Abstract
<jats:p>Biological responses to environmental stimuli are inherently dynamic. Recent technological advances enable detailed time-resolved measurements of such responses. However, a standard for quantitative characterisation of dynamics is lacking, thus limiting biological insights and comparisons. We developed an unbiased mathematical model structure that allows for the quantification of biological response curve dynamics without a priori knowledge of underlying biochemical mechanisms. Using the model to quantify the dynamics of stress-induced plant volatiles, we uncover a range of novel patterns in volatile signalling, including i) a strong light-independent impact of the time of day of wounding on the onset, duration and shape of the volatile induction responses, ii) an accentuation of volatile-specific induction curve shapes by herbivory-associated molecular patterns (HAMPs) and iii) independent regulation of the strength and duration of volatile induction across genotypes. The model performs well across biochemically diverse responses, suggesting broad applicability to inducible responses. The model is also robust to partial response curves, low resolution data and complex multi-modal responses arising from overlapping stimuli, enabling identification of priming events from otherwise convoluted curves. As all responses measured conform to a common model structure, yet parameter values diverge markedly, we conclude that biologically meaningful information is ignored when dynamics are not quantified. The presented approach will pave the way to identifying new biological response patterns, and their function, across the tree of life.</jats:p>