A review of modern coral δ18O and Δ14C proxy records

A review of modern coral δ18O and Δ14C proxy records

Earth-Science Reviews 81 (2007) 67 – 91 www.elsevier.com/locate/earscirev A review of modern coral δ 18 O and Δ 14 C proxy records Andréa G. Grottoli...

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Earth-Science Reviews 81 (2007) 67 – 91 www.elsevier.com/locate/earscirev

A review of modern coral δ 18 O and Δ 14 C proxy records Andréa G. Grottoli a,⁎, C. Mark Eakin b b

a School of Earth Sciences, 125 South Oval Mall, Ohio State University, Columbus, OH 43210, United States Coral Reef Watch, NOAA, NESDIS Center for Satellite Applications and Research, Silver Spring, MD 20910–3226, United States

Received 30 September 2005; accepted 3 October 2006 Available online 13 December 2006

Abstract This paper is a review of published modern coral δ18O and Δ14C isotopic records that are at least 30 and 20 years long, respectively. The data are presented to show basin-scale trends in both of these proxy records on decadal-to-centennial timescales. The goal was to qualitatively integrate the general inter-annual-to-centennial timescale variability revealed in these data, as well as the statistical and modeling output results that have been produced using these coral records. While many review papers typically include a representative subset of the data available, this review aims to include as much of the available data as possible. In general, coral δ18O records show a long-term warming and/or freshening throughout the tropical oceans, and agree with the NOAA Extended Reconstruction Sea Surface Temperature 2 (ERSST) on decadal timescales. In the western Pacific, it is most likely a freshening of the seawater δ18O that dominates the signal. El Niño Southern Oscillation (ENSO) variability dominates most δ18O records either by varying local seawater temperature or salinity, depending on the regional oceanography/climatology. Outside of the Pacific, ENSO affects seawater temperature and salinity via atmospheric or oceanic teleconnections. Post-bomb coral Δ14C records collectively show that the uptake of 14C has been greatest in gyrewater fed sites, followed in descending order by western boundary current areas, equatorial upwelling regions, and eastern tropical Pacific upwelling sites. These surface water Δ14C values indicate the proportion of surface water and/or the residence time of water at the surface at a given location, and can be used to model water mass mixing rates. Such models have only begun to be run and show that the amount of eastern Pacific water entering the central South Pacific increases during El Niños and that the Indonesian throughflow is supplied year-round by the North Pacific. Comparing ocean circulation models with coral Δ14C-modelled circulation enables researchers to explore the mechanisms that drive seawater Δ14C variability and fine-tune their models. In addition, our comparison between the rate of coral Δ14C increase between 1960 and 1970 and total anthropogenic CO2 uptake rates show general agreement, demonstrating the value of coral records in understanding past carbon fluxes. Overall, coral δ18O and Δ14C proxy records represent natural archives of seawater conditions and are critical for studying the natural variability in local and regional patterns within, and teleconnection patterns between, the tropics, extra-tropics, temperate, and Polar Regions on intra-annual-to-centennial timescales. © 2006 Elsevier B.V. All rights reserved. Keywords: coral; isotope; O-18; C-14; sea surface temperature; paleoceanography

1. Introduction Coral skeletons serve as excellent recorders of paleoenvironmental conditions in tropical nearshore waters ⁎ Corresponding author. Tel.: +1 614 292 5782; fax: +1 614 292 7688. E-mail address: [email protected] (A.G. Grottoli). 0012-8252/$ - see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.earscirev.2006.10.001

(see reviews by Druffel, 1997a; Gagan et al., 2000; Grottoli, 2001; Eakin and Grottoli, in press). The isotopic, trace, and minor elemental signatures of coral skeletons vary in a predictable way as a result of temperature, salinity, cloud cover, river discharge, upwelling, ocean circulation, and other oceanic features. As such, coral cores provide a natural archive of tropical paleoclimatic

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and paleoceanographic conditions on intra-annual-tocentennial timescales. This is especially valuable since multi-century instrumental climate records in the tropics are sparse to non-existent and century-long sea surface temperature (SST) reconstructions developed from historical records (Reynolds et al., 2002; Rayner et al., 2003; Smith and Reynolds, 2004) have various limitations. Massive, symbiotic stony corals are good tropical proxy recorders because: 1) they are widely distributed throughout the tropics, 2) their unperturbed annual skeletal banding pattern offers excellent chronological control, 3) they incorporate a variety of isotopic and elemental tracers used for paleoclimatic and paleoceanographic reconstruction, 4) their proxy records can be reliably interpreted, 5) their records can span several centuries, and 6) their high skeletal growth rate (usually ranging from 5 to 25 mm/year) permits sub-seasonal sampling resolution. Thus proxy records in corals provide an excellent means of obtaining long seasonal-to-centennial timescale paleoclimatic information in the tropics. The geochemical records preserved in the coral skeleton are used to reconstruct paleorecords (Table 1). Scientists commonly reconstruct sea surface temperature, salinity, winds and upwelling, cloud cover, pH,

ocean mixing, and river discharge histories from coral proxy records. In addition, living corals provide a record of intra-annual, inter-annual, inter-decadal, and centennial timescale variability often associated with seasonal variability, the El Niño Southern Oscillation system (ENSO), the Pacific Decadal Oscillation (PDO), and pre- versus post-industrial climate events, respectively. While paleoclimatic records have their limitations (see Section 5.1), they remain the most cost-effective tools that we have to develop long records of environmental variability. This paper is a review of coral stable oxygen (δ18O) and radiocarbon (Δ14C) isotopic records with emphasis on the 27 available published modern coral δ18O records that are at least 30 years long and could be normalized to the most common overlap interval of 1962–1979, and all 26 published modern Δ14C coral records that span at least 20 years. The data are presented to show basin-scale trends in both of these proxy records on decadal-to-centennial timescales, and compare these against data sets from global-scale data assimilation models. While most review papers highlight a small selection of the published coral records, this paper assesses the overall patterns observed in the coral

Table 1 Environmental variable(s) that can be reconstructed from coral skeletal isotopes, trace and minor elements, and growth records Proxy

Environmental variable

Selected references

Isotopes δ18O

Sea surface temperature, sea surface salinity

δ13C

Light (e.g., seasonal cloud cover), plankton intake

δ14C

Ocean ventilation, water mass circulation

δ11B

pH

Quinn et al., 1993; Dunbar et al., 1994; Swart et al., 1996a, 1998; Evans et al., 1999; Cole et al., 2000; LeBec et al., 2000 Cole and Fairbanks, 1990; Felis et al., 1998; Boiseau et al., 1999; Grottoli and Wellington, 1999 Druffel and Griffin, 1993; Guilderson and Schrag, 1998b; Grottoli et al., 2003; Grumet et al., 2004 Hemming and Hanson, 1992; Honisch et al., 2004

Trace and minor elements Sr/Ca Sea surface temperature U/Ca Mg/Ca Mn/Ca Cd/Ca

Sea surface temperature Sea surface temperature Wind anomalies, upwelling Upwelling, contamination

Ba/Ca Pb/Ca

Upwelling, river outflow Gasoline burning, pollution

Skeleton Skeletal growth bands

Luminescence

Light (seasonal changes), stress, water motion, sedimentation, sea surface temperature River outflow, ocean productivity

McCulloch et al., 1994; Alibert and McCulloch, 1997; Linsley et al., 2000a,b; Hendy et al., 2002 Min et al., 1995; Hendy et al., 2002 Mitsuguchi et al., 1996; Fallon et al., 1999; Wei et al., 2000 Shen et al., 1991, 1992b; Delaney et al., 1993 Shen et al., 1987, Linn et al., 1990; Shen et al., 1992a; Delaney et al., 1993; Reuer et al., 2003 Lea et al., 1989; Shen et al., 1992a; McCulloch et al., 2003 Fallon et al., 2002; Medina-Elizalde et al., 2002; Desenfant et al., 2003

Dodge and Thomson, 1974; Dodge and Vaisnys, 1975; Hudson et al., 1976; Dodge and Lang, 1983; Hudson et al., 1989; Scoffin et al., 1989; Eakin et al., 1993, 1994; Lough, 2004 Isdale, 1984; Tudhope et al., 1995, 1996; Lough et al., 2002; Nyberg, 2002

