell Collection whose collection dates could only be determined to be between
AD 1902 and AD 1950 using biographical information.

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Only specimens with a firm collection date or where collection can be constrained within a
single year were accepted for this study. Although the time resolution of Marine20 is 10 years
(Heaton et al. 2020), this criterion is designed to identify samples with ambiguous collection
dates. Individual museum lots of mollusks collected over a period of more than a year have an
elevated risk of containing mixed samples from different years and different locations. This
criterion is designed to remove those samples.

Even where the year of collection appears unambiguous, sources of error can occur. For
example, samples Wk-43560, Wk-43561, and Wk-43562 were dated on the basis that
documentation accompanying the samples indicated a collection year of AD 1950. The
specimens all conjoin and exhibit ligament and color suggesting live-collection. Subsequent
radiocarbon dating revealed that the mollusks lived post-AD 1960s, after 14C derived from
atmospheric nuclear bomb tests entered the oceans (F14C values of 1.055, 1.023, and 0.989,
respectively) (Reimer et al. 2004). Subsequent examination of museum records and other
sources (Wilson and Stevenson 1977:98) indicated that nearly all specimens from the Broome
area sourced from Anthony Kalnins were collected in the mid-to-late AD 1960s, indicating
likely mislabelling of the year of collection and/or mixing of specimens in the lot.

5. Known Collection Location: Samples must have reliable provenance data (i.e., geographic
location). There are many complexities that affect samples at the local level, such as upwelling,
tidal flushing, terrestrial runoff effects from freshwater input, and local geology (Dye 1994;
Stuiver and Braziunas 1993; Ulm 2002; Ulm et al. 2009). As some species have wide tolerance
levels, detailed collection provenance is essential.

6. Species Identified: Samples must be reliably identified to species. Different species, even
those belonging to the same family, may exhibit differences in diets and relationships with the
carbon cycle, contributing to variability in ΔR values (see Criterion #1 above) (Petchey et al.
2012, 2013). Only samples identified to species are included in this study.

7. Suspension-Feeder: Samples must be suspension-feeding species. ΔR values will vary as a
result of species-specific feeding habits (i.e., carnivores, deposit feeders, algal grazers,
omnivores or suspension feeders). Carnivores (e.g., Syrinx aruanus, Melo amphora), deposit
feeders (e.g., Terebralia spp., Telescopium spp.) and algal grazers (e.g., Rochia spp.) are likely
to have a greater uptake of carbon from the other animals, sediments and geology they feed
upon (Tanaka et al. 1986; Hogg et al. 1998; Petchey et al. 2012, 2013). Some grazers with
magnetite-toughened teeth remove and ingest the surface of the rock with the algae, potentially
exacerbating this problem. Although most bivalves are suspension-feeders, several families
including Cyrenidae and Tellinidae appear to be able to switch to other feeding pathways
(Snelgrove and Butman 1994:151; Beesley et al. 1998:342; Twaddle et al. 2017). These taxa are
excluded from the analyses presented here.

8.Ages from Same Lot, Pair or Valve have 14C ages that are Statistically Indistinguishable:Ages
from samples assumed to be collected from the same location and same time, but not returning
similar ages, are excluded. Dissimilar ages from the same lot (i.e., ages on multiple individuals)
suggest confounding problems, for example, mixed mollusks in the lots (see Criterion #4
above), pointing to possible mixing of specimens within the lot, potentially from different times
and locations. Dissimilar ages from the same pair (i.e., ages on both valves of a single bivalve)
could indicate laboratory errors, contamination, or sampling of different years of growth.
Where individual specimens of the same taxa from the same lot have more than one
radiocarbon determination (e.g., both valves of a bivalve, or multiple valves sampled from the

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same lot), ages were subject to a chi-squared test to test if they are coeval following the
procedures outlined in Ward and Wilson (1978). Specimens with ages that failed the chi-
squared test were excluded. For specimens and lots with two or more 14C ages, a chi-squared
test was undertaken to determine whether the ages were statistically indistinguishable. For lots,
pairs or valves with only two ages that failed the test, all ages were excluded from further
analysis as it was not possible to determine which age accurately reflected the true age of death
of the specimen. For specimens with three or more ages, the T statistic was used to identify non-
contemporaneous age/s and exclude the affected samples from subsequent analyses (Ward and
Wilson 1978). Details are presented in Table S1.

