College of Science and Health Theses and Dissertations

Date of Award

Spring 6-10-2023

Degree Type


Degree Name

Master of Science (MS)


Biological Science

First Advisor

Jalene LaMontagne, PhD

Second Advisor

Benjamin Zuckerberg, PhD

Third Advisor

Windsor Aguirre, PhD


Tick-borne diseases in humans such as Lyme disease cases in the United States have doubled between 2004 and 2016. Understanding the dynamics of infectious diseases has long been of interest for ecologists. Tick and tick-borne diseases are influenced by temperature and precipitation at local scales, indirectly through mast seeding in forest trees which increases the abundance of tick hosts (e.g., small mammals), as well as direct effects on survival. Most tick studies occur at local scales that comprise only a small part of their range. The aim of my thesis is to characterize spatiotemporal dynamics of ticks and tick-borne diseases in the eastern United States. I used datasets from National Ecological Observatory Network (NEON) from 2014 to 2021 to quantify the level of synchrony in tick dynamics in seven NEON Domains, representing different ecoregions, and spanning distances up to 2,000 km. I used multiple regression matrices (MRM) to examine patterns of synchrony across sites in regional to sub-continental patterns of host-seeking ticks, and climatic variation. I found that spatial synchrony in temporal patterns of nymph abundance for both Amblyomma americanum and Ixodes scapularis declined with increasing distance between NEON sites. Weather variables associated with the spatiotemporal dynamics and key predictors of ticks and tick-borne diseases vary between the two species. A. americanum was driven by lags in July temperature differences, ∆T3 (difference in mean July temperatures in year t-3 and t-4) and ∆T4 (difference in mean July temperatures in year t-4 and t-5); and January conditions impacted tick survival for I. scapularis. The proportion of nymph-infected ticks was explained by environmental factors for the genus A. americanum. Whereas, for I. scapularis proportion of infected nymphs we were unable to explain. Nymph abundance and tick-borne diseases could be understood by identifying environmental variables influencing tick spatiotemporal patterns, allowing for potential prediction of a future tick outbreak.

SLP Collection


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Biology Commons