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Keywords:

  • Alkenone;
  • isotope;
  • foraminifera;
  • paleotemperature;
  • carbon dioxide;
  • paleosalinity

Abstract

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Opportunities for Multiproxy Studies
  5. 3. Water Column Structure
  6. 4. Ecosystem Structure
  7. 5. Paleosalinity
  8. 6. Paleo-pCO2
  9. 7. Seafloor Processes
  10. 8. Summary and Recommendations
  11. Acknowledgments
  12. References
  13. Supporting Information

[1] We assess multiproxy strategies involving alkenone-based and other paleoceanographic indicators in an effort to define uncertainties and to advance understanding of past oceanic and climatic changes. Looking to the future, we recommend a parallel strategy of applying proxies to the geologic record while continuously seeking refinements in methods and understanding of mechanisms that control each proxy. A multiproxy strategy increases confidence in results and provides oceanographic context for more effective interpretation of processes. A combination of proxies allows derivation of additional properties, such as upper ocean paleosalinity or paleo-pCO2, for a more complete view of the oceanographic and climate mechanisms involved in changing Earth's environment.

1. Introduction

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Opportunities for Multiproxy Studies
  5. 3. Water Column Structure
  6. 4. Ecosystem Structure
  7. 5. Paleosalinity
  8. 6. Paleo-pCO2
  9. 7. Seafloor Processes
  10. 8. Summary and Recommendations
  11. Acknowledgments
  12. References
  13. Supporting Information

[2] Measures of concentration, relative abundance, and other properties of alkenones, specific long-chain organic molecules produced in the ocean by haptophyte algae (such as certain species of Coccolithophoridae), offer great potential as proxy indices of climate change in marine sediments. Paleoceanographers rely on proxy data, which in the geologic record substitute for the kind of instrumental measures made in today's world. No proxies are perfect. All have analytical uncertainties, and all have biases associated with real-world recording processes. Although an ideal proxy would be dependable and predictable based on primary control by laws of thermodynamics, this situation is rarely realized because most paleoceanographic proxy data are at least partly controlled by poorly understood biological processes.

[3] Biological processes in the water or sediment column create some biases associated with the ecological or physiological responses of the organisms with which a proxy is associated. Such factors underscore the value of multiple measurements. Because secondary influences on proxies such as the biological or postdepositional effects are likely to differ, multiproxy studies can help to identify the primary signals of interest. Here we review the status of such multiproxy studies in the context of alkenone-based measurements. Our assessment of future research strategies stems from discussion at the National Science Foundation sponsored workshop Alkenone-Based Paleoceanographic Indicators, hosted by Woods Hole Oceanographic Institution and the U.S. National Academy of Sciences in October 1999.

[4] We begin with the conviction that all of the proxies discussed here are useful. Where they agree, they confirm and increase confidence in results. Where they disagree, they lead us to assess the reasons for their differences, yielding new insights into underlying processes. Consistent with our focus on alkenone-based proxies, we ask the question, “How can other proxies, combined with alkenone indices, help to constrain the interpretation of paleoceanographic and paleoclimatic processes?” We seek to identify key research opportunities that exploit multiple proxies to gain confidence in results with complementary data or in combination to derive important properties that cannot be reconstructed with a single proxy measure.

[5] Following early studies that identified the promise of alkenones as paleoceanographic proxies [e.g., Volkman et al., 1980a, 1980b; Marlowe et al., 1984; Brassell et al., 1986a, 1986b; Prahl and Wakeham, 1987] measurements made in modern (core top) sediments have supported the concept of using the U37k′ index, (e.g., [C37:2]/([C37:2]+[C37:3]), as a reasonable measure of mean annual sea surface temperature (SST) [Herbert et al., 1998; Müller et al., 1998]. No significant diagenetic effects on the U37k′ index have been detected [Prahl et al., 1989; Madureira et al., 1995; Teece et al., 1998]. Patterns of temperature change based on the index appear to behave in systematic ways through the last few hundred thousand years [Schneider et al., 1996, 1999; Bard et al., 1997]. The alkenones thus provide powerful tools for estimating past changes in ocean temperatures on a global scale, except for regions in which alkenone productivity and contents in sediments are very low, such as the centers of subtropical gyres, and areas in which temperatures may exceed the limits of temperature calibration, such as the polar oceans or tropical warm pools.

[6] As with all geologic proxies, care must be taken to evaluate potential biases and errors on a case-by-case basis. Second-order problems regarding the use of alkenone-based measurements as indices of sea surface properties include the following:

[7] 1. Observations of peak alkenone production ta subsurface depths suggest that alkenone indices may not record sea surface conditions [Prahl et al., 1993; Okouchi et al., 1999].

[8] 2. Observations of seasonal blooms in alkenone production suggest that alkenone indices may not record annual-average conditions [Prahl et al., 1993].

[9] 3. The finding of different relationships of U37k′ to temperature in different species or strains of haptophyte algae in laboratory cultures leads to uncertainties in the choice of temperature calibrations applied to the geological record in some areas [Conte et al., 1998].

[10] 4. Kinetic effects of cellular growth, obsreved to affect both the calibration of the U37k′ index relative to temperature and δ13C values within the alkenone fraction, suggest that these measures may be subject to ecological biases [Bidigare et al., 1997; Epstein et al., 1998].

[11] 5. Owing to erosion and redeposition at the seafloor, fine-grained particles (likely carriers of alkenones in the geological record) may in some areas such as sediment drifts be contaminated with material that is older or from another geographic area [Laine and Hollister, 1981; Keigwin and Jones, 1989].

[12] 6. Bioturbation in the sediment column, which appears to be strongest for fine particles that carry alkenones [Wheatcroft, 1992] may distrupt the stratigraphic record of alkenone indices relative to other proxy data carried on larger sedimentary particles.

[13] Alkenone-based proxies are not the only ones subject to the sorts of challenges noted above. Essentially all paleoceanographic proxy data are affected by these or analogous problems or biases. Paleoceanographers often live with these problems, limiting their choice of study materials and interpretations to the parts of the record that are robust. They constantly strive to reduce or mitigate such problems by improving analytical methods or by developing complementary data sets to confirm or reject inferences based on a single proxy. Over the years this mode of operation has yielded dramatic improvements in proxies and deep insights into the operation of a constantly changing Earth system.

2. Opportunities for Multiproxy Studies

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Opportunities for Multiproxy Studies
  5. 3. Water Column Structure
  6. 4. Ecosystem Structure
  7. 5. Paleosalinity
  8. 6. Paleo-pCO2
  9. 7. Seafloor Processes
  10. 8. Summary and Recommendations
  11. Acknowledgments
  12. References
  13. Supporting Information

[14] In the following sections we outline opportunities for multiproxy studies that combine alkenone-based indices with other proxies in a way that provides unique information. This can be viewed in two ways. First, application of two or more proxies thought to record similar aspects of the environment (SST, for instance) enhances confidence in a result. Analysis of differences in results offers the potential of richer, more complete insights into each proxy by helping to identify specific conditions associated with preferred habitats. Second, analysis of a combination of proxies that examine different aspects of the environment provides an oceanographic context, which can help to reveal biases or overprints on the primary signal. Other strategies for combining proxies allow derivation of new indices, such as paleo-pCO2 or paleosalinity. The discussion begins by addressing opportunities to mitigate or capitalize on some of the challenges discussed above. This is not a comprehensive review. Our intent is to provide key examples to illustrate a general strategy of using multiple proxies to gain richer understanding of the environment.

3. Water Column Structure

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Opportunities for Multiproxy Studies
  5. 3. Water Column Structure
  6. 4. Ecosystem Structure
  7. 5. Paleosalinity
  8. 6. Paleo-pCO2
  9. 7. Seafloor Processes
  10. 8. Summary and Recommendations
  11. Acknowledgments
  12. References
  13. Supporting Information

[15] Tests or calibrations of paleoceanographic proxies often compare measures from modern (core top) sediments to historical atlas data or from sediment traps to coeval water column data. The strength of core top tests is the broad geographic range of available test sites. However, high-quality cores that preserve the sediment-water interface and have sufficiently high accumulation rates to verify (based on 14C dating) the presence of modern sediments remain limited. Sediment trap materials are guaranteed to represent the modern sediment rain within a given year but offer less geographic coverage, sometimes lack suitable water column data, and are unlikely to represent long-term average conditions at a site. Nevertheless, both strategies are useful.

[16] When observed at large spatial scales, alkenone measurements in modern (core top) sediments support the concept of using the U37k′ index as a reasonable measure of SST [Herbert et al., 1998; Müller et al., 1998]. In some regions, however, detailed analysis of core tops suggests that geologic records of U37k′ may be biased due to seasonal and/or subsurface alkenone production [e.g., Okouchi et al., 1999]. Water column and sediment trap samples provide evidence for production of alkenones in association with subsurface chlorophyll maxima, which are often observed within the pycnocline or thermocline [Prahl et al., 1993]. For example, off Oregon, U37k′ growth temperatures were 5°–8°C lower than SST values during a summer-dominated bloom in September 1998 (Figure 1). Confirming this pattern, temperatures recorded by U37k′ in core top sediments here are similar to sea surface temperatures in the winter [Prahl et al., 1995; Doose et al., 1997]. Little biological production occurs here in winter, but these findings are consistent with a well-known regional pattern of phytoplankton growth 40–80 m below the sea surface in summer, associated with a deep chlorophyll maximum [Prahl et al., 1993]. In the northeast Pacific this biological feature is often found near the top of the so-called Shallow Salinity Minimum water, which forms near the North Pacific Subpolar Front in winter [Kenyon, 1978; Talley, 1985].

image

Figure 1. (top) Water column temperature and salinity profiles in a conductivity-temperature-depth transect along 42°N off southern Oregon in September 1989 [Ortiz et al., 1995]. Labeled points note the apparent depths recorded by U37k′ temperatures [Prahl et al., 1993] in sediment trap samples collected in September, 1988. G is the “gyre” site (9.3°C), M is the “midway” site (11.3°C), and N is the “nearshore” site (10.4°C). U37k′ temperatures suggest subsurface formation of alkenones, consistent with the location of deep chlorophyll maxima along a density surface of 25.0–25.2 σt. Solid triangles denote locations of depth-stratified plankton tow samples. (bottom) Abundance of living (protoplasm full) shells of the planktonic foraminifer Neogloboquadrina dutertrei, captured in plankton tows along 42°N (distances offshore noted) in September 1989 [Ortiz et al., 1995], records subsurface habitats offshore that are broadly similar to those recorded by the alkenones.

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[17] Among planktonic organisms that carry paleoceanographic information, subsurface growth is not unique to alkenones. In a transect similar to that studied by Prahl et al. [1993], some species of foraminifera were found living in roughly the same depths and seasons as the alkenone producers [Ortiz and Mix, 1992; Ortiz et al., 1995]. For example, living (protoplasm full) shells of the planktonic foraminifer Neogloboquadrina dutertrei, captured in plankton tows off Oregon in September 1989, were most abundant in subsurface habitats offshore (Figure 1). Subsurface maxima such as these reflect this species need for both food (most abundant in a subsurface maximum) and light (for algal symbionts, most abundant at the sea surface). The broad similarity of depths occupied by the phytoplankton and zooplankton offers hope that multiproxy comparison of tracers in these different organisms is possible.

