1. Investigating Spatio-Temporal Variation in Abundance of Black-legged Ticks in the Williamsburg Area
Joyner Miller (Advisor: Matthias Leu)
Introduction
Conclusions
Has there been an increase in the number of black-legged ticks in the Williamsburg area?
Question 1:
We did not observe an increase in black-legged ticks from 2010 to 2019.
Increase of Lyme disease cases discussed by Lantos et al. was concentrated in SW VA.
Habitat fragmentation may lead to more ticks feeding on one infected host  no change in number of ticks in the area but a change in Lyme disease.
Question 2:
We did observe differences in detection rate and abundance among sites but not plots.
Host activity likely governs much of ticks’ site preference and colonization patterns.
White-footed mice (a major host for black-legged ticks) thrive in fragmented environments (Allan, Keesing, and Ostfeld, 2003).
Increased patch isolation is positively correlated with increased tick density  suburban patches tend to be more isolated (Brownstein et al., 2005).
Further Directions:
Incorporate landscape effects into predictive models.
Continue analyses for relationships between tick abundance and temperature and humidity, as well as daily trends.
Employ models that adjust estimates of occupancy based on imperfect detection.
Question 1: Has there been an increase in the number of black-legged ticks (Ixodes scapularis) we collect over our study period?
The state of Virginia has seen an increase in Lyme disease cases (Lantos, 2015). Does this mean that the tick’s range is expanding?
A model that predicted risk of encountering host-seeking nymphs overestimated risk in eastern Virginia (Diuk-Wasser et al., 2010). The authors suggested that eastern Virginia might be an expansion front for I. scapularis.
Hypothesis: I. scapularis is expanding into the Williamsburg area, or southward as a whole.
Question 2: Are there sites where we consistently collect ticks, and are there sites where we collect consistently more ticks?
Ticks have been collected more frequently in certain habitats, particularly forests (Ostfeld et al., 1995).
Generally, tick abundance is related to deer density (Rand et al., 2003).
Hypothesis: Ticks prefer forest sites to grassy sites because they are more likely to encounter hosts.
Figure 1. Shown is the average number (± SEM) of adult ticks collected between 2010 and 2019, excluding There is no significant difference between 2012 and 2019 (t116 = 1.55, p = 0.13).
Figure 2. Shown is the average number (± SEM) of nymphs collected between 2010 and 2019, excluding There is no significant difference between 2010 and 2019 (t116 = 0.96, p = 0.34).
How does black-legged tick detection vary regionally?
Methods and Materials
Acknowledgements
Thank you to Dr. Matthias Leu for all your advice and support!
Thank you to Olivia Spencer for letting me tag along this summer!
Thank you to the Charles Center and the Monroe Scholars Program for funding and making this entire project possible!
Tick sampling has been conducted on the Virginia and Middle Peninsulas from 2010 to 2019, excluding 2014 due to a gap in funding. Although exact numbers vary from year to year, up to 136 plots were sampled at 13 sites.
Two 30 m transects were established at each plot, one north-south and the other east-west. To collect ticks, a 1 m2 canvas was dragged along these transects on the forest floor and were flipped every 3 m to check for ticks.
Ticks identified on the cloth were removed and placed in a 70% ethanol solution and frozen at -80 oC.
In the lab, ticks were identified to species and tested for occurrence of tickborne pathogens.
All data was analyzed using either a t-test or ANOVA.
Figure 4. Shown are the proportion (± SEM) of sites where ticks were detected from 2010 to 2019, excluding Each site is labelled with the number of times visited during the study period in parentheses. Overall, a significant difference between proportions for nymphs was found (ANOVA12,87 = 3.40, p < 0.001). Sites marked with * significantly differed from WAM, and sites marked with + and ~ differed significantly from CNPS and WM, respectively. The proportions also significantly differed among adults (ANOVA12,87 = 3.45, p < 0.001). Sites marked with 1 significantly differed from URB. Sites that differed from CNPS were marked with 2, and sites that differed from NNP were marked with 3. No individual plots had a significantly higher proportion of successful collections for nymphs (ANOVA67,429 = 0.60, p = 0.99) or adults (ANOVA43,280 = 0.41, p = 1.00).
Figure 5. This graph displays the average number (± SEM) of ticks collected at a specific site from , excluding Although no significant difference was found between the average number of adults collected (ANOVA12,1014 = 1.27, p = 0.23), there was a significant difference between the number of nymphs collected at the sites (ANOVA12,1015 = 1.95, p = 0.03). Differences between individual sites were detected using t-tests with an α of , adjusted for multiple comparisons using the Bonferroni method. Sites marked with * significantly differed from CNPS, whereas sites marked with + significantly differed from WM. Again, no plots had a significantly higher average number of adults (ANOVA43,280 = 0.656, p = 0.95) or nymphs (ANOVA67,429 = 0.875, p = 0.75).
References
Allan B, Keesing F, and Ostfeld RS. (2003). Effect of forest fragmentation on Lyme disease risk. Conservation Biology 17(1):
Brownstein JS, Skelly DK, Holford TR, Fish D. (2005). Forest fragmentation predicts local scale heterogeneity of Lyme disease risk, Oecologia 146(3):
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:
Lantos, PM, Nigrovic LE, et al. (2015). Geographic expansion of Lyme Disease in the southeastern United States, Open Forum Infectious Diseases, 2(4).
Ostfeld RS, Cepeda OM, Hazler KR, and Miller MC (1995). Ecology of Lyme disease: Habitat associations of ticks (Ixodes scapularis) in a rural landscape. Ecological Applications 5(2):
Rand PW, Lubelczyk C, et al. (2003). Deer density and the abundance of Ixodes scapularis (Acari: Ixodidae). J Med Entomol 40(2):