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Laurance Donnelly and Martin Culshaw discuss ‘The new Abandoned Mine Workings Manual (C758D)’, a manual that provides a risk-based approach to the identification, evaluation, mitigation and remediation of mining hazards and their associated risks.
Reviewed by Leigh Sharpe
Bruce Yardley (Leeds University) has been appointed Chief Geologist by The Radioactive Waste Management Directorate (RWMD) of the Nuclear Decommissioning Authority (NDA).
Chartership Officer Bill Gaskarth reports on a projected new logo for use by CGeols, advice on applications and company training schemes
The Society has published an addendum to 'Climate Change: Evidence from the Geological Record' (November 2010) taking account of new research
Oliver Pritchard, Stephen Hallett, and Timothy Farewell consider the role of soil science in maintaining the British 'evolved road'
Kathryn Goodenough* on a Society-sponsored hunt for the rare metals that underpin new technologies
As Nina Morgan Discovers, the debate over HS2 is nothing new...
Ted Nield hails the new refurbished Council Room as evidence that the Society is growing up
Fellows - renew, vote for Council, and volunteer for Earth Science Week 2014! Also - who is honoured in the Society's Awards and Medals 2014.
Peter Fookes (Imperial College, London) celebrated at Society event in honour of Engineering Group Working Parties and their reports
When are University Earth Science departments going to shed their outmoded obsession with maths, physics and chemistry?
Nancy Tupholme, Librarian of the Society and the Royal Society, has died, reports Wendy Cawthorne.
Ted Nield reviews the refurbishment of the Council Room, Burlington House
You can help the Haslemere Educational Museum to identify subjects in Sir Archibald Geikie's amazing field notebook sketches, writes John Betterton.
Who are the top 100 UK practising scientists? The Science Council knows...
Image: Toarcian sands showing 'cyclic' sedimentation pattern frequently ascribed to orbitally induced climatic fluctuations. Photo: Ted Nield, from the Society's Online Photolibrary. Detecting Milankovitch-band (orbitally-forced) cyclicity in stratigraphic data holds out the tantalising possibility of time calibration. Most of such detections derive from statistical analyses of power spectra; but in a new paper Vaughan, Bailey and Smith1 demonstrate that many (perhaps the majority) of those in the literature (generated by procedures that have become the standard) are false. Stratigraphic data suitable for spectral analysis comprise measurements of rock properties taken at regularly-spaced intervals. The key question concerns the nature of the peaks in the ‘red noise’ power spectra that these data display. Do the peaks represent cycles, or chance fluctuations from the noise? Significance tests are then used to answer the question: “How unlikely is it that a peak in the observed spectrum was generated by the noise?”
QUASI-PERIODIC
One problem in the detection of quasi-periodic (M-) forcing in stratigraphic data is the generally unknown relationship between stratal thickness and geological time. The question thus becomes: “Are there any cycles in the data?” Answering this means testing each of perhaps hundreds of frequencies in the spectrum; but despite using the canonical p < 0.05 threshold for detection, the multiple testing methods commonly used will result in false positives for almost any reasonably-sized dataset. This fact is easily demonstrated with cycle-free synthetic, random data. There are simple methods to correct for the effect of multiple tests, but these are not routinely applied in cyclo-stratigraphic analysis. The result of the significance test is conditional on the null hypothesis model adopted for the noise in the data series. Apparent ‘detections’ will arise wherever the noise model differs significantly from the data, whether or not this difference arises as a result of cyclic variations or an undiagnosed mismatch between the noise model and the noise spectrum in the data. The model most often used in cyclo-stratigraphic work is the autoregressive AR(1), a simple process characterised by only two parameters. It would be surprising if a wide range of different and complex sedimentary systems all generated variations with such simple statistical properties. Vaughan et al. demonstrate that real datasets often display power spectra rather different from the simplistic AR(1) case. This data-model mismatch is another source of spurious cycle detections, and goes unnoticed because model checking is not routinely applied in stratigraphic spectral analysis. Vaughan et al. analysed four well-known datasets for which cyclicities have been claimed, applying model checking and accounting for multiple tests. The cyclicity detections were reproduced, in only one case. This suggests that the majority of published reports of regular Milankovitch-band cyclicities (eg in Paleogene, Mesozoic, and older strata), and the resultant astrochronological time calibrations, are based on statistically unsound detections. On a positive note, the more general approaches outlined by Vaughan et al. allow for the investigation of a wider range of spectral features than considered by the standard approaches.