A Pliocene-Pleistocene stack of 57 globally distributed benthic δ18O records
Summary (5 min read)
1. Introduction
- [2] Alley [2003] recently called for a paleoceanographic ‘‘type section’’ to which all paleoceanographic measurements could be compared, in the same way that researchers have used data gathered by the Second Greenland Ice Sheet Project (GISP2) and Greenland Ice Core Project (GRIP) in studies of the last glacial cycle.
- Here the authors present a new 5.3-Myr benthic d18O stack (the ‘‘LR04’’ stack), which they propose would make an excellent paleoceanographic type section for the Pliocene-Pleistocene. [3].
- In the following section the authors provide background infor- mation on d18O and previously published stacks.
- Section 5 describes the creation of the orbitally tuned LR04 age model, which is additionally constrained by two measures of global sedimentation rate.
- Owing to the observed similarity of most marine d18O records and the global nature of the ice volume signal, d18O measurements also serve as the primary means for placing marine climate records on a common timescale.
3. Data
- The stack presented in this paper contains benthic d18O records from 57 globally distributed sites.
- These sites are well distributed in latitude, longitude, and depth in the Atlantic and Pacific and include two sites in the Indian Ocean (Figure 1).
- Most of the d18O measurements in these records are from Uvigerina peregrina or Cibicidoides wuellerstorfi, with appropriate species offset corrections [Shackleton and Hall, 1984].
- The included records vary widely in resolution and time span.
- The aligned d18O records used in the stack are shown in Figure 2.
4.1. Graphic Correlation
- Graphic correlation is the process of aligning paleoclimate signals based on the features within those signals [Prell et al., 1986], for example, by matching corresponding PA1003 LISIECKI AND RAYMO: PLIOCENE-PLEISTOCENE BENTHIC STACK 2 of 17 PA1003 peaks.
- This allows the LSR at individual sites to vary a great deal and preserves as much coherent d18O variation as possible.
- Graphic correlation actually corrects for any potential mixing lags between sites to produce an estimate of the d18O signal as if it had been recorded with the same phase everywhere. [12].
- The authors also add white noise (s = 0.15%) to the d18O values of each alignment target before applying their graphic correlation and stacking algorithms.
- Figure 3 shows test PA1003 LISIECKI AND RAYMO: PLIOCENE-PLEISTOCENE BENTHIC STACK 3 of 17 PA1003 PA1003 LISIECKI AND RAYMO: PLIOCENE-PLEISTOCENE.
4.2. Stacking
- The alignment process for the stack’s construction is iterative.
- The LR04 stack (Figure 4) is the average of all d18O records aligned to the transitional stack.
- This final step improves alignment accuracy because the transitional stack resembles the average d18O curve more closely than any individual site does.
- For any given time interval, the PA1003 LISIECKI AND RAYMO: PLIOCENE-PLEISTOCENE BENTHIC STACK 5 of 17 PA1003 concentration of data used in the LR04 stack is at least twice as high as in any previous stack or individual d18O record spanning that interval.
- The authors do not adjust the mean or variance of the records, except to make species offset corrections.
5. Age Model
- Because the LR04 stack is constructed by graphic correlation, its stratigraphic features are essentially independent of any timescale.
- Below the authors describe the construction of an age model which takes advantage of the high signal-to-noise ratio of the stack and analysis of the sedimentation rates at 57 sites.
- Almost any age model could be applied to the LR04 stack.
- Constraining average LSR does not prevent individual sites from exhibiting highly variable sedimentation rates.
- Therefore their tuning goals are to prevent rapid fluctuations in stacked LSR and to minimize its variance.
5.1. From 0 to 135 ka
- While generally robust, their LSR tuning strategy is not effective for the most recent portion of the stack, where apparent sedimentation rates can be distorted by uncompacted sediments in the top few meters of a core [e.g., Skinner and McCave, 2003; Huybers and Wunsch, 2004].
- Fortunately, reliable age estimates are available for this portion of the benthic d18O record.
5.2. Tuning Target
- The authors tuning target is a simple nonlinear model of ice volume, y, which follows the equation dy dt ¼ 1 b Tm x yð Þ ð1Þ where the nonlinearity coefficient b is subtracted during ice growth and added during ice decay [Imbrie and Imbrie, 1980].
