Signal detection and optimal acceptance thresholds in avian brood parasite–host systems: implications for egg rejection. (6th July 2020)

• Record Type: Journal Article
• Authors: Ruiz-Raya, Francisco; Soler, Manuel
• Is Part Of: Philosophical transactions. Volume 375:Number 1802(2020)
• Publication Date: 2020-07-06
• Subjects: avian brood parasitism -- decision making -- egg recognition -- flexible behaviour -- rejection decisions; Biology -- Periodicals; Science -- Periodicals; 570
• DOI: 10.1098/rstb.2019.0477
• Languages: English
• ISSNs: 0962-8436

Abstract

Abstract : Signal detection theory addresses the challenge of successfully identifying informative signals in noisy information contexts, allowing optimal behavioural decisions in diverse ecological contexts. The optimal acceptance threshold hypothesis proposed by Reeve (Reeve 1989 Am. Nat. 133, 407–435. (doi:10.1086/284926 )) is an elegant theoretical model to predict the flexibility of acceptance thresholds for conspecific discrimination. This model has provided a robust framework used to explore recognition systems in a broad range of contexts such as animal communication, nest-mate discrimination or anti-parasitic host responses. In this review, we discuss key concepts related to the optimal acceptance threshold hypothesis applied to egg rejection decisions in avian brood parasite–host interactions. We explore those factors determining signal detectability in parasitized nests and how hosts adjust their rejection decisions to both the risk of parasitism and the potential costs associated with egg rejection. In addition, we discuss recent results that challenge some traditional assumptions of the optimal acceptance threshold hypothesis and provide a novel perspective to explore rejection decisions, such as the existence of single-threshold decision rules or acceptance decisions. An integrative view combining current evidence with traditional theory is needed to further advance the comprehension of optimal acceptance thresholds. This article is part of the theme issue 'Signal detection theory in recognition systems: from evolving models to experimental tests'.