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δ18O and Δ14C data sets by including as many of those published records as possible and by discussing them in relation to other isotopic or elemental coral and sclerosponge records. 2. Methods 2.1. Collection, preparation, and chronology establishment Massive corals of the genera Porites, Pavona, and Montastraea are the most commonly targeted for paleoclimate studies because they are mounding species that form distinct annual bands, can grow for several hundred years, and are commonly found. Continuous records of past tropical climate conditions can be obtained by extracting a core from an individual massive coral head along its major axis of growth. Typically, this involves drilling a corer through the top center of the coral head to its initial point of growth. The extracted core is cut longitudinally into slabs ranging in thickness from 0.5 to 1 cm, cleaned with water, dried, and then Xrayed. X-ray positive prints reveal the banding pattern of the slab and are used: 1) as a guide for sample drilling and 2) to establish a chronology for the entire coral record when the banding pattern is clear. For geochemical analysis, carbonate powder samples are extracted along the major axis of growth by grinding the skeletal material with a dental-type drill. For highresolution climate reconstructions, skeletal material is extracted every millimeter or less down the entire length of the core. Since corals grow about 5–25 mm per year, this sampling method can yield sub-seasonal resolution. Much higher resolution sampling is possible, yielding ∼ weekly samples (e.g., Gagan et al., 1994; Swart et al., 1999), but this is not commonly performed. The drilled out coral powder is then analyzed for one or more isotopes or elements to build any one of a number of possible paleoproxy records (Table 1). In most cases, the stable carbon (δ13C) and oxygen (δ18O) values of each sample are measured. Since the δ13C and δ18O composition of corals usually have a strong seasonal component, they are often used to establish the chronology and/or to confirm or adjust the chronology established from the X-rays. 2.2. Stable isotope analyses (δ13C and δ18O) Carbonate samples are analyzed for δ18O (the per mil deviation of the ratio of 18O/16O relative to ViennaPeedee Belemnite Limestone Standard (V-PDB) and δ13C (the per mil deviation of the ratio of 13C/12C

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relative to V-PDB) by acidifying the sample in 100% ortho-phosphoric acid and measuring the resulting CO2 with a mass spectrometer. Typically, 10% of samples are run in duplicate. In addition, to evaluate the precision and accuracy of the analyses, replicate analyses of known standards are run, and the standard deviation of the mean is reported. The standard deviation is generally ≤0.1‰ for both δ13C and δ18O though better precision is regularly achieved with modern automated carbonate systems. Typically, 10% of samples are run in duplicate. In addition, to evaluate the precision and accuracy of the analyses, replicate analyses of known standards are run, and the standard deviation of the mean is reported. 2.3. Radiocarbon analyses (Δ14C) Approximately 7–10 mg of coral skeleton is acidified with 85% phosphoric acid under vacuum to produce CO2 gas. The CO2 is reduced with hydrogen gas on iron or cobalt metal catalyst to produce a graphite target which is analyzed by Accelerator Mass Spectrometry (AMS) (Vogel et al., 1987). For gas counting analyses, the CO2 is measured directly or converted to acetylene (Druffel, 1980) or benzene (Nozaki et al. 1978). In all cases, results are reported as Δ14C (the per mil deviation of 14C/12C of the sample relative to that of 95% Oxalic Acid-1 standard) (Stuiver and Polach, 1977). All Δ14C values are corrected for fractionation to a δ13C of − 25‰ and the reported uncertainty of duplicate analyses is typically ± 5–8‰ for standard precision and ± 2–3‰ for high precision measurements. 3. Coral skeletal δ18O Coral skeletal δ18O is the most commonly used proxy. Within a species and geographic location, most variability in skeletal δ18O in marine organisms results from temperature-induced fractionation and seawater δ18O (Epstein et al., 1953). As temperature increases, the precipitated coral skeletal δ18O decreases due to temperature-dependent kinetic fractionation effects (Kim and O'Neil, 1997). Based on empirical studies, a 1 °C increase in sea water temperature corresponds to an average decrease of about 0.22‰ in coral δ18O though that slope can vary significantly among species and locations (Weber and Woodhead, 1972) (see also Section 3.1 below). In addition, corals draw on seawater as their primary source of δ18O for calcification. As seawater δ18O decreases, coral skeletal δ18O decreases. In general, seawater δ18O decreases as rainfall increases and/or due to changes in the source or relative contribution

70 Stable oxygen (δ18O) coral isotope records longer than 30 years and spanning the period 1962–1979. Location of each record shown on map in Fig. 1. The location name of data sets that are archived on the World Data Center for Paleoclimatology website as of April 2005 are bolded (http://www.ncdc.noaa.gov/paleo/corals.html) Location

Country

Lat, Long

Collection depth (m)

Species

Dates

Caribbean and Atlantic Ocean Alina's Reef Florida Florida Bay Florida John Smith Bay Bermuda Principe Gulf of Guinea

24°25N, 80°10W 24°56N, 80°45W 32°N, 64°W 0°N, 5°E

10 5 13 4–6

Montastraea faveolata Solenastrea bournoni Diploria labyrinthiformis Siderastrea sp.

1751–1986 1824–1993 1960–1998 1928–1993

Red Sea and Indian Ocean Ras Umm Sidd Aqaba core 18 Aqaba core 19 Dur-Ghella I. Malindi Mahe Pirotan Island Peros Banhos Atoll Peros Banhos Atoll Ifaty La Reunion Ningaloo Reef Houtman Abrolhos Island

27°51N, 34°18E 29°26N, 34°58E 29°26N, 34°58E 15°43N, 39°54E 3°S, 40°E 4°7S, 55°0E 22.6°N, 70°E 5°20S, 71°55E 5°20S, 71°55E 23°08S, 43°35E 21°S, 55°E 21°54S, 113°58E 28°28S, 113°46E

5 4 4 5 6 7 1 3 2 0 12 3 5

Porites Porites Porites Porites – Porites lutea Favia speciosa Porites solida Porites lobata Porites lobata Porites Porites lutea Porites lutea

22°20N, 110°39E 9°33N, 112°54E 19°20N, 110°39E

5 3 5

Porites lutea Porites lutea Porites lutea

Egypt Jordan Jordan Eritrea Kenya Seychelles India Chagos Archipelago Chagos Archipelago Madagascar La Reunion Australia Australia

Indonesian throughflow and South China Sea Hainan Island China Nansha Islands China Longwan China

# years

# samples/year

Reference

235 169 38 65

5–20 3–12 ∼15 ∼3

Swart et al., 1996a Swart et al., 1996b, 1999 Cohen et al., 2004 Swart et al., 1998

1750–1995 1788–1992 1788–1992 1931–1993 1801–1994 1846–1995 1948–1989 1962–1996 1962–1996 1660–1995 1832–1995 1878–1994 1794–1994

245 204 204 63 193 149 42 34 34 335 163 116 200

6 1 1 5–7 1 12 2–8 7–8 7–8 6 5–7 6 6

Felis et al., 2000 Heiss, 1994 Heiss, 1994 Klein et al., 1997 Cole et al., 2000 Charles et al., 1997 Chakraborty and Ramesh, 1998 Pfeiffer et al., 2004a Pfeiffer et al., 2004a Zinke et al,. 2004 Pfeiffer et al., 2004b Kuhnert et al., 2000 Kuhnert et al., 1999

1943–1998 1950–1999 1944–1997

55 49 53

12 20 1

He et al., 2002 Yu et al., 2001 Peng et al., 2003

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Table 2

Indonesia Indonesia

8°S, 115°E 2.8°N, 123°E

3–5m 3–5m

Porites Porites

1783–1990 1863–1990

207 127

12 12

Charles et al., 2003 Charles et al., 2003

Pacific Ocean Madang Lagoon (1) Madang Lagoon (2)

Papua New Guinea Papua New Guinea

5°13S, 145°49E 5°13S, 145°49E

3 3

Porites Porites

1880–1993 1922–1991

113 69

6 4

Tudhope et al., 2001 Tudhope et al., 1995

Pacific Ocean Laing Island Nauru Island Central Great Barrier Reef Maiana Tarawa Atoll Espirito Santo Island Espirito Santo Island Savusavu Bay Amédée Lighthouse

Papua New Guinea Nauru Australia Gilbert Islands Gilbert Islands Vanuatu Vanuatu Fiji New Caledonia

4°9S, 144°53E 0°5S, 166°E 18°50S, 146°40E 1°00N, 173°00E 1°N, 172°E 15S, 167E 15°7S, 167°2E 16°49S, 179°14E 22°29S, 166°28E

3 14 – 6 7 <1 2 2 3

Porites Porites Porites – Porites Platygyra lamellina Porites lutea Diploastrea Porites lutea

1884–1993 1897–1995 1565–1985 1840–1995 1894–1990 1806–1979 1927–1992 1940–2001 1657–1992

109 98 1370 155 96 173 65 61 335

9 4–11 0 6 16 1 12 7–13 4

Moorea Lagoon Palmyra Island Kiritimati Island Rarotonga Clipperton Atoll Punta Pitt, Galapagos Urvina Bay, Galapagos Secas Island

French Polynesia Republic of Kiribati Republic of Kiribati Cook Islands France Ecuador Ecuador Panamà

17°30S, 149°50W 5°52N, 162°8W 2°00N, 157°3W 21°5S, 159°49W 10°18N, 109°13W 0°40S, 89°10W 00°25S, 91°14W 7°59N, 82°3W

– 10 9 18 8 14 Uplift and 1.5 3

Porites lutea – Porites Porites lutea Porites lobata Pavona clavus Pavona clavus & Pavona gigantea Porites lobata

1852–1990 1886–1998 1938–1993 1726–1997 1893–1994 1936–1982 1607–1981 1707–1984

138 112 55 529 101 46 374 277

12 12 12 12 12 4 1 7–12

Tudhope et al., 2001 Guilderson and Schrag, 1999 Hendy et al., 2002 a Urban et al., 2000 Cole et al., 1993 b Quinn et al., 1993, 1996b Kilbourne et al., 2004 Bagnato et al., 2004 Crowley et al., 1997; Quinn et al., 1998; Quinn and Sampson, 2002 Boiseau et al., 1998, 1999 Cobb et al., 2001 Evans et al., 1998 Ren et al., 2002 Linsley et al., 1999, 2000a Lea et al., 1989; Shen et al., 1992a Dunbar et al., 1994 Wellington and Dunbar, 1995; Linsley et al., 1999

a b

Average of 8 cores, data not plotted in Fig. 3 because reported normalized data not normalized to the same period as the plotted data. Long record not available on website.