9. Only a Single Mollusk Dated: Samples are only included where a single mollusk is dated,
avoiding samples comprising multiple individual mollusks with different life histories. Some
studies using conventional radiocarbon dating methods (e.g., liquid scintillation counting)
combined multiple mollusks, sometimes from different taxa, to reach minimum sample sizes
(e.g., Bowman 1985a).

Physical Collection of Samples

After photographing each specimen, an 8–10 mm-long and ∼4–5 mm-wide sample was taken
parallel to the margin of each shell using a Dremel® 3000 Rotary Tool fitted with a diamond
wheel. This sample size is designed to achieve adequate quantities for 14C, 18O, and 13C
analyses, minimise damage to samples, avoid seasonal variation and give an average value
approximating the 14C age of death of the mollusk (Culleton et al. 2006; Petchey et al. 2008).

Radiocarbon Dating

Accelerator mass spectrometry (AMS) 14C age determinations were undertaken at the
University of Waikato Radiocarbon Dating Laboratory and the Australian Nuclear Science
and Technology Organisation (ANSTO).

Waikato samples were pre-treated following standard AMS protocols (UCI KCCAMS
Facility 2011a, 2011b). Shell (<3 mm fragments, 35–45 mg) were etched in 0.1M HCl at 80ºC
to remove ∼45% of the surface, then dried. Cleaned shells were then tested for recrystallization
by Feigl staining (Friedman 1959) to ensure either aragonite, or a natural aragonite/calcite
distribution was present in the shell. CO2 was collected from shells by reaction with 85%H3PO4

under vacuum at 70ºC for 30 min. Cryogenically separated CO2 was reduced to graphite with
H2 at 550°C using an iron catalyst. δ13C was measured on a LGR Isotope analyser CCIA-
46EP. Pressed graphite was analysed at the Keck Radiocarbon Dating Laboratory, University
of California on a NEC 0.5MV 1.5SDH-2 AMS system (Beverly et al. 2010).

At ANSTO, after visual inspection for the presence of any powdery, potentially extraneous
calcite deposition, shell surfaces were physically cleaned by abrasion with a Dremel® rotary
tool. 20–100 mg of shell was cut from the shell and the surface etched using 0.5M HCl for
3–5 min under sonication at room temperature, removing ∼10–50% of the surface (Hua et al.
2001). The Feigl staining test (Friedman 1959) was undertaken on cleaned aragonite shells
(OZM111–OZM116) to confirm removal of calcite. Hydrolysis was performed with 85%
H3PO4 at 60ºC overnight and the resulting CO2 was collected and purified cryogenically. The
purified CO2 was reduced to graphite using H2 over an Fe catalyst at 600ºC (Hua et al. 2001)
and measured for 14C on the STAR 2MV HVEE Tandetron (AMS) at ANSTO (Fink et al.
2004). 14C measurements were normalised to NBS Oxalic Acid I (HOxI) as primary standard

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and corrected for process blanks using IAEA C-1 marble (Rozanski 1991) and δ13C isotopic
fractionation which was determined on residual graphite targets using an elemental analyser
Elementar vario MICRO cube coupled to a Micromass Isoprime IRMS.

The removal of 10–50% of the sample surface by physical cleaning and/or acid etch removed
any surficial contaminants. 14C ages are reported without rounding, following the
recommendations of Russell et al. (2011). F14C is calculated according to Reimer et al. (2004).

Calculation of ΔR

ΔR20 was calculated using Reimer and Reimer’s (2017) online deltar program (http://calib.org/
deltar/), where the collection year of each shell sample (i.e., year of death) was converted to an
equivalent global marine modeled 14C age using the Marine20 calibration dataset and then this
age was subtracted from the mean of the measured 14C age of the sample. Uncertainty of each
ΔR value is the uncertainty of the sample 14C measurement, without including the uncertainty
associated with the equivalent marine modeled 14C age. This practice aims to avoid the
inclusion of this uncertainty twice in the final calibrated ages (first in the determination of ΔR
and second during age calibration using Marine20 and the estimated ΔR value). Reimer and
Reimer’s (2017) online deltar calculation tool only returns values on calendar ages up to AD
1949. For samples collected ≥AD 1950, an equivalent global marine modeled 14C age was
derived from the Marine20 calibration curve data and subtracted from the measured 14C age.
Note that any updates of the marine calibration curve beyond Marine20 (Heaton et al. 2020)
would require recalculation of the ΔR values presented here using the primary data presented
in Table S1.

