Evidence map›Paper›PMID 42678938›Full record

ArticlePloS one2026

Spatiotemporal dynamics of questing activity by four tick species in the central Great Plains.

Marlon E Cobos, Joanna L Corimanya, Eric Ng'eno, Claudia Nuñez-Penichet, Abigail C Perkins, Zenia Ruiz-Utrilla, Abdelghafar Alkishe, Daniel Romero-Alvarez, Yuan Yao, Anuradha Ghosh and 3 more

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Marlon E CobosDepartment of Ecology and Evolutionary Biology & Biodiversity Institute, University of Kansas, Lawrence, Kansas, United States of America.ORCID https://orcid.org/0000-0002-2611-1767
Joanna L CorimanyaDepartment of Ecology and Evolutionary Biology & Biodiversity Institute, University of Kansas, Lawrence, Kansas, United States of America.ORCID https://orcid.org/0000-0002-5426-9692
Eric Ng'enoDepartment of Ecology and Evolutionary Biology & Biodiversity Institute, University of Kansas, Lawrence, Kansas, United States of America.
Claudia Nuñez-PenichetDepartment of Ecology and Evolutionary Biology & Biodiversity Institute, University of Kansas, Lawrence, Kansas, United States of America.
Abigail C PerkinsDepartment of Ecology and Evolutionary Biology & Biodiversity Institute, University of Kansas, Lawrence, Kansas, United States of America.
Zenia Ruiz-UtrillaDepartment of Ecology and Evolutionary Biology & Biodiversity Institute, University of Kansas, Lawrence, Kansas, United States of America.
Abdelghafar AlkisheDepartment of Ecology and Evolutionary Biology & Biodiversity Institute, University of Kansas, Lawrence, Kansas, United States of America.
Daniel Romero-AlvarezDepartment of Ecology and Evolutionary Biology & Biodiversity Institute, University of Kansas, Lawrence, Kansas, United States of America.ORCID https://orcid.org/0000-0002-6762-6046
Yuan YaoSchool of Biological Sciences, Center for Earth Observation and Modeling, University of Oklahoma, Norman, Oklahoma, United States of America.
Anuradha GhoshBiology Department, Pittsburg State University, Pittsburg, Kansas, United States of America.
Xiangming XiaoSchool of Biological Sciences, Center for Earth Observation and Modeling, University of Oklahoma, Norman, Oklahoma, United States of America.
A Townsend PetersonDepartment of Ecology and Evolutionary Biology & Biodiversity Institute, University of Kansas, Lawrence, Kansas, United States of America.ORCID https://orcid.org/0000-0003-0243-2379
Kathryn T DuncanDepartment of Veterinary Pathobiology, College of Veterinary Medicine, Oklahoma State University, Stillwater, Oklahoma, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

TicksAnimalsEcosystemModels, BiologicalSeasonsSpatio-Temporal AnalysisSpecies Specificity

Identifiers

PMID42678938
PMCPMC13533356

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.