Using mathematical models to understand the impact of climate change on tick-borne infections across Scotland

Ticks are of global interest as the pathogens they spread can cause diseases that are of importance to both human health and economies. In Scotland, the most populous tick species is the sheep tick Ixodes ricinus, which is the vector of pathogens causing diseases such as Lyme borreliosis and Louping-ill. Recently, both the density and spread of I. ricinus ticks have grown across much of Europe, including Scotland, increasing disease risk. Due to the nature of the tick lifecycle they are particularly dependent on environmental factors, including temperature and habitat type. Because of this, the recent increase in tick-borne disease risk is believed to be linked to climate change. Many mathematical models have been used to explore the interactions between ticks and factors within their environments; this thesis begins by presenting a thorough review of previous modelling of tick and tick-borne pathogen dynamics, identifying current knowledge gaps. The main body of this thesis introduces an original mathematical modelling framework with the aim to further our understanding of the impact of climate change on tick-borne disease risk. This modelling framework takes into account how key environmental factors influence the I. ricinus lifecycle, and is used to create predictions of how I. ricinus density and disease risk will change across Scotland under future climate warming scenarios. These predictions are mapped using Geographical Information System software to give a clear spatial representation of the model predictions. It was found that as temperatures increase, so to do I. ricinus densities, as well as Louping-ill and Lyme borreliosis risk. These results give a strong indication of the disease risk implications of any changes to the Scottish environment, and so have the potential to inform policy-making. Additionally, the models identify areas of possible future research

Past and future perspectives on mathematical models of tick-borne pathogens

Ticks are vectors of pathogens which are important both with respect to human health and economically. They have a complex lifecycle requiring several blood meals throughout their life. These blood meals take place on different individual hosts and potentially on different host species. Their lifecycle is also dependent on environmental conditions such as the temperature and habitat type. Mathematical models have been used for the more than 30 years to help us understand how tick dynamics are dependent on these environmental factors and host availability. In this paper we review models of tick dynamics and summarise the main results. This summary is split into two parts, one which looks at tick dynamics and one which looks at tick borne-pathogens. In general, the models of tick dynamics are used to determine when the peak in tick densities is likely to occur in the year and how that changes with environmental conditions. The models of tick borne pathogens focus more on the conditions under which the pathogen can persist and how host population densities might be manipulated to control these pathogens. In the final section of the paper we identify gaps in the current knowledge and future modelling approaches

Techniques for evaluating the spatial behaviour of river fish

Radio-tagging is widely used for studies of movements, resource use and demography of land vertebrates, with potential to combine such data for predictive modelling of populations from individuals. Such modelling requires standard measures of individual space use, for combination with data on resources, survival, dispersal and breeding. This paper describes how protocols for efficient collection of space-use data can be developed during a pilot study, and reviews the ways in which such data can be used for space-use indices that help answer biological questions, with examples from a study of riverine pike (Esox lucius). Analyses of diurnal activity and spatio-temporal correlation were used to assess when to record locations, and analyses of home range increments were used to define the number of location records necessary to assess seasonal ranges. We stress the importance of developing protocols that use minimal numbers of locations from each individual, so that analyses can be based on samples of many individuals. The efficacy of link-distance (e.g. cluster analysis) and location density (e.g. contouring) techniques for spatial analysis for river fish were compared, and the utility of clipping off areas to river banks was assessed. In addition, a new automated analysis was used to estimate distances along river mid-lines. These techniques made it possible to quantify interactions between individuals and their habitat: including a significant increase in core range size during floods, significant preference for deep pools, and a lack of exclusive territories