Coefficient estimates and feature importance of burden. A) Coefficient estimates and B) feature importance of infection prevalence in Daphnia magna infected with Ordospora colligata. Coefficient Effect (Effect) represents the estimated coefficient of the ‘glmnet’ elastic net regression model. Positive values indicate a positive relationship between the variable and infection prevalence, while negative values indicate a negative relationship (i.e., a positive value means the explanatory variables increased prevalence). Effect sizes represent the strength of these relationships, with larger absolute values indicating stronger effects. Lower (Lower CI) and Upper (Upper CI) Confidence Intervals indicate the range (95<sup>th</sup> percentile) from bootstrapping; non-significant values have CIs encompassing 0, suggesting no important relationship to the response variable. Temperature, modelled as a cubic polynomial, is delineated by each degree (linear [L], quadratic [Q], cubic [C]). Fe
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Coefficient estimates and feature importance of burden. A) Coefficient estimates and B) feature importance of infection prevalence in Daphnia magna infected with Ordospora colligata. Coefficient Effect (Effect) represents the estimated coefficient of the ‘glmnet’ elastic net regression model. Positive values indicate a positive relationship between the variable and infection prevalence, while negative values indicate a negative relationship (i.e., a positive value means the explanatory variables increased prevalence). Effect sizes represent the strength of these relationships, with larger absolute values indicating stronger effects. Lower (Lower CI) and Upper (Upper CI) Confidence Intervals indicate the range (95th percentile) from bootstrapping; non-significant values have CIs encompassing 0, suggesting no important relationship to the response variable. Temperature, modelled as a cubic polynomial, is delineated by each degree (linear [L], quadratic [Q], cubic [C]). Fe