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Bali Bunaken

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Fig. 1. Locations of all published modern δ18O coral records listed in Table 2. Black circles ( ) denote records archived at the World Data Center for Paleoclimatology website (http://www.ncdc.noaa.gov/paleo/corals.html), and grey symbols ( ) denote records not archived on WDCP website at the time of publication.

of water masses to an area (i.e., different water masses have different δ18O composition). Rainwater in the tropics is isotopically depleted in δ18O relative to seawater because the greater convection of moisture reduces the 18O relative to 16O in cloud-borne moisture. During periods of significant precipitation, large amounts of rain can decrease the salinity and seawater δ18O in the surface ocean. Thus, increases in rainfall results in both a decrease in seawater δ18O and sea surface salinity (SSS). In the surface ocean of the tropical Pacific, seawater δ18O generally decreases by 0.27‰ for each 1.0 p.s.u. decrease in salinity (Fairbanks et al., 1997). However, the exact relationship between seawater δ18O and salinity varies with latitude, depth, and ocean basin. Thus, coral skeletal δ18O is influenced by both seawater δ18O (which is correlated with SSS) and SST. In regions where salinity is relatively constant year-round, coral δ18O records are primarily recording SST variability. However, in some locations SSS is highly variable and dominates the δ18O signal. In yet other cases, both SST and SSS vary significantly and the interpretation of the coral δ18O can be difficult (see more detailed discussion in Sections 3.1 and 3.2). Thus, the interpretation of the skeletal δ18O record depends on a combination of the hydrologic, physical circulation patterns, and the temperature regime of the collection site. 3.1. δ18O variability The slope and intercept of the SST versus coral skeletal δ18O can vary significantly between species, locations, and depth (e.g., Weber and Woodhead, 1972; Weil et al., 1981; Carriquiry et al., 1994; Wellington et al., 1996; Linsley et al., 1999; Cardinal et al., 2001). In eastern Pacific mounding corals, decreases in coral δ18O can range from

0.16 to 0.53‰/°C both within a species (between coral individuals) and between species (Wellington and Dunbar, 1995; Wellington et al., 1996; Linsley et al., 1999). For example for Porites lobata, δ18O decreases by 0.19‰/°C in the Gulf of Panama (Wellington and Dunbar, 1995), 0.22‰/°C in the Galapagos (Wellington et al., 1996) and Costa Rica (Carriquiry et al., 1994) and averaged 0.23‰/°C at Clipperton Atoll (Linsley et al., 1999). The variation in the intercept between species, also refereed to as the species-specific offset, can be as large as 1‰ even if the slopes are very similar (Wellington et al., 1996; Linsley et al., 1999). In some locations, sea surface salinity (SSS) also contributes significantly to the coral δ18O (Linsley et al., 1994; Tudhope et al., 1995; Quinn et al., 1996a; Hendy et al., 2002; Morimoto et al., 2002) and may even be the dominant factor in some cases (Cole et al., 1993; Urban et al., 2000). Other physiological factors that can influence coral δ18O are skeletal extension rate (e.g., Land et al., 1975; McConnaughey, 1989; Leder et al., 1991; deVilliers et al., 1995; Cardinal et al., 2001; Felis et al., 2003; Rodrigues and Grottoli, 2006), light intensity (Reynaud-Vaganay et al., 2001), and feeding rate (Reynaud et al., 2002). However, light and growth rate do not always have a significant effect on coral δ18O. In healthy Panamanian Pavona clavus and Pavona gigantea corals, δ18O did not differ between species or depths even though linear skeletal extension significantly decreased with depth and differed between species (Grottoli and Wellington, 1999), and feeding rates increased with depth and differed between species (Palardy et al., 2005). It would appear that only when growth rates are very low, such as those observed during bleaching events or in corals growing under low light conditions (i.e., at deep depths, in shadowed environments, or on the sides of colonies) does growth significantly affect skeletal δ18O values (e.g.,

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Fig. 2. (a) Annual δ18O anomalies versus time for all Red Sea and Indian Ocean coral records available on the WDCP website at the time of publication from Table 2. All records were normalized to the 1962–1979 period and annual values are centered on January of each year. (b) 10-year running mean of the annual δ18O anomalies from (a) centered on the fifth year, versus time. Red S. = Red Sea, W. Aust. = Western Australia.

McConnaughey, 1989; Muscatine et al. 1989). In healthy, fast-growing corals, growth appears to have a negligible effect on coral skeletal δ18O values. 3.2. Patterns in δ18O records Coupling the variation in SST–δ18O relationship with the added effect of SSS and possible physiological effects, interpreting δ18O would appear cumbersome. However, despite the nuances of skeletal δ18O isotopes, coral δ18O records have been successfully used as SST and/or SSS recorders in a large number of studies. In total, there are over 40 coral δ18O records longer than 30 years for all tropical oceans combined (Table 2, Fig. 1), and researchers have contributed most of these data sets to the World Data Center for Paleoclimatology in Boulder, Colorado (http:// www.ncdc.noaa.gov/paleo/corals.html). Individually, each of these records contributes knowledge of a particular

region. For example, in the Galapagos, > 80% of the variability in coral δ18O is due to SST, providing a reliable recorder of paleotemperature for the region (Dunbar et al., 1994). However in Fiji, variability δ18O on annual timescales is only driven weakly by SST (LeBec et al., 2000). On inter-annual timescales, 71% of the variability in Fijian coral δ18O is due to SSS and tracks changes in rainfall associated with ENSO-driven migration of the South Pacific Convergence Zone in that region (LeBec et al., 2000). In other cases, such as the Gulf of Panama, increases in SSS are often accompanied by increases in SST (particularly during El Niño years) resulting in opposing effects on the coral δ18O signal and making it very difficult to interpret (Wellington and Dunbar, 1995). The ratio of strontium to calcium (Sr/Ca) is insensitive to salinity changes (Weber, 1973; Beck et al., 1992). By interpreting (Sr/Ca) and δ18O values together, changes in SST and SSS are sometimes decoupled. The δ18O residual,

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Fig. 3. (a) Annual δ18O anomalies versus time for all Pacific Ocean coral records available on the World Data Center for Paleoclimatology website at the time of publication from Table 2. All records were normalized to the 1962–1979 period and annual values are centered on January of each year. (b) 10-year running mean (yrm) of the annual δ18O anomalies from (a) centered on the fifth year, versus time. PNG = Papua New Guinea, Galap = Galapagos.

calculated by subtracting the coral Sr/Ca-derived SST component from coral δ18O signal, has been shown to be a good recorder of paleo-SSS (McCulloch et al., 1994; Gagan et al., 1998; Swart et al., 1999; Ren et al., 2002; Kilbourne et al., 2004; Linsley et al., 2004). Thus, accurate interpretation of a coral δ18O record from a given site depends on a strong calibration of δ18O in the top portion of the coral record with existing in situ SST, SSS, and/or satellite derived SST data (Wellington et al., 1996; Iijima et al., 2005). For this paper, we examined all 32 δ18O coral records available from the World Data Center for paleoclimatology (WDC-Paleo) that were 30 years or longer and that spanned a common normalization period of 1962– 1979. Annual δ18O records were prepared for comparison both among coral paleorecords and against

globally-gridded records (see Section 3.3). For 13 of the records, the original data had been measured as annual values. For the remaining 19 δ18O records that had been measured at sub-annual resolution all data points within each calendar year were averaged to produce a single annual value. All 32 records were then normalized to the most common overlapping period between the records of 1962–1979. This optimized the strength of the comparison between data sets (i.e., all annual values and all normalized to the same time interval). Examination of these 32 δ18O coral records revealed several dominant trends (Figs. 2 and 3). In the Red Sea and Indian Ocean (excluding Madagascar), annual δ18O values show an overall warming/freshening trend equivalent to ∼ 0.68 °C (0.15‰ decrease) from 1860

