a multiproxy reconstruction of hebridean (nw scotland) spring sea

Palaeogeography, Palaeoclimatology, Palaeoecology xxx (2013) xxx–xxx

PALAEO-06518; No of Pages 11

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Palaeogeography, Palaeoclimatology, Palaeoecology

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A multiproxy reconstruction of Hebridean (NW Scotland) spring seasurface temperatures between AD 1805 and 2010

D.J. Reynolds a,⁎, P.G. Butler a, S.M. Williams a, J.D. Scourse a, C.A. Richardson a, A.D. Wanamaker Jr. b,W.E.N. Austin c, A.G. Cage d, M.D.J. Sayer e

a School of Ocean Sciences, College of Natural Science, Bangor University, Menai Bridge, Anglesey LL59 5AB, UKb Department of Geological & Atmospheric Sciences, Iowa State University, 50011-3212, USAc School of Geography and Geosciences, University of St. Andrews, St Andrews, Fife KY16 9AL, UKd School of Physical and Geographical Sciences, Keele University, Staffordshire ST5 5BG, UKe NERC National Facility for Scientific Diving & Dunstaffnage Hyperbaric Unit Scottish Association for Marine Science, Dunbeg, Oban, Argyll PA37 1QA, UK

⁎ Corresponding author. Tel.: +44 1248382874.E-mail addresses: [email protected] (D.J. Reyn

(P.G. Butler), [email protected] (S.M. Williams), [email protected] (C.A. Richardson), adw@[email protected] (W.E.N. Austin), a.g.cage@[email protected] (M.D.J. Sayer).

0031-0182/$ – see front matter © 2013 Published by Elhttp://dx.doi.org/10.1016/j.palaeo.2013.05.029

Please cite this article as: Reynolds, D.J., et al.AD 1805 and 2010, Palaeogeography, Palaeo

a b s t r a c t
a r t i c l e i n f o
Article history:Received 2 February 2013Received in revised form 10 May 2013Accepted 28 May 2013Available online xxxx

Keywords:Glycymeris glycymerisDog cockleSclerochronologySea surface temperaturesHebridean shelf seaHoloceneMultiproxy

There is currently a deficiency of annually-resolved temperature series from the marine environment. Wepresent a multiproxy reconstruction of Hebridean shelf sea (Tiree Passage; NW Scotland) spring sea surfacetemperatures (SSTs) for the period AD 1805–2010. The reconstruction is based on the growth increment se-ries from the first absolutely dated annually-resolved multi-centennial Glycymeris glycymeris bivalve molluscsclerochronology coupled with previously published stable oxygen isotope data (δ18O) from benthic foraminif-era sampled from a dated sediment core from nearby Loch Sunart. The independent series contain significantcorrelations with SSTs across complementary frequency domains. The low frequency component of the sedi-mentary archive was combined with the mid and high frequency components of the G. glycymeris chronologyindices to create a single multiproxy series. Split calibration-verification statistics (reduction of error, RE, coeffi-cient of efficiency, CE, and R2) indicate that the multiproxy record, calibrated to local instrumental sea surfacetemperatures, contains significant precision and skill at reconstructing spring SSTs (RE = 0.59, CE = 0.26,R2 = 0.54). These data demonstrate that bivalve sclerochronologies, when combined with low frequency prox-ies such as sediment archives, can facilitate statistically robust reconstructions of palaeoceanographic variabilityduring the late Holocene for hydrographically-significant regions of the temperate marine system previouslyvoid of annually-resolved archives. The reconstructed SSTs contain a general warming trend of 0.60 ± 0.14 °Cper century. Only four years in the reconstructed period (1999, 2000, 2002 and 2003) exceed temperaturesgreater than two standard deviations higher than the reconstructed mean SST (9.03 °C), whilst just threeyears in the first half of the 19th century (1835, 1838 and 1840) fall more than 2σ below the reconstructedmean (6.80 °C).

© 2013 Published by Elsevier B.V.

1. Introduction

The Intergovernmental Panel for Climate Change (IPCC) 2007 report(Jansen et al., 2007) identified the generation of detailed climate recon-structions across a broad range of frequencies from both atmosphericand marine systems as critical to understanding the mechanisms anddynamics of natural and anthropogenic climatic change. Proxy recon-structions are required because direct instrumental observations ofpast environmental change are spatially incomplete and temporallyconstrained generally to the period post AD 1860 – all dates reported

olds), [email protected]@bangor.ac.uk (J.D. Scourse),tate.edu (A.D. Wanamaker),.ac.uk (A.G. Cage),

sevier B.V.

, Amultiproxy reconstructionclimatology, Palaeoecology (2

hereafter are AD – (Hurrell and Trenberth, 1999; Smith andReynolds, 2003). Palaeoclimate proxies can provide environmentalrecords which span several years to millennia covering the full spec-trumof temporal frequency domains and as such they can help facilitatethe calibration of climate models (Braconnot et al., 2012).

