Pea Plants Show Risk Sensitivity
Pea Plants Show Risk Sensitivity
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DOI：
10.1016/j.cub.2016.05.008
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发表时间：
2016-07-11
期刊：
影响因子：
9.2
通讯作者：
Shemesh, Hagai
中科院分区：
文献类型：
--
作者：
Dener, Efrat;Kacelnik, Alex;Shemesh, Hagai
人类、灵长类动物、鸟类和群居昆虫对资源变化的敏感性已经被证明，但经验结果与风险敏感性理论（Risk Sensitivity Theory，RISK）的预测之间的拟合很弱，RISK旨在用适应性术语解释这种敏感性。他预测，代理人应该根据状态和环境在风险倾向和风险厌恶之间切换，特别是根据最小变量选项的丰富性[2]。对智能体信息处理机制的不切实际的假设和对自然界中变异性对特定选择的影响程度的缺乏了解是解释理论与数据之间差距的有力候选人。这一理论也适用于植物，但迄今为止还没有进行过测试。考虑到动物和植物信息处理机制的差异，这样的测试应该有助于解决理论和数据之间的冲突。通过测量分根豌豆植物的根系生长分配，我们发现，当平均营养水平较低时，它们有利于变异，而当它们较高时，它们则相反，支持最广泛的营养预测。然而，在当地和系统水平的氮供应量的非线性效应的组合可能会解释一些这些效应的机制不一定进化到科普方差的结果[3，4]。这类似于动物的例子，其中感知和学习的特性导致风险敏感性，即使它们不是风险适应[5]。
Sensitivity to variability in resources has been documentedinhumans, 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].