Host plant adaptation during recent global range expansion in the monarch butterfly
Data files
Dec 19, 2019 version files 973.94 KB
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2017_adults.csv
55.97 KB
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Adults_2018.csv
141.02 KB
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concatenated_cardenolides.csv
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experiment_master.csv
311.95 KB
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larval_data.csv
193.78 KB
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masses.csv
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Monarch_local_adaptation_2018_-_Latex.csv
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Monarch_local_adaptation_script.R
63.08 KB
Abstract
Herbivores that have recently expanded their host plant ranges provide opportunities to test hypotheses about the evolution of host plant specialization. Here, we take advantage of the contemporary global range expansion of the monarch butterfly (Danaus plexippus) and conduct a reciprocal rearing experiment involving monarch populations with divergent host plant assemblages. Specifically, we ask the following questions: (1) Do geographically disparate populations of monarch butterflies show evidence for local adaptation to their host plants? If so, what processes contribute to this pattern? (2) How is dietary breadth related to performance across multiple host species in monarch populations? (3) Does the coefficient of variation in performance vary across sympatric versus allopatric hosts?
We find evidence for local adaptation in larval growth rate and survival based on sympatric/allopatric contrasts. Migratory North American monarchs, which have comparatively broad host breadth, have higher mean performance than derived non-migratory populations across all host plant species. Monarchs reared on their sympatric host plants show lower coefficient of variation in performance than monarchs reared on allopatric hosts. We focus our discussion on possible mechanisms contributing to local adaptation to novel host plants and potential explanations for the reduction in performance that we observed in derived monarch populations.
All data included here are from two summers of experiments. Data were collected by hand on printed datasheets, and then uploaded into Google spreadsheets. The accompanying datafiles represent .csv files that correspond to these Google spreadsheets. All processing was done using R. The accompanying script needed for all analysis presented in the manuscript is included.
The R script includes annotations describing what is included in each dataset.