
UCPH
FundRef: 501100006442 , 501100001734 , 501100006316 , 501100005193 , 501100006534
ISNI: 000000010674042X
FundRef: 501100006442 , 501100001734 , 501100006316 , 501100005193 , 501100006534
ISNI: 000000010674042X
3 Projects, page 1 of 1
assignment_turned_in Project2020 - 2023Partners:UCL, WSU, VUA, Pennsylvania State University, University of Rome Tor Vergata +17 partnersUCL,WSU,VUA,Pennsylvania State University,University of Rome Tor Vergata,New Mexico Institute of Mining and Techn,Plymouth University,NHMD,University of Kansas,PSU,BBK,College of Charleston,Pennsylvania State University,British Geological Survey,University of Michigan–Flint,KU,Natural History Museum of Denmark,New Mexico Institute of Mining and Technology,University of Michigan–Ann Arbor,UCPH,NERC British Geological Survey,Free (VU) University of AmsterdamFunder: UK Research and Innovation Project Code: NE/T001518/1Funder Contribution: 502,980 GBPThe development of radiometric geochronology is one of the greatest triumphs of 20th century geoscience. Geochronology underpins the study of Earth history and puts fundamental constraints on the rate of biological evolution. Tremendous resources are invested in the development of sophisticated mass spectrometers capable of measuring isotopic ratios with ever increasing resolution and sensitivity. Unfortunately, the statistical treatment of mass spectrometer data has not kept up with these hardware developments and this undermines the reliability of radiometric geochronology. This proposal aims to create a 'software revolution' in geochronology, by building an internally consistent ecosystem of computer programs to account for inter-sample error correlations. These have a first order effect on the precision and accuracy of geochronology but are largely ignored by current geochronological data processing protocols. The proposed software will modify existing data reduction platforms and create entirely new ones. It will implement a data exchange format to combine datasets from multiple chronometers together whilst keeping track of the correlated uncertainties between them. The new algorithms will be applied to five important geological problems. 1. The age of the Solar System is presently constrained to 4567.30 +/- 0.16 Ma using primitive meteorites. The meteorite data are 'underdispersed' with respect to the analytical uncertainties. The presence of strong inter-sample error correlations is one likely culprit for this underdispersion. Accounting for these correlations will significantly improve the accuracy and precision of this iconic age estimate. 2. The Cretaceous-Palaeogene boundary marks the disappearance of the dinosaurs in the most notorious mass extinction of Earth history. We will re-evaluate the timing of critical events around this boundary using high precision 40Ar/39Ar geochronology. Preliminary results from other samples show that 40Ar/39Ar data are prone to strong (r^2 > 0.9) inter-sample error correlations, and that these have a first order effect on the precision and accuracy of weighted mean age estimates. A sensitivity test indicates that this may change the timing of the mass extinction by up to 200ka. 3. The 'Taung Child' is a famous hominin fossil that was discovered in a South African cave in 1924. It is considered to be the world's first Australopithecine, but has not yet been dated. We have a good unpublished U-Pb age of 1.99 +/- 0.05 Ma from a tufa collected above the hominid, and an imprecise upper age limit of 1.4 +/- 2.7 Ma on a calcrete deposit below it. Applying the new algorithms to the latter date will greatly improve its precision. This will be further improved with additional measurements, in time for the 100th anniversary of the Taung Child's discovery. 4. Depth profiling of the U-Pb ages in rutile and apatite provides an exciting new way to constrain the thermal evolution of lower crustal rocks. However, the laser ablation data used for this research are prone to strong error correlations that are not accounted for by current data reduction protocols. These protocols will be revised using the new software, permitting better resolution of the inferred t-T paths. (5) Radiogenic noble gases such as 40Ar (from 40K), 4He (from U, Th and Sm), and 129Xe (from 129I) are lost by volume diffusion at high temperatures. The revised regression algorithms implemented by the research programme will be applied to step-heating 'Arrhenius' experiments. This will improve the calculation of diffusion coefficients for these gas species, resulting in further improvement of (noble gas) thermochronology.
