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Data from: The effect of resource limitation on the temperature-dependence of mosquito population fitness

Citation

Huxley, PJ; Murray, KA; Pawar, S; Cator, LJ (2021), Data from: The effect of resource limitation on the temperature-dependence of mosquito population fitness, Dryad, Dataset, https://doi.org/10.5061/dryad.h9w0vt4gg

Abstract

Laboratory-derived temperature dependencies of life history traits are increasingly being used to make mechanistic predictions for how climatic warming will affect vector-borne disease dynamics, partially by affecting abundance dynamics of the vector population. These temperature-trait relationships are typically estimated from juvenile populations reared on optimal resource supply, even though natural populations of vectors are expected to experience variation in resource supply, including intermittent resource limitation. Using laboratory experiments on the mosquito Aedes aegypti, a principal arbovirus vector, combined with stage-structured population modelling, we show that low-resource supply in the juvenile life stages significantly depresses the vector’s maximal population growth rate across the entire temperature range (22–32°C) and causes it to peak at a lower temperature than at high-resource supply. This effect is primarily driven by an increase in juvenile mortality and development time, combined with a decrease in adult size with temperature at low-resource supply. Our study suggests that most projections of temperature-dependent vector abundance and disease transmission are likely to be biased because they are based on traits measured under optimal resource supply. Our results provide compelling evidence for future studies to consider resource supply when predicting the effects of climate and habitat change on vector-borne disease transmission, disease vectors and other arthropods.

Methods

The dataset was collected during a laboratory study at Imperial College London and has been processed by a series of generalized linear models (GLMs) and stage-structured

matrix projection models (MPMs) in R to produce a MS accepted for publication in Proceedings of the Royal Society B: Biological Sciences

Usage Notes

The readme file contains an explanation of each of the variables in the dataset, its measurement units.

NA =  values not available. Information on how the measurements were done can be found in the associated manuscript referenced above. 

Funding

Natural Environment Research Council, Award: NE/L002515/1