- The authors allow the nonlinearity b and mean time constant Both increase linearly to 0.6 and 15 kyr, respectively, by 1.5 Ma and remain at those values to the present.
- The authors assume that small ice sheets respond more quickly than the massive ones of the late Pleistocene and choose early Pliocene values of b and Tm to reflect the absence of large northern hemisphere ice sheets.
- Different values of tidal dissipation in the orbital solution can shift the age model by 5 kyr at 5 Ma [Laskar et al., 1993].
5.3. Sedimentation Rate Constraints
- To prevent tuning errors the authors monitor the implied average sedimentation rate of the stack throughout the tuning process.
- The authors construct two different estimates of global sedimentation rates: an LSR stack, which averages the sites’ sedimentation rates, and a ‘‘normalized’’ LSR stack, which compensates for different mean sedimentation rates (MSR) across sites.
- The LSR of each site is calculated by placing its d18O record on the stack’s timescale and calculating its sedimentation rate.
- For the eleven sites with d18O records aligned to the stack in multiple segments, the LSR of each segment is normalized separately.
- For the idealized case in which each LSR is generated by an independent, stationary random process, the normalized LSR stack for the ‘‘true’’ age model would converge to a constant value of unity.
5.4. Tuning
- The LR04 stack is tuned to their simple ice model in a two-step process by the addition of age control points with an average spacing of 20 kyr.
- Figure 5 shows the early Pleistocene portion of the stack and illustrates the balance achieved between strictly tuning the stack and minimizing the variance of normalized LSR. [26].
- The authors ice-model tuning target, which inherently accentuates the effects of obliquity relative to precession due to its long time constant, produces a fairly good match to the d18O stack.
- The normalized LSR stack generally varies by less than 10% from 4.3–0.1.
- The stack is generally incoherent with respect to the eccentricity component of insolation, but coherence with the obliquity component is at the 95% confidence level for most of its length and is always above the 80% confidence level.
6. Results
- The LR04 benthic stack reconstructs the average d18O signal of each marine isotope stage and substage within the Pliocene and Pleistocene.
- The features of these stages are largely independent of the assigned age model because the stack is constructed by graphic correlation.
- Overall, the mean standard error of the stack is 0.06%, and only 2% of the data points have errors greater than 0.1%.
- The authors define termination magnitude as the difference between the maximum d18O value of the preceding glacial and the minimum of the following interglacial.
- In comparison, stages 9 and 5 remained below 3.6% for 13 and 12 kyr, respectively, and the Holocene interglacial has lasted 11 kyr so far.
6.2. MIS Identification
- Below MIS 104 the authors adopt the stage identification scheme of Shackleton et al. [1995a] (hereinafter referred to as SHP95).
- Co2 is the uppermost glacial excursion within the Cochiti subchron.
- Additionally, the flexibility of the SHP95 numbering scheme minimizes the number of renamed stages because new stages in one magnetic subchron will not alter MIS names in other subchrons. [33].
- Some of the smaller Pliocene stages from Sites 607 and 846 become better defined in the stack (e.g., MIS 77 and 83) while others almost disappear because they are small or absent in most d18O records.
- Below the Mammoth subchron, the LR04 stack reduces noise in some portions of the record to the extent that new isotopic stages can be resolved.
6.3. Paleomagnetic Polarity Reversals
- Errors in these estimates can arise from both age model construction and reversal identification within sediment cores.
- Because fewer records are available, below the Matuyama the authors also use reversal identifications from Leg 138, correlated to Site 846 [Shackleton et al., 1995b].
- Ages for the Kaena and Mammoth subchrons are averages from Sites 607 and 846 while the Gauss/Gilbert boundary and the top of the Cochiti subchron are dated from Sites 659 and 846.
- All other polarity reversals are based solely on Site 846.
- Given the error involved in reversal identification, the authors observe that all four age models are quite similar.
6.4. Comparison to S95 Composite
- With a few exceptions, the LR04 global PliocenePleistocene stack is similar to the S95 composite, which contains unstacked, high-resolution benthic records from sites V19-30, ODP 677, and ODP 846.
- Additionally, the higher signal-to-noise ratio of the LR04 stack allows us to resolve new isotopic stages in the early Pliocene, as detailed above.
