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Categorical identity signatures can reduce host error rates during brood parasitism

Abstract:
Biological recognition is often modeled as involving discrimination of continuously-distributed (and continuously-perceived) traits according to decision thresholds. However, traits such as animal signals can be categorically distributed. Here, we test how such categorical distributions may influence fundamental trade-offs in signal recognition, using a brood parasite–host system involving identity recognition. The African cuckoo finch Anomalospiza imberbis parasitizes several host species, each of which has evolved inter-individual variation in egg appearance (“egg signatures”) that facilitates recognition and rejection of mimetic cuckoo finch eggs. We demonstrate that egg signature traits in one host species, the zitting cisticola Cisticola juncidis, are categorically distributed. Field experiments reveal that zitting cisticolas make fewer Type II errors (accepting parasitic eggs) and Type I errors (rejecting their own eggs) than hosts exhibiting continuous variation. This challenges the long-standing expectation (from classification models, statistics, and signal detection theory) of a strict trade-off between these two error types. Individual-based simulations clarify mechanisms by which categorical variation can generate low error rates, especially when combined with “category-based rejection”, whereby hosts only reject eggs of different categories to their own. Our findings show that the categorical distribution and category-based perception of trait variation can shape error trade-offs and coevolutionary dynamics, which should inform studies on other mimicry or self/non-self recognition systems, including immune recognition. They also highlight the importance of quantifying trait distributions and how they are perceived, when understanding coevolution between deceivers and those they deceive.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1371/journal.pbio.3003667

Authors

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Role:
Author
ORCID:
0000-0001-5604-7965
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Institution:
University of Oxford
Division:
MPLS
Department:
Biology
Sub department:
Biology
Role:
Author


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Funder identifier:
https://ror.org/013meh722
Grant:
Balfour Studentship
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Funder identifier:
https://ror.org/057kr0a20
Grant:
Rosemary Grant Advanced Award
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Funder identifier:
10.13039/100010663
Grant:
advanced grant (no. 789240)
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Funder identifier:
https://ror.org/03wnrjx87
Grant:
Dorothy Hodgkin Fellowship
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Funder identifier:
https://ror.org/012p63287
Grant:
Adaptive Life Scholarship


Publisher:
Public Library of Science
Journal:
PLoS Biology More from this journal
Volume:
24
Issue:
2
Pages:
e3003667
Article number:
e3003667
Publication date:
2026-02-20
Acceptance date:
2026-02-06
DOI:
EISSN:
1545-7885
ISSN:
1544-9173


Language:
English
Keywords:
Source identifiers:
3815306
Deposit date:
2026-03-02
ARK identifier:
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.

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