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Tuesday, July 5, 2016

Plants Can Gamble

Plants Can Gamble, According to Study

Virginia Morell | June 30, 2016

[...] “Like most people, I used to look at plants as passive,” says lead author Efrat Dener, a master’s student in environmental sciences at Ben-Gurion University of the Negev in Beersheba, Israel. His group’s experiments show “how wrong that view is.” Although plants do other things—such as bending toward sunlight and responding to humidity—they haven’t been thought of as “dynamic strategists,” says Dener’s co-author Alex Kacelnik, a behavioral ecologist at the University of Oxford in the United Kingdom. That is, they haven’t been shown to be able to respond when times are tough by changing their behavior and taking a chance.
Humans, primates, birds, and social insects take fewer risks when faced with a steady supply of food. But when the supply is uncertain, they switch strategies and take more risks. For instance, in lab experiments, honey bees turn to gambling when they’re starving, choosing to sip nectar from a tube that may dispense plentiful amounts or nothing. And dark-eyed juncos (small songbirds) that are cold will ignore a seed dispenser that regularly releases three seeds, and choose one that may give out six—or zero.

"Study: Pea plants know how to gamble. The pea plant's adaptive behavior mimics the decision making of humans when faced with varying levels of risk." Source:

<more at; related articles and links: (+Video) (Apparently, Plants Know How To 'Gamble'. In a recent study, they took risks to get more nutrients. July 4, 2016) and (Pea Plants Show Risk Sensitivity. Efrat Dener, Alex Kacelnik, and Hagai Shemesh. DOI: [Summary: 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. 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. 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. This resembles animal examples in which properties of perception and learning cause risk sensitivity even though they are not risk adaptations.])>

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