Sensitivity to variability in resources has been documented in humans, primates, birds, and social insects, but the fit between empirical results and the predictions of risk sensitivity theory (RST), which aims to explain this sensitivity in adaptive terms, is weak [1]. RST predicts that agents should switch between risk proneness and risk aversion depending on state and circumstances, especially according to the richness of the least variable option [2]. Unrealistic assumptions about agents' information processing mechanisms and poor knowledge of the extent to which variability imposes specific selection in nature are strong candidates to explain the gap between theory and data. RST's rationale also applies to plants, where it has not hitherto been tested. Given the differences between animals' and plants' information processing mechanisms, such tests should help unravel the conflicts between theory and data. Measuring root growth allocation by split-root pea plants, we show that they favor variability when mean nutrient levels are low and the opposite when they are high, supporting the most widespread RST prediction. However, the combination of non-linear effects of nitrogen availability at local and systemic levels may explain some of these effects as a consequence of mechanisms not necessarily evolved to cope with variance [3, 4]. This resembles animal examples in which properties of perception and learning cause risk sensitivity even though they are not risk adaptations [5].

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A key facet of floral scent is diel fluctuations in emission, often studied in the context of plant-pollinator interactions, while contributions of environment and phylogeny remain overlooked. Here, we ask if these factors are involved in shaping temporal variations in scent emission. To that end, we coupled light/dark floral emission measurements of 17 desert Brassicaceae species with environmental and phylogenetic data to explore the individual/combined impacts of these predictors on diel emission patterns. We further investigated these patterns by conducting high-resolution emission measurements in a subset of genetically distant species with contrasting temporal dynamics. While diel shifts in magnitude and richness of emission were strongly affected by genetic relatedness, they also reflect the environmental conditions under which the species grow. Specifically, light/ dark emission ratios were negatively affected by an increase in winter temperatures, known to impact both plant physiology and insect locomotion, and sandy soil fractions, previously shown to exert stress that tempers with diel metabolic rhythms. Additionally, the biosynthetic origins of the compounds were associated with their corresponding production patterns, possibly to maximize emission efficacy. Using a multidisciplinary chemical/ecological approach, we uncover and differentiate the main factors shaping floral scent diel fluctuations, highlighting their consequences under changing global climate.

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