In wild animal societies, how do the costs (disease spread, competition) and benefits (healthy microbes, cooperation) of social connections operate over individuals’ lifetimes? Can individuals optimally position themselves within their social networks to maximise the benefits of social connections while minimising the costs? How is the overall structure of the society shaped by the social behaviour of individuals within them and the operation of social processes (e.g. contagions) upon them?
The potential importance of an individual’s social connections for their health and well-being is now widely recognised for social systems across the animal kingdom. Nevertheless, many important unanswered questions exist regarding exactly how sociality can govern individual’s health, especially in regards to which trade-offs might exist in terms of maximising the benefits of social connections while minimising the costs. In particular, an individual’s exposure to disease may depend on the same social settings that also determine their exposure to beneficial microbes fundamental for a healthy microbiome. But, how this trade-off is structured, and how individuals navigate this, remains almost entirely unknown, primarily because such questions require intense monitoring on individuals and their social associates across their entire lifespan.
Aims of the Project
This research will address the questions of health-related costs and benefits of individual’s sociality by drawing upon a unique long-term field study of red deer on the Isle of Rum, Scotland. Using data consisting of detailed ecological assessments, core long-term individual monitoring, and recent bio-sampling, the project will aim to: (1) understand how social processes operate within this system to provide both costs and benefits to individuals, (2) determine whether individuals can alter their own social network positions to optimize their health and fitness outcomes and (3) assess how social trade-offs shape individual-level behaviour and how this scales up to govern the arising architecture of the society.
Since the 1970s, this red deer study system has closely monitored the life history, health, and behaviour of individually-identifiable, pedigreed, individuals from birth and through their whole lives. Recently, using data on many thousands of red deer from this population in combination with year-round group censuses, we have shown that various aspects of these individuals’ lives, such as their fitness and ageing, depend on and shape their social networks. Furthermore, over the past 5 years a large effort in routine faecal sampling can now be used to provide complementary data on parasite infection levels and the gut microbiome health, both of which are likely to be closely linked to sociality and health in these wild ruminants. As such, this project will test how sociality predicts health and fitness at different life stages, and how early life environment and social conditions predict adult sociality and associated health outcomes. In addition, through fully utilising the collection of faecal samples and parasite counts, the trade-offs associated with variation in social behaviour can be directly assessed. For example, combining this unique data with analytical methods will allow us to disentangle how more social individuals suffer costs of increased risk of infection with parasites but may benefit from greater sharing of particular strains of beneficial gut microbes.
Methods to be used
The project will be primarily computational, with additional potential for engaging in further sample processing and analysis as well as core ecological data collection. More specifically, Dr Firth will be primarily responsible for technical training of computational biology skills, large data analyses and statistical approaches to ‘big data’ that will be needed for the conceptual learnings on how sociality influences health and fitness in real-world populations. Dr Knowles will be primarily responsible for technical training related to microbiology measurement and analysis and relevant laboratory skills training and guidance that will allow insights into microbiome and mammalian infection dynamics. Finally, the candidate will also be co-supervised by Prof Dan Nussey of Edinburgh University’s School of Biological Sciences. Prof Nussey will provide mentoring in gathering, handling and understanding the biological elements of ecological data (particularly ones which span individuals’ entire lifetime) which will be needed for gaining understanding of individual-level health and ageing within this data set.
Specialised skills required
Due to the intense analytical nature of the project, this research would be particularly suited to individuals with experience in the handling and the statistical analysis of large, highly detailed, datasets in the R programming environment. Further, having a strong biological knowledge of natural populations and associated data collection, as well as experience with processing and analyzing microbiome data, would be of benefit.
Please contact Josh Firth on firstname.lastname@example.org if you are interested in this project