- On the basis of the average sedimentation rates of over 30 marine sediment records, the authors propose that the MIS 13 and 14 age estimates of the S95 composite and EDC2 are in error.
- Because the EDC2 timescale is otherwise in close agreement with ours, the misalignment of stages 13 and 14 may indicate a stratigraphic disturbance in the ice core at the top of MIS 15. [38].
- Ma the S95 composite is on average 7 kyr older than the LR04 age model, primarily due to the different phase lag assumptions used.
6.5. Comparison to Other Stacks
- The LR04 benthic stack is generally similar to previously published stacks with respect to MIS features and timescale but differs somewhat in its variance and spectral density.
- Indeed, the tropical stack has only 25% as much precessional variance as the LR04 stack (Table 5).
- These age differences all fall within the uncertainty estimates published for the HW04 age model.
- The leading EOF of their best benthic and planktonic records contains proportionally more variance than the LR04 stack in the 100-kyr band but less in the 41- and 23-kyr bands.
- The spectral power and substage features of their EOF are also affected by the use of only 17 age control points to align the records.
7.1. Age Model Uncertainty
- The greatest potential source of error in the LR04 age model is uncertainty in the orbital solution, which may be as high as 25 kyr in the early Pliocene.
- Relative to the orbital solution, their tuning errors should be no more than a few thousand years because the authors tune a low-noise signal and avoid spikes in the stack’s average sedimentation rate.
- Ma the LR04 age model is also subject to increased uncertainty because the stack contains fewer records and inherently has fewer tuning and alignment constraints. [44].
- In the more recent part of the age model, most of the uncertainty derives from their sedimentation rate constraint and the assumed response times of the ice sheets.
- The LSR tuning technique may neglect some real but highfrequency changes in global LSR, such as those resulting from global climate reorganizations over glacial-interglacial cycles.
7.2. Precession Phase and Deep-Water Temperature
- As explained in section 5.4, the time constant of their ice model is the primary factor controlling the stack’s phase relative to obliquity.
- Indeed, Figure 7 shows that the stack’s lag in precession actually decreases at 2.7.
- This small lag suggests that a PA1003 LISIECKI AND RAYMO: PLIOCENE-PLEISTOCENE BENTHIC STACK 14 of 17 PA1003 significant portion of the precession component of late Pliocene d18O is a deep-water temperature signal which leads ice volume.
- Ma the precession lag suddenly jumps by 45 relative to that of obliquity, putting it in close agreement with their ice model for the rest of the Pleistocene. [46].
- If the ice model’s mean time constant Tm is held constant at 15 kyr for the last 3 Myr, a 30 change in precession lag still occurs at 1.6 Ma.
8. Conclusions
- The global Pliocene-Pleistocene stack presented in this paper contains benthic d18O data from 57 globally distributed sites and has an average standard error of only 0.06%.
- The LR04 stack and the LR04 agemodel provide the paleoclimate community with two stratigraphic tools, which can be applied to a wide variety of Pliocene-Pleistocene studies.
- The authors define 24 new isotopic stages from 5.0– 3.4 Ma and identify several likely errors in the S95 composite.
- Tm mean time constant of ice, kyr; s standard deviation. [51].
- L. Lisiecki also thanks T. Herbert, W. Prell, and S. Clemens for their guidance throughout this project.
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"A Pliocene-Pleistocene stack of 57 ..." refers background in this paper
...to as SCHPS95) and Cande and Kent [1995] (hereinafter referred to as CK95) also result in higher LSR variability before 4....
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1,995 citations
1,885 citations
"A Pliocene-Pleistocene stack of 57 ..." refers background in this paper
...The LR04 stack contains significantly more variance in benthic d18O than previously published stacks of the late Pleistocene as the result of higherresolution records, a better alignment technique, and a greater percentage of records from the Atlantic....
[...]
...The stack’s resolution of orbital-scale (23-kyr) features in the Pleistocene is comparable to that of millennial-scale (1.5-kyr) features in the GISP2 d18O record [Grootes et al., 1993], with 10–20 samples per cycle....
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Frequently Asked Questions (21)
Q2. What are the future works mentioned in the paper "A pliocene-pleistocene stack of 57 globally distributed benthic do records" ?