Stable Isotope Analyses

δ13C and δ18O values were measured on solid shell samples or CO2 gas prepared on AMS
vacuum lines using a CO2 isotope analyser (CRDS) (Los Gatos Research model CCIA-46).
Phosphoric acid (102%) was added to each ground shell sample (0.42–0.5 mg) to evolve CO2.
Samples were heated (72ºC, ≥1 hr) to promote hydrolysis before analysis of the δ18O and δ13C
values. International Atomic Energy Agency (IAEA) standards NBS-18 (calcite) and NBS-19
(limestone) were used to construct a two-point isotope calibration curve (δ13C= –5.014‰, δ18O
= –23.2‰ and δ13C= 1.95‰, δ18O = –2.20‰ respectively) and further evaluated using BDH
(δ13C = –24.95‰, δ18O = –13.99‰) and Sigma (δ13C = –14.18‰, δ18O = –20.07‰) synthetic
CaCO3 standards (Beinlich et al. 2017). A drift correction was made after every two samples
using 1500 ppm CO2 reference gas. δ13C and δ18O values are reported as ‰ V-PDB. Routine
precision of 0.3‰ or better is typical, as determined using sample reproducibility of duplicate
measurements.

Modeling ΔR Variability around the Australian Coast

To model spatial variability of ΔR values around the coast of Australia, 182 records of ΔR
measurements that met the inclusion criteria were processed. Kriging, a Gaussian process
regression, was used to interpolate ΔR20 values around the Australian coast at unsampled
locations, using Python tools from the SciKit GStat package (Mälicke et al. 2021). Different
models were fit against the variogram data, with the spherical variogram returning the lowest
error chosen (Figure S19). A semi-variogram was produced plotting the semi-variance against
lag for the point pairs in the data set. The spherical model was applied to the kriging function
and kriging was performed for all pixels with a size of 10 km within a rectangular region

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bounding the Australian mainland and Tasmania. The Australian Equal Albers projection
EPSG:3577 was adopted to minimise distortion. Results were masked to a 300 km border
around the coast. The outputs resulted in two raster images, one representing the kriged ΔR
values, and the other the Error Variance, of which the square root represents the standard error
of the interpolation process. To account for both the standard errors of the original ΔR
measurements, and those of the interpolation process, a further interpolation of measurement
standard errors was performed, creating a measurement standard error surface. The two error
surfaces were combined by taking the square root of the sum of their squares to produce an
overall standard error surface.

RESULTS AND DISCUSSION

The 292 samples in this study, including 59 previously published values, were live-collected
between AD 1841 and AD 1956 (a single legacy sample collected in AD 1956 from Key Island,
Tasmania, by Gill 1983, is the only sample in the dataset post-dating AD 1950). The samples
derive from 114 unique locations around the Australian coastline, spanning fromMer (Murray
Island) in the north (10ºS) to Hobart (lutruwita) in the south (43ºS), and from Shark Bay
(Gutharraguda) in the west (113°E) to North Stradbroke Island (Minjerribah) in the east
(153°E) (Tables S1–3; Figure 1). Full details are presented in Table S1 and all data points are
plotted by laboratory number in Figures S1–9. Specimens from the Veneridae and Arcidae
families comprise almost half (47%, n=136) of the dataset (Table 1).

In total, 110 samples did not meet the selection criteria and were excluded from the analysis
(Table 2). Fifty-nine percent of ΔR values obtained prior to this study were excluded. Most
values in the full dataset (see Table S1) were excluded as they were not bivalves (n=52;
Criterion #1); because 14C ages from shells in the same lot failed the chi-squared test (n=21;
Criterion #8); or because the period of collection could not be confidently limited to ≤1 year
(n=20; Criterion #4). Smaller numbers of samples were rejected where determined F14C values
showed that mollusks were live-collected after AD 1950 (n=7; Criterion #3), where samples
were not live-collected or where there was uncertainty about live-collection status (n=5;
Criterion #2), where the sample was a bivalve but not a suspension feeder (n=3; Criterion #7),
where the collection location was unknown or where there was uncertainty about the collection
location (n=1; Criterion #5), and where the mollusk species was not identified or where there
was uncertainty over species identification (n=1; Criterion #6).

