Transmission pathways in reptile ticks

Author: Caroline Wohlfeil

  • Thesis download: available for open access on 19 Jan 2019.

Wohlfeil, Caroline, 2017 Transmission pathways in reptile ticks, Flinders University, School of Biological Sciences

This electronic version is made publicly available by Flinders University in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exceptions. If you are the owner of any included third party copyright material and/or you believe that any material has been made available without permission of the copyright owner please contact with the details.


Understanding how parasites are transmitted through a population is fundamental to the understanding of the spread of wildlife diseases. Emerging threats to wildlife species include both exotic and new endemic diseases. Coupled with the spread of diseases are new paradigms due to habitat restrictions where a local outbreak of a pathogen may have greater relative impact than in other less restricted areas. Another route which is increased by restricted habitats is the spill over of previously benign parasites from other species. There are serious human health concerns from exposure to pathogens from wildlife as a result of the increased frequency of interactions between humans and wildlife. The main aim of this study is to investigate the pathways of reptile tick transmission, by utilising GPS data collected in the lizard activity season (Sept-Dec) over four years (2008-2011) to create social networks of the Sleepy lizard (Tiliqua rugosa) host and genotypes of the reptile tick, Bothriocroton hydrosauri. Initially this study explored the ability that transmission network models had on predicting parasite loads. Creating, transmission networks derived from the infection windows of the tick species, Bothriocroton hydrosauri and Amblyomma limbatum, among their sleepy lizard (Tiliqua rugosa) hosts in a natural population in South Australia. The consistent correlations over time between B. hydrosauri infection intensity and network derived infection risk suggest that network models can be robust to environmental variation among years. However, the contrasting lack of consistent correlation in A. limbatum suggests that the utility of the same network models may depend on the specific biology of a parasite species. The second part of this study was to develop new diagnostic microsatellite DNA loci for the reptile tick, Bothriocroton hydrosauri using next generation sequencing. I used the alleles I identified to assign adult ticks collected in 2010 and 2011 to either the background wild population at the study site, or to larvae from other locations experimentally attached in pulses to lizards at the study site. For the adult ticks identified as background, I asked whether ticks were more closely related to each other on hosts that were more closely linked in a parasite transmission network. Then also asked which of three alternative network structures best explained the patterns of genetic relatedness. The three network models were social, asynchronous refuge sharing and spatial proximity. I found that adult ticks were more related to each other when they were collected from the same host, than when collected from different hosts. I also established that when adult ticks were on different lizards they had higher relatedness if those lizards had shorter path lengths connecting them on each of the three networks we explored. In each of the two study years a different network best explained the dynamics of transmission. The social contact network was the poorest predictor of tick relatedness in both years, while the spatial overlap based network (in one year) and the asynchronous shared refuges network (in the other year) were the strongest predictors. Lastly, this study investigates which transmission pathway model could best explain the likelihood that a lizard receives a tick from a donor lizard. Using the tick samples identified as originating from experimental infection pulses and Exponential random graph models (ERGMs). My major discovery with this section was that in each year a different model was the best predicator. In 2010 the transmission network (adjacency and distance) was the best predictor and in 2011 it was a model of the social network distance between lizard pairs. My study highlights, that changing environmental conditions might vary the relative importance of alternative processes driving the parasite transmission dynamics. This could lead to further studies specifically investigating the effects and influence that the environment has on host behaviors, in turn extending our understanding on parasite transmission. There were limitations in my study due to limited genetic markers and further work would benefit from utilizing newer genomic techniques to trace pulses of tick progeny in social networks within this amenable study system.

Keywords: lizard, tick, social network, parasite transmission, Bothriocroton hydrosauri, genetics
Subject: Biological Sciences thesis

Thesis type: Doctor of Philosophy
Completed: 2017
School: School of Biological Sciences
Supervisor: Assoc. Prof. Mike Gardner