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Fig. 4. Map of sea surface temperature (SST) change in degrees Celsius per decade for the period 1962–1979 from the NOAA Extended Reconstruction Sea Surface Temperature (ERSST) by Smith and Reynolds (2004). Overlain are symbols depicting the change in SST in degrees Celsius per decade based on the slope of the annual coral δ18O-derived SST for 1962–1969 for all applicable records. Slopes and statistical details are listed in Table 3. Dashed lines represent every 30° latitude and longitude. Smith and Reynolds ERSST data are available from the NOAA-CIRES Climate Diagnostics Center (http://www.cdc.noaa.gov/cdc/data.noaa.oisst.v2.html).

to 1990 (Fig. 2a, references listed in Table 2). Such a warming is consistent with instrumental and model observations for the tropical ocean over the same time period (Folland and Karl, 2001; Smith and Reynolds, 2004, Levitus et al., 2005). At La Reunion, the change was the most dramatic (0.82‰ decrease), indicating a ∼ 3.5 °C warming or a combination of significant warming and freshening. Madagascar showed no secular change in δ18O over time. Other patterns emerge on decadal-to-inter-decadal timescales (Fig. 2b, references in Table 2). Prior to 1905, Madagascar was relatively warmer/fresher than all of the other sites. Kenya also shows relatively warmer/fresher periods from ∼ 1850 to 1905, and from 1975 to 1995. The decreases in δ18O in Kenya could be due to a dampening of the upwelling in the Red Sea resulting in warmer less dense water at the surface that is then transported meridionally along the African coast (see Δ14C records for details on water mass transport in this region). However if this were true, then we would expect that the Jordan, Eritrea, and perhaps the Seychelles records would also show a decrease in δ18O at the same time: but they do not. Although the Kenya and Seychelles records are statistically coherent on decadal timescales (Cole et al., 2000), they are not coherent on longer

timescales. Thus, the large inter-decadal δ18O patterns observed at Madagascar and Kenya we hypothesize are likely to be due to variation in local oceanographic conditions. Overall, there appears to be no coherence in decadal variability in these records as suggested by Bradley et al. (2003). In addition, the two Red Sea cores do not agree on annual or decadal timescales but their overall trend is similar (Heiss, 1994). This contrasts with paired δ18O records in the Pacific (see below). In the Pacific, annual coral δ18O records reveal an overall warming trend of ∼0.79 °C (0.17‰ decrease) from 1860 to 1990 (Fig. 3a, references in Table 2). This is a bit higher than instrumental and model data for the tropical oceans (Folland and Karl, 2001) and suggests that at least some of the decrease in coral δ18O is probably due to seawater freshening. At Nauru, the warming and/or freshening was very dramatic over the last century (1.1‰ decrease) indicating a warming of up to ∼5 °C, a decrease in salinity of ∼4.0 ppt, or a combination of the two. In particular, from 1900 to 1925 conditions are dramatically cooler/more saline at Nauru relative to other records, and then in the 1940s both Galapagos records show dramatic positive δ18O anomalies (Fig. 3a,b, references in Table 2). On decadal-to-inter-decadal timescales other patterns emerge (Fig. 3a,b, references in Table 2). From ∼1860

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Table 3 Slope, intercept, r2, and p-value of the best fit line of annual δ18O between 1962 and 1979. Calibration values of δ18O per degree Celsius are derived either from the original publication of each isotope record, or from the most relevant calibration for the coral species and location in question. The SST change per decade was calculated assuming that all coral δ18O variability was SST driven Location Atlantic Ocean Alina's Reef, Florida FloridaBay Gulf of Guinea Indian Ocean and Red Sea Ras Umm Sidd, Egypt Aqada core 18, Jordan Aqada core 19, Jordan Dur-Ghella, Eritrea Malindi, Kenya Mahe, Seyshelles Peros Banhos Atoll, Chagos Archipelago Ifaty, Madagascar La Reunion Ningaloo, W. Australia Houtman Abrolhos, W.Australia Pacific Ocean Madang Lagoon 1, Papua New Guinea Madang Lagoon 2, Papua New Guinea Laing, Papua New Guinea Nauru Island, Nauru Maiana, Gilbert Islands Espirito Santo Island, Vanuatu Susuva Bay 1, Fiji Susuva Bay 2, Fiji Amédée Lighthouse, New Caledonia Moorea Lagoon, French Plynesia Palmyra Island, Republic of Kiribati Kiritimati Island, Republic of Kiribati Clipperton Atoll, France Punta Pitt, Galapagos Urvina Bay, Galapagos Secas Island, Panamà

Best fit slope (δ18O‰/yr)

Intercept

r2

0.02354 − 0.01985 0.04278

−47.038 39.105 −84.290

0.138 0.146 0.612

− 0.00052 0.00854 0.00243 0.00593 − 0.01634 − 0.00419 − 0.00532

1.028 −16.817 − 4.779 − 11.679 32.203 80.265 10.475

0.00881 0.00022 0.00686 − 0.00338

p-value

Calibration (δ18O‰/°C)

SST (°C)/decade

Reference for calibration values

0.129 0.118 0.000

0.236 0.220 0.220

− 0.9975 0.9023 − 1.9445

Leder et al., (1996) Epstein et al., 1953 a Epstein et al., 1953 a

0.002 0.138 0.012 0.135 0.748 0.139 0.173

0.863 0.130 0.660 0.134 <0.0001 0.128 0.086

0.164 0.164 0.164 0.164 0.240 0.240 0.200

0.0317 − 0.5204 − 0.1479 − 0.3614 0.6809 0.1748 0.2658

Felis et al., 2000 Felis et al., 2000 Felis et al., 2000 Felis et al., 2000 Cole et al., 2000 Cole et al., 2000 Pfeiffer et al., 2004a,b

−17.361 − 0.437 −13.457 6.655

0.309 0.000 0.160 0.030

0.017 0.935 0.100 0.491

0.190 0.200 0.180 0.180

− 0.4635 − 0.0111 − 0.3812 0.1876

Zinke et al., 2004 Pfeiffer et al., 2004a,b Kuhnert et al., 2000 Kuhnert et al., 2000

− 0.00302

5.949

0.019

0.585

0.210

0.1439

Tudhope et al., 2001

0.00185

− 3.648

0.008

0.730

0.210

− 0.0880

Tudhope et al., 2001

− 0.01302 − 0.00831 − 0.01781 0.00464 − 0.00354 − 0.01350 − 0.00516

25.651 16.369 35.109 − 9.151 6.963 26.608 10.159

0.281 0.076 0.223 0.032 0.025 0.251 0.107

0.239 0.268 0.048 0.478 0.532 0.034 0.186

0.210 0.180 0.180 0.224 0.155 0.155 0.465

0.6200 0.4616 0.9897 − 0.2073 0.2282 0.8711 0.1109

Tudhope et al., 2001 Gagan et al., 1994 Gagan et al., 1994 Quinn et al., 1993 Bagnato et al., 2004 Bagnato et al., 2004 Quinn et al., 1993

− 0.00478

9.415

0.080

0.256

0.230

0.2077

0.00251

− 4.936

0.009

0.706

0.230

− 0.1091

Cobb et al., 2001

− 0.00323

6.381

0.012

0.663

0.180

0.1797

Evans et al., 1999

− 0.00343 − 0.00943 0.00359 0.00165

6.748 18.590 − 7.073 − 3.246

0.042 0.129 0.018 0.003

0.415 0.143 0.622 0.833

0.230 0.180 0.226 0.195

0.1490 0.5238 − 0.1588 − 0.0847

Boiseau et al., 1998

Linsley et al., 1999 Wellington and Dunbar, 1995 Wellington and Dunbar, 1995 Wellington and Dunbar, 1995

a Note that species-specific calibrations have not been published for the species used in the Florida Bay and Gulf of Guinea records. Thus, the general default value of 0.22‰ / °C was used.

to 1940 Vanuatu is warmer/fresher than all other records. This is largely consistent with findings from the Great Barrier Reef where analyses of coral Sr/Ca and δ18O records (data not shown in Fig. 3) indicate that the southwestern tropical Pacific experienced a dramatic freshening post-1870 (Hendy et al., 2002). In addition, all of the Pacific coral records except Fiji show secular warming/freshening. Most of the western and central

Pacific δ 18 O records also show a dramatic warming/ freshening after 1970 (i.e., Maiana, Moorea, Nauru, Palmyra, Kiritimati). Although there is agreement between records within a site (i.e., the two Fiji cores and the three Papua New Guinea core records agree on decadal–inter-decadal timescales), there appears to be strong spatial variability at inter-decadal timescales in these records.

