Medicinal Plants Entering Trade: Local Use to Global Impact (PhD Opportunity) University of Reading in United Kingdom

This PhD opportunity, hosted at the University of Reading within the AI-INTERVENE department, explores the global and local impact of medicinal plants entering trade. The medicinal plant trade is a multi-billion-dollar industry, but unsustainable harvesting practices have led to the decimation of wild populations and local extinctions. While some medicinal plants are traded globally for their high value, others remain accessible within local communities, guided by traditional knowledge. This project aims to systematically categorize the local and global significance of medicinal plants and test hypotheses about the drivers of globalization in this sector.

Central to the research is the integration of ethnobotanical survey data, which provides rich insights into the use of plants in local communities and markets. Historically, identifying relevant publications and extracting usable data has been a major bottleneck due to the extensive time and effort required. However, recent advances in AI-driven text mining now make it feasible to integrate these dispersed data sources into comprehensive global analyses. The project will use AI methods to identify publications that record locally-used or locally-sold plants and extract plant species names and associated data from these sources.

The research will build a comprehensive body of literature, targeting publications never before analyzed in this way. There is currently no global bibliometric analysis of ethnobotanical studies describing medicinal plant uses. Previous surveys, such as one for Brazil, identified hundreds of relevant articles, suggesting that thousands could be found globally using AI methods. For urban market ethnobotany, a global study using conventional search strategies identified 170 publications, which will serve as training sets for deeper searches. The project will compare compiled species lists to global lists of internationally-traded medicinal plants from sources such as MPNS, CITES, IUCN, FAO, and international trade statistics, revealing the subset of locally-used medicinal species entering international trade.

Key hypotheses to be tested include whether species in trade represent a phylogenetically and geographically non-random subset of medicinal plants, and what characteristics enable certain species to transition from local use to global trade. The project offers a comprehensive training programme, including applied AI, biodiversity, and transferable professional and research skills. A placement with an AI-INTERVENE project partner (3-18 months) is included, and the student will have opportunities to present at national and international conferences, positioning them at the forefront of the discipline and enhancing future employment prospects.

Applicants should have a degree in data science or a biological science with a focus on managing and analyzing biodiversity information. The funding is subject to a competition, with UKRI funding covering Home fees only; international students must pay the difference between International and Home fees. The application deadline is January 19, 2026. For more information and to apply, visit the project page on FindAPhD.