The LR04 stack is also the first stack to extend before 2. 5 Ma and therefore offers an invaluable improvement in signal quality for the early to mid-Pliocene. Finally, the LR04 stack ’ s phase relative to precession suggests the presence of a large deep-water temperature signal from 2. 7– 1. 6 Ma and reveals a sudden change in the phase of precession response at 1.
Q3. Why is the phase of the stack determined by the lag?
Because the authors emphasize obliquity in their tuning process, its phase relative to insolation is primarily determined by the lag generated by their ice model.
Q4. What is the way to reduce stack error?
Stacking records of varying resolution (while holding the total number of data points constant) tends to reduce stack error by improving the alignment accuracy of high resolution records.
Q5. What are the stages which are unusually small or poorly defined in the LR04 stack?
The stages which are unusually small or poorly defined in the LR04 stack are MIS 68, 69, 79, 80, 94, 102, G5, G8, G9, K2, and KM6. [34]
Q6. What are the objective correlation techniques?
Automated correlation algorithms provide the most objective correlation techniques because alignment criteria are explicit and applied consistently.
Q7. What is the common d18O reference signal?
Another important d18O reference signal is the 6-Myr composite benthic d18O sequence of Shackleton [1995] (hereinafter referred to as S95), which was constructed by placing high-resolution d18O records from three different sites (V19-30, ODP 677, and ODP 846) in series.
Q8. What is the only record in the stack to contain both large glacial excursions?
Site 846 is the only record in the stack to contain both large glacial excursions, suggesting a possible coring or splicing error.
Q9. What is the standard deviation of the stack?
The normalized stack, in which each LSR record is divided by its mean sedimentation rate, has a standard deviation of 0.09 in the final LR04 age model.
Q10. What is the average coherence of the stack with obliquity?
The stack is generally incoherent with respect to the eccentricity component of insolation, but coherence with the obliquity component is at the 95% confidence level for most of its length and is always above the 80% confidence level.
Q11. How much precession can be expected from the tropical stack?
Phase differences of up to 11 kyr between their d18O records can be expected to reduce their stack’s precession component in particular.
Q12. What is the way to align d18O records?
The authors align 57 benthic d18O records using an automated graphic correlation program [Lisiecki and Lisiecki, 2002], which considers all possible alignments to find the best global fit and penalizes alignments based on extreme sedimentation rates and sudden sedimentation rate changes.
Q13. Why is the LR04 stack robust to the inclusion of records of varying quality?
Their stacking technique, described below, is robust to the inclusion of records of varying quality because sites with higher resolution are more heavily weighted in the averaging process.
Q14. Why do the authors not adjust the isotope curves?
The authors choose not to adjust the isotope curves based on their modern bottom water temperatures because the temperature differences between sites may have changed dramatically over the last 5.3 Myr.
Q15. Why is the LR04 age model more reliable than a single d18O record?
This age model is more reliable than one from a single d18O record because individual d18O records have more noise and fewer constraints on linear sedimentation rates (LSR) than a stack.
Q16. What is the tuning target for the ice core?
Their tuning target is a simple nonlinear model of ice volume, y, which follows the equationdy dt ¼ 1 b Tm x yð Þ ð1Þwhere the nonlinearity coefficient b is subtracted during ice growth and added during ice decay [Imbrie and Imbrie, 1980].
Q17. Why do the authors avoid assumptions about the age of each glacial cycle?
Because this initial age model is derived primarily from globally averaged sedimentation rates with minimal orbital tuning, the authors avoid assumptions about the age or length of each glacial cycle.
Q18. How many records could be aligned to the LR04 stack?
most of their records could be aligned to it in one piece, reducing the potential for errors where the shorter stacks join together.
Q19. What is the effect of the LR04 age model on the precession power of the tropical?
the lower precession power of the tropical stack (Figure 12) is not caused by age model differences because using the LR04 age model only increases the tropical stack’s precession power to 2.8% of total variance. [42]
Q20. What is the way to compare d18O records to planktonic records?
Benthic d18O records should produce a better stack than planktonic records because the deep ocean is more uniform in temperature and salinity than surface water.
Q21. Why do they present a second, tropical stack?
they present a second, tropical stack containing only six of these records because they find their alignment technique to be inadequate for cores with highly variable sedimentation rates.