Research

Working with public and private data sources, we are developing new systems to integrate data to help develop, test and identify implementation routes for national level livestock improvement tools.  

This project considers the effect of the COVID-19 pandemic on dietary behaviours and impacts on health and well-being in Scotland using information from a large household survey. We focus on whether people changed how much fruit and vegetables they ate, how much alcohol they drank, and whether they worried more about buying healthy food. We also assess whether mental health and overall life satisfaction changed, and whether that affected diet. 

This project consists of an analysis of the Scottish demand for fruits and vegetables to help produce a detailed set of scenarios and recommendations about the scope and potential value of increasing soft fruit and vegetable production in Scotland. We are addressing topics such as: consumers' willingness to buy products out of season, consumers' interest on alternative to supermarkets retailing models, consumers' provenance preferences, and interest in plant-based products.

Building on data driven approaches in this and other themes, we explore how new data analysis approaches can be used to develop new understand in livestock performance and sustainability of livestock systems. Techniques will include exploring the use of machine learning to help integrate data sources across our livestock food chains.

The most pressing societal challenges of the first half of the 21st century, including climate change, the biodiversity crisis and building a restorative economy, are systems challenges. To solve them requires understanding and quantification of how key systems respond to both global change and local responses.

This project maps major food supply chains both within Scotland and those where Scottish industries are heavily involved to improve our understanding of how hey operate. To achieve this aim, we propose a methodology to be able to update changes in the maps, a modelled analysis of individual sectors that demonstrates where value is created, added, and lost during the supply chain, and to use the modelled analysis to simulate various scenarios whereby the value in the supply chain could be increased and distributed in Scotland among producers and processors. 

This project is modelling scenarios of alternative livestock futures for Scotland and identifying appropriate improvement tools to get there considering policy and sustainability of the transition paths.

This project is developing better targeted greenhouse has policies and industry initiatives, thus contributing to achieving Scotland’s net zero goal and reductions in the emissions intensity of Scottish food commodities. It combines scientific modelling and national scale data to improve the prediction of future greenhouse gas emission reduction scenarios in agricultural production, the cost-effectiveness of solutions and their wider environmental impacts. The specific focus of the project is ruminant systems, given their importance in Scottish agriculture, however, the tools and analyses will be embedded in the overall Scottish agriculture and include the wider resources used on livestock farms in Scotland as well. 

This project is increasing our understanding of the impacts of land-based funding mechanisms on land values, and related outcomes for landownership diversification and land use change. The project incorporates regional case studies and qualitative, quantitative and spatial analysis methods. It provides recommendations for policy interventions and land-based funding models which are aligned with both land use and land reform policy.

This project applies different modelling approaches to assess opportunities and impacts of land use in Scotland. Synergies and conflicts in land use policy are explored to identify how multiple objectives can be achieved. The greenhouse gas inventory is being disaggregated to holding level to identify hotspots for emissions and mitigation potential. Farm business models are scaled up to regional levels to identify patterns of responses to policy and management change. And, natural capital is modelled spatially to explore ecosystem service supply and opportunities.