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Collection effort, geological context and the hominin fossil record

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Project Description

Statistical evaluation of the evolutionary and sampling signals within the hominin fossil record has only recently been considered (Faith et al., 2021), and much of the fundamental data collection and statistical work has yet to be attempted. 

This research will investigate rock record bias within the extensional basins of the East African Rift Valley, where many hominin fossils have been collected. Karstic settings, like those that have yielded many southern African hominin specimens, will present a different set of biases. Collection biases, such as the bonanza effect, can be investigated via proxies for sampling intensity and researcher effort (Maxwell et al., 2018). These proxies can be established from historical expedition archives; for future expeditions, sampling effort can be directly observed and recorded using new software applications.

For too long, the sparse hominin fossil record has been taken at face-value, enabling the proliferation of un-tested hypotheses relating to speciation, extinction and migration. This research will place geological and collection biases at the center of the discipline, resulting in a far more rigorous approach to hypothesis testing.

Faith, J. T. et al. (2021). Rethinking the ecological drivers of hominin evolution. Trends in Ecology & Evolution 36(9): 797-807.

Maxwell, S. J, Hopley, P. J., Upchurch, P., Soligo, C. (2018). Sporadic sampling, not climatic forcing, drives observed early hominin diversity, PNAS 115(19): 4891-4896.

Research themes
Project Specific Training

The student will receive one-to-one instruction in quantitative palaeobiology using R and field training in sedimentology and geological mapping. Training in archival research, museum collection management and software development will be provided by project partners, as required.

Potential Career Trajectory

This PhD project could lead to careers in museum management, environmental conservation, academic research or statistical analysis, amongst others.

Project supervisor/s
Philip Hopley
Natural Sciences
Birkbeck
p.hopley@bbk.ac.uk
Paul Upchurch
Earth Sciences
UCL
p.upchurch@ucl.ac.uk
Supervision balance
60:40