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3.3. Comparison of coral- and globally-gridded SST The coral-based and globally-gridded decadal rates of SST change are compared in Fig. 4. For each available coral record shown in Figs. 2 and 3, a slope was calculated from the best fit line of annual δ18O between 1962 and 1979. Then, the decadal rate of SST change was calculated assuming that all coral δ18O variability was SST driven. Coral δ18O data were converted into SST values using the species-specific and locationspecific calibration equations whenever available. The results of each regression and decadal rate of SST change are listed in Table 3 and references for each data source are given in Table 2. For the globally-gridded data, annual averages were generated for the period 1962–1979 from the monthly ERSSTs at 2×2° spatial resolution. The decadal rate of SST change was then calculated for the same time period from the NOAA Extended reconstructed sea surface temperature version 2 (ERSST) by Smith and Reynolds (2004) (http:// lwf.ncdc.noaa.gov/oa/climate/research/sst/sst.html). Though δ18O is also influenced by SSS, the comparison enabled us to directly assess how well strictly coral δ18O-derived SST records track the ERSST over large geographical areas on decadal timescales. In general, there was a good agreement between the coral δ18O and ERSST variability on decadal timescales (Fig. 4). Warming in the ERSST in the eastern and western tropical Pacific, and in the central and western Indian Ocean was recorded in the coral δ18O records. However, ∼ 50% of the coral records tended to overestimate SST increases. These may indicate a combination of warming and freshening in these regions. One dramatic exception is in Madagascar where the corals recorded a 0.6 °C cooling in an area where the ERSST data show a ∼ 0.3 °C warming. Cooling trends in the central Pacific, eastern Indian, and Red Sea are only observed in 55% of the coral δ18O records in those regions. However, several of these records (Abrolhos, Moorea, and Clipperton) are proximate to the zero-degree ERSST change contour lines, suggesting that the globally-gridded fields may slightly underrepresent the spatial extent of the warming regions. In the Atlantic, both the Florida Bay and Gulf of Guinea corals show cooling trends that are larger than those detected by the ERSST data, and may be driven by the high evaporation losses (and consequent decreases in seawater δ18O) experienced at both these sites. The second Florida core is from Alina's reef in the Florida Keys, which is exposed to both Atlantic Ocean and Florida Bay waters that flush through this site. It is not surprising that the very specific local scale effects that

77

influence this site are not captured by the larger-scale climatology of the ERSST. Also of interest is the lack of agreement between any of the replicate cores during this time interval (Jordan, Madang, and Vanuatu). The two Jordan cores both show cooling trends but their rates differ by almost 0.3 °C per decade, despite both Porites cores coming from the same coral head. The Vanuatu cores both show warming but their rates differ by 0.45 °C per decade. Since the cores came from different genera of corals, the difference may in part be due to fundamental differences in the biomineralization process within each genus. In Papua New Guinea, the three records do not agree at all. This is in contrast to Stephans et al. (2004) and Guilderson and Schrag (1999) who found close agreement between adjacent New Caledonian and Nauru Porites cores, respectively. Overall, though coral δ18O records usually track the general decadal trends in the gridded SSTs, the differences between the data sets may have multiple origins. Firstly, the influence of salinity on coral δ18O is significant throughout the tropical oceans often causing overestimations of SST rise. Secondly, replicate cores do not always agree suggesting that only the average of several cores from a given location can yield a reliable proxy record with a good signal-to-noise ratio. Thirdly, optimal comparisons between coral records from different geographic locations are best achieved when all corals are of the same species and depth. Fourthly, both the paleodata and the globally-gridded SST data are measured with error. While the ERSST data are among the best global reconstructions of SST that exist, they are based on statistical relationships among observations that were taken irregularly in space and time. The resultant globalscale data are strongly coherent at large scales, however, local SST variability at many reef sites may be underrepresented due to a lack of actual observations in many nearshore areas. Finally, some differences can be expected because of differences in the spatial and temporal resolution and sampling patterns of the data. While this does not take away from the power of coral δ18O-derived SST records, it does suggest that caution should be exercised when extrapolating a single coral isotope records to represent basin-scale SST reconstructions. 3.4. Large-scale climate processes and teleconnections Coral δ18O records also are used to study how “connected” local climate processes are to broader basin or global-scale climate processes. In a large number of century-long or longer coral δ18O records throughout the global tropics, corals record 3–7-year frequency patterns associated with ENSO variability (e.g., Cole et al.,

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Table 4 All coral radiocarbon (Δ14C) records longer than 20 years. Location of each record shown in Fig. 5 map. The location name of data sets that are archived on the World Data Center for Paleoclimatology website as of April 2005 are bolded (http://www.ncdc.noaa.gov/paleo/corals.html). ⁎ = multiple cores used to construct one record Location

Country

Collection depth Species (m)

Dates

Caribbean and Atlantic Ocean The Rocks Florida USA 24°57N, 80°33W

4

Montastraea annularis

1900–1952

Belize

15N, 85W





1872–1977 105

32°25N, 64°43W 32°N, 64W

11

Diploria strigosa and 1950–1983 33 D. labyrinthiformis Diploria 1976–1770 206 labyrinthiformis Musdsismilia 1950–1982 32 braziliensis

Belize

Sam's Hall & Bermuda North Rocks North Rock Bermuda Abrolhos Bank

Brazil

Red Sea and Indian Ocean Djibouti Red Sea Watamatu Reef

Kenya

Lat, Long

5

1

⁎Druffel and Linick, 1978; Druffel, 1982; Druffel and Suess, 1983; Druffel, 1989 Druffel, 1980; Druffel and Suess, 1983 Druffel, 1989, 1997b

3–15

Nozaki et al., 1978

1

Druffel, 1996

1

<1

3–4

12°N, 42°E





1951–1985

34

1

3°32S, 39°52E

5

Porites lutea

1947–1998

51

6

Cember, 1989; Toggweiler et al., 1991 Grumet et al., 2002

Porites

1944–1992

48

12

Grumet et al., 2004

Platygyra

1977–1998

21

1

Shen et al., 2004



Porites lutea

1940–1980

40

1

Konishi et al., 1981



Porites lutea

1912–1979

67

1

Konishi et al., 1981

8

Porites lobata

1787–2000 213

12

Asami et al., 2005

10–12

Porites autraliensis

1849–1983 134

1

10–12

Porites autraliensis

1635–1991 356

1–2

≤ 10 m

Porites

1957–1978

21

1

⁎Druffel and Griffin, 1995, 1999 ⁎Druffel and Griffin, 1993, 1995, 1999 Druffel, 1987





1958–1979

21

1–2





1890–1979

89

1

18

Porites lutea

1950–1997

47

8–11





1925–1978

53

<1

10°S, 161°E –

Porites

1944–1994

50

2

⁎Toggweiler, 1983; Toggweiler et al., 1991 Schmidt et al., 2004

9°S, 160°E

14

Porites autraliensis

1942–1995

53

3–9

Guilderson et al., 2004

3°54N, 159°19W

11

Porites

1922–1956

34

9

Grottoli et al., 2003

Pacific Ocean Sesoko, Japan Okinawa Naha, Okinawa Japan

26°38N, 127°52E 26°14N, 127°41E Guam USA 13°35N, 144°50E Heron Island Australia 23°S, 152°E Abraham Reef Australia 22°06S, 153°00E French Frigate Line Islands 23°43N, Shoals 166°06W Oahu Hawaii 21°N, (USA) 158°W Kona Hawaii 21°18N, (USA) 158°07W Rarotonga Cook 21°14S, Islands 159°49W Fiji Fiji 18°S, 179°E Solomon Islands Tambea Solomon Islands Fanning Island Republic of Kiribati

52

17°30S, 39°20W

Indonesian throughflow and South China Sea Sumatra Indonesia 0°08S, 6 98°31E – DayaBay South China 22°33N, Sea 114°32E

Marau Sound

# # Reference years samples/ year

Toggweiler, 1983; Druffel, 1987 ⁎Druffel, 1987; Druffel et al., 2001 Guilderson et al., 2000

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Table 4 (continued ) Location

Country

Fanning Island Republic of Kiribati Nauru Island Nauru

Lat, Long

Collection depth Species (m)

