Literature DB >> 27374342

Pea Plants Show Risk Sensitivity.

Efrat Dener1, Alex Kacelnik2, Hagai Shemesh3.   

Abstract

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].
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  energy budget rule; phenotypic plasticity; plant behavior; risk sensitivity; roots foraging

Mesh:

Substances:

Year:  2016        PMID: 27374342     DOI: 10.1016/j.cub.2016.05.008

Source DB:  PubMed          Journal:  Curr Biol        ISSN: 0960-9822            Impact factor:   10.834


  13 in total

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Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2018-09-19       Impact factor: 6.237

Review 2.  Challenges for theories of consciousness: seeing or knowing, the missing ingredient and how to deal with panpsychism.

Authors:  Victor A F Lamme
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2018-09-19       Impact factor: 6.237

3.  Economic behaviours among non-human primates.

Authors:  Sacha Bourgeois-Gironde; Elsa Addessi; Thomas Boraud
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Review 4.  Plants make smart decisions in complex environments.

Authors:  Liv S Severino
Journal:  Plant Signal Behav       Date:  2021-08-29

Review 5.  Dynamic decision making and value computations in medial frontal cortex.

Authors:  Bilal A Bari; Jeremiah Y Cohen
Journal:  Int Rev Neurobiol       Date:  2021-01-23       Impact factor: 3.230

6.  The adaptive value of probability distortion and risk-seeking in macaques' decision-making.

Authors:  A Nioche; N P Rougier; M Deffains; S Bourgeois-Gironde; S Ballesta; T Boraud
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2021-01-11       Impact factor: 6.237

Review 7.  Predictability of Biotic Stress Structures Plant Defence Evolution.

Authors:  Daan Mertens; Karina Boege; André Kessler; Julia Koricheva; Jennifer S Thaler; Noah K Whiteman; Erik H Poelman
Journal:  Trends Ecol Evol       Date:  2021-01-16       Impact factor: 17.712

8.  Identification of an insect-produced olfactory cue that primes plant defenses.

Authors:  Anjel M Helms; Consuelo M De Moraes; Armin Tröger; Hans T Alborn; Wittko Francke; John F Tooker; Mark C Mescher
Journal:  Nat Commun       Date:  2017-08-24       Impact factor: 14.919

9.  Neighbour presence, not identity, influences root and shoot allocation in pea.

Authors:  Cory E Jacob; Eric Tozzi; Christian J Willenborg
Journal:  PLoS One       Date:  2017-03-14       Impact factor: 3.240

10.  An asymmetry of treatment between lotteries involving gains and losses in rhesus monkeys.

Authors:  Aurélien Nioche; Sacha Bourgeois-Gironde; Thomas Boraud
Journal:  Sci Rep       Date:  2019-07-18       Impact factor: 4.379

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