Department of Integrative Biology, University of Texas, Austin, TX, USA.
Department of Biological Sciences and Advanced Environmental Research Institute, University of North Texas, Denton, TX, USA.
Philos Trans R Soc Lond B Biol Sci. 2020 Jul 6;375(1802):20190486. doi: 10.1098/rstb.2019.0486. Epub 2020 May 18.
Floral communities present complex and shifting resource landscapes for flower-foraging animals. Strong similarities among the floral displays of different plant species, paired with high variability in reward distributions across time and space, can weaken correlations between floral signals and reward status. As a result, it should be difficult for foragers to discriminate between rewarding and rewardless flowers. Building on signal detection theory in behavioural ecology, we use hypothetical probability density functions to examine graphically how plant signals pose challenges to forager decision-making. We argue that foraging costs associated with incorrect acceptance of rewardless flowers and incorrect rejection of rewarding ones interact with community-level reward availability to determine the extent to which rewardless and rewarding species should overlap in flowering time. We discuss the evolutionary consequences of these phenomena from both the forager and the plant perspectives. This article is part of the theme issue 'Signal detection theory in recognition systems: from evolving models to experimental tests'.
花卉群落为采花动物呈现出复杂且不断变化的资源景观。不同植物物种的花卉展示之间存在很强的相似性,加上奖励在时间和空间上的分布高度变化,这可能削弱花卉信号与奖励状态之间的相关性。因此,对于觅食者来说,区分有奖励和无奖励的花朵应该很困难。基于行为生态学中的信号检测理论,我们使用假设的概率密度函数以图形方式检查植物信号如何给觅食者的决策带来挑战。我们认为,与错误接受无奖励花朵和错误拒绝有奖励花朵相关的觅食成本与群落水平的奖励可获得性相互作用,决定了无奖励和有奖励物种在开花时间上重叠的程度。我们从觅食者和植物的角度讨论了这些现象的进化后果。本文是主题为“识别系统中的信号检测理论:从进化模型到实验检验”的一部分。