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For further information contact us at helpdesk@openaire.euassignment_turned_in Project2014 - 2017Partners:University of California Los Angeles, CNRS, NHMD, Leiden University, University of Salford +32 partnersUniversity of California Los Angeles,CNRS,NHMD,Leiden University,University of Salford,Natural History Museum of Denmark,LMU,University of Oxford,RAS,Hokkaido University,The University of Manchester,University of Rennes 1,Biodiscovery - LLC / MYcroarray,École Normale Supérieure de Lyon,Trinity College Dublin, Ireland,University of Edinburgh,MYcroarray (United States),Australian National University,Royal Belgium Inst of Natural Sciences,Russian Academy of Sciences,PACIFIC IDentifications Inc,University of California Los Angeles,Ludwig Maximilian University of Munich,UCPH,Natural History Museum,Royal Belgium Inst of Natural Sciences,University of Rennes 1,University of Alberta,Chinese Academy of Social Sciences,Australian National University (ANU),ENS de Lyon,University of Alberta,CNRS,PACIFIC IDentifications Inc,CASS,Uppsala University,Natural History MuseumFunder: UK Research and Innovation Project Code: NE/K005243/2Funder Contribution: 330,678 GBPThe shift from hunting and gathering to an agricultural way of life was one of the most profound events in the history of our species and one which continues to impact our existence today. Understanding this process is key to understanding the origins and rise of human civilization. Despite decades of study, however, fundamental questions regarding why, where and how it occurred remain largely unanswered. Such a fundamental change in human existence could not have been possible without the domestication of selected animals and plants. The dog is crucial in this story since it was not only the first ever domestic animal, but also the only animal to be domesticated by hunter-gatherers several thousand years before the appearance of farmers. The bones and teeth of early domestic dogs and their wild wolf ancestors hold important clues to our understanding of how, where and when humans and wild animals began the relationship we still depend upon today. These remains have been recovered from as early as 15,000 years ago in numerous archaeological sites across Eurasia suggesting that dogs were either domesticated independently on several occasions across the Old World, or that dogs were domesticated just once and subsequently spreading with late Stone Age hunter gatherers across the Eurasian continent and into North America. There are also those who suggest that wolves were involved in an earlier, failed domestication experiment by Ice Age Palaeolithic hunters about 32,000 years ago. Despite the fact that we generally know the timing and locations of the domestication of all the other farmyard animals, we still know very little for certain about the origins of our most iconic domestic animal. New scientific techniques that include the combination of genetics and statistical analyses of the shapes of ancient bones and teeth are beginning to provide unique insights into the biology of the domestication process itself, as well as new ways of tracking the spread of humans and their domestic animals around the globe. By employing these techniques we will be able to observe the variation that existed in early wolf populations at different levels of biological organization, identify diagnostic signatures that pinpoint which ancestral wolf populations were involved in early dog domestication, reveal the shape (and possibly the genetic) signatures specifically linked to the domestication process and track those signatures through time and space. We have used this combined approach successfully in our previous research enabling us to definitively unravel the complex story of pig domestication in both Europe and the Far East. We have shown that pigs were domesticated multiple times and in multiple places across Eurasia, and the fine-scale resolution of the data we have generated has also allowed us to reveal the migration routes pigs took with early farmers across Europe and into the Pacific. By applying this successful research model to ancient dogs and wolves, we will gain much deeper insight into the fundamental questions that still surround the story of dog domestication.
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For further information contact us at helpdesk@openaire.euassignment_turned_in Project2013 - 2014Partners:LMU, University of California Los Angeles, Ludwig Maximilian University of Munich, University of Edinburgh, Natural History Museum +35 partnersLMU,University of California Los Angeles,Ludwig Maximilian University of Munich,University of Edinburgh,Natural History Museum,CASS,NHMD,Australian National University,Trinity College Dublin, Ireland,University of Alberta,University of Manchester,Hokkaido University,Australian National University (ANU),Royal Belgium Inst of Natural Sciences,University of Rennes 1,Natural History Museum,University of California, Los Angeles,Biodiscovery - LLC / MYcroarray,University of Salford,ENS de Lyon,MYcroarray (United States),Chinese Academy of Social Sciences,RAS,Royal Belgium Inst of Natural Sciences,Russian Academy of Sciences,Natural History Museum of Denmark,UCPH,Uppsala University,University of Alberta,Leiden University,PACIFIC IDentifications Inc,The University of Manchester,University of Rennes 1,École Normale Supérieure de Lyon,Durham University,University of California Los Angeles,CNRS,CNRS,PACIFIC IDentifications Inc,Durham UniversityFunder: UK Research and Innovation Project Code: NE/K005243/1Funder Contribution: 443,723 GBPThe shift from hunting and gathering to an agricultural way of life was one of the most profound events in the history of our species and one which continues to impact our existence today. Understanding this process is key to understanding the origins and rise of human civilization. Despite decades of study, however, fundamental questions regarding why, where and how it occurred remain largely unanswered. Such a fundamental change in human existence could not have been possible without the domestication of selected animals and plants. The dog is crucial in this story since it was not only the first ever domestic animal, but also the only animal to be domesticated by hunter-gatherers several thousand years before the appearance of farmers. The bones and teeth of early domestic dogs and their wild wolf ancestors hold important clues to our understanding of how, where and when humans and wild animals began the relationship we still depend upon today. These remains have been recovered from as early as 15,000 years ago in numerous archaeological sites across Eurasia suggesting that dogs were either domesticated independently on several occasions across the Old World, or that dogs were domesticated just once and subsequently spreading with late Stone Age hunter gatherers across the Eurasian continent and into North America. There are also those who suggest that wolves were involved in an earlier, failed domestication experiment by Ice Age Palaeolithic hunters about 32,000 years ago. Despite the fact that we generally know the timing and locations of the domestication of all the other farmyard animals, we still know very little for certain about the origins of our most iconic domestic animal. New scientific techniques that include the combination of genetics and statistical analyses of the shapes of ancient bones and teeth are beginning to provide unique insights into the biology of the domestication process itself, as well as new ways of tracking the spread of humans and their domestic animals around the globe. By employing these techniques we will be able to observe the variation that existed in early wolf populations at different levels of biological organization, identify diagnostic signatures that pinpoint which ancestral wolf populations were involved in early dog domestication, reveal the shape (and possibly the genetic) signatures specifically linked to the domestication process and track those signatures through time and space. We have used this combined approach successfully in our previous research enabling us to definitively unravel the complex story of pig domestication in both Europe and the Far East. We have shown that pigs were domesticated multiple times and in multiple places across Eurasia, and the fine-scale resolution of the data we have generated has also allowed us to reveal the migration routes pigs took with early farmers across Europe and into the Pacific. By applying this successful research model to ancient dogs and wolves, we will gain much deeper insight into the fundamental questions that still surround the story of dog domestication.
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