[18] Information from other proxies can place U37k′ temperature estimates into the context of vertical and seasonal gradients of temperature within the euphotic zone and may open opportunities to estimate important water column properties such as thermocline temperature. For example, planktonic foraminifera and radiolarians, the zooplankton groups most commonly preserved in the geologic record, include many different species with distinct depth and seasonal preferences [Deuser et al., 1981; Fairbanks et al., 1982; Sautter and Thunell, 1989; Ortiz and Mix, 1992; Welling and Pisias, 1998]. Distribution of species in the water column and their seasonal succession clearly depend on water column structure and food supply in addition to SST [Mix, 1989a; Ravelo and Fairbanks, 1992; deVernal et al., 1993; Ortiz et al., 1995, 1996; Kohfeld et al., 1996; Watkins et al., 1996, 1998; Pisias et al., 1997; Ravelo and Andreasen, 1999].

[19] Statistical methods for estimating water column properties from an array of species assemblages build on the pioneering work of Imbrie and Kipp [1971]. The strength of such whole-fauna methods lies in their ability to predict large-scale patterns of ocean properties, using statistical relationships to “see through” local biases such as the depth habitat of individual species. In theory, statistical transfer functions that estimate mean annual SST do not require the fauna or flora to live at the sea surface, in all seasons, or even to be controlled mechanistically by temperature. The method does require that whatever properties actually control species distributions are linearly related to SST. If this relationship varies through time, then estimates may be biased. In spite of nearly 30 years of continuous study, new statistical methods continue to be developed [Hutson, 1979; Prell, 1985; Pflaumann et al., 1996; Ortiz and Mix, 1997; Malmgren and Nordlund, 1997; Waelbroeck et al., 1998; Mix et al., 1999]. Analysis of transfer functions based on multiple fossil groups provides a useful check on the results from any individual proxy [Molfino et al., 1982; Pisias and Mix, 1997].

[20] Identification of fossil species assemblages and geochemical measurements on several species of foraminifera are commonly used to provide information regarding water mass properties (such as temperature) at the sea surface, seasonal ranges in temperature, biological productivity, and pycnocline depth or structure [Imbrie and Kipp, 1971; Mix, 1989a, 1989b; Abrantes, 1992; Watkins et al., 1996, 1998; Andreasen and Ravelo, 1997; Mulitza et al., 1997; Pisias and Mix, 1997; Cayre et al., 1999a; Wolff et al., 1999]. Theory suggests that prediction of multiple environmental properties is possible from rich, multispecies data sets [Imbrie and Kipp, 1971] but does not offer definitive guidance about which environmental properties are most important. Debate continues regarding the potential for biases in estimates and the difficulty in uniquely assigning variations in the fauna to any particular environmental property, in part because many environmental properties covary in the modern ocean [Watkins and Mix, 1998]. Nevertheless, most paleoceanographers accept that species assemblages can yield useful quantitative or semiquantitative indices of upper ocean temperature, as well as estimates of either biological productivity (as reflected in food supply) or pycnocline structure (noting that these two variables tend to be correlated in the modern ocean). In addition, stable isotope and trace metal/calcium ratio measurements made on different species of planktonic foraminifera (such as those known to tolerate oligotrophic conditions and others limited to food-rich conditions associated with nutrient-replete subsurface waters) can be used to detect changes in the position of nutricline relative to the thermocline and water column stratification [Fairbanks et al., 1982; Ravelo and Fairbanks, 1992; Farrell et al., 1995].

[21] Faunal or isotopic estimates related to pycnocline depth or structure would add value to alkenone-based temperature estimates by placing the U37k′ index into an appropriate oceanographic context [Chapman et al., 1996]. Consider the effects of thermocline depth on the U37k′ record of temperature (Figure 2). Here we use water column data for annual-average distributions of temperature, nitrate, and chlorophyll (World Ocean Atlas -98, [Ocean Climate Laboratory, 1999]) to model such effects. We assume, for purposes of this sensitivity test, that alkenones are produced in the water column proportional to observed chlorophyll concentrations. We calculate the temperature expected to be recorded by alkenones as the chlorophyll-weighted average temperature in the water column. This exercise is intended as a sensitivity test. Although chlorophyll is a reasonably good qualitative measure of phytoplankton concentration and production at low latitudes, subsurface chlorophyll maxima are not always associated with highest total production [Cullen, 1982], and it is unclear how chlorophyll data relate to total alkenone production in many settings.

image

Figure 2. Water column profiles of annual-average temperature T, nitrate N, and chlorophyll C (open symbols [from Ocean Climate Laboratory, 1999]); are used to explore hypothetical influences of thermocline depth on temperatures recorded by alkenone proxies. This exercise is intended as a sensitivity test. Atlas chlorophyll data are limited to 100-m depth, and we assume exponential decrease at greater depths. Here we assume that alkenones are produced in the water column proportional to observed chlorophyll distributions, and calculate the chlorophyll-weighted average temperature in the water column (solid symbols). (a–c) T, N, and C at two sites with a deep pycnocline, with warm SST (squares, 10°S, 135°W), and cool SST (diamonds, 28°N, 137°W). Here chlorophyll-weighted temperatures (solid symbols, shown at chlorophyll-weighted depths) approximately record the SST contrast of 7°C between sites, but slightly underestimate absolute SST due to subsurface production. (d–f) T, N, and C at two sites with a shallow thermocline, one with warm SST (squares, 9°N, 91°W), and one with cool SST (diamonds, 3°S, 82°W). Here chlorophyll-weighted temperatures (solid symbols) underestimate the SST contrast of 5°C between sites as well as the absolute SST values due to subsurface production. (g–i) T, N, and C at two sites with similar SST but contrast in thermocline depth, one deep (squares, 10°S, 135°W), and one shallow (diamonds, 9°N, 91°W). Here chlorophyll-weighted temperatures (solid symbols) would predict unrealistic SST contrast of 5°C between sites, but if the primary control by pycnocline depth was recognized based on other proxies, the recorded temperatures would provide a useful confirmation of changes in the pycnocline.

