Dynamic patterns of ice recession in northern Patagonia

Theme: Past Life & Environments

Primary Supervisor:

Bethan Davies

Department of Geography, RHUL

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Secondary Supervisor:

Varyl Thorndycraft

Department of Geography, RHUL

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Project Description:

During the Last Glacial Maximum (LGM), the Patagonian Ice Sheet expanded eastwards as a series of lobes into the foothills of the Andes. Patterns of recession north of the North Patagonian Icefield are however poorly constrained, and the location and timing of the LGM in many places is undefined (Martínez et al., 2011). Ice may have reached its maximum and receded at different rates across a latitudinal gradient in southern South America, but a lack of data north of the North Patagonian Icefield makes it challenging to test this hypothesis. This project will investigate the timing and style of deglaciation in northern Patagonia to ascertain controls and influences on glaciation.

This project will use detailed geomorphological mapping across several eastward-flowing ice lobes (from remote sensing and field surveys) to generate a landsystems model describing ice dynamics during and after the LGM (cf. Darvill et al., 2016). It will also utilise multiproxy dating techniques (tephrochronology and radiocarbon dating of sediment cores from inter-morainic lakes and lakes behind moraines (e.g., Stern et al., 2015); cosmogenic nuclide dating from glacially transported boulders on moraine crests) to determine and date dynamic patterns of ice recession. We will test the hypothesis that patterns of recession vary on a latitudinal gradient by comparing our data to well-dated ice margins further south, and investigate the climatic causes and controls on glacier recession.

Policy Impact of Research:

This research will yield insights into the past behaviour of Southern Hemisphere Westerlies. Changes in these winds may affect the future rate of recession of glaciers. These glaciers provide water, and recession could result in increased risk of glacier-lake outburst floods. This research could therefore inform climate change adaptation here.

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