Research topic

Modelling community turnover, invasibility and impacts to safeguard biodiversity.

Host

Mathematical Biosciences Hub

Department of Mathematical Sciences, Stellenbosch University, South Africa

Remuneration

R 220 000 p.a. x 3 years (ZAR)

Project start date

August 2023

A competitive PhD position is open for a student with a background or interest in ecology, applied mathematics, biodiversity informatics, ecological modelling, computer and/or information science. Funded through the EU Horizon project, Biodiversity Building Blocks for Policy (B3) (https://cordis.europa.eu/ project/id/101059592), the PhD candidate will focus on assemblage-level ecological community responses to global change challenges from biological invasions in both South Africa and beyond. With the concern over global biodiversity declines mounting, a biodiversity data pipeline is urgently needed to meet the needs of diverse stakeholders and policy makers (DOI:10.1016/ j.biocon.2022.109736). The successful candidate will therefore also work closely with a multidisciplinary team within the B3 project to design data cubes – a computationally efficient means of processes large volumes of biodiversity data (e.g. from Global Biodiversity Information Facility, GBIF) through a cloud computing environment. The overarching aim is to develop real-time and on-demand queries with products of species turnover, community invasibility, and indicators of alien impacts that can facilitate regional and international conservation policy making. In this project, species turnover will be analysed using dissimilarity modelling of zeta diversity (DOI:10.1086/678125); invasibility estimated for ecological communities and networks with trait-mediated interactions (DOI:10.1007/s10530-021-02484-w); and indicators and metrics of alien impacts designed to track and monitor biodiversity change at timescales relevant to policy makers (DOI:10.1093/biosci/biu193). The project will be supervised by the Stellenbosch team of the B3 project, in collaboration with 12 other international teams, to deliver Information Technology solutions to improve and implement statistical and mathematical models for biodiversity monitoring.

Prospective students, to send an expression of interest and full CV to Hanlie by 05 June 2023.