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[22] In our sensitivity tests, at sites in which the thermocline is always deeper than the euphotic zone (Figure 2a2c) the chlorophyll-weighted temperatures approximate the contrast in SST between sites (or by inference, through time at a site). Absolute temperature estimates are slightly colder than surface values because such sites generally have a deep chlorophyll maximum associated with a deep nutricline. In such oceanographic settings the U37k′ index would complement species-based estimates of paleotemperatures and agreement would yield confidence in the result.

[23] At sites with a shallow thermocline (Figure 2d2f), the chlorophyll-weighted temperatures significantly underestimate both absolute SSTs and the SST difference between the sites (or by inference, through time at a site). The U37k′ index could, however, yield insight into temperatures within the thermocline. This context would present an exciting opportunity to understand the properties of water masses that ventilate the pycnocline and act as source waters in upwelling systems, for example, in comparison to studies of paleoproductivity.

[24] In a test case comparing sites with different thermocline depths and similar SSTs (Figure 2g2i) the chlorophyll-weighted temperatures misrepresent the lack of SST contrast between sites. If a site changed through time between these two conditions, alkenones would likely provide insight into the sense of pycnocline change (apparent cooling would imply pycnocline shoaling). This application could be used to confirm estimates based on other proxies such as the comparison of shallow-dwelling and deep-dwelling species of foraminifera.

[25] In each of the hypothetical cases noted above, the use of alkenone measurements in concert with other proxies would add value and convert a potential problem of interpretation into an opportunity for rich insight into oceanographic processes responsible for changes in the observations.

4. Ecosystem Structure

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Opportunities for Multiproxy Studies
  5. 3. Water Column Structure
  6. 4. Ecosystem Structure
  7. 5. Paleosalinity
  8. 6. Paleo-pCO2
  9. 7. Seafloor Processes
  10. 8. Summary and Recommendations
  11. Acknowledgments
  12. References
  13. Supporting Information

[26] Laboratory cultures show that different species or strains of alkenone-producing algae yield significantly different relationships between U37k′ and temperature [Conte et al., 1998]. Although evidence for some of the culture-based temperature relationships is rare in sediment core tops, it remains possible that ecosystem changes in the past would favor one strain or another. Such changes, if undetected, could lead to biases in the geologic record of temperature change.

[27] Attempts to assess changes in the dominance of alkenone producers based on the preserved record of coccolith species abundances [Müller et al., 1997; Weaver et al., 1999] so far suggest no significant biases in U37k′ temperature estimates related to species dominance changes. Such tests have only been made in a few locations, however, and should be extended. Species abundance data from other fossil groups such as foraminifera, radiolarians, diatoms, and others may also add value as a record of the structure of ecosystems or water column processes that influence the dominant strain of algae that produce alkenones. As a preliminary step, we see value in investigating relationships of residuals in U37k′ temperature estimates (i.e., the difference between inferred temperatures and atlas values) with species distributions (based on raw species data in all fossil groups in addition to derived properties such as transfer-function temperature estimates) in the same core top sediment samples.

[28] This strategy for assessing ecosystem composition can also be applied to multimolecular proxies, i.e., those based on the abundances of a range of organic compounds analyzed in the same samples. Alkenone distributions (e.g., unsaturation in n-C37, C38, and C39) and those of other biosynthetically related compounds (e.g., alkenonates, alkenes) probably vary among the present-day species (and strains) that synthesize them. Several hundred biomarkers are now known to occur virtually ubiquitously in marine sediments [Brassell, 1993]. Some are rather specific in their origin, as are the alkenones (e.g., dinosterol comes from dinoflagellates), while others are of rather general biological origin (e.g., cholesterol is present in a broad range of zooplankton and other animal groups). Some biomarkers are clearly of terrigenous origin (e.g., long straight chain lipids such as n-C29 and n-C31 alkanes and n-C28 and n-C30 alkanols, from land plants). Relative or absolute abundances and fluxes of biomarkers such as these can provide valuable indications of the inputs of the various groups of organisms through time (molecular stratigraphy) or space (molecular mapping). However, relationships between biomarker production and sediment input remain poorly calibrated for many organic compounds.

[29] Opportunities exist to collect major sets of biomarker data as part of the alkenone analyses with comparatively little additional effort. The requirements are that the analytical steps, which can be largely automated, be restricted to extraction, simple fractionation, derivatization, identification, and quantification by gas chromatography mass spectrometry (GCMS) or other methods. A conservative estimate of the resolving power of this approach is that 50–100 biomarkers could be quantified in semiautomatic fashion, with little additional cost relative to the measurement of just a few compounds (Table 1).

Table 1. Classes of Biomarkers and Numbers of Compounds as Candidates of Multimolecular Proxies
Biomarker ClassCompounds
C37−39 alkenones, related alkenoates, and alkenes∼15
Sterols (e. g., dinosterol, cholesterol)∼20
Long chain n-alkanes, alkanols, and alkanoics (methyl esters), diols, and ketols∼40
Phytol, diplopterol, and other triterpenoids (e. g., amyrins, hopenes)∼10

[30] Multimolecular procedures of this type are routinely employed in large numbers of analyses for pollutants, as in Environmental Protection Agency (EPA) studies. Extensive data sets on molecular abundance may be manipulated statistically in conjunction with other types of proxy data in attempts to relate ecosystem components (species and strains of alga or other organisms) with covarying biomarker distributions. Such chemometric strategies [e.g., Brassell et al., 1986a] mirror those used for multivariate statistical analyses and transfer function calculations based on other fossil groups [e.g., Imbrie and Webb, 1981; Imbrie et al., 1989]. Challenges will arise as these strategies are developed, in part because some organic compounds are much more vulnerable to diagenetic alteration than are others. Nevertheless, examination of a variety of compounds with different diagenetic properties may yield insights into these secondary processes, in a way that will benefit primary environmental reconstructions.