Statistically different ages derived from shells in the same museum lot may have several
possible explanations. Culleton et al. (2006) and Jones et al. (2007) have documented
significant intrashell 14C variability. These impacts are usually associated with areas of near-
shore upwelling. However, other short-term impacts may influence 14C in individual growth
bands, such as heightened storm activity resulting in higher rates of mixing of atmospheric
carbon into marine waters (Goodfriend and Flessa 1997). This could be a particular problem
for older legacy marine reservoir values obtained on whole mollusk valves, potentially
averaging different 14C abundances across the growth of the mollusk. The precise provenance
of samples could also explain some variability/unexpected values. The level of museum
documentation available for most specimens was not specific enough to determine whether
collection occurred from enclosed or semi-enclosed water bodies (e.g., estuary or bay versus
adjacent open coasts). Specimens living in enclosed water bodies with incomplete exchange
with the open ocean could returnΔR values at variance with adjacent well-mixed surface ocean
values (e.g., Ulm 2002).

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Table 1 Mollusk families represented in the dataset.

Family # samples # species

Veneridae 100 24
Arcidae 36 10
Neritidae 27 3
Donacidae 25 2
Mesodesmatidae 22 3
Glycymerididae 15 1
Pectinidae 15 7
Cardiidae 9 3
Volutidae 5 1
Pteriidae 4 3
Mactridae 3 2
Patellidae 3 1
Potamididae 3 2
Turbinidae 3 2
Cerithiidae 2 1
Cypraeidae 2 2
Cyrenidae 2 1
Limidae 2 1
Muricidae 2 1
Tellinidae 2 2
Buccinidae 1 1
Carditidae 1 1
Chitonidae 1 1
Crassatellidae 1 1
Haliotidae 1 1
Mytilidae 1 1
Phasianellidae 1 1
Pinnidae 1 1
Placunidae 1 1
Tegulidae 1 1
TOTAL 292 82

Table 2 Primary reason samples were excluded from analysis, following the inclusion criteria
hierarchy.

# Criterion
#

samples %

1 Not Bivalvia 52 47.3
8 Ages from Same Lot, Pair, or Valve have 14C ages that are Statistically

Different
21 19.1

4 Collection Date Not Confined to ≤1 Year 20 18.2
3 Not Live-Collected ≤AD 1950 7 6.4
2 Not Live-Collected 5 4.5
7 Not Suspension-Feeder 3 2.7
5 Unknown Collection Location 1 0.9
6 Species Not Identified 1 0.9

TOTAL 110 100

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The remaining 182 accepted ΔR20 values range from 68 ± 24 14C years at Port Hedland
(Marapikurrinya) in Western Australia to –337 ± 46 14C years at Mornington Island (Gununa)
in the southern Gulf of Carpentaria in Queensland (see ΔR20 Atlas in Figures S10–18). Most
sets of local values are internally consistent, reflecting the dominant influence of regional
oceanography. Most Australian coasts are adjacent to broad and shallow areas of the
continental shelf (<75 m deep), with only a few localities like Cape Range in Western Australia
<10 km from the edge of the crustal continental shelf.

MeanΔR values for major regions in Australia are shown in Figure 2 and Table S4. There are
three areas where published coral 14C data are available in the current study time frame (AD
1841–1950) including southeast Queensland, Bass Strait, and southeast Tasmania. For the first
region, a meanΔR value of –166 ± 27 14C years (see Table S5) was derived from 116 coral data
points from Heron Island and Abraham Reef (Druffel and Griffin 1993, 1999), Masthead
Island (Wu et al. 2021) and Heron Reef (Hua et al. 2015). This value agrees well with our mean
ΔR value of –167 ± 12 14C years for this region (Figure 2). The mean ΔR value for the Bass
Strait based on U-Th dated deep-sea corals (n=9 from AD 1865–1946; Komugabe-Dixson
et al. 2016) of –128 ± 33 14C years (see Table S6) also agrees well with our value for this area of
–120 ± 13 14C years (Figure 2). For southeast Tasmania, there is a coral datum for North Sister
at AD 1856 indicating a ΔR value of –117 ± 41 14C years (Komugabe-Dixson et al. 2016; see
Table S6), which overlaps with our value for this region of –111 ± 14 14C years within 1σ
uncertainties (Figure 2). The strong concordance between our shell-based and published coral-
derived ΔR values gives us confidence in our mollusk-derived ΔR values.