There is an increasing emphasis on utilizing multiple proxies to re-construct past climatic conditions (Gedalof et al., 2002; Black et al,2009; Trouet et al., 2009). Such reconstructions have been demon-strated to be sensitive to large scale climate parameters such as NEAtlantic SSTs (Cunningham et al., 2013), the North Atlantic Oscillation(NAO, Trouet et al., 2009) and the Atlantic Multidecadal Oscilation(AMO, Mann et al., 2009). Hitherto however themajority of multiproxyreconstructions have combined proxies that are of equivalent temporalresolution. It would be advantageous to utilizemultiple proxies of com-plementary temporal resolution, allowing the combination of low reso-lution proxies with high resolution records, that are deficient in lowfrequency variability, to facilitate the reconstruction of the complete

of Hebridean (NWScotland) spring sea surface temperatures between013), http://dx.doi.org/10.1016/j.palaeo.2013.05.029

http://dx.doi.org/10.1016/j.palaeo.2013.05.029

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2 D.J. Reynolds et al. / Palaeogeography, Palaeoclimatology, Palaeoecology xxx (2013) xxx–xxx

spectrum of climatic variability. Such a process would negate issuesassociatedwith the “segment length curse” (Cook et al., 1995) and facil-itate the use of sclerochronologies constructed from bivalve specieswith relatively short mean longevities in climate reconstructions.

Although crossdated annually-resolvedpalaeoenvironmental archivessuch as tree-rings (Roig et al., 2001; D'Arrigo et al., 2012), and high reso-lution (up to annual, but not crossdated) archives such as ice cores(Grootes et al., 1993; McManus et al., 1994) and corals (Peirano et al.,2004; Corrège, 2006) have enabled reconstructions of atmospheric andtropical marine climates respectively, until recently equivalent proxiesfor themiddle and high latitude oceans have been lacking. This deficiencyis nowbeing addressed following the realization that the variability in theannual growth increments in the shells of long-lived bivalve molluscs,such as Arctica islandica L. and Glycymeris glycymeris L., can be used tobuild long chronologies using techniques derived fromdendrochronology(Marchitto et al., 2000; Brocas et al., 2013; Butler et al., 2013). Suchabsolutely-dated chronologies contain geochemical and increment-width proxies which, when successfully calibrated against instrumentalseries, can be used for palaeoenvironmental reconstructions at annualresolution (Schöne et al., 2005; Black et al., 2011; Brocas et al., 2013).Hitherto, reconstructions of marine conditions using sclerochronologyhave been largely based on shell-derived geochemical proxies (Schöneet al., 2005;Wanamaker et al., 2008, 2012); the application of growth in-crementwidths, widely used in dendrochronology as a proxy for air tem-perature (Luckman et al., 2004) and precipitation (Case and MacDonald,1995; Tan et al., 2011), has not been fully explored.

In recent decades Arctica islandica has become a keysclerochronological archive due in part to its great longevity(>500 years, Butler et al., 2013), demonstrated annual periodicityof growth line formation (Jones, 1980; and Witbaard et al., 1994)and proven synchronous nature of growth line formation withinand between local populations (Butler et al., 2010). Arctica islandicais widely distributed in the Atlantic coastal shelf seas of NWEurope andNE America (Dahlgren et al., 2000). Despite this wide geographicaldistribution, the temporal and spatial extent of A. islandica populationsis constrained to muddy sand to soft mud substrata in water depths of5m to ~250 m. There are therefore clear advantages to further developadditional annually resolved sclerochronological archiveswhich inhabitenvironments complementary to A. islandica. Such archives may permitinvestigation of areas of oceanographic and hydrographic interest wherethere are currently no known A. islandica populations.

One such species is the dog cockle, Glycymeris glycymeris (L.), alarge (up to 65 mm shell length in Scottish waters) marine bivalvemollusc which inhabits the shallow shelf seas of NW Africa and Europein coarse sand to gravel substrata in water depths of 5m to 100m(Hayward and Ryland, 1995). The habitat preference of G. glycymerisis complementary to that of Arctica islandica and as such its use as apalaeoenvironmental archive would enable additional areas of oceano-graphic interest to be investigated. It has been demonstrated that theperiodic growth increments in G. glycymeris are formed annually andin synchrony within populations (Berthou et al., 1986; Brocas et al.,2013; Royer et al., 2013). Previous studies have also shownG. glycymeristo live in excess of 100 years (Ramsay et al., 2000). Brocas et al (2013)and Royer et al. (2013), utilising live-collected specimens, demonstratethat both the growth increment widths and the geochemical composi-tion of the shell calcium carbonate are sensitive to localised sea watertemperature variability. These results indicate that G. glycymeris chro-nologies could facilitate the reconstruction of past marine environ-ments at annual resolution and with absolute dating precision overrecent centuries. Such reconstructions would only be temporally andspatially limited by the availability of shell material in the fossil record.

