Did the Sun tickle the diatoms of Disko Bugt?

Diatoms, transfer functions and claims of palaeoecological evidence of solar variability: how could I resist discussing Sha et al. (2014)?

Sha et al develop a diatom-sea ice transfer function and apply it to a diatom record from a core from Disko Bugt on the west coast of Greenland. They compare the resulting reconstruction with the reconstruction of total solar irradiance from Steinhilber et al. (2012).

I’m not going to discuss the sea-ice transfer function.

OK, well just a bit.

The paper reports the results of a constrained correspondence analysis (an ordination method suitable for ecological data)

The eigenvalues of CCA axes 1 and 2 are 0.441 and 0.165, respectively, indicating that axis 1 captures most of the variance in the data set and therefore is most important.

Since it is guaranteed that CCA axis 1 will be at least as large as CCA axis 2, reporting that CCA axis 1 is largest does not provide any information (at least not about the data).

The initial CCA model contains mean sea-ice concentration of each month of the year as predictors. Months with a variance inflation factor greater than 20 were then deleted as they contain little unique information. This is a poor strategy for simplifying models: variables are deleted on the basis of their correlation with other variables rather than on their ecological importance. There is no guarantee that this procedure will find the most important ecological variables.

Skipping over some other issues with the reconstruction, some of which are generic to sea-ice reconstructions, lets have a look at the evidence for the sea ice-solar relationship.

Figure 1. The relationship between the reconstructed April sea-ice concentrations of marine sediment core DA06-139G, changes in warm-water diatom taxa and Atlantic foraminiferal assemblage, the reconstructed May sea-ice concentration based on diatom data from core MD99-2269 on the North Iceland shelf (Justwan and Koç Karpuz, 2008), as well as total solar irradiance variations constructed from the 10Be record in the Greenland and Antarctica ice cores and tree-ring records of 14C fluctuations (Steinhilber et al., 2012).

Figure 1. The relationship between the reconstructed April sea-ice concentrations of marine sediment core DA06-139G, changes in warm-water diatom taxa and Atlantic foraminiferal assemblage, the reconstructed May sea-ice concentration based on diatom data from core MD99-2269 on the North Iceland shelf (Justwan and Koç Karpuz, 2008), as well as total solar irradiance variations constructed from the 10Be record in the Greenland and Antarctica ice cores and tree-ring records of 14C fluctuations (Steinhilber et al., 2012).

This graph is it.

Focus on the upper and lower curve in figure 1, the total solar irradiance curve and the April sea-ice reconstruction. Are you convinced the records are correlated? No statistical measure of the strength or significance of the correlation of these two records are given in the paper.

A correlation-by-eye of two autocorrelated proxy records is not evidence: it is too easy to see the wiggles that matches in both records, and ignore the wiggles that don’t. There are methods to calculate the correlation between age-uncertain proxy records. Use them!

If you are reviewing a paper that relies on correlation-by-eye, don’t play Lord Polonius,  sycophantically nodding to any suggested resemblance  between shapes; challenge the authors to substantiate their claims. All clouds look like weasels if you have enough imagination.


Sha et al. (2014) A diatom-based sea-ice reconstruction for the Vaigat Strait (Disko Bugt, West Greenland) over the last 5000 yr. Palaeogeography, Palaeoclimatology, Palaeoecology 403, 66–79.

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About richard telford

Ecologist with interests in quantitative methods and palaeoenvironments
This entry was posted in climate, Peer reviewed literature, solar variability, transfer function and tagged , , . Bookmark the permalink.

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