Fusing ecology and evolution with animal health.
“Academia was never the intended plan,” says Professor Dan Haydon, but after becoming obsessively interested in ecological stability and its relationship to complexity as an undergraduate at Southampton, and following a key intervention by a watchful mentor, the career plan changed from fish-farming to theoretical ecology and a PhD with Eric Pianka at the University of Texas.
“Twelve post-doctoral years later after moving back and forth between North American institutions (where the focus was always ecological) and UK universities (where the focus seemed to be the latest epidemiological disaster to befall us – BSE, foot and mouth disease …) I settled here in Glasgow, which is really a personal ideal for me,” he says. “A strong interdisciplinary and collaborative environment, wonderful access to coastal and highland environments, and a lively and friendly city.
“I work as a quantitative ecologist on a wide range of spatial and temporal dynamical processes, always in close collaboration with experienced teams familiar with the biology of a system. This has generated a wealth of fascinating collaborations focused on a wide range of topics including population dynamics of grouse and hares, movement of elk and seabirds, the dispersal of lichens; managing infectious diseases in Ethiopian wolves and domestic dogs, brucellosis in cattle, and FMDV (foot and mouth disease virus) in different parts of the world, new ways of analysing habitat use and movement data, serological data, and thinking about antimicrobial resistance, and infection reservoirs. Underpinning all this work is the need to find new ways to link available data to tractable models.
Disciplinary transformation
“It is increasingly obvious that the most interesting and important contemporary problems require interdisciplinary approaches with effective teamwork and partnership nationally and internationally. Ecological and epidemiological modelling has undergone a transformation from the 1970s and 80s when theoreticians would churn out models, and rather optimistically challenge empiricists to parameterize them, to today’s approach where the models are co-designed with empiricists to facilitate engagement with obtainable data.
“The development of state-space models that bridge between ‘unobservable’ biological process, and manifest observable data is an exciting but technically challenging research area that requires a new generation of quantitatively minded ecologists and epidemiologists, and Scotland and the UK more generally is in the vanguard of this disciplinary transformation.
One Health
“As I have worked alongside these changes my interests have evolved along previously travelled pathways leading from purely theoretical considerations of higher-dimensional systems, to more tractable lower dimensional data rich(er) problems that are often epidemiological – and more recently into research management and policy considerations.
“I have spent much of the last 12 years leading a department that is seeking to fuse the traditional bastions of ecology and evolution with animal health and veterinary science, with a focus around One Health, and this has led to the formation of a unique new School of Biodiversity, One Health and Veterinary Medicine here at the University of Glasgow.”
Dan Haydon is the Director of the Glasgow Centre for International Development at the University of Glasgow, former Director of the Institute of Biodiversity, Animal Health and Comparative Medicine, and Boyd Orr Centre of Population and Ecosystem Health, and Scientific Advisor to Nature Scot. He is a Fellow of the Royal Society of Edinburgh. Find out more here.
This post is part of a series showcasing Scotland’s innovative, high-impact research supporting biodiversity conservation, in partnership with Scottish Government and NatureScot. Read the rest of the series here.
Further reading
Cattadori, I.M., et al. 2005. Parasites and climate synchronize red grouse populations. Nature 433: 737—741. https://doi.org/10.1038/nature03276
Haydon, D.T., et al. 2006. Low-coverage vaccination strategies for the conservation of endangered species. Nature 443: 692—695. https://doi.org/10.1038/nature05177
Mather, A.E., et al. 2013. Distinguishable epidemics of multidrug resistant Salmonella Typhimurium DT104 in different hosts. Science 341: 1514—1517. https://doi.org/10.1126/science.1240578
Viana, M., et al. 2014. Assembling evidence for identifying reservoirs of infection. Trends in Ecology and Evolution 29: 270—279. https://doi.org/10.1016/j.tree.2014.03.002
Matthiopoulos, J., et al. 2015. Establishing the link between habitat-selection and animal population dynamics. Ecological Monographs 85: 413—436. https://doi.org/10.1890/14-2244.1
Halliday, J.E.B., et al. 2017. Driving improvements in emerging disease surveillance through locally-relevant capacity strengthening. Science 357(6347): 146—148. https://doi.org/10.1126/science.aam8332
Eaton, S., et al. 2018. Adding small species to the big picture: Species distribution modelling in an age of landscape scale conservation. Biological Conservation 217: 251—258. https://doi.org/10.1016/j.biocon.2017.11.012
Jarrett, C., et al. 2022. Integration of mark-recapture and acoustic detections for unbiased population estimation in animal communities. Ecology 103(10): e3769. https://doi.org/10.1002/ecy.3769