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ENDOGENOUS AND EXOGENOUS FACTORS CONTROLLING TEMPORAL ABUNDANCE PATTERNS OF TROPICAL MOSQUITOES

Overview of attention for article published in Ecological Applications, December 2008
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

Mentioned by

blogs
1 blog
policy
1 policy source

Citations

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60 Dimensions

Readers on

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109 Mendeley
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Title
ENDOGENOUS AND EXOGENOUS FACTORS CONTROLLING TEMPORAL ABUNDANCE PATTERNS OF TROPICAL MOSQUITOES
Published in
Ecological Applications, December 2008
DOI 10.1890/07-1209.1
Pubmed ID
Authors

Guo-Jing Yang, Barry W. Brook, Peter I. Whelan, Sam Cleland, Corey J. A. Bradshaw

Abstract

The growing demand for efficient and effective mosquito control requires a better understanding of vector population dynamics and how these are modified by endogenous and exogenous factors. A long-term (11-year) monitoring data set describing the relative abundance of the saltmarsh mosquito (Aedes vigilax) in the greater Darwin region, northern Australia, was examined in a suite of Gompertz-logistic (GL) models with and without hypothesized environmental correlates (high tide frequency, rainfall, and relative humidity). High tide frequency and humidity were hypothesized to influence saltmarsh mosquito abundance positively, and rainfall was hypothesized to correlate negatively by reducing the availability of suitable habitats (moist substrata) required by ovipositing adult female mosquitoes. We also examined whether environmental correlates explained the variance in seasonal carrying capacity (K) because environmental stochasticity is hypothesized to modify population growth rate (r), carrying capacity, or both. Current and lagged-time effects were tested by comparing alternative population dynamics models using three different information criteria (Akaike's Information Criterion [corrected; AIC(c)], Bayesian Information Criterion [BIC], and cross-validation [C-V]). The GL model with a two-month lag without environmental effects explained 31% of the deviance in population growth rate. This increased to > 70% under various model combinations of high tide frequency, rainfall, and relative humidity, of which, high tide frequency and rainfall had the highest contributions. Temporal variation in K was explained weakly by high tide frequency, and there was some evidence that the filling of depressions to reduce standing water availability has reduced Aedes vigilax carrying capacity over the study period. This study underscores the need to consider simultaneously both types of drivers (endogenous and exogenous) when predicting mosquito abundance and population growth patterns. This work also indicates that climate change, via continued increases in rainfall and higher expected frequencies and intensities of high tide events with sea level rise, will alter mosquito abundance trends in northern Australia.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 <1%
Australia 1 <1%
Brazil 1 <1%
United Kingdom 1 <1%
Mexico 1 <1%
Japan 1 <1%
United States 1 <1%
Unknown 102 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 27%
Student > Ph. D. Student 16 15%
Student > Bachelor 12 11%
Student > Master 12 11%
Other 7 6%
Other 20 18%
Unknown 13 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 48 44%
Environmental Science 18 17%
Medicine and Dentistry 6 6%
Social Sciences 5 5%
Mathematics 3 3%
Other 11 10%
Unknown 18 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 19 February 2013.
All research outputs
#4,367,050
of 25,374,917 outputs
Outputs from Ecological Applications
#1,080
of 3,326 outputs
Outputs of similar age
#23,010
of 179,597 outputs
Outputs of similar age from Ecological Applications
#10
of 25 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,326 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.5. This one has gotten more attention than average, scoring higher than 67% 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 179,597 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.