In this study we examine both live- and dead-collected Glycymerisglycymeris shells collected from the Tiree Passage (TP), located betweenthe islands of Mull and Tiree in NW Scotland, UK. This area is of signifi-cant oceanographic and climatic interest due to its location in the easternfringe of the Gulf Stream/North Atlantic Current (GS/NAC) system. The

Please cite this article as: Reynolds, D.J., et al., Amultiproxy reconstructionAD 1805 and 2010, Palaeogeography, Palaeoclimatology, Palaeoecology (2

water body which flows northwards through the TP originates fromtwo sources, the Scottish Coastal Current (SCC) and the ContinentalSlope Current (CSC), the CSC being a major branch of the GS/NAC (Inallet al., 2009). The SCC and CSC are distinct water masses with the SCCbeing less saline and cooler due to origins in theNorth Channel (betweenN Ireland and Scotland) and the Celtic Sea; the CSC waters however,originating from the oceanic GS/NAC, are warmer and more saline(Inall et al., 2009). Data from the oceanographic mooring that hasbeen maintained in the TP since June 1981 highlights pronouncedwarming trends in sea water temperatures over the past two decades(0.57 °C per decade, Inall et al., 2009). However the short nature of the in-strumental record precludes the assessment of these trends relative tolong-term climatic variability. It would therefore be advantageous to de-velop a robust proxy archive which could facilitate the reconstruction ofseawater temperatures over past centuries in the TP allowing for the ex-amination of the context of these recent trends relative to longer-termenvironmental variability.

The objectives of this study were to 1) examine the internal growthincrement widths in live- and dead-collected Glycymeris glycymerisfrom the TP; 2) to crossdate the growth increment series and to con-struct the first statistically robust multi-centennial G. glycymerissclerochronology; 3) to define the correlation between the masterG. glycymeris sclerochronology and local oceanographic instrumentaltimeseries; 4) to combine the G. glycymeris sclerochronology withlocal marine proxies that contain low frequency variability in order tofacilitate the reconstruction and examination of environmental variabil-ity across the full spectrum of temporal frequency domains.

2. Methods

2.1. Shell collection and preparation

Two collections of Glycymeris glycymeris shells were made fromthe TP (Fig. 1). In 2006 four live and 136 paired and single G. glycymerisvalves were collected by means of mechanical dredge deployed bythe RV Prince Madog in 50–55 m water depth. In 2011 an additionalten live and 52 dead G. glycymeris were collected by scientific divingfrom a site in close proximity to the dredging location (ca. 25 m waterdepth). Both collection sites were adjacent to the instrumental oceano-graphic mooring buoy in the TP (56°37.75N, 6°24.00W, Inall et al.,2009).

The morphometrics (shell length, height, width and mass) andshell condition (ligament preservation, margin condition, conditionof the nacre and periostracum preservation) of all the shells collectedwere measured and recorded in the School of Ocean Science (BangorUniversity, UK) shell database. The recorded biometrics were thenutilised to select optimal dead-collected shells (least shell damage, liga-ment preserved, articulated) for sectioning (see Butler et al., 2010).

All the live- and selected dead-collected shells were sectionedusing the methodology described by Ramsay et al. (2000, 2001). Arough 1-2 cm section was cut using a diamond tipped blade mountedon a rotary grinding saw from the hinge through to the ventral marginencapsulating the apex of the umbone and the axis of maximum growththrough to the ventral margin. The cut section was then embedded intoKleer set epoxy resin before a final sectionwas cut along the axis ofmax-imum growth (ca. 5–10 mm width, Fig. 2). The cut surface was groundusing carborundum paper (grades 120–4000). The polished shell sec-tions were then etched in 0.1M HCl for 90 s, soaked in a water bathand left to air dry (Ramsay et al., 2000, 2001; Brocas et al., 2013). Acetatepeel replicas, constructed using methods described by Richardson(2001), were digitally photographedunder a Leica light-transmittingmi-croscope under 2.5×, 5×and10×magnification using a 3-megapixel SoftImaging System digital camera and AnalySIS and later Buehler Omnimetimaging software (Butler et al., 2010). Photomosaics were constructedfrom the individual photomicrographs using Adobe Photoshop CS4 andBuehler Omnimet. The growth increment series were digitally measured



Fig. 1. A) Map of the Sea of the Hebrides with the approximate positions of the Continental Slope Current (CSC, dark grey arrows) and the Scottish Coastal Current (SCC, light greyarrows) (current positions from Inall et al., 2009); the black box marks the position of map B. B) Location map identifying the position of the Tiree Passage (TP) oceanographicmooring in NW Scotland which is also the location from where all the Glycymeris glycymeris shells examined in this study were collected. KP denotes the position of the KeppelPier sea surface temperature series; ST denotes the position of the Loch Sunart coring site from where the δ18Oforam series originates. SM indicates the position of the Sound of Mull.

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three times through the hinge and a mean value taken to reduce thevariability resulting from measurement error (Brocas et al., 2013). Thegrowth measurements were taken through the hinge rather thanthe ventral margin portion as the hinge provides a more concise,yet equally clear and complete, record of the entire growth record(Ramsay et al, 2000).

