Assumed representative center-of-stand measurements are typical inputs to models that scale forest transpiration to stand and regional extents. These inputs do not consider gradients in transpiration at stand boundaries or along moisture gradients and therefore potentially bias the large-scale estimates. We measured half-hourly sap flux (J _S ) for 173 trees in a spatially explicit cyclic sampling design across a topographically controlled gradient between a forested wetland and upland forest in northern Wisconsin. Our analyses focused on three dominant species in the site: quaking aspen (Populus tremuloides Michx), speckled alder (Alnus incana (DuRoi) Spreng), and white cedar (Thuja occidentalis L.). Sapwood area (A _S ) was used to scale J _S to whole tree transpiration (E _C). Because spatial patterns imply underlying processes, geostatistical analyses were employed to quantify patterns of spatial autocorrelation across the site. A simple Jarvis type model parameterized using a Monte Carlo sampling approach was used to simulate E _C (E _C−SIM). E _C−SIM was compared with observed E _C (E _C−OBS) and found to reproduce both the temporal trends and spatial variance of canopy transpiration. E _C−SIM was then used to examine spatial autocorrelation as a function of environmental drivers. We found no spatial autocorrelation in J _S across the gradient from forested wetland to forested upland. E _C was spatially autocorrelated and this was attributed to spatial variation in A _S which suggests species spatial patterns are important for understanding spatial estimates of transpiration. However, the range of autocorrelation in E _C−SIM decreased linearly with increasing vapor pressure deficit, implying that consideration of spatial variation in the sensitivity of canopy stomatal conductance to D is also key to accurately scaling up transpiration in space.