[31] Looking farther into the future, we see great promise in rapidly improving methods of genetic sequence analysis, which may eventually be able to detect the genetic makeup of the organisms that produce alkenones or other organic compounds. Suitable methods that would be applicable to sedimentary materials do not exist at present, but development may be possible. If such a strategy could identify unambiguously the relative abundance of the various strains of haptophyte algae responsible for making the biomarker molecules preserved in deep-sea sediments, it would be relatively straightforward to choose the proper temperature calibration scheme for a paleotemperature estimate.

5. Paleosalinity

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Opportunities for Multiproxy Studies
  5. 3. Water Column Structure
  6. 4. Ecosystem Structure
  7. 5. Paleosalinity
  8. 6. Paleo-pCO2
  9. 7. Seafloor Processes
  10. 8. Summary and Recommendations
  11. Acknowledgments
  12. References
  13. Supporting Information

[32] For many years, paleoceanographers have sought viable proxies of regional salinity variations in the ocean. The combination of salinity and temperature estimates would enable calculation of water densities, important in the high latitudes for discerning sources of intermediate- and deep-water ventilation. In the low latitudes, salinity estimates also help to constrain the balance between precipitation and evaporation and to infer freshwater transports between ocean basins. Near coastlines, paleosalinity estimates would help record the history of river fluxes associated with climate changes on land. The importance of having a proxy for paleosalinity cannot be overstated. In models, even small changes in the flux of fresh water to the ocean in the high latitudes, or the transport of water vapor between ocean basins in the low latitudes, have dramatic effects on global thermohaline circulation and global climate [Rahmstorf, 1995]. Even a semiquantitative salinity proxy would be valuable.

[33] Presently, there is no direct geologic proxy for paleosalinity. Estimates are derived from multiple proxies, for example, by combining measurements of δ18O in the calcite shells of planktonic organisms such as foraminifera with independent estimates of paleotemperature [Imbrie et al., 1973; Broecker, 1989; Duplessy et al., 1993; Rostek et al., 1993; Wang et al., 1995; Cayre et al., 1999b] after correction for the imprint of changing ice volume on global oceanic δ18O budgets [Labeyrie et al., 1987; Mix, 1987; Shackleton, 1987]. For example, comparison of U37k′ temperature estimates with foraminiferal δ18O data led Rostek et al. [1993] to propose large changes in Indian Ocean salinity related to monsoon strength (Figure 3). In practice, rigorous estimation of paleosalinity has proven quite difficult, as propagation of errors from each part of the proxy adds uncertainties to the result [Schmidt, 1999a, 1999b]. Comparison of multiple independent proxies for salinity would provide important crosschecks on results.

image

Figure 3. The combination of U37k′ temperature estimates and foraminiferal δ18O data estimate changes in paleosalinity in Indian Ocean core MD900963, 5°04′N, 73°53′E [Rostek et al., 1993]. (a) U37k′ SST estimates, based on the calibration of Prahl and Wakeham [1987]. (b) The δ18O values of the surface-dwelling foraminifera Globigerinoides ruber. (c) Smoothed δ18O of G. ruber (solid line), compared to an estimate of global oceanic δ18O history associated with changing ice volume (dashed line, following Labeyrie et al. [1987]). (d) Estimates of surface-water paleosalinity at the site of MD900963 based on temperature and ice-volume corrections to the δ18O of G. ruber, and a modern salinity of 35 PSU. Upper and lower lines reflect the range of slopes in the relationship of δ18O and salinity observed in surface waters of the modern Indian Ocean [Rostek et al., 1993].

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[34] Two primary challenges have so far limited the application of isotopic salinity estimates: uncertainties in the constancy of the relationship between salinity and the oxygen isotopic composition of water, and the precision of temperature estimates applicable to foraminiferal shells [Rohling and Bigg, 1998]. Progress is being made on the first challenge in modeling studies that include both water and isotopic transports in the atmosphere and ocean [Juillet-Leclerc et al., 1997; Schmidt, 1998; Jouzel et al., 2000; Delaygue et al., 2000]. Multiproxy estimates of temperature may improve estimates of paleosalinity by narrowing the range of uncertainty for temperature corrections. U37k′ indices will play a role in this effort. Other new methods will also help. For example, estimates of calcification temperature based on proxies such as Mg/Ca within the same shells as the isotope measurements now appear promising [Nürnberg et al., 1996; Hastings et al., 1998; Lea et al., 1999, 2000; Mashiotta et al., 1999; Rosenthal et al., 2000a; Elderfield and Ganssen, 2000].

[35] Similar strategies to derive paleosalinity estimates from temperature estimates and oxygen isotope data may come from the combination of the U37k′ index and δ18O in the coccolith fraction in deep-sea sediments. Isotopic disequilibrium effects in coccoliths from oceanic sediments remain poorly known, however, because the small size of coccoliths makes it nearly impossible to isolate species [Dudley and Goodney, 1979]. New technologies for analyses of isotopes and trace metals of small particles by laser ablation may overcome such difficulties in the future.

[36] Preliminary data on the distribution of the alkenone n-C37:4 suggest an intriguing correlation to sea surface salinity [Rosell-Melé, 1998]. The cause of this relationship remains unknown, but one option is a biological effect based on differences in the saturation index of n-C37 alkenones of species that survive in conditions of low salinities relative to species prevalent at higher salinities. At present, the cause of this relationship is little more than speculation, and other methods to identify the organisms creating the alkenone molecules (genetic sequencing, or additional molecular information) may be needed. Nevertheless, we see value in exploring relationships of this and other types of organic molecules to salinity and to a rich array of environmental properties in general. If the relationships to salinity involve the presence of different species or strains of alkenone producers, resolving these effects may yield further insights into interpretations of temperature from unsaturation indices.