2.2. Crossdating and chronology construction

Standard sclerochronological statistical techniques were used tocrossdate the Glycymeris glycymeris growth increment series (Scourseet al., 2006; Brocas et al., 2013; Butler et al., 2013). The year of collection(2006 and 2011) was assigned to the most modern (outermost) growthincrement in the live-collected specimens. For the dead-collected shells,where the date of death was unknown, 2006 was arbitrarily assigned tobe themostmodern growth increment (thiswas doneas the SHELLCORRsoftware requires all growth increment series to be associated with aspecific calendar year). All subsequent growth increments were datedrelative to the outermost and modern growth increment. The graphicalcorrelation application SHELLCORR V5b (run in Matlab v13) was usedto crossdate the shell growth series. Log transformation and flexible

Fig. 2. A) Illustration demonstrating the line of section along the axis of maximum growthlower photograph) and the resulting cross section. U and V denote the positions of the umbothe tooth (enlargement of box B in plate A) and a single photomicrograph from the mosaic


spline detrending were used to remove ontogenetic growth trendswhilst preserving high frequency variability in order to compareinter-annual growth variability (Butler et al., 2010). Running correlationanalysis, with correlations calculated over a seven to 45 year runningwindow, was used to assess the temporal stability of the correlationsand detect possible offsets/lags between shell series.

The successfully crossdated shell series were used to construct amaster sclerochronology using the dendrochronology applicationARSTAN for Windows (version 41d, Cook and Krusic, 2007). Theoriginal (non-detrended) growth series that had been successfullycrossdated were first collated using FMT.exe into a compact formattedfile. Both ARSTAN and FMT.exe are available through the dendrochro-nology software library (http://www.ltrr.arizona.edu/software.html).We used detrending methods that have been used previously insclerochronological studies to produce Arctica islandica and Glycymerisglycymeris chronologies (Butler et al., 2010, 2013; Brocas et al., 2013).An adaptive power transformation was first applied to each series toequalize variance throughout the growth series (Cook and Peters,1997) and negative exponential detrending was then applied to thetransformed series to remove the ontogenetic growth curve. Threemastersclerochronologies (standardized, residual and arstan) were constructed

from the umbone to the ventral margin in a single G. glycymeris valve (dashed line onne and the ventral margin portions of the shell respectively. B) A digital photomosaic ofillustrating the clarity of the growth increment series in G. glycymeris shells.


http://www.ltrr.arizona.edu/software.html



by ARSTAN, each with differing degrees of reintegrated autoregressivemodeling (Cook and Krusic, 2007). Data was output both as a mastersclerochronology and as individually detrended growth increment series.

Expressed population signal statistics (EPS, Wigley et al., 1984)were used to assess the degree to which the chronology representedthe common population growth signal with respect to noise. EPS wascalculated over a running window of 50 years with 25 years overlap.

2.3. Chronology validation

Accelerator mass spectrometry (AMS) radiocarbon (14C) datingwas used to provide a test of the crossdating between the twolongest-lived dead- and the live-collected Glycymeris glycymeris incor-porated into themaster sclerochronology. In total four shell CaCO3 sam-ples were drilled using a handheld Dremmel drill, two from each of thelongest-lived dead collected specimens (shell ID #06004 and #0020).Samples were taken from the outer shell layer from the ventral marginand the umbone of each of the shell valves and analyzed at the UKNatural Environment Research Council Radiocarbon Laboratory (NRCF,East Kilbride, UK). Conventional 14C determinations were correctedfor a regional marine radiocarbon reservoir age effect (MRRE) usingΔR of −26 ± 14 years (Harkness, 1983; see Cage et al., 2006 for de-tails) and then calibrated using the online calibration program OxCal(Bronk Ramsey, 1994, 2001) whilst those with post-bomb (post 1950)dates were calibrated using regional bomb-pulse calibration curves(Scourse et al., 2012).

2.4. Environmental analysis

As the TP sea water temperature (referred to hereafter as TP SWT)series is relatively short (1981-2006) with some missing years (Inallet al., 2009), the chronology indices were compared with localizedmonthly SST timeseries from Keppel Pier, Oban, Scotland (KP, 55°44′ 55 N, 4° 54′ 20 W; measured mean monthly between 1953 and2007; www.bodc.ac.uk/data/). The TP instrumental series, situatedca.130 km north of KP, is a detailed record of seawater temperaturesmeasured 11 and 22m above sea bed (total water depth ca. 55 m,Inall et al., 2009). The KP series, however, is a direct record of SSTs.Due to the different geographic and hydrographic settings of the TPand KP records there may be differences in the timing, direction andamplitude of seasonal and annual variability. Linear regression andspatial field correlation analysis were conducted between the KP SSTs,TP SWTs and the ERSST V3b gridded SST dataset (Smith et al., 2008)to assess whether the KP timeseries adequately represented the vari-ability found in the TP and surrounding waters and, as such, their suit-ability for this analysis.

Pearson correlation coefficients were calculated between the chro-nology indices and the SST data over the entire common period as wellas using a split calibration-verification approach (North et al., 2006).The KP SST series was divided into two halves; the period 1981–2007was used to calibrate the chronology indices using linear regression anal-ysis. The data from 1953 to 1980, which was independent of the calibra-tion process, provided validation of the resulting reconstructed SSTs.Reduction of error (RE), coefficient of efficiency (CE) and coefficient ofdetermination (R2) were used to assess the sensitivity of the reconstruc-tion over the respective calibration and verification periods.

