Research (PAGE IS INCOMPLETE)

Live Projects

Oppenheimer Programme in African Landscape Systems (OPALS)

The Oppenheimer Programme in African Landscape Systems (OPALS) at the University of Exeter conducts applied systems-focused research to support sustainable human–environment interactions across African landscapes. It empowers African researchers and partners to co-produce evidence-based solutions addressing climate change, land management, and socio-ecological resilience. OPALS integrates six thematic areas, including strengthening African environmental leadership, improving data representation in decision tools, enhancing rangeland monitoring, enabling access to nature and carbon finance, and informing climate adaptation in cities. It emphasises open science, partnership, and systems thinking to generate actionable insights that inform policy and practice for more sustainable, equitable landscapes. For more information, see the OPALS Website.

Relative Productivity Index

Our research on the Relative Productivity Index is transforming rangeland health monitoring and evaluation of management effectiveness (Lomax et al. 2025, In Review). The framework applies machine learning with dynamic spatial and temporal data to estimate potential photosynthetic productivity and benchmark it against satellite-observed outcomes. This enables productivity shortfalls attributable to local management, particularly herbivory, to be isolated and assessed. The approach convincingly outperforms existing tools that underpin hundreds of studies and major global investments. We are now scaling delivery towards a global product, with the framework being applied and refined across multiple regional contexts (Mureithi et al., In Prep).

Understanding and Conserving Tropical Rainforests

Our research supporting the understanding and conservation of Tropical Rainforests integrates remote sensing, field data, and advanced analytical methods to improve monitoring of forest structure, degradation, and function. Work led by Bri Pickstone, a former MSc student, developed canopy height models for the Katingan landscape, demonstrating how spaceborne and airborne data can robustly characterise tropical forest structure (Pickstone et al. 2025). Complementing this, Emily Doyle’s PhD research explored the use of GEDI observations to define a forest degradation continuum, drawing on fine-resolution Cautario LiDAR to link satellite metrics with on-the-ground structural change (Doyle et al. 2025). Building on the Cautario collaboration, Jess Thomas is actively developing her PhD chapters on relationships between soil organic carbon, forest structure, and near-surface microclimates. In parallel, work led by Guy Lomax, tests synthetic control methodologies for assessing deforestation monitoring approaches. These activities are closely aligned with our industry collaborators at Permian and Belian.Earth, reflecting productive and dynamic partnerships.

PREDICT: Predicting Resilience and Early Detection of Impending Climate Transitions

PREDICT is advancing our ability to anticipate and understand major transitions in the Earth system. This project develops methods to detect early warning signals of climate tipping points using Earth observation data. Our team is led by the University of Exeter in partnership with the University of Leicester and UK Centre for Ecology and Hydrology, and is creating new methodologies for tipping point detection, analyse critical case studies, and share scientific insights. PREDICT is a three-year project funded by ESA’s CLIMATE-SPACE programme.

Former Projects

DRIVING-C: Do dryland ecosystems control variability and recent trends in the land CO2 sink?

The NERC-funded DRIVING-C project, led by the University of Exeter, aimed to reduce uncertainties in understanding terrestrial carbon cycle processes by integrating field data with ecosystem modelling. It focused on improving estimates of carbon stocks and fluxes in dryland and vegetated ecosystems, where existing dynamic global vegetation models showed high uncertainty. The DRIVING-C team combined multi-scale observations, including drone photogrammetry (Cunliffe et al., 2020, 2022; McIntire et al., 2022), eddy covariance measurements (Cunliffe et al., 2022; Zhu et al., 2023), and satellite remote sensing (Slade et al., 2023) across a range of field sites to quantify above-ground biomass and carbon dynamics. By linking empirical measurements with model simulations (Fawcett and Cunliffe et al., 2022), the project constrained key model parameters and improved predictions of ecosystem carbon responses to environmental change, increasing confidence in projections of the global carbon cycle under future climate scenarios.

Climate as a driver of shrub expansion and tundra greening

The NERC-funded Shrub Tundra project, led by Isla Myers-Smith at the University of Edinburgh, investigated how climate change drove shrub expansion and greening across Arctic and alpine tundra ecosystems. It quantified rates of shrub canopy increase, identified climate drivers of growth, and assessed how plot-scale vegetation change corresponded with remotely sensed greening trends across the tundra biome. Our team combined biome-wide data synthesis (Myers-Smith et al., 2020) with detailed field measurements at sites such as Qikiqtaruk–Herschel Island to test predictions of vegetation responses to warming (Myers-Smith et al., 2019; Assmann et al., 2018, 2020; Cunliffe et al., 2019, 2020). Results demonstrated that rising temperatures and altered environmental conditions were associated with increased shrub cover and changes in plant community structure and decomposition rates (Galloise et al., 2023), improving understanding of tundra vegetation dynamics under recent climate warming and informing projections of future ecosystem change.