Complex signals alter recognition accuracy and conspecific acceptance thresholds
Many aspects of behaviour depend on recognition, but accurate recognition is difficult because the traits used for recognition often overlap. For example, brood parasitic birds mimic host eggs, so it is challenging for hosts to discriminate between their own eggs and parasitic eggs. Complex signals...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Royal Society
2020
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| _version_ | 1797104993694646272 |
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| author | Tibbetts, EA Liu, M Laub, EC Shen, S-F |
| author_facet | Tibbetts, EA Liu, M Laub, EC Shen, S-F |
| author_sort | Tibbetts, EA |
| collection | OXFORD |
| description | Many aspects of behaviour depend on recognition, but accurate recognition is difficult because the traits used for recognition often overlap. For example, brood parasitic birds mimic host eggs, so it is challenging for hosts to discriminate between their own eggs and parasitic eggs. Complex signals that occur in multiple sensory modalities or involve multiple signal components are thought to facilitate accurate recognition. However, we lack models that explore the effect of complex signals on the evolution of recognition systems. Here, we use individual-based models with a genetic algorithm to test how complex signals influence recognition thresholds, signaller phenotypes and receiver responses. The model has three main results. First, complex signals lead to more accurate recognition than simple signals. Second, when two signals provide different amounts of information, receivers will rely on the more informative signal to make recognition decisions and may ignore the less informative signal. As a result, the particular traits used for recognition change over evolutionary time as sender and receiver phenotypes evolve. Third, complex signals are more likely to evolve when recognition errors are high cost than when errors are low cost. Overall, redundant, complex signals are an evolutionarily stable mechanism to reduce recognition errors.
This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests’.
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| first_indexed | 2024-03-07T06:41:16Z |
| format | Journal article |
| id | oxford-uuid:f95c7e0f-b620-4892-ba35-86fc5f6c2b17 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T06:41:16Z |
| publishDate | 2020 |
| publisher | Royal Society |
| record_format | dspace |
| spelling | oxford-uuid:f95c7e0f-b620-4892-ba35-86fc5f6c2b172022-03-27T12:57:26ZComplex signals alter recognition accuracy and conspecific acceptance thresholdsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:f95c7e0f-b620-4892-ba35-86fc5f6c2b17EnglishSymplectic ElementsRoyal Society2020Tibbetts, EALiu, MLaub, ECShen, S-FMany aspects of behaviour depend on recognition, but accurate recognition is difficult because the traits used for recognition often overlap. For example, brood parasitic birds mimic host eggs, so it is challenging for hosts to discriminate between their own eggs and parasitic eggs. Complex signals that occur in multiple sensory modalities or involve multiple signal components are thought to facilitate accurate recognition. However, we lack models that explore the effect of complex signals on the evolution of recognition systems. Here, we use individual-based models with a genetic algorithm to test how complex signals influence recognition thresholds, signaller phenotypes and receiver responses. The model has three main results. First, complex signals lead to more accurate recognition than simple signals. Second, when two signals provide different amounts of information, receivers will rely on the more informative signal to make recognition decisions and may ignore the less informative signal. As a result, the particular traits used for recognition change over evolutionary time as sender and receiver phenotypes evolve. Third, complex signals are more likely to evolve when recognition errors are high cost than when errors are low cost. Overall, redundant, complex signals are an evolutionarily stable mechanism to reduce recognition errors. This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests’. |
| spellingShingle | Tibbetts, EA Liu, M Laub, EC Shen, S-F Complex signals alter recognition accuracy and conspecific acceptance thresholds |
| title | Complex signals alter recognition accuracy and conspecific acceptance thresholds |
| title_full | Complex signals alter recognition accuracy and conspecific acceptance thresholds |
| title_fullStr | Complex signals alter recognition accuracy and conspecific acceptance thresholds |
| title_full_unstemmed | Complex signals alter recognition accuracy and conspecific acceptance thresholds |
| title_short | Complex signals alter recognition accuracy and conspecific acceptance thresholds |
| title_sort | complex signals alter recognition accuracy and conspecific acceptance thresholds |
| work_keys_str_mv | AT tibbettsea complexsignalsalterrecognitionaccuracyandconspecificacceptancethresholds AT lium complexsignalsalterrecognitionaccuracyandconspecificacceptancethresholds AT laubec complexsignalsalterrecognitionaccuracyandconspecificacceptancethresholds AT shensf complexsignalsalterrecognitionaccuracyandconspecificacceptancethresholds |