6. Paleo-pCO2

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Opportunities for Multiproxy Studies
  5. 3. Water Column Structure
  6. 4. Ecosystem Structure
  7. 5. Paleosalinity
  8. 6. Paleo-pCO2
  9. 7. Seafloor Processes
  10. 8. Summary and Recommendations
  11. Acknowledgments
  12. References
  13. Supporting Information

[37] The carbon isotopic composition of alkenones or other organic compounds combined with those of foraminifera offer the potential to reconstruct the distribution of aqueous CO2 concentrations in the upper ocean (Figure 4). In concert with paleotemperature measurements these data can be used to estimate atmospheric pCO2 values that would be in equilibrium with surface waters. This is commonly referred to as paleo-pCO2 [Jasper and Hayes, 1990; Jasper et al., 1994]. The calculation of paleo-pCO2 from the carbon isotopic composition of alkenones depends, among others, on an accurate estimation of the temperature at the precise season and depth of the alkenone production. This is best done with alkenone proxy U37k′. Even if U37k′ records a subsurface or seasonally biased temperature estimate, it is the most appropriate temperature to use in estimating pCO2 from alkenone isotopic data because it is carried in the same molecule and thus is likely to record corresponding environmental conditions.

image

Figure 4. Multiproxy measurements of paleo-pCO2 in core W8402A-14GC from the equatorial Pacific Ocean. (a) Equatorial Pacific paleo-pCO2 estimates based on δ13C and temperature data (open squares from Jasper et al. [1994]) and similar values corrected for growth rate effects estimated from Sr/Ca (solid circles from Stoll and Schrag [2000], error bars reflect the estimated range of growth rates). Solid line without symbols is atmospheric pCO2 history as recorded in the Vostok ice core [Petit et al., 1999]. (b) ΔpCO2, the difference between equatorial Pacific paleo-pCO2 estimates and atmospheric values (open squares without growth rate corrections, solid circles with growth rate corrections and error bars as in Figure 4a). Positive values of ΔpCO2 indicate that the equatorial Pacific was a consistent source of CO2 to the atmosphere over the past ∼250 ka. (c) U37k′ temperature estimates in core W8402A-14GC [Lyle et al., 1992]. (d) Sea surface PO4 concentrations, estimated from Sr/Ca in the coccolith fraction of core W8402A-14GC, used for growth rate corrections on alkenone δ13C [Stoll and Schrag, 2000].

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[38] Metabolic processes within cells and within populations may affect alkenone indices. For example, some studies suggest potential impacts of cell growth rate on alkenones [Bidigare et al., 1997], which complicate estimation of dissolved CO2 concentrations based on δ13C [Popp et al., 1999], and perhaps also temperature estimates based on the U37k′ index [Epstein et al., 1998]. Application of additional proxies offer the potential to constrain growth rates in the geologic record and thus to correct for such effects. Empirical evidence from the water column suggests that population growth rates are related to nutrient contents of water masses [Bidigare et al., 1999]. On the basis of these relationships, molecular indices of growth rate are under development.

[39] Several geologic proxies offer the potential to constrain the environmental or ecosystem controls on growth rates of the biota. Proxies exist for upper ocean nutrient concentrations based on trace metal/calcium ratios in planktonic foraminifera [Boyle, 1981; Keigwin and Boyle, 1989], although effects of algal symbionts [Mashiotta et al., 1997] and temperature [Rickaby and Elderfield, 1999] may also influence such estimates. Nutrient utilization estimates have been based on δ15N of sedimentary organic matter [Altabet and Francois, 1994]. Primary productivity estimates are based on transfer function approaches using planktonic foraminiferal, calcareous nannofossil, diatom, or dynocyst species data [Mix, 1989a; Abrantes, 1992; Cayre et al., 1999a; Beaufort et al., 1999], benthic foraminiferal species percentages [Loubere and Fariduddin, 1999] or abundance [Herguera and Berger, 1991], or mass accumulation rates of biogenic materials or chemical tracers [Dymond et al., 1992; Lyle et al., 1992].

[40] Preliminary culture experiments suggest that Sr/Ca in calcite liths may reflect the growth rate of the coccolithophorid Emiliania huxleyi [Rosenthal et al., 2000b], perhaps owing to a kinetic effect on calcification rate. Because E. huxleyi is a known alkenone producer, Sr/Ca in this species may, in turn, reflect the growth rate of the alkenone-producing flora. A recent study of surface sediments across a latitudinal transect in the equatorial Pacific suggests that Sr/Ca of the bulk coccolith fraction, cleaned to the extent possible of contaminants associated with Fe and Mn oxyhydroxides, covaries with modern spatial patterns of primary productivity [Stoll and Schrag, 2000].

[41] Under an assumption that Sr/Ca variations in the bulk coccolith fraction track growth rates of the alkenone-producing haptophytes, Stoll and Schrag [2000] use downcore data to correct for growth rate changes on the carbon isotopic paleo-pCO2 estimates of Jasper et al. [1994], which include estimates of temperature based on the U37k′ index [Lyle et al., 1992]. These new calculations confirm the earlier inference that the equatorial Pacific was always a regional source of CO2 to the atmosphere; i.e., local paleo-pCO2 values were consistently higher than atmospheric pCO2 values in the Vostok ice core [Petit et al., 1999]. The new calculations suggest even greater CO2 outgassing from the region and a long-term drift from much higher pCO2 values in the past (especially >150 kyr BP) to lower values with the last 100 ka. Significant uncertainties in the Sr/Ca growth rate corrections include possible changes in the Sr content of seawater through time, which remains controversial [Stoll and Schrag, 1998; Martin et al., 2000]. Clearly, more work is needed to test the efficacy of these multiproxy approaches in constraining regional sources and sinks of CO2 in the paleoceanographic record. Nevertheless, we are encouraged that qualitative or semiquantitative corrections for growth rates on alkenone δ13C data and paleo-pCO2 estimates may be possible.