2.5. Multiproxy analysis

In order to reconstruct SST variability across the complete spectrumoffrequency domains we combined the Glycymeris glycymeris chronologyindices with the low frequency variability preserved in the δ18O recordof benthic foraminifera from a previously published sediment archive(δ18Oforam) cored from the main basin of Loch Sunart (ca. 50m waterdepth, Cage and Austin, 2008, 2010). The δ18Oforam record was the firstdecadal-scale reconstruction of British coastal temperature anomalies


spanning the last millennium (Cage and Austin, 2010). Loch Sunart islocated approximately 15 km to the east of the Tiree Passage and has alargely unrestricted exchange with the adjacent coastal waters ofthe Sound of Mull, notably into the main basin of Loch Sunart wheresub-halocline salinity remains stable and tracks the coastal ocean(e.g. Gillibrand et al., 2005). Benthic foraminiferal oxygen isotopesfrom this record have been interpreted as a record of summer tem-perature (Cage and Austin, 2010). The age control of the compositesedimentary record from Loch Sunart was recently indirectly testedby tephrochronology (Cage et al., 2011), further supporting the chrono-logical interpretation of the record based on various independent linesof evidence, including the identification of the post-AD1900 oceanicδ13C Suess effect (Cage and Austin, 2010).

As the construction of the δ18Oforam archive does not require anydetrending the record preserves the lowest frequency component ofSST variability. Combination of the low frequency variability in theδ18Oforam with the mid and high frequency variability contained in theGlycymeris glycymeris chronology therefore facilitates a more accuratereconstruction of SST variability.

The δ18Oforam data were converted to SST anomalies with a mean ofone and fitted with a cubic polynomial smoothing function allowing forinterpolation of the low frequency trends to annual resolution. The annu-al values from the cubic polynomial smoothing function were then usedas a scaling factor, by multiplying the associated annual polynomialsmoothing function value against the corresponding chronology indices,facilitating the low frequency from the δ18Oforam data to be transposedonto the mid and high frequency variability in the mean growth indices.The new (shell and δ18Oforam) annually resolved multiproxy series wasthen calibrated against the KP SSTs using the calibration–verificationmethods. In order to assess the spatial extent of the multiproxy SST re-construction we used spatial correlation analysis between the SST recon-struction and the HadISST1 gridded SST data set.

3. Results

3.1. Collection data and biometrics

In total, 133 single valves, three articulated and four live Glycymerisglycymeris were collected in a single tow of a mechanical dredge inSeptember 2006. An additional ten live, 48 single-valves and four artic-ulated dead G. glycymeriswere collected by scientific divers in April andAugust 2011. The shell specimens collected by dredging have a meanshell length of 57.6 mm (σ = 7.7 mm) whilst those collected by thedivers have a mean shell length of 60.8 mm (σ = 4.7 mm). Of the136 dead dredge-collected shells, 75 shells contained a large amountof bioerosion compared to only six of 52 dead specimens collected bythe divers. All 81 specimens with a high degree of bioerosion weredisregarded for sectioning due to the growth records being degradedand potentially incomplete.

3.2. Growth increment analysis and chronology construction

The annually-resolved internal growth increments in the shells ofthe Glycymeris glycymeris examined in this study were clearly visiblein the acetate peel replicas (Fig. 2B) permitting accurate measure-ments to be taken. The mean longevity of all the shells examined inthis study was 101 years (σ = 47) with a range of ages from nineto 192 years.

In total, the ten longest-lived live- and 12 dead-collected speci-mens were successfully crossdated, enabling the construction of themulti-centennial sclerochronology (Fig. 3). The four shortest livedlive-collected Glycymeris glycymeris were not crossdated as theirlongevities were insufficient to allow satisfactory overlap with otherspecimens to forma statistically significant crossdate. Themean longevityof the shells used to construct the sclerochronology was 83.7 years.Although the most modern increment present in specimens used in the


http://www.bodc.ac.uk/data/


Fig. 3. A) Raw growth increment measurements (grey lines) and mean annual growth increment data (black line); B–D) annual (grey lines) and running 5-year mean (black lines)standardized, residual and arstan chronologies respectively; E) running sample depth (number of shells in the chronology for any given year); F) the positions of each of the shellsin the chronology (each shell represented by an individual black line); and G) running segment lengths (grey line) and mean shell age (black line) for each year represented in thechronology.


chronology was 2011, this year was omitted from all further analyses asgrowth did not represent a complete year. The running EPS calculatedover a 50 year window with a 25 year overlap is stable at ca. 0.85 overthe period 1860–2010 (Fig. 4). Prior to 1860 the chronology does not con-tain a statistically robust EPS as the replication of shells in any given yearis reduced.


