Life Sciences PhD Biology Studentship (2020)
Type of award
Exploitation of wild species globally: exploiting the internet for data
Biological diversity continues to decline, with direct exploitation identified as the second most important cause of observed changes in terrestrial biodiversity. Exploitation of living biomass has increased over 3-fold between 1970s and today and looks set to increase.
Despite the pressure posed by exploitation, quantitative studies of the exploitation of terrestrial wild species have until now been conducted at site level, e.g. individual settlements or protected areas. Without quantitative information on the distribution and magnitude of exploitation of terrestrial wild species, assessment of the importance of exploitation and guiding conservation actions, such as regulation of hunting, is impossible. Furthermore, exploitation likely impacts human wellbeing by disrupting ecosystem functions, e.g. the removal of seed dispersers affecting forest regeneration.
Combining datasets collated over the last few years by Scharlemann for Africa with text analysis tools developed by Weeds, we can offer a PhD project that will produce the first comprehensive global maps of the distribution and magnitude of exploitation of terrestrial and freshwater wild species. A challenge is finding the data in peer-reviewed and grey literatures, which will be overcome by using text analysis tools. These tools combine statistical methods to identify key words and phrases of interest in papers known to be relevant; machine translation to translate key words and phrases into other languages of interest; web-scraping technology to pull back from the internet more documents containing various combinations of key words and phrases and/or their translations; semi-automatic text classification algorithms to filter and categorise the identified documents; and multi-lingual named entity recognition techniques to identify portions of documents with relevant information.
Collected data will be analysed using spatial modelling techniques, ancillary datasets and GIS to identify drivers of global exploitation, and map the human exploitation ‘footprint’. Analyses will be performed at local to global scales. Further, predictions of future exploitation pressure and which species may be affected will be modelled.
This School funded position covers Home / EU tuition fees and a stipend at standard UKRI rates.
Ideal candidates will have a strong background in ecology with experience in data science including statistical analysis and programming (python preferred); or a strong background in computer science with experience in ecology. Eligible applicants will have recently received an MSc and/or a First or high 2:1 BSc in a relevant subject. Candidates for whom English is not their first language will require an IELTS score of 6.5 overall, with not less than 6.0 in any section.
Deadline30 March 2020 23:45 (GMT)
How to apply
Please submit a formal application using our online application system at http://www.sussex.ac.uk/study/phd/apply, including a CV, degree transcripts and certificates, statement of interest and names of two academic referees.
On the application system use Programme of Study – PhD Biology.
Please make sure you include the project title under Funding Information, the Supervisor’s name and a statement of interest on the application form.
Deadline: 30 March, interviews w/c 6 April 2020
Contact Emma Chorley for application enquiries (email@example.com)
Contact Jörn Scharlemann (firstname.lastname@example.org) and Julie Weeds (email@example.com) for enquiries about the project.
30 March 2020 23:45 (GMT)
the deadline has now expired
The award is available to people from these specific countries: