Location: Animal Disease Research Unit
Title: Spatial and temporal activity patterns of Amblyomma americanumAuthor
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MARSHALL, DANIEL - Washington State University |
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Poh, Karen |
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REICHARD, MASON - Oklahoma State University |
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STARKEY, LINDSAY - Oklahoma State University |
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OWN, JEB - Washington State University |
Submitted to: Parasites & Vectors
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 1/6/2025 Publication Date: 1/16/2025 Citation: Marshall, D.S., Poh, K.C., Reichard, M.V., Starkey, L.A., Own, J.P. 2025. Spatial and temporal activity patterns of Amblyomma americanum. Parasites & Vectors. (18):12. https://doi.org/10.1186/s13071-025-06661-x. DOI: https://doi.org/10.1186/s13071-025-06661-x Interpretive Summary: The lone star tick (Amblyomma americanum) is a tick that actively moves towards a host while host-seeking. Because the tick remains active while seeking for a new host, risk models should consider estimates of tick movement across time and space to accurately represent risk assessment. This study released lone star ticks into plots to measure the distance ticks will travel, the time they spend moving in space, and how these activities may change depending on tick abundance in an area. To gain a better understanding of the potential for far-distance travel in the absence of obstacles, tick movement was analyzed in the laboratory using video tracking software. In the field, lone star ticks can travel up to 9 meters while ticks were able to travel up to 360 meters in the laboratory. The mark-recapture method allowed us to detect ticks up to 2 weeks post-release. Recapture of ticks increased when more ticks were present in the study area, however, ticks were still detectable at least 33% of the time even when only one tick was present. Given that lone star ticks can move far distances and are responsive after several weeks, it is important that risk models incorporate these movement data to gain a better estimate of tick-host encounter and tick-borne disease risk. Technical Abstract: Estimates of tick abundance and distribution are used to determine the risk of tick bites. Tick surveys provide estimates of distributions and relative abundance for species that remain stationary and wait for passing hosts (i.e., questing). Measures of tick populations may be less reliable for species that actively move in search of a host, such as Amblyomma americanum, the lone star tick (LST). Risk estimates for contact with LST require knowledge of the spatial and temporal activity of the tick. Understanding the movement and the temporal patterns of host-seeking behavior will enhance risk assessment for LST. Using CO2-baited traps over a two-year period, we collected wild adult LST in Oklahoma. We used mark-recapture techniques to determine the distance ticks will travel, the amount of time they remain active, and the effect of tick abundance on the number of recaptured ticks in the field. Using video tracking software, we measured the distance traveled and activity time in the laboratory. In 24 hours, LST travel up to 9 meters (mean=3.2 m, sd=3.6) in the field and 360 meters (mean=70.4 m, sd=81.0) in the laboratory. Marked LST were detectable in the environment for up to 14 days after release. We found that the number of recaptured ticks significantly increased with the relative abundance of ticks released, and at a minimum abundance (N=1 tick released) LST were detectable 33.3% of the time. Across all experiments, fewer than half of marked ticks were recovered and at most 28.4% of ticks were responsive to host cues at any given time. Our results demonstrate that LST actively move through the environment and pose a risk for host contact at distances of tens of meters. Ticks will remain responsive to host cues for several weeks, but only a fraction of available ticks are detectable at any given time. Larger numbers of ticks are detected as their population size increases, but even at very low numbers, LST are recovered with CO2 baiting. These spatial and temporal aspects of LST behavior should be considered when building predictive risk models of LST-host contact. |