3.3. Verification of crossdating

The two AMS 14C determinations derived from the ventral marginsof shells #06004 and #0020 were dated as post-bomb (post 1950;Table S1). As a result, these determinationswere calibrated using the re-gional marine bomb-pulse curve (Scourse et al., 2012). The calibration



Fig. 4. Running expressed population signal (EPS, light grey line) with corresponding sample depth (N) and mean correlation (R) between the shell series (labelled black lines respec-tively). The dashed line signifies the target EPS of 0.85. EPS. The running correlations and sample depth are calculated over a 50-year window with a 25-year overlap.


dated the samples to the period 1965–1994. The two samples derivedfrom the umbonal regions had pre-bomb 14C ages and as suchwere cal-ibrated using the Marine 09 14C calibration curve (Reimer et al., 2009).The pre-bomb14C determinations were calibrated to the period from1724 to 1850.

3.4. Environmental analysis

Correlation analysis between the KP SST record and the ERSSTdataset identifies significant positive correlation coefficients(R > 0.60, N = 54 and P b 0.01) over the common period of 1953–2007. The areas identified by the analysis as significant are predomi-nantly the coastal shelf seas of the western British Isles and Ireland(Supplementary Figure S1). There is a small difference in the amplitudeof seasonal monthly SSTs between KP and the TP over the period 1981to 2005, likely due to the different water depths of the recorded series.Visual comparison of the annual averages suggests that the inter-annualfluctuations are very similar (Supplementary Figure S2).

Significant positive correlations (P b 0.01) were identified, overthe common period (1953-2007), between the arstan, standardizedand residual chronology indices and mean monthly, seasonal (spring,summer, autumn and winter) and annual KP SSTs. Correlations rangedfromR = 0.28 to R = 0.63 (N = 54; Fig. 5A). Correlations between theresidual chronology indices andmean January, July andOctober KP SSTswere non statistically significant. Examination of these relationshipsover split calibration-verification periods (1981–2007 and 1953–1980respectively) indicated that only correlations between the standardizedand arstan chronology indices and mean spring (March–May) SSTs andthe standardized indices andmeanMarch SSTswere consistently signif-icant over both periods (Fig. 5B and C). The strongest correlation coeffi-cients identified over the common period, calibration and verificationperiods were between the arstan chronology indices and mean springSSTs (R = 0.63, 0.74 and 0.46, N = 54, 54 and 27 respectively).

Fig. 6 suggests that low frequency variability present in the KP SSTdata, represented as linear trends over the calibration, verification(N = 27) and common periods (N = 54), are not precisely mirroredin the reconstructed SSTs. The corresponding RE and CE statistics(RE = 0.51 and CE = −0.28) also indicate that the reconstructedSSTs lack precision at the low frequency scale. We assessed the limitof low frequency variability that may be resolved in the chronologyindices using the expression 3/n, where n represents mean segmentlength (MSL) and 3/n is a realistic assessment of the lowest resolvablefrequency after segments of length n have been detrended (Cook et al.,1995). The lowest frequency variability preserved in the Glycymerisglycymeris sclerochronology would be 0.02 year−1 which equates toanoscillationwith a 45.9 year period.However, examination of the run-ning segment lengths (Figure S3) indicates that the lowest frequencypreserved varies from 0.02 to 0.07 year−1, oscillations with 13.9 to64.0 year periods respectively.


Analysis of the combined δ18Oforam/Glycymeris glycymeris proxyidentifies highly significant positive correlations with spring SSTs(R = 0.73, P b 0.01, N = 54). Positive RE, CE and high R2 statistics(RE = 0.59, CE = 0.26 and R2 = 0.54) indicate that the calibratedmultiproxy (shell and 18Oforam) series contains significant skill atreconstructing the spring SSTs and is sufficiently sensitive to detectthe shift in mean SST from the calibration to the verification period.

The spatial correlation analysis between the multiproxy SST recon-struction and the HadISST1 dataset for the N Atlantic (Fig. 8) showedsignificant (P b 0.01) positive correlations, over the period 1870-2010,with large areas of the North Atlantic coherent with the Gulf Stream/North Atlantic system.

4. Discussion

In this study we examined the internal growth increment series inshells of the common marine bivalve Glycymeris glycymeris collectedfrom the TP, NW Scotland. We successfully crossdated the annuallyresolved growth increments in ten live- and 12 dead-collected shellsand constructed the first multi-centennial (1805–2010) absolutelydated G. glycymeris sclerochronology. The chronology is also thefirst G. glycymeris chronology to successfully crossdate live- anddead-collected shells, indicating that it is possible to extend thegrowth increment series backwards through time by utilizing fossilmaterial. Sample replication and the degree of correlation between thecrossdated specimens contained in the chronology are similar to, orgreater than, other previously published sclerochronologies (Butleret al., 2010; Brocas et al., 2013). For the years prior to 1860 the low rep-lication within the chronology (n b 4) results in the EPS statistics fallingbelow 0.85, therefore interpretations for this period should be treatedwithmore caution (Wigley et al., 1984). The calibrated AMS 14C determi-nations from the ventral margins/umbones of the two longest-livedG. glycymeris are,withinuncertainties, in agreementwith the crossdatingand sclerochronological age determinations. The calibrated 14C determi-nations therefore provide independent evidence that the crossdating be-tween the dead- and live-collected specimens is valid.

