Climate change is expected to increase the frequency, intensity, and duration of future droughts with many associated environmental and socioeconomic consequences. Large-scale droughts have lately been implicated as the driver behind widespread reports of vegetation die-off across a variety of hydro-climates and are expected to drive more mortality in the future. Yet, projecting the impact of future droughts on the vegetation using state-of-the-art land-surface models (LSMs) is problematic. Most LSMs employ empirical functions to limit the exchange of carbon and water with declining water availability, therefore performing poorly during periods of water stress. Implementing sophisticated treatments of plant hydraulics is one way to address the issue, but it comes at an added computational cost and the need for additional parameterisation. An alternative solution recently proposed involves using a profit maximisation approach, in which stomata act to dynamically optimise carbon uptake against the cost of maintaining hydraulic function. Here, we evaluate such a profit maximisation approach at the ecosystem scale across a suite of eddy covariance sites, which experienced seasonal droughts. We show how plants exhibit behaviour consistent with attaining optimal profit and how they acclimate their drought response over time. We also ask whether departures from the observed fluxes could be attributed to structural acclimation (i.e. the turnover of leaves/branches). Finally, we exploit insight from this optimisation approach to assess how the vegetation would be impacted by the same drought conditions under a doubled CO2 scenario.