There is a notable depletion in ΔR values southwards along the eastern Australian coastline
coincident with the East Australian Current (EAC) (Figure 2). Although not a major difference
(∼40 14C years from –190 years in northern Queensland to –152 years for southern New South
Wales), it is significant and somewhat surprising given the well-equilibrated nature of waters of
the EAC along the length of the eastern Australian seaboard. In terms of simple oceanographic
conditions, we would expect very similar ΔR values along the entire east coast south to
southern New South Wales where the Tasman Front breaks off (Wijeratne et al. 2018). It is
possible that the enrichedΔR values reported here for areas of northeast Australia impacted by
the EAC result from the extended period of atmospheric-ocean surface exchange during
transport along the northeast seaboard with limited mixing with older subsurface waters.
Enriched ΔR values have been associated with 14C enrichment of ocean waters in shallow
marine environments subject to active wave and wind action (Forman and Polyak 1997). In
contrast, much of the southeast Australian coastline is impacted by intermittent upwelling
when northerly winds and eddies from the EAC bring water from offshore into near-shore
waters (CSIRO 2012).

The ΔR values along the west coast of Australia are substantially depleted compared with the
values for the east and north coast of Australia (Figure 2). There is a confluence of source
waters on the west coast: in the north the Holloway Current is fed by the Indonesian
Throughflow and Eastern Gyral Current whereas the South Indian Counter Current feeds the
Leeuwin Current on the mid-Western Australian coast and the southwest coast is impacted by
the South Indian Counter Current from the west as well as the Leeuwin Current from the north
(Wijeratne et al. 2018). The northeast coast area is also subject to upwelling where tidal
motions bring deeper nutrient-rich waters to the surface (CSIRO 2012). Although the west
coast is fed by different water sources, their average ΔR values are very similar, overlapping
with each other within 1σ (see Figure 2).

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The variability in ΔR noted above for the east and west coasts of Australia is at odds with
Ulm’s (2006) previous assumption, based on fewer data points, that ΔR values were very
similar along both coastlines. Ulm (2006) also suggested thatΔR values in southeast Australia
(extending from southern New South Wales, Victoria and to around Tasmania), would be very
difficult to predict owing to localised variation in currents and local upwelling. However, the
data reported here (albeit with limited data available for Tasmania) indicate that the general
magnitude of marine reservoir variability is similar across this region.

These new data suggest general uniformity in the magnitude ofΔR across the Torres Strait and
northern Cape York Peninsula, with more negative values in the southern Gulf of Carpentaria.
The enriched ΔR values documented here are associated with the shallow waters of Torres
Strait and the Gulf of Carpentaria where there are high rates of atmospheric-ocean surface 14C
exchange and less mixing with older subsurface waters (cf. Petchey 2009; Ulm et al. 2009). As
noted previously, such 14C enrichment of ocean waters may occur in shallow marine
environments subject to active wave and wind action (Forman and Polyak 1997), exacerbated
in this region by input of monsoon runoff combined with the less open circulation of the Gulf.

The new values broadly spanning most of the Australian coastline provide more confidence in
characterisation of regional MRE, with high-resolution values derived from a wider range and
larger number of samples, and from a range of geographic contexts. The large error estimates

Figure 2 Map of Australia, showing determined pooled ΔR values and major surface
ocean currents (after Wijeratne et al. 2018). IndividualΔR values selected for pooling were
all accepted values within a contiguous area, with pooledΔR value groupings separated by
large lengths of coastline with no values, but within a dominant marine surface current.
Average ΔR values are used here to broadly characterize ΔR variability around the
Australian coastline. We recommend researchers use a location specific ΔR value
calculated using the AustralianΔR Calculator, available at: https://delta-r-calc.jcu.io/ (see
below). See Table S4 for pooled ΔR methods and statistics.

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associated with previous ΔR values may have masked our appreciation of variability in the
MRE around Australia.

Australian ΔR Calculator

The interpolated krigedΔR surface is shown in Figure 3 and the overall standard error surface
in Figure 4 (combining both the standard errors of the originalΔRmeasurements, and those of
the interpolation process). Figure 5 shows modeled predictions at selected locations around the
coast of Australia.