The construction of the chronology was aided by the discovery ofspecimens with longevities of 185 and 192 years. These specimensare the longest-lived Glycymeris glycymeris shells that have so farbeen described and they considerably extend the previous maximumlongevity (101 years) reported by Ramsay et al. (2000). This may in-dicate that there is a latitudinal gradient in G. glycymeris longevity.The longevities reported by Ramsay et al. (2000) and Brocas et al.(2013) relate to specimens from the waters surrounding the Isle ofMan, while Royer et al. (2013) report a maximum longevity of just46 years from live shell material collected from northwest France, cur-rently the most southerly location with published data on G. glycymerisages. Although there is an observed trend between longevity and lati-tude, with longevity increasing from south to north, it is not possible,with the current available data, to identify a single parameter as the



Fig. 5. Correlation coefficients calculated between the standardized (grey bars), residual (black bars) and arstan (white bars) chronology indices over A) the entire common period(1953–2007); B) 1953–1980; and C) 1981–2007. Black horizontal bar (A, B and C) represents the 99% significance level.


principal driver of longevity. The trend therefore requires further inves-tigation to examine its validity and possible causation.

The comparison of the KP series with TP and gridded environmentaldata shows that it represents a significant degree of variabilitywith SSTsacross the coastal Hebridean shelf sea and as such it is suitable for com-parison with the Glycymeris glycymeris chronology indices.

The significant positive correlations between the chronologyindices and KP SSTs are stronger than those identified in previoussclerochronological studies such as Brocas et al. (2013) and Butleret al. (2010). Despite the growing number of studies that report alink between SST variability and Glycymeris glycymeris shell growth(Brocas et al., 2013 and Royer et al., 2013) the mechanisms of sucha relationship have yet to be identified. Two potential hypothesesare; 1) given thatmanyG. glycymeris live on the surface of the sedimentsrather than infaunally it is possible that the physiology (rate of respira-tion and/or metabolism) of the organisms are responding more directlyto changes in SST; 2) as Witbaard et al. (2003) have demonstrated, thegrowth of Arctica islandica is positively linked to food availability, ofwhich SSTs are one of a number of drivers (see Bresnan et al., 2009);the same could be true forG. glycymeris populations. It is unlikely that ei-ther of these mechanisms solely drive G. glycymeris growth; it is moreprobable that a combination ofmechanisms link SSTswith the variabilityof growth in the TP G. glycymeris population. However, this study pro-vides no direct evidence to test these hypotheses and further researchis necessary.

Fig. 6. Reconstructed SSTs (thin black line) derived by linear regression over the calibrationinstrumental series (thin grey line). The solid bold black/dark grey lines represent the associa(1981–2007) and verification (1953–1980) periods, whilst the dashed black/grey lines denote


Despite the strong correlation coefficients between the Glycymerisglycymeris chronology indices and spring SSTs, examination of the REand CE statistics calculated between the chronology indices and theKP SSTs (RE = 0.51 and CE = −0.28) and instability of the correla-tion coefficients, although still both significant, over the respectivecalibration verification periods (R = 0.74 and 0.46 respectively) indi-cates that the chronology does not contain sufficient low frequencyvariability to detect a small shift in themean SST between the calibrationand verification periods. Such a deficiency in low frequency variability islikely due to the necessity to detrend the growth records and relativelyshort nature of themean longevity (83.7 years) of the shell growth seriescontained in the chronology. Although G. glycymeris is long-lived bycomparison with other temperate marine organisms, its longevity is sig-nificantly shorter than dendrochronological archives. Dendrochronol-ogies that contain specimens with short mean longevities commonlysuffer from a lack of low frequency variability (variability with periodic-ities equivalent or greater than the species longevity). This problem hasbecome knownas the “segment length curse” (Cook et al., 1995). Variousstatistical methods have been deployed in dendrochronological studiesto mitigate the effects of the segment length curse, such as the use ofregional curve standardization (RCS) detrending rather than negativeexponential (Briffa et al., 1992), exclusion of short-lived specimensfrom the chronologies, or removal of the earliest years from the growthincrement series which would then negate the necessity of statisticallyremoving ontogenetic trends through detrending techniques similar to

period from the arstan chronology indices compared with the Keppel Pier Spring SSTted trends in the reconstruction and instrumental data respectively over the calibrationtrends over the entire common period (1953–2007).




those used originally by LaMarche (1974). Such methods could not beapplied in this instance because 1) a “high degree of replication” (Cooket al., 1995) is required for the construction of a reliable RCS curve; thenumber of dated G. glycymeris examined in this study is insufficient toproduce a valid RCS curve; and 2) the removal of the earliest years tonegate statistical detrending, or the removal of the shortest lived individ-uals to increase the MSL in the chronology, would have a detrimentaleffect on the sample replication of the chronology and as a result reducethe overall statistical robustness of the master chronology indices.

