Trees take in carbon from the atmosphere as they grow, but this is eventually released when they die. The sheer number of trees in tropical forests means that small changes in these rates of growth and death, and the resulting change in the balance of carbon taken in or released, can have a big effect on the climate. While a lot of research has focused on how changes in temperature and rainfall affects the growth and death of tropical forest trees, the potential effects of lightning have been largely neglected. A study tracking lightning strikes in Panama found that they caused more than half of all deaths of large trees, a previously undocumented effect despite being in one of the most intensively studied forests in the world. This project will provide important steps towards assessing whether this strong impact of lightning is a more widespread phenomenon. Forests in Africa are characterised by a greater dominance of large trees than elsewhere in the tropics, so based on results from Panama they would be expected to be more vulnerable to lightning. Alternatively, the high frequency of lightning in Africa may have selected for trees that are better able to withstand its effects. Knowing whether or not lightning has a consistent effect across continents is important for determining whether future work should focus on understanding the causes of variation in the impact of lightning, or can instead explore the wider implications these effects. The new international collaborator (Evan Gora) has developed an approach for detecting lightning damage from drone surveys and follow-up investigation on foot that allows large areas of forest to be surveyed. We will apply this at four sites along a dramatic gradient of lightning frequency in the Albertine Rift (on the boundary of the Democratic Republic of the Congo, Rwanda and Uganda) to (1) test whether trees at different sites in Africa are more or less vulnerable to being killed by lightning than those in Panama, (2) determine how forest structure varies with lightning frequency and (3) use these observations to assess the potential effect of lightning on carbon stocks and dynamics. The project team will have regular online meetings throughout the project, will all meet in Rwanda to receive training from Gora in how to detect lightning damage, and a subset of the team will also meet in the UK after fieldwork. Collectively, these meetings provide considerable space to share ideas as the project develops, culminating in a five-year plan for future collaboration. We will seek wider input from scientist and stakeholders through a regular series of seminars and roundtable discussions, and will hold online training workshops to build capacity in monitoring the effects of lightning on tropical forests.

Access to safe drinking water is centrally linked to public health, well-being and economic prosperity. Although water quality is strongly linked to many of the UN Sustainable Development Goals (SDG 6: Clean Water & Sanitation, 3: Good Health & Well-Being, 5: Gender Equality, and 2: Zero Hunger), there is still a long way to go to achieve equitable access to safe drinking water, particularly in the Global South. To accelerate progress, we need new interdisciplinary approaches to tackle complex water quality challenges, especially with increasing stressors like rapid urbanisation and climate change impacting groundwater resources widely used for drinking. The aim of my FLF is to create a roadmap towards improved groundwater quality management in the context of the Global South by bringing together systematic approaches to improve the understanding of dominant groundwater processes and to support evidence-based decision-making for effective groundwater remediation. We will develop and demonstrate this approach in relation to two selected contrasting locations in South Asia (e.g. Bihar, India) and East Africa (e.g. Uganda) and for selected priority groundwater contaminants relevant to those locations. The roadmap approach developed here could then be applied to different scenarios in the future. We will bring together expertise in groundwater pollution (e.g. chemical, microbial, emerging contaminants, antimicrobial resistance), (bio)geochemical processes, remediation technologies, machine learning, decision science (e.g. agent based modelling, multi-criteria decision analysis) and social science to address local water quality and remediation challenges in these two areas. We will co-design decision tools, iteratively integrating scientific data with modelled predictions, to enable informed, locally-relevant decision-making for effective groundwater remediation. We will address an integrated set of key objectives and hypothesis (see objectives) through a series of Workpackages (WP) implemented as: (i) WP 1: Field-based Investigations comprising of WP 1.1 Multipollutant & Process Investigation and WP 1.2 Community Science; (ii) WP 2: Lab-based Investigations comprising of WP 2.1: Water & Sediment Characterisation and WP 2.2 Remediation Evaluation; (iii) WP 3: Predictive Modelling comprising of WP 3.1 Machine Learning; WP 3.2 Agent Based Modelling; and WP 3.3 Multi-Criteria Decision Analysis; and (iv) WP 4: Synthesis & Communication comprising of WP 4.1 Stakeholder Engagement and WP 4.2 Open Resource Bank Development. Our project team brings together highly complementary expertise and skillsets. I am an environmental engineer with expertise in groundwater pollution and remediation, with substantial experience managing and implementing complex, multi-partner research projects in South/Southeast Asia, Africa and South America. I am joined by Co-Investigators from The University of Manchester, British Geological Survey, University of Birmingham and University of Bath, along with international Project Partners from University of Melbourne (Australia), KTH Royal Institute of Technology (Sweden), Mahavir Cancer Sansthan (India), University of Heidelberg (Germany), Mbarara University of Science and Technology (Uganda) and independent affiliates from India and Malaysia. Collectively we bring together decades of interdisciplinary expertise in water science, remediation, water management, water and health, biotechnology, decision science, social science, participatory science, stakeholder engagement and extensive local knowledge in India and East Africa. The results and tools generated will improve the understanding of the complex natural and anthropogenic processes impacting groundwater quality in the selected locations and will better enable evidence-based decision making for effective groundwater remediation, with the roadmap generated able to be applied to other scenarios in the future.