Citizen science supports ecological predictions of phenology in North American mimetic butterflies

Abstract Phenological synchrony enables species to occur when conditions are optimal for survival. While phenological synchrony between butterflies and their host plants has been extensively documented, the importance of phenology in maintaining interspecies interactions, such as mimicry, is less understood. Mimicry occurs when a species (i.e. the mimic) evolves a phenotypic resemblance to an unpalatable species (i.e. the model), resulting in protection against predation for the mimic. Theory predicts that in Batesian mimicry systems, models should appear seasonally before their mimics to give predators sufficient time to learn, recognize, and avoid their aposematic signal (i.e. model-first hypothesis). Here, we use citizen science data from iNaturalist to test these long-standing predictions. To understand how mimicry influences the evolution of different phenological strategies, we estimate onset phenology in two systems: the defended model species Battus philenor and its classic Batesian mimic Limenitis arthemis astyanax, and the more complex system consisting of Mullerian co-mimics Danaus plexippus and Limenitis archippus. Our results support the model-first hypothesis and demonstrate that unpalatable models appear significantly before their mimics across large geographical scales. This research highlights a new avenue for utilizing large-scale citizen science datasets to address long-standing questions about how phenology impacts complex ecological interactions.

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Publication Details

Journal
Biological Journal of the Linnean Society
Published
2025-09-01
DOI
https://doi.org/10.1093/biolinnean/blaf068
Primary Topic
Plant and animal studies
Type
article
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article

Citizen science supports ecological predictions of phenology in North American mimetic butterflies

John E. Herrmann, Hannah E. Aichelman, Sean P. Mullen, Abigail E. Robinson
Biological Journal of the Linnean Society
Plant and animal studies
article

Citizen science supports ecological predictions of phenology in North American mimetic butterflies

John E. Herrmann, Hannah E. Aichelman, Sean P. Mullen, Abigail E. Robinson
article en

Abstract

Abstract Phenological synchrony enables species to occur when conditions are optimal for survival. While phenological synchrony between butterflies and their host plants has been extensively documented, the importance of phenology in maintaining interspecies interactions, such as mimicry, is less understood. Mimicry occurs when a species (i.e. the mimic) evolves a phenotypic resemblance to an unpalatable species (i.e. the model), resulting in protection against predation for the mimic. Theory predicts that in Batesian mimicry systems, models should appear seasonally before their mimics to give predators sufficient time to learn, recognize, and avoid their aposematic signal (i.e. model-first hypothesis). Here, we use citizen science data from iNaturalist to test these long-standing predictions. To understand how mimicry influences the evolution of different phenological strategies, we estimate onset phenology in two systems: the defended model species Battus philenor and its classic Batesian mimic Limenitis arthemis astyanax, and the more complex system consisting of Mullerian co-mimics Danaus plexippus and Limenitis archippus. Our results support the model-first hypothesis and demonstrate that unpalatable models appear significantly before their mimics across large geographical scales. This research highlights a new avenue for utilizing large-scale citizen science datasets to address long-standing questions about how phenology impacts complex ecological interactions.

Biological Journal of the Linnean SocietyVol. 146(1)
Boston University (US), University of Rochester (US)
Openalex Percentile: Top 81%
Plant and animal studies
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Citizen science supports ecological predictions of phenology in North American mimetic butterflies — John E. Herrmann, Hannah E. Aichelman, et al. · Biological Journal of the Linnean Society (2025) | TGRS Research Map | TGRS