The temperature dependence of maximal population growth rate (rm) is key to predicting ectotherm responses to climatic change. Matrix projection models (MPMs) are used to calculate rm because they can incorporate variation and inherent time-delays in underlying life-history traits. However, MPM calculations can be laborious and do not reflect time’s continuous nature. Ordinary differential equation-based models (ODEMs) offer a relatively tractable alternative, but it is largely unknown whether ODEM-based calculations and MPM broadly agree when environmental variation affects temperature–dependent rm by introducing time-delays and altering juvenile survival trajectories. We investigate differences in predicted temperature-dependent rm from an ODEM with that calculated from MPMs using temperature– and resource-dependent life-history trait data for the mosquito vector, Aedes aegypti. We show that discrete- and continuous-time calculations of temperature-dependent rm can vary with resource availability and are sensitive to juvenile survival characterisations, suggesting ODEMs can provide comparable temperature–dependent rm calculations unless resources are constraining.

The survival of animals under global warming strongly depends on their individual thermal niches, which result from the balance between energy loss and gain. Active movement is an important component of this energetic balance, as it affects not only energy gain via food intake but also energy loss via activity metabolism. Here, we develop a novel trait-based approach for how thermal niches arise from temperature-dependent movement. Therefore, we used image-based tracking to quantify the unimodal responses of the movement speed of carabid beetles to temperature. We used these empirical data to parameterize a mathematical model based on metabolic and predator-prey theory for net energy gain to derive a general mechanistic concept of thermal niches. This trait-based approach allows a relatively rapid and cost-effective assessment of climate change vulnerability for a wide range of animal taxa on broad geographic scales.

Laboratory-derived temperature dependencies of life history traits are increasingly being used to make mechanistic predictions for how climatic warming will affect disease vector abundance. However, laboratory data are typically from vector populations reared on optimal resource supply, even though natural populations experience fluctuations in resource availability. Here, using laboratory experiments on Aedes aegypti, a principal arbovirus vector, we show that low-resource supply significantly depresses its maximal population growth rate (rmax) and causes it to decrease from 22 to 32°C. In contrast, at high-resource supply, rmax is not just higher, but also increases across the same temperatures. This striking difference is driven by the fact that resource-limitation significantly increases juvenile mortality, slows development, and reduces lifespan and size at maturity (which then decreases fecundity). Our results suggest that future studies need to account for the effects of resource-limitation when using Ecological Metabolic Theory to predict climatic warming effects on disease vectors.