ΔR values and the overall standard errors for any location around the Australian coastline can
be calculated using the online Australian ΔR Calculator available at: https://delta-r-calc.jcu.io/.
ΔR values produced by the calculator can be used with theMarine20 calibration dataset (Heaton
et al. 2020) and common radiocarbon calibration programs including OxCal (Bronk Ramsey
1995) and CALIB (Stuiver and Reimer 1993) for age calibration of radiocarbon ages on
Australian marine samples.

Future Research Directions

This study aimed to provide a robust understanding of the marine radiocarbon reservoir effects
in Australia and improve the accuracy of radiocarbon dating of marine materials. A more
complete understanding ofΔR variability would benefit from broadening this study to include
more locations and more suspension-feeding mollusk species, particularly a broader range of
species than currently represented in 14C age datasets. Species-specific ΔR predictions can be
further refined with larger numbers of samples representing robust stratification of species (e.g.,
Petchey et al. 2012, 2013), to further refine knowledge and application ofΔR variability. Live-
collected mollusks held in museums outside Australia and in private collections are important
potential additional sampling sources. Additional specimens may be identified in Australian
collections as they are progressively electronically databased.

Samples used in this study represent the majority of Australian coastlines, with notable
concentrations around population centres where late nineteenth and early twentieth century
shell collecting was focussed. Some stretches of coastline are poorly represented in the accepted
ΔR dataset, such as the Great Australian Bight between Spencer Gulf and Esperance (ca. 1650
km of coastline), between Esperance and Perth in southwest Australia (ca. 950 km), between
Melbourne and Adelaide (ca. 750 km), between the Mitchell Plateau and Darwin (ca. 750 km),
and between Perth and Shark Bay in central Western Australia (ca. 700 km). Other locations
with documented concentrations of archaeological shell deposits also have no localΔR values,
such as the north coast of New South Wales and the north and west coasts of Tasmania.

The values recommended in this study should only be considered reliable for the recent past,
with samples collected in the nineteenth and early twentieth centuries. ΔR fluctuates through
time, responding to 14C activity in source waters. Hua et al.’s (2015, 2020) study of corals from
the Great Barrier Reef demonstrates largeΔR variations of ca. 490 14C years between 5500 and
7000 cal BP, while ΔR has been relatively stable in this region over the past ca. 5500 years (see
also Komugabe-Dixson et al. 2016; cf. Petchey 2020; Petchey et al. 2023). Further studies of
temporal variability are needed to characterize the magnitude and spatial variability of MRE
in the past. Even more substantial changes in ΔR are likely during periods of sea-level change
associated with glaciation/deglaciation (Heaton et al. 2023). Dating of shell/charcoal paired
samples from archaeological sites in Australia has often yielded ambiguous results, largely

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attributable to the low degree of confidence in the temporal association of many paired samples
(Gillespie and Temple 1977; Hughes and Djohadze 1980; Ulm 2002). One way to address this
challenge is to develop local marine calibration curves by expanding regional sample sizes to
examine ΔR through time in particular localities (e.g., Petchey and Schmid 2020). Large-scale
U-Th dating programs of long-lived and fossil corals are likely to provide some of the most
robust records using current techniques. Another way is to ensure that paired shell/charcoal
samples are obtained from high-integrity contexts of well-stratified sites employing fine-
grained excavation methods and ensuring that the charcoal (or unburnt plant matter) is from
short-lived plant parts such as seeds or leaves (Petchey et al. 2012, 2013).

Future studies could also shed further light on short-term variability in ΔR through
implementing intrashell dating programs paired with sclerochronological analysis (Culleton
et al. 2006). Similarly, stable isotope analysis may help shed light on intraspeciesΔR variability
in the same taxa living in different environments.

CONCLUSION

This study represents the largest regional assessment of ΔR variability in the world. Although
equatorial, tropical, and subtropical waters exhibit low reservoir ages, this study demonstrates
significant variability around the Australian landmass that is closely related to regional
hydrological conditions. These data suggest relative geographical uniformity in open ocean

Figure 3 Interpolated kriged ΔR (14C years) surface. Color scale shows range of ΔR
values from enriched in red to depleted in dark blue. The kriging layer extends 300 km
offshore from the closest mainland point.

