Mountain meadows in the western USA are experiencing increased rates of conifer encroachment due to climate change and land management practices. Past research has focused on conifer removal as a meadow restoration strategy, but there has been limited work on conifer transpiration in a pre-restoration state. Meadow restoration by conifer removal has the primary goal of recovering sufficient growing season soil moisture necessary for endemic, herbaceous meadow vegetation. Therefore, conifer water use represents an important hydrologic output toward evaluating the efficacy of this active management approach. This study quantified and evaluated transpiration of encroached conifers in a mountain meadow using sap flow prior to restoration by tree removal. We report results of lodgepole pine transpiration estimates for an approximate 1-year period and an evaluation of key environmental variables influencing water use during a dry growing season. The study was conducted at Rock Creek Meadow (RCM) in the southern Cascade Range near Chester, CA, USA. Sap flow data were collected in a sample of lodgepole pine and scaled on a per-plot basis to the larger meadow using tree survey data within a stratified random sampling design (simple scaling). These estimates were compared to a MODIS evapotranspiration (ET) estimate for the meadow. The 1-year period for transpiration estimates overlapped each of the 2019 and 2020 growing seasons partially. The response of lodgepole pine transpiration to solar radiation, air temperature, vapor pressure deficit, and volumetric soil water content was investigated by calibrating a modified Jarvis-Stewart (MJS) model to hourly sap flow data collected during the 2020 growing season, which experienced below average antecedent winter precipitation. The model was validated using spatially different sap flow data in the meadow from the 2021 growing season, also part of a dry year. Calibration and validation were completed using a MCMC approach via the DREAM(ZS) algorithm and a generalized likelihood (GL) function, enabling model parameter and total uncertainty assessment. We also used the model to inform transpiration scaling for the calibration period in select plots in the meadow, which allowed comparison with simple scaling transpiration estimates. Average total lodgepole pine transpiration at RCM was estimated between 220.57 ± 25.28 and 393.39 ± 45.65 mm for the entire campaign (mid-July 2019 to mid-August 2020) and between 100.22 ± 11.49 and 178.75 ± 20.74 mm for the 2020 partial growing season (April to mid-August). The magnitude and seasonal timing were similar to MODIS ET. The model showed good agreement between observed and predicted sap velocity for the 2020 partial growing season (RMSE = 1.25 cm h-1), with meteorological variables modulating early growing season sap flow and volumetric soil water content decline imposing transpiration decrease in the late growing season. The model validation performed similarly to calibration in terms of performance metrics and the influence of meteorological variables. The consistency of the declining volumetric soil water content effect during the late growing season between periods could not be evaluated due to an abridged validation period. Overall, the implementation GL-DREAM(ZS) showed promise for future use in MJS models. Lastly, the model derived transpiration estimates for the 2020 partial growing season showed some of the potential utility in using the MJS model to scale sap flow at the study locale. It also highlights some of the key limitations of this approach as it is executed in the present study.