YES-27-E-01: QUANTIFYING HABITABILITY WITH A MORE-THAN-HUMAN LENS. Exploring Positive Feedbacks between Ecosystem Health and Societal Wellbeing with a Knowledge Graph Approach.

What if ecological flourishing and societal wellbeing are locked together in a virtuous cycle, and we could map, model, and quantify it? This project offers an exciting opportunity to build a Knowledge Graph that connects ecological flourishing with societal wellbeing and reveals the complex, non linear positive feedback loops that link them. The aim is to show how restoring ecosystems can improve human wellbeing and how improved wellbeing can, in turn, drive values, behaviours, and institutions that support further restoration.

Real world examples show why this matters. River valley parks in Edmonton and Valencia illustrate how restoration can create virtuous cycles. Edmonton’s Ribbon of Green transformed the North Saskatchewan River Valley into biodiversity corridors and community spaces that support physical activity, psychological wellbeing, social connection, and community gathering, helping to sustain public investment and engagement. In Valencia, the Turia Garden was created after a citizen led movement pushed authorities to replace a planned motorway with an 8 km park; it now supports urban biodiversity and provides recreation for millions, generating civic pride that helps maintain its quality. These cases suggest that strategic restoration investments can be self amplifying: initial improvements in wellbeing can generate further support for regeneration. The project will help identify the conditions under which such loops emerge.

You will work at the interface of social ecological systems science, complex systems, data science, and policy. Rather than treating environmental and social data as separate silos, you will help design and build a knowledge graph that integrates heterogeneous evidence, including biodiversity and ecosystem health, human wellbeing and inequality, governance, and cross scale exposures, so that we can trace causal mechanisms, identify tipping points and leverage points, and explore scenarios through linked models. The project is methodologically ambitious but highly structured: you will learn to turn messy, multi source data into a transparent, queryable, open source framework for assessing habitability.

A particular strength of the project is its empirical anchor: Born in Bradford, a cohort established in part in 2007 to examine how environmental factors affect health and wellbeing. This gives the project a real world, place based living lab in which to test how green infrastructure, biodiversity, and nature based solutions shape habitability for both human and non human communities, and where synergies and feedback loops between ecological restoration and wellbeing can be examined empirically.

This project is ideal for a student who wants to combine data science and knowledge engineering with environmental and health research, and who is excited by big, interdisciplinary questions. You will gain skills in knowledge graph construction, causal and systems modelling, cross scale analysis, and policy relevant evidence synthesis, while contributing to an open source framework designed to inform strategic restoration investments that reduce inequality and enhance both ecological and human wellbeing.