Bi-directionality in host-parasite interactions : impacts of host community structure on parasite infestation and consequences of tick traits on host specificity
Keywords: Biology.

Host-parasite interactions have far-reaching consequences for the health of Earth's living organisms. Although the negative impacts of parasites on their hosts have been well-studied, especially for those that cause disease in humans, the mechanisms of how host communities influence their parasites has been relatively understudied. Feedback between these bi-directional relationships, which are critical to the understanding of host and parasite ecology as well as human health, have been a neglected field of study. To investigate the impacts of mammalian hosts on their ectoparasites, I utilized a long-term ecological research site which segregated habitat between ectoparasite hosts, jackrabbits and a rodent community dominated by kangaroo rats (Dipodomys spp.). A specialist tick species (Dermacentor parumapertus) and a flea community dominated by a generalist species responded differently to spatial segregation of their hosts. With the removal of their primary hosts from study plots, ticks were also absent. Infestation on rodents by generalist fleas was unaffected by the removal of kangaroo rats and was instead more affected by differences between individual rodent host species. Increased habitat segregation between kangaroo rats and jackrabbits, the primary hosts for D. parumapertus, significantly decreased tick infestation on kangaroo rats. Next, I quantified habitat overlap between jackrabbits and cottontails by comparing two survey methods: fecal pellet surveys and camera trapping. I found that the quantification of sympatry, or spatial co-occurrence between the two focal species, was comparable between the two survey techniques. The results of this project have implications for the use of camera trapping in monitoring the activity of highly mobile animal species. For a broad perspective of how parasite traits can affect their host species, I compiled a comprehensive database on the morphological characteristics, mammalian host species, and geographic range of Dermacentor tick species, a disease-vectoring genus. I used a machine learning technique, generalized boosted regression, to determine which species traits are most influential to determine whether a given tick species vectors zoonotic diseases, as well as predict which understudied tick species are most likely to be yet-undiscovered disease vectors. The number of mammalian host families a Dermacentor tick species is known to infest was the top predictor variable in my model, followed by the size of its geographic range and the body size of adult male ticks. I hypothesize that there is a positive feedback loop between the traits profiles associated with zoonotic vector species. For example, when a tick species can survive in a wide variety of environmental conditions, and occurs in a large geographic range, it is likely to encounter more mammalian host species. These host species are mobile and can further expand the geographic distribution of the tick species by helping it disperse into new environments. I found that not only do the traits of parasites affect their ability to infect host species, but that host community traits can in turn affect their parasites and are therefore both critical components of the study of host-parasite interactions in an ecological context. Given the detrimental effects parasites and pathogens have on humans and other animals, this work emphasizes the need to take a more holistic and mechanistic approach to the study of bi-directionality in host-parasite interactions