Abstract
Müllerian mimicry theory states that frequency-dependent selection should favour geographical convergence of harmful species onto a shared colour pattern. As such, mimetic patterns are commonly circumscribed into discrete mimicry complexes, each containing a predominant phenotype. Outside a few examples in butterflies, the location of transition zones between mimicry complexes and the factors driving mimicry zones has rarely been examined. To infer the patterns and processes of Müllerian mimicry, we integrate large-scale data on the geographical distribution of colour patterns of social bumblebees across the contiguous United States and use these to quantify colour pattern mimicry using an innovative, unsupervised machine-learning approach based on computer vision. Our data suggest that bumblebees exhibit geographically clustered, but sometimes imperfect colour patterns, and that mimicry patterns gradually transition spatially rather than exhibit discrete boundaries. Additionally, examination of colour pattern transition zones of three comimicking, polymorphic species, where active selection is driving phenotype frequencies, revealed that their transition zones differ in location within a broad region of poor mimicry. Potential factors influencing mimicry transition zone dynamics are discussed.
| Original language | English (US) |
|---|---|
| Article number | 20191501 |
| Journal | Proceedings of the Royal Society B: Biological Sciences |
| Volume | 286 |
| Issue number | 1910 |
| DOIs | |
| State | Published - Sep 11 2019 |
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All Science Journal Classification (ASJC) codes
- Biochemistry, Genetics and Molecular Biology(all)
- Immunology and Microbiology(all)
- Environmental Science(all)
- Agricultural and Biological Sciences(all)
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Unsupervised machine learning reveals mimicry complexes in bumblebees occur along a perceptual continuum. / Ezray, Briana D.; Wham, Drew C.; Hill, Carrie E.; Hines, Heather M.
In: Proceedings of the Royal Society B: Biological Sciences, Vol. 286, No. 1910, 20191501, 11.09.2019.Research output: Contribution to journal › Article
TY - JOUR
T1 - Unsupervised machine learning reveals mimicry complexes in bumblebees occur along a perceptual continuum
AU - Ezray, Briana D.
AU - Wham, Drew C.
AU - Hill, Carrie E.
AU - Hines, Heather M.
PY - 2019/9/11
Y1 - 2019/9/11
N2 - Müllerian mimicry theory states that frequency-dependent selection should favour geographical convergence of harmful species onto a shared colour pattern. As such, mimetic patterns are commonly circumscribed into discrete mimicry complexes, each containing a predominant phenotype. Outside a few examples in butterflies, the location of transition zones between mimicry complexes and the factors driving mimicry zones has rarely been examined. To infer the patterns and processes of Müllerian mimicry, we integrate large-scale data on the geographical distribution of colour patterns of social bumblebees across the contiguous United States and use these to quantify colour pattern mimicry using an innovative, unsupervised machine-learning approach based on computer vision. Our data suggest that bumblebees exhibit geographically clustered, but sometimes imperfect colour patterns, and that mimicry patterns gradually transition spatially rather than exhibit discrete boundaries. Additionally, examination of colour pattern transition zones of three comimicking, polymorphic species, where active selection is driving phenotype frequencies, revealed that their transition zones differ in location within a broad region of poor mimicry. Potential factors influencing mimicry transition zone dynamics are discussed.
AB - Müllerian mimicry theory states that frequency-dependent selection should favour geographical convergence of harmful species onto a shared colour pattern. As such, mimetic patterns are commonly circumscribed into discrete mimicry complexes, each containing a predominant phenotype. Outside a few examples in butterflies, the location of transition zones between mimicry complexes and the factors driving mimicry zones has rarely been examined. To infer the patterns and processes of Müllerian mimicry, we integrate large-scale data on the geographical distribution of colour patterns of social bumblebees across the contiguous United States and use these to quantify colour pattern mimicry using an innovative, unsupervised machine-learning approach based on computer vision. Our data suggest that bumblebees exhibit geographically clustered, but sometimes imperfect colour patterns, and that mimicry patterns gradually transition spatially rather than exhibit discrete boundaries. Additionally, examination of colour pattern transition zones of three comimicking, polymorphic species, where active selection is driving phenotype frequencies, revealed that their transition zones differ in location within a broad region of poor mimicry. Potential factors influencing mimicry transition zone dynamics are discussed.
UR - http://www.scopus.com/inward/record.url?scp=85072028359&partnerID=8YFLogxK
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U2 - 10.1098/rspb.2019.1501
DO - 10.1098/rspb.2019.1501
M3 - Article
C2 - 31506052
AN - SCOPUS:85072028359
VL - 286
JO - Proceedings of the Royal Society B: Biological Sciences
JF - Proceedings of the Royal Society B: Biological Sciences
SN - 0962-8452
IS - 1910
M1 - 20191501
ER -