Post #2: Temporal Variation of Ticks

Hello everyone! I apologize for my long hiatus—I’ve been manipulating my data and compiling it into lots and lots of graphs. I’m glad I’m finally getting the opportunity to show some of them to you! I realize that what I talk about in this post wasn’t something that I clearly said that I wanted to study in my last one, but I thought time variables could definitely be a big influence in tick abundance.

A lot of the questions I had involved how Ixodes scapularis (black-legged tick) populations in the greater Williamsburg area change over time. For example, I wanted to look at trends on a yearly and daily basis and see if we could find any patterns. This year, we were fortunate enough to visit almost two-thirds of the sites in the spring and the summer, which gave us the opportunity to see if there was seasonal variation in tick populations as well. In this post, I wanted to elaborate on why temporal variation in tick populations is important on each of these scales and showcase some of the analyses that I’ve performed so far.

Various scientists postulate that Virginia is an expansion front for the black-legged tick. Lyme Disease cases have been on the rise throughout Virginia between 2000 and 2014, and the range in which we see cases has also expanded (Lantos et al., 2015). Perhaps this means that the range of Lyme Disease’s vector (the black-legged tick) is also expanding. A model that predicted risk of encountering host-seeking I. scapularis nymphs suggested that black-legged ticks might be likely to expand into southeastern Virginia (Diuk-Wasser et al., 2010). Thus, I wanted to test if this model had the right idea—have we seen an increase in the number of black-legged ticks that we collect during our study period?

On the accompanying document, figures 1 and 2 address yearly variation: MonroeBlogGraphs1

Now what do these graphs mean? Basically, they mean that we haven’t seen any sort of significant change in the number of ticks we collect over our study period, minus the fact that we didn’t collect any adults in 2010 and 2011. Frankly, I am not that surprised that there isn’t a significant difference. Most of the expansion of Lyme Disease that Lantos and his co-authors discussed in this paper was concentrated in southwestern Virginia, closer to Roanoke. I think I’ll talk about this more in my conclusion post—we still have to talk about seasonal and daily variation.

Studies of seasonal and daily variation are important because they can elucidate when we are most at risk for encountering ticks and becoming infected with tickborne diseases. A 2015 study by Levi et al. explained that nymph activity often peaks around spring and early summer, when humans are most likely to spend time outdoors. Nymphs are probably the most threatening tick life stage because they have consumed a blood meal (and can consequently transmit diseases) but are too small to detect easily. Taking this into account, understanding the tick life cycle in the Williamsburg area can, in turn, help us understand the risks we take when we choose to go hiking in the College Woods, for example.

Figures 3, 4, and 5 help visualize the seasonal and daily variation of tick abundance.

Now what do these mean? The first graph is displaying the difference in the average number of ticks we collect between seasons. Again, we don’t see a significant difference. I would guess that this is because late spring and early summer are pretty similar in Williamsburg. I’ll continue to look into this, and I’ll update you all in my conclusion.

I included the other two graphs just for fun. The analysis I want to do for them is a little too complex for this summer (something to look forward to!), but without any statistics they still provide valuable information as to when we are most likely to find ticks. I should also give a quick explanation of the Julian date measure that I used for the x variable. Julian date simply translates a calendar date into a number, which made it much easier to graph. I notice peaks around day 150 (May 30th) and day 210 (July 29th) for adults, and one around day 150 for nymphs.

I am looking forward to showing you all the rest of my analysis in my next post! I’ll be discussing spatial variation patterns and the effects of temperature and humidity on tick abundance. I’ll continue to work on these graphs so they look their best at the research showcase during the semester.


Diuk-Wasser MA, Vourc’h G, et al. (2010). Field and climate-based model for predicting the density of host-seeking nymphal Ixodes scapularis, an important vector of tick-borne disease agents in the eastern United States. Global Ec. Biogeogr., 19:504-514.

Lantos, PM, Nigrovic LE, et al. (2015). Geographic expansion of Lyme Disease in the southeastern United States, 2000-2014. Open Forum Infectious Diseases, 2(4).

Levi T, Keesing F, Oggenfuss K, Ostfeld RS. (2015). Accelerated phenology of blacklegged ticks under climate warming. Royal Society, 370(1665).

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