Reconstruction of sea-surface temperatures from assemblages of planktonic foraminifera: multi-technique approach based on geographically constrained calibration data sets and its application to glacial Atlantic and Pacific Oceans
Introduction
All biological processes, from the growth of individual organisms to the dynamics of large ecological systems, are affected by the physical and chemical state of their environment. If we knew how the environment modifies the basic genetic design of organisms and how it controls their spatial and temporal distribution, we could use the fossil record of such organisms to reconstruct the state and variation of past environments. Whilst most fossils record and preserve environmentally valuable and extractible information, planktonic foraminifera are by far the most important signal carriers in palaeoceanography. The physical and chemical properties of foraminiferal shells provide a multitude of palaeoproxies, including passively recorded chemical and isotopic signals, signatures of environmentally modulated metabolic processes, and ecologically controlled aspects of taxonomic abundances and shell morphology (Henderson, 2002). Physical and chemical properties of foraminiferal shells follow different taphonomic pathways and proxies based on these properties rely on different sets of assumptions. This makes it possible to derive independent estimates of palaeoceanographic parameters from the same fossil assemblage, thus providing a unique opportunity to assess the robustness of such palaeoenvironmental reconstructions.
In an ideal world, one would wish to have a full mechanistic understanding of how a proxy works. Unfortunately, in most cases we lack the detailed knowledge of the chemical, physical and biological processes that operate to record and preserve an environmental signal in a proxy record. In the absence of a direct deterministic relationship we are forced to resort to the process of empirical calibration. Here, the relationship between a relatively easily measured parameter of a fossil and an environmental variable is derived by observing and describing such relationship in the present-day situation. This process is methodologically relatively simple but it involves a number of assumptions that have significant impact on the applicability and reliability of each empirically calibrated proxy (Hutson, 1977; Birks, 1995; ter Braak, 1995).
Due to the nature of the processes involved, chemical proxies are more likely to approach the desired mechanistic level of understanding, whilst proxies based on organism size, shape and abundance remain bound to the realms of empirical calibration. Despite this limitation, the possibility to complement and cross-validate the reliability of chemical proxies, especially those derived from samples with unfavourable taphonomic histories has provided the impetus to improve existing physical palaeoproxies (ter Braak and Juggins, 1993; Pflaumann et al., 1996; Waelbroeck et al., 1998; Malmgren et al., 2001) as well as development of new ones (e.g. Bollmann et al., 2002; Schmidt et al., 2004).
The most commonly used physical palaeoproxy involves mathematical analysis of census counts of microfossil assemblages: the so-called “transfer function” approach. Although this kind of species–environment calibration has a long history in the natural sciences its application to palaeoenvironmental reconstruction was brought to prominence by the CLIMAP group in their pivotal effort to reconstruct the sea-surface temperature field of the last glacial maximum ocean (CLIMAP Project Members, 1976, CLIMAP Project Members, 1981). The results of the CLIMAP reconstructions have been used extensively for forcing and validating ocean circulation models (e.g. Webb et al., 1997). These are the same models that are being used to evaluate the effects of man-made changes to our planet's surface and atmosphere. Many political decisions that are being taken today are based on such evaluations. It is therefore very important to understand properly how the validation data for these models are produced and, equally important, what is their reliability and precision.
Ever since the pioneering study by CLIMAP Project Members (1976), the Last Glacial Maximum (LGM), with its different, yet well defined, insolation and greenhouse gas forcing, has been the prime target for comparison of model outputs and proxy data. The international EPILOG initiative has been recently launched (Mix et al., 2001) with the view to revise the reconstruction of the glacial Earth surface. The MARGO effort is focused on providing a new LGM Sea-Surface Temperature (SST) reconstruction, using the enormous body of new, high-quality data produced in the last two decades. Transfer functions based on planktonic foraminifer counts have always played a central role in glacial palaeothermometry and the new calibration techniques developed in the last decade have contributed greatly to renewed interest in foraminifer SST reconstructions. In this study, we review the use of planktonic foraminifer counts for palaeotemperature reconstructions and present the rationale for a new approach based on the application of multiple techniques calibrated on geographically constrained calibration data sets. We then use this approach to develop a new LGM SST reconstruction for the Atlantic and Pacific Oceans and compare our results with previous studies and other palaeothermometers.
Section snippets
Principles of ecological calibration
The process of ecological calibration as applied to the technique of transfer functions based on assemblages of planktonic foraminifera consists of three steps: firstly, a calibration data set is assembled consisting of counts of planktonic foraminifer taxa in modern ocean and of instrumentally recorded values of environmental parameters extracted at corresponding locations. Secondly, a mathematical model is developed to characterise or describe the relationship between the environmental
Geographically constrained calibration data sets
The classical CLIMAP (1976) study employed six regionally calibrated foraminifer transfer functions. This practice has since been followed in regional studies (Niebler and Gersonde, 1998; Pflaumann and Jian, 1999; Barrows et al., 2000), and to some extent in more global calibration exercises (Ortiz and Mix, 1997; Mix et al., 1999; Trend-Staid and Prell, 2002). Our study follows the CLIMAP approach in the aspect of regionally constrained calibrations, but unlike the earlier studies, we provide a
Atlantic LGM data base
The LGM data set used here is adopted from the GLAMAP-2000 study (Niebler et al., 2003; Pflaumann et al., 2003) which greatly benefits from a stringent quality and age control and careful selection of the LGM interval. GLAMAP-2000 presented glacial SST reconstructions using two alternative LGM definitions. The first, covering the time interval from 21,500 to 18,000 yBP, is based on the concept of the last isotopic maximum (LIM) when ice-sheets reached their maximum extent (Sarnthein et al., 2003a
Reliability of LGM SST reconstructions
Fig. 20 shows how the conceptual model for assessment of reliability of SST estimates outlined in Section 2.3 (Fig. 1) applies to glacial Atlantic and Pacific SST reconstructions. The standard deviation of the 10 ANN SST estimates was <1 °C in >98% of the calibration data set samples. Since the distribution of prediction errors suggests that all data sets offer sufficient coverage of SST range and faunal variation (see Section 3.3.1, Fig. 6), we have adopted the 1 °C value as a threshold
Conclusions
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In an attempt to minimise bias associated with the presence of cryptic species of planktonic foraminifera and to provide an objective tool for assessing reliability of environmental estimates in fossil samples, we have developed the conceptual framework for a multi-technique approach of environmental calibration of planktonic foraminifer census counts in geographically constrained calibration data sets. Using calibration data sets from the Atlantic and Pacific Oceans, we demonstrate the merit
Acknowledgements
This research has been supported by grants from The Leverhulme Trust (MK, AH), Nuffield Foundation (MK), the UK Natural Environmental Research Council (MK, TK) and by the International Marine Past Global Changes Study (IMAGES) program. We thank James Casford and two anonymous referees for constructive criticism of an earlier draft of this paper.
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