Themultiproxy record (Fig. 7, blue line) contains themost significantpositive correlations yet identified between SSTs and an annually re-solved temperate marine palaeoenvironmental archive. Over the entireinstrumental period (1953–2007) the multiproxy reconstruction con-tains 53.6% of the variability in spring SSTs for the Sea of the Hebrides.The significant RE and CE statistics suggest that the combined recordcontains significant precision and skill at reconstructing spring SSTsover both the calibration and verification periods. The significant CEstatistics indicates that the reconstruction is sensitive enough to detectthe 0.56 °C shift in SSTs between the calibration and verification periods.Mean squared error (MSE) was used as an assessment of the errorthroughout the reconstruction. Over the instrumental period (1953–2007)MSEwas 0.3 °C. Examination of theMSE for individual years indi-cates an apparent weakness in the capability of the reconstruction to de-tect abnormally cold years (spring SSTs b 7 °C). Of the four abnormallycold years contained in the 54-year instrumental record, all but onecontain significantly higherMSEs (MSE for the four years is 1.1 comparedto 0.3 for the entire instrumental period). Each of these increasedMSEs isdue to an overestimate of SST by themultiproxy reconstruction. As theseerrors are associated with the highest frequency component of the re-construction it is likely they originate from the Glycymeris glycymerischronology. One possible explanation for this overestimate of tempera-ture could be that the animals have an energy store from the previousyear that, in the event of an abnormally cold year, can be used to contin-ue shell growth. Given the nature of these errors, and its likely causation,it is not possible to identify for the period prior to the instrumentalrecord which years contain the increased errors. However, provid-ing the number of these abnormal years is constant through time,

Fig. 7. Multiproxy reconstructed and instrumental spring (April–June) SSTs (blue and red liand dashed black lines correspond to the reconstructed mean SST ±2σ. (For interpretation othis article.)


there is a 7% probability that any given year contains the increasederror margin (based on the number of abnormal years in the KP series,1953–2007).

Over the period of 1850–2004 the reconstructed spring SSTs (Fig. 7)show a significant linear warming trend of 0.60 ± 0.14 °C (95% CI)which is comparable to the general northern hemisphere SST trend of0.59 ± 0.20 °C over the same period reported by Rayner et al. (2006).Examination of the reconstructed decadal (calculated from 2000 to2009) SST averages identifies three decades that fall outside the mean±1σ. The period 1830-1839 has a reconstructed mean temperature of7.21 °C compared to the entire reconstructed mean of 7.91 °C ± 0.56,making this the coldest decade in the reconstructed period. The two de-cades from 1990-2009, withmean spring SSTs of 8.56 °C and 8.85 °C re-spectively, are the two warmest decades in the reconstructed period.Included in these decades are four years (1999, 2000, 2002 and 2003)which have reconstructed temperatures that exceed the reconstructionmean+2σ temperature (9.03 °C), whilst three years in the first half ofthe 19th century (1835, 1838 and 1840) fall more than 2σ below thereconstructed mean (6.80 °C); the latter three years, however, fall inthe period pre-1850 where sample replication is low.

The spatial correlation analysis between the multiproxy SST re-construction and HadISST1 SSTs (Fig. 8) identifies that the multiproxySST reconstruction significantly correlates (P b 0.01) with areas acrossthe North Atlantic coherent with the trajectory of the GS/NAC. Thesedata indicate that the multiproxy SST reconstruction is sensitive tolarge scale variability in the N Atlantic system and that given adequatespatial replication of combined Glycymeris glycymeris/sedimentary ar-chive proxy series it may be possible to reconstruct the dynamics ofthe GS/NAC system over past centuries.

These data demonstrate thatGlycymeris glycymeris growth incrementchronologies are highly sensitive to SST variability and can provide a ro-bust source of mid and high frequency palaeoclimatic information. Bycombining the G. glycymeris chronologies with low frequency climateproxies that are similarly sensitive to SSTs it is possible to reconstructpalaeoceanographic variability over the late Holocene. These recordscould be invaluable for the calibration of future climate models as theyprovide a unique source of annually resolved palaeoclimate information

nes respectively) with corresponding MSE (blue and grey lines respectively). The solidf the references to color in this figure legend, the reader is referred to the web version of



Fig. 8. A) Spatial correlation analysis between the multiproxy SST reconstruction and Spring HadISST1 gridded SSTs, calculated over the period 1870–2010, and B) the associatedprobabilities.


for regions of temperate coastal marine environment that have hithertobeen void of high-resolution archives.

Acknowledgements

This work was supported both financially and technically by theEU Millennium Integrated Project (European Climate of the LastMillennium; Project no. 017008), Climate Change Consortium of Wales(C3W), NERC-funded ULTRA project (Project Number NE/H023356/1),NERC Facility for Scientific Diving (award # NFSD/09/01), Dr. PaulineGulliver of the Natural Environment Research Council (NERC) Radiocar-bon Facility (NRCF) (Allocation No. 1419.1009), and the Quaternary Re-search Association (QRA) New Research Workers Award. Officers


and crew of the RV Prince Madog (School of Ocean Sciences, BangorUniversity) as well as the NERC Facility for Scientific Diving teamare thanked for their assistance in collecting the Glycymerisglycymeris material from NW Scotland. We thank Ian Harris ofUEA for the use of SHELCORR. We acknowledge the two anony-mous reviewers for their useful comments in the preparation ofthis manuscript.

Appendix A. Supplementary data

Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.palaeo.2013.05.029.






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a multiproxy reconstruction of hebridean (nw scotland) spring sea

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