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Impact of life stage-dependent dispersal on the colonization dynamics of host patches by ticks and tick-borne infectious agents

Overview of attention for article published in Parasites & Vectors, August 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

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12 X users

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Title
Impact of life stage-dependent dispersal on the colonization dynamics of host patches by ticks and tick-borne infectious agents
Published in
Parasites & Vectors, August 2017
DOI 10.1186/s13071-017-2261-y
Pubmed ID
Authors

Sarah Kada, Karen D. McCoy, Thierry Boulinier

Abstract

When colonization and gene flow depend on host-mediated dispersal, a key factor affecting vector dispersal potential is the time spent on the host for the blood meal, a characteristic that can vary strongly among life history stages. Using a 2-patch vector-pathogen population model and seabird ticks as biological examples, we explore how vector colonization rates and the spread of infectious agents may be shaped by life stage-dependent dispersal. We contrast hard (Ixodidae) and soft (Argasidae) tick systems, which differ strongly in blood- feeding traits. We find that vector life history characteristics (i.e. length of blood meal) and demographic constraints (Allee effects) condition the colonization potential of ticks; hard ticks, which take a single, long blood meal per life stage, should have much higher colonization rates than soft ticks, which take repeated short meals. Moreover, this dispersal potential has direct consequences for the spread of vector-borne infectious agents, in particular when transmission is transovarial. These results have clear implications for predicting the dynamics of vector and disease spread in the context of large-scale environmental change. The findings highlight the need to include life-stage dispersal in models that aim to predict species and disease distributions, and provide testable predictions related to the population genetic structure of vectors and pathogens along expansion fronts.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 89 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 17%
Student > Master 13 15%
Researcher 12 13%
Student > Postgraduate 6 7%
Student > Bachelor 5 6%
Other 11 12%
Unknown 27 30%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 29%
Environmental Science 10 11%
Veterinary Science and Veterinary Medicine 6 7%
Immunology and Microbiology 3 3%
Biochemistry, Genetics and Molecular Biology 3 3%
Other 12 13%
Unknown 29 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 September 2017.
All research outputs
#5,097,453
of 24,717,692 outputs
Outputs from Parasites & Vectors
#1,116
of 5,813 outputs
Outputs of similar age
#82,505
of 322,046 outputs
Outputs of similar age from Parasites & Vectors
#26
of 125 outputs
Altmetric has tracked 24,717,692 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,813 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has done well, scoring higher than 80% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 322,046 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 125 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.