Conclusion: Ticks Are Too Interesting for Just One Summer

It is time to say my final hello! Here is my conclusion post for my 2019 summer research. It has been an exciting time full of hiking, biking, reading, number-crunching, and, most importantly, ticks. I’ve talked a lot about my results in the last two posts, but as any good conclusion to a scientific study does, I wanted to dive into why I think I got the results I did and suggest future directions for my study. I also wanted to take some time on reflect what I’ve learned over the summer by taking on this project.

First, I wanted to return to my second post. This one talked about temporal variation—the patterns that we’ve seen in the tick population over the years and during 2019.

I predicted that we would have noticed an increase in ticks over our study period. It turns out this wasn’t true. As I mentioned earlier, the expansion of Lyme disease that inspired this line of thought was actually concentrated closer to Roanoke—maybe if we were to sample there, we actually would see an increase in ticks. I also read a paper that to some degree discredited the model I referred to in my original thinking as well. Apparently, a lot of models that try to predict risk of encountering ticks fall victim to using collinear variables (Estrada-Peña, Estrada-Sánchez, and Estrada-Sánchez, 2015). Collinear variables are variables that are correlated with each other (for example, temperature and elevation). Sometimes, models will be forced to choose between two explanatory variables that are collinear, and they will choose the one that fits the data best. However, what fits the data best is not always the best biological or ecological explanation for the trend. The authors directly state that altitude, a key variable in Diuk-Wasser’s model, is a bad covariate because many climatic patterns are collinear with changes in altitude. This might mean that eastern Virginia isn’t as suitable for ticks as Diuk-Wasser suggested. Another possible explanation that I thought of is an increase in Lyme disease cases does not automatically mean there is an increase in the tick population. There could be other drivers for this increase—perhaps there are fewer available hosts for ticks to latch onto as a result of habitat fragmentation, meaning that the likelihood that an uninfected tick feeds on an infected host goes up.

After meeting again with my advisor, we decided to leave seasonal variation off of my poster. I had so much else to say, it was too crowded! I didn’t want to leave you hanging, so here are my thoughts. I found it interesting that there was no seasonal difference in tick activity. Although I predicted that there would be a difference since spring is usually cooler than summer in the ‘Burg, I am not surprised since most of our sampling occurred in May, which isn’t that much cooler than June. I also found a paper that studied seasonal activity in black-legged ticks in the Southeast, which is apparently wildly variable (Ogden et al., 2018). Some states saw peaks in nymphs in early spring, while others (like our not-too-far neighbor, North Carolina) saw a peak in the fall. Perhaps we missed the peak of activity altogether, and there was no significant difference because we sampled primarily in the off-season. We could expand our sampling effort even further, but it was difficult to consistently sample during the school year.

On to spatial variation.

I hypothesized that ticks would be encountered more often in forested areas versus grassy areas because they would be more likely to find hosts there. I didn’t really have the tools to evaluate that claim specifically (although I will later), but I do think that I was right in thinking that being able to find hosts is a key factor. Many of the sites where we saw ticks at higher rates or saw a higher number of ticks tended to be in suburban areas, where forests are more fragmented. It turns out that the black-legged tick’s primary host, Peromyscus leucopus (the white-footed mouse), can thrive in fragmented forests (Allan, Keesing, and Ostfeld, 2003). Suburban patches also tend to be more isolated from one another, and a separate study found that higher patch isolation is associated with higher tick densities (Brownstein et al., 2005). I definitely plan to look further into why we find ticks where we do as I expand upon this study. It is also important to note that no individual plot had significantly more ticks or a significantly higher rate of collection. This also suggests the major influence that hosts have on tick presence—whether a site is colonized or the population there goes extinct is extremely dependent on the availability of hosts.

I’ve really enjoyed the work that I’ve done over the summer, and I have several ideas of how I can carry it further into my college career. For example, I can start using GIS to answer some of my questions. Conveniently, I’m taking GIS for Biologists this semester. I think after taking that class, I’ll be able to better account for land cover type and the effect of habitat fragmentation on tick abundance. I would also like to continue my analysis of questions from this summer that I couldn’t get to—namely, those about temperature, humidity, and daily variation. Given that I did much of my data analysis at home, I wasn’t well suited to learn how to build the models that would help me answer my questions. Now that I’m back on campus, I’ll have better access to professors and tools that will make learning easier. As I originally proposed in my abstract, I could also look into Lyme disease prevalence and other tickborne diseases in the ticks we collect. Finally, I can combine a lot of what I’ve learned from this summer with what I plan to do later to create an occupancy model that helps account for imperfections in our collection process.

Through this project, I’ve gotten valuable field work experience and I’ve become more familiar with Excel (especially my new favorite function, Pivot Tables). There were a lot of times that I wished I knew how to code. Excel is not always the easiest to work with, and I wish I could have relegated some tedious things that I did manually to a computer. I hope that I’ll get into a data science class next semester (fingers crossed). More abstractly, I think this project made me a better thinker. Given that I had so many questions, I had to deliberate over the best way to answer them and then the best way to get Excel to do what I wanted. This wasn’t always easy, but I’m glad I persevered.

Ultimately, I’m super happy with how my project turned out! There’s still a lot of work that I can do (something to look forward to!). I’ve loved reading about your projects, and I’ll see you around!

Here’s what my poster looks like at the moment, although it is likely to change before I present it in October! (MonroePoster2019)


Allan B, Keesing F, and Ostfeld RS. (2003). Effect of forest fragmentation on Lyme disease risk. Conservation Biology 17(1): 267-272.

Brownstein JS, Skelly DK, Holford TR, Fish D. (2005). Forest fragmentation predicts local scale heterogeneity of Lyme disease risk, Oecologia 146(3): 469-475.

Estrada-Peña A, Estrada-Sánchez A, Estrada-Sánchez D. (2015). Methodological caveats in the environmental modelling and projection of climate niche for ticks, with examples for Ixodes Ricinus (Ixodidae). Veterinary Parasitology 208(1-2): 14-25.

Ogden NH, Pang G, Ginsberg HS, Hickling GJ, Burke RL, Beati L, and Tsao JI. (2018). Evidence for geographic variation in life-cycle processes affecting phenology of the Lyme disease vector Ixodes scapularis (Acari: Ixodidae) in the United States. J Med Entomol 55(6): 1386-1401.


  1. Hi! This is so interesting! I’ve never really thought about ticks, prefering to ignore their existence, but I know that they can have a large impact on an ecosystem. Knowing their habitats and what influences a higher tick population could be crucial. I think that it was really cool that you got to go out hiking and do your research in the field. Your research looks absolutely fascinating, and I look forward to seeing how you can continue this in the future!

  2. kjwiese16 says:


    I was impressed with how straight-forward your blog posts have been about your research. I was expecting to have a lot of trouble understanding since I do not study biology and your lab sounds extremely technical. However, you used common terms that anybody could understand which I really appreciated. I was curious however, why did you choose to study the blacklegged tick as opposed to any of the other species of ticks? Do the other ones not live here or are just harder to find in Virginia? Did you ever find the wrong kind of tick while you were collecting the blacklegged ones?

    As you move forward with your research and career I was also wondering if you ever plan to extend your study to the prevalence of other animals, particularly deer. It sounds like you concluded that the blacklegged ticks exist in higher concentrations where there are host animals. I would imagine that where there are larger numbers of deer, there would also be larger numbers of ticks. Perhaps it would be easier to count and track deer herds than to collect ticks? I am excited to see your poster at the summer research fair!