  Knowledge of a star's evolutionary history combined with estimates of planet
occurrence rates allows one to infer its relative quality as a location in the
search for biosignatures, and to quantify this intuition using long-term
habitability metrics. In this study, we analyse the sensitivity of the
biosignature yield metrics formulated by Tuchow & Wright (2020) to
uncertainties in observable stellar properties and to model uncertainties. We
characterize the uncertainties present in fitting a models to stellar
observations by generating a stellar model with known properties and adding
synthetic uncertainties in the observable properties. We scale the uncertainty
in individual observables and observe the the effects on the precision of
properties such as stellar mass, age, and our metrics. To determine model
uncertainties we compare four well accepted stellar models using different
model physics and see how they vary in terms of the values of our metrics. We
determine the ability of future missions to rank target stars according to
these metrics, given the current precision to which host star properties can be
measured. We show that obtaining independent age constraints decreases both the
model and systematic uncertainties in determining these metrics and is the most
powerful way to improve assessments of the long-term habitability of planets
around low mass stars.