[42] Relatively little data exist on the chemical or isotopic composition of coccolith species in the geologic record. This reflects the difficulty of isolating the calcite plates formed by individual species of coccoliths, because of their small size. New technologies for isolating such particles or for analyzing them individually within a mixed sample may be possible, based on advances in small sample techniques such as microprobe or laser ablation inductively coupled plasma–mass spectrometer (ICP–MS). Recently developed analytical methods also offer the opportunity to measure multiple elemental ratios rapidly (e.g., Cd/Ca, Ba/Ca, Mg/Ca, and others), thereby making the multiproxy approach much easier to apply [Rosenthal et al., 1999]. With these new technologies we expect further progress on development of growth rate corrections and other isotopic proxies related to paleo-pCO2 estimates. In spite of large uncertainties in several aspects of these measurements and their interpretation, establishing regional patterns of paleo-pCO2 to assess changes in sources and sinks of atmospheric CO2 in the ocean would be of such enormous benefit that these studies are worth pursuing, recognizing that estimates will improve as knowledge of controls on the proxies is refined.

7. Seafloor Processes

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Opportunities for Multiproxy Studies
  5. 3. Water Column Structure
  6. 4. Ecosystem Structure
  7. 5. Paleosalinity
  8. 6. Paleo-pCO2
  9. 7. Seafloor Processes
  10. 8. Summary and Recommendations
  11. Acknowledgments
  12. References
  13. Supporting Information

[43] Alkenones, as hydrophobic compounds originally part of the cells of coccolithophores, should have an affinity for fine-grained sediments through adsorption on clays and silts, or absorption in organic particles. Although reasonable, this conjecture is unproven, and one of our recommendations is for studies to confirm which phases in the sediment actually carry the alkenone signal.

[44] A present focus of paleoceanographers is on rapidly accumulating sequences in sediment drifts and continental margin sediments as a means of obtaining high-resolution paleoceanographic records [Sachs and Lehman, 1999]. We worry, however, that artifacts may be introduced into alkenone-based (and other) environmental histories in such settings because fine-grained sediments in drift deposits may be transported downslope or across an ocean basin by turbidity currents or may be advected by bottom currents in deep recirculating gyres.

[45] For example, more than 30 years ago, it was recognized that fine-grained sediments rich in hematite all along the U.S. Atlantic continental margin were introduced by the St. Lawrence river system and redistributed by deep-sea contour currents [Heezen et al., 1966]. These reddish sediments (which also include pre-Pleistocene coccoliths) extend as far as Bermuda Rise, where excess fines accumulate in drifts [Laine and Hollister, 1981; McCave et al., 1982; Suman and Bacon, 1989]. Rapid changes in carbonate contents of Bermuda Rise sediments reflect changing input of fine-grained terrigenous sediments from eastern Canada [Keigwin and Jones, 1989]. Thus changes in the fine sediments at Bermuda Rise reflect variability of high-latitude climate and deep-water circulation, rather than local conditions in the subtropical gyre. If alkenones were carried along with these fine-grained sediments, an intermittent cold artifact associated with waters from the continental slope could occur that might mimic high-latitude climate changes [Sachs and Lehman, 1999]. Likewise, the presence of shallow-water microfossils in deep-water sequences from continental margins provides clear evidence of downslope transport that could carry an anomalous signal. Measures of reworked tracers appropriate to each site (such as shallow-water fossils in continental margin settings or mineralogical tracers of fine-grained sediment sources) will help to identify problems associated with sediment transport.

[46] Bioturbation induced by benthic organisms moves clay- and silt-sized particles more readily than sand-sized particles [Wheatcroft, 1992]. Thus there is a potential for bias in alkenone records relative to records based on sand-sized foraminifera. For example, in ultrahigh resolution studies the alkenone record of brief climate change events may be smoothed or even shifted in depth compared to estimates based on foraminiferal species or stable isotope records. This would not be a large problem in laminated sediments that have not been bioturbated or for low-resolution studies in which the depth spacing between samples is >10 cm. Indeed, downcore scanning based on reflectance spectroscopy suggests that significant information can be preserved at the scale of a few centimeters in spite of bioturbation effects. Barring effects of sediment transport noted above, meaningful records of climatic variability on the scale of a few centuries can be produced where sedimentation rate exceeds 10 cm ka−1 [Chapman and Shackleton, 1998].

[47] Deconvolving the effects of bioturbation on sedimentary signals is not straightforward. In part this reflects a lack of quantitative indices of bioturbation intensity through time, except in isolated cases such as where thin ash layers are present [Ruddiman and Glover, 1972]. Pisias [1983] argued based on time series analysis of geologic records that bioturbation intensity increases with sedimentation rate, implying a result that even sediments accumulating slowly would preserve a useful geologic record. Some progress in developing tracers of bioturbation intensity has come with studies that suggest a link to total food supply (i.e., biological productivity of overlying waters) [Trauth et al., 1997], which also may leave an imprint on the benthic species assemblages [Loubere, 1989].

[48] Bioturbation models typically treat only the part of mixing that can be simulated as a diffusive process [Peng et al., 1979], which occurs typically within a few centimeters of the sediment-water interface. In addition, burrows are commonly preserved below the well-mixed surface layer. The presence of burrows and other bioturbation structures may be detected by careful visual description or digital imaging of the sediments [Ortiz and Rack, 1999] or by systematic X-ray analysis of sediment cores. In many cases, such data can help investigators to avoid major artifacts associated with burrows at the time of sampling.

