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9:00 Maria Zicos: Exploring the genetics of the extinct Darwin’s ground sloth (Mylodon darwinii) population from Cueva del Milodón, Chile
Sloths (Xenarthra, Folivora) were one of the dominant mammalian groups in Southern and Central America until the early Holocene. Folivora used to have a large range of body sizes, locomotion and ecology, while extant sloths are morphologically and ecologically similar. Research into the molecular evolution and biology of sloths, previously limited to extant species, has started to leverage information contained in the large recent fossil record of this group through ancient DNA methods.
Cueva del Milodón (Ultima Esperanza, Chile) is renowned for its exceptionally preserved faunal record. Remains of Darwin’s ground sloth (Mylodon darwinii) are found there from the end of the last Ice Age to their extinction in the early Holocene.
Here I present novel findings from genomic data from multiple M. darwinii individuals, exploring genetic diversity in this site. Using ancient DNA methods, twelve new mitochondrial genomes and two nuclear genomes were recovered from bone, skin and coprolites from Cueva del Milodón in British and Swiss museum collections.
The mitochondrial diversity was low, yet higher than that found in another megaherbivore population, sampled near its extinction: Holocene woolly mammoths (Mammuthus primigenius) from Wrangel Island. Nuclear diversity in the two higher coverage genomes will reveal whether low diversity is also found in the nuclear genome.
These findings, combined with direct radiocarbon dates, will be used to reconstruct the demographic history of the species, and to test models for their extinction, hoping to better understand why these sloths became extinct, while extant sloths persisted.
9:15 Daniel Parkes: Investigating the cause and structure of abrupt climate change events during MIS 11c
Throughout the last 2.6 million years the earth’s climate has oscillated between cold and warm phases, known as glacial-interglacial cycles, as a result of orbital forcing. To better understand climatic responses, it is necessary to look at interglacial periods with similar orbital parameters to today. Of these, Marine Oxygen Isotope Stage (MIS) 11 (~424,000 years ago) is of growing importance as; 1) an orbital analogue to the present day; and 2) a time of significant Greenland Ice Sheet (GIS) loss. Freshwater influx as a result of GIS melt is thought to induce climatic instability in the northern hemisphere by disrupting ocean circulation, which normally brings warm water to the higher latitudes. This is hypothesised to be the cause of a cooling event known as “The Non-Arboreal Pollen Phase” in MIS 11c, which is recorded in sediments across Europe, though the mechanism of this event is not well understood. Presently, there are a number of cores that indicate reduction in sea surface temperature in the early stages of MIS 11c, seemingly concurrent with this event, though no deep-water connection has yet been found. This PhD project aims to investigate this further by (1) producing high-resolution temperature and aridity records for palaeolake basin(s) that record the event (2) investigating this event in multiple marine sites across the North Atlantic (3) establishing the driving factors responsible for this event.
9:30 Adam Smith: Never mind the trunk stream, here’s the tributaries! Incorporating entire stream networks into river profile analysis
The shape of river profiles reflects local tectonic processes and climate conditions. The stream power model, a family of equations based on river properties, is widely used by geologists and geomorphologists to learn about landscape development and the underlying conditions that shape it. One particularly important metric derived from the stream power laws is channel steepness index (ksn ), a proxy for uplift rate. Owing to the development of different solutions to the stream power laws, multiple approaches can be used to calculate ksn, however, each approach can produce different values. This is problematic. How can we compare values across studies that have used different approaches, how do we know which values are truly representative, and which approach is best?
We have evaluated several key approaches, assessing accuracy and bias with aid of an artificial river profile. Each approach is used to calculate ksn from the same artificial dataset, where the values of ksn are already known. A river profile is then reconstructed using the calculated ksn values, and the residuals between the reconstructed profile and the true profile are determined, offering some quantification of bias. Two of the best performing approaches were then tested on a real dataset from the Sierra Nevada, California. This mountain range has an interesting and debated uplift history, owing to it's unusual structure. It was found that an approach based on a linear inversion of river network data provides the most accurate results with high spatial resolution. Applying this approach to the southern Sierra Nevada two separate processes of uplift that operated in different parts of the study area are identified, improving on the resolution of previous geomorphic studies and the other approach in this study. Choice of methodology is therefore crucial to ensure we leverage as many signals from a dataset as possible.