Data from: Navigating “tip fog”: Embracing uncertainty in tip measurements

Nature is full of messy variation, which serves as the raw material for
evolution. Overlooking this variation not only weakens our analyses but
also risks selecting inaccurate models, generating false precision in
parameter estimates, and creating artificial patterns. Furthermore, the
complexity of uncertainty extends beyond traditional “measurement error,”
encompassing various sources of variance. To address this, we propose the
term “tip fog” to describe the variance between the value from the overall
modeled evolutionary process and what is recorded, without implying a
specific mechanism. We show why accounting for tip fog remains critical by
showing its impact on continuous comparative models and discrete
comparative and diversification models. We rederive methods to estimate
this variance and use simulations to assess its feasibility and importance
in a comparative context. Our findings reveal that ignoring tip fog
substantially affects the accuracy of rate estimates, with higher tip fog
levels showing greater biases from the true rates, as well as affecting
which models are chosen. The findings underscore the importance of model
selection and the potential consequences of neglecting tip fog, providing
insights for improving the accuracy of comparative methods in evolutionary
biology.