[49] Bioturbation is potentially damaging when materials carrying a chemical tracer are moved from intervals of high abundance into barren or nearly barren zones. This is called the “bioturbation-abundance couple” [Broecker et al., 1984]. Its effects have been explored in the context of radiocarbon dating [Bard et al., 1987; Broecker et al., 1999] and stable isotope records [Mix and Ruddiman, 1985]. Such studies require precise data on abundance (relative to total sediment) of the material carrying a paleoceanographic tracer. Even if the effects of bioturbation cannot be removed completely from measured records using mathematical models, potential problems can be identified if reliable abundance data are available. Thus we recommend that that absolute abundances of alkenones (and other proxy carriers such as microfossil shells) be reported for studies in which bioturbation may be a problem.

8. Summary and Recommendations

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Opportunities for Multiproxy Studies
  5. 3. Water Column Structure
  6. 4. Ecosystem Structure
  7. 5. Paleosalinity
  8. 6. Paleo-pCO2
  9. 7. Seafloor Processes
  10. 8. Summary and Recommendations
  11. Acknowledgments
  12. References
  13. Supporting Information

[50] Great opportunities exist for application of multiple proxies to the record of past changes in the oceans and global climate. Multiproxy strategies can help one to “see” through the biological processes that mediate most paleoceanographic records. In many cases, the exact biological mechanisms or chemical pathways controlling paleoceanographic proxies are uncertain. We suggest a strategy of application of proxies to the geologic record in parallel with continuous efforts to refine understanding of mechanisms and calibration of methods. Our experience is that this two-pronged approach leads to rapid advancement of knowledge.

[51] In the simplest case, application of multiple proxies to estimate a single environmental property, such as SST, helps gain confidence in the result by reducing errors. Differences between estimates based on multiple proxies are equally important, as they lead to deeper understanding based on the oceanographic context of each measurement. Thus we recommend analysis of residuals between estimates based on multiple proxies or between proxy estimates and actual (atlas or measured) environmental values as a path toward greater insight into the true nature of each proxy. In an example of oceanographic context we note that faunal or isotopic estimates of pycnocline depth or structure would add value to alkenone-based temperature estimates by placing the U37k′ index into an appropriate oceanographic context. Information on overall ecosystem structure based on faunal and floral species assemblages, or identification of alkenone producers via a biomarker or genetic strategy, would constrain the choice of temperature calibrations and thus improve paleotemperature estimates.

[52] A more complicated multiproxy strategy involves the use of dissimilar proxies to derive oceanic properties that cannot be assessed with any single measurement. Examples in which progress is likely are estimating paleosalinity and paleo-pCO2. Significant uncertainties are involved in both properties. Nevertheless, both are so important that continued study is warranted. For paleosalinity estimates, multiproxy temperature estimates (including faunal transfer functions, U37k′, and trace metal indices) coupled to oxygen isotope data in foraminifera are needed. We also recommend detailed study of the coccolith fraction, using emerging technologies for small-sample chemical and isotopic analysis. On the basis of preliminary relationships between alkenone n-C37:4 and salinity we believe exploration of full chromatograms for multimolecular geochemical evidence of salinity change and other environmental effects is warranted. Estimates of paleo-pCO2 call for a geologic proxy for cell or population growth rate, and we suggest further explorations of proxies for nutrients, nutrient utilization, biological productivity, and calcification rate.

[53] As a first step toward identifying biases in the sedimentary record associated with sediment transport and bioturbation, we recommend research to identify the particles that carry alkenones, as well as a practice of reporting absolute abundances of alkenones (and other particles carrying environmental signals for other proxies).

[54] Confirmation that multiproxy strategies actually work in the geologic record requires coordinated study of core top sediments. This is easier to recommend than to accomplish, as high-quality core top samples are relatively rare commodities. We thus recommend that field programs involving coring make special efforts to archive and share high-quality samples of the sediment-water interface. The best available tool for this purpose is the multicore, which is fortunately available in many institutions. Where possible, high-quality core tops should be dated using 14C and other stratigraphic methods to verify the presence of essentially modern sediments and if possible to establish sedimentation rates.

[55] Finally, we note that the level of scrutiny the alkenone community is applying to their proxies, as exemplified by the Woods Hole workshop of 1999, serves as a model for other communities. One of our recommendations is for workers on other data types to join together in a similar fashion to intercalibrate, refine, and revise their proxies as needed for a richer and more complete view of ocean and climate history.

Acknowledgments

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Opportunities for Multiproxy Studies
  5. 3. Water Column Structure
  6. 4. Ecosystem Structure
  7. 5. Paleosalinity
  8. 6. Paleo-pCO2
  9. 7. Seafloor Processes
  10. 8. Summary and Recommendations
  11. Acknowledgments
  12. References
  13. Supporting Information

[56] We thank T. I. Eglinton, M. H. Conte, G. Eglinton, and J. M. Hayes, organizers of the NSF sponsored workshop Alkenone-Based Paleoceanographic Indicators. We also thank the workshop participants for spirited discussions and the U.S. National Academy of Sciences and Woods Hole Oceanographic Institution for facilitating this effort. Reviews by W. Curry, M. Feldberg, L. Labeyrie, F. Prahl, and R. Thunell improved the manuscript.

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  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Opportunities for Multiproxy Studies
  5. 3. Water Column Structure
  6. 4. Ecosystem Structure
  7. 5. Paleosalinity
  8. 6. Paleo-pCO2
  9. 7. Seafloor Processes
  10. 8. Summary and Recommendations
  11. Acknowledgments
  12. References
  13. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Opportunities for Multiproxy Studies
  5. 3. Water Column Structure
  6. 4. Ecosystem Structure
  7. 5. Paleosalinity
  8. 6. Paleo-pCO2
  9. 7. Seafloor Processes
  10. 8. Summary and Recommendations
  11. Acknowledgments
  12. References
  13. Supporting Information
FilenameFormatSizeDescription
ggge47-sup-0001-tab01.txtplain text document0KTab-delimited Table 1.

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