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Jayne was a land use policy researcher at SRUC but now works at Uppsala University.
Sheena is the theme coordinator for Theme 2: Productive and Sustainable Land Management and Rural Economies.
Dave Miller is a GIS Specialist with 10 years' experience in interdisciplinary research in support of a wide variety of research objectives for Scottish Government, EU, and other funding bodies (for example, SRUC, BNSC-FC). Dave's principal role is as a GIS Specialist embedded within a multi-disciplinary team focusing on sustainable land use systems, climate change and agricultural policy issues.
To advance our knowledge of how to improve disease control strategies through epidemiological and socio-economic approaches. This includes research into the spread of important, targeted, endemic pathogens and antimicrobial resistance (AMR) via livestock and the environment including transmission of such pathogens to humans. In order to achieve this, we will more specifically: analyse existing, large data sets to improve knowledge of the threat of disease incursion and to aid the rapid detection of endemic livestock diseases. investigate new strategies for disease control and investigate two
The aim of research deliverable is to explore the uptake of practices which improve the efficiency, productivity and sustainability of land, crop and livestock management throughout Scotland. The research builds on previous work within the RESAS Strategic Programme and on collaborations with UK and international partners.
The key aims and drivers of this research are: Trade-offs in livestock systems. There is a need to understand how best to improve the production, economic and wider environmental resilience and sustainability of upland sheep systems which cover over 60% of farmed land in Scotland. This project has established two alternative Precision Livestock Farming (PLF)-based upland sheep systems and is subsequently comparing and contrasting the overall sustainability of the systems. Sustainability metrics being assessed include a focus on environmental implications (e.g. above and below ground carbon
This RD will involve the development of tools and strategies to promote the increased use of data from across agricultural supply chains and industry networks, for management and feedback, in order to improve efficiency across the agri-food industry. We will focus on developing methodologies to help quantify and communicate the uncertainties resulting from pooling data across the supply chain. We will develop crop and livestock case studies building links with RDs 2.3.9 & 2.4.1 (barley) and WP2.2 & 2.4 (beef supply chains). We will work with cattle industry data to identify data that could be
The aim of this research is to develop integrated management systems to enhance economic and environmental sustainability in agriculture, focusing on two production systems: arable and ruminant livestock. First, new technologies and management strategies rom existing research and linked RDs (primarily 2.1.6, 2.1.8, 2.3.4, 2.3.8) will be reviewed to identify state-of-the-art best practice options. These will then be combined into a set of integrated management systems, applied in four case studies: animal mounted sensors for the detection of parturition in beef cattle; targeted selective