Dates

≤10 m

Porites

1949–1979

30

2

Druffel, 1985, 1987

14

Porites

1947–1995

48

12



1950–1980

30

1

3–4 m

Gardineroseris planulata Pavona clavus

Guilderson and Schrag, 1998a Druffel, 1987

1930–1977

47

1

1

Porites lobata

1956–1983

27

6–11

Uva Island

Panamà

Galapagos Islands

Ecuador

3°52N, 159°23W 0°5S, 166°E 7°48N, 81°45W 0.5S, 90W

Urvina Bay, Galapagos

Ecuador

0.5S, 90W

1993; Dunbar et al., 1994; Wellington and Dunbar, 1995; Charles et al., 1997; Boiseau et al., 1998; Urban et al., 2000; Rimbu et al., 2003; Pfeiffer et al., 2004b) and/or 10–30-year inter-decadal timescale patterns often associated with the Pacific Decadal Oscillation (PDO) or Interdecadal Pacific Oscillation (IPO) (e.g., Boiseau et al., 1999; Linsley et al., 2000b; Cobb et al., 2001; Linsley et al., 2004). Combining the SST reconstructions from many coral records and several locations to model basin- and global-scale climate variability has proven to be quite informative. Such modeling efforts have revealed that ENSO has been a dominant frequency pattern throughout the tropical Pacific and that there is a uniform warming trend in the mean state of the Pacific over the past two centuries (Evans et al., 2002). In addition, some records show that the frequency of ENSO warm phases has increased over the past several decades coinciding with the more dramatic mean state SST warming (Cole et al., 1993; Evans et al., 2002), while others find no such evidence despite unprecedented warming/freshening since the 1970s (Urban et al., 2000). Statistical analyses of central equatorial Pacific corals and an Indian Ocean coral show that the central tropical Pacific is highly coherent with the equatorial Atlantic and Indian oceans on ENSO and/or decadal timescales (Evans et al., 1999; Kuhnert et al., 1999; Cole et al., 2000; Cobb et al., 2001; Charles et al., 2003). However, the strength of the coherence between the central Pacific and Indian Ocean appears to have varied over the past 300 years (Pfeiffer et al., 2004b; Zinke et al., 2004), perhaps due to inter-decadal timescale variations in the South Equatorial Current transport in response to changes in surface wind fields and/or the Indonesian throughflow (Pfeiffer et al., 2004b). Other coral records have been successfully used to study the teleconnections between regional and global

# # Reference years samples/ year

⁎Druffel, 1981; Druffel and Suess, 1983; Druffel, 1985, 1987 Guilderson and Schrag, 1998b

climate processes, and between regional and continental climate processes. In the Gulf of Chiriqui, Panama, the coral δ18O reconstruction of local rainfall variability is associated with the meridional movement of the Intertropical Convergence Zone (Linsley et al., 1994). Coral records from the central and eastern tropical Pacific have been shown to have strong coherence with temperature in the northwestern and southeastern US, respectively, demonstrating the strong climatic links between the Pacific and North America (Evans et al., 1998). Comparisons between a central Pacific coral record of ENSO variability with tree-ring reconstructions of U.S. drought have demonstrated connections between long and persistent U.S. droughts with tropical Pacific ENSO forcing and variability in the strength of the connection on inter-decadal timescales (Cole and Cook, 1998). Sr/Ca and δ18O records from Rarotonga and Fiji indicate that the spatial pattern of the interdecadal variability in the South Pacific has varied over the past 300 years with major reorganization in circulation patterns occurring after ∼ 1880 (Linsley et al., 2004). A record of wintertime coral δ18O values in the Red Sea has been shown to be linked to the Arctic Oscillation, a dominant mode of atmospheric variability in the Northern hemisphere, and thus could provide a record of winter circulation variability during the preinstrumental period (Rimbu et al., 2001). While Red Sea coral δ18O records do show significant coherence with ENSO (Felis et al., 2000; Rimbu et al., 2001), a shift in the correlation in the 1970s indicated that the circulation regimes that teleconnect tropical Pacific ENSO with the Middle East can vary on inter-decadal or longer timescales (Rimbu et al., 2003). Together, these studies indicate that the central tropical Pacific is a driving and unifying forcing factor in decadal climate variability throughout the tropics and some subtropical and temperate regions. Thus, coral δ18O records are critical to

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studying the natural variability in teleconnection patterns between the tropics, extra-tropics, temperate, and Polar Regions on decadal-to-centennial timescales. 4. Coral skeletal Δ14C Radiocarbon is produced naturally in the stratosphere and was also produced en masse as a result of thermonuclear weapon explosions in the atmosphere in the late 1950s and early 1960s (referred to as bomb carbon). In the surface ocean, atmospheric CO2 diffuses into the seawater and becomes part of the dissolved inorganic carbon (DIC) pool, which corals draw upon for calcification. The Δ14C composition of the DIC is then archived in the CaCO3 that forms coral skeletons. The Δ14C value of surface water DIC and coral skeletons varies as a result of three main factors: 1—the Suess Effect, 2—physical processes such as vertical mixing and advection of water masses, and 3—the input of bombproduced Δ14C. First, during the pre-bomb period, twentieth century coral Δ14C records show a declining trend termed the Suess Effect: a dilution of natural 14C primarily by the addition of 14C-free fossil fuel-derived CO2 to the atmosphere (e.g., Suess 1953; Druffel and Griffin, 1993, 1999; Druffel et al., 2001). Second, deep water is isolated from direct CO2 exchange with the atmosphere resulting in lower 14C as this radioactive isotope decays, and lower Δ14C of the seawater dissolved inorganic carbon. The more time that a water parcel spends at the ocean's surface, the greater the influx of 14 C, and the greater the Δ14C value of the seawater dissolved inorganic carbon. Seawater Δ14C can increase until it is in equilibrium with atmospheric Δ14C. Vertical mixing and/or upwelling introduce water masses with low Δ14C values to the surface resulting in an overall decrease in the surface ocean Δ14C values. Changes in

the Δ14C signature in coral records from the Galapagos, Australia, and Kenya document the strength and duration of upwelling events (e.g., Druffel and Griffin, 1993; Guilderson and Schrag, 1998b; Grumet et al., 2004). Following the introduction of large quantities of bombderived 14C to the surface ocean during the 1950s and 1960s, the difference between surface and deep ocean Δ14C values became very pronounced and vertical mixing or upwelling events became even more apparent in the coral Δ14C record (e.g., Guilderson and Schrag, 1998b; Grumet et al., 2004). In addition, the addition of bomb 14C is readily identifiable by major increases in coral and sclerosponge Δ14C carbonate records at ∼1955 (e.g., Druffel and Linick, 1978; Druffel, 1981; Fallon et al., 2003; Grottoli, 2006). This bomb-curve signature can be used to help confirm/establish coral and sclerosponge chronologies. Since corals incorporate seawater dissolved inorganic carbon into their calcium carbonate skeletons, coral Δ14C records provide excellent archives of water mass movement, upwelling, and changes in seawater circulation on inter-annual-todecadal timescales. 4.1. Δ14C records: regional and basin-scale reconstructions of ocean circulation In total, there are 26 coral Δ14C records longer than 20 years for all tropical oceans combined (Table 4, Fig. 5). Individually, each of these records contributes to our specific knowledge of their particular region. For example, in the eastern equatorial Pacific Ocean, Δ14C evidence from a Galapagos coral indicates that upwelling intensity varies on inter-annual timescales and that there was a major shift in the source of upwelling water in 1976 (Guilderson and Schrag, 1998b) coinciding with a switch from a negative to a positive Pacific Decadal



Fig. 5. Locations of all published modern radiocarbon (Δ14C) coral records listed in Table 4. Black circles ( ) denote records archived at the World Data Center for Paleoclimatology website (http://www.ncdc.noaa.gov/paleo/corals.html), and grey symbols ( ) denote records not archived on WDCP website at time of publication.

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Fig. 6. Plot of coral radiocarbon (Δ14C) records listed in Table 4 with locations shown in Fig. 4 map. In total, raw data was available for 25 of the 26 records producing 23 curves. ⁎ = records comprised of two or more coral cores. GBR = Great Barrier Reef.

Oscillation phase (Trenberth and Hurrell, 1994; Mantua et al., 1997). In the central equatorial Pacific, a Δ14C record from a Fanning coral showed that a switch in the Pacific Decadal Oscillation from a positive to a negative phase in the late 1940s also appeared to be associated with a major change in the source water upwelling in the central equatorial Pacific (Grottoli et al., 2003). At Rarotonga, seasonal variations in coral Δ 14 C of 10–15‰ indicated that vertical mixing occurred each year over the past ∼ 50 years (Guilderson et al., 2000). Collectively, the 26 coral records together contribute to our knowledge of basin-scale and globalscale circulation patterns over time. Our analysis of all 26 coral records together builds upon other such compilations that have been analyzed over the past two decades (e.g., Druffel and Suess, 1983). In particular, examination of the post-bomb period in all available records reveals several distinct trends (Fig. 6, references in Table 4). Firstly, Δ 14 C generally increases most rapidly, and attains the local maximum earliest in the gyres (i.e., Hawaii and French Frigate Shoals in the North Pacific gyre and Rarotonga in the South Pacific Gyre) and in the gyre fed western boundary

currents (Japan, Bermuda, Florida, Brazil). This is because the seawater in these locations has a long residence time at the surface and exchanges its CO2 maximally with the atmosphere resulting in high Δ14 C values. Secondly, Δ14 C increases more rapidly along western boundary currents than within eastern boundary currents (i.e., Australia versus Galapagos). In eastern boundary currents, older, deeper water upwells to the surface depressing the surface water Δ14 C values. Upwelling and/or deep water ventilation events are often seasonally timed and can result in large sub-annual and inter-annual variations in Δ14 C (i.e., Urvina Bay, Galapagos; Daya Bay, China; Djibouti, Red Sea). Thirdly, the annual amplitude in Δ14 C along the Equator (seen only in sub-annually resolved records) is highest in the eastern Pacific, intermediate in the western Pacific, and lowest in the Indian Ocean (i.e., Urvina Bay versus Nauru versus Sumatra and Kenya). This indicates that the greatest annual Δ14C amplitude is found in locations where the most deep water is upwelled or advected to the surface, such as the eastern Pacific Ocean, while the least is found in the Indian Ocean. Finally, latitudinal trends are seen in the central Pacific records. The annual amplitude is

