Spatiotemporal dynamics of questing activity by four tick species in the central Great Plains
6 affiliations
- 1Department of Ecology and Evolutionary Biology & Biodiversity Institute, University of Kansas, Lawrence, Kansas, United States of America
- 2Fish and Wildlife Conservation Department, Virginia Tech, Blacksburg, Virginia, United States of America
- 3Research Group of Emerging and Neglected Diseases, Ecoepidemiology and Biodiversity, Health Science Faculty, School of Biomedical Sciences, Universidad Internacional SEK (UISEK), Quito, Ecuador
- 4School of Biological Sciences, Center for Earth Observation and Modeling, University of Oklahoma, Norman, Oklahoma, United States of America
- 5Biology Department, Pittsburg State University, Pittsburg, Kansas, United States of America
- 6Department of Veterinary Pathobiology, College of Veterinary Medicine, Oklahoma State University, Stillwater, Oklahoma, United States of America
Abstract
The distributional expansions of several medically relevant tick species across the central Great Plains create a complex and shifting landscape of tick-borne disease risk. Traditional modeling approaches provide a general picture of distributional potential, but predictions are often static representations of species’ ranges. As pathogen transmission is directly linked to tick questing activity, characterizing the spatiotemporal heterogeneity of this behavior is essential to a better understanding of transmission risk and planning of interventions in the area. In this study, we explore novel ecological niche modeling frameworks based on full use of presence-absence data to illuminate the spatiotemporal dynamics of questing activity of four tick species in the central Great Plains region. We processed data from two years of field tick surveillance to derive presence and absence records of active ticks, maximizing sample sizes and making model evaluation more robust. We coupled sampling events with time-specific environmental covariates to leverage longitudinal sampling data still more. We also constrained model response curves to align with fundamental niche theory within a strong conceptual framework. Model outcomes demonstrate both seasonal dynamics of individual species and differences between species in terms of the geographic potential of questing behavior by Great Plains tick species. These modeling approaches provide a more robust basis for understanding ecological drivers of tick questing activity and characterizing the shifting landscape of vector-borne disease risk.
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BibTeX
@article{cobos2026spatiotemporal,
title = {{Spatiotemporal dynamics of questing activity by four tick species in the central Great Plains}},
author = {Marlon E. Cobos and Joanna L. Corimanya and Eric Ng’eno and Claudia Nuñez-Penichet and Abigail C. Perkins and Zenia Ruiz-Utrilla and Abdelghafar Alkishe and Daniel Romero-Alvarez and Yuan Yao and Anuradha Ghosh and Xiangming Xiao and A. Townsend Peterson and Kathryn T. Duncan},
journal = {PLOS One},
year = {2026},
month = sep,
doi = {10.1371/journal.pone.0351160},
url = {https://doi.org/10.1371/journal.pone.0351160},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Spatiotemporal dynamics of questing activity by four tick species in the central Great Plains
AU - Marlon E. Cobos
AU - Joanna L. Corimanya
AU - Eric Ng’eno
AU - Claudia Nuñez-Penichet
AU - Abigail C. Perkins
AU - Zenia Ruiz-Utrilla
AU - Abdelghafar Alkishe
AU - Daniel Romero-Alvarez
AU - Yuan Yao
AU - Anuradha Ghosh
AU - Xiangming Xiao
AU - A. Townsend Peterson
AU - Kathryn T. Duncan
PY - 2026
DA - 2026/09/01
JO - PLOS One
DO - 10.1371/journal.pone.0351160
UR - https://doi.org/10.1371/journal.pone.0351160
AB - The distributional expansions of several medically relevant tick species across the central Great Plains create a complex and shifting landscape of tick-borne disease risk. Traditional modeling approaches provide a general picture of distributional potential, but predictions are often static representations of species’ ranges. As pathogen transmission is directly linked to tick questing activity, characterizing the spatiotemporal heterogeneity of this behavior is essential to a better understanding of transmission risk and planning of interventions in the area. In this study, we explore novel ecological niche modeling frameworks based on full use of presence-absence data to illuminate the spatiotemporal dynamics of questing activity of four tick species in the central Great Plains region. We processed data from two years of field tick surveillance to derive presence and absence records of active ticks, maximizing sample sizes and making model evaluation more robust. We coupled sampling events with time-specific environmental covariates to leverage longitudinal sampling data still more. We also constrained model response curves to align with fundamental niche theory within a strong conceptual framework. Model outcomes demonstrate both seasonal dynamics of individual species and differences between species in terms of the geographic potential of questing behavior by Great Plains tick species. These modeling approaches provide a more robust basis for understanding ecological drivers of tick questing activity and characterizing the shifting landscape of vector-borne disease risk.
SN - 1932-6203
ER -