Abstract
Predicting the effects of seasonality and climate change on the emergence and spread of infectious disease remains difficult, in part because of poorly understood connections between warming and the mechanisms driving disease. Trait-based mechanistic models combined with thermal performance curves arising from the metabolic theory of ecology (MTE) have been highlighted as a promising approach going forward; however, this framework has not been tested under controlled experimental conditions that isolate the role of gradual temporal warming on disease dynamics and emergence. Here, we provide experimental evidence that a slowly warming host-parasite system can be pushed through a critical transition into an epidemic state. We then show that a trait-based mechanistic model with MTE functional forms can predict the critical temperature for disease emergence, subsequent disease dynamics through time and final infection prevalence in an experimentally warmed system of Daphnia and a microsporidian parasite. Our results serve as a proof of principle that trait-based mechanistic models using MTE subfunctions can predict warming-induced disease emergence in data-rich systems-a critical step towards generalizing the approach to other systems.