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marine carbon reservoir variability across east, southeast, south, west, northwest, and north
Australia, in the late nineteenth and early twentieth centuries. The new values provide more
confidence than previous studies, with the more precise values derived from a wider range of
species and from a wider range of geographic contexts. Systematic evaluation of legacy MRE
studies using strict sampling criteria highlights systemic problems with sample selection and
provenance as well as species identification. Legacy marine reservoir data points should only be
used with caution and following appropriate evaluation. There is a need to broaden the study
to include more locations and marine materials and expand regional sample sizes to examine
ΔR through time in particular localities, to address challenges in developing local marine
calibration curves. Understanding ΔR through time is significant because accurate marine
reservoir corrections for mollusks and other marine taxa are central to debates concerning
changes in Aboriginal and Torres Strait Islander societies, cultures, and technologies through
the archaeological record, refining sea-level curves and the geomorphological development of
coastal environments. The results reported here will support research in many fields by
providing a more secure characterisation of local marine reservoir conditions.

Figure 4 Overall standard error (14C years) surface (combining both the standard errors of the original ΔR
measurements, and those of the interpolation process). Color scale shows range of ΔR standard errors from small in
blue with large in red. The kriging layer extends 300 km offshore from the closest mainland point.

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ACKNOWLEDGMENTS

We respectfully acknowledge the First Nations Traditional Owners and custodians of the
lands, seas, and skies where this study took place. SU is the recipient of an Australian
Research Council Future Fellowship (project number FT120100656). This project was
supported by the Australian Institute of Nuclear Sciences and Engineering funding scheme
(AINGRA06181, AINGRA07150, AINGRA08063, AINGRA09025) and ARC Centre of
Excellence for Australian Biodiversity and Heritage (CE170100015). For assistance and
support in accessing and sampling malacological collections, we thank Val Attenbrow, Ian
Loch, Mandy Reid, and Alison Miller (Australian Museum), Lisa Kirkendale and Corey
Whisson (Western Australian Museum), Thierry Laperousaz and Peter Hunt (South
Australian Museum), John Healy and Darryl Potter (Queensland Museum), and Chris
Rowley (Museums Victoria). Robin Twaddle and Katherine Woo also assisted with
locating specimens. For advice on previous samples, we thank Jamie Shulmeister
(University of Canterbury).

Figure 5 Australian ΔR (14C years) Calculator modeled predictions at selected locations around the coast of
Australia. Kriging was performed for all pixels with a size of 10 km. The kriging layer extends 300 km offshore from
the closest mainland point. Color scale shows range of ΔR values from enriched in dark blue to depleted in red.

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SUPPLEMENTARY MATERIAL

To view supplementary material for this article, please visit https://doi.org/10.1017/RDC.
2023.95

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Australian Marine 14C Reservoir Effects 1159

https://doi.org/10.1017/RDC.2023.95 Published online by Cambridge University Press

https://doi.org/10.1029/2017JC013221
https://doi.org/10.1016/j.quascirev.2017.11.030
https://doi.org/10.11141/ia.36.6
https://doi.org/10.1029/2006GL028875
https://doi.org/10.1029/2006GL028875
https://www.marinespecies.org
https://doi.org/10.14284/170
https://doi.org/10.14284/170
https://doi.org/10.1029/2019JC015979
https://doi.org/10.1029/2019JC015979
https://doi.org/10.1017/RDC.2020.141
https://doi.org/10.1017/RDC.2020.141
https://doi.org/10.1017/RDC.2023.95

	AUSTRALIAN MARINE RADIOCARBON RESERVOIR EFFECTS: &Delta;R ATLAS AND &Delta;R CALCULATOR FOR AUSTRALIAN MAINLAND COASTS AND NEAR-SHORE ISLANDS
	INTRODUCTION
	METHODS
	Synthesis of Previous Studies
	Identification of Samples in Museum Collections
	Selection Criteria
	Physical Collection of Samples
	Radiocarbon Dating
	Calculation of &Delta;R
	Stable Isotope Analyses
	Modeling &Delta;R Variability around the Australian Coast

	RESULTS AND DISCUSSION
	Australian &Delta;R Calculator
	Future Research Directions

	CONCLUSION
	ACKNOWLEDGMENTS
	SUPPLEMENTARY MATERIAL
	REFERENCES