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Table 5 Slope (rate of change of Δ14C per year) as used in Fig. 7, intercept, and r2 of the best fit line of Δ14C between 1960 and 1970 for each available coral record. This represents the time period when the slope was greatest in all records. GBR = Great Barrier Reef Location

Best fit slope (Δ14C‰/yr)

Intercept

r2

p-value

Δ14C‰/decade

Indian and W. Pacific Oceans Sesoko, Japan Naha, Japan Daya Bay, China Heron, GBR Abraham, GBR Watamatu Reef, Kenya Sumatra, Indonesia Djibuti, Red Sea

19.642 18.651 – 16.074 14.416 11.491 17.218 9.963

− 38517 − 36565 – − 31548 − 28292 − 22528 − 33801 − 19584

0.958 0.967 – 0.965 0.957 0.831 0.945 0.953

0.0038 <0.000 – <0.0001 <0.0001 <0.0001 <0.0001 <0.0001

196.42 186.51 – 160.74 144.16 114.91 172.18 99.63

Central Pacific Ocean French Frigate Shoals Oahu, Hawaii Kona, Hawaii Rarotonga, Cook Islands Fiji Marau, Solomon Islands Tambea, Solomon Islands Fanning Island, Kiribati Nauru

19.317 17.495 14.173 17.469 14.709 10.434 13.301 11.242 10.737

− 37854 − 34303 − 27771 − 34280 − 28864 − 20468 − 26127 − 22069 − 21086

0.886 0.927 0.785 0.967 0.950 0.940 0.959 0.893 0.856

0.0002 <0.0001 0.1142 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001

193.17 174.95 141.73 174.69 147.09 104.34 133.01 112.42 107.37

E. Pacific and AtlanticOceans Florida Belize Bermuda Albrolhos, Brazil Uva Island, Panamà Galapagos Urvina Bay, Galapagos

18.991 18.509 17.061 15.111 12.391 9.672 5.805

− 37232 − 36291 − 33472 − 29656 − 24327 − 19025 − 11446

0.927 0.929 0.966 0.953 0.931 0.908 0.629

<0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001

189.91 185.09 170.61 151.11 123.91 96.72 58.05

greater in equatorial sites where there is equatorial upwelling than in higher latitude sites influenced by gyre water (i.e., Nauru versus Rarotonga). 4.2. Comparison of coral Δ14C and anthropogenic CO2 inventory The rate of bomb-14C uptake per year was calculated from the best fit line of Δ14C values between 1960 and 1970 for each available coral record (Table 5). This represents the time period when the slope was greatest in all records. We compared these Δ14C slopes with the globally-gridded anthropogenic CO2 inventory in global surface waters (Fig. 7). The global oceanic anthropogenic CO2 inventory from 1800 to 1994 was calculated using seawater inorganic carbon measurements from 9618 hydrographic stations collected over 95 cruises in the 1990s (Key et al., 2004; Sabine et al., 2004). Since both coral Δ14C and surface water anthropogenic CO2 inventory are both measures of the influx of atmospheric carbon into the surface ocean, we expected them to correlate.

In general, we see agreement between the coral Δ14C and anthropogenic CO2 uptake rates, demonstrating the value of coral records in understanding past carbon fluxes (Fig. 7). However, in the subtropical Pacific coral records (north and south of 20° latitude) the Δ14C uptake rates were consistently higher than the globallygridded CO2 uptake rates. Possible reasons for their disagreement are as follows. Firstly, it is possible that these corals, unlike corals in any other part of the tropical oceans, have weaker fractionation rates, incorporate more 14C into their skeletons, and over-represent the seawater 14C concentrations. This is not likely since the subtropical Pacific corals were of the same species and depths as in many other locations. Secondly, coral records represent a very local signal with at least annually resolved data. Whereas the CO2 uptake rates are calculated on a much larger scale (1° by 1° grids) using available instrumental data that often contain large gaps that may not adequately represent the true CO2 uptake rates at a given location. If this were the source of the differences, we would expect a random distribution in the poor correlations throughout the

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Fig. 7. Map of surface water anthropogenic CO2 inventory (μmol CO2/kg seawater) (from 1800 to 1994, after Key et al., 2004; Sabine et al., 2004) overlain with symbols depicting the change in Δ14C per year based on the slopes of Δ14C from 1960 to 1970 in Fig. 6. Statistical details are listed in Table 5. Dashed lines represent every 30° latitude and longitude. Global 1 × 1° gridded anthropogenic CO2 data are available from http://cdiac.esd. ornl.gov/oceans/glodap/Glodap_home.htm.

tropics, which we do not see in the records. Thirdly, ocean–atmosphere 14C equilibration occurs on the order of 10 years (Druffel and Suess 1983), while CO2 equilibration occurs on a much shorter timescale (∼ 1 year, Broecker and Peng, 1982). In the Pacific gyres and western boundary currents where the surface ocean has the longest residence time for exchange with the atmosphere of any location in the global tropics, we would expect corals to underestimate carbon uptake rates, not overestimate them. Fourthly, coral cores are typically collected from shallow coastal environments where local seawater may have a long residence time and uptake rates may be higher than observed in the offshore measurements used in constructing the global oceanic anthropogenic CO2 inventory. Finally, the models used to calculate the CO2 uptake rates are based on a wide variety of assumptions about the physical oceanography of each region. In the subtropical Pacific, deficiencies in the physical oceanographic assumptions of the model could account for the underestimation of the anthropogenic CO2 uptake rates. These last two items are the most likely reasons for the discrepancy. It is important to point out that the globally-gridded CO2 inventory data have most of the same limitations described above for the ERSST data. These data represent the best global reconstructions of

oceanic CO2 that exist and are strongly coherent at large scales. These are based on data taken since 1990 during open-ocean cruises with no observations in nearshore waters. Finally, some differences between the two data sets can be expected because of differences in the spatial and temporal resolution and sampling patterns of the data. Despite these few sites that do not agree with the inventory data, the coral records pick up key parts of the pattern of anthropogenic CO2 uptake. These include maxima in both values in the western North Atlantic, a decrease in the areas around Bermuda and the South Atlantic, and lows in the central South Pacific, eastern Indian Ocean and eastern Pacific. Differences among closely positioned coastal coral records suggest that they are influenced by local coastal water source effects. A wider network of Δ14C data from corals and sclerosponges, with careful attention to minimizing coastal impacts, will provide us with more robust and longer estimates of carbon fluxes between the ocean and the atmosphere, and of past patterns of ocean circulation. 4.3. Modeling applications Increasingly, the integration of the data contained in multiple Δ14C records has been used to model basin-

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scale water mass movement and circulation patterns over the last century. Combining coral Δ14C data from Rarotonga, Galapagos, and the Solomon Sea, Guilderson et al. (2004) constructed a mixing model showing that the amount of eastern Pacific water entering the Solomon Sea increases during El Niño events and that the intensity of the shallow overturning cell of the tropical Pacific has decreased over the past ∼ 20 years. Coral Δ14C records from Guam and western Indonesia together showed that seawater in the Indonesian throughflow is supplied year-round from the North Pacific with only a negligible contribution from South Equatorial Current water (Moore et al., 1997). And in another study, comparison of the Δ14C records in corals from within and outside of the Cariaco basin revealed that the reservoir age of the basin waters was ∼ 312 years (Guilderson et al., 2005). Coral Δ14C records have also been used to test models. Comparisons of Pacific sea surface Δ14C model output with coral Δ14C records from Guam, Galapagos, Fanning, and Canton indicate that inter-annual variation in sea surface Δ14C is associated with changes in surface currents and/or in the proportionate contribution of source waters entrained into the surface currents (Rodgers et al., 1997, 2004). In a separate study, Rodgers et al. (2000) compared their Pacific sea surface Δ14C model output with coral Δ14C records from Fiji, Galapagos, Nauru, and the French Frigate Shoals to show where the model reproduced in situ proxy records and where it differed. Comparing these sea surface temperature models with coral paleorecords of Δ14C allows modelers to explore the changes in ocean circulation that drive seawater Δ14C variability, leading to a better overall understanding of water mass movement throughout the oceans over time. 5. Future challenges Coral paleoclimatic records provide a unique perspective on climatic variability. They are one of the few sources of data at timescales of decades and longer, and the only direct source of annually-resolved multicentury records over most of the world's tropical oceans. They can provide records of both local changes and global-scale variability. 5.1. Limitations to coral paleoclimatic records While corals have proven their worth as reliable recorders of past environmental conditions, they do have limitations. Though laboratory precision is no longer a major issue (Lough, 2004), the important

