Forests across the globe are becoming increasingly fragmented due to anthropogenic changes in land use. Fragmented forests create more forest edges, where trees experience different environmental conditions than those in the forest interior, such as increased sunlight, air temperature, and vapor pressure deficits. Previous research has found that, in temperate forests, trees at the forest edge experience increased growth but a greater sensitivity to climate stressors. However, the physiological mechanisms underpinning these responses are not well understood. To better understand the interactive effects of the forest edge and climate stressors such as drought, a 180-by-45 meter section of forest at the Harvard Forest was cleared in 2023 to create a new forest edge, and a 95% through-fall water exclusion treatment was installed on a portion of this edge in the summer of 2025. We affixed 20 sap flow sensors on canopy dominant red oaks (Quercus rubra) and red maples (Acer rubrum) at the forest edge and interior and across the control and droughted treatments, and recorded sap flow data from July 2025. We found that trees at the forest edge had lower sap flow rates than those in the interior, but sap flow of interior trees were reduced under the droughted treatment to similar rates as the edge trees. Red oaks and red maples displayed different diurnal patterns, with red oaks experiencing brief, steep stomatal closures midday. Sap flow of red maples appeared to be more sensitive to environmental variables than the sap flow of red oaks, supporting previous research on these two species. Most forest research is performed within continuous forest stands, ignoring differences in microenvironments that trees experience at the forest edge. Our research addresses this knowledge gap, and provides novel information about water use dynamics in fragmented temperate forests. With projected increases in drought throughout temperate regions, understanding how trees at the forest edge will respond to periods of water deficits is vital for predicting future forest dynamics and managing forests accordingly.