Luminescence Dating in Fluvial Settings: Overcoming the Challenge of Partial Bleaching

Optically stimulated luminescence (OSL) dating is a versatile technique that utilises the two most ubiquitous minerals on Earth (quartz or K-feldspar) for constraining the timing of sediment deposition. It has provided accurate ages in agreement with independent age control in many fluvial settings, but is often characterised by partial bleaching of individual grains. Partial bleaching can occur where sunlight exposure is limited and so only a portion of the grains in the sample was exposed to sunlight prior to burial, especially in sediment-laden, turbulent or deep water columns. OSL analysis on multiple grains can provide accurate ages for partially bleached sediments where the OSL signal intensity is dominated by a single brighter grain, but will overestimate the age where the OSL signal intensity is equally as bright (often typical of K-feldspar) or as dim (sometimes typical of quartz). In such settings, it is important to identify partial bleaching and the minimum dose population, preferably by analysing single grains, and applying the appropriate statistical age model to the dose population obtained for each sample. To determine accurate OSL ages using these age models, it is important to quantify the amount of scatter (or overdispersion) in the well-bleached part of the partially bleached dose distribution, which can vary between sediment samples depending upon the bedrock sources and transport histories of grains. Here, we discuss how the effects of partial bleaching can be easily identified and overcome to determine accurate ages. This discussion will therefore focus entirely on the burial dose determination for OSL dating, rather than the dose-rate, as only the burial doses are impacted by the effects of partial bleaching

Growth and retreat of the last British–Irish Ice Sheet, 31 000 to 15 000 years ago: the BRITICE-CHRONO reconstruction

The BRITICE-CHRONO consortium of researchers undertook a dating programme to constrain the timing of advance, maximum extent and retreat of the British?Irish Ice Sheet between 31?000 and 15?000?years before present. The dating campaign across Ireland and Britain and their continental shelves, and across the North Sea included 1500?days of field investigation yielding 18?000?km of marine geophysical data, 377 cores of sea floor sediments, and geomorphological and stratigraphical information at 121 sites on land; generating 690 new geochronometric ages. These findings are reported in 28 publications including synthesis into eight transect reconstructions. Here we build ice sheet-wide reconstructions consistent with these findings and using retreat patterns and dates for the inter-transect areas. Two reconstructions are presented, a wholly empirical version and a version that combines modelling with the new empirical evidence. Palaeoglaciological maps of ice extent, thickness, velocity, and flow geometry at thousand-year timesteps are presented. The maximum ice volume of 1.8?m sea level equivalent occurred at 23?ka. A larger extent than previously defined is found and widespread advance of ice to the continental shelf break is confirmed during the last glacial. Asynchrony occurred in the timing of maximum extent and onset of retreat, ranging from 30 to 22?ka. The tipping point of deglaciation at 22?ka was triggered by ice stream retreat and saddle collapses. Analysis of retreat rates leads us to accept our hypothesis that the marine-influenced sectors collapsed rapidly. First order controls on ice-sheet demise were glacio-isostatic loading triggering retreat of marine sectors, aided by glaciological instabilities and then climate warming finished off the smaller, terrestrial ice sheet. Overprinted on this signal were second order controls arising from variations in trough topographies and with sector-scale ice geometric readjustments arising from dispositions in the geography of the landscape. These second order controls produced a stepped deglaciation. The retreat of the British?Irish Ice Sheet is now the world?s most well-constrained and a valuable data-rich environment for improving ice-sheet modelling