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People often display essentialist biases, which can lead them to underestimate within-species variability. This bias is especially pronounced when traits are described as advantageous for survival. However, it is unclear whether this bias is limited to the specified trait or encompasses complex trait interactions. We used Markov Chain Monte Carlo with People (MCMCp) to analyze people’s representations of biological variability, using ladybeetles as a model species. Participants either received contextual information about the benefits of ladybeetle color for survival, or survival-irrelevant information. Overall, participants held consistent beliefs about ladybeetle features, but those with survival-relevant context produced lighter and larger ladybeetles; this difference was consistent with survey responses. However, we found no significant interaction between MCMCp variability and essentialism scores, given our context manipulation. We discuss potential explanations for these results and highlight advantages of MCMCp for assessing biological variability, particularly when studying the development of essentialist biases. 

People often display essentialist biases, which can lead them to underestimate within-species variability. This bias is espe- cially pronounced when traits are described as advantageous for survival. However, it is unclear whether this bias is limited to the specified trait or encompasses complex trait interactions. We used Markov Chain Monte Carlo with People (MCMCp) to analyze people’s representations of biological variability, using ladybeetles as a model species. Participants either re- ceived contextual information about the benefits of ladybeetle color for survival, or survival-irrelevant information. Overall, participants held consistent beliefs about ladybeetle features, but those with survival-relevant context produced lighter and larger ladybeetles; this difference was consistent with survey responses. However, we found no significant interaction be- tween MCMCp variability and essentialism scores, given our context manipulation. We discuss potential explanations for these results and highlight advantages of MCMCp for assess- ing biological variability, particularly when studying the devel- opment of essentialist biases. 

People often display essentialist biases, which can lead them to underestimate within-species variability. This bias is especially pronounced when traits are described as advantageous for survival. However, it is unclear whether this bias is limited to the specified trait or encompasses complex trait interactions. We used Markov Chain Monte Carlo with People (MCMCp) to analyze people’s representations of biological variability, using ladybeetles as a model species. Participants either received contextual information about the benefits of ladybeetle color for survival, or survival-irrelevant information. Overall, participants held consistent beliefs about ladybeetle features, but those with survival-relevant context produced lighter and larger ladybeetles; this difference was consistent with survey responses. However, we found no significant interaction be- tween MCMCp variability and essentialism scores, given our context manipulation. We discuss potential explanations for these results and highlight advantages of MCMCp for assess- ing biological variability, particularly when studying the development of essentialist biases.