Partly cloudy with a chance of mosquitoes: Developing a flexible approach to forecasting mosquito populations

Abstract Climate‐induced shifts in mosquito phenology and population structure have important implications for the health of humans and wildlife. The timing and intensity of mosquito interactions with infected and susceptible hosts are a primary determinant of vector‐borne disease dynamics. Like most ectotherms, rates of mosquito development and corresponding phenological patterns are expected to change under shifting climates. However, developing accurate forecasts of mosquito phenology under climate change that can be used to inform management programs remains challenging despite an abundance of available data. As climate change will have variable effects on mosquito demography and phenology across species it is vital that we identify associated traits that may explain the observed variation. Here, we review a suite of modeling approaches that could be applied to generate forecasts of mosquito activity under climate change and evaluate the strengths and weaknesses of the different approaches. We describe four primary life history and physiological traits that can be used to constrain models and demonstrate how this prior information can be harnessed to develop a more general understanding of how mosquito activity will shift under changing climates. Combining a trait‐based approach with appropriate modeling techniques can allow for the development of actionable, flexible, and multi‐scale forecasts of mosquito population dynamics and phenology for diverse stakeholders.

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Publication Details

Journal
Ecosphere
Published
2024-12-01
DOI
https://doi.org/10.1002/ecs2.70074
Citations
1
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
0.92

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article

Partly cloudy with a chance of mosquitoes: Developing a flexible approach to forecasting mosquito populations

Sara H. Paull, Shannon L. LaDeau, Howard S. Ginsberg, Ilia Rochlin et al.
1 citations
Ecosphere
Species Distribution and Climate Change
0.92
article

Partly cloudy with a chance of mosquitoes: Developing a flexible approach to forecasting mosquito populations

Sara H. Paull, Shannon L. LaDeau, Howard S. Ginsberg, Ilia Rochlin, Erin Posthumus, John R. Foster, Daniel A. Grear, Travis McDevitt‐Galles, Sarah C. Elmendorf, Arthur T. DeGaetano, Mevin B. Hooten, Katherine M. McClure
article en
1 citations

Abstract

Abstract Climate‐induced shifts in mosquito phenology and population structure have important implications for the health of humans and wildlife. The timing and intensity of mosquito interactions with infected and susceptible hosts are a primary determinant of vector‐borne disease dynamics. Like most ectotherms, rates of mosquito development and corresponding phenological patterns are expected to change under shifting climates. However, developing accurate forecasts of mosquito phenology under climate change that can be used to inform management programs remains challenging despite an abundance of available data. As climate change will have variable effects on mosquito demography and phenology across species it is vital that we identify associated traits that may explain the observed variation. Here, we review a suite of modeling approaches that could be applied to generate forecasts of mosquito activity under climate change and evaluate the strengths and weaknesses of the different approaches. We describe four primary life history and physiological traits that can be used to constrain models and demonstrate how this prior information can be harnessed to develop a more general understanding of how mosquito activity will shift under changing climates. Combining a trait‐based approach with appropriate modeling techniques can allow for the development of actionable, flexible, and multi‐scale forecasts of mosquito population dynamics and phenology for diverse stakeholders.

EcosphereVol. 15(12)
Boston University (US), United States Geological Survey (US), University of Arizona (US), University of Rhode Island (US), Institute of Arctic and Alpine Research (US), University of Colorado Boulder (US), Cornell University (US), National Ecological Observatory Network (US), Cary Institute of Ecosystem Studies (US), Northeast Climate Adaptation Science Center (US), National Wildlife Health Center (US), Pacific Island Ecosystems Research Center, Eastern Ecological Science Center, Stony Brook University (US), The University of Texas at Austin (US)
National Science Foundation, Battelle, U.S. Geological Survey
Openalex Percentile: Top 14%
Species Distribution and Climate Change
0.92
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