School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, 2006, Australia.
The Sydney Informatics Hub, The University of Sydney, Sydney, NSW, 2006, Australia.
New Phytol. 2022 Nov;236(4):1605-1619. doi: 10.1111/nph.18432. Epub 2022 Sep 13.
All organisms emit odour, providing 'open-access' olfactory information for any receiver with the right sensory apparatus. Characterizing open-access information emitted by groups of organisms, such as plant species, provides the means to answer significant questions about ecological interactions and their evolution. We present a new conceptual framework defining information reliability and a practical method to characterize and recover information from amongst olfactory noise. We quantified odour emissions from two tree species, one focal group and one outgroup, to demonstrate our approach using two new R statistical functions. We explore the consequences of relaxing or tightening criteria defining information and, from thousands of odour combinations, we identify and quantify those few likely to be informative. Our method uses core general principles characterizing information while incorporating knowledge of how receivers detect and discriminate odours. We can now map information in consistency-precision reliability space, explore the concept of information, and test information-noise boundaries, and between cues and signals.
所有生物都会散发气味，为任何具有适当感官设备的接收者提供“开放获取”的嗅觉信息。对群体生物（如植物物种）散发的开放获取信息进行特征描述，为回答关于生态相互作用及其进化的重要问题提供了手段。我们提出了一个新的概念框架，定义了信息可靠性，并提出了一种从嗅觉噪声中提取和恢复信息的实用方法。我们量化了两种树种（一个焦点组和一个外群）的气味排放，使用两个新的 R 统计函数来演示我们的方法。我们探讨了放宽或收紧定义信息的标准的后果，并从数千种气味组合中，确定并量化了那些可能具有信息量的少数气味组合。我们的方法使用了表征信息的核心一般原则，同时结合了接收者如何检测和区分气味的知识。我们现在可以在一致性-精度可靠性空间中绘制信息图，探索信息的概念，并测试信息-噪声边界以及线索和信号之间的关系。
