Dener Efrat, Kacelnik Alex, Shemesh Hagai
Department of Environmental Sciences, Tel-Hai College, 12208 Upper Galilee, Israel; Mitrani Department of Desert Ecology, The Albert Katz International School for Desert Studies, The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, 8499000 Midreshet Ben-Gurion, Israel.
Department of Zoology, Oxford University, Oxford OX1 3PS, UK.
Curr Biol. 2016 Jul 11;26(13):1763-1767. doi: 10.1016/j.cub.2016.05.008. Epub 2016 Jun 30.
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].
人类、灵长类动物、鸟类和群居昆虫对资源变异性的敏感性已有文献记载，但实证结果与旨在从适应性角度解释这种敏感性的风险敏感性理论（RST）预测之间的契合度较低[1]。RST预测，主体应根据状态和环境在风险倾向和风险厌恶之间切换，尤其是根据最稳定选项的丰富程度[2]。关于主体信息处理机制的不切实际假设以及对变异性在自然界中施加特定选择程度的了解不足，很可能是解释理论与数据之间差距的原因。RST的基本原理也适用于植物，但迄今尚未在植物中进行测试。鉴于动物和植物信息处理机制的差异，此类测试应有助于揭示理论与数据之间的冲突。通过对分根豌豆植株的根系生长分配进行测量，我们发现，当平均养分水平较低时，它们倾向于变异性，而当平均养分水平较高时则相反，这支持了RST最普遍的预测。然而，局部和系统水平上氮有效性的非线性效应相结合，可能会解释其中一些效应，这是由不一定为应对变异性而进化出的机制导致的[3,4]。这类似于动物的例子，即感知和学习的特性会导致风险敏感性，尽管它们并非风险适应性特征[5]。