limiting factors now tend to be the frequent lack of replicate cores to develop records (Lough, 2004) and insufficient temporal resolution (Felis and Pätzold, 2003). While reproducibility between two cores can sometimes be high (Stephans et al., 2004), replicate cores can just as likely disagree (see Section 3.3) and the potentially large range in isotopic and Sr/Ca natural variability among coral heads, locations, species, and depth (see Section 3.1; deVilliers et al., 1995; Beck et al., 1997; Schrag, 1999; Grottoli 1999; Linsley et al., 2000b) makes conclusions based on single cores risky. Within and among-colony natural variability in other trace elements has not been investigated sufficiently, but is likely to be important as well. It cannot be stated too strongly: multiple colonies need to be cored to help identify local perturbations that limit the reliability of geochemical proxies as recorders of climate. Ideally, this should involve multiple records from each of multiple (at least 3) colonies (Lough, 2004). While still the most popular tool for paleothermometry, δ 18 O is now frequently supplemented or supplanted by strontium calcium records. δ18O has been a faithful recorder for the analysis of large-scale patterns of climate variability (Evans et al., 2002) (Fig. 4). However, the proximity of many corals to coastal runoff or isolated evaporative basins makes the interaction of temperature and salinity an important confounding factor. However, runoff waters may vary substantially in their strontium content (Swart pers. comm.), and strontium content may vary due to hydrodynamic (Cohen and Sohn, 2004) or biological factors (deVilliers et al., 1995). While Sr/Ca ratios are more direct recorders of paleotemperature, they are not without their own limitations and δ18O should not yet be discarded. In addition to multiple cores, the use of multiple proxies is essential to accurately reconstruct paleotemperatures from coral cores. A multiproxy approach may be especially valuable in locations where one of the proxies is particularly problematic (Quinn and Sampson, 2002). Ongoing work is pushing the envelope of temporal resolution. Information yielded from paleoclimatic data increases when records are analyzed at sub-seasonal resolution. Felis and Pätzold (2003) discussed the particular value of bimonthly resolution, which is probably the best balance between resolution and cost. Many studies are now accessing records at resolutions far beyond that, and use of laser ablation systems may allow records to reach daily resolution at a reasonable cost (Potts, pers. comm.). However, time will tell whether samples at that high a resolution actually yield greater information content. Infilling and recalcification

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within coral skeletons may mute signals or introduce non-climatic noise, limiting the value of such high resolution. 5.2. Coral paleoclimatology as part of observing systems Fig. 4 helps us to understand the spatial variability seen in ocean temperature patterns. Examination of the record provided by globally-gridded ocean temperature reconstructions, such as the ERSST data used here, show how much these patterns vary through time. Unfortunately, these data sets are based on observation networks that dramatically decline in density and accuracy in the earlier portion of the roughly 125-year record. Coral data can help with this problem by adding independent data with constant technique and error throughout the period of this record and beyond. Records such as those from Linsley et al. (2000b) demonstrated this value of coral records for particular locations and patterns. Populations of long coral records of temperature throughout ocean basins will provide a more synoptic perspective, and will be more valuable than attempting to interpret basin-scale past climatic variability from only a few records. Despite the value of coral skeletons as recorders of past climate and environmental stress, most funding and research have focused on reconstructing large-scale climate patterns. They typically have not been considered as necessary parts of monitoring programs. However, it should be recognized that these proxy records are very cost-effective tools to develop long records of environmental variability. Most importantly, they provide data retrospectively, before a monitoring program is put in place. In the U.S., the NOAA Coral Reef Watch (Strong et al., 2004; NOAA, 2005) includes a wide range of observations on coral reefs, including coral paleoclimatic data that provide “retrospective” monitoring of reefs (Eakin et al., 2006). Paleoclimatic records need to be included in monitoring programs in the future so that marine protected area management can benefit from the long records that only paleoenvironmental proxies can provide. 5.3. Coral records of past bleaching events The next frontier will be to relate high-ocean temperatures recorded in coral skeletons with an all too frequent result of thermal stress: coral bleaching. We currently have no geochemical recorder of past bleaching events. While we can identify high-ocean temperatures that we believe were sufficient to cause

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bleaching, we cannot yet identify whether the coral actually bleached. A bleaching proxy would greatly increase the information we can glean from corals relative to both their past history of bleaching, and the relationship between bleaching and natural climatic variability. Results of studies to determine if stable isotopes can be used as proxies for bleaching have been mixed. In some cases, distinct skeletal and isotopic signatures do indicate bleaching events (Leder et al., 1991; Suzuki et al., 2003; Grottoli et al., 2004). However, under severe bleaching conditions, coral growth significantly slows (Allison et al., 1996; Rodrigues and Grottoli, 2006; Burr, 2002) and the stable isotopic signal does not reliably record the event (Rodrigues and Grottoli, 2006). While this may provide clues to possible changes in coral structure, it also suggests that corals may not record the highest, most stressful temperatures if their symbiotic relationship is disrupted to the point where calcification dramatically slows or ceases. Thus, coral paleothermometers appear to lose their accuracy when thermal stress nears the bleaching point. 5.4. Coral records of past ocean circulation Coral-based measurements of Δ 14 C are useful indicators of change in water masses in the tropical surface ocean, especially where upwelling or other oceanographic circulation patterns mix source waters with different exposures to the atmosphere. Comparison between coral records and oceanographic observations has demonstrated the accuracy of coral paleorecords of water mass movement. Coral-based circulation reconstructions provide long records of circulation changes that can be useful in understanding how ocean circulations have changed in response to climatic conditions. At this point, a wide network of coral-based SST reconstructions is helping the scientific community understand long-term changes in the mean state and variability of ocean temperatures. Development of a similarly large network of coral Δ14C measurements is needed to provide long records of circulation patterns. Large networks of paleoclimatic data have been established on land using tree-ring reconstructions of temperature and precipitation patterns. Similar marine networks using corals will be even more effective as changes in oceanic conditions tend to be more gradual. Δ14C circulation indices will especially benefit studies in key areas such as the Indonesian seaway where records are shorter and less well documented than in areas such as the Gulf Stream.

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Fig. 7 provides insight into a valuable application of coral Δ14C measurements. The similarity between the coral data and the global surface water CO2 data is striking. Despite the limited number of global samples, and the assumptions used in the model to produce the global grid, it is closely matched by the independent samples of circulation provided by the corals. Combining this with potential proxies for pH (Hemming and Hanson, 1992; Honisch et al., 2004; Pelejero et al., 2005), corals may provide a powerful tool for our understanding of CO2 variability, uptake, and transport in the oceans since the start of the industrial revolution. Sadly, these increases in CO2 that coral skeletons can monitor may soon lead to declines in the ability of corals to form their skeletons (Raven et al., 2005; Kleypas et al., 2006).

in Boulder, CO. Without their participation in data sharing, this and many other publications would not be possible. We thank the NOAA/MASC Library and Lindsey Swiacki at the University of Pennsylvania for helping us find copies of publications. Thanks also to Joan Kleypas for her suggestions on and to Dwight Gledhill and Gang Liu for the production of Figs. 4 and 7, and to Ellen Druffel for her review and comments of the manuscript. AG thanks the Woodrow Wilson Foundation Early Career Fellowship grant, NSF grant #OCE-0610487, and the Andrew Mellon Foundation grant #1040644. CME thanks NOAA, including the Coral Reef Conservation Program, for supporting work that contributed to this manuscript. The manuscript contents are solely the opinions of the author(s) and do not constitute a statement of policy, decision, or position on behalf of NOAA or the U. S. Government.

5.5. The case for networks of coral paleodata Today, instrumental and satellite sources provide us with a continuously improving global-scale picture of important parameters such as ocean temperatures, salinity, and CO2 content. Local instrument arrays monitor our coastal areas. Global integrated observing systems pull these together and bring these data to our fingertips. Unfortunately, many of the questions that we need answered today require long records that do not exist. Despite their limitations, paleodata provide us with that bridge between today's observing systems and variability of the past. The data in Figs. 4 and 7, like the earlier global analysis by Evans et al. (2002), show us that coral data faithfully monitor many of these same parameters, albeit at reduced spatial and temporal resolution. What is lost in resolution on the global scale is gained in the ability to extend these records back in time well before modern observations were in place. They also provide excellent, long-term records of local variability. While extensive, the list of available coral paleoclimatic records is woefully sparse. Unfortunately, increasing ocean pCO2 and temperature threaten these invaluable recorders of the climate system. Researchers and funding agencies need to develop a concerted effort to fill in the spatial gaps in our coral paleoclimatic records so that we can better understand the variability of the climate system both during and before major anthropogenic alterations of our climate system began. Acknowledgements We thank the many authors who have contributed their data to the World Data Center for Paleoclimatology

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