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Knowledge of a star's evolutionary history combined with estimates of planetoccurrence rates allows one to infer its relative quality as a location in thesearch for biosignatures, and to quantify this intuition using long-termhabitability metrics. In this study, we analyse the sensitivity of thebiosignature yield metrics formulated by Tuchow & Wright (2020) touncertainties in observable stellar properties and to model uncertainties. Wecharacterize the uncertainties present in fitting a models to stellarobservations by generating a stellar model with known properties and addingsynthetic uncertainties in the observable properties. We scale the uncertaintyin individual observables and observe the the effects on the precision ofproperties such as stellar mass, age, and our metrics. To determine modeluncertainties we compare four well accepted stellar models using differentmodel physics and see how they vary in terms of the values of our metrics. Wedetermine the ability of future missions to rank target stars according tothese metrics, given the current precision to which host star properties can bemeasured. We show that obtaining independent age constraints decreases both themodel and systematic uncertainties in determining these metrics and is the mostpowerful way to improve assessments of the long-term habitability of planetsaround low mass stars.

Potential Habitability as a Stellar Property: